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TELKOMNIKA (Telecommunication, Computing, Electronics and Control)
Number of Followers: 2  Open Access journalISSN (Print) 1693-6930 - ISSN (Online) 2302-9293 This journal is no longer being updated because: the publisher no longer provides RSS feeds |
- Planar broadband antenna for 2G/3G systems
Authors: Ashutosh Singh Chauhan; Priyansh Kasyap, Ankit Gupta, Debani Prasad Mishra, Surender Reddy Salkuti, Seong-Cheol Kim
Abstract: A planar antenna with broadband gestalt is presented for mobile networks. The structure of the antenna is made up of a folded dipole pair with an L-figure microstrip coupling line. The microstrip coupling along with the dipoles are attached on the similar substrate. The radiation parts are plotted at 1.7, 2.2 and 2.7 GHz. A flexible coaxial cable made of PEC material is attached to the L-figure microstrip whereas the outside conductor made up of RO4350B material is attached to the coplanar strip of line. The gain of the antenna is almost 9 dBi. The benefit of the planar structure is that it offers a simple feeding structure and compact size that is necessary for 2G/3G/LTE systems. Finally the antenna proposed is designed by using CST Microwave Studio.
PubDate: Wed, 01 Jun 2022 00:00:00 +000
- A Novel Wideband Circularly-Polarized Microstrip Antenna Array Based On
Defected Ground Structure For Wireless Power Transmission
Authors: Fatima OUBERRI; Abdelali Tajmouati, Noha Chahboun, Larbi El Abdellaoui, Mohamed Latrache
Abstract: The requirement for applications operating at a variety of frequencies in a unified wireless device has greatly enhanced in recent years. For this purpose, multi-functional wireless components are essential. This paper presents a new design of a wideband circularly-polarized microstrip antenna array with defected ground structure (DGS). A previous design was introduced in [1], which cover the C-band at 5.8GHz and operates in the Industrial Scientific Medical band (ISM) for wireless communication applications. The proposed antenna has excellent performances which include good input impedance matching with fed of the circular polarization at 5.8GHz. The proposed design is validated and optimized by adding a new design of the defective ground structure. This aperture geometry enables the antenna to operate in a wide band. The obtained results show that the modified antenna has a good performance in terms of return loss, bandwidth, gain, and radiation pattern and demonstrate that the proposed antenna offers a good solution for multi-standard wireless communication applications
PubDate: Wed, 01 Jun 2022 00:00:00 +000
- Design and Bandwidth Enhancement of Zeroth-Order Resonator Antenna using
Metamaterial
Authors: Sadiq Ahmed; Zaid A. Abdul Hassain, Hussein A. Abdulnabi, Mohammed AL-Saadi
Abstract: In this paper, a compact configuration of zeroth-order resonator antenna is described. The unit cell zeroth-order resonator properties are introduced by composite right/left-handed transmission line approach is fed by coplanar waveguide. The proposed resonator is analyzed by changing the coupling space and stub length of the unit cell. The size of implemented resonator is (0.185λ0 ×0.185λ0×0.027λ0) at the centre frequency. In this work, a zeroth-order resonator antenna design with enhanced bandwidth has been presented, and the size reduction by using the metamaterial inclusion. The proposed ZORA achieves a 64% reduction compared to a traditional λ/2 microstrip patch antenna. The bandwidth for the 10 dB return loss is 5.66 GHz (2.76-8.42 GHz), the peak value of gain is 0.8 dBi and radiation efficiency of the designed antenna is 87% at 5.5GHz. The return loss is about -59.48 dB at the center frequency. The competition among the simulated performances and other antennas shows that the proposed resonator achieves wide bandwidth. The performance of zeroth-order resonator antenna is evaluated by full-wave EM simulator HFSS11.
