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International Journal of Electrical and Computer Engineering
Published by Institute of Advanced Engineering and Science
ISSN : 20888708     EISSN : 27222578     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
International Journal of Electrical and Computer Engineering (IJECE, ISSN: 2088-8708, a SCOPUS indexed Journal, SNIP: 1.001; SJR: 0.296; CiteScore: 0.99; SJR & CiteScore Q2 on both of the Electrical & Electronics Engineering, and Computer Science) is the official publication of the Institute of Advanced Engineering and Science (IAES). The journal is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication and computer engineering from the global world.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 6,301 Documents
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Design and development of a delta robot system to classify objects using image processing Vo Duy Cong; Le Hoai Phuong
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i3.pp2669-2676

Abstract

In this paper, a delta robot is designed to grasp objects in an automatic sorting system. The system consists of a delta robot arm for grasping objects, a belt conveyor for transmitting objects, a camera mounted above the conveyor to capture images of objects, and a computer for processing images to classify objects. The delta robot is driven by three direct current (DC) servo motors. The controller is implemented by an Arduino board and Raspberry Pi 4 computer. The Arduino is programmed to provide rotation to each corresponding motor. The Raspberry Pi 4 computer is used to process images of objects to classify objects according to their color. An image processing algorithm is developed to classify objects by color. The blue, green, red (BGR) image of objects is converted to HSV color space and then different thresholds are applied to recognize the object’s color. The robot grasps objects and put them in the correct position according to information received from Raspberry. Experimental results show that the accuracy when classifying red and yellow objects is 100%, and for green objects is 97.5%. The system takes an average of 1.8 s to sort an object.
Fisher exact Boschloo and polynomial vector learning for malware detection Sheelavathy Veerabhadrappa Kudrekar; Udaya Rani Vinayaka Murthy
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i3.pp2942-2952

Abstract

Computer technology shows swift progress that has infiltrated people’s lives with the candidness and pliability of computers to work ease shows security breaches. Thus, malware detection methods perform modifications in running the malware based on behavioral and content factors. The factors are taken into consideration compromises of convergence rate and speed. This research paper proposed a method called fisher exact Boschloo and polynomial vector learning (FEB-PVL) to perform both content and behavioral-based malware detection with early convergence to speed up the process. First, the input dataset is provided as input then fisher exact Boschloo’s test Bernoulli feature extraction model is applied to obtain independent observations of two binary variables. Next, the extracted network features form input to polynomial regression support vector learning to different malware classes from benign classes. The proposed method validates the results with respect to the malware and the benign files. The present research aimed to develop the behaviors to detect the accuracy process of the features that have minimum time speeds the overall performances. The proposed FEB-PVL increases the true positive rate and reduces the false positive rate and hence increasing the precision rate using FEB-PVL by 7% compared to existing approaches.
A transportation scheduling management system using decision tree and iterated local search techniques Thittaporn Ganokratanaa; Mahasak Ketcham
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i3.pp2899-2907

Abstract

This paper aimed to develop a delivery truck scheduling management system using a decision tree to support decision-making in selecting a delivery truck. First-in-first-out (FIFO) and decision tree techniques were applied to prioritize loading doors for delivery trucks with the use of iterated local search (ILS) in recommending the route for the transport of goods. Besides, an arrangement of loading doors can be assigned to the door that meets the specified conditions. The experimental results showed that the system was able to assign the job to a delivery truck under the specified conditions that were close to the actual operation at a similarity of 0.80. In addition, the application of ILS suggested the route of the food delivery truck in planning the most effective transportation route with the best total distance.
Performance analysis of multicore processors using multi-scaling techniques Jwan Mohammed; Diary R. Sulaiman
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i3.pp3079-3087

