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  Subjects -> ELECTRONICS (Total: 202 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: 99)
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  
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  
Batteries     Open Access   (Followers: 9)
Batteries & Supercaps     Hybrid Journal   (Followers: 4)
Bell Labs Technical Journal     Hybrid Journal   (Followers: 31)
Bioelectronics in Medicine     Hybrid Journal  
Biomedical Instrumentation & Technology     Hybrid Journal   (Followers: 6)
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: 304)
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: 108)
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  
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)
IACR Transactions on Symmetric Cryptology     Open Access   (Followers: 1)
IEEE Antennas and Propagation Magazine     Hybrid Journal   (Followers: 100)
IEEE Antennas and Wireless Propagation Letters     Hybrid Journal   (Followers: 81)
IEEE Embedded Systems Letters     Hybrid Journal   (Followers: 56)
IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology     Hybrid Journal   (Followers: 2)
IEEE Journal of Emerging and Selected Topics in Power Electronics     Hybrid Journal   (Followers: 52)
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 Letters on Electromagnetic Compatibility Practice and Applications     Hybrid Journal   (Followers: 3)
IEEE Magnetics Letters     Hybrid Journal   (Followers: 7)
IEEE Nanotechnology Magazine     Hybrid Journal   (Followers: 42)
IEEE Open Journal of Circuits and Systems     Open Access   (Followers: 2)
IEEE Open Journal of Industry Applications     Open Access   (Followers: 2)
IEEE Open Journal of the Industrial Electronics Society     Open Access   (Followers: 2)
IEEE Power Electronics Magazine     Full-text available via subscription   (Followers: 77)
IEEE Pulse     Hybrid Journal   (Followers: 5)
IEEE Reviews in Biomedical Engineering     Hybrid Journal   (Followers: 22)
IEEE Solid-State Circuits Letters     Hybrid Journal   (Followers: 2)
IEEE Solid-State Circuits Magazine     Hybrid Journal   (Followers: 13)
IEEE Transactions on Aerospace and Electronic Systems     Hybrid Journal   (Followers: 364)
IEEE Transactions on Antennas and Propagation     Full-text available via subscription   (Followers: 74)
IEEE Transactions on Automatic Control     Hybrid Journal   (Followers: 59)
IEEE Transactions on Autonomous Mental Development     Hybrid Journal   (Followers: 8)
IEEE Transactions on Biomedical Engineering     Hybrid Journal   (Followers: 38)
IEEE Transactions on Broadcasting     Hybrid Journal   (Followers: 13)
IEEE Transactions on Circuits and Systems for Video Technology     Hybrid Journal   (Followers: 26)
IEEE Transactions on Consumer Electronics     Hybrid Journal   (Followers: 45)
IEEE Transactions on Electron Devices     Hybrid Journal   (Followers: 19)
IEEE Transactions on Geoscience and Remote Sensing     Hybrid Journal   (Followers: 221)
IEEE Transactions on Haptics     Hybrid Journal   (Followers: 4)
IEEE Transactions on Industrial Electronics     Hybrid Journal   (Followers: 76)
IEEE Transactions on Industry Applications     Hybrid Journal   (Followers: 40)
IEEE Transactions on Information Theory     Hybrid Journal   (Followers: 27)
IEEE Transactions on Learning Technologies     Full-text available via subscription   (Followers: 12)
IEEE Transactions on Power Electronics     Hybrid Journal   (Followers: 79)
IEEE Transactions on Services Computing     Hybrid Journal   (Followers: 4)
IEEE Transactions on Signal and Information Processing over Networks     Hybrid Journal   (Followers: 14)
IEEE Transactions on Software Engineering     Hybrid Journal   (Followers: 79)
IEEE Women in Engineering Magazine     Hybrid Journal   (Followers: 11)
IEEE/OSA Journal of Optical Communications and Networking     Hybrid Journal   (Followers: 16)
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: 59)
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 Technology Research Journal Phranakhon Rajabhat University     Open Access  
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: 37)
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   (Followers: 1)
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: 181)
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   (Followers: 1)
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: 31)
Journal of Power Electronics     Hybrid Journal   (Followers: 1)
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  
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, 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)
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)
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)
Solid State Electronics Letters     Open Access  
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)

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Similar Journals
Journal Cover
Journal of Sensors
Journal Prestige (SJR): 0.288
Citation Impact (citeScore): 1
Number of Followers: 26  

  This is an Open Access Journal Open Access journal
ISSN (Print) 1687-725X - ISSN (Online) 1687-7268
Published by Hindawi Homepage  [342 journals]
  • Vehicle Detection and Ranging Using Two Different Focal Length Cameras

    • Abstract: Vehicle detection is a crucial task for autonomous driving and demands high accuracy and real-time speed. Considering that the current deep learning object detection model size is too large to be deployed on the vehicle, this paper introduces the lightweight network to modify the feature extraction layer of YOLOv3 and improve the remaining convolution structure, and the improved Lightweight YOLO network reduces the number of network parameters to a quarter. Then, the license plate is detected to calculate the actual vehicle width and the distance between the vehicles is estimated by the width. This paper proposes a detection and ranging fusion method based on two different focal length cameras to solve the problem of difficult detection and low accuracy caused by a small license plate when the distance is far away. The experimental results show that the average precision and recall of the Lightweight YOLO trained on the self-built dataset is 4.43% and 3.54% lower than YOLOv3, respectively, but the computing speed of the network decreases 49 ms per frame. The road experiments in different scenes also show that the long and short focal length camera fusion ranging method dramatically improves the accuracy and stability of ranging. The mean error of ranging results is less than 4%, and the range of stable ranging can reach 100 m. The proposed method can realize real-time vehicle detection and ranging on the on-board embedded platform Jetson Xavier, which satisfies the requirements of automatic driving environment perception.
      PubDate: Fri, 20 Mar 2020 08:50:11 +000
  • Quantitative Nondestructive Testing of Broken Wires for Wire Rope Based on
           Magnetic and Infrared Information