PubDate: Wed, 01 Jun 2022 00:00:00 +000
- Low Overhead Optimal Parity Codes
Authors: Neelima K; C. Subhas
Abstract: The error detecting and correcting codes are used in critical applications like in intensive care units, defense applications, etc require highly reliable data. This brief focuses on developing EDAC codes capable of detecting and correcting adjacent errors within a single clock cycle by using modulo-2 addition of data bits for parity generation, syndrome calculation, error location identification and correction by improving code rate and minimizing bit overhead. The optimal parity codes devised can correct odd number of adjacent errors upto (N/2)-1 data bits when compared with the existing codes with less delay. Four optimal codes are proposed based on the properties specified by existing decimal matrix codes which are further optimized. All the codes are evaluated for their performance in terms of area, delay, power, bit overhead, code rate, code efficiency, etc. The proposed codes are better choice with an assurance of good reliability. The EDAC components are developed in Verilog HDL and verified for Zynq 7000 series FPGA in Xilinx ISE 14.5 Tool. Among the four codes devised, optimal code – 4 proves to be a better code with 65.3% code rate and 53.12% bit overhead. Also when compared other codes, it uses 33.3% less area and 1.89% less power delay product for encoder and 32.2% less area and 0.36% power delay product for decoder respectively.
PubDate: Wed, 01 Jun 2022 00:00:00 +000
- A Hybrid Soft Bit Flipping Decoder Algorithm for effective signal
transmission and reception
Authors: Shaik Asif. Hussain; J Chinna Babu, Raza Hasan, Salman Mahmood
Abstract: The Euclidean Geometry (EG) based Low-Density Parity Check (LDPC) codes are enciphered and deciphered in various modes. These algorithms have the back-and-forth between decoding delay, and power usage, device unpredictability resources, and error rate efficacy are all available with these methods. As a result, the goal of this paper is to develop a comprehensive method to describe both soft and burst error bits for optimal data transfer. As a result, for EG-LDPC codes, a Hybrid Soft Bit Flipping (HSBF) decoder is suggested, which decreases decoding complications while improving message data transfer. A simulation model is formed using Xilinx synthesis and SPARTAN 3e to study decoding latency, hardware usage, and power usage. A Hybrid Soft Bit Flipping (HSBF) or SRWSBF decoder is used in this paper, which accepts a 64-bit coding sequence and assigns 64 Adjustable nodes to it. It checks all Customizable cluster connections and quantifies adjustable node values and actions. According to the simulation findings, the suggested method achieves outstanding results, reducing average latency to 19.65 percent, reducing power consumption to 31.68 percent, reducing hardware utilization to 3.25 percent, and reducing the number of slices Flip-flop resource use to 1.85 percent. As a consequence of the data collected, our simulation model demonstrates that the Hybrid Soft Bit Flipping (HSBF) technique outperforms Soft Bit Flipping (SBF) algorithms. As a result, the techniques are ideal for usage in intermediate applications and as well as in cyber security processing technologies, medical applications
PubDate: Wed, 01 Jun 2022 00:00:00 +000
- Empirical Measurement for Path Loss Characteristics at Multiple Frequency
Bands from 2.2 to 14.6 GHz in Chamber Room
Authors: A.B. Basri; K. Badron, A.F. Ismail, A. Chanik, M. Ismail
Abstract: Free Space Path Loss (FSPL) is the loss of electromagnetic signal strength. This loss is caused by the line-of-sight path through free space without obstacles that hinder reflection or diffraction. Even in a LoS (Line of Sight) indoor single layer, as the distance increases, the path loss in the 1 GHz frequency band also exceeds the free space path loss. This is because the first Fresnel zone is shielded by the floor and ceiling. In order to improve the measurement results, a fully covered anechoic chamber is used in this empirical measurement, which is designed to completely absorb any signal reflections. The measurement is based on multiple frequency bands from 2.23201 GHz to 14.685 GHz. This article details how to achieve it. Measurements are made to establish the correlation between the power transmit value and the frequency value. This movement involves the establishment of microwave link transmissions, which include transmitters, receivers and related antennas with different displacements. Use a signal generator to control the transmit power and use a Vector Network Analyzer in the electromagnetic compatibility (EMC) room to measure the received power level. Appropriate analysis that determines the correlation. The logarithm function developed based on the empirical experiment conducted, the result suggested the formulation of LFS . These findings enable people to understand the required FSPL value as the power transmission and frequency change during each measurement. The collected data will also be used to investigate free space path loss formulas applicable to satellite links in tropical regions.