Abstract

Integrating more cores per chip enables more programs to run simultaneously, and more easily switch from one program to another, and the system performance will be improved significantly. However, this current trend of central processing unit (CPU) performance cannot be maintained since the budget of power per chip has not risen while the consumption of power per core has slowly reduced. Generally, the processor’s maximum performance is proportional to the product of the number of their cores and the frequency they are running at. However, this is usually limited by constraints of power. In this study, first, the voltage/frequency adjustment of the running cores has been analyzed for several programs to improve the processor’s performance within the constraint of power. Second, the impact of dynamically scaling the number of running cores is summarized for additional performance improvements of the active programs and applications. Finally, it has been verified that scaling the number of the running cores and their voltage/frequency simultaneously can improve the processor’s performance for a higher power dissipation or under power constraints. The performance analysis and improvements are obtained in a real-time simulation on a Linux operating system using a GEM5 simulator. Results indicated that performance improvement was attained at 59.98%, 33.33%, and 66.65% for the three scenarios, respectively.
Unloaded quality factor optimization of substrate integrated waveguide resonator using genetic algorithm Souad Akkader; Hamid Bouyghf; Abdennaceur Baghdad
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i3.pp2857-2864

Abstract

The main objective purpose of this paper is to study the enhancement techniques of the unloaded quality factor of substrate integrated waveguide (SIW) resonator, given that the quality of filters depends first on the quality of the resonators that compose it. Performance enhancement is achieved by employing a MATLAB-based genetic algorithm to optimize the geometrical parameters of the SIW resonator by iterative convergence to the target frequency (10 GHz frequency). On the other hand, the Ansys HFSS tool is used to model and optimize the SIW resonator with the suitable transition and plot the S-parameters for a frequency sweep range to validate its property. The results obtained allow increasing the unloaded Q-factor to be more than 1609 and reducing not only insertion and return losses but also reducing the size of the resonator. The proposed SIW resonator with its small size and low loss is directly useful for microwave and millimeter-wave applications.
Pedestrian classification on transfer learning based deep convolutional neural network for partial occlusion handling May Thu; Nikom Suvonvorn; Nichnan Kittiphattanabawon
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i3.pp2812-2826

Abstract

The investigation of a deep neural network for pedestrian classification using transfer learning methods is proposed in this study. The development of deep convolutional neural networks has significantly improved the autonomous driver assistance system for pedestrian classification. However, the presence of partially occluded parts and the appearance variation under complex scenes are still robust to challenge in the pedestrian detection system. To address this problem, we proposed six transfer learning models: end-to-end convolutional neural network (CNN) model, scratch-trained residual network (ResNet50) model, and four transfer learning models: visual geometry group 16 (VGG16), GoogLeNet (InceptionV3), ResNet50, and MobileNet. The performance of the pedestrian classification was evaluated using four publicly datasets: Institut National de Recherche en Sciences et Technologies du Numérique (INRIA), Prince of Songkla University (PSU), CVC05, and Walailak University (WU) datasets. The experimental results show that six transfer learning models achieve classification accuracy of 65.2% (end-to-end CNN), 92.92% (scratch-trained ResNet50), 97.15% (pre-trained VGG16), 94.39% (pre-trained InceptionV3), 90.43% (pre-trained ResNet50), and 98.69% (pre-trained MobileNet) using data from Southern Thailand (PSU dataset). Further analysis reveals that the deeper the ConvNet architecture, the more specific information of features is provided. In addition, the deep ConvNet architecture can distinguish pedestrian occluded patterns while being trained with partially occluded parts of data samples.
Improving the reliability in bio-nanosensor modules using hardware redundancy techniques Rahebeh Ghasemzadeh; Razieh Farazkish; Nasrin Amiri; Amir Sahafi
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i3.pp2891-2898