    • Abstract: The lifetime of wire rope is crucial in industry manufacturing, mining, and so on. The damage can be detected by using appropriate nondestructive testing techniques or destructive tests by cutting the part. For broken wires classification problems, this work is aimed at improving the recognition accuracy. Facing the defects at the exterior of the rope, a novel method for recognition of broken wires is firstly developed based on magnetic and infrared information fusion. A denoising method, which is adopted for magnetic signal, is proposed for eliminating baseline signal and wave strand. An image segmentation method is employed for parting the defects of infrared images. Characteristic vectors are extracted from magnetic images and infrared images, then kernel extreme learning machine network is applied to implement recognition of broken wires. Experimental results show that the denoising method and image segmentation are effective and the information fusion can improve the classification accuracy, which can provide useful information for estimating the residual lifetime of wire rope.
      PubDate: Wed, 11 Mar 2020 13:05:06 +000
  • Using AI-Based Classification Techniques to Process EEG Data Collected
           during the Visual Short-Term Memory Assessment

    • Abstract: Visual short-term memory (VSTM) is defined as the ability to remember a small amount of visual information, such as colors and shapes, during a short period of time. VSTM is a part of short-term memory, which can hold information up to 30 seconds. In this paper, we present the results of research where we classified the data gathered by using an electroencephalogram (EEG) during a VSTM experiment. The experiment was performed with 12 participants that were required to remember as many details as possible from the two images, displayed for 1 minute. The first assessment was done in an isolated environment, while the second assessment was done in front of the other participants, in order to increase the stress of the examinee. The classification of the EEG data was done by using four algorithms: Naive Bayes, support vector, KNN, and random forest. The results obtained show that AI-based classification could be successfully used in the proposed way, since we were able to correctly classify the order of the images presented 90.12% of the time and type of the displayed image 90.51% of the time.
      PubDate: Mon, 09 Mar 2020 13:50:07 +000
  • Theoretical Comparison between the Flicker Noise Behavior of Graphene and
           of Ordinary Semiconductors

    • Abstract: Graphene is a material of particular interest for the implementation of sensors, and the ultimate performance of devices based on such a material is often determined by its flicker noise properties. Indeed, graphene exhibits, with respect to the vast majority of ordinary semiconductors, a peculiar behavior of the flicker noise power spectral density as a function of the charge carrier density. While in most materials flicker noise obeys the empirical Hooge law, with a power spectral density inversely proportional to the number of free charge carriers, in bilayer, and sometimes monolayer, graphene a counterintuitive behavior, with a minimum of flicker noise at the charge neutrality point, has been observed. We present an explanation for this stark difference, exploiting a model in which we enforce both the mass action law and the neutrality condition on the charge fluctuations deriving from trapping/detrapping phenomena. Here, in particular, we focus on the comparison between graphene and other semiconducting materials, concluding that a minimum of flicker noise at the charge neutrality point can appear only in the presence of a symmetric electron-hole behavior, a condition characteristic of graphene, but which is not found in the other commonly used semiconductors.
      PubDate: Mon, 09 Mar 2020 09:05:03 +000
  • Response Mechanism of Cotton Growth to Water and Nutrients under Drip
           Irrigation with Plastic Mulch in Southern Xinjiang

    • Abstract: The effects of water and nutrient control measures on the cotton plant height, stem diameter, biomass, seed yield, and soil moisture under an irrigated plastic mulch production system were studied. Using field experiments in the 2018 cotton-growing season, 6 fertilization treatments (30-10.5-4.5 (N-P2O5-K2O), 24-8.4-3.6 (N-P2O5-K2O), 20-7-3 (N-P2O5-K2O), 16-5.6-2.4 (N-P2O5-K2O), 10-3.5-1.5 (N-P2O5-K2O), and 0-0-0 (N-P2O5-K2O) kg/mu) and 6 deficit irrigation treatments (40% PET, 60% PET, and 80% PET) were established at the cotton budding and flowering stages. Analysis of variance (ANOVA) () was used to evaluate the significant differences among the treatments. The results showed that the effects of the water and nutrient control measures were obvious. The irrigation water use efficiency (IWUE) was the highest under the 80% deficit irrigation (T7) treatment at the flowering stage (2.62 kg/m3). Increases in cotton plant height and stem diameter were promoted by mild or moderate deficit irrigation at the flowering stage, but normal growth and development were affected by severe deficit irrigation at any growth stage. The growth indexes of cotton increased with increasing fertilization, but significant differences between each fertilization gradient were not obvious. At the same time, excessive fertilization not only had a positive effect on the LAI (leaf area index) and yield but also caused fertilizer waste and unnecessary cotton growth. The cotton seed yield and single boll yield reached their highest values (566 kg/mu) under the 1.2 times fertilizer treatment (T9), but the 0.8 times fertilizer treatment had the highest IWUE among the nutrient control treatments (1.91 kg/m3). Therefore, it is suggested that deficit irrigation at 60~80% of the potential evapotranspiration (PET) at the flowering stage and 16-5.6-2.4 (N-P2O5-K2O) fertilizer be applied as an optimal water and nutrient management strategy to maximize the seed cotton yield, IWUE, and overall growth and development of cotton.
      PubDate: Sat, 07 Mar 2020 07:35:04 +000
  • Real-Time Nonlinear Characterization of Soft Tissue Mechanical Properties