PubDate: Wed, 01 Jun 2022 00:00:00 +000
- Design of a microstrip antenna patch with a rectangular slot for 5G
applications operating at 28GHz
Authors: Salah-Eddine DIDI; Imane HALKHAMS, Mohammed FATTAH, Younes BALBOUL, Said MAZER, Moulhime EL BEKKALI
Abstract: In this paper, we present a study and design of a rectangular-shaped microstrip patch antenna with a rectangular shaped slot at the operating frequency is 28GHz, for 5G wireless applications, using the microstrip line technique for feeding. The objective of this slot is to contribute to the improvement of antenna performance. This antenna is built on a Roger RT Duroid 5880 type substrate having a relative permittivity equal to 2.2, a height of h= 0.5mm, and a loss tangent of 0.0009. The compact size of this antenna is 4.2 mm×3.3 mm×0.5 mm. The simulations of this antenna were performed using HFSS (High-Frequency Structure Simulator) and CST (Computer Simulation Technology) software whose main purpose is to confirm the results obtained for this proposed antenna. The results obtained during these simulations are as follows: resonant frequency of 27.97 GHz and reflection coefficient (S11) of -20.95 dB, bandwidth of 1.06 GHz, a gain of 7.5 dB, radiated power of 29.9 dBm, and efficiency of 99.83%. These results obtained by this proposed antenna are better than those obtained from already existing antennas that are published in current scientific journals. Consequently, this antenna is likely to satisfy the needs for 5G wireless communication applications.
PubDate: Wed, 01 Jun 2022 00:00:00 +000
- Reconfigurable PIFA antenna for RFID tag and GPS applications
Authors: Assiya Amri; Tomader Mazri
Abstract: This paper presents the design of a reconfigurable PIFA (Planar Inverted-F Antenna) antenna. The proposed antenna is designed and optimized to operate in two frequency bands. 2.4 GHz allocated to the ISM band for the identification of a set of vehicules within a given area, and 1.575 GHz allocated to the GPS band to locate them outside. The ISM band is used for microwave frequencies for active RFID tag, which is associated with the object to be identified. This antenna consists of two radiating elements connected by a PIN diode to obtain the frequency reconfigurability. Its total size is 30x50x7 mm3. The substrate used is FR4 with constant dielectric relativity of 4.4 and a height of 1.6 mm. CST Microwave Studio software is used to simulate and optimize the proposed reconfigurable PIFA antenna
PubDate: Wed, 01 Jun 2022 00:00:00 +000
- Model Development for Pneumonia Detection from Chest Radiograph using
Transfer Learning
Authors: Fagbuagun Ojo Abayomi, Nwankwo Obinna, Akinpelu S. A; Folorunsho O
Abstract: Accurate interpretation of chest radiographs outcome in epidemiological studies facilitates the process of correctly identifying chest-related or respiratory diseases. Despite the fact that radiological results have been used in the past and is being continuously used for diagnosis of pneumonia and other respiratory diseases, there abounds much variability in the interpretation of chest radiographs. This variability often leads to wrong diagnosis due to the fact that chest diseases often have common symptoms. Moreover, there is no single reliable test that can identify the symptoms of pneumonia. Therefore, this paper presents a standardized approach using Convolutional Neural Network (CNN) and transfer learning technique for identifying pneumonia from chest radiographs that ensure accurate diagnosis and assist physicians in making precise prescriptions for the treatment of pneumonia. A training set consisting of 5,232 OCT and Chest X-ray images dataset from Mendelev public database was used for this research and the performance evaluation of the model developed on the test set yielded 88.14% accuracy, 90% precision, 85% recall and f1 score of 0.87.
