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  Subjects -> ELECTRONICS (Total: 194 journals)
Showing 1 - 200 of 277 Journals sorted alphabetically
Acta Electronica Malaysia     Open Access  
Advanced Materials Technologies     Hybrid Journal  
Advances in Electrical and Electronic Engineering     Open Access   (Followers: 9)
Advances in Electronics     Open Access   (Followers: 94)
Advances in Magnetic and Optical Resonance     Full-text available via subscription   (Followers: 8)
Advances in Power Electronics     Open Access   (Followers: 39)
Advancing Microelectronics     Hybrid Journal  
Aerospace and Electronic Systems, IEEE Transactions on     Hybrid Journal   (Followers: 352)
American Journal of Electrical and Electronic Engineering     Open Access   (Followers: 28)
Annals of Telecommunications     Hybrid Journal   (Followers: 9)
APSIPA Transactions on Signal and Information Processing     Open Access   (Followers: 9)
Archives of Electrical Engineering     Open Access   (Followers: 15)
Australian Journal of Electrical and Electronics Engineering     Hybrid Journal  
Autonomous Mental Development, IEEE Transactions on     Hybrid Journal   (Followers: 8)
Batteries     Open Access   (Followers: 7)
Batteries & Supercaps     Hybrid Journal   (Followers: 3)
Bell Labs Technical Journal     Hybrid Journal   (Followers: 31)
Bioelectronics in Medicine     Hybrid Journal  
Biomedical Engineering, IEEE Reviews in     Full-text available via subscription   (Followers: 22)
Biomedical Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 38)
Biomedical Instrumentation & Technology     Hybrid Journal   (Followers: 6)
Broadcasting, IEEE Transactions on     Hybrid Journal   (Followers: 13)
BULLETIN of National Technical University of Ukraine. Series RADIOTECHNIQUE. RADIOAPPARATUS BUILDING     Open Access   (Followers: 2)
Bulletin of the Polish Academy of Sciences : Technical Sciences     Open Access   (Followers: 1)
Canadian Journal of Remote Sensing     Full-text available via subscription   (Followers: 47)
China Communications     Full-text available via subscription   (Followers: 9)
Chinese Journal of Electronics     Hybrid Journal  
Circuits and Systems     Open Access   (Followers: 15)
Consumer Electronics Times     Open Access   (Followers: 5)
Control Systems     Hybrid Journal   (Followers: 301)
ECTI Transactions on Computer and Information Technology (ECTI-CIT)     Open Access  
ECTI Transactions on Electrical Engineering, Electronics, and Communications     Open Access   (Followers: 2)
Edu Elektrika Journal     Open Access   (Followers: 1)
Electrica     Open Access  
Electronic Design     Partially Free   (Followers: 123)
Electronic Markets     Hybrid Journal   (Followers: 7)
Electronic Materials Letters     Hybrid Journal   (Followers: 4)
Electronics     Open Access   (Followers: 104)
Electronics and Communications in Japan     Hybrid Journal   (Followers: 10)
Electronics For You     Partially Free   (Followers: 103)
Electronics Letters     Hybrid Journal   (Followers: 26)
Elkha : Jurnal Teknik Elektro     Open Access  
Embedded Systems Letters, IEEE     Hybrid Journal   (Followers: 55)
Energy Harvesting and Systems     Hybrid Journal   (Followers: 4)
Energy Storage     Hybrid Journal   (Followers: 1)
Energy Storage Materials     Full-text available via subscription   (Followers: 4)
EPE Journal : European Power Electronics and Drives     Hybrid Journal  
EPJ Quantum Technology     Open Access   (Followers: 1)
EURASIP Journal on Embedded Systems     Open Access   (Followers: 11)
Facta Universitatis, Series : Electronics and Energetics     Open Access  
Foundations and Trends® in Communications and Information Theory     Full-text available via subscription   (Followers: 6)
Foundations and Trends® in Signal Processing     Full-text available via subscription   (Followers: 10)
Frequenz     Hybrid Journal   (Followers: 1)
Frontiers of Optoelectronics     Hybrid Journal   (Followers: 1)
Geoscience and Remote Sensing, IEEE Transactions on     Hybrid Journal   (Followers: 218)
Haptics, IEEE Transactions on     Hybrid Journal   (Followers: 4)
IACR Transactions on Symmetric Cryptology     Open Access  
IEEE Antennas and Propagation Magazine     Hybrid Journal   (Followers: 100)
IEEE Antennas and Wireless Propagation Letters     Hybrid Journal   (Followers: 81)
IEEE Journal of Emerging and Selected Topics in Power Electronics     Hybrid Journal   (Followers: 51)
IEEE Journal of the Electron Devices Society     Open Access   (Followers: 9)
IEEE Journal on Exploratory Solid-State Computational Devices and Circuits     Hybrid Journal   (Followers: 1)
IEEE Power Electronics Magazine     Full-text available via subscription   (Followers: 75)
IEEE Transactions on Antennas and Propagation     Full-text available via subscription   (Followers: 73)
IEEE Transactions on Automatic Control     Hybrid Journal   (Followers: 59)
IEEE Transactions on Circuits and Systems for Video Technology     Hybrid Journal   (Followers: 26)
IEEE Transactions on Consumer Electronics     Hybrid Journal   (Followers: 44)
IEEE Transactions on Electron Devices     Hybrid Journal   (Followers: 19)
IEEE Transactions on Information Theory     Hybrid Journal   (Followers: 26)
IEEE Transactions on Power Electronics     Hybrid Journal   (Followers: 78)
IEEE Transactions on Signal and Information Processing over Networks     Full-text available via subscription   (Followers: 14)
IEICE - Transactions on Electronics     Full-text available via subscription   (Followers: 12)
IEICE - Transactions on Information and Systems     Full-text available via subscription   (Followers: 5)
IET Cyber-Physical Systems : Theory & Applications     Open Access   (Followers: 1)
IET Energy Systems Integration     Open Access   (Followers: 1)
IET Microwaves, Antennas & Propagation     Hybrid Journal   (Followers: 35)
IET Nanodielectrics     Open Access  
IET Power Electronics     Hybrid Journal   (Followers: 57)
IET Smart Grid     Open Access   (Followers: 1)
IET Wireless Sensor Systems     Hybrid Journal   (Followers: 18)
IETE Journal of Education     Open Access   (Followers: 4)
IETE Journal of Research     Open Access   (Followers: 11)
IETE Technical Review     Open Access   (Followers: 13)
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems)     Open Access   (Followers: 3)
Industrial Electronics, IEEE Transactions on     Hybrid Journal   (Followers: 74)
Industrial Technology Research Journal Phranakhon Rajabhat University     Open Access  
Industry Applications, IEEE Transactions on     Hybrid Journal   (Followers: 38)
Informatik-Spektrum     Hybrid Journal   (Followers: 2)
Instabilities in Silicon Devices     Full-text available via subscription   (Followers: 1)
Intelligent Transportation Systems Magazine, IEEE     Full-text available via subscription   (Followers: 13)
International Journal of Advanced Research in Computer Science and Electronics Engineering     Open Access   (Followers: 18)
International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems     Open Access   (Followers: 12)
International Journal of Antennas and Propagation     Open Access   (Followers: 11)
International Journal of Applied Electronics in Physics & Robotics     Open Access   (Followers: 4)
International Journal of Computational Vision and Robotics     Hybrid Journal   (Followers: 5)
International Journal of Control     Hybrid Journal   (Followers: 11)
International Journal of Electronics     Hybrid Journal   (Followers: 7)
International Journal of Electronics and Telecommunications     Open Access   (Followers: 13)
International Journal of Granular Computing, Rough Sets and Intelligent Systems     Hybrid Journal   (Followers: 3)
International Journal of High Speed Electronics and Systems     Hybrid Journal  
International Journal of Hybrid Intelligence     Hybrid Journal  
International Journal of Image, Graphics and Signal Processing     Open Access   (Followers: 16)
International Journal of Microwave and Wireless Technologies     Hybrid Journal   (Followers: 10)
International Journal of Nanoscience     Hybrid Journal   (Followers: 1)
International Journal of Numerical Modelling: Electronic Networks, Devices and Fields     Hybrid Journal   (Followers: 4)
International Journal of Power Electronics     Hybrid Journal   (Followers: 25)
International Journal of Review in Electronics & Communication Engineering     Open Access   (Followers: 4)
International Journal of Sensors, Wireless Communications and Control     Hybrid Journal   (Followers: 10)
International Journal of Systems, Control and Communications     Hybrid Journal   (Followers: 4)
International Journal of Wireless and Microwave Technologies     Open Access   (Followers: 6)
International Transaction of Electrical and Computer Engineers System     Open Access   (Followers: 2)
JAREE (Journal on Advanced Research in Electrical Engineering)     Open Access  
Journal of Biosensors & Bioelectronics     Open Access   (Followers: 4)
Journal of Advanced Dielectrics     Open Access   (Followers: 1)
Journal of Artificial Intelligence     Open Access   (Followers: 12)
Journal of Circuits, Systems, and Computers     Hybrid Journal   (Followers: 4)
Journal of Computational Intelligence and Electronic Systems     Full-text available via subscription   (Followers: 1)
Journal of Electrical and Electronics Engineering Research     Open Access   (Followers: 36)
Journal of Electrical Bioimpedance     Open Access  
Journal of Electrical Bioimpedance     Open Access   (Followers: 2)
Journal of Electrical Engineering & Electronic Technology     Hybrid Journal   (Followers: 7)
Journal of Electrical, Electronics and Informatics     Open Access  
Journal of Electromagnetic Analysis and Applications     Open Access   (Followers: 8)
Journal of Electromagnetic Waves and Applications     Hybrid Journal   (Followers: 9)
Journal of Electronic Design Technology     Full-text available via subscription   (Followers: 6)
Journal of Electronic Science and Technology     Open Access  
Journal of Electronics (China)     Hybrid Journal   (Followers: 5)
Journal of Energy Storage     Full-text available via subscription   (Followers: 4)
Journal of Engineered Fibers and Fabrics     Open Access   (Followers: 2)
Journal of Field Robotics     Hybrid Journal   (Followers: 3)
Journal of Guidance, Control, and Dynamics     Hybrid Journal   (Followers: 182)
Journal of Information and Telecommunication     Open Access   (Followers: 1)
Journal of Intelligent Procedures in Electrical Technology     Open Access   (Followers: 3)
Journal of Low Power Electronics     Full-text available via subscription   (Followers: 10)
Journal of Low Power Electronics and Applications     Open Access   (Followers: 10)
Journal of Microelectronics and Electronic Packaging     Hybrid Journal  
Journal of Microwave Power and Electromagnetic Energy     Hybrid Journal   (Followers: 3)
Journal of Microwaves, Optoelectronics and Electromagnetic Applications     Open Access   (Followers: 11)
Journal of Nuclear Cardiology     Hybrid Journal  
Journal of Optoelectronics Engineering     Open Access   (Followers: 4)
Journal of Physics B: Atomic, Molecular and Optical Physics     Hybrid Journal   (Followers: 30)
Journal of Power Electronics & Power Systems     Full-text available via subscription   (Followers: 11)
Journal of Semiconductors     Full-text available via subscription   (Followers: 5)
Journal of Sensors     Open Access   (Followers: 26)
Journal of Signal and Information Processing     Open Access   (Followers: 9)
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer     Open Access  
Jurnal Rekayasa Elektrika     Open Access  
Jurnal Teknik Elektro     Open Access  
Jurnal Teknologi Elektro     Open Access  
Kinetik : Game Technology, Information System, Computer Network, Computing, Electronics, and Control     Open Access  
Learning Technologies, IEEE Transactions on     Hybrid Journal   (Followers: 12)
Magnetics Letters, IEEE     Hybrid Journal   (Followers: 7)
Majalah Ilmiah Teknologi Elektro : Journal of Electrical Technology     Open Access   (Followers: 2)
Metrology and Measurement Systems     Open Access   (Followers: 6)
Microelectronics and Solid State Electronics     Open Access   (Followers: 28)
Nanotechnology Magazine, IEEE     Full-text available via subscription   (Followers: 42)
Nanotechnology, Science and Applications     Open Access   (Followers: 6)
Nature Electronics     Hybrid Journal   (Followers: 1)
Networks: an International Journal     Hybrid Journal   (Followers: 5)
Open Electrical & Electronic Engineering Journal     Open Access  
Open Journal of Antennas and Propagation     Open Access   (Followers: 9)
Optical Communications and Networking, IEEE/OSA Journal of     Full-text available via subscription   (Followers: 16)
Paladyn. Journal of Behavioral Robotics     Open Access   (Followers: 1)
Power Electronics and Drives     Open Access   (Followers: 2)
Problemy Peredachi Informatsii     Full-text available via subscription  
Progress in Quantum Electronics     Full-text available via subscription   (Followers: 7)
Pulse     Full-text available via subscription   (Followers: 5)
Radiophysics and Quantum Electronics     Hybrid Journal   (Followers: 2)
Recent Advances in Communications and Networking Technology     Hybrid Journal   (Followers: 4)
Recent Advances in Electrical & Electronic Engineering     Hybrid Journal   (Followers: 11)
Research & Reviews : Journal of Embedded System & Applications     Full-text available via subscription   (Followers: 6)
Revue Méditerranéenne des Télécommunications     Open Access  
Security and Communication Networks     Hybrid Journal   (Followers: 2)
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of     Hybrid Journal   (Followers: 56)
Semiconductors and Semimetals     Full-text available via subscription   (Followers: 1)
Sensing and Imaging : An International Journal     Hybrid Journal   (Followers: 2)
Services Computing, IEEE Transactions on     Hybrid Journal   (Followers: 4)
Software Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 79)
Solid State Electronics Letters     Open Access  
Solid-State Circuits Magazine, IEEE     Hybrid Journal   (Followers: 13)
Solid-State Electronics     Hybrid Journal   (Followers: 9)
Superconductor Science and Technology     Hybrid Journal   (Followers: 3)
Synthesis Lectures on Power Electronics     Full-text available via subscription   (Followers: 3)
Technical Report Electronics and Computer Engineering     Open Access  
TELE     Open Access  
Telematique     Open Access  
TELKOMNIKA (Telecommunication, Computing, Electronics and Control)     Open Access   (Followers: 9)
Transactions on Electrical and Electronic Materials     Hybrid Journal   (Followers: 1)
Universal Journal of Electrical and Electronic Engineering     Open Access   (Followers: 7)
Ural Radio Engineering Journal     Open Access   (Followers: 1)
Visión Electrónica : algo más que un estado sólido     Open Access   (Followers: 1)
Wireless and Mobile Technologies     Open Access   (Followers: 6)
Wireless Power Transfer     Full-text available via subscription   (Followers: 4)
Women in Engineering Magazine, IEEE     Full-text available via subscription   (Followers: 11)
Електротехніка і Електромеханіка     Open Access   (Followers: 1)

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Journal Prestige (SJR): 0.548
Citation Impact (citeScore): 3
Number of Followers: 104  

  This is an Open Access Journal Open Access journal
ISSN (Print) 2079-9292
Published by MDPI Homepage  [222 journals]
  • Electronics, Vol. 9, Pages 201: Hybrid Translation with Classification:
           Revisiting Rule-Based and Neural Machine Translation

    • Authors: Huang, Lee, Kim
      First page: 201
      Abstract: This paper proposes a hybrid machine-translation system that combines neural machine translation with well-developed rule-based machine translation to utilize the stability of the latter to compensate for the inadequacy of neural machine translation in rare-resource domains. A classifier is introduced to predict which translation from the two systems is more reliable. We explore a set of features that reflect the reliability of translation and its process, and training data is automatically expanded with a small, human-labeled dataset to solve the insufficient-data problem. A series of experiments shows that the hybrid system’s translation accuracy is improved, especially in out-of-domain translations, and classification accuracy is greatly improved when using the proposed features and the automatically constructed training set. A comparison between feature- and text-based classification is also performed, and the results show that the feature-based model achieves better classification accuracy, even when compared to neural network text classifiers.
      Citation: Electronics
      PubDate: 2020-01-21
      DOI: 10.3390/electronics9020201
      Issue No: Vol. 9, No. 2 (2020)
  • Electronics, Vol. 9, Pages 202: Correction: Woo, J.; et al. Estimating the
           Information Source under Decaying Diffusion Rates. Electronics 2019, 8,

    • Authors: Woo, Choi
      First page: 202
      Abstract: The reason why we, the authors, want to make a change is that this paper was partially supported by the funding of a research project at Honam University [...]
      Citation: Electronics
      PubDate: 2020-01-21
      DOI: 10.3390/electronics9020202
      Issue No: Vol. 9, No. 2 (2020)
  • Electronics, Vol. 9, Pages 203: EEG Feature Extraction Based on a Bilevel
           Network: Minimum Spanning Tree and Regional Network

    • Authors: Luo, Lu, Xi
      First page: 203
      Abstract: Feature extraction is essential for classifying different motor imagery (MI) tasks in a brain–computer interface (BCI). Although the methods of brain network analysis have been widely studied in the BCI field, these methods are limited by differences in network size, density, and standardization. To address this issue and improve classification accuracy, we propose a novel method, in which the hybrid features of the brain function based on the bilevel network are extracted. Minimum spanning tree (MST) based on electroencephalogram (EEG) signal nodes in different MIs is constructed as the first network layer to solve the global network connectivity problem. In addition, the regional network in different movement patterns is constructed as the second network layer to determine the network characteristics, which is consistent with the correspondence between limb movement patterns and cerebral cortex in neurophysiology. We attempt to apply MST to the classification of the MI EEG signals, and the bilevel network has better interpretability. Thereafter, a vector is formed by combining the MST fundamental features with the directional features of the regional network. Our method is validated using the BCI Competition IV Dataset I. Experimental results verify the feasibility of the bilevel network framework. Furthermore, the average classification performance of the proposed method reaches 89.50%, which is higher than that of other competing methods, thereby indicating that the bilevel network is effective for MI classification.
      Citation: Electronics
      PubDate: 2020-01-21
      DOI: 10.3390/electronics9020203
      Issue No: Vol. 9, No. 2 (2020)
  • Electronics, Vol. 9, Pages 204: A CMOS Programmable Fourth-Order
           Butterworth Active-RC Low-Pass Filter