    • Abstract: Online soft tissue characterization is important for robotic-assisted minimally invasive surgery to achieve precise and stable robotic control with haptic feedback. This paper presents a new nonlinear recursive adaptive filtering methodology for online nonlinear soft tissue characterization. An adaptive unscented Kalman filter is developed based on the Hunt-Crossley model by windowing approximation to online estimate system and measurement noise covariances. To improve the accuracy of noise covariance estimations, a recursive formulation is subsequently developed for estimation of system and measurement noise covariances by introducing a weighting factor. This weighting factor is further modified to accommodate noise statistics of large variation which could be caused by rupture events and geometric discontinuities in robotic-assisted surgery. Simulations, experiments, and comparison analyses demonstrate that the proposed nonlinear recursive adaptive filtering methodology can characterize soft tissue parameters in the presence of system or measurement noise statistics in both small and large variations for robotic-assisted surgery. The proposed methodology can effectively estimate soft tissue parameters under system and measurement noises in both small and large variations, leading to improved filtering accuracy and robustness in comparison with UKF.
      PubDate: Wed, 04 Mar 2020 08:20:01 +000
  • Design and Development of Weigh-In-Motion Using Vehicular Telematics

    • Abstract: Identifying overloaded vehicles on a highway is essential for the safety of vehicles on the road as well as for the performance monitoring of highway infrastructure and planning. Traffic enforcement uses various weigh-in-motion (WIM) methods. Since Vehicular Telematics (VT) is favoured in the transport industry, using it for building a new WIM system to infer the payload of a vehicle at any road segment would be beneficial for the transport industry. This paper presents the effort taken to use VT data from onboard diagnostics modules and smartphones to infer the payload of a vehicle. The experiment done to find the correlation between VT data and the payload of a vehicle is discussed. Feature engineering was done; nine different settings were tested to find the best regression model. A multiple nonlinear regression model produced significant a value of 6.322-08 and an -squared value of 0.8736. Results support the notion of using the VT data for nonintrusive measurement of the weight of a vehicle in motion.
      PubDate: Wed, 04 Mar 2020 07:20:01 +000
  • Fringing Field Capacitive Smart Sensor Based on PCB Technology for
           Measuring Water Content in Paper Pulp

    • Abstract: We present a capacitive smart sensor based on printed circuit board (PCB) technology to measure the amount of water content in a paper pulp at the wet end of a paper machine. The developed sensor incorporates in the same PCB the signal processing circuits. It is a handheld portable device, and its output is sent to the reading equipment using a Bluetooth wireless connection, providing to the sensor’s operator ease of mobility around the wet end of a paper machine. The prototype was tested in a laboratory, using a wire mesh to emulate the end of a paper machine, and we were able to measure and easily detect when it reaches the water content in the range of 90% to 92%, as required in the paper fabrication process. Standard deviation of the capacitance measurements at various moisture levels is four orders of magnitude smaller than the mean. The smart sensor was tested in the 20°C to 40°C temperature range, in a paper pulp with a gravimetric water content of 91%. Since the variation of capacitance with temperature is practically linear, we propose a simple linear compensation equation to correct the observed sensitivity with the temperature. To keep the signal processing circuits small, low cost, simple, and robust, a novel direct interface sensor to microcontroller circuit technique was used to make the capacitive measurement, allowing for measuring small capacitance deviations without high-frequency oscillators. It was shown that it is possible to integrate the signal processing circuits in the top layer of the PCB interdigitated sensor without adding noise or degrading the performance of the capacitive sensor.
      PubDate: Wed, 04 Mar 2020 07:20:00 +000
  • An Optimal Backoff Time-Based Internetwork Interference Mitigation Method
           in Wireless Body Area Network

    • Abstract: When multiple Wireless Body Area Networks (WBANs) are aggregated, the overlapping region of their communications will result in internetwork interference, which could impose severe impacts on the reliability of WBAN performance. Therefore, how to mitigate the internetwork interference becomes the key problem to be solved urgently in practical applications of WBAN. However, most of the current researches on internetwork interference focus on traditional cellular networks and large-scale wireless sensor networks. In this paper, an Optimal Backoff Time Interference Mitigation Algorithm (OBTIM) is proposed. This method performs rescheduling or channel switching when the performance of the WBANs falls below tolerance, utilizing the cell neighbour list established by the beacon method. Simulation results show that the proposed method improves the channel utilization and the network throughput, and in the meantime, reduces the collision probability and energy consumption, when compared with the contention-based beacon schedule scheme.
      PubDate: Mon, 02 Mar 2020 04:05:01 +000
  • Self-Excited Codirectionally Magnetically Compensated Rotating Ranging