PubDate: Wed, 01 Jun 2022 00:00:00 +000
- Enhancement Process of AES: A Lightweight Cryptography Algorithm-AES For
Constrained Devices
Authors: Hussein M. Mohammad; Alharith A. Abdullah
Abstract: The restricted devices have a small memory, simple processor, and limited power. To secure them, we need lightweight cryptography algorithms, taking into account the limited specifications. Lightweight encryption algorithms (LWC) provide confidentiality and maintain information integrity for devices with limited resources such as smart cards, RFID tags, sensor networks, and embedded systems. They have the same levels of security as traditional cryptographic algorithms. Significant challenges face LWC's efficiency and robustness, such as small size, limited computational capacity, limited memory, and devices' power supplies against providing high-security levels. This paper improves and enhances Advanced Encryption Standard (AES) algorithm by reducing algorithm computation power (time consumption, Memory-RAM and CPU Usage ) and improving cryptography performance from the point of resource constraint devices. The proposed algorithm is fast and lightweight, which is essential for securing all kinds of data, like text, video, image, Etc. Besides, the use of Mix column overhead is dispense with, and the ciphertext is processed by the mathematical function (continued fraction) to compress the ciphertext and make it more confusing and also to increasing the data transfer speed. All above advantages make the proposed LWC-AES algorithm highly suitable for the timely execution of encryption and decryption (such as when encrypt text has (45.1KB) encryption execution time for AES was (294 ms), while in LWC-AES was 280 ms), as well as suitable for the memory size of the resource-constrained devices for all types of data, than the AES algorithm. The proposed algorithm tested for security analysis using the Avalanche Effect parameter, and this test showed acceptable and within required security results.
PubDate: Wed, 01 Jun 2022 00:00:00 +000
- General Rules of Evaluating Binary Number Divisibility on Prime Numbers
Authors: Alaa Ghazi Abdulbaqi; Ghadah A. Al-Sakkal, Yasir Hashim
Abstract: This research paper is to define new rule to find the divisibility of stream of binary on any prime numbers 3, 5, 7 …... with reminder 0. In general, the divisibility of binary numbers is most important in many digital circuits and mathematical applications. This paper explains this new rule for evaluating the divisibility of any binary number on any prime number greater than 2. This rule will depend on separating the binary number into blocks of bits then processes each block separately in a special procedure to find the possible divisibility on the prime number. After testing this new rule with prime numbers 3, 5 and 7 as a sample of prime numbers, the finding shows that this rule provides fast and true results.
PubDate: Wed, 01 Jun 2022 00:00:00 +000
- Crime Index Based on Text Mining on Social Media Using Multi Classifier
Neural-net Algorithm
Authors: Teddy Mantoro; M. Anton Permana, Media A. Ayu
Abstract: Every day criminal issues appear on social media, even some crime news is often very disturbing to the public. Sharing news about crime can give a warning to the public to remain careful and alert to the surrounding environment. However, following large amounts of information about criminals on social media is not effective, especially for people who have a very busy schedule. Therefore, there is a need to efficiently and effectively summarize information in a way that is meaningful and easy to see, attracts people's attention, and can be used by law enforcement officials. The purpose of this study is to present the index crime based on social media by looking for patterns of crime. This study proposes the projected index crime based on crime trends by using text mining to classify tweet texts and post contents into 10 crime classes. The classification method uses the Neural-net Multi Classifier Algorithm which has several Classifiers namely Logistic Regression, Naïve Bayes, Support Vector Machine (SVM), and Decision Tree in parallel. In this approach, the classifier that provides the best accuracy will be the winning classifier and will be used in the next learning process. In this experiment, in using the Multi Classifier Neural-net, the Logistics Regression classifier often provides the best accuracy
PubDate: Wed, 01 Jun 2022 00:00:00 +000
- Hiding Health report in X-Ray Images to protect People Privacy
Authors: Enas Ali Jameel; Sameera l Abbas Fadhe
Abstract: X-rays images are a popular medical diagnoses method. These images are hard to read and to be understandable outside the medical community. However, the radiologist writes a report of the X-ray. This report can be understandable easily which, can impact the privacy of the patients medical records. To tackle this issue, in this work, X-ray image steganography algorithm based on Sudoku mathematical game is proposed. The method converts the image into triangular shaped blocks. Subsequently, the data is encoded and segmented two bits at the time to be embedded in the image. To evaluate the algorithm, eight different X-ray images from allX-ray types have been utilized for data hiding process. The algorithm has been compared to the lest significant bit (LSB) and the turtle shell algorithms using the mean square error (MSE) and peak signal to noise ratio (PSNR) performance metric. The proposed algorithm obtained higher bit per pixel embedding capacity with 2bpp which is higher than LSB and turtle shell. Moreover, the algorithm has higher PSNR compared to turtle shell algorithm.
