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.
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FSDA: Framework for Secure Data Aggregation in Wireless Sensor Network for Enhancing Key Management
Jyoti Metan;
K. N. Narashinha Murthy
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.pp4684-4692
An effective key management plays a crucial role in imposing a resilient security technique in Wireless Sensor Network (WSN). After reviewing the existing approaches of key management, it is confirmed that existing approachs does not offer good coverage on all potential security breaches in WSN. With WSN being essential part of Internet-of-Things (IoT), the existing approaches of key management can definitely not address such security breaches. Therefore, this paper introduces a Framework for Secure Data Aggregation (FSDA) that hybridizes the public key encryption mechanism in order to obtain a novel key management system. The proposed system does not target any specific attacks but is widely applicable for both internal and external attacks in WSN owing to its design principle. The study outcome exhibits that proposed FSDA offers highly reduced computational burden, minimal delay, less energy consumption, and higher data transmission perforance in contrast to frequency used encryption schemes in WSN.
Cross Layer Solution for Energy and Delay Optimization in MANETs
Bhagyashri R. Hanji;
Rajashree Shettar
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.pp4745-4754
A novel method for packet forwarding in MANETs has been proposed in this paper. A node in the network acts as both host and router. Energy utilization of the node increases as all nodes in MANET operate as source, destination, and router to forward packets to the next hop ultimately to reach destination. Routers execute a variety of functions from simple packet classification for forwarding to complex payload revision. As the number of tasks and complexity increases, processing time required also increases resulting in significant processing delay in routers. The proposed work optimizes packet header at transport and network layer by calculating Unique Identifier using pairing function for the fields which do not change for a source–destination pair. This technique optimizes the processing cost of each packet header thereby conserving energy and reducing delay. It also simplifies the task of system administration. This paper elucidates an extension to basic AODV protocol, allowing routing of most packets without an explicit header, reducing the overhead of the protocol while still conserving its basic properties. The proposed method improves the network performance significantly compared to AODV, MTPR, and S-AODV protocol.
Comparison Analysis of Gait Classification For Human Motion Identification Using Embedded Computer
Agung Nugroho Jati;
Astri Novianty;
Nanda Septiana;
Leni Widia Nasution
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.pp5014-5020
In this paper, it will be discussed about comparison between two kinds of classification methods in order to improve security system based of human gait. Gait is one of biometric methods which can be used to identify person. K-Nearest Neighbour has parallelly implemented with Support Vector Machine for classifying human gait in same basic system. Generally, system has been built using Histogram and Principal Component Analysis for gait detection and its feature extraction. Then, the result of the simulation showed that K-Nearest Neighbour is slower in processing and less accurate than Support Vector Machine in gait classification.
Advanced SOM & K Mean Method for Load Curve Clustering
Phan Thi Thanh Binh;
Trong Nghia Le;
Nui Pham Xuan
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.pp4829-4835
From the load curve classification for one customer, the main features such as the seasonal factors, the weekday factors influencing on the electricity consumption may be extracted. By this way some utilities can make decision on the tariff by seasons or by day in week. The popular clustering techniques are the SOM & K-mean or Fuzzy K-mean. SOM &Kmean is a prominent approach for clustering with a two-level approach: first, the data set will be clustered using the SOM and in the second level, the SOM will be clustered by K-mean. In the first level, two training algorithms were examined: sequential and batch training. For the second level, the K-mean has the results that are strongly depended on the initial values of the centers. To overcome this, this paper used the subtractive clustering approach proposed by Chiu in 1994 to determine the centers. Because the effective radius in Chiu’s method has some influence on the number of centers, the paper applied the PSO technique to find the optimum radius. To valid the proposed approach, the test on well-known data samples is carried out. The applications for daily load curves of one Southern utility are presented.
A Compact Planar Low-Pass Filter Based on SRR-Metamateria
Badr Nasiri;
Ahmed Errkik;
Jamal Zbitou;
Abdelali Tajmouati;
Larbi El Abdellaoui;
Mohamed Latrach
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.pp4972-4980
In this work, a novel design of a Microstrip Low-pass filter based on metamaterial square split ring resonators (SRRs) is proposed. The SRRs has been added to obtain a reduced size and high performances. The filter is designed on an FR-4 substrate having a thickness of 1.6mm, a dielectric constant of 4.4 and loss tangent of 0.025. The proposed low-pass filter is characterized by a cutoff frequency of 2.4 GHz and an attenuation level below than -20dB in the stopband. The LPF is designed, simulated and optimized by using two electromagnetic solvers CST microwave studio and ADS. The computed results obtained by both solvers are in good agreement. The total surface area of the proposed circuit is 18x18mm2 excluding the feed line, its size is miniaturized by 40% compared to the conventional filter. The experimental results illustrate that the filter achieves very good electrical performances in the passband with a low insertion loss of 0.2 dB. Moreover, a suppression level can reach more than 35 dB in the rejected band.