    • Abstract: During the Steam-Assisted Gravity Drainage (SAGD) technology-based dual horizontal well drilling process, it is necessary to accurately monitor the well spacing in real time to ensure safe and parallel drilling. In this paper, a self-excited codirectionally magnetically compensated rotating ranging method and device is proposed. In the numerical calculation and simulation, both parallel and nonparallel drilling models are established. Based on the models and the magnetic dipole theory, the relation between the magnetization field and the well spacing is analyzed. Furthermore, the one-to-one correspondence between the peak-to-peak value of the magnetization field and the well spacing is revealed. Well spacing is then determined according to the measured peak-to-peak value. To achieve better results, the influence of magnetic source (the magnetic moment) and casing characteristics (magnetic susceptibility, dynamic magnetization length) on measured peak-to-peak value is analyzed. Finally, field tests are carried out, and the feasibility and effectiveness of the theory and device are proved. This study provides innovation for a new approach of magnetic guidance while drilling and has a great significance in the development, testing, and calibration of well-ranging instruments.
      PubDate: Sun, 01 Mar 2020 00:20:12 +000
  • Target Recognition of Synthetic Aperture Radar Images Based on Two-Phase
           Sparse Representation

    • Abstract: A synthetic aperture radar (SAR) target recognition method is proposed via linear representation over the global and local dictionaries. The collaborative representation is performed on the local dictionary, which comprises of training samples from a single class. Then, the reconstruction errors as for representing the test sample reflect the absolute representation capabilities of different training classes. Accordingly, the target label can be directly decided when one class achieves a notably lower reconstruction error than the others. Otherwise, several candidate classes with relatively low reconstruction errors are selected as the candidate classes to form the global dictionary, based on which the sparse representation-based classification (SRC) is performed. SRC also produces the reconstruction errors of the candidate classes, which reflect their relative representation capabilities for the test sample. As a comprehensive consideration, the reconstruction errors from the collaborative representation and SRC are fused for decision-making. Therefore, the proposed method could inherit the high efficiency of the collaborative representation. In addition, the selection of the candidate training classes also relieves the computational burden during SRC. By combining the absolute and relative representation capabilities, the final classification accuracy can also be improved. During the experimental evaluation, the Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset is employed to test the proposed method under several different operating conditions. The proposed method is compared with some other SAR target recognition methods simultaneously. The results show the superior performance of the proposed method.
      PubDate: Fri, 28 Feb 2020 16:35:20 +000
  • Performance of Tightly Coupled Integration of GPS/BDS/MEMS-INS/Odometer
           for Real-Time High-Precision Vehicle Positioning in Urban Degraded and
           Denied Environment

    • Abstract: Global Navigation Satellite System Real-Time Kinematic (GNSS-RTK) technology is widely used in vehicle navigation, but in complex environments such as urban high-rise street, wooded street, overpass, and tunnel, satellite signals are prone to attenuation or even unavailability. It brings great challenges to the continuous high-precision navigation. For this reason, a tightly coupled (TC) integration algorithm for GPS (Global Positioning System)/BDS (BeiDou Navigation Satellite System)/MEMS-INS (Micro-Electro-Mechanical System-Inertial Navigation System)/Odometer (GCIO) is proposed for vehicle navigation in complex urban environments. The accuracy improvement and ambiguity resolution (AR) performance are analysed in this research. First of all, the INS positioning error is constrained by fusion GPS/BDS (GC) and odometer; then, the predicted position information is used to aid GPS/BDS ambiguity resolution. In GNSS-denied environments, the odometer/INS integration is still carried out for continuous navigation. Real-time experiments are carried out in urban degraded and denied environments to validate the performance of the integrated system. In high-rise streets, the ambiguity fixing success rate of GCIO mode is 13.57% higher than that of GC mode. In the wooded street environment, the success rate has increased particularly significantly, by about 55 percent. The positioning accuracy analysis for open environment, high-rise street, wooded street, overpass, and tunnel is conducted. The experimental results show that in the above environment, the order of 0.1 m positioning accuracy can be achieved in the case of satellite outage for 1 minute, which can meet the positioning needs in most scenarios.
      PubDate: Fri, 28 Feb 2020 16:35:19 +000
  • Application of Low-Cost Sensors for the Development of a Methodology to
           Design Front-End Loaders for Tractors

    • Abstract: Tractor front-end loaders are an essential part of the equipment used on farms. At present, there are an important number of small- and medium-sized companies involved in the manufacturing of this equipment. These companies rely heavily on experience for innovative designs, as in the vast majority of cases they lack access to adequate methodology for the optimal design of new front-end loaders. The study conducted has developed a methodology to design tractor front-end loaders with a view of obtaining their accurate design during the bucket loading process. The methodology comprises two phases: the first phase involves a numerical analysis of the structural behaviour of the front-end loader components by means of the Finite Element Method; the second phase, the experimental phase, makes use of low-cost sensors, in particular, strain gauges, to analyse existing strains at selected points in the front-end loader structure. The experimental results obtained by means of low-cost sensors fitted onto the front-end loader allow analysing the existing strains at the points measured, as well as validate the numerical model developed. This methodology is validated by applying it to a commercial front-end loader, more specifically to model 430E2 of the company Maquinaria Agrícola El León S.A (Spain).
      PubDate: Fri, 28 Feb 2020 11:20:11 +000
  • Passive Target Localization Problem Based on Improved Hybrid Adaptive
           Differential Evolution and Nelder-Mead Algorithm