    • Authors: Zhang, Shang, Wang, Tang
      First page: 204
      Abstract: This paper presents a low-pass filter (LPF) for an ultra-high frequency (UHF) radio frequency identification (RFID) reader transmitter in standard SMIC 0.18 μm CMOS technology. The active-RC topology and Butterworth approximation function are employed mainly for high linearity and high flatness respectively. Two cascaded fully-differential Tow-Thomas biquads are chosen for low sensitivity to process errors and strong resistance to the imperfection of the involved two-stage fully-differential operational amplifiers. Besides, the LPF is programmable in order to adapt to the multiple data rate standards. Measurement results show that the LPF has the programmable bandwidths of 605/870/1020/1330/1530/2150 kHz, the optimum input 1dB compression point of −7.81 dBm, and the attenuation of 50 dB at 10 times cutoff frequency, with the overall power consumption of 12.6 mW from a single supply voltage of 1.8 V. The silicon area of the LPF core is 0.17 mm2.
      Citation: Electronics
      PubDate: 2020-01-21
      DOI: 10.3390/electronics9020204
      Issue No: Vol. 9, No. 2 (2020)
  • Electronics, Vol. 9, Pages 205: Dual-/Tri-Wideband Bandpass Filter with
           High Selectivity and Adjustable Passband for 5G Mid-Band Mobile

    • Authors: Hou, Liu, Zhang, Song, Wu, Zhang, He
      First page: 205
      Abstract: The design and implementation of the filters for the fifth-generation (5G) mobile communication systems are challengeable due to the demands of high integration, low-cost, and high-speed data transmission. In this paper, a dual-wideband bandpass filter (BPF) and a tri-wideband BPF for 5G mobile communications are proposed. The dual-wideband BPF consists of two folded open-loop stepped-impedance resonators (FOLSIRs), and the tri-wideband BPF is designed by placing a pair of folded uniform impedance resonator inside the dual-wideband BPF with little increase in the physical size of the filter. By employing a novel structural deformation of a stepped-impedance resonator, the FOLSIR is achieved with a more compact structure, a controllable transmission zero, and an adjustable resonant frequency. The measurement results show that the working bands of the two filters are 1.98–2.28/3.27–3.66 GHz and 2.035–2.305/3.31–3.71/4.54–5.18 GHz, respectively, which are consistent with the full-wave EM simulation results. The implemented filters have a compact size and the results show low loss, good out-of-band rejection, and wide passbands covering sub-6 GHz bands of 5G mobile communications and a commonly used spectrum.
      Citation: Electronics
      PubDate: 2020-01-22
      DOI: 10.3390/electronics9020205
      Issue No: Vol. 9, No. 2 (2020)
  • Electronics, Vol. 9, Pages 206: Matrix Extraction of Parasitic Parameters
           and Suppression of Common-Mode Conducted Interference in a PMSG-IDOS
           Rectifier Module

    • Authors: Liu, Xia, Liu, Wang
      First page: 206
      Abstract: The rectifier module is the key part of a permanent magnet synchronous generator integrated DC output system (PMSG-IDOS) with low-voltage and high-current. The high-speed switching device of the rectifier module is the main source of electromagnetic interference (EMI). In this paper, the matrix extraction method is proposed to establish an accurate conducted interference model, and a 3D crimped SiC MOSFET model is established via Ansoft Q3D simulation software. The matrix of the parasitic parameters between poles of the MOSFET is simulated to extract the accurate parasitic parameters. Furthermore, a high-precision conducted interference simulation model of the pulse width modulation (PWM) rectifier system is established. Then, the space vector pulse width modulation (SVPWM) jump-backward control strategy based on the three-phase four-leg structure is proposed to suppress the common-mode interference, and the comparison with other two methods is carried out based on this model. Finally, the experimental platform of a 5 V/1000 A synchronous generator with rectifier is constructed, and conducted interference is tested in accordance with the simulated results. It demonstrates the accuracy of the model with parasitic parameters based on the matrix extraction method. This paper provides a more simple and effective reference method for the prediction study of conducted interference in power converter systems. After comparing the simulation results with the experimental results, it is proven that the SVPWM jump-backward control strategy based on the three-phase four-leg structure can ensure the output balance of the bridge leg and allow the common-mode (CM) interference to reach the ideal state.
      Citation: Electronics
      PubDate: 2020-01-22
      DOI: 10.3390/electronics9020206
      Issue No: Vol. 9, No. 2 (2020)
  • Electronics, Vol. 9, Pages 207: The Mechanical Effects Influencing on the
           Design of RF MEMS Switches

    • Authors: Igor E. Lysenko, Alexey V. Tkachenko, Olga A. Ezhova, Boris G. Konoplev, Eugeny A. Ryndin, Elena V. Sherova
      First page: 207
      Abstract: Radio-frequency switches manufactured by microelectromechanical systems technology are now widely used in aerospace systems and other mobile installations for various purposes. In these operating conditions, these devices are often exposed to intense mechanical environmental influences that have a strong impact on their operation. These negative effects can lead to unwanted short-circuit or open-circuit in the radio-frequency transmission line or to irreversible damage to structural elements. Such a violation in the operation of radio-frequency microelectromechanical switches leads to errors and improper functioning of the electronic equipment in which they are integrated. Thus, this review is devoted to the analysis of the origin of these negative intense mechanical effects of the environment, their classification, and analysis, as well as a review of methods to reduce or prevent their negative impact on the design of radio-frequency microelectromechanical switches.
      Citation: Electronics
      PubDate: 2020-01-22
      DOI: 10.3390/electronics9020207
      Issue No: Vol. 9, No. 2 (2020)
  • Electronics, Vol. 9, Pages 208: An Area-Efficient 10-Bit Buffer-Reused DAC
           for AMOLED Column Driver ICs

    • Authors: Xia, Huang, Tian, Wang, Zhu, Wang, Feng
      First page: 208
      Abstract: In this paper, we proposed an area-efficient 10-bit digital-to-analog converter (DAC) with buffer-reusing method to dramatically relief the severe area exploding issue in high-definition active-matrix organic light-emitting diode (AMOLED) driver integrated circuits (ICs). In our design, we implement the functionalities of a large number of switches and capacitors in conventional DAC by a compact internal buffer. Furthermore, we minimize the buffer capacity requirement by elaborately reusing the indispensable output buffer in the typical column driver. In this way, we can cut down nearly a half of the decoder-switches and simultaneously reduce the capacitor size from 8 C to 3 C without designing an intricate and power-consuming amplifier separately. A prototype 6-channel column driver employing the proposed buffer-reused DAC was fabricated by 0.35 μm 2P3M BCD (Bipolar, CMOS, DMOS) process and its effective layout area per channel is 0.0429 mm2, which is 42.8% smaller than that of the conventional 10-bit R-C DAC. Besides, the measured differential nonlinearity (DNL) and integral nonlinearity (INL) are 0.514 LSB/0.631 LSB, respectively and the maximum value of inter-channel deviation voltage output (DVO) is 3.25 mV. The settling time within 5.6 μs is readily achieved under 1.5 kΩ-resistance and 100 pF-capacitance load. Measurement results indicate that the proposed buffer-reused DAC can successfully minimize the die area while maintaining other required performances.
      Citation: Electronics
      PubDate: 2020-01-22
      DOI: 10.3390/electronics9020208
      Issue No: Vol. 9, No. 2 (2020)
  • Electronics, Vol. 9, Pages 209: Compact Ultra-Wideband Bandpass Filters
           Achieved by Using a Stub-loaded Stepped Impedance Resonator

    • Authors: Weng, Zheng, Lai, Liu
      First page: 209
      Abstract: In this paper, we develop a bandpass filter using a stub-loaded stepped impedance resonator (SLSIR) and calculate the even and odd resonant modes of this type of resonator using the input impedance/admittance analysis. In this study, two impedance ratios and two length ratios are operated as the design parameters for controlling the resonant modes of the SLSIR. Several resonant mode variation curves operating three resonant modes with different impedance ratios and two length ratios are developed. By tuning the desired impedance ratios and length ratios of the SLSIRs, compact ultra-wideband (UWB) bandpass filters (BPFs) can be achieved. Two examples of the UWB BPFs are designed in this study. The first example is UWB filter with a wide stopband and the second one is dual UWB BPF, namely, with UWB performance and a notch band. The first filter is designed for a UWB response from 3.1 to 5.26 GHz having a stopband from 5.3 to 11 GHz, with an attenuation level better than 18 dB. The second filter example is a dual UWB BPF with the frequency range from 3.1 to 5 GHz and 6 to 10.1 GHz using two sets of the proposed SLSIR. The measured results have insertion loss of less than 1dB, and return loss greater than 10 dB. Furthermore, the coupling structures and open stub of the SLSIR also provide several transmission zeros at the skirt of the passbands for improving the passband selectivity.
      Citation: Electronics
      PubDate: 2020-01-22
      DOI: 10.3390/electronics9020209
      Issue No: Vol. 9, No. 2 (2020)
  • Electronics, Vol. 9, Pages 210: Stereo Vision-Based Object Recognition and
           Manipulation by Regions with Convolutional Neural Network

    • Authors: Du, Muslikhin, Hsieh, Wang
      First page: 210
      Abstract: This paper develops a hybrid algorithm of adaptive network-based fuzzy inference system (ANFIS) and regions with convolutional neural network (R-CNN) for stereo vision-based object recognition and manipulation. The stereo camera at an eye-to-hand configuration firstly captures the image of the target object. Then, the shape, features, and centroid of the object are estimated. Similar pixels are segmented by the image segmentation method, and similar regions are merged through selective search. The eye-to-hand calibration is based on ANFIS to reduce computing burden. A six-degree-of-freedom (6-DOF) robot arm with a gripper will conduct experiments to demonstrate the effectiveness of the proposed system.
      Citation: Electronics
      PubDate: 2020-01-24
      DOI: 10.3390/electronics9020210
      Issue No: Vol. 9, No. 2 (2020)
  • Electronics, Vol. 9, Pages 211: Operating-Condition-Based Voltage Control
           Algorithm of Distributed Energy Storage Systems in Variable Energy
           Resource Integrated Distribution System

    • Authors: Noh, Choi, Kook
      First page: 211
      Abstract: Penetration of variable energy resource (VER) is limited by voltage constraints in distribution systems. Hence, distributed energy storage systems (ESS) have been considered to be a promising solution owing to their fast and flexible control capability. This paper proposes a voltage control algorithm of the distributed ESS based on the varying operating conditions of the distribution systems. In the proposed algorithm, the required responses of the distributed ESS are controlled for regulating the monitored voltage on the distribution system by using the matched Jacobian element derived from the operating conditions as its control gain. In addition, each required response is readjusted by allocating the violated voltage to distributed ESS respectively based on the portion of its Jacobian element and its available state of charge (SoC). The effectiveness of the proposed algorithm is verified through time-series simulation by employing one of the actual distribution systems with a high penetration of VER in Korea.
      Citation: Electronics
      PubDate: 2020-01-24
      DOI: 10.3390/electronics9020211
      Issue No: Vol. 9, No. 2 (2020)
  • Electronics, Vol. 9, Pages 212: Analysis of High-Power Charging
           Limitations of a Battery in a Hybrid Railway System

    • Authors: Abbas, Cho, Kim
      First page: 212
      Abstract: Fuel cell (FC)-driven railroad propulsion systems (RPSs) have been much appreciated for the past two decades to get rid exhausts of fossil fuels, but the inability of FCs to capture regenerative power produced by propulsion systems during regenerative braking and the dependency of its power density on operating current density necessitates the hybridization of FCs with batteries and/or supercapacitors to utilize the best features of all three power sources. Contrary to the research trend in hybridization where the purpose of hybridization such as fuel saving, high efficiency, or high mileage is achieved by certain operational algorithms without going into detail models, this study using detailed models explores the impact of high-power charging limitations of batteries on the optimization of hybridization, and proposes a solution accordingly. In this study, all three power sources were modeled, the optimal and suboptimal behaviors at the individual level were identified, and power distribution was implemented for a propulsion system, as recommended by the optimal features of all individual power sources. Since the detailed modeling of these power sources involves many mathematical equations and requires the implementation of continuous and discrete states, this study also demonstrates how, using C-MEX S-Functions, these models can be implemented with a reduced computational burden.
      Citation: Electronics
      PubDate: 2020-01-24
      DOI: 10.3390/electronics9020212
      Issue No: Vol. 9, No. 2 (2020)
  • Electronics, Vol. 9, Pages 213: Adaptive Semantic Segmentation for
           Unmanned Surface Vehicle Navigation

    • Authors: Zhan, Xiao, Wen, Zhou, Yuan, Xiu, Zou, Xie, Li
      First page: 213
      Abstract: The intelligentization of unmanned surface vehicles (USVs) has recently attracted intensive interest. Visual perception of the water scenes is critical for the autonomous navigation of USVs. In this paper, an adaptive semantic segmentation method is proposed to recognize the water scenes. A semantic segmentation network model is designed to classify each pixel of an image into water, land or sky. The segmentation result is refined by the conditional random field (CRF) method. It is further improved accordingly by referring to the superpixel map. A weight map is generated based on the prediction confidence. The network trains itself with the refined pseudo label and the weight map. A set of experiments were designed to evaluate the proposed method. The experimental results show that the proposed method exhibits excellent performance with few-shot learning and is quite adaptable to a new environment, very efficient for limited manual labeled data utilization.
      Citation: Electronics
      PubDate: 2020-01-24
      DOI: 10.3390/electronics9020213
      Issue No: Vol. 9, No. 2 (2020)
  • Electronics, Vol. 9, Pages 214: Research on Current Backflow of Asymmetric
           CHB Multi-Level Inverter

    • Authors: Ye, Song, Ren, Wei
      First page: 214
      Abstract: For the traditional asymmetric cascaded H-bridge multi-level inverters, the conventional hybrid modulation method has the problem of current backflow in a certain modulation index range. Although the monopolar modulation method effectively solves this problem, the high-voltage unit participates in the high-frequency operation in part of the range, which limits the improvement of the switching frequency of the whole system. The hybrid frequency modulation method can reduce the switching frequency of the high voltage unit to a certain extent, but the harmonic characteristics of the output voltage will be affected. In order to solve the above problems, a double frequency modulation method based on level-shifted PWM (LS-PWM) is proposed. On the one hand, it solves the inherent power back filling problem of the traditional hybrid modulation method, on the other hand, it ensures that the output voltage of the inverter has good harmonic characteristics when the switching frequency of the high voltage unit is low. The results of simulation and experiment prove the correctness of the theoretical analysis.
      Citation: Electronics
      PubDate: 2020-01-24
      DOI: 10.3390/electronics9020214
      Issue No: Vol. 9, No. 2 (2020)
  • Electronics, Vol. 9, Pages 215: A Blockchain-Based Hybrid Incentive Model
           for Crowdsensing

    • Authors: Lijun Wei, Jing Wu, and Chengnian Long
      First page: 215
      Abstract: Crowdsensing is an emerging paradigm of data aggregation, which has a pivotal role in data-driven applications. By leveraging the recruitment, a crowdsensing system collects a large amount of data from mobile devices at a low cost. The critical issues in the development of crowdsensing are platform security, privacy protection, and incentive. However, the existing centralized, platform-based approaches suffer from the single point of failure which may result in data leakage. Besides, few previous studies have addressed the considerations of both the economic incentive and data quality. In this paper, we propose a decentralized crowdsensing architecture based on blockchain technology which will help improve the attack resistance. Furthermore, we present a hybrid incentive mechanism, which integrates the data quality, reputation, and monetary factors to encourage participants to contribute their sensing data while discouraging malicious behaviors. The effectiveness our of proposed incentive model is verified through a combination of the theory of mechanism design. The performance analysis and simulation results illustrate that the proposed hybrid incentive model is a reliable and efficient mean to promote data security and incentivizing positive conduct on the crowdsensing application.
      Citation: Electronics
      PubDate: 2020-01-24
      DOI: 10.3390/electronics9020215
      Issue No: Vol. 9, No. 2 (2020)
  • Electronics, Vol. 9, Pages 216: Reconfigurable 3-D Slot Antenna Design for
           4G and Sub-6G Smartphones with Metallic Casing

    • Authors: Yang
      First page: 216
      Abstract: The design of a reconfigurable three-dimensional (3-D) slot antenna for 4G and sub-6G smartphone application is presented in this paper. The antenna is located at the bottom of the smartphone and integrated with a metallic casing. Positive-Intrinsic-Negative (PIN) diodes are loaded at the dual-open slot and the folded U-shaped slot, respectively, which are used to realize four working states. The antenna has a compact volume of 42 × 6 × 6 mm3, which can cover the long term evolution (LTE) bands of 698-960 MHz and 1710-2690 MHz, and the sub-6G bands of 3300-3600 MHz & 4800-5000 MHz. The design processes are presented and the structure is optimized, fabricated and measured. The comparison to other state-of-the-art antennas shows that the proposed design has multiband characteristics with small size.
      Citation: Electronics
      PubDate: 2020-01-25
      DOI: 10.3390/electronics9020216
      Issue No: Vol. 9, No. 2 (2020)
  • Electronics, Vol. 9, Pages 217: Dynamic Basic Activity Sequence Matching
           Method in Abnormal Driving Pattern Detection Using Smartphone Sensors

    • Authors: Nguyen, Lu, Nguyen, Nguyen
      First page: 217
      Abstract: In this work, we present a novel method, namely dynamic basic activity sequence matching (DAS), a combination of machine learning methods and flexible threshold based methods for distinguishing normal and abnormal driving patterns. Indeed, DAS relies on the activity detection module (ADM) presented in our previous work to analyze each driving pattern as a sequence of basic activities—stopping (S), going straight (G), turning left (L), and turning right (R). In fact, the threshold value and other parameters like the duration of long and short activities are iteratively induced from the collected dataset. Hence, DAS is flexible and independent of driving contexts such as vehicle modes and road conditions. Experimental results, on the dataset collected from numerous motorcyclists, show the outperformance of our proposed method against dynamic time warping and the two popular machine learning methods—random forest and neural network—in distinguishing the normal and abnormal driving patterns. Moreover, we propose an efficient framework composing of two phases: in the first phase, the normal and abnormal driving patterns are distinguished by relying on DAS. In the second phase, the detected abnormal patterns are further classified into various specific abnormal driving patterns—weaving, sudden braking, etc. This fusion framework again achieves the highest overall accuracy of 97.94%.
      Citation: Electronics
      PubDate: 2020-01-27
      DOI: 10.3390/electronics9020217
      Issue No: Vol. 9, No. 2 (2020)
  • Electronics, Vol. 9, Pages 218: Flux Weakening Control Technique without
           Look-Up Tables for SynRMs Based on Flux Saturation Models

