International Journal of Electrical and Computer 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.
Articles
6,301 Documents
The Analysis of Student Colla borative Work Inside Social Learning Network Analysis Based on Degree and Eigenvector Centrality
Andi Besse Firdausiah Mansur;
Norazah Yusof;
Ahmad Hoirul Basori
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 5: October 2016
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v6i5.pp2488-2498
Social learning network analysis is a potential approach to analyze the behaviour of students in collaborative work. However, most of the previous works focus on asynchronous discussion forum as the learning activity. Very few of them are trying to analyze the students' collaborative work while using wiki e-learning. This paper proposes the degree centrality and eigenvector method for identifying the collaborative work of students while in wiki e-learning. The log data of the Moodle e-learning system is observed that records the students' activities and actions while using wiki. The result shows that there is a close similarity between the degree centrality and the eigenvector. The result also reveals the students who obtain high outdegree values. Furthermore, Agent_1 and Agent_12 represent the students who obtained high outdegree values, which mean these two nodes are acting as source providers that able to supply information and knowledge through the network. This result also strengthened by value of closeness and betweenness where Agent_1 and Agent_12 leading on this measurement. The high closeness value of Agent_1 and Agent_12 will lead into fast spreading information since they have fastest route and has the most direct route to the other node inside the network, thus collaborative work is easy to be initialized by these Agents. This work has successfully identified collaborative work of student. This finding is believed to bring enormous benefit on the e-learning system improvement in the future.
Modelling Electronic Characteristic of InP/InGaAs Double Heterojunction Bipolar Transistor
Berrichi Yamina;
Ghaffour Kherreddine
International Journal of Electrical and Computer Engineering (IJECE) Vol 5, No 3: June 2015
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v5i3.pp525-530
In this paper, we are interested in studying InP/InGaAs heterojunction bipolar transistor NPN type. First and for most we should describe the structure of our simulation, then, we ploted at room temperature: Energy band diagram, Gummel plot, IC-VC characteristic and conduction bands for different values of VBE. The simulation of this structure has demonstrated the validity of our model and the method of the simulation.
IDDQ Testing of Low Voltage CMOS Operational Transconductance Amplifier
Maninder Kaur;
Jasdeep Kaur
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 3: June 2018
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v8i3.pp1467-1477
The paper describes the design for testability (DFT) of low voltage two stage operational transconductance amplifiers based on quiescent power supply current (IDDQ) testing. IDDQ testing refers to the integral circuit testing method based upon measurement of steady state power supply current for testing both digital as well as analog VLSI circuit. A built in current sensor, which introduces insignificant performance degradation of the circuit-under-test, has been proposed to monitor the power supply quiescent current changes in the circuit under test. Moreover, the BICS requires neither an external voltage reference nor a current source and able to detect, identify and localize the circuit faults. Hence the BICS requires less area and is more efficient than the conventional current sensors. The testability has also been enhanced in the testing procedure using a simple fault-injection technique. Both bridging and open faults have been analyzed in proposed work by using n-well 0.18µm CMOS technology.
A new digital signature scheme with message recovery using hybrid problems
Nedal Tahat;
Rania Shaqboua;
Emad E. Abdallah;
Mohammad Bsoul;
Wasfi Shatanawi
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 5: October 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v9i5.pp3576-3583
We present a new digital signature scheme with message recovery and its authenticated encryption based on elliptic curve discrete logarithm and quadratic residue. The main idea is to provide a higher level of security than all other techniques that use signatures with single hard problem including factoring, discrete logarithm, residuosity, or elliptic curves. The proposed digital signature schemes do not involve any modular exponentiation operations that leave no gap for attackers. The security analysis demonstrates the improved performance of the proposed schemes in comparison with existing techniques in terms of the ability to resist the most common attacks
Novel Framework for Navigation using Enhanced Fuzzy Approach with Sliding Mode Controller
T. Someswari;
Anil Kumar Tiwari;
Nagaraj R.
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 6: December 2018
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v8i6.pp4310-4320
The reliability of any embedded navigator in advanced vehicular system depends upon correct and precise information of navigational data captured and processed to offer trustworthy path. After reviewing the existing system, a significant trade-off is explored between the existing navigational system and present state of controller design on various case studies and applications. The existing design of controller system for navigation using error-prone GPS/INS data doesn‟t emphasize on sliding mode controller. Although, there has been good number of studies in sliding mode controller, it is less attempted to optimize the navigational performance of a vehicle. Therefore, this paper presents a novel optimized design of a sliding mode controller that can be effectively deployed on advanced navigational system. The study outcome was found to offer higher speed, optimal control signal, and lower error occurances to prove that proposed system offers reliable and optimized navigational services in contrast to existing system.