    • Abstract: This paper considers a passive target localization problem in Wireless Sensor Networks (WSNs) using the noisy time of arrival (TOA) measurements, obtained from multiple receivers and a single transmitter. The objective function is formulated as a maximum likelihood (ML) estimation problem under the Gaussian noise assumption. Consequently, the objective function of the ML estimator is a highly nonlinear and nonconvex function, where conventional optimization methods are not suitable for this type of problem. Hence, an improved algorithm based on the hybridization of an adaptive differential evolution (ADE) and Nelder-Mead (NM) algorithms, named HADENM, is proposed to find the estimated position of a passive target. In this paper, the control parameters of the ADE algorithm are adaptively updated during the evolution process. In addition, an adaptive adjustment parameter is designed to provide a balance between the global exploration and the local exploitation abilities. Furthermore, the exploitation is strengthened using the NM method by improving the accuracy of the best solution obtained from the ADE algorithm. Statistical analysis has been conducted, to evaluate the benefits of the proposed modifications on the optimization performance of the HADENM algorithm. The comparison results between HADENM algorithm and its versions indicate that the modifications proposed in this paper can improve the overall optimization performance. Furthermore, the simulation shows that the proposed HADENM algorithm can attain the Cramer-Rao lower bound (CRLB) and outperforms the constrained weighted least squares (CWLS) and differential evolution (DE) algorithms. The obtained results demonstrate the high accuracy and robustness of the proposed algorithm for solving the passive target localization problem for a wide range of measurement noise levels.
      PubDate: Thu, 27 Feb 2020 09:35:10 +000
  • Change Analysis of Spring Vegetation Green-Up Date in Qinba Mountains
           under the Support of Spatiotemporal Data Cube

    • Abstract: In recent decades, global and local vegetation phenology has undergone significant changes due to the combination of climate change and human activities. Current researches have revealed the temporal and spatial distribution of vegetation phenology in large scale by using remote sensing data. However, researches on spatiotemporal differentiation of remote sensing phenology and its changes are limited which involves high-dimensional data processing and analysing. A new data model based on data cube technologies was proposed in the paper to efficiently organize remote sensing phenology and related reanalysis data in different scales. The multidimensional aggregation functions in the data cube promote the rapid discovery of the spatiotemporal differentiation of phenology. The exploratory analysis methods were extended to the data cube to mine the change characteristics of the long-term phenology and its influencing factors. Based on this method, the case study explored that the spring phenology of Qinba Mountains has a strong dependence on the topography, and the temperature plays a leading role in the vegetation green-up date distribution of the high-altitude areas while human activities dominate the low-altitude areas. The response of green-up trend slope seems to be the most sensitive at an altitude of about 2000 meters. This research provided a new approach for analysing phenology phenomena and its changes in Qinba Mountains that had the same reference value for other regional phenology studies.
      PubDate: Thu, 27 Feb 2020 09:35:08 +000
  • Efficient Routing Approach Using a Collaborative Strategy

    • Abstract: Wireless sensor networks (WSNs) are a huge number of sensors, which are distributed in area monitoring to collect important signals. WSNs are widely used in several applications such as home automation, environment, and healthcare monitoring. However, most of these applications face various difficulties due to sensor design. Therefore, the major challenge of designing WSNs is saving the energy consumed during communication and extending the network lifetime. Multicriteria Decision Analysis (MCDA) methods have been exploited for saving network energy. However, the majority of researches focus on the Cluster Head (CH) selection. In this paper, we aim to enhance the process of forwarder selection using an efficient combined multicriteria model. The proposed scheme improved the intercluster communication by controlling the distance separating CHs from the sink node. To minimize the cluster density, this work consists of activating only sensor nodes that detect enough strong signals. The activation phase presents a fault-tolerant technique to succeed in the communication process. Moreover, the proposed work is aimed at selecting the most efficient hops, which are responsible for routing data to the sink using the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods. Simulation results proved that our new protocol maximized the residual energy by 15% and 25% and the network lifetime by 35% and 47% compared to the Distributed Clustering Protocol using Voting and Priority (DCPVP) and Low-Energy Adaptive Clustering Hierarchy (LEACH), respectively.
      PubDate: Tue, 25 Feb 2020 16:05:07 +000
  • Variation Characteristics of Stem Water Content in Lagerstroemia indica
           and Its Response to Environmental Factors

    • Abstract: To achieve a rational allocation of limited water resources, and formulation of an appropriate irrigation system, this research studied the change characteristics of stem water content (StWC) in plant and its response to environmental factors. In this study, the StWC and environmental factors of Lagerstroemia indica in Beijing were continuously observed by a BD-IV plant stem water content sensor and a forest microclimate monitoring station from 2017 to 2018. The variation of StWC and its correlation with environmental factors were analyzed. The results showed that the StWC of Lagerstroemia indica varies regularly day and night during the growth cycle. Meanwhile, the rising time, valley time, and falling time of StWC were various at the different growth stages of Lagerstroemia indica. The results of correlation analysis between StWC and environmental factors indicated that the StWC of Lagerstroemia indica was positively correlated with air relative humidity, while it was negatively correlated with total radiation and air temperature. The multiple regression equation of StWC and environmental factors of Lagerstroemia indica was , and the coefficient of determination of the equation was of 0.87. Furthermore, the results illustrated that the irrigation should pay attention to supplementing irrigation in time during the peak growing season of fruit.
      PubDate: Tue, 25 Feb 2020 16:05:05 +000
  • Edge Computing-Enabled Wireless Sensor Networks for Multiple Data
           Collection Tasks in Smart Agriculture