    • Authors: Woo, Lee, Lee, Yoon
      First page: 218
      Abstract: This paper presents a flux weakening algorithm for synchronous reluctance motors (SynRMs) based on parameters estimated at standstill. Recently, flux saturated motors have been studied. Flux saturation models were identified and look-up tables were generated based on the saturation model for maximum torque per ampere (MTPA) and flux weakening operations. The operation with tables would degrade the accuracy of operating points when the table size is not enough. The proposed method implements a flux weakening operation without tables, and the operating points are determined with voltages and currents on operating points. Therefore, the accuracy can be maintained. In addition, the computation time to generate the tables is not needed, so the initial commissioning process can be reduced. The proposed method consists of two parts: the determination of a flux weakening region and the modification of current references. The flux weakening region is determined by the angle between direction vectors along the constant torque and voltage decreasing directions in the d-q axis current plane. After identifying the flux weakening region, the current references are modified for flux weakening according to the direction vector and appropriate magnitude. The direction and magnitude are determined by the operating point of the currents and magnitude of the output voltage, respectively. Using the flux saturation model for SynRMs, the flux weakening direction can be determined accurately. As a result, flux weakening can be performed precisely. The experimental results prove the validity of the proposed method.
      Citation: Electronics
      PubDate: 2020-01-27
      DOI: 10.3390/electronics9020218
      Issue No: Vol. 9, No. 2 (2020)
  • Electronics, Vol. 9, Pages 219: A Novel PCA-Firefly based XGBoost
           classification model for Intrusion Detection in Networks using GPU

    • Authors: Sweta Bhattacharya, Siva Ramakrishnan S, Praveen Kumar Reddy M, Rajesh Kaluri, Saurabh Singh, Thippa Reddy G, Mamoun Alazab, Usman Tariq
      First page: 219
      Abstract: The enormous popularity of the internet across all spheres of human life has introduced various risks of malicious attacks in the network. The activities performed over the network could be effortlessly proliferated, which has led to the emergence of intrusion detection systems. The patterns of the attacks are also dynamic, which necessitates efficient classification and prediction of cyber attacks. In this paper we propose a hybrid principal component analysis (PCA)-firefly based machine learning model to classify intrusion detection system (IDS) datasets. The dataset used in the study is collected from Kaggle. The model first performs One-Hot encoding for the transformation of the IDS datasets. The hybrid PCA-firefly algorithm is then used for dimensionality reduction. The XGBoost algorithm is implemented on the reduced dataset for classification. A comprehensive evaluation of the model is conducted with the state of the art machine learning approaches to justify the superiority of our proposed approach. The experimental results confirm the fact that the proposed model performs better than the existing machine learning models.
      Citation: Electronics
      PubDate: 2020-01-27
      DOI: 10.3390/electronics9020219
      Issue No: Vol. 9, No. 2 (2020)
  • Electronics, Vol. 9, Pages 220: Image Text Deblurring Method Based on
           Generative Adversarial Network

    • Authors: Wu, Du, Wu, Zhang
      First page: 220
      Abstract: In the automatic sorting process of express delivery, a three-segment code is used to represent a specific area assigned by a specific delivery person. In the process of obtaining the courier order information, the camera is affected by factors such as light, noise, and subject shake, which will cause the information on the courier order to be blurred, and some information will be lost. Therefore, this paper proposes an image text deblurring method based on a generative adversarial network. The model of the algorithm consists of two generative adversarial networks, combined with Wasserstein distance, using a combination of adversarial loss and perceptual loss on unpaired datasets to train the network model to restore the captured blurred images into clear and natural image. Compared with the traditional method, the advantage of this method is that the loss function between the input and output images can be calculated indirectly through the positive and negative generative adversarial networks. The Wasserstein distance can achieve a more stable training process and a more realistic generation effect. The constraints of adversarial loss and perceptual loss make the model capable of training on unpaired datasets. The experimental results on the GOPRO test dataset and the self-built unpaired dataset showed that the two indicators, peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM), increased by 13.3% and 3%, respectively. The human perception test results demonstrated that the algorithm proposed in this paper was better than the traditional blur algorithm as the deblurring effect was better.
      Citation: Electronics
      PubDate: 2020-01-27
      DOI: 10.3390/electronics9020220
      Issue No: Vol. 9, No. 2 (2020)
  • Electronics, Vol. 9, Pages 121: An Automatic Diagnosis of Arrhythmias
           Using a Combination of CNN and LSTM Technology

    • Authors: Zhenyu Zheng, Zhencheng Chen, Fangrong Hu, Jianming Zhu, Qunfeng Tang, Yongbo Liang
      First page: 121
      Abstract: Electrocardiogram (ECG) signal evaluation is routinely used in clinics as a significant diagnostic method for detecting arrhythmia. However, it is very labor intensive to externally evaluate ECG signals, due to their small amplitude. Using automated detection and classification methods in the clinic can assist doctors in making accurate and expeditious diagnoses of diseases. In this study, we developed a classification method for arrhythmia based on the combination of a convolutional neural network and long short-term memory, which was then used to diagnose eight ECG signals, including a normal sinus rhythm. The ECG data of the experiment were derived from the MIT-BIH arrhythmia database. The experimental method mainly consisted of two parts. The input data of the model were two-dimensional grayscale images converted from one-dimensional signals, and detection and classification of the input data was carried out using the combined model. The advantage of this method is that it does not require performing feature extraction or noise filtering on the ECG signal. The experimental results showed that the implemented method demonstrated high classification performance in terms of accuracy, specificity, and sensitivity equal to 99.01%, 99.57%, and 97.67%, respectively. Our proposed model can assist doctors in accurately detecting arrhythmia during routine ECG screening.
      Citation: Electronics
      PubDate: 2020-01-08
      DOI: 10.3390/electronics9010121
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 122: Iterative Decoding of LDPC-Based Product
           Codes and FPGA-Based Performance Evaluation

    • Authors: Weigang Chen, Wenting Zhao, Hui Li, Suolei Dai, Changcai Han, Jinsheng Yang
      First page: 122
      Abstract: Low-density parity-check (LDPC) codes have the potential for applications in future high throughput optical communications due to their significant error correction capability and the parallel decoding. However, they are not able to satisfy the very low bit error rate (BER) requirement due to the error floor phenomenon. In this paper, we propose a low-complexity iterative decoding scheme for product codes consisting of very high rate outer codes and LDPC codes. The outer codes aim at eliminating the residual error floor of LDPC codes with quite low implementation costs. Furthermore, considering the long simulation time of computer simulation for evaluating very low BER, the hardware platform is built to accelerate the evaluation of the proposed iterative decoding methods. Simultaneously, the fixed-point effects of the decoding algorithms are also be evaluated. The experimental results show that the iterative decoding of the product codes can achieve a quite low bit error rate. The evaluation using field programmable gate array (FPGA) also proves that product codes with LDPC codes and high-rate algebraic codes can achieve a good trade-off between complexity and throughput.
      Citation: Electronics
      PubDate: 2020-01-08
      DOI: 10.3390/electronics9010122
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 123: Design of Nonequiprobable High-Order
           Constellations over Non-Linear Satellite Channels

    • Authors: Weigang Chen, Yu Peng, Changcai Han, Jinsheng Yang
      First page: 123
      Abstract: High-order modulations are essential to improve the bandwidth efficiency of communication systems. However, such modulated signals with large envelopes are typically sensitive to the non-linear distortion caused by high power amplifiers (HPAs) in the transponder of satellite channels. In this paper, a new nonequiprobable constellation is designed to combat the non-linear effects of HPAs. We use non-uniformly distributed symbols to construct the appropriate high-order constellation for non-linear satellite channels. The nonequiprobable symbols are generated using the non-linear mapping method, which specifically consists of expansion mapping, symbol decomposition, permutation, and combination. Moreover, the demapping method adapting to the designed nonequiprobable constellation is also discussed. The simulation results show that the proposed scheme has considerable performance improvements compared with the traditional equiprobable constellations over the non-linear satellite channel.
      Citation: Electronics
      PubDate: 2020-01-08
      DOI: 10.3390/electronics9010123
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 124: Smart Public Lighting Control and
           Measurement System Using LoRa Network

    • Authors: F. Sánchez Sutil, Antonio Cano-Ortega
      First page: 124
      Abstract: The installation of smart meters in smart cities to monitor streetlights (SLs) provides easy access to measurements of electrical variables and lighting levels, which improves the operation of installation. The use of smart meters in cities requires temporary high-resolution data to improve the energy efficiency (EE) of SLs. Long range (LoRa) is an ideal wireless protocol for use in smart cities due to its low energy consumption, secure communications, and long range indoors and outdoors. For this purpose, we developed a low-cost new system and successfully evaluated it by developing three devices, namely the measure and control device for street lights (MCDSL), lighting level measurement device (LLMD) and gateway LoRa network (GWLN), based on the Arduino open-source electronic platform. This paper describes the hardware and software design and its implementation. Further, an algorithm has been developed to enhance the energy efficiency of public lights using MCDSL, the energy efficiency for street lights (EESL) algorithm, that use the illumination level measured on the same set of SLs with a dynamic control, which assumed different lighting levels throughout the night, and adjusted luminous flux based on the traffic intensity of pedestrians. It sends the acquired data through the LoRa low-power wide-area-network (LPWAN) to the cloud.
      Citation: Electronics
      PubDate: 2020-01-09
      DOI: 10.3390/electronics9010124
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 125: Approximate CPU Design for IoT End-Devices
           with Learning Capabilities

    • Authors: İbrahim Taştan, Mahmut Karaca, Arda Yurdakul
      First page: 125
      Abstract: With the rise of Internet of Things (IoT), low-cost resource-constrained devices have to be more capable than traditional embedded systems, which operate on stringent power budgets. In order to add new capabilities such as learning, the power consumption planning has to be revised. Approximate computing is a promising paradigm for reducing power consumption at the expense of inaccuracy introduced to the computations. In this paper, we set forth approximate computing features of a processor that will exist in the next generation low-cost resource-constrained learning IoT devices. Based on these features, we design an approximate IoT processor which benefits from RISC-V ISA. Targeting machine learning applications such as classification and clustering, we have demonstrated that our processor reinforced with approximate operations can save power up to 23% for ASIC implementation while at least 90% top-1 accuracy is achieved on the trained models and test data set.
      Citation: Electronics
      PubDate: 2020-01-09
      DOI: 10.3390/electronics9010125
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 126: Novel Extensions to Enhance Scalability
           and Reliability of the IEEE 802.15.4-DSME Protocol

    • Authors: Filippo Battaglia, Mario Collotta, Luca Leonardi, Lucia Lo Bello, Gaetano Patti
      First page: 126
      Abstract: The Deterministic and Synchronous Multichannel Extension (DSME) of the IEEE 802.15.4 standard was designed to fulfill the requirements of commercial and industrial applications. DSME overcomes the IEEE 802.15.4 limitation on the maximum number of Guaranteed Time Slots (GTS) in a superframe and it also exploits channel diversity to increase the communication reliability. However, DSME suffers from scalability problems, as its multi-superframe structure does not efficiently handle GTS in networks with a high number of nodes and periodic flows. This paper proposes the enhanceD DSME (D-DSME), which consists of two extensions that improve the DSME scalability and reliability exploiting a GTS within the multi-superframe to accommodate multiple flows or multiple retransmissions of the same flow. The paper describes the proposed extensions and the performance results of both OMNeT simulations and experiments with real devices implementing the D-DSME.
      Citation: Electronics
      PubDate: 2020-01-09
      DOI: 10.3390/electronics9010126
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 127: Performance Degradation of Nanofilament
           Switching Due to Joule Heat Dissipation

    • Authors: Mohammad Shah Al-Mamun, Marius K. Orlowski
      First page: 127
      Abstract: When a memory cell of a Resistive Random Access Memory (ReRAM) crossbar array is switched repeatedly, a considerable amount of Joule heat is dissipated in the cell, and the heat may spread to neighboring cells that share one of the electrode lines with the heat source device. The remote heating of a probed memory cell by another cell allows separating the influence of temperature effects from the impact of the electric field on the resistive switching kinetics. We find that the cell-to-cell heat transfer causes severe degradation of electrical performance of the unheated neighboring cells. A metric for the thermal degradation of the I–V characteristics is established by a specific conditioning of a so-called “marginal” device used as a temperature-sensitive probe of electrical performance degradation. We find that even neighboring cells with no common metal electrode lines with the heated cell suffer substantial electrical performance degradation provided that intermediate cells of the array are set into a conductive state establishing a continuous thermal path via nanofilaments between the heated and probed cells. The cell-to-cell thermal cross-talk poses a serious electro-thermal reliability problem for the operation of a memory crossbar array requiring modified write/erase algorithms to program the cells (a thermal sneak path effect). The thermal cross-talk appears to be more severe in nanometer-sized memory arrays even if operated with ultra-fast, nanosecond-wide voltage/current pulses.
      Citation: Electronics
      PubDate: 2020-01-09
      DOI: 10.3390/electronics9010127
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 128: A Semidefinite Relaxation Method for
           Elliptical Location

    • Authors: Xin Wang, Ying Ding, Le Yang
      First page: 128
      Abstract: Wireless location is a supporting technology in many application scenarios of wireless communication systems. Recently, an increasing number of studies have been conducted on range-based elliptical location in a variety of backgrounds. Specifically, the design and implementation of position estimators are of great significance. The difficulties arising from implementing a maximum likelihood estimator for elliptical location come from the nonconvexity of the negative log-likelihood functions. The need for computational efficiency further enhances the difficulties. Traditional algorithms suffer from the problems of high computational cost and low initialization justifiability. On the other hand, existing closed-form solutions are sensitive to the measurement noise levels. We recognize that the root of these drawbacks lies in an oversimplified linear approximation of the nonconvex model, and accordingly design a maximum likelihood estimator through semidefinite relaxation for elliptical location. We relax the elliptical location problems to semidefinite programs, which can be solved efficiently with interior-point methods. Additionally, we theoretically analyze the complexity of the proposed algorithm. Finally, we design and carry out a series of simulation experiments, showing that the proposed algorithm outperforms several widely used closed-form solutions at a wide range of noise levels. Extensive results under extreme noise conditions verify the deployability of the algorithm.
      Citation: Electronics
      PubDate: 2020-01-09
      DOI: 10.3390/electronics9010128
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 129: A Hybrid PV-Battery/Supercapacitor System
           and a Basic Active Power Control Proposal in MATLAB/Simulink

    • Authors: Şahin, Blaabjerg
      First page: 129
      Abstract: An increase in the integration of renewable energy generation worldwide brings along some challenges to energy systems. Energy systems need to be regulated following grid codes for the grid stability and efficiency of renewable energy utilization. The main problems that are on the active side can be caused by excessive power generation or unregulated energy generation, such as a partially cloudy day. The main problems on the load side can be caused by excessive or unregulated energy demand or nonlinear loads which deteriorate the power quality of the energy networks. This study focuses on the energy generation side as active power control. In this study, the benefits of supercapacitor use in a hybrid storage system are investigated and analyzed. A hybrid system in which photovoltaic powered and stored the energy in battery and supercapacitor are proposed in this study to solving the main problems in two sides. The supercapacitor model, photovoltaic model, and the proposed hybrid system are designed in MATLAB/Simulink for 6 kW rated power. Also, a new topology is proposed to increase the energy storage with supercapacitors for a passive storage system. The instantaneous peak currents energy is aimed to store in supercapacitors temporarily with this topology. The main advantages of this topology are voltage stabilization in two sides by the supercapacitors and a limitation of the battery load, which directly results in longer battery life and decreases the system cost. The simulation results are investigated for this topology.
      Citation: Electronics
      PubDate: 2020-01-09
      DOI: 10.3390/electronics9010129
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 130: Safety Risk Assessment of a Pb-Zn Mine
           Based on Fuzzy-Grey Correlation Analysis

    • Authors: Dong, Wei, Xia, Woźniak, Damaševičius
      First page: 130
      Abstract: Improving safety management and risk evaluation methods is important for the global mining industry, which is the backbone of the industrial development of our society. To prevent any accidental loss or harm to human life and property, a safety risk assessment method is needed to perform the continuous risk assessment of mines. Based on the requirements of mine safety evaluation, this paper proposes the Pb-Zn mine safety risk evaluation model based on the fuzzy-grey correlation analysis method. The model is compared with the risk assessment model based on the fuzzy TOPSIS method. Through the experiments, our results demonstrate that the proposed fuzzy-grey correlation model is more sensitive to risk and has less effect on the evaluation results under different scoring attitudes (cautious, rational, and relaxed).
      Citation: Electronics
      PubDate: 2020-01-09
      DOI: 10.3390/electronics9010130
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 131: Adapting Techniques to Improve Efficiency
           in Radio Frequency Power Amplifiers for Visible Light Communications

    • Authors: Daniel G. Aller, Diego G. Lamar, Juan Rodriguez, Pablo F. Miaja, Valentin Francisco Romero, Jose Mendiolagoitia, Javier Sebastian
      First page: 131
      Abstract: It is well known that modern wireless communications systems need linear, wide bandwidth, efficient Radio Frequency Power Amplifiers (RFPAs). However, conventional configurations of RFPAs based on Class A, Class B, and Class AB exhibit extremely low efficiencies when they manage signals with a high Peak-to-Average Power Ratio (PAPR). Traditionally, a number of techniques have been proposed either to achieve linearity in the case of efficient Switching-Mode RFPAs or to improve the efficiency of linear RFPAs. There are two categories in the application of aforementioned techniques. First, techniques based on the use of Switching-Mode DC–DC converters with a very-fast-output response (faster than 1 µs). Second, techniques based on the interaction of several RFPAs. The current expansion of these techniques is mainly due to their application in cellphone networks, but they can also be applied in other promising wireless communications systems such as Visible Light Communication (VLC). The main contribution of this paper is to show how Envelope Tracking (ET), Envelope and Elimination (EER), Outphasing, and Doherty techniques can be helpful in developing more efficient VLC transmitters capable of reaching high bit-rates (higher than 1 Mbps) by using advance modulation schemes. Finally, two examples based on the application of the Outphasing technique and the use of a Linear-Assisted Envelope Amplifier (EA) to VLC are presented and experimentally verified.
      Citation: Electronics
      PubDate: 2020-01-10
      DOI: 10.3390/electronics9010131
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 132: A Fast Transient Response Digital LDO with
           a TDC-Based Signal Converter

