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International Journal of Electrical and Computer Engineering

IJECE
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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 116 Documents

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Search results for , issue "Vol 10, No 5: October 2020" : 116 Documents clear

Modified sub-gradient based combined objective technique and evolutionary programming approach for economic dispatch involving valve-point loading, enhanced prohibited zones and ramp rate constraints Susanta Kumar Gachhayat; Saroja Kumar Dash
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

A security constrained non-convex power dispatch problem with prohibited operation zones and ramp rates is formulated and solved using an iterative solution method based on the feasible modified sub-gradient algorithm (FMSG). Since the cost function, all equality and inequality constraints in the nonlinear optimization model are written in terms of the bus voltage magnitudes, phase angles, off-nominal tap settings, and the Susceptance values of static VAR (SVAR) systems, they can be taken as independent variables. The actual power system loss is included in the current approach and the load flow equations are inserted into the model as the equality constraints. The proposed modified sub gradient based combined objective technique and evolutionary programming approach (MSGBCAEP) with as decision variable and cost function as fitness function is tested on the IEEE 30-bus 6 generator test case system. The absence of crossover operation and adoption of fast judicious modifications in initialization of parent population, offspring generation and normal distribution curve selection in EP enables the proposed MSGBCAEP approach to ascertain global optimal solution for cost of generation and emission level shown in Table 6 and displayed in Figure 2 and Figure 3 respectively.

The impact of gamification on students learning engagement Firas Layth Khaleel; Noraidah Sahari Ashaari; Tengku Siti Meriam Tengku Wook
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

Gamification is to use game elements in a non-game context to increase engagement between human and computer, on the other hand, to encourage in-demand for good behaviors in learning. This research tried to increase student engagements in learning by conducted Gamification technique especially in difficult subjects such as Programming Language courses. The previous work was shown that students dropped, failed, or withdrew from the course at rates of between 35% and 50%. Therefore the main objective of this study is to increase student engagements in learning programming subject, and also to measure the impact of game elements on student’s engagements. Finally, the findings have shown the score of game elements that have a good effect on student’s engagement in the experiment group.

Comparative analysis of feeding techniques for cylindrical surrounding patch antenna Erhiega N. Umayah; Viranjay M. Srivastava
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

In this research work, a Cylindrical Surrounding Patch Antenna (CSPA) with improved performance parameters based on inset feed method compared to other feed techniques has been proposed for 1.8 GHz applications. The designed and simulated CSPA is a rotary version of an initially designed Rectangular Planar Patch Antenna (RPPA). The RPPA is mounted on a cylindrical surface with radius (r) 10 mm which is an increased curvature for better -10 dB S-parameter (S11), impedance Band Width (BW), Voltage Standing Wave Ratio (VSWR), radiation pattern, and gain. The copper radiating patch has been conformed on the surface of the grounded flexible polyimide substrate with relative permittivity (εr) 3.5 and thickness (h) 1.6 mm at normalized input impedance of 50 Ω. Results for the RPPA and the proposed CSPA have been compared with existing designs in terms of antenna size, resonant frequency (fr), return loss (S11), and gain while taking cognizance of the feeding techniques. The S11, BW, VSWR, and gain are -12.784 dB, 28 MHz, 1.8, and 4.81 dBi respectively for the rectangular planar patch antenna and -35.571 dB, 66 MHz, 1.5, and 3.74 dBi, respectively for the cylindrical surrounding patch antenna.

Algorithm of detection, classification and gripping of occluded objects by CNN techniques and Haar classifiers Paula Useche; Robinson Jimenez-Moreno; Javier Martinez Baquero
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

The following paper presents the development of an algorithm, in charge of detecting, classifying and grabbing occluded objects, using artificial intelligence techniques, machine vision for the recognition of the environment, an anthropomorphic manipulator for the manipulation of the elements. 5 types of tools were used for their detection and classification, where the user selects one of them, so that the program searches for it in the work environment and delivers it in a specific area, overcoming difficulties such as occlusions of up to 70%. These tools were classified using two CNN (convolutional neural network) type networks, a fast R-CNN (fast region-based CNN) for the detection and classification of occlusions, and a DAG-CNN (directed acyclic graph-CNN) for the classification tools. Furthermore, a Haar classifier was trained in order to compare its ability to recognize occlusions with respect to the fast R-CNN. Fast R-CNN and DAG-CNN achieved 70.9% and 96.2% accuracy, respectively, Haar classifiers with about 50% accuracy, and an accuracy of grip and delivery of occluded objects of 90% in the application, was achieved.

An intrusion detection system for packet and flow based networks using deep neural network approach Kaniz Farhana; Maqsudur Rahman; Md. Tofael Ahmed
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

Study on deep neural networks and big data is merging now by several aspects to enhance the capabilities of intrusion detection system (IDS). Many IDS models has been introduced to provide security over big data. This study focuses on the intrusion detection in computer networks using big datasets. The advent of big data has agitated the comprehensive assistance in cyber security by forwarding a brunch of affluent algorithms to classify and analysis patterns and making a better prediction more efficiently. In this study, to detect intrusion a detection model has been propounded applying deep neural networks. We applied the suggested model on the latest data set available at online, formatted with packet based, flow based data and some additional metadata. The data set is labeled and imbalanced with 79 attributes and some classes having much less training samples compared to other classes. The proposed model is build using Keras and Google Tensorflow deep learning environment. Experimental result shows that intrusions are detected with the accuracy over 99% for both binary and multi-class classification with selected best features. Receiver operating characteristics (ROC) and precision-recall curve average score is also 1. The outcome implies that Deep Neural Networks offers a novel research model with great accuracy for intrusion detection model, better than some models presented in the literature.