PubDate: Wed, 01 Jun 2022 00:00:00 +000
- Overall outage event of self-sustaining low-power cooperative relaying
networks
Authors: Hoang-Sy Nguyen; Thanh-Khiet Bui
Abstract: This paper investigates the implementation of the household low-power energy harvesting (LoPEH) wireless sensor networks (WSN) over log-normal fading channels. The relays are battery-operated and the stochastic harvested energy flow to the batteries is characterized with the Markov property of energy buffer status. The communication is established with the combination of direct link and cooperative relays. The best relay is chosen based on a relay selection (RS) scheme namely optimal relay selection (OPRS). It can be drawn that within a particular range of signal-to-noise ratio (SNR), the EH relay-aided protocol can remarkably boost the overall system performance. On the other hand, the study reports how increasing the log-normal channel variance can degenerate the in-studied EH relaying protocol.
PubDate: Wed, 01 Jun 2022 00:00:00 +000
- Recent Systematic Review on Students’ Performance Prediction Using
Backpropagation Neural Network Algorithms
Authors: Edi Ismanto; Hadhrami Ab. Ghani, Nurul Izrin Binti Md Saleh, Januar Al Amien, Rahmad Gunawan
Abstract: A thorough systematic study is carried out to identify different deep learning methods developed and applied for students’ academic performance prediction. Although machine learning schemes are previously popular, deep learning algorithms are currently explored to solve challenging predictions of students’ performance with more data attributes in larger datasets. The study is focused on prediction methods developed based on deep neural networks with clear modeling and parameter measurements based on public and recognized datasets. Based on the systematic review, the backpropagation is the most widely employed deep neural network method for predicting the students’ academic performance. Various datasets have been used in literature and the most frequently used datasets are the learning management system (LMS) and the massive open online course (MOOC) datasets. The standard artificial neural network approach is observed to be the most widely adopted method for prediction. For temporal students' performance data, the long short-term memory (LSTM) approach is found to result in a better accuracy value of around 87%. The upward trend towards deep neural network research and development in students’ academic management and prediction is clearly observed from the number of papers in which this method is studied and developed.