Game-Theoretic Channel Allocation in Cognitive Radio Networks
Sangsoon Lim
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 2: April 2017
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v7i2.pp986-991
Cognitive radio networks provide dynamic spectrum access techniques to support the increase in spectrum demand. In particular, the spectrum sharing among primary and secondary users can improve spectrum utilization in unused spectrum by primary users. In this paper, we propose a novel game theoretic channel allocation framework to maximize channel utilization in cognitive radio networks. We degisn the utility function based on the co-channel interference among primary and secondary users. In addition, we embed the property of the adjacent channel intererence to consider real wireless environment. The results show that the utility function converges quickly to Nash equilibrium and achieves channel gain by up to 25 dB compared to initial assignment.
Optimal design of adaptive power scheduling using modified ant colony optimization algorithm
Vijo M Joy;
S. Krishnakumar
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 1: February 2020
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v10i1.pp738-745
For generating and distributing an economic load scheduling approach, artificial neural network (ANN) has been introduced, because power generation and power consumption are economically non-identical. An efficient load scheduling method is suggested in this paper. Normally the power generation system fails due to its instability at peak load time. Traditionally, load shedding process is used in which low priority loads are disconnected from sources. The proposed method handles this problem by scheduling the load based on the power requirements. In many countries the power systems are facing limitations of energy. An efficient optimization algorithm is used to periodically schedule the load demand and the generation. Ant colony optimization (ACO) based ANN is used for this optimal load scheduling process. The present work analyse the technical economical and time-dependent limitations. Also the works meets the demanded load with minimum cost of energy. Inorder to train ANN back propagation (BP) technics is used. A hybrid training process is described in this work. Global optimization algorithms are used to provide back propagation with good initial connection weights.
Modified Variational Mode Decomposition for Power Line Interference Removal in ECG Signals
Neethu Mohan;
Sachin Kumar S;
Prabaharan Poornachandran;
Soman K.P
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 1: February 2016
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v6i1.pp151-159
Power line interferences (PLI) occurring at 50/60 Hz can corrupt the biomedical recordings like ECG signals and which leads to an improper diagnosis of disease conditions. Proper interference cancellation techniques are therefore required for the removal of these power line disturbances from biomedical recordings. The non-linear time varying characteristics of biomedical signals make the interference removal a difficult task without compromising the actual signal characteristics. In this paper, a modified variational mode decomposition based approach is proposed for PLI removal from the ECG signals. In this approach, the central frequency of an intrinsic mode function is fixed corresponding to the normalized power line disturbance frequency. The experimental results show that the PLI interference is exactly captured both in magnitude and phase and are removed. The proposed approach is experimented with ECG signal records from MIT-BIH Arrhythmia database and compared with traditional notch filtering.
Intelligent Automatic Extraction of Canine Cataract Object with Dynamic Controlled Fuzzy C-Means based Quantization
Kwang Baek Kim;
Doo Heon Song
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 2: April 2018
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v8i2.pp666-672
Canine cataract is developed with aging and can cause the blindness or surgical treatment if not treated timely. Since the pet owner do not have professional knowledge nor professional equipment, there is a growing need of providing pre-diagnosis software that can extract cataract-suspicious regions from simple photographs taken by cellular phones for the sake of preventive public health. In this paper, we propose a software that is highly successful for that purpose. The proposed software uses dynamic control of FCM clusters in quantification and trapezoid membership function in fuzzy stretching in order to enhance the intensity contrast from such rough photograph input. Through experiment, the proposed system demonstrates sufficiently enough accuracy in extraction (successful in 42 out of 45 cases) with better quality comparing with previous attempt.
A Novel Retinal Blood Vessel Segmentation Algorithm using Fuzzy segmentation
Razieh Akhavan;
Karim Faez
International Journal of Electrical and Computer Engineering (IJECE) Vol 4, No 4: August 2014
Publisher : Institute of Advanced Engineering and Science
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Assessment of blood vessels in retinal images is an important factor for many medical disorders. The changes in the retinal vessels due to the pathologies can be easily identified by segmenting the retinal vessels. Segmentation of retinal vessels is done to identify the early diagnosis of the disease like glaucoma, diabetic retinopathy, macular degeneration, hypertensive retinopathy and arteriosclerosis. In this paper, we propose an automatic blood vessel segmentation method. The proposed algorithm starts with the extraction of blood vessel centerline pixels. The final segmentation is obtained using an iterative region growing method that merges the binary images resulting from centerline detection part with the image resulting from fuzzy vessel segmentation part. In this proposed algorithm, the blood vessel is enhanced using modified morphological operations and the salt and pepper noises are removed from retinal images using Adaptive Fuzzy Switching Median filter. This method is applied on two publicly available databases, the DRIVE and the STARE and the experimental results obtained by using green channel images have been presented and compared with recently published methods. The results demonstrate that our algorithm is very effective method to detect retinal blood vessels.DOI:http://dx.doi.org/10.11591/ijece.v4i4.6253