    • Authors: Hongda Zhang, Peiyuan Wan, Jiarong Geng, Zhaozhe Liu, Zhijie Chen
      First page: 132
      Abstract: The digital low drop-out regulator (LDO) has been used widely in digital circuits for its low supply voltage characteristics. However, as the traditional digital LDOs regulate the output voltage code at a rate of 1 bit per clock cycle, the transient response speed is limited. This paper presents a digital LDO to improve transient response speed with a multi-bit conversion technique. The proposed technology uses a voltage sensor and a time-to-digital converter to convert the output voltage to digital codes. Based on a 65-nm CMOS process, the proposed DLDO reduces the settling time from 147.8 ns to 25.2 ns on average and the response speed is improved by about six times.
      Citation: Electronics
      PubDate: 2020-01-10
      DOI: 10.3390/electronics9010132
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 133: 0.13 μm CMOS Traveling-Wave Power
           Amplifier with On- and Off-Chip Gate-Line Termination

    • Authors: Aleksandr Vasjanov, Vaidotas Barzdenas
      First page: 133
      Abstract: Broadband amplifiers are essential building blocks used in high data rate wireless, radar, and instrumentation systems, as well as in optical communication systems. Only a traveling-wave amplifier (TWA) provides sufficient bandwidth for broadband applications without reducing modern linearization techniques. TWA requires gate-line and drain-line termination, which can be implemented on- and off-chip. This article compares the performance of identical 0.13 μm CMOS TWAs, differing only in gate-line termination placement. Measurement results revealed that the designed TWAs with on- and off-chip termination have a bandwidth of 10 GHz with a maximum gain of 15 dB and a power-added efficiency (PAE) of 5%–22% in the whole operating frequency range. Placing the gate-line termination off-chip results in an S21 flatness reduction, compared to the gain of a TWA with on-chip termination. Gain fluctuation over frequency is reduced by 4–8 dB when the termination resistor is placed as an external circuit.
      Citation: Electronics
      PubDate: 2020-01-10
      DOI: 10.3390/electronics9010133
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 134: CENNA: Cost-Effective Neural Network

    • Authors: Sang-Soo Park, Ki-Seok Chung
      First page: 134
      Abstract: Convolutional neural networks (CNNs) are widely adopted in various applications. State-of-the-art CNN models deliver excellent classification performance, but they require a large amount of computation and data exchange because they typically employ many processing layers. Among these processing layers, convolution layers, which carry out many multiplications and additions, account for a major portion of computation and memory access. Therefore, reducing the amount of computation and memory access is the key for high-performance CNNs. In this study, we propose a cost-effective neural network accelerator, named CENNA, whose hardware cost is reduced by employing a cost-centric matrix multiplication that employs both Strassen’s multiplication and a naïve multiplication. Furthermore, the convolution method using the proposed matrix multiplication can minimize data movement by reusing both the feature map and the convolution kernel without any additional control logic. In terms of throughput, power consumption, and silicon area, the efficiency of CENNA is up to 88 times higher than that of conventional designs for the CNN inference.
      Citation: Electronics
      PubDate: 2020-01-10
      DOI: 10.3390/electronics9010134
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 135: Deep Learning-Based Stacked Denoising and
           Autoencoder for ECG Heartbeat Classification

    • Authors: Nurmaini, Darmawahyuni, Sakti Mukti, Rachmatullah, Firdaus, Tutuko
      First page: 135
      Abstract: The electrocardiogram (ECG) is a widely used, noninvasive test for analyzing arrhythmia. However, the ECG signal is prone to contamination by different kinds of noise. Such noise may cause deformation on the ECG heartbeat waveform, leading to cardiologists’ mislabeling or misinterpreting heartbeats due to varying types of artifacts and interference. To address this problem, some previous studies propose a computerized technique based on machine learning (ML) to distinguish between normal and abnormal heartbeats. Unfortunately, ML works on a handcrafted, feature-based approach and lacks feature representation. To overcome such drawbacks, deep learning (DL) is proposed in the pre-training and fine-tuning phases to produce an automated feature representation for multi-class classification of arrhythmia conditions. In the pre-training phase, stacked denoising autoencoders (DAEs) and autoencoders (AEs) are used for feature learning; in the fine-tuning phase, deep neural networks (DNNs) are implemented as a classifier. To the best of our knowledge, this research is the first to implement stacked autoencoders by using DAEs and AEs for feature learning in DL. Physionet’s well-known MIT-BIH Arrhythmia Database, as well as the MIT-BIH Noise Stress Test Database (NSTDB). Only four records are used from the NSTDB dataset: 118 24 dB, 118 −6 dB, 119 24 dB, and 119 −6 dB, with two levels of signal-to-noise ratio (SNRs) at 24 dB and −6 dB. In the validation process, six models are compared to select the best DL model. For all fine-tuned hyperparameters, the best model of ECG heartbeat classification achieves an accuracy, sensitivity, specificity, precision, and F1-score of 99.34%, 93.83%, 99.57%, 89.81%, and 91.44%, respectively. As the results demonstrate, the proposed DL model can extract high-level features not only from the training data but also from unseen data. Such a model has good application prospects in clinical practice.
      Citation: Electronics
      PubDate: 2020-01-10
      DOI: 10.3390/electronics9010135
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 136: BBR-ACD: BBR with Advanced Congestion

    • Authors: Imtiaz Mahmud, Geon-Hwan Kim, Tabassum Lubna, You-Ze Cho
      First page: 136
      Abstract: With the aim of improved throughput with reduced delay, Google proposed the bottleneck bandwidth and round-trip time (BBR) congestion control algorithm in 2016. Contrasting with the traditional loss-based congestion control algorithms, it operates without bottleneck queue formation and packet losses. However, we find unexpected behaviour in BBR during testbed experiments and network simulator 3 (NS-3) simulations. We observe huge packet losses, retransmissions, and large queue formation in the bottleneck in a congested network scenario. We believe this is because of BBR’s nature of sending extra data during the bandwidth probing without considering the network conditions, and the lack of a proper recovery mechanism. In a congested network, the sent extra data creates a large queue in the bottleneck, which is sustained due to insufficient drain time. BBR lacks a proper mechanism to detect such large bottleneck queues, cannot comply with the critical congestion situation properly, and results in excessive retransmission problems. Based on these observations, we propose a derivative of BBR, called “BBR with advanced congestion detection (BBR-ACD)”, that reduces the excessive retransmissions without losing the merits. We propose a novel method to determine an actual congestion situation by considering the packet loss and delay-gradient of round-trip time, and implement a proper recovery mechanism to handle such a congestion situation. Through extensive test and NS-3 simulations, we confirmed that the proposed BBR-ACD could reduce the retransmissions by about 50% while improving the total goodput of the network.
      Citation: Electronics
      PubDate: 2020-01-10
      DOI: 10.3390/electronics9010136
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 137: Modeling of High-Resolution Data
           Converter: Two-Step Pipelined-SAR ADC based on ISDM

    • Authors: Gao, Li, Sun, Wu
      First page: 137
      Abstract: The features of high-resolution and high-bandwidth are in an increasing demand considering to the wide range application fields based on high performance data converters. In this paper, a modeling of high-resolution hybrid analog-to-digital converter (ADC) is proposed to meet those requirements, and a 16-bit two-step pipelined successive approximation register (SAR) analog-to-digital converter (ADC) with first-order continuous-time incremental sigma-delta modulator (ISDM) assisted is presented to verify this modeling. The combination of high-bandwidth two-step pipelined-SAR ADC with low noise ISDM and background comparator offset calibration can achieve higher signal-to-noise ratio (SNR) without sacrificing the speed and plenty of hardware. The usage of a sub-ranging scheme consists of a coarse SAR ADC followed by an fine ISDM, can not only provide better suppression of the noise added in 2nd stage during conversion but also alleviate the demands of comparator’s resolution in both stages for a given power budget, compared with a conventional Pipelined-SAR ADC. At 1.2 V/1.8 V supply, 33.3 MS/s and 16 MHz input sinusoidal signal in the 40 nm complementary metal oxide semiconductor (CMOS) process, the post-layout simulation results show that the proposed hybrid ADC achieves a signal-to-noise distortion ratio (SNDR) and a spurious free dynamic range (SFDR) of 86.3 dB and 102.5 dBc respectively with a total power consumption of 19.2 mW.
      Citation: Electronics
      PubDate: 2020-01-10
      DOI: 10.3390/electronics9010137
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 138: New Application of an Instantaneous
           Frequency Parameter for Assessing Far Infrared Fabric Effects in Aged

    • Authors: Wei, Li, Wu, Xiao, Tang, Chen, Wu
      First page: 138
      Abstract: A microcirculation microscope has recently been introduced to reveal finger blood flow changes by visualization, before and after using far-infrared fabric. Digital volume pulses (DVPs) from the dominant index fingertip of healthy young subjects (Group 1, n = 66) and healthy upper middle-aged subjects (Group 2, n = 33) were acquired through a photoplethysmographic electrical device (PED). By using the one intrinsic mode function (i.e. IMF5), an instantaneous frequency difference (ΔfEmax) was revealed through the second part of the Hilbert–Huang transformation. Parameters from DVPs in the time domain, i.e. the stiffness index, crest time, crest time ratio, and finger perfusion index, were also obtained for comparison. The results showed significant differences in FPI and ΔfEmax between the two groups (p = 0.002 and p = 0.043, respectively). A significant ΔfEmax was also noted for the two groups under the effects of far-infrared radiation (FIR) (Group 1: p = 0.046; Group 2: p = 0.002). In conclusion, this study aimed to validate a self-developed and economical device, with a good extensibility, which can be operated in a domestic setting, and to demonstrate that the PED performed quantitative indexes on finger blood flow comparable to those investigated through a microcirculation microscope.
      Citation: Electronics
      PubDate: 2020-01-10
      DOI: 10.3390/electronics9010138
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 139: A Review on Stochastic Approach for PHEV
           Integration Control in a Distribution System with an Optimized Battery
           Power Demand Model

    • Authors: Boudina, Wang, Benbouzid , Yao , Zhou
      First page: 139
      Abstract: The future adoption of electric vehicles (EV) as the main means of commuting will put an additional stress on the distribution grid; the level where EVs are mainly expected to be charged. Estimation of the EV charging influence on the distribution grid is a critical task for distribution system operators (DSO) in order to plan for grid reinforcement and to avoid service failure. Due to the unpredictable nature of daily human activities, stochastic modeling for daily EVs’ owner behavior and residential power consumption is needed. In our study a new estimation model for the EV power demand during the charging process is developed to accurately estimate the charging demand, which is combined with daily household power consumption loads based on real life measurements to estimate the total demand in the system. This demand can be applied to the standard IEEE 69 distribution system and can quantify the influence of different penetration levels under an uncontrolled (dumb) charging case, also under a proposed controlled charging algorithm for both summer and winter seasons.
      Citation: Electronics
      PubDate: 2020-01-10
      DOI: 10.3390/electronics9010139
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 140: Secondary Control for Storage Power
           Converters in Isolated Nanogrids to Allow Peer-to-Peer Power Sharing

    • Authors: Eva González-Romera, Enrique Romero-Cadaval, Carlos Roncero-Clemente, Mercedes Ruiz-Cortés, Fermín Barrero-González, María-Isabel Milanés Montero, Antonio Moreno-Muñoz
      First page: 140
      Abstract: It is usual in literature that power sharing among grid-forming sources of an isolated microgrid obeys their energy rating, instead of economic agreements between stakeholders, and circulating energy among them is usually avoided. However, these energy interchanges make strong sense and classical power sharing methods must be reformulated in the context of prosumer-based microgrids. This paper proposes a secondary control method for a prosumer-based low-voltage nanogrid that allows for energy interchange between prosumers, where storage systems, together with PV generators, are the controllable grid-forming sources. A power flow technique adapted to islanded microgrids is used for secondary control algorithm and the whole hierarchical control strategy for the prosumer converter is simulated and validated. This hierarchical control consists of three stages: tertiary control plans the energy interchange among prosumers, secondary obtains different voltage and power setpoints for each of the grid-forming sources, and, finally, primary control guarantees stable voltage and frequency values within the nanogrid with droop rules. Inner control loops for the power converter are also defined to track setpoints and assure stable performance. Simulation tests are carried out, which prove the stability of the proposed methods and the accuracy of the setpoint tracking.
      Citation: Electronics
      PubDate: 2020-01-11
      DOI: 10.3390/electronics9010140
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 141: Frequency Splitting and Transmission
           Characteristics of MCR-WPT System Considering Non-Linearities of
           Compensation Capacitors

    • Authors: Jun Liu, Chang Wang, Xiaofeng Wang, Weimin Ge
      First page: 141
      Abstract: The frequency splitting phenomenon and transmission characteristics have been research hotspots in the field of magnetically coupled resonance wireless power transfer (MCR-WPT). In this paper, non-linear dynamics theory was innovatively introduced into the research, and non-linear coupled transmission dynamics modelling of the MCR-WPT system was established considering the non-linearities of the compensation capacitor. The mechanism of the frequency splitting phenomenon of the MCR-WPT system was revealed through systematic mathematical analyses based on the modelling. The analysis results showed that the system usually has dual natural frequencies which are low resonance frequency and high resonance frequency. Based on non-linear dynamics theory, the transmission characteristics of the system with different non-linear parameters were discussed comprehensively in relation to the modelling. The results of the numerical simulations and theoretical analyses showed that non-linear parameters can cause the jumping phenomena with the output responses, and the output responses in the vicinities of the lower resonance frequencies were extremely sensitive to changes in the coupling coefficient. According to analyses of the linear and non-linear systems, the energy transmissions performed in the vicinity of the high resonance frequency had a wider working frequency band and a better transmission stability under non-linear conditions.
      Citation: Electronics
      PubDate: 2020-01-11
      DOI: 10.3390/electronics9010141
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 142: Optimal Feature Search for Vigilance
           Estimation Using Deep Reinforcement Learning

    • Authors: Woojoon Seok, Minsoo Yeo, Jiwoo You, Heejun Lee, Taeheum Cho, Bosun Hwang, Cheolsoo Park
      First page: 142
      Abstract: A low level of vigilance is one of the main reasons for traffic and industrial accidents. We conducted experiments to evoke the low level of vigilance and record physiological data through single-channel electroencephalogram (EEG) and electrocardiogram (ECG) measurements. In this study, a deep Q-network (DQN) algorithm was designed, using conventional feature engineering and deep convolutional neural network (CNN) methods, to extract the optimal features. The DQN yielded the optimal features: two CNN features from ECG and two conventional features from EEG. The ECG features were more significant for tracking the transitions within the alertness continuum with the DQN. The classification was performed with a small number of features, and the results were similar to those from using all of the features. This suggests that the DQN could be applied to investigating biomarkers for physiological responses and optimizing the classification system to reduce the input resources.
      Citation: Electronics
      PubDate: 2020-01-11
      DOI: 10.3390/electronics9010142
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 143: CoRL: Collaborative Reinforcement
           Learning-Based MAC Protocol for IoT Networks

    • Authors: Taegyeom Lee , Ohyun Jo  and Kyungseop Shin 
      First page: 143
      Abstract: Devices used in Internet of Things (IoT) networks continue to perform sensing, gathering, modifying, and forwarding data. Since IoT networks have a lot of participants, mitigating and reducing collisions among the participants becomes an essential requirement for the Medium Access Control (MAC) protocols to increase system performance. A collision occurs in wireless channel when two or more nodes try to access the channel at the same time. In this paper, a reinforcement learning-based MAC protocol was proposed to provide high throughput and alleviate the collision problem. A collaboratively predicted Q-value was proposed for nodes to update their value functions by using communications trial information of other nodes. Our proposed protocol was confirmed by intensive system level simulations that it can reduce convergence time in 34.1% compared to the conventional Q-learning-based MAC protocol.
      Citation: Electronics
      PubDate: 2020-01-11
      DOI: 10.3390/electronics9010143
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 144: Towards a Lightweight Detection System for
           Cyber Attacks in the IoT Environment Using Corresponding Features

    • Authors: Soe, Feng, Santosa, Hartanto, Sakurai
      First page: 144
      Abstract: The application of a large number of Internet of Things (IoT) devices makes our life more convenient and industries more efficient. However, it also makes cyber-attacks much easier to occur because so many IoT devices are deployed and most of them do not have enough resources (i.e., computation and storage capacity) to carry out ordinary intrusion detection systems (IDSs). In this study, a lightweight machine learning-based IDS using a new feature selection algorithm is designed and implemented on Raspberry Pi, and its performance is verified using a public dataset collected from an IoT environment. To make the system lightweight, we propose a new algorithm for feature selection, called the correlated-set thresholding on gain-ratio (CST-GR) algorithm, to select really necessary features. Because the feature selection is conducted on three specific kinds of cyber-attacks, the number of selected features can be significantly reduced, which makes the classifiers very small and fast. Thus, our detection system is lightweight enough to be implemented and carried out in a Raspberry Pi system. More importantly, as the really necessary features corresponding to each kind of attack are exploited, good detection performance can be expected. The performance of our proposal is examined in detail with different machine learning algorithms, in order to learn which of them is the best option for our system. The experiment results indicate that the new feature selection algorithm can select only very few features for each kind of attack. Thus, the detection system is lightweight enough to be implemented in the Raspberry Pi environment with almost no sacrifice on detection performance.
      Citation: Electronics
      PubDate: 2020-01-11
      DOI: 10.3390/electronics9010144
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 145: DSFTL: An Efficient FTL for Flash Memory
           Based Storage Systems