PubDate: Wed, 01 Jun 2022 00:00:00 +000
- A Novel Fern-like Lines Detection Using a Hybrid of Pre-trained CNN Model
and Frangi Filter
Authors: Heri Pratikno; Mohd Zamri Ibrahim, Jusak Jusak
Abstract: Full ferning is the peak of the formation of a salt crystallization line pattern shaped like a fern tree in a woman's saliva at the time of ovulation. The main problem in this study is to detect the shape of the salivary ferning line pattern, namely: the presence of layers of transparent line pattern forms, several hidden layers, uneven lighting, dense and irregular ferning line patterns. This study aims to detect transparent, invisible, irregular, and illuminating fern-like lines on the salivary ferning surface using a comparison of 15 pre-trained Convolutional Neural Network models. To reveal fern-like lines in transparent, hidden, and irregular layers, a pre-processing stage was carried out using the Frangi Filter. The pre-trained Convolutional Neural Network model is a framework that promises high precision and accuracy to detect fern-like lines in salivary ferning. Transfer learning can adapt networks that can be used to perform specific tasks. The results of this study using the fixed learning rate model ResNet50 revealed the best performance with an error rate of 4.37% and an accuracy of 95.63%. Meanwhile, in applying the experimental auto-learning rate empirically, ResNet18 achieved the best results with an error rate of 1.99% and an accuracy of 98.01%. The results of visually detecting the form of fern-like lines on salivary ferning using a patch size of 34x34 pixels showed the ResNet34 model gave the best appearance.
PubDate: Wed, 01 Jun 2022 00:00:00 +000
- The extraction and segmentation process of Iraqi paper currency
Authors: Bassam H. Abd; Bassam H. Abd, Ivan A. Hashim, Shaimaa H. Shaker
Abstract: Different application like image segmentation, moving objects detection and objects tracking, Required an object detection and segmentation techniques. Recently, these techniques become so important especially when only a specific part of image is important. This research paper present an efficient algorithm that employed for objects detection and extraction process. This algorithm consist of a several steps and the validity of this algorithm is measured based on different denomination of Iraqi currency. These steps arrange as following: image conversion, deleting small and unnecessary objects from images, extraction of interest objects boundary, finally calculating the rotation angle automatically, and rotate image based on the calculated angle. The validity of algorithm measured on the seven denomination of Iraqi currency (250, 500, 1000, 5000, 10000, 25000 and 50000). This image saved in a database that contain 40 image for each denomination and the total images for all denominations are 280 image. After testing the validity of designed algorithm on all captured image, the algorithm show high accuracy which equally to 99.6%.
PubDate: Wed, 01 Jun 2022 00:00:00 +000
- Detection of image manipulation with Convolutional Neural Network and
local feature descriptors
Authors: Ali Ahmad Aminu; Nwojo Nnanna Agwu, Steve Adeshina, Muhammed Kabir Ahmed
Abstract: In recent times, numerous digital image manipulation detection approaches have been proposed to detect which processing operations were applied to manipulate digital images. Most of these approaches consider the situation in which an image is manipulated by only one manipulation operation. However, practical image manipulation often involves multiple manipulation operations. It is important to detect multiple image manipulation operations and the order in which they were applied to establish the origin and genuineness of a given image as well as the processing history it has gone through. In this article, we proposed a new method to determine multiple image processing operation and operation chains based on CNN and Local Optimal Oriented pattern (LOOP). The proposed method is based on Convolutional Neural Network (CNN) and Local Optimal Oriented Patterns (LOOP) in which CNN extracts and learns image manipulation traces from the LOOP maps of the input images that are classified using Softmax, Extra-Tree, and XGBOOST classifiers. Detailed experiments show that the proposed model can attain overall detection accuracies of 99.81% and 99.15% in identifying different image manipulations and manipulation operation chains, respectively.
PubDate: Wed, 01 Jun 2022 00:00:00 +000
- Design of UTEM Logo-Shape Wearable Antenna for Communication Application
made from Graphene- Silver Nanocomposites
Authors: Mohd Muzafar Ismail; Jeefferie Abd Razak, Ahmad Rifhan Salman
Abstract: Previously, the antenna conductive patch was made of copper, which was costly, susceptible to multi-fading, bulky, environmentally sensitive, and difficult to produce. Because of their exceptional electrical conductivity and superior strength to metal, while remaining versatile, the miracle nanotechnology of graphene has made them a possible candidate to replace uncompromising copper metallic content. To the best of our knowledge, in this research work, this is the first time the novel formulation of graphene is incorporated into conductive silver nanocomposites through simulation modeling. With the microstrip feeding technology, the suggested antenna design features a logo-shaped made of graphene and silver patch on a textile substrate and radiates at 2.45GHz frequency. The antenna's total dimensions are 60×60×1.6 mm. CST Studio Suite software was used to generate the simulation results, which are higher gain, higher directivity, larger bandwidth, lower return loss, higher voltage standing wave ratio (VSWR), and promising overall efficiency as compared to a copper conductive material. Wearable antennas are promising and have a bright future, especially with the advent of wireless communication technologies, so this new design is essential for the materials revolution in advanced communication and IR4.0 applications, as well as wireless sensor applications.