    • Abstract: At present, precision agriculture and smart agriculture are the hot topics, which are based on the efficient data collection by using wireless sensor networks (WSNs). However, agricultural WSNs are still facing many challenges such as multitasks, data quality, and latency. In this paper, we propose an efficient solution for multiple data collection tasks exploiting edge computing-enabled wireless sensor networks in smart agriculture. First, a novel data collection framework is presented by merging WSN and edge computing. Second, the data collection process is modeled, including a plurality of sensors and tasks. Next, according to each specific task and correlation between task and sensors, on the edge computing server, a double selecting strategy is established to determine the best node and sensor network that fulfills quality of data and data collection time constraints of tasks. Furthermore, a data collection algorithm is designed, based on set values for quality of data. Finally, a simulation environment is constructed where the proposed strategy is applied, and results are analyzed and compared to the traditional methods. According to the comparison results, the proposal outperforms the traditional methods in metrics.
      PubDate: Tue, 25 Feb 2020 07:50:03 +000
  • Wireless Photoplethysmography Sensor for Continuous Blood Pressure
           Biosignal Shape Acquisition

    • Abstract: Blood pressure assessment plays a vital role in day-to-day clinical diagnosis procedures as well as personal monitoring. Thus, blood pressure monitoring devices must afford convenience and be easy to use with no side effects on the user. This paper presents a compact, economical, power-efficient, and convenient wireless plethysmography sensor for real-time blood pressure biosignal monitoring. The proposed sensor facilitates blood pressure signal shape sensing, signal conditioning, and data conversion as well as its wireless transmission to a monitoring terminal. Received data can, subsequently, be compiled and stored on a computer via a Wi-Fi module. During monitoring, users can observe blood pressure signals being processed and displayed on the graphical user interface (GUI)—developed using a virtual instrumentation (VI) application. The proposed device comprises a finger clip optical pulse sensor, analogue signal preprocessing, microcontroller, and Wi-Fi module. It consumes approximately 500 mW power when operating in the active mode and synthesized using commercial off-the-shelf (COTS) components. Experimental results reveal that the proposed device is reliable and facilitates efficient blood pressure monitoring. The proposed wireless photoplethysmographic (PPG) sensor is a preliminary (or first) version of the intended device manifestation. It provides raw blood pressure data for further classification. Additionally, the collected data concerning the blood pressure wave shape can be easily analysed for use in other biosignal observations, interpretations, and investigations. The design approach also allows the device to be built into a wearable system for further research purposes.
      PubDate: Mon, 24 Feb 2020 08:05:09 +000
  • Efficient Coverage Hole Detection Algorithm Based on the Simplified Rips
           Complex in Wireless Sensor Networks

    • Abstract: The appearance of coverage holes in the network leads to transmission links being disconnected, thereby resulting in decreasing the accuracy of data. Timely detection of the coverage holes can effectively improve the quality of network service. Compared with other coverage hole detection algorithms, the algorithms based on the Rips complex have advantages of high detection accuracy without node location information, but with high complexity. This paper proposes an efficient coverage hole detection algorithm based on the simplified Rips complex to solve the problem of high complexity. First, Turan’s theorem is combined with the concept of the degree and clustering coefficient in a complex network to classify the nodes; furthermore, redundant node determination rules are designed to sleep redundant nodes. Second, according to the concept of the complete graph, redundant edge deletion rules are designed to delete redundant edges. On the basis of the above two steps, the Rips complex is simplified efficiently. Finally, from the perspective of the loop, boundary loop filtering and reduction rules are designed to achieve coverage hole detection in wireless sensor networks. Compared with the HBA and tree-based coverage hole detection algorithm, simulation results show that the proposed hole detection algorithm has lower complexity and higher accuracy and the detection accuracy of the hole area is up to 99.03%.
      PubDate: Mon, 24 Feb 2020 06:35:10 +000
  • Improving Packet Delivery Performance in Water Column Variations through
           LOCAN in Underwater Acoustic Sensor Network

    • Abstract: This paper proposes Lion Optimized Cognitive Acoustic Network (LOCAN) to reduce packet delay and packet loss during packet transmission in Underwater Acoustic Sensor Network (UWASN). Packet delay and packet loss in UWASN are because of water column variations such as Doppler effect and geometric spreading (GS). Doppler effect forms due to sensor node’s motion and sea surface variations such as salinity and temperature. Geometric spreading (GS) occurs due to sediment drift wave fronts and frequent changes in node’s location and depth. Water column variations change the amplitude of sound propagation, causing channel coherence and multipath interference, which affect packet transmission. The existing UWASN algorithms focus only on temperature and salinity variations. In LOCAN, channel selection through Lion Optimization Algorithm solves the problems of water column variation and improves the battery life, network lifetime, and throughput. The proposed algorithms show a better result in terms of efficiency, when compared to existing UWASN algorithms.
      PubDate: Thu, 20 Feb 2020 06:20:05 +000
  • Accurate 3D Surface Reconstruction for Smart Farming Application with an
           Inexpensive Shape from Focus System

    • Abstract: In precision agriculture, 3D vision systems are becoming increasingly important. By applying different optical 3D vision techniques, the acquired 3D data can provide information regarding the most important phenotype features in every agricultural scenario. However, most of these 3D vision systems are expensive, except some of the triangulation techniques. In this study, we focus on estimating accurate shapes using shape from focus (SFF), which is a triangulation technique. Typically, the SFF system incurs significant errors from images, including noise. As a solution to this problem, a simple low-pass filter such as the Gaussian filter has generally been used in most studies. However, when a low filter is applied, the noise is depressed but the signals are also blurred, which results in inaccuracies regarding the depth map. In this study, the noise is depressed independently without losing the original signals, and the edge components, which play important roles in finding a focused surface, are enhanced using the independent component analysis (ICA). The edge signals are amplified with a simple basis vector correction in the IC vector space. The experiments are implemented with simulated objects and real objects. The experimental results demonstrate that the obtained accuracy is comparable to that of existing methods.
      PubDate: Wed, 19 Feb 2020 08:05:08 +000
  • Block-Split Array Coding Algorithm for Long-Stream Data Compression