Abstract

A nano-robot is a controlled robotic system at the nanoscale. Nowadays, nanorobotics has become of particular interest in medicine and pharmacy. The accurate diagnosis of the diseases as well as their rapid treatment will make everyone surprised and will significantly reduce the associated risks. The modeling of reliability in biosensors is studied for the first time in this paper. The use of practical hardware redundancy has turned into the most cost-effective to improve the reliability of a system. Additionally, the Markov model is used to design fault-tolerant systems in nanotechnology. The proposed method is compared with some existing methods, such as triple modular redundancy and non-fault-tolerant systems; it is shown that using this method, a larger number of faults between 3-5 can be tolerated. Using the proposed method, the number of modules can be increased to nine. However, a larger number than 9 MR is not recommended because of an increased delay and requiring more hardware. As the scale of components used in digital systems has gotten smaller, the use of hardware redundancy has become cost-effective. But there is a trade-off between the amount of used hardware and fault tolerance, which can also be investigated.
High-efficiency 2.45 and 5.8 GHz dual-band rectifier design with modulated input signals and a wide input power range Sara El Mattar; Abdennaceur Baghdad
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i3.pp2419-2427

Abstract

This paper presents a new rectifier design for radio frequency (RF) energy harvesting by adopting a particular circuit topology to achieve two objectives at the same time. First, work with modulated input signal sources instead of only continuous waveform (CW) signals. Second, operate with a wide input power range using the Wilkinson power divider (WPD) and two different rectifier diodes (HSMS2852 and SMS7630) instead of using active components. According to the comparison with dual-band rectifiers presented in the literature, the designed rectifier is a high-efficiency rectifier for wide RF power input ranges. A peak of 67.041% and 49.089% was reached for 2.45 and 5.8 GHz, respectively, for CW as the input signal. An efficiency of 72.325% and 45.935% is obtained with a 16 QAM modulated input signal for the operating frequencies, respectively, 69.979% and 54.579% for 8PSK. The results obtained demonstrate that energy recovery systems can use modulated signals. Therefore, the use of a modulated signal over a CW signal may have additional benefits.
Evaluation of optical and synthetic aperture radar image fusion methods: a case study applied to Sentinel imagery Jose Manuel Monsalve-Tellez; Yeison Alberto Garcés-Gómez; Jorge Luís Torres-León
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i3.pp2778-2787

Abstract

This paper evaluates different optical and synthetic aperture radar (SAR) image fusion methods applied to open-access Sentinel images with global coverage. The objective of this research was to evaluate the potential of image fusion methods to get a greater visual difference in land cover, especially in oil palm crops with natural forest areas that are difficult to differentiate visually. The application of the image fusion methods: Brovey (BR), high-frequency modulation (HFM), Gram-Schmidt (GS), and principal components (PC) was evaluated on Sentinel-2 optical and Sentinel-1 SAR images using a cloud computing environment. The results show that the application of the implemented optical/SAR image fusion methods allows the creation of a synthetic image with the characteristics of both data sources. The multispectral information provided by the optical image and information associated with the geometry and texture/roughness of the land covers, provided by the SAR image, allows a greater differentiation in the visualization of the various land covers, achieving a better understanding of the study area. The fusion methods that visually presented greater characteristics associated with the SAR image were the BR and GS methods. The HFM method reached the best statistical indicators; however, this method did not present significant visual changes in the SAR contribution.
Two-section branch-line hybrid couplers based broadband transmit/receive switch Ashraf Abuelhaija; Gameel Saleh
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i3.pp2600-2607

Abstract

This article introduces a broadband microstripline-based transmit/receive switch for 7-Tesla magnetic resonance imaging. The designed switch aims to handle a signal of multiple frequencies to/from a multi-tuned radio-frequency coil that resonates at frequencies corresponding to the speed of precession of a wide range of atomic X-nuclei, at the same time and without tuning. These include 1H, 23Na, 13C, 31P, 19F, and 7Li used in magnetic resonance spectroscopy as a measure to the existence of many diseases. The fundamental and third harmonic center frequencies of the switch are adjusted to resonate at two broadbands covering a wide range of atomic X-nuclei. Two section branch-line hybrid couplers with phase inverters are designed to build the broadband switch. The designed switch used the minimum trace widths of transmission lines that reveal a compact size without increasing the heat and then the loss beyond specific values. The couplers and the switch S-parameters exhibited good return loss (<-10 dB), high isolation (<-40 dB), less insertion loss (<1 dB) and two clear wide bands covering many atomic X-nuclei used in diagnosis, at the same time and without the need for any tuning circuit during operation.

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