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International Journal of Electrical and Computer Engineering
ISSN : 20888708     EISSN : 27222578     DOI : -
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 75 Documents
Search results for , issue "Vol 8, No 4: August 2018" : 75 Documents clear
Coal-Fired Boiler Fault Prediction using Artificial Neural Networks Nong Nurnie Mohd Nistah; King Hann Lim; Lenin Gopal; Firas Basim Ismail Alnaimi
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 4: August 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (688.597 KB) | DOI: 10.11591/ijece.v8i4.pp2486-2493

Abstract

Boiler fault is a critical issue in a coal-fired power plant due to its high temperature and high pressure characteristics. The complexity of boiler design increases the difficulty of fault investigation in a quick moment to avoid long duration shut-down. In this paper, a boiler fault prediction model is proposed using artificial neural network. The key influential parameters analysis is carried out to identify its correlation with the performance of the boiler. The prediction model is developed to achieve the least misclassification rate and mean squared error. Artificial neural network is trained using a set of boiler operational parameters. Subsequenlty, the trained model is used to validate its prediction accuracy against actual fault value from a collected real plant data. With reference to the study and test results, two set of initial weights have been tested to verify the repeatability of the correct prediction. The results show that the artificial neural network implemented is able to provide an average of above 92% prediction rate of accuracy.
Performance Evaluation of Two Port and Four Port Measurement for Twisted Pair Cable Azhari Bin Asrokin; Mohamad Kamal Bin A. Rahim
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 4: August 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1087.008 KB) | DOI: 10.11591/ijece.v8i4.pp2624-2632

Abstract

A balance-unbalance (balun) transformer is commonly used to connect the balance 100 Ohm twisted pair cable to the unbalance 50 Ohm network analyzer ports, but due to the limitations of the core (i.e. ferrite) inside the balun, the balun can only effectively operates at a certain band of frequencies. This limitation can be eliminated by using a 4-port vector network analyzer (VNA) which is done by connecting the VNA’s ports to each conductor end. The extracted S-parameters will then be transformed to a 2-port S-parameters in differential mode at both ports. To validate the measurement technique, S-parameter measurement by using the 4-Port Network Analyzer without any balun will be compared to the measurement which used the 2-Port Network Analyzer with the balun transformers. Two twisted pair cable distances are selected as reference which are 500, and 1000 meters with nominal copper diameter of 0.5mm. Based on the measurement results, the 4-ports measurement shows good correlation with the 2-ports measurement especially at 500m distance. This shows that the 4-ports measurement setup is suitable to be used to measure twisted pair copper cable and possible to measure at a higher frequency band such as up to 500 MHz but at a shorter twisted pair cable distance.
Extensive Analysis on Generation and Consensus Mechanisms of Clustering Ensemble: A Survey Yalamarthi Leela Sandhya Rani; V. Sucharita; K. V. V. Satyanarayana
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 4: August 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (376.886 KB) | DOI: 10.11591/ijece.v8i4.pp2351-2357

Abstract

Data analysis plays a prominent role in interpreting various phenomena. Data mining is the process to hypothesize useful knowledge from the extensive data. Based upon the classical statistical prototypes the data can be exploited beyond the storage and management of the data. Cluster analysis a primary investigation with little or no prior knowledge, consists of research and development across a wide variety of communities. Cluster ensembles are melange of individual solutions obtained from different clusterings to produce final quality clustering which is required in wider applications. The method arises in the perspective of increasing robustness, scalability and accuracy. This paper gives a brief overview of the generation methods and consensus functions included in cluster ensemble. The survey is to analyze the various techniques and cluster ensemble methods.
Throughput Maximization of Cognitive Radio Multi Relay Network with Interference Management Pradip Varade; Akanksha Wabale; Ravinder Yerram; Rupesh Jaiswal
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 4: August 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (334.763 KB) | DOI: 10.11591/ijece.v8i4.pp2230-2238

Abstract

In this paper, an Orthogonal Frequency Division Multiplexing (OFDM) based cognitive multi relay network is investigated to maximize the transmission rate of the cognitive radio (CR) with enhanced  fairness among CR users  with interference to the primary users (PUs) being managed below a certain threshold level. In order to improve the transmission rate of the CR, optimization of the subcarrier pairing and power allocation is to be carried out simultaneously. Firstly joint optimization problem is formulated and Composite Genetic and Ordered Subcarrier Pairing (CGOSP) algorithm is proposed to solve the problem. The motivation behind merging genetic and OSP algorithm is to reduce the complexity of Genetic Algorithm (GA). Further, to have a fair allocation of resources among CR users, the Round Robin allocation method is adopted so as to allocate subcarrier pairs to relays efficiently. The degree of fairness of the system is calculated using Jain’s Fairness Index (JFI). Simulation results demonstrate the significant improvement in transmission rate of the CR, low computational complexity and enhanced fairness.
A Survey: Data Leakage Detection Techniques K. S. Wagh
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 4: August 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (295.481 KB) | DOI: 10.11591/ijece.v8i4.pp2247-2253

Abstract

Data is an important property of various organizations and it is intellectual property of organization. Every organization includes sensitive data as customer information, financial data, data of patient, personal credit card data and other information based on the kinds of management, institute or industry. For the areas like this, leakage of information is the crucial problem that the organization has to face, that poses high cost if information leakage is done. All the more definitely, information leakage is characterize as the intentional exposure of individual or any sort of information to unapproved outsiders. When the important information is goes to unapproved hands or moves towards unauthorized destination. This will prompts the direct and indirect loss of particular industry in terms of cost and time. The information leakage is outcomes in vulnerability or its modification. So information can be protected by the outsider leakages. To solve this issue there must be an efficient and effective system to avoid and protect authorized information. From not so long many methods have been implemented to solve same type of problems that are analyzed here in this survey.  This paper analyzes little latest techniques and proposed novel Sampling algorithm based data leakage detection techniques.
A Blind Multiple Watermarks based on Human Visual Characteristics Ferda Ernawan; Siau-Chuin Liew; Zuriani Mustaffa; Kohbalan Moorthy
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 4: August 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (689.989 KB) | DOI: 10.11591/ijece.v8i4.pp2578-2587

Abstract

Digital watermarking is an alternative solution to prevent unauthorized duplication, distribution and breach of ownership right. This paper proposes a watermarking scheme for multiple watermarks embedding. The embedding of multiple watermarks use a block-based scheme based on human visual characteristics. A threshold is used to determine the watermark values by modifying first column of the orthogonal U matrix obtained from Singular Value Decomposition (SVD). The tradeoff between normalize cross-correlation and imperceptibility of watermarked image from