    • Abstract: With the advent of IR (Industrial Revolution) 4.0, the spread of sensors in IoT (Internet of Things) may generate massive data, which will challenge the limited sensor storage and network bandwidth. Hence, the study of big data compression is valuable in the field of sensors. A problem is how to compress the long-stream data efficiently with the finite memory of a sensor. To maintain the performance, traditional techniques of compression have to treat the data streams on a small and incompetent scale, which will reduce the compression ratio. To solve this problem, this paper proposes a block-split coding algorithm named “CZ-Array algorithm,” and implements it in the shareware named “ComZip.” CZ-Array can use a relatively small data window to cover a configurable large scale, which benefits the compression ratio. It is fast with the time complexity O() and fits the big data compression. The experiment results indicate that ComZip with CZ-Array can obtain a better compression ratio than gzip, lz4, bzip2, and p7zip in the multiple stream data compression, and it also has a competent speed among these general data compression software. Besides, CZ-Array is concise and fits the hardware parallel implementation of sensors.
      PubDate: Tue, 18 Feb 2020 05:35:04 +000
  • Dynamic Measurement of Legs Motion in Sagittal Plane Based on Soft
           Wearable Sensors

    • Abstract: Human motion capture is widely used in exoskeleton robots, human-computer interaction, sports analysis, rehabilitation training, and many other fields. However, soft-sensor-based wearable dynamic measurement has not been well achieved. In this paper, the dynamic measurements of legs were investigated by using dielectric elastomers as stain sensors, and an alternating signal was applied to detect the dynamic rotational angles of the legs. To realize a quick response, parameters of the sensors were optimized by circuit analysis. The sensor can detect hip, knee, and ankle joint motions with a sample frequency of 200 Hz. The measurements of the sensors were compared with a commercial motion capture system from PhaseSpace, and dynamic errors between them were smaller than 3° when squatting and walking at low speed and smaller than 5° when walking at high speed. Experiments therefore demonstrate the feasibility of the integrated wearable stretch sensors with pants.
      PubDate: Sat, 15 Feb 2020 14:20:02 +000
  • Feasibility of Using Dynamic Time Warping to Measure Motor States in
           Parkinson’s Disease

    • Abstract: The aim of this paper is to investigate the feasibility of using the Dynamic Time Warping (DTW) method to measure motor states in advanced Parkinson’s disease (PD). Data were collected from 19 PD patients who experimented leg agility motor tests with motion sensors on their ankles once before and multiple times after an administration of 150% of their normal daily dose of medication. Experiments of 22 healthy controls were included. Three movement disorder specialists rated the motor states of the patients according to Treatment Response Scale (TRS) using recorded videos of the experiments. A DTW-based motor state distance score (DDS) was constructed using the acceleration and gyroscope signals collected during leg agility motor tests. Mean DDS showed similar trends to mean TRS scores across the test occasions. Mean DDS was able to differentiate between PD patients at Off and On motor states. DDS was able to classify the motor state changes with good accuracy (82%). The PD patients who showed more response to medication were selected using the TRS scale, and the most related DTW-based features to their TRS scores were investigated. There were individual DTW-based features identified for each patient. In conclusion, the DTW method can provide information about motor states of advanced PD patients which can be used in the development of methods for automatic motor scoring of PD.
      PubDate: Fri, 14 Feb 2020 14:05:01 +000
  • Adjacent Channel Interference Modeling of Single Vibration Point on
           Multichannel Dynamic Pressure Sensors

    • Abstract: Pulse waves of a radial artery under different pressures applied through a cuff play an important role in disease diagnosis, especially in traditional chinese medicine (TCM). Pulse waves could be collected by a pressure sensor array affixed to an inflatable cuff. During a process of collecting pulse waves, one sensor of a sensor array moves up and down when the sensor is shocked by a pulse wave. Movement of the sensor leads to the passive displacement of other nearby sensors because of a connecting structure between them. Then, vibration signals will be generated by the nearby sensors although these sensors do not receive radial artery pulse waves. These vibration signals considered an interference are usually superimposed on real signals obtained from these nearby sensors and degrade signal quality. The problem mentioned above does not only generally exist in a pressure sensor array attached to a wristband but also is easy to ignore. This paper proposes a novel interference suppression algorithm based on Welch’s method for estimating and weakening adjacent sensor channel interference to overcome the problem. At first, a sensor array attached to an inflatable cuff and a vibration generator is proposed to establish an experimental platform for simplifying the pulse wave collection process. Then, the interference suppression algorithm is proposed according to mechanical analysis and Welch’s method based on the proposed sensor array and vibration generator. Next anti-interference abilities of the algorithm based on a simplified process are evaluated by different vibration frequencies and applied pressures. The anti-interference abilities of the algorithm based on pulse waves of the radial artery are evaluated indirectly. The results show that the novel interference suppression algorithm could weaken adjacent sensor channel interference and upgrade the signal quality.
      PubDate: Wed, 12 Feb 2020 09:50:04 +000
  • Characterization of Filamentous Flocs to Predict Sedimentation Parameters
           Using Image Analysis