PubDate: Wed, 01 Jun 2022 00:00:00 +000
- Benefits of using TiO2 Quantum Dots in producing low-cost and high-quality
white LEDs
Authors: Nguyễn Đoàn Quốc Anh; Phung Ton That, Tran Thanh Trang, Phan Xuan Le, Nguyen Doan Quoc Anh
Abstract: Quantum dots (QDs) is considered as a potential material for the improvement of light-emitting diodes (LEDs). However, different from the traditional phosphor materials, they have unique scattering and absorption properties affected by their several nanometers sizes, which makes their application in the production of LED confronts more challenges. In addition to this, the influence of QDs on QDs-converted LEDs (QCLEDs) is barely studied. In order to propose solutions for those problems, in this article, we carried out experimental and theoretical investigation of the effect of TiO2 QDs’ scattering and absorption on the optical performance of QCLEDs by comparing their properties with the traditional yttrium aluminum garnet phosphors’. The results showed that the strong absorption (reabsorption) of QDs is the cause of low radiant efficacy and stability of QCLEDs, and their weak scattering ability results in a low color homogeneity. For achieving high efficiency and stability white LEDs, we highly suggest using a low QD concentration to get reductions in the reabsorption loss and the total internal reflection loss. With 0.05 concentration of TiO2 NPs, the white LEDs can achieve a high CCT of ∼7500 K and a high CRI of ∼85 simultaneously. Moreover, this TiO2 concentration can also increase the luminous intensity by ∼31%. Therefore, we believe that the study can propose a potential approach to the production of low-cost CDs-based LEDs with high performance in a near future.
PubDate: Wed, 01 Jun 2022 00:00:00 +000
- Energy-efficient speed profile: An optimal approach with fixed running
time
Authors: An Thi Hoai Thu Anh; Nguyen Van Quyen
Abstract: Tracking the optimal speed profile in electric train operation has been proposed as an efficient and feasible solution for not only reducing energy consumption, but also no at costs to upgrading the existing railway systems. This paper focuses on finding the optimal speed profile based on Pontryagin's maximum principle (PMP) while ensuring the fixed running time, and comparing energy saving levels in the cases of applying or not applying PMP. The way to determine the fixed running time also differs from works published is to calculate the total trip time equal to scheduled timetable exactly. Calculating accelerating time ta, coasting time tc, braking time tb via values of maximum speed vh, braking speed vbof optimal speed profile. The other hands, vh and vb are determined by solving nonlinear equations with constraint condition: the running time equal to the demand time. Simulation results with data collected from electrified trains of Cat Linh-Ha Dong metro line, Vietnam show that energy reduction for the entire route when PMP utilization is up to 8.7% and running time complied with scheduled timetables.
PubDate: Wed, 01 Jun 2022 00:00:00 +000
- PID-Based Aneroid Sphygmomanometer Testing Method
Authors: Wuwus Ardiatna; Nurdina Gita Pratiwi, Siddiq Wahyu Hidayat, Prayoga Bakti, Asep Rahmat Hidayat, Ihsan Supono
Abstract: One of the parameters to be tested on the sphygmomanometer is the deflection of the dial. The testing method based on the standard uses manual air pressure to increase the pressure so that the dial is pointed to the desired pressure. This paper proposed an automatic testing method using a Proportional–Integral–Derivative (PID) controller based on Arduino to control the pressure. The result shows that the system is not suitable to use. The process capability index at each given setpoint is less than 1. This low cost proposed testing method still needs to be improved and could become an alternative solution for laboratory testing of the sphygmomanometer.