Misusability Measure Based Sanitization of Big Data for Privacy Preserving MapReduce Programming
D. Radhika;
D. Aruna Kumari
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.pp4524-4532
Leakage and misuse of sensitive data is a challenging problem to enterprises. It has become more serious problem with the advent of cloud and big data. The rationale behind this is the increase in outsourcing of data to public cloud and publishing data for wider visibility. Therefore Privacy Preserving Data Publishing (PPDP), Privacy Preserving Data Mining (PPDM) and Privacy Preserving Distributed Data Mining (PPDM) are crucial in the contemporary era. PPDP and PPDM can protect privacy at data and process levels respectively. Therefore, with big data privacy to data became indispensable due to the fact that data is stored and processed in semi-trusted environment. In this paper we proposed a comprehensive methodology for effective sanitization of data based on misusability measure for preserving privacy to get rid of data leakage and misuse. We followed a hybrid approach that caters to the needs of privacy preserving MapReduce programming. We proposed an algorithm known as Misusability Measure-Based Privacy serving Algorithm (MMPP) which considers level of misusability prior to choosing and application of appropriate sanitization on big data. Our empirical study with Amazon EC2 and EMR revealed that the proposed methodology is useful in realizing privacy preserving Map Reduce programming.
A Survey on Multimedia Content Protection Mechanisms
Gottumukkala Hima Bindu;
Chinta Anuradha;
Patnala S. R. Chandra Murthy
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.pp4204-4211
Cloud computing has emerged to influence multimedia content providers like Disney to render their multimedia services. When content providers use the public cloud, there are chances to have pirated copies further leading to a loss in revenues. At the same time, technological advancements regarding content recording and hosting made it easy to duplicate genuine multimedia objects. This problem has increased with increased usage of a cloud platform for rendering multimedia content to users across the globe. Therefore it is essential to have mechanisms to detect video copy, discover copyright infringement of multimedia content and protect the interests of genuine content providers. It is a challenging and computationally expensive problem to be addressed considering the exponential growth of multimedia content over the internet. In this paper, we surveyed multimedia-content protection mechanisms which throw light on different kinds of multimedia, multimedia content modification methods, and techniques to protect intellectual property from abuse and copyright infringement. It also focuses on challenges involved in protecting multimedia content and the research gaps in the area of cloud-based multimedia content protection.
A Detail Study of Wavelet Families for EMG Pattern Recognition
Jingwei Too;
A. R. Abdullah;
Norhashimah Mohd Saad;
N. Mohd Ali;
H. Musa
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.pp4221-4229
Wavelet transform (WT) has recently drawn the attention of the researchers due to its potential in electromyography (EMG) recognition system. However, the optimal mother wavelet selection remains a challenge to the application of WT in EMG signal processing. This paper presents a detail study for different mother wavelet function in discrete wavelet transform (DWT) and continuous wavelet transform (CWT). Additionally, the performance of different mother wavelet in DWT and CWT at different decomposition level and scale are also investigated. The mean absolute value (MAV) and wavelength (WL) features are extracted from each CWT and reconstructed DWT wavelet coefficient. A popular machine learning method, support vector machine (SVM) is employed to classify the different types of hand movements. The results showed that the most suitable mother wavelet in CWT are Mexican hat and Symlet 6 at scale 16 and 32, respectively. On the other hand, Symlet 4 and Daubechies 4 at the second decomposition level are found to be the optimal wavelet in DWT. From the analysis, we deduced that Symlet 4 at the second decomposition level in DWT is the most suitable mother wavelet for accurate classification of EMG signals of different hand movements.
Wireless Technology for Monitoring Site-specific Landslide in Vietnam
Gian Quoc-Anh;
Nguyen Dinh-Chinh;
Tran Duc-Nghia;
Tran Duc-Tan;
Kieu Nguyen Thi;
Kumbesan Sandrasegaran
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.pp4448-4455
Climate change has caused an increasing number of landslides, especially in the mountainous provinces of Vietnam, resulting in the destruction of vital transport and other infrastructure. Current monitoring and forecasting systems of the meteorology department cannot deliver accurate and reliable forecasts for weather events and issue timely warnings. This paper describes the development of a simple, low cost, and efficient system for monitoring and warning landslide in real-time. The authors focus on the use of wireless and related technologies in the implementation of a technical solution and some of the problems of the wireless sensor network (WSN) related to power consumption. Promising compressed sensing (CS) based solution for landslide monitoring is discussed and evaluated in the paper.
Negative Total Float to Improve a Multi-Objective Integer Non-Linear Programming for Project Scheduling Compression
Fachrurrazi Fachrurrazi;
Abdullah Abdullah;
Yuwaldi Away;
Teuku Budi Aulia
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.pp5292-5302
This paper presents Multi-Objective Integer Non-Linear Programming (MOINLP) involving Negative Total Float (NTF) for improving the basic model of Multi-Objective Programming (MOP) in case the optimization of the additional cost for Project Scheduling Compression (PSC). Using the basic MOP to solve the more complex problems is a challenging task. We suspect that Negative Total Float (NTF) having an indication to make the basic MOP to solve the more general case, both simple and complex of PSC. The purpose of this research is identifying the conflicting objectives in PSC problem using NTF and improving MOINLP by involving the NTF parameter to solve the PSC problem. The Solver Application, which is an add-in of MS Excel, is used to perform optimization process to the model developed. The results show that NTF has an important role to identify the conflicting objectives in PSC. We define NTF is an automatic maximum value of the activity duration reduction to achieve due date of PSC. Furthermore, the use of NTF as a constraint in MOINLP can solve the more general case for both simple and complex PSC problem. Base on the condition, we state that the basic MOP is still significant to solve the PSC complex problems using MOINLP as a sophisticated MOP technique.