    • Abstract: In wastewater treatment plants, the degradation of complex substances that contaminate water is carried out by microorganisms, which are fixed by a network formed by filamentous bacteria, creating large flocs that settle easily. However, the excessive growth of said bacteria causes a series of drawbacks such as the reduction of settling velocity, leakage of activated sludge with the effluent, and formation of supernatant, a phenomenon known as bulking. This research work seeks to develop and evaluate a procedure for the physical characterization of the flocs to determine the parameters that affect the settling velocity and thereby detect and control bulking. For this purpose, sedimentation and image analysis tests were carried out from wastewater from the Aguas Antofagasta treatment plant (Chile). The image analysis was performed with images captured from an optical microscope in two magnifications (100x and 50x), which were analyzed by marking each floc individually and characterized by an image processing software. Additionally, sedimentation tests were performed on columns (area of 74 (cm2) and height of 70 (cm)). As a result, an inversely proportional dependence was found on the settling velocity evaluated by the Vesilind equation in the zone of constant fall velocity with respect to the number of flocs connected per cluster, giving an estimate of the settling velocity depending on the number of flocs connected. This would allow predicting settling velocity with image analysis, taking into account that the problem of bulking is determined by the type of filamentous bacteria that causes it and the sedimentation process is affected in large part by local factors. It can be concluded through this study that as the number of flocs connected per cluster increases, the settling velocity decreases. This study provides wastewater treatment plants with a practical tool to determine sedimentation times and thus improve the quality of the treated water, avoiding problems of flocs leaking with the effluent. In addition, the image analysis itself allows rapid detection of the phenomenon of bulking and its severity.
      PubDate: Tue, 11 Feb 2020 10:20:05 +000
  • Sensors Applied for the Detection of Pesticides and Heavy Metals in

    • Abstract: Water is essential for every life living on the planet. However, we are facing a more serious situation such as water pollution since the industrial revolution. Fortunately, many efforts have been done to alleviate/restore water quality in freshwaters. Numerous sensors have been developed to monitor the dynamic change of water quality for ecological, early warning, and protection reasons. In the present review, we briefly introduced the pollution status of two major pollutants, i.e., pesticides and heavy metals, in freshwaters worldwide. Then, we collected data on the sensors applied to detect the two categories of pollutants in freshwaters. Special focuses were given on the sensitivity of sensors indicated by the limit of detection (LOD), sensor types, and applied waterbodies. Our results showed that most of the sensors can be applied for stream and river water. The average LOD was  ng/ml () for all pesticides, which is significantly higher than that for heavy metals ( ng/ml, ). However, the LODs of a considerable part of pesticides and heavy metal sensors were higher than the criterion maximum concentration for aquatic life or the maximum contaminant limit concentration for drinking water. For pesticide sensors, the average LODs did not differ among insecticides ( ng/ml, ), herbicides ( ng/ml, ), and fungicides ( ng/ml, ). The LODs that differed among sensor types with biosensors had the highest sensitivity, while electrochemical optical and biooptical sensors showed the lowest sensitivity. The sensitivity of heavy metal sensors varied among heavy metals and sensor types. Most of the sensors were targeted on lead, cadmium, mercury, and copper using electrochemical methods. These results imply that future development of pesticides and heavy metal sensors should (1) enhance the sensitivity to meet the requirements for the protection of aquatic ecosystems and human health and (2) cover more diverse pesticides and heavy metals especially those toxic pollutants that are widely used and frequently been detected in freshwaters (e.g., glyphosate, fungicides, zinc, chromium, and arsenic).
      PubDate: Tue, 11 Feb 2020 07:50:01 +000
  • Edge Prior Multilayer Segmentation Network Based on Bayesian Framework

    • Abstract: In recent years, methods based on neural network have achieved excellent performance for image segmentation. However, segmentation around the edge area is still unsatisfactory when dealing with complex boundaries. This paper proposes an edge prior semantic segmentation architecture based on Bayesian framework. The entire framework is composed of three network structures, a likelihood network and an edge prior network at the front, followed by a constraint network. The likelihood network produces a rough segmentation result, which is later optimized by edge prior information, including the edge map and the edge distance. For the constraint network, the modified domain transform method is proposed, in which the diffusion direction is revised through the newly defined distance map and some added constraint conditions. Experiments about the proposed approach and several contrastive methods show that our proposed method had good performance and outperformed FCN in terms of average accuracy for 0.0209 on ESAR data set.
      PubDate: Mon, 10 Feb 2020 14:50:06 +000
  • Using Artificial Intelligence Techniques to Improve the Prediction of
           Copper Recovery by Leaching

    • Abstract: Copper mining activity is going through big changes due to increasing technological development in the area and the influence of industry 4.0. These changes, produced by technological context and more controls (e.g., environmental controls), are also becoming visible in Chilean mining. New regulations from the Chilean government and changes in the copper mining industry (such as a trend to underground mining) are fostering the search for better results in typical processes such as leaching. This paper describes an experience using artificial intelligence techniques, particularly random forest, to develop predictive models for copper recovery by leaching, using data from an enterprise present in northern Chile for more than 20 years. Two models, one of them with actual operational data and another one with data generated in a controlled environment (piling) are presented. Well-classified values of 98.90% for operational data and 98.72% for pile/piling data were obtained. The methodology devised for the study can be transferred to piling columns or piles with other characteristics, though the operation must focus on copper leaching. It can even be transferred to other leaching processes using another type of mineral, with proper adjustments.
      PubDate: Fri, 07 Feb 2020 09:50:07 +000
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