    • Authors: Chae, Mativenga, Paik, Attique, Chung
      First page: 145
      Abstract: Flash memory is widely used in solid state drives (SSD), smartphones and so on because of their non-volatility, low power consumption, rapid access speed, and resistance to shocks. Due to the hardware features of flash memory that differ from hard disk drives (HDD), a software called FTL (Flash Translation Layer) was presented. The function of FTL is to make flash memory device appear as a block device to its host. However, due to the erase before write features of flash memory, flash blocks need to be constantly availed through the garbage collection (GC) of invalid pages, which incurs high-priced overhead. In the previous hybrid mapping schemes, there are three problems that cause GC overhead. First, operation of partial merge causes more page copies than operation of switch merge. However, many authors just concentrate on reducing operation of full merge. Second, the availability between a data block and a log block makes the space availability of the log block lower, and it also generates a very high-priced operation of full merge. Third, the space availability of the data block is low because the data block, which has many free pages, is merged. Therefore, we propose a new FTL named DSFTL (Dynamic Setting for FTL). In this FTL, we use many SW (sequential write) log blocks to increase operation of switch merge and to decrease operation of partial merge. In addition, DSFTL dynamically handles the data blocks and log blocks to reduce the operations of erase and the high-priced operation of full merge. Additionally, our scheme prevents the data block with many free pages from being merged to increase the space availability of the data block. Our extensive experimental results prove that our proposed approach (DSFTL) reduces the count of erase and increases the operation of switch merge. As a result, DSFTL decreases the garbage collection overhead.
      Citation: Electronics
      PubDate: 2020-01-12
      DOI: 10.3390/electronics9010145
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 146: A Low-Dropout Regulator with PSRR
           Enhancement through Feed-Forward Ripple Cancellation Technique in 65 nm
           CMOS Process

    • Authors: Young-Joe Choe, Hyohyun Nam, Jung-Dong Park
      First page: 146
      Abstract: In this paper, a low-dropout (LDO) regulator with an enhanced power supply rejection ratio (PSRR) is proposed with a feed-forward ripple cancellation technique (FFRC) in 65 nm CMOS technology. This technique significantly improves the PSRR over a wide range of frequencies, compared to a conventional LDO regulator. The LDO regulator provides 35–76.8 dB of PSRR in the range of 1 MHz–1 GHz, which shows up to 30 dB of PSRR improvement, compared with that of the conventional LDO regulator. The implemented LDO regulator has a dropout voltage of 0.22 V and a maximum load current of 20 mA. It can also provide an output voltage of 0.98 V at a range of 1–1.3 V of the input voltage. The load regulation is 2.3 mV/mA while the line regulation is 0.05 V/V. The circuit consumes 385 μA with an input voltage of 1.2 V. The total area without pads is 0.092 mm2.
      Citation: Electronics
      PubDate: 2020-01-12
      DOI: 10.3390/electronics9010146
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 147: Action Recognition Using Deep 3D CNNs with
           Sequential Feature Aggregation and Attention

    • Authors: Anvarov, Kim, Song
      First page: 147
      Abstract: Action recognition is an active research field that aims to recognize human actions and intentions from a series of observations of human behavior and the environment. Unlike image-based action recognition mainly using a two-dimensional (2D) convolutional neural network (CNN), one of the difficulties in video-based action recognition is that video action behavior should be able to characterize both short-term small movements and long-term temporal appearance information. Previous methods aim at analyzing video action behavior only using a basic framework of 3D CNN. However, these approaches have a limitation on analyzing fast action movements or abruptly appearing objects because of the limited coverage of convolutional filter. In this paper, we propose the aggregation of squeeze-and-excitation (SE) and self-attention (SA) modules with 3D CNN to analyze both short and long-term temporal action behavior efficiently. We successfully implemented SE and SA modules to present a novel approach to video action recognition that builds upon the current state-of-the-art methods and demonstrates better performance with UCF-101 and HMDB51 datasets. For example, we get accuracies of 92.5% (16f-clip) and 95.6% (64f-clip) with the UCF-101 dataset, and 68.1% (16f-clip) and 74.1% (64f-clip) with HMDB51 for the ResNext-101 architecture in a 3D CNN.
      Citation: Electronics
      PubDate: 2020-01-12
      DOI: 10.3390/electronics9010147
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 148: An Investigation of Spectral Band
           Selection for Hyperspectral LiDAR Technique

    • Authors: Hui Shao, Yuwei Chen, Wei Li, Changhui Jiang, Haohao Wu, Jie Chen, Banglong Pan, Juha Hyyppä
      First page: 148
      Abstract: Hyperspectral LiDAR (HSL) has been widely discussed in recent years, which attracts increasing attention of the researchers in the field of electronic information technology. With the application of supercontinuum laser source, it is now possible to develop an HSL system, which can collect spectral and spatial information of targets simultaneously. Meanwhile, eye-safety and miniature HSL device with multiple spectral bands are given more priorities in on-site applications. In this paper, we tempt to investigate how to select spectral bands with a selection method. The proposed method consists of three steps: first, the variances among the classes based on hyperspectral feature parameters, termed inter-class variances, are calculated; second, the channels are sorted based on corresponding variances in descending order, and those with the two highest values are adopted as the initial input of classification; finally, the channels are selected successively from the rest of the sorted sequence until the classification accuracy reaches 100%. To test the performance of the proposed method, we collect 91/71-channel hyperspectral measurements of four different categories of materials with 5 nm spectral resolution using an acousto-optic tunable filter (AOTF) based HSL. Experimental results demonstrate that the proposed method could achieve higher classification accuracy than a random band selection method with different classifiers (naïve Bayes (NB) and support vector machine (SVM)) regardless of classification feature parameters (echo maximum and reflectance). To reach 100% accuracy, it demands 8–9 channels on average by echo maximum and 4–5 channels on average by reflectance based on NB classifier; these figures are 3–4 by echo maximum and 2–3 by reflectance with SVM classifier. The proposed method can complete classification task much faster than the random selection method. We further confirm the specific channels for the classification of different materials, and find that the optimal channels vary with different materials. The experimental results prove that the optimal band selection of HSL system for classification is reliable.
      Citation: Electronics
      PubDate: 2020-01-13
      DOI: 10.3390/electronics9010148
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 149: Commercial ICT Smart Solutions for the
           Elderly: State of the Art and Future Challenges in the Smart Furniture

    • Authors: Robert Frischer, Ondrej Krejcar, Petra Maresova, Oluwaseun Fadeyi, Ali Selamat, Kamil Kuca, Signe Tomsone, João Paulo Teixeira, Joana Madureira, Francisco Jose Melero
      First page: 149
      Abstract: Within a ubiquitous environment, home and office furniture can be maximally utilized to provide ease, especially if the items are designed based on smart technology. For this reason, the acceptance of smart furniture has soared over the years. Given the vast influence of the Internet of Things (IoT) and Industry 4.0 on technological advancement in furniture design, it is imperative to examine information and communication technology (ICT) solutions for the elderly in the context of smart furniture design and implementation. This article presents a review of the state-of-the-art literature in smart solutions for the elderly based on publications under ICT smart solutions for these elderly, along with smart furniture options and manufacturer activities in terms of fixing market prices for these furniture materials. Furthermore, patenting rights on some existing smart furniture designs for the elderly, given the current trends in worldwide acceptance, are examined. Moreover, this article also highlights opportunities introduced by IoT-based solutions for the elderly as current trends in research and their effects on human life. Some smart product examples from different enterprises are also presented. New, innovative and active designs must be developed, focusing upon human healthcare, and in turn providing greater comfort and convenience for elderly people. To fulfil these requirements, the also selected technical aspects of new Smart Furniture solutions in connection to the cost of these solutions are discussed. Simultaneously, Smart Furniture solutions need to be flexible, low-cost, easy to buy and install without expert knowledge, and widely available on the market.
      Citation: Electronics
      PubDate: 2020-01-13
      DOI: 10.3390/electronics9010149
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 150: Design and Validation of 100 nm GaN-On-Si
           Ka-Band LNA Based on Custom Noise and Small Signal Models

    • Authors: Lorenzo Pace, Sergio Colangeli, Walter Ciccognani, Patrick Ettore Longhi, Ernesto Limiti, Remy Leblanc, Marziale Feudale, Fabio Vitobello
      First page: 150
      Abstract: In this paper a GaN-on-Si MMIC Low-Noise Amplifier (LNA) working in the Ka-band is shown. The chosen technology for the design is a 100 nm gate length HEMT provided by OMMIC foundry. Both small-signal and noise models had been previously extracted by the means of an extensive measurement campaign, and were then employed in the design of the presented LNA. The amplifier presents an average noise figure of 2.4 dB, a 30 dB average gain value, and input/output matching higher than 10 dB in the whole 34–37.5 Ghz design band, while non-linear measurements testify a minimum output 1 dB compression point of 23 dBm in the specific 35–36.5 GHz target band. This shows the suitability of the chosen technology for low-noise applications.
      Citation: Electronics
      PubDate: 2020-01-13
      DOI: 10.3390/electronics9010150
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 151: Calibration and Characterization of a
           Reduced Form-Factor High Accuracy Three-Axis Teslameter

    • Authors: Johann Cassar, Andrew Sammut, Nicholas Sammut, Marco Calvi, Zarko Mitrovic, Radivoje S. Popovic
      First page: 151
      Abstract: A new reduced form-factor three axes digital teslameter, based on the spinning current technique, has been developed. This instrument will be used to characterize the SwissFEL insertion devices at the Paul Scherrer Institute (PSI) for the ATHOS soft X-ray beamline. A detailed and standardized calibration procedure is critical to optimize the performance of this precision instrument. This paper presents the measurement techniques used for the corrective improvements implemented through non-linearity, temperature offset, temperature sensitivity compensation of the Hall probe and electronics temperature compensation. A detailed quantitative analysis of the reduction in errors on the application of each step of the calibration is presented. The percentage peak error reduction attained through calibration of the instrument for reference fields in the range of ±2 T is registered to drop from 1.94% down to 0.02%.
      Citation: Electronics
      PubDate: 2020-01-13
      DOI: 10.3390/electronics9010151
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 152: Perspective on Commercial Li-ion Battery
           Testing, Best Practices for Simple and Effective Protocols

    • Authors: Dubarry, Baure
      First page: 152
      Abstract: Validation is an integral part of any study dealing with modeling or development of new control algorithms for lithium ion batteries. Without proper validation, the impact of a study could be drastically reduced. In a perfect world, validation should involve testing in deployed systems, but it is often unpractical and costly. As a result, validation is more often conducted on single cells under control laboratory conditions. Laboratory testing is a complex task, and improper implementation could lead to fallacious results. Although common practice in open literature, the protocols used are usually too quickly detailed and important details are left out. This work intends to fully describe, explain, and exemplify a simple step-by-step single apparatus methodology for commercial battery testing in order to facilitate and standardize validation studies.
      Citation: Electronics
      PubDate: 2020-01-14
      DOI: 10.3390/electronics9010152
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 153: Low-Cost Image Search System on Off-Line

    • Authors: Diana, Chikama, Amagasaki, Iida
      First page: 153
      Abstract: Implementation of deep learning in low-cost hardware, such as an edge device, is challenging. Reducing the complexity of the network is one of the solutions to reduce resource usage in the system, which is needed by low-cost system implementation. In this study, we use the general average pooling layer to replace the fully connected layers on the convolutional neural network (CNN) model, used in the previous study, to reduce the number of network properties without decreasing the model performance in developing image classification for image search tasks. We apply the cosine similarity to measure the characteristic similarity between the feature vector of image input and extracting feature vectors from testing images in the database. The result of the cosine similarity calculation will show the image as the result of the searching image task. In the implementation, we use Raspberry Pi 3 as a low-cost hardware and CIFAR-10 dataset for training and testing images. Base on the development and implementation, the accuracy of the model is 68%, and the system generates the result of the image search base on the characteristic similarity of the images.
      Citation: Electronics
      PubDate: 2020-01-14
      DOI: 10.3390/electronics9010153
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 154: Single-Phase Inverter Deadbeat Control
           with One-Carrier-Period Lag

    • Authors: Yao, Cui, Yao
      First page: 154
      Abstract: This paper presents a novel digital control scheme for the regulation of single-phase voltage source pulse width modulation (PWM) inverters used in AC power sources. The proposed scheme adopts two deadbeat controllers to regulate the inner current loop and the outer voltage loop of the PWM inverter. For the overhead of digital processing, the change of duty of PWM lags one carrier period behind the sampling signal, which is modeled as a first-order lag unit in a discrete domain. Based on this precise modeling, the deadbeat controllers make the inverter get a fast dynamic response, so that the inverter’s output voltage is obtained with a very low total harmonic distortion (THD), even when the load is fluctuating. The parameter sensitivity of the deadbeat control was analyzed, which shows that the proposed deadbeat control system can operate stably when the LC filter’s parameters vary within the range allowed. The experimental results of a 2kW inverter prototype show that the THD of the output voltage is less than 3% under resistive and rectifier loads, which verifies the feasibility of the proposed scheme. An additional advantage of the proposed scheme is that the parameter design of the controller can be fully programmed without the experience of a designer.
      Citation: Electronics
      PubDate: 2020-01-14
      DOI: 10.3390/electronics9010154
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 155: A Hierarchical Modeling and Analysis
           Framework for Availability and Security Quantification of
           IoT Infrastructures

    • Authors: Nguyen, Min, Choi
      First page: 155
      Abstract: Modeling a complete Internet of Things (IoT) infrastructure is crucial to assess its availabilityand security characteristics. However, modern IoT infrastructures often consist of a complex andheterogeneous architecture and thus taking into account both architecture and operative details ofthe IoT infrastructure in a monolithic model is a challenge for system practitioners and developers.In that regard, we propose a hierarchical modeling framework for the availability and securityquantification of IoT infrastructures in this paper. The modeling methodology is based on ahierarchical model of three levels including (i) reliability block diagram (RBD) at the top levelto capture the overall architecture of the IoT infrastructure, (ii) fault tree (FT) at the middle level toelaborate system architectures of the member systems in the IoT infrastructure, and (iii) continuoustime Markov chain (CTMC) at the bottom level to capture detailed operative states and transitionsof the bottom subsystems in the IoT infrastructure. We consider a specific case-study of IoT smartfactory infrastructure to demonstrate the feasibility of the modeling framework. The IoT smartfactory infrastructure is composed of integrated cloud, fog, and edge computing paradigms. Acomplete hierarchical model of RBD, FT, and CTMC is developed. A variety of availability andsecurity measures are computed and analyzed. The investigation of the case-study’s analysis resultsshows that more frequent failures in cloud cause more severe decreases of overall availability, whilefaster recovery of edge enhances the availability of the IoT smart factory infrastructure. On theother hand, the analysis results of the case-study also reveal that cloud servers’ virtual machinemonitor (VMM) and virtual machine (VM), and fog server’s operating system (OS) are the mostvulnerable components to cyber-security attack intensity. The proposed modeling and analysisframework coupled with further investigation on the analysis results in this study help develop andoperate the IoT infrastructure in order to gain the highest values of availability and security measuresand to provide development guidelines in decision-making processes in practice.
      Citation: Electronics
      PubDate: 2020-01-14
      DOI: 10.3390/electronics9010155
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 156: A Low-Complex Frame Rate Up-Conversion
           with Edge-Preserved Filtering

    • Authors: Ran Li, Wendan Ma, Yanling Li, Lei You
      First page: 156
      Abstract: The improvement of resolution of digital video requires a continuous increase of computation invested into Frame Rate Up-Conversion (FRUC). In this paper, we combine the advantages of Edge-Preserved Filtering (EPF) and Bidirectional Motion Estimation (BME) in an attempt to reduce the computational complexity. The inaccuracy of BME results from the existing similar structures in the texture regions, which can be avoided by using EPF to remove the texture details of video frames. EPF filters out by the high-frequency components, so each video frame can be subsampled before BME, at the same time, with the least accuracy degradation. EPF also preserves the edges, which prevents the deformation of object in the process of subsampling. Besides, we use predictive search to reduce the redundant search points according to the local smoothness of Motion Vector Field (MVF) to speed up BME. The experimental results show that the proposed FRUC algorithm brings good objective and subjective qualities of the interpolated frames with a low computational complexity.
      Citation: Electronics
      PubDate: 2020-01-15
      DOI: 10.3390/electronics9010156
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 157: Novel Prediction Framework for Path Delay
           Variation Based on Learning Method

    • Authors: Guo, Cao, Sun, Xu, Liu, Yang
      First page: 157
      Abstract: Path delay variation becomes a serious concern in advanced technology, especially for multi-corner conditions. Plenty of timing analysis methods have been proposed to solve the issue of path delay variation, but they mainly focus on every single corner and are based on a characterized timing library, which neglects the correlation among multiple corners, resulting in a high characterization effort for all required corners. Here, a novel prediction framework is proposed for path delay variation by employing a learning-based method using back propagation (BP) regression. It can be used to solve the issue of path delay variation prediction under a single corner. Moreover, for multi-corner conditions, the proposed framework can be further expanded to predict corners that are not included in the training set. Experimental results show that the proposed model outperforms the traditional Advanced On-Chip Variation (AOCV) method with 1.4X improvement for the prediction of path delay variation for single corners. Additionally, while predicting new corners, the maximum error is 4.59%, which is less than current state-of-the-art works.
      Citation: Electronics
      PubDate: 2020-01-15
      DOI: 10.3390/electronics9010157
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 158: An Urban Autodriving Algorithm Based on a
           Sensor-Weighted Integration Field with Deep Learning