Creation of speech corpus for emotion analysis in Gujarati language and its evaluation by various speech parameters Vishal P. Tank; S. K. Hadia
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

In the last couple of years emotion recognition has proven its significance in the area of artificial intelligence and man machine communication. Emotion recognition can be done using speech and image (facial expression), this paper deals with SER (speech emotion recognition) only. For emotion recognition emotional speech database is essential. In this paper we have proposed emotional database which is developed in Gujarati language, one of the official’s language of India. The proposed speech corpus bifurcate six emotional states as: sadness, surprise, anger, disgust, fear, happiness. To observe effect of different emotions, analysis of proposed Gujarati speech database is carried out using efficient speech parameters like pitch, energy and MFCC using MATLAB Software.

Optimum reactive power compensation for distribution system using dolphin algorithm considering different load models Waleed Khalid Shakir Al-Jubori; Ali Nasser Hussain
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

The distribution system represents the connection between consumers and the entire power network. The radial structure is preferred for distribution system due to its simple design and low cost. The electrical distribution system suffers from problems of rising power losses higher than the transmission system and voltage drop. One of the important solutions to improve the voltage profile and to reduce the electrical distribution system losses is the reactive power compensation which is based on the optimum choice of position and capacitor size in the network. In this paper, different models of electrical loads such as constant power(P), constant current(I), constant impedance(Z), and composite (ZIP) model are implemented with comparisons between them in order to identify the most effective load type that produces the optimal settlement for alleged loss reduction ,enhancement of the voltage profile, and cost savings. To minimize search space, Dolphin Optimization Algorithm (DOA) is applied for selecting the size and location of capacitors. Two case studies (IEEE 16- bus and 33- bus) are employed to evaluate the different load models with optimal reactive power compensation. The results of comparison between the different load models show that ZIP model is the best to produce the optimum solution for capacitor position and size. In addition, comparison of results with literature works are done and showed that DOA is the most robust among other algorithms to achieve the optimum solution for voltage profile enhancement significant reduction of losses, and saving cost.

Energy-aware strategy for data forwarding in IoT ecosystem K. Nagarathna
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

The Internet of Things (IoT) is looming technology rapidly attracting many industries and drawing research attention. Although the scale of IoT-applications is very large, the capabilities of the IoT-devices are limited, especially in terms of energy. However, various research works have been done to alleviate these shortcomings, but the schemes introduced in the literature are complex and difficult to implement in practical scenarios. Therefore, considering the energy consumption of heterogeneous nodes in IoT eco-system, a simple energy-efficient routing technique is proposed. The proposed system has also employed an SDN controller that acts as a centralized manager to control and monitor network services, there by restricting the access of selfish nodes to the network. The proposed system constructs an analytical algorithm that provides reliable data transmission operations and controls energy consumption using a strategic mechanism where the path selection process is performed based on the remaining energy of adjacent nodes located in the direction of the destination node. The proposed energy-efficient data forwarding mechanism is compared with the existing AODV routing technique. The simulation result demonstrates that the protocol is superior to AODV in terms of packet delivery rate, throughput, and end-to-end delay.

An enhanced energy-efﬁcient routing protocol for wireless sensor network Ikram Daanoune; Abdennaceur Baghdad; Abdelhakim Ballouk
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

Recent few years, Wireless Sensor Network (WSN) has been an increasingly important technology that has been applied in almost all domains, even in complex environments where human activity is impossible. In WSN, various factors are impacted energy consumption, such as communication protocols, packet data transmission, and limited battery. So, the lifespan of the WSNs is limited. In this context, energy efficiency is the factor most attracted by many researchers. In this paper, we proposed a new improved LEACH routing protocol. This proposed protocol based on the current energy to select cluster-heads, and it uses a root cluster-head with more current energy and low distance to the sink to gather all data, then sends it to the sink. The simulation results in MATLAB confirmed that the proposed algorithm performed better than the conventional LEACH protocol, and increased the network lifetime in WSN.

Face recognition using selected topographical features Maitham Ali Naji; Ghalib Ahmed Salman; Muthna Jasim Fadhil
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

This paper represents a new features selection method to improve an existed feature type. Topographical (TGH) features provide large set of features by assigning each image pixel to the related feature depending on image gradient and Hessian matrix. Such type of features was handled by a proposed features selection method. A face recognition feature selector (FRFS) method is presented to inspect TGH features. FRFS depends in its main concept on linear discriminant analysis (LDA) technique, which is used in evaluating features efficiency. FRFS studies feature behavior over a dataset of images to determine the level of its performance. At the end, each feature is assigned to its related level of performance with different levels of performance over the whole image. Depending on a chosen threshold, the highest set of features is selected to be classified by SVM classifier

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Tole Sutikno

Contact Email
ijece@iaesjournal.com

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Journal Mail Official
ijece@iaesjournal.com

Editorial Address
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Location
Kota yogyakarta,

Daerah istimewa yogyakarta

INDONESIA

Abstract

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Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name Tole Sutikno

Contact Email ijece@iaesjournal.com

Phone -

Journal Mail Official ijece@iaesjournal.com

Editorial Address -

Location Kota yogyakarta, Daerah istimewa yogyakarta INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Contact Name
Tole Sutikno

Contact Email
ijece@iaesjournal.com

Phone
-

Journal Mail Official
ijece@iaesjournal.com

Editorial Address
-

Location
Kota yogyakarta,

Daerah istimewa yogyakarta

INDONESIA