PubDate: Wed, 01 Jun 2022 00:00:00 +000
- Attenuated-Chattering Adaptive Second Order Variable Structure Controller
for Mismatched Uncertain Systems
Authors: Phan-Thanh Nguyen; Trieu Ton Ngoc, Cong-Trang Nguyen
Abstract: In this paper, an attenuated-chattering adaptive second order variable structure controller (ACASOVSC) is proposed for mismatched uncertain systems using a Moore-Penrose Inverse method. The key achievements of this study include three tasks: 1) influence of the chattering in control input is diminished; 2) finite-time convergence of system states is guaranteed; 3) external disturbance is generally assumed to be unknown in advance. Firstly, a switching manifold which comprises only output information is defined. Secondly, a reduced-order variable structure estimator (ROVSE) with lower dimension is designed to reduce the computation burden and enhance the robustness. Thirdly, an adaptive approach is used to guess the upper bound of the unknown exogenous disturbance. Next, an ACASOVSC is investigated for attenuating the chattering phenomenon and stabilizing the system. Then, a novel linear matrix inequality (LMI) constraint by the Lyapunov technique is given such that the plant is entirely invariant to matched uncertainties and asymptotically stable. Finally, a mathematical illustration is simulated, which exhibits the usefulness and the feasible application of the proposed method.
PubDate: Wed, 01 Jun 2022 00:00:00 +000
- An open-source active power controller for grid required ancillary
services
Authors: Nadia Zendehdel; Danyal Bustan
Abstract: With increasing penetration of renewable energies into modern power systems, supporting grid required ancillary services become a challenging problem. Wind turbines, as one of the main sources of renewable energies, has some inherit features which can be employed to support ancillary services for utility grids. One of the key requirements of grid operators is active power control for frequency regulation. But this requirement cannot addressed with traditional wind turbine controllers as these controllers try to capture maximum of available power while with active power control, the output power should limited to a predefined (time varying) set-point. Although new methods are introduced for active power control, there is no suitable comparison between them because of lack of a standards and easy to implement tools. In this paper, an extension to well-known open source ROSCO controller based on NREL 5 MW FAST model is proposed to support active power control. With this extension, In addition to active power control support the resulted mechanical loads on various turbine parts can be evaluated
PubDate: Wed, 01 Jun 2022 00:00:00 +000
- Comparative Study of Extraction Features and Regression Algorithms for
Predicting Drought Rates
Authors: Irza Hartiantio Rahmana; Amalia Rizki Febriyani, Indra Ranggadara, Suhendra Suhendra, Inna Sabily
Abstract: Rice is the primary staple food source for Indonesian people, with consumption increasing so that rice production needs to be increased. Rice drought is one of the problems that can hamper rice production. This research aims to determine the best extraction feature between the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Water Index (NDWI) in describing rice fields' dryness. Moreover, using the random forest regression algorithm. This research compares NDVI with NDWI using data originating from Sentinel-2A and retrieved via the google earth engine. Regression Algorithms are used in research to predict drought in paddy fields. This research shows that NDVI is better than NDWI in predicting drought using random forest regression algorithms and logistic regression algorithms. The random forest regression algorithm based on the results obtained shows that the average Root Mean Square Error (RMSE) on NDVI is 0.018, and NDWI is 0.012. Based on the logistic regression algorithm results, it was found that the average value of RMSE on NDVI was 0.346, and NDWI was 0.336. Based on the results of the RMSE, it shows that the forecasting ability of the random forest regression algorithm is better than the logistic regression.
PubDate: Tue, 01 Mar 2022 00:00:00 +000