    • Authors: Oh, Cha, Bae, Lim
      First page: 158
      Abstract: This paper proposes two algorithms for adaptive driving in urban environments: the first uses vision deep learning, which is named the sparse spatial convolutional neural network (SSCNN); and the second uses a sensor integration algorithm, named the sensor-weighted integration field (SWIF). These algorithms utilize three kinds of sensors, namely vision, Light Detection and Range (LiDAR), and GPS sensors, and decide critical motions for autonomous vehicle, such as steering angles and vehicle speed. SSCNN, which is used for lane recognition, has 2.7 times faster processing speed than the existing spatial CNN method. Additionally, the dataset for SSCNN was constructed by considering both normal and abnormal driving in 7 classes. Thus, lanes can be recognized by extending lanes for special characteristics in urban settings, in which the lanes can be obscured or erased, or the vehicle can drive in any direction. SWIF generates a two-dimensional matrix, in which elements are weighted by integrating both the object data from LiDAR and waypoints from GPS based on detected lanes. These weights are the integers, indicating the degree of safety. Based on the field formed by SWIF, the safe trajectories for two vehicles’ motions, steering angles, and vehicle speed are generated by applying the cost field. Additionally, to flexibly follow the desired steering angle and vehicle speed, the Proportional-Integral-Differential (PID) control is moderated by an integral anti-windup scheme. Consequently, as the dataset considers characteristics of the urban environment, SSCNN is able to be adopted for lane recognition on urban roads. The SWIF algorithm is also useful for flexible driving owing to the high efficiency of its sensor integration, including having a resolution of 2 cm per pixel and speed of 24 fps. Thus, a vehicle can be successfully maneuvered with minimized steering angle change, without lane or route departure, and without obstacle collision in the presence of diverse disturbances in urban road conditions.
      Citation: Electronics
      PubDate: 2020-01-15
      DOI: 10.3390/electronics9010158
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 159: Computer Vision Intelligent Approaches to
           Extract Human Pose and Its Activity from Image Sequences

    • Authors: Paulo J. S. J. S. Gonçalves, Bernardo Lourenço, Samuel Santos, Rodolphe Barlogis, Alexandre Misson
      First page: 159
      Abstract: The purpose of this work is to develop computational intelligence models based on neural networks (NN), fuzzy models (FM), support vector machines (SVM) and long short-term memory networks (LSTM) to predict human pose and activity from image sequences, based on computer vision approaches to gather the required features. To obtain the human pose semantics (output classes), based on a set of 3D points that describe the human body model (the input variables of the predictive model), prediction models were obtained from the acquired data, for example, video images. In the same way, to predict the semantics of the atomic activities that compose an activity, based again in the human body model extracted at each video frame, prediction models were learned using LSTM networks. In both cases the best learned models were implemented in an application to test the systems. The SVM model obtained 95.97% of correct classification of the six different human poses tackled in this work, during tests in different situations from the training phase. The implemented LSTM learned model achieved an overall accuracy of 88%, during tests in different situations from the training phase. These results demonstrate the validity of both approaches to predict human pose and activity from image sequences. Moreover, the system is capable of obtaining the atomic activities and quantifying the time interval in which each activity takes place.
      Citation: Electronics
      PubDate: 2020-01-15
      DOI: 10.3390/electronics9010159
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 160: Expected Income of New Currency in
           Blockchain Based on Data-Mining Technology

    • Authors: Li, Zeng
      First page: 160
      Abstract: In order to realize the understanding of expected returns after issuance of blockchain new currency initial coin offerings (ICO) and maximize investment returns, in this study, the Semantic Orientation Pointwise Mutual Information (SO-PMI) algorithm is used to create a customer emotional dictionary of blockchain new currency, and collect users’ online comments based on blockchain currency before ICO. The Support Vector Machine (SVM) algorithm is used to construct an evaluation model, analyze and judge users’ comments, make accurate prediction of the expected return of ICO issuing new currency, improve investment operations, and maximize the return of investment. The results show that the combination of the SO-PMI and SVM algorithms can accurately evaluate the price after the issuance of new currency, and then realize the judgment of expected return and obtain the expected return of investment. It can be seen that the combination of algorithms based on data-mining technology is applied to the study of the expected return of new currency issuance in blockchain, which achieves the goal of revenue anticipation and greatly reduces the investment risk of new currency issuance in blockchain.
      Citation: Electronics
      PubDate: 2020-01-15
      DOI: 10.3390/electronics9010160
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 161: Design and Measurement of a 0.67 THz
           Biased Sub-Harmonic Mixer

    • Authors: Ji, Zhang, Meng, Liu, Yao
      First page: 161
      Abstract: To effectively reduce the requirement of Local Oscillator (LO) power, this paper presents the design and measurement of a biased sub-harmonic mixer working at the center frequency of 0.67 THz in hybrid integration. Two discrete Schottky diodes were placed across the LO waveguide in anti-series configuration on a 50 μm thick quartz-glass substrate, and chip capacitors were not required. At the driven of 3 mW@335 GHz and 0.35 V, the mixer had a minimum measured Signal Side-Band (SSB) conversion loss of 15.3 dB at the frequency of 667 GHz. The typical conversion loss is 18.2 dB in the band of 650 GHz to 690 GHz.
      Citation: Electronics
      PubDate: 2020-01-15
      DOI: 10.3390/electronics9010161
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 162: Collaborative Mobile-Learning Architecture
           Based on Mobile Agents

    • Authors: Atawneh, Al-Akhras, AlMomani, Liswi, Alawairdhi
      First page: 162
      Abstract: : The connection between collaborative learning and the new mobile technology has become tighter. Mobile learning enhances collaborative learning as learners can access information and learning materials from anywhere and at any time. However, supporting efficient mobile learning in education is a critical challenge. In addition, incorporating technological and educational components becomes a new, complex dimension. In this paper, an efficient collaborative mobile-learning architecture based on mobile agents is proposed to enhance learning activity and to allow teachers and students to collaborate in knowledge and information transfer. A mobile agent can control its own actions, is able to communicate with other agents, and adapts in accordance with previous experience. The proposed model consists of four components: the learner agent, the teacher agent, the device agent and the social agent. The social agent plays the main role in the collaborative tasks since it is responsible for evaluating the collaborative interactions among different learners. Additionally, it offers an evaluation indicator for the learners’ collaboration and supplies the teacher with learner’s collaboration reports. The proposed model is evaluated by introducing a collaborative mobile-learning case study applied to two full classes of undergraduate students. To conduct the model experiments, students were asked to complete a questionnaire after they used the proposed model. The questionnaire results statistically revealed that the proposed architecture is easy to use and access, well-organized, convenient, and facilitates the learning process. The students thought the proposed m-learning application should complement rather than replace the traditional lectures. Moreover, the experimental results show that the proposed collaborative mobile learning model enhances the learner’s skills in problem solving, increases the learner’s knowledge in comparison with individual learning, and social agent encourages learners for more participation in the learning tasks. Based on the experiments conducted, the authors found that the proposed model can improve the quality of the learning process by assessing learners’ and groups’ collaboration, and it can help teachers make learners improve how they work in groups. This also provides various ways of assessing learners abilities and skills in groups. It is also possible to integrate the collaborative e-learning with the proposed collaborative m-learning.
      Citation: Electronics
      PubDate: 2020-01-15
      DOI: 10.3390/electronics9010162
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 163: Design of Reconfigurable Bandwidth
           Filtering Antenna and Its applications in IR/UWB System

    • Authors: Zhang, Pan
      First page: 163
      Abstract: A reconfigurable bandwidth antenna for an impulse radio-UWB (IR/UWB) system design is illustrated in this paper. By adopting a continuously tunable low-pass filter by varactor at the feed of the antenna, the proposed antenna obtains a continuous tunable bandwidth from 1.02 GHz to 2.42 GHz. To ensure the identifiability of transmitted pulses in (IR-UWB) system, the antenna is analyzed in both frequency domain and time domain. The proposed antenna is valid with a system fidelity factor (SFF) above 0.8 while the bandwidth is tuning. The compact size, low cost, and tunable bandwidth with the identifiability of the transmitted pulse makes it suitable for UWB impulse radars to improve the utility ratio of frequency, and dynamic adjustment avoids interference of the IR-UWB in other communication frequency bands.
      Citation: Electronics
      PubDate: 2020-01-15
      DOI: 10.3390/electronics9010163
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 164: File Type and Access Pattern Aware Buffer
           Cache Management for Rendering Systems

    • Authors: Shin, Cho, Bahn
      First page: 164
      Abstract: Rendering is the process of generating high-resolution images by software, which is widely used in animation, video games and visual effects in movies. Although rendering is a computation-intensive job, we observe that storage accesses may become another performance bottleneck in desktop-rendering systems. In this article, we present a new buffer cache management scheme specialized for rendering systems. Unlike general-purpose computing systems, rendering systems exhibit specific file access patterns, and we show that this results in significant performance degradation in the buffer cache system. To cope with this situation, we collect various file input/output (I/O) traces of rendering workloads and analyze their access patterns. The results of this analysis show that file I/Os in rendering processes consist of long loops for configuration, short loops for texture input, random reads for input, and single-writes for output. Based on this observation, we propose a new buffer cache management scheme for improving the storage performance of rendering systems. Experimental results show that the proposed scheme improves the storage I/O performance by an average of 19% and a maximum of 55% compared to the conventional buffer cache system.
      Citation: Electronics
      PubDate: 2020-01-15
      DOI: 10.3390/electronics9010164
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 165: Low Noise, High Input Impedance
           Digital-Analog Hybrid Offset Suppression Amplifier for Wearable Dry
           Electrode ECG Monitoring

    • Authors: Weilin Xu, Taotao Wang, Xueming Wei, Hongwei Yue, Baolin Wei, Jihai Duan, Haiou Li
      First page: 165
      Abstract: The portable real-time electrocardiogram (ECG) is a convenient and promising electronic device for cardiovascular diseases patients. However, unlike wet gel electrodes in traditional clinical applications, dry electrodes are competent for comfortable long-time wearing and can prevent skin ulceration. Its ultra-high source impedance and electrode offset (EOS) make traditional chopper amplifiers with low input impedance and limited EOS range difficult to apply to this area. To overcome these challenges, this paper proposes a novel chopper amplifier topology. This architecture includes a gain control loop, a ripple reduction loop, and a DC-servo loop (DSL). The proposed sampling input stage and digital-analog hybrid DSL are employed to boost input impedance and extend the EOS handing range. Designed with a 0.18 µm 1P6M 1.8 V CMOS salicide process, the proposed chopper capacitively coupled instrumentation amplifier achieves an ultra-high input impedance of 120 GΩ (<0.05 Hz) or 2.1 GΩ (0.6~250 Hz), an EOS handing range of ±325 mV and a low noise of 1.9 μVrms at 0.6~250 Hz. It occupies an area of 0.36 mm2 and only consumes a quiescent current of 11 μA.
      Citation: Electronics
      PubDate: 2020-01-16
      DOI: 10.3390/electronics9010165
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 166: A Novel Rate Control Algorithm Based on ρ
           Model for Multiview High Efficiency Video Coding

    • Authors: Tao Yan, In-Ho Ra, Qian Zhang, Hang Xu, Linyun Huang
      First page: 166
      Abstract: Most existing rate control algorithms are based on the rate-quantization (R-Q) model. However, with video coding schemes becoming more flexible, it is very difficult to accurately model the R-Q relationship. Therefore, in this study we propose a novel ρ domain rate control algorithm for multiview high efficiency video coding (MV-HEVC). Firstly, in order to further improve the efficiency of MV-HEVC, this paper uses our previous research algorithm to optimize the MV-HEVC prediction structure. Then, we established the ρ domain rate control model based on multi-objective optimization. Finally, it used image similarity to analyze the correlation between viewpoints, using encoded information and frame complexity to proceed in bit allocation and bit rate control of the inter-view, frame lay, and base unit. The experimental simulation results show that the algorithm can simultaneously maintain high coding efficiency, where the average error of the actual bit rate and the target bit rate is only 0.9%.
      Citation: Electronics
      PubDate: 2020-01-16
      DOI: 10.3390/electronics9010166
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 167: Direct Usage of Photovoltaic Solar Panels
           to Supply a Freezer Motor with Variable DC Input Voltage

    • Authors: Ali Farzan Moghaddam, Alex Van den Bossche
      First page: 167
      Abstract: In this paper, a single-phase photovoltaic (PV) inverter fed by a boost converter to supply a freezer motor with variable DC input is investigated. The proposed circuit has two stages. Firstly, the DC output of the PV panel that varies between 150 and 300 V will be applied to the boost converter. The boost converter will boost the input voltage to a fixed 300 V DC. Next, this voltage is supplied to the single-phase full bridge inverter to obtain 230 V AC. In the end, The output of the inverter will feed a freezer motor. The PV panels can be stand-alone or grid-connected. The grid-connected PV is divided into two categories, such as with a transformer and without a transformer, a transformer type has galvanic isolation resulting in increasing the security and also provides no further DC current toward the grid, but it is expensive, heavy and bulky. The transformerless type holds high efficiency and it is cheaper, but it suffers from leakage current between PV and the grid. This paper proposes a stand-alone direct use of PV to supply a freezer; therefore, no grid connection will result in no leakage current between the PV and Grid. The proposed circuit has some features such as no filtering circuit at the output of the inverter, no battery in the system, DC-link instead of AC link that reduces no-loads, having a higher efficiency, and holding enough energy in the DC-link capacitor to get the motor started. The circuit uses no transformers, thus, it is cheaper and has a smaller size. In addition, the system does not require a complex pulse width modulation (PWM) technique, because the motor can operate with a pulsed waveform. The control strategy uses the PWM signal with the desired timing. With this type of square wave, the harmonics (5th and 7th) of the voltage are reduced. The experimental and simulation results are presented to verify the feasibility of the proposed strategy.
      Citation: Electronics
      PubDate: 2020-01-16
      DOI: 10.3390/electronics9010167
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 168: Extended Spatial-Index LED Modulation for
           Optical MIMO-OFDM Wireless Communication

    • Authors: Hany S. Hussein, Mohamed Hagag, Mohammed Farrag
      First page: 168
      Abstract: An efficient optical modulation technique for multi-input multi-output (MIMO) orthogonal frequency division multiplexing (OFDM) visible light communication system is proposed in this paper. The proposed modulation technique is termed as extended spatial-index light-emitting diode (LED) modulation. In the proposed technique, the indices (the spatial domain) of the LEDs are exploited in a dynamic style to not only get rid of the optical OFDM time-domain ( OFDM t d ) shaping problem but also to expand the LED indices spatial modulation domain. The indices of the active LEDs in the proposed technique are changed from the two LEDs active situation to the situation where all or several LEDs are active. Moreover, within the selected active LED indices, the power weight distribution and the positions of the OFDM components are varied to expand the resultant spatial domain. Therefore, the proposed technique offers a considerable spectral efficiency improvement over the up-to-date LED index OFDM modulation schemes even with a lower number of LEDs. The key idea of the proposed technique is to maximize the LEDs’ indices spatial position (spatial domain) utilization, where both the power weight allocation and the positions of the complex OFDM time domain components are varying several times over the same active LED indices combination, which improve the optical system spectral efficiency. The simulation results asserted the superiority of the proposed technique, as it improves both the average bit error rate (ABER) and the achievable data rate (R) compared with existing up-to-date OFDM-LED index modulations with even lower computational complexity.
      Citation: Electronics
      PubDate: 2020-01-16
      DOI: 10.3390/electronics9010168
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 169: Two-Source Asymmetric Turbo-Coded
           Cooperative Spatial Modulation Scheme with Code Matched Interleaver

    • Authors: Zhao, Yang, Umar, Mughal
      First page: 169
      Abstract: This paper proposes, for the first time, a two-source asymmetric turbo-coded-cooperative spatial modulation (SM) scheme over the slow Rayleigh fading channel. As in any coded cooperative communication, the interleaver plays a vital role in mitigating the harsh effect of the wireless channel. Therefore, the code matched interleaver (CMI) is effectively used in the proposed design. The simulated results reveal that the bit error rate (BER) performance of the proposed coded cooperative communication system outperforms the asymmetric turbo-coded non-cooperative scheme under identical conditions. This prominent performance improvement has been made possible due to the joint asymmetric turbo decoding at the destination node. Furthermore, to check the effectiveness of the proposed scheme, we have also developed a two-source asymmetric turbo-coded cooperative scheme based on the vertical bell labs layered space-time (VBLAST), incorporating the CMI as the suitable benchmark. It is observed that the proposed scheme employing SM has a better BER performance than the VBLAST scheme under identical conditions.
      Citation: Electronics
      PubDate: 2020-01-16
      DOI: 10.3390/electronics9010169
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 170: A Design of Hybrid Appliance Local Network
           (HALN) Communication Architecture

    • Authors: Park, Lee
      First page: 170
      Abstract: Recently, appliance networks have been widely adopted in many home applications. Usually, an appliance network requires a server. However, as the number of network users increases, there is not only the problem of costs due to extension of the server and the increase in power consumption, but also the problem that the functions of appliances are restricted when the connection to a server is unavailable. This paper presents a hybrid appliance local network (HALN) communication architecture to tackle the problems with server-based appliance networks. The HALN architecture is designed to remove and/or minimize the utilization of servers by offering the capability of communicating directly with other appliance products. The proposed architecture can also be integrated with existing server-based communication architectures. The HALN architecture is based on the simple service discovery protocol (SSDP) and HTTP protocol (RESTful HTTP server/client architecture) technologies. The effectiveness of HALN is experimentally demonstrated using a smartphone and a set of Linux-based Wi-Fi modems on which the functions that can be provided by typical appliances are implemented. Using the proposed architecture, the communication reliability is also improved by 1.6% as compared with that of an existing server-based communication architecture.
      Citation: Electronics
      PubDate: 2020-01-16
      DOI: 10.3390/electronics9010170
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 171: Design and Implementation of a Test
           Fixture for ELF Schumann Resonance Magnetic Antenna Receiver and Magnetic
           Permeability Measurements

    • Authors: Tatsis, Christofilakis, Chronopoulos, Kostarakis, Nistazakis, Repapis, Tritakis
      First page: 171
      Abstract: This paper presents a prototype test fixture for the absolute calibration and estimation of the equivalent magnetic flux noise of the extremely low frequency (ELF) Schumann resonant (SR) magnetic antenna receiver and rods’ magnetic permeability measurement. The test fixture, for ELF the SR detector’s calibration, consists of a constructed coil, the signal generator, and the oscilloscope. The ELF SR detector used has been operating since 2016 near the Doliana village in the Ioannina prefecture, Northwestern Greece. At precisely this spot, far away from electromagnetic noise, the whole setup and experiment took place. The experiments performed with the proposed test fixture showed a sensitivity of 70 nV/pT/Hz and an apparent magnetic permeability at around 250 for the magnetic antenna. The total sensitivity of the ELF receiver was 210 mV/pT near 20 Hz, while the total input noise was around 0.04 pT.
      Citation: Electronics
      PubDate: 2020-01-16
      DOI: 10.3390/electronics9010171
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 172: Current Control Methods for an Asymmetric
           Six-Phase Permanent Magnet Synchronous Motor

    • Authors: Wu, Gu, Zhu, Lu
      First page: 172
      Abstract: Via the vector space decomposition(VSD)transformation, the currents in an asymmetric six-phase permanent magnet synchronous motor (ASP_PMSM) can be decoupled into three orthogonal subspaces. Control of α–β currents in α–β subspace is important for torque regulation, while control of x-y currents in x-y subspace can suppress the harmonics due to the dead time of converters and other nonlinear factors. The zero-sequence components in O1-O2 subspace are 0 due to isolated neutral points. In α–β subspace, a state observer is constructed by introducing the error variable between the real current and the internal model current based on the internal model control method, which can improve the current control performance compared to the traditional internal model control method. In x–y subspace, in order to suppress the current harmonics, an adaptive-linear-neuron (ADALINE)-based control algorithm is employed to generate the compensation voltage, which is self-tuned by minimizing the estimated current distortion through the least mean square (LMS) algorithm. The modulation technique to implement the four-dimensional current control based on the three-phase SVPWM is given. The experimental results validate the robustness and effectiveness of the proposed control method.
      Citation: Electronics
      PubDate: 2020-01-16
      DOI: 10.3390/electronics9010172
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 173: Hybrid Intrusion Detection System Based on
           the Stacking Ensemble of C5 Decision Tree Classifier and One Class Support
           Vector Machine

    • Authors: Ansam Khraisat, Iqbal Gondal, Peter Vamplew, Joarder Kamruzzaman, Ammar Alazab
      First page: 173
      Abstract: Cyberttacks are becoming increasingly sophisticated, necessitating the efficient intrusion detection mechanisms to monitor computer resources and generate reports on anomalous or suspicious activities. Many Intrusion Detection Systems (IDSs) use a single classifier for identifying intrusions. Single classifier IDSs are unable to achieve high accuracy and low false alarm rates due to polymorphic, metamorphic, and zero-day behaviors of malware. In this paper, a Hybrid IDS (HIDS) is proposed by combining the C5 decision tree classifier and One Class Support Vector Machine (OC-SVM). HIDS combines the strengths of SIDS) and Anomaly-based Intrusion Detection System (AIDS). The SIDS was developed based on the C5.0 Decision tree classifier and AIDS was developed based on the one-class Support Vector Machine (SVM). This framework aims to identify both the well-known intrusions and zero-day attacks with high detection accuracy and low false-alarm rates. The proposed HIDS is evaluated using the benchmark datasets, namely, Network Security Laboratory-Knowledge Discovery in Databases (NSL-KDD) and Australian Defence Force Academy (ADFA) datasets. Studies show that the performance of HIDS is enhanced, compared to SIDS and AIDS in terms of detection rate and low false-alarm rates.
      Citation: Electronics
      PubDate: 2020-01-17
      DOI: 10.3390/electronics9010173
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 174: Motor Imagery Based Continuous
           Teleoperation Robot Control with Tactile Feedback

    • Authors: Baoguo Xu, Wenlong Li, Xiaohang He, Zhiwei Wei, Dalin Zhang, Changcheng Wu, Aiguo Song
      First page: 174
      Abstract: Brain computer interface (BCI) adopts human brain signals to control external devices directly without using normal neural pathway. Recent study has explored many applications, such as controlling a teleoperation robot by electroencephalography (EEG) signals. However, utilizing the motor imagery EEG-based BCI to perform teleoperation for reach and grasp task still has many difficulties, especially in continuous multidimensional control of robot and tactile feedback. In this research, a motor imagery EEG-based continuous teleoperation robot control system with tactile feedback was proposed. Firstly, mental imagination of different hand movements was translated into continuous command to control the remote robotic arm to reach the hover area of the target through a wireless local area network (LAN). Then, the robotic arm automatically completed the task of grasping the target. Meanwhile, the tactile information of remote robotic gripper was detected and converted to the feedback command. Finally, the vibrotactile stimulus was supplied to users to improve their telepresence. Experimental results demonstrate the feasibility of using the motor imagery EEG acquired by wireless portable equipment to realize the continuous teleoperation robot control system to finish the reach and grasp task. The average two-dimensional continuous control success rates for online Task 1 and Task 2 of the six subjects were 78.0% ± 6.1% and 66.2% ± 6.0%, respectively. Furthermore, compared with the traditional EEG triggered robot control using the predefined trajectory, the continuous fully two-dimensional control can not only improve the teleoperation robot system’s efficiency but also give the subject a more natural control which is critical to human–machine interaction (HMI). In addition, vibrotactile stimulus can improve the operator’s telepresence and task performance.
      Citation: Electronics
      PubDate: 2020-01-17
      DOI: 10.3390/electronics9010174
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 175: Analysis of the Critical Bits of a RISC-V
           Processor Implemented in an SRAM-Based FPGA for Space Applications

    • Authors: Luis Alberto Aranda, Nils-Johan Wessman, Lucana Santos, Alfonso Sánchez-Macián, Jan Andersson, Roland Weigand, Juan Antonio Maestro
      First page: 175
      Abstract: One of the traditional issues in space missions is the reliability of the electronic components on board spacecraft. There are numerous techniques to deal with this, from shielding and rad-hard fabrication to ad-hoc fault-tolerant designs. Although many of these solutions have been extensively studied, the recent utilization of FPGAs as the target architecture for many electronic components has opened new possibilities, partly due to the distinct nature of these devices. In this study, we performed fault injection experiments to determine if a RISC-V soft processor implemented in an FPGA could be used as an onboard computer for space applications, and how the specific nature of FPGAs needs to be tackled differently from how ASICs have been traditionally handled. In particular, in this paper, the classic definition of the cross-section is revisited, putting into perspective the importance of the so-called “critical bits” in an FPGA design.
      Citation: Electronics
      PubDate: 2020-01-17
      DOI: 10.3390/electronics9010175
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 176: Application of a Stub-Loaded Square Ring
           Resonator for Wideband Bandpass Filter Design

    • Authors: Ping Zhang, Liqin Liu, Deli Chen, Min-Hang Weng, Ru-Yuan Yang
      First page: 176
      Abstract: In this paper, a stub-loaded square ring resonator (SLSRR) is analyzed and applied to design a very simple and compact wideband bandpass filter structure. Resonant modes dependent on the structure parameters of the SLSRR are analyzed first, and then the first two modes are used to achieve a required passband. The input and output terminals are supplied with high impedance and strong coupling to provide sufficient coupling energy. Two wideband filter examples are designed, manufactured, and measured using the SLSRRs. The first filter is a wideband filter with a wide upper stopband, and the second filter is a dual wideband filter with a notched stopband between two passbands. The two filter examples are designed, fabricated, and measured to verify the design concept and present the advantages of easy design and a simple and compact structure.
      Citation: Electronics
      PubDate: 2020-01-17
      DOI: 10.3390/electronics9010176
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 177: Acknowledgement to Reviewers of
           Electronics in 2019

    • Authors: Electronics Editorial Office
      First page: 177
      Abstract: n/a
      Citation: Electronics
      PubDate: 2020-01-17
      DOI: 10.3390/electronics9010177
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 178: Maximized Privacy-Preserving Outsourcing
           on Support Vector Clustering

    • Authors: Yuan Ping, Bin Hao, Xiali Hei, Jie Wu, Baocang Wang
      First page: 178
      Abstract: Despite its remarkable capability in handling arbitrary cluster shapes, support vector clustering (SVC) suffers from pricey storage of kernel matrix and costly computations. Outsourcing data or function on demand is intuitively expected, yet it raises a great violation of privacy. We propose maximized privacy-preserving outsourcing on SVC (MPPSVC), which, to the best of our knowledge, is the first all-phase outsourceable solution. For privacy-preserving, we exploit the properties of homomorphic encryption and secure two-party computation. To break through the operation limitation, we propose a reformative SVC with elementary operations (RSVC-EO, the core of MPPSVC), in which a series of designs make selective outsourcing phase possible. In the training phase, we develop a dual coordinate descent solver, which avoids interactions before getting the encrypted coefficient vector. In the labeling phase, we design a fresh convex decomposition cluster labeling, by which no iteration is required by convex decomposition and no sampling checks exist in connectivity analysis. Afterward, we customize secure protocols to match these operations for essential interactions in the encrypted domain. Considering the privacy-preserving property and efficiency in a semi-honest environment, we proved MPPSVC’s robustness against adversarial attacks. Our experimental results confirm that MPPSVC achieves comparable accuracies to RSVC-EO, which outperforms the state-of-the-art variants of SVC.
      Citation: Electronics
      PubDate: 2020-01-17
      DOI: 10.3390/electronics9010178
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 179: Energy Management of Solar-Powered
           Aircraft-Based High Altitude Platform for Wireless Communications

    • Authors: Steve Chukwuebuka Arum, David Grace, Paul Daniel Mitchell, Muhammad Danial Zakaria, Nils Morozs
      First page: 179
      Abstract: With the increasing interest in wireless communications from solar-powered aircraft-based high altitude platforms (HAPs), it is imperative to assess the feasibility of their deployment in different locations with the constraints on energy consumption and payload weight under consideration. This paper considers the energy management of solar-powered aircraft-based HAPs for wireless communications service provisioning in equatorial regions and regions further up the northern hemisphere. The total solar energy harvested and consumed on the shortest day of the year is analyzed, and it is explained how this determines the feasibility of long endurance, semi-permanent missions. This takes into account the different aircraft-based HAPs and the energy storage systems currently available, and how these can be deployed for wireless communications. We show that the solar-powered HAPs are energy and weight limited, and this depends largely on the platform’s wingspan available for the deployment of solar collectors. Our analysis show that services can be provided for a duration of 15–24 h/day using current platforms, with wingspans ranging between 25–35 m, depending on the configuration and coverage radius. Furthermore, we show that doubling an aircraft’s wingspan can increase its payload capacity by a factor of 6, which in turn enhances its feasibility for wireless communications.
      Citation: Electronics
      PubDate: 2020-01-18
      DOI: 10.3390/electronics9010179
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 180: Activities of Daily Living and Environment
           Recognition Using Mobile Devices: A Comparative Study

    • Authors: José M. Ferreira, Ivan Miguel Pires, Gonçalo Marques, Nuno M. Garcia, Eftim Zdravevski, Petre Lameski, Francisco Flórez-Revuelta, Susanna Spinsante, Lina Xu
      First page: 180
      Abstract: The recognition of Activities of Daily Living (ADL) using the sensors available in off-the-shelf mobile devices with high accuracy is significant for the development of their framework. Previously, a framework that comprehends data acquisition, data processing, data cleaning, feature extraction, data fusion, and data classification was proposed. However, the results may be improved with the implementation of other methods. Similar to the initial proposal of the framework, this paper proposes the recognition of eight ADL, e.g., walking, running, standing, going upstairs, going downstairs, driving, sleeping, and watching television, and nine environments, e.g., bar, hall, kitchen, library, street, bedroom, living room, gym, and classroom, but using the Instance Based k-nearest neighbour (IBk) and AdaBoost methods as well. The primary purpose of this paper is to find the best machine learning method for ADL and environment recognition. The results obtained show that IBk and AdaBoost reported better results, with complex data than the deep neural network methods.
      Citation: Electronics
      PubDate: 2020-01-18
      DOI: 10.3390/electronics9010180
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 181: A Novel Intrusion Detection Model Using a
           Fusion of Network and Device States for Communication-Based Train Control

    • Authors: Yajie Song, Bing Bu, Li Zhu
      First page: 181
      Abstract: Security is crucial in cyber-physical systems (CPS). As a typical CPS, the communication- based train control (CBTC) system is facing increasingly serious cyber-attacks. Intrusion detection systems (IDSs) are vital to protect the system against cyber-attacks. The traditional IDS cannot distinguish between cyber-attacks and system faults. Furthermore, the design of the traditional IDS does not take the principles of CBTC systems into consideration. When deployed, it cannot effectively detect cyber-attacks against CBTC systems. In this paper, we propose a novel intrusion detection method that considers both the status of the networks and those of the equipment to identify if the abnormality is caused by cyber-attacks or by system faults. The proposed method is verified on a hardware-in-the-loop simulation platform of CBTC systems. Simulation results indicate that the proposed method has achieved 97.64% true positive rate, which can significantly improve the security protection level of CBTC systems.
      Citation: Electronics
      PubDate: 2020-01-18
      DOI: 10.3390/electronics9010181
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 182: FPGA-Based Hardware Matrix Inversion
           Architecture Using Hybrid Piecewise Polynomial Approximation Systolic

    • Authors: Javier Vázquez-Castillo, Alejandro Castillo-Atoche, Roberto Carrasco-Alvarez, Omar Longoria-Gandara, Jaime Ortegón-Aguilar
      First page: 182
      Abstract: The hardware of the matrix inversion architecture using QR decomposition with Givens Rotations (GR) and a back substitution (BS) block is required for many signal processing algorithms. However, the hardware of the GR algorithm requires the implementation of complex operations, such as the reciprocal square root (RSR), which is typically implemented using LookUp Table (LUT) and COordinate Rotation DIgital Computer (CORDICs), among others, conveying to either high-area consumption or low throughput. This paper introduces an Field-Programmable Gate Array (FPGA)-based full matrix inversion architecture using hybrid piecewise polynomial approximation systolic cells. In the design, a hybrid segmentation technique was incorporated for the implementation of piecewise polynomial systolic cells. This hybrid approach is composed by an external and internal segmentation, where the first is nonuniform and the second is uniform, fitting the curve shape of the complex functions achieving a better signal-quantization-to noise-ratio; furthermore, it improves the time performance and area resources. Experimental results reveal a well-balanced improvement in the design achieving high throughput and, hence, less resource utilization in comparison to state-of-the-art FPGA-based architectures. In our study, the proposed design achieves 7.51 Mega-Matrices per second for performing 4 × 4 matrix operations with a latency of 12 clock cycles; meanwhile, the hardware design requires only 1474 slice registers, 1458 LUTs in an FPGA Virtex-5 XC5VLX220T, and 1474 slice registers and 1378 LUTs when a FPGA Virtex-6 XC6VLX240T is used.
      Citation: Electronics
      PubDate: 2020-01-18
      DOI: 10.3390/electronics9010182
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 183: Stator Inductance Identification Based on
           Low-Speed Tests for Three-Level NPC Inverter-Fed Induction Motor Drives

    • Authors: Khojakhan, Choo, Won
      First page: 183
      Abstract: This paper proposes a stator inductance identification process for three-level neutral point clamped (NPC), inverter-fed Induction Motor (IM) drives based on a low-speed test drive. Conventionally, the stator inductance of an IM is identified by methods based on standstill or rotational tests. Since conventional standstill test-based methods have several practical problems when used with three-level inverters because of their nonlinearity, an identification method based on rotational tests is superior in such applications. However, conventional rotational tests cause unintended behavior because of the high speeds used during the test. In the proposed stator inductance identification process, the stator inductance is identified based on a low-speed test drive. In the proposed method, the stator flux is estimated using the instantaneous reactive power of the IM during low-frequency sinusoidal current excitation, and the stator inductance is then identified based upon this. Therefore, the proposed identification process is safer than conventional approaches, as it uses only a low-speed test. The accuracy and reliability of this method are verified by simulation and experiment using three motors with different rated voltage and power.
      Citation: Electronics
      PubDate: 2020-01-18
      DOI: 10.3390/electronics9010183
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 184: Optimized Distributed Subgraph Matching
           Algorithm Based on Partition Replication

    • Authors: Ling Yuan, Jiali Bin, Peng Pan
      First page: 184
      Abstract: At present, with the explosive growth of data scale, subgraph matching for massive graph data is difficult to satisfy with efficiency. Meanwhile, the graph index used in existing subgraph matching algorithm is difficult to update and maintain when facing dynamic graphs. We propose a distributed subgraph matching algorithm based on Partition Replica (noted as PR-Match) to process the partition and storage of large-scale data graphs. The PR-Match algorithm first splits the query graph into sub-queries, then assigns the sub-query to each node for sub-graph matching, and finally merges the matching results. In the PR-Match algorithm, we propose a heuristic rule based on prediction cost to select the optimal merging plan, which greatly reduces the cost of merging. In order to accelerate the matching speed of the sub-query graph, a vertex code based on the vertex neighbor label signature is proposed, which greatly reduces the search space for the subquery. As the vertex code is based on the increment, the problem that the feature-based graph index is difficult to maintain in the face of the dynamic graph is solved. An abundance of experiments on real and synthetic datasets demonstrate the high efficiency and strong scalability of the PR-Match algorithm when handling large-scale data graphs.
      Citation: Electronics
      PubDate: 2020-01-18
      DOI: 10.3390/electronics9010184
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 185: Discrete Sliding Mode Speed Control of
           Induction Motor Using Time-Varying Switching Line

    • Authors: Tarchała, Orłowska-Kowalska
      First page: 185
      Abstract: Sliding mode control (SMC) of electric drives constitutes a very popular control method for nonlinear multivariable and time-varying systems, e.g., induction motor (IM) drives. Nowadays, IM are the most popular electrical machines (EM) applied in many industrial applications as motion control devices, including electrical and hybrid vehicles. Nowadays, the control systems of EM are mostly realized using digital techniques (microprocessors and microcontrollers). Therefore, all control algorithms should be discretized or the whole control system should be designed in the discrete-time domain. This paper deals with a discrete-time sliding mode control (DSMC) for IM drives. The discrete algorithms for sliding mode control of the motor speed and rotor flux are derived in detail and next tested in simulation research. The simulation tests include the discrete nature of the power converter supplying the IM and present excellent performance of the developed control structure. To obtain the rotor speed regulation invariant to external disturbances, like load torque or inertia, especially during the reaching phase of the switching line, the discrete version of a time-varying switching line was introduced. It is shown that the assumed dynamics of the IM flux and speed is achieved and the proposed control algorithm can be realized using commonly available microcontrollers. The paper is illustrated with comprehensive simulation results for 1.5 kW IM drive, which are verified by experimental tests.
      Citation: Electronics
      PubDate: 2020-01-18
      DOI: 10.3390/electronics9010185
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 186: A Novel 183 GHz Solid-State Sub-Harmonic

    • Authors: Ji, Zhang, Meng, Liu, Yao
      First page: 186
      Abstract: This paper proposes a novel sub-harmonic mixing topology. Based on the proposed topology and the precise three-dimensional electromagnetic model of the Schottky barrier diode; a novel 183 GHz solid-state sub-harmonic mixer is designed and measured. By adding a compact low-pass filter near the ground of the mixer’s circuit, the effect on the mixer’s RF performance of the random error of the conductive adhesive in assembling is effectively decreased. The test results show that the optimal single-sideband conversion loss of the mixer is 8.1dB@183GHz when the local oscillator signal is 4mw@91GHz. In the RF bandwidth from 173 GHz to 191 GHz, the single-sideband conversion loss is less than −10.6 dB. At the same time, the RF port return loss is less than 9.8 dB.
      Citation: Electronics
      PubDate: 2020-01-18
      DOI: 10.3390/electronics9010186
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 187: A Multi-Feature Representation of Skeleton
           Sequences for Human Interaction Recognition

    • Authors: Xiaohang Wang, Hongmin Deng
      First page: 187
      Abstract: Inspired from the promising performances achieved by recurrent neural networks (RNN) and convolutional neural networks (CNN) in action recognition based on skeleton, this paper presents a deep network structure which combines both CNN for classification and RNN to achieve attention mechanism for human interaction recognition. Specifically, the attention module in this structure is utilized to give various levels of attention to various frames by different weights, and the CNN is employed to extract the high-level spatial and temporal information of skeleton data. These two modules seamlessly form a single network architecture. In addition, to eliminate the impact of different locations and orientations, a coordinate transformation is conducted from the original coordinate system to the human-centric coordinate system. Furthermore, three different features are extracted from the skeleton data as the inputs of three subnetworks, respectively. Eventually, these subnetworks fed with different features are fused as an integrated network. The experimental result shows the validity of the proposed approach on two widely used human interaction datasets.
      Citation: Electronics
      PubDate: 2020-01-19
      DOI: 10.3390/electronics9010187
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 188: Leukemia Image Segmentation Using a Hybrid
           Histogram-Based Soft Covering Rough K-Means Clustering Algorithm

    • Authors: Hannah Inbarani H., Ahmad Taher Azar, Jothi G
      First page: 188
      Abstract: Segmenting an image of a nucleus is one of the most essential tasks in a leukemia diagnostic system. Accurate and rapid segmentation methods help the physicians identify the diseases and provide better treatment at the appropriate time. Recently, hybrid clustering algorithms have started being widely used for image segmentation in medical image processing. In this article, a novel hybrid histogram-based soft covering rough k-means clustering (HSCRKM) algorithm for leukemia nucleus image segmentation is discussed. This algorithm combines the strengths of a soft covering rough set and rough k-means clustering. The histogram method was utilized to identify the number of clusters to avoid random initialization. Different types of features such as gray level co-occurrence matrix (GLCM), color, and shape-based features were extracted from the segmented image of the nucleus. Machine learning prediction algorithms were applied to classify the cancerous and non-cancerous cells. The proposed strategy is compared with an existing clustering algorithm, and the efficiency is evaluated based on the prediction metrics. The experimental results show that the HSCRKM method efficiently segments the nucleus, and it is also inferred that logistic regression and neural network perform better than other prediction algorithms.
      Citation: Electronics
      PubDate: 2020-01-19
      DOI: 10.3390/electronics9010188
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 189: Developing Efficient Discrete Simulations
           on Multicore and GPU Architectures

    • Authors: Daniel Cagigas-Muñiz, Fernando Diaz-del-Rio, Manuel Ramón López-Torres, Francisco Jiménez-Morales, José Luis Guisado
      First page: 189
      Abstract: In this paper we show how to efficiently implement parallel discrete simulations on multicore and GPU architectures through a real example of an application: a cellular automata model of laser dynamics. We describe the techniques employed to build and optimize the implementations using OpenMP and CUDA frameworks. We have evaluated the performance on two different hardware platforms that represent different target market segments: high-end platforms for scientific computing, using an Intel Xeon Platinum 8259CL server with 48 cores, and also an NVIDIA Tesla V100 GPU, both running on Amazon Web Server (AWS) Cloud; and on a consumer-oriented platform, using an Intel Core i9 9900k CPU and an NVIDIA GeForce GTX 1050 TI GPU. Performance results were compared and analyzed in detail. We show that excellent performance and scalability can be obtained in both platforms, and we extract some important issues that imply a performance degradation for them. We also found that current multicore CPUs with large core numbers can bring a performance very near to that of GPUs, and even identical in some cases.
      Citation: Electronics
      PubDate: 2020-01-19
      DOI: 10.3390/electronics9010189
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 190: Fusion High-Resolution Network for
           Diagnosing ChestX-ray Images

    • Authors: Zhiwei Huang, Jinzhao Lin, Liming Xu, Huiqian Wang, Tong Bai, Yu Pang, Teen-Hang Meen
      First page: 190
      Abstract: The application of deep convolutional neural networks (CNN) in the field of medical image processing has attracted extensive attention and demonstrated remarkable progress. An increasing number of deep learning methods have been devoted to classifying ChestX-ray (CXR) images, and most of the existing deep learning methods are based on classic pretrained models, trained by global ChestX-ray images. In this paper, we are interested in diagnosing ChestX-ray images using our proposed Fusion High-Resolution Network (FHRNet). The FHRNet concatenates the global average pooling layers of the global and local feature extractors—it consists of three branch convolutional neural networks and is fine-tuned for thorax disease classification. Compared with the results of other available methods, our experimental results showed that the proposed model yields a better disease classification performance for the ChestX-ray 14 dataset, according to the receiver operating characteristic curve and area-under-the-curve score. An ablation study further confirmed the effectiveness of the global and local branch networks in improving the classification accuracy of thorax diseases.
      Citation: Electronics
      PubDate: 2020-01-19
      DOI: 10.3390/electronics9010190
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 191: A Recent Electronic Control Circuit to a
           Throttle Device

    • Authors: Leonardo Acho, Gisela Pujol-Vázquez, José Gibergans-Báguena
      First page: 191
      Abstract: The main objective of this paper was to conceive a new electronic control circuit to the throttle device. The throttle mechanical actuator is the most important part in an automotive gasoline engine. Among the different control strategies recently reported, an easy to implement control scheme is an open research topic in the analog electronic engineering field. Hence, we propose using the nonlinear dwell switching control theory for an analog electronic control unit, to manipulate an automotive throttle plate. Due to the switching mechanism commuting between a stable and an unstable controllers, the resultant closed-loop system is robust enough to the control objective. This fact is experimentally evidenced. The proposed electronic controller uses operational amplifiers along with an Arduino unit. This unit is just employed to generate the related switching signal that can be replaced by using, for instance, the timer IC555. Thus, this study is a contribution on design and realization of an electronic control circuit to the throttle device.
      Citation: Electronics
      PubDate: 2020-01-19
      DOI: 10.3390/electronics9010191
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 192: Identification of Daily Activites and
           Environments Based on the AdaBoost Method Using Mobile Device Data: A
           Systematic Review

    • Authors: José M. Ferreira, Ivan Miguel Pires, Gonçalo Marques, Nuno M. Garcia, Eftim Zdravevski, Petre Lameski, Francisco Flórez-Revuelta, Susanna Spinsante
      First page: 192
      Abstract: Using the AdaBoost method may increase the accuracy and reliability of a framework for daily activities and environment recognition. Mobile devices have several types of sensors, including motion, magnetic, and location sensors, that allow accurate identification of daily activities and environment. This paper focuses on the review of the studies that use the AdaBoost method with the sensors available in mobile devices. This research identified the research works written in English about the recognition of daily activities and environment recognition using the AdaBoost method with the data obtained from the sensors available in mobile devices that were published between 2012 and 2018. Thus, 13 studies were selected and analysed from 151 identified records in the searched databases. The results proved the reliability of the method for daily activities and environment recognition, highlighting the use of several features, including the mean, standard deviation, pitch, roll, azimuth, and median absolute deviation of the signal of motion sensors, and the mean of the signal of magnetic sensors. When reported, the analysed studies presented an accuracy higher than 80% in recognition of daily activities and environments with the Adaboost method.
      Citation: Electronics
      PubDate: 2020-01-20
      DOI: 10.3390/electronics9010192
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 193: Vehicular Navigation Based on the Fusion
           of 3D-RISS and Machine Learning Enhanced Visual Data in Challenging

    • Authors: Yunlong Sun, Lianwu Guan, Menghao Wu, Yanbin Gao, Zhanyuan Chang
      First page: 193
      Abstract: Based on the 3D Reduced Inertial Sensor System (3D-RISS) and the Machine Learning Enhanced Visual Data (MLEVD), an integrated vehicle navigation system is proposed in this paper. In demanding conditions such as outdoor satellite signal interference and indoor navigation, this work incorporates vehicle smooth navigation. Firstly, a landmark is set up and both of its size and position are accurately measured. Secondly, the image with the landmark information is captured quickly by using the machine learning. Thirdly, the template matching method and the Extended Kalman Filter (EKF) are then used to correct the errors of the Inertial Navigation System (INS), which employs the 3D-RISS to reduce the overall cost and ensuring the vehicular positioning accuracy simultaneously. Finally, both outdoor and indoor experiments are conducted to verify the performance of the 3D-RISS/MLEVD integrated navigation technology. Results reveal that the proposed method can effectively reduce the accumulated error of the INS with time while maintaining the positioning error within a few meters.
      Citation: Electronics
      PubDate: 2020-01-20
      DOI: 10.3390/electronics9010193
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 194: Design of SWB MIMO Antenna with Extremely
           Wideband Isolation

    • Authors: Habib Ullah, Saeed Ur Rahman, Qunsheng Cao, Ijaz Khan, Hamid Ullah
      First page: 194
      Abstract: This paper presents a compact planar multiple input multiple output (MIMO) antenna for super wide band (SWB) applications. The presented MIMO antenna comprises two identical patches on the same substrate. Dimensions of the MIMO antenna are 0.17λ × 0.20λ × 0.006λ mm3, with respect to the lowest resonance of 1.30 GHz. The SWB antenna was manufactured using F4B substrate having a dielectric constant of 2.65 that provides a percent impedance bandwidth and bandwidth ratio of 187% and 30.76:1, respectively. The mutual coupling between the antenna elements is suppressed by placing a T-shaped corrugated strip in the mid of two antenna elements. The proposed MIMO antenna exhibits maximum diversity gain of 10 dB, low mutual coupling (<−20 dB), low envelope correlation coefficient (ECC < 0.02), efficiency >80%, and low reflection coefficient (<−10 dB) in the SWB frequency range (1.30 GH–40 GHz). The presented antenna is a good candidate for SWB applications. The designed antenna has been experimentally validated, and the simulated results were also verified.
      Citation: Electronics
      PubDate: 2020-01-20
      DOI: 10.3390/electronics9010194
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 195: Area-Efficient Error Detection Structure
           for Linear Feedback Shift Registers

    • Authors: Hwasoo Shin, Soyeon Choi, Jiwoon Park, Byeong Yong Kong, Hoyoung Yoo
      First page: 195
      Abstract: This paper presents a novel error detection linear feedback shift register (ED-LFSR), which can be used to realize error detection with a small hardware overhead for various applications such as error-correction codes, encryption algorithms and pseudo-random number generation. Although the traditional redundancy methods allow the incorporation of the error detection/correction capability in the original LFSRs, they suffer from a considerable amount of hardware overheads. The proposed ED-LFSR alleviates such problems by employing the parity check technique. The experimental results indicate that the proposed ED-LFSR requires an additional area of only 31.1% compared to that required by the conventional LFSR and it saves 39.1% and 31.9% of the resources compared to the corresponding utilization of the hardware and time redundancy methods.
      Citation: Electronics
      PubDate: 2020-01-20
      DOI: 10.3390/electronics9010195
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 196: Spatiotemporal Feature Learning Based
           Hour-Ahead Load Forecasting for Energy Internet

    • Authors: Liufeng Du, Linghua Zhang, Xu Wang
      First page: 196
      Abstract: In this paper, we analyze the characteristics of the load forecasting task in the Energy Internet context and the deficiencies of existing methods and then propose a data driven approach for one-hour-ahead load forecasting based on the deep learning paradigm. The proposed scheme involves three aspects. First, we formulate a historical load matrix (HLM) with spatiotemporal correlation combined with the EI scenario and then create a three-dimensional historical load tensor (HLT) that contains the HLMs for multiple consecutive time points before the forecasted hour. Second, we preprocess the HLT leveraging a novel low rank decomposition algorithm and different load gradients, aiming to provide a forecasting model with richer input data. Third, we develop a deep forecasting framework (called the 3D CNN-GRU) featuring a feature learning module followed by a regression module, in which the 3D convolutional neural network (3D CNN) is used to extract the desired feature sequences with time attributes, while the gated recurrent unit (GRU) is responsible for mapping the sequences to the forecast values. By feeding the corresponding load label into the 3D CNN-GRU, our proposed scheme can carry out forecasting tasks for any zone covered by the HLM. The results of self-evaluation and a comparison with several state-of-the-art methods demonstrate the superiority of the proposed scheme.
      Citation: Electronics
      PubDate: 2020-01-20
      DOI: 10.3390/electronics9010196
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 197: From Hotel Reviews to City Similarities: A
           Unified Latent-Space Model

    • Authors: Luca Cagliero, Moreno La Quatra, Daniele Apiletti
      First page: 197
      Abstract: A large portion of user-generated content published on the Web consists of opinions and reviews on products, services, and places in textual form. Many travellers and tourists routinely rely on such content to drive their choices, shaping trips and visits to any place on earth, and specifically to select hotels in large cities. In the context of hospitality management, a challenging research problem is to identify effective strategies to explain hotel reviews and ratings and their correlation with the urban context. Under this umbrella, the paper investigates the use of sentence-based embedding models to deeply explore the similarities and dissimilarities between cities in terms of the corresponding hotel reviews and the surrounding points of interests. Reviews and point of interest (POI) descriptions are jointly modelled in a unified latent space, allowing us to deeply investigate the dependencies between guest feedbacks and the hotel neighborhood at different aggregation levels. The experiments performed on public TripAdvisor hotel-review datasets confirm the applicability and effectiveness of the proposed approach.
      Citation: Electronics
      PubDate: 2020-01-20
      DOI: 10.3390/electronics9010197
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 198: Real-Time Image Stabilization Method Based
           on Optical Flow and Binary Point Feature Matching

    • Authors: Deng, Yang, Zhang, Dong, Liu, Shen
      First page: 198
      Abstract: The strap-down missile-borne image guidance system can be easily affected by the unwanted jitters of the motion of the camera, and the subsequent recognition and tracking functions are also influenced, thus severely affecting the navigation accuracy of the image guidance system. So, a real-time image stabilization technology is needed to help improve the image quality of the image guidance system. To satisfy the real-time and accuracy requirements of image stabilization in the strap-down missile-borne image guidance system, an image stabilization method based on optical flow and image matching with binary feature descriptors is proposed. The global motion of consecutive frames is estimated by the pyramid Lucas-Kanade (LK) optical flow algorithm, and the interval frames image matching based on fast retina keypoint (FREAK) algorithm is used to reduce the cumulative trajectory error. A Kalman filter is designed to smooth the trajectory, which is conducive to fitting to the main motion of the guidance system. Simulations have been carried out, and the results show that the proposed algorithm improves the accuracy and real-time performance simultaneously compared to the state-of-art algorithms.
      Citation: Electronics
      PubDate: 2020-01-20
      DOI: 10.3390/electronics9010198
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 199: A Power-Efficient Pipelined ADC with an
           Inherent Linear 1-Bit Flip-Around DAC

    • Authors: Wan, Su, Zhang, Chen
      First page: 199
      Abstract: An unity-gain 1-bit flip-around digital-to-analog converter (FADAC), without any capacitor matching issue, is proposed as the front-end input stage in a pipelined analog-to-digital converter (ADC), allowing an input signal voltage swing up to be doubled. This large input swing, coupled with the inherent large feedback factor (ideally β = 1) of the proposed FADAC, enables a power-efficient low-voltage high-resolution pipelined ADC design. The 1-bit FADAC is exploited in a SHA-less and opamp-sharing pipelined ADC, exhibiting 12-bit resolution with an input swing of 1.8 Vpp under a 1.1 V power supply. Fabricated in a 0.13-μm CMOS process, the prototype ADC achieves a measured signal-to-noise plus distortion ratio (SNDR) of 66.4 dB and a spurious-free dynamic range (SFDR) of 76.7 dB at 20 MS/s sampling rate. The ADC dissipates 5.2 mW of power and occupies an active area of 0.44 mm2. The measured differential nonlinearity (DNL) is +0.72/−0.52 least significant bit (LSB) and integral nonlinearity (INL) is +0.84/−0.75 LSB at a 3-MHz sinusoidal input.
      Citation: Electronics
      PubDate: 2020-01-20
      DOI: 10.3390/electronics9010199
      Issue No: Vol. 9, No. 1 (2020)
  • Electronics, Vol. 9, Pages 200: Impact of Laser Attacks on the Switching
           Behavior of RRAM Devices

    • Authors: Arumí, Manich, Gómez-Pau, Rodríguez-Montañés, Montilla, Hernández, González, Campabadal
      First page: 200
      Abstract: The ubiquitous use of critical and private data in electronic format requires reliable and secure embedded systems for IoT devices. In this context, RRAMs (Resistive Random Access Memories) arises as a promising alternative to replace current memory technologies. However, their suitability for this kind of application, where the integrity of the data is crucial, is still under study. Among the different typology of attacks to recover information of secret data, laser attack is one of the most common due to its simplicity. Some preliminary works have already addressed the influence of laser tests on RRAM devices. Nevertheless, the results are not conclusive since different responses have been reported depending on the circuit under testing and the features of the test. In this paper, we have conducted laser tests on individual RRAM devices. For the set of experiments conducted, the devices did not show faulty behaviors. These results contribute to the characterization of RRAMs and, together with the rest of related works, are expected to pave the way for the development of suitable countermeasures against external attacks.
      Citation: Electronics
      PubDate: 2020-01-20
      DOI: 10.3390/electronics9010200
      Issue No: Vol. 9, No. 1 (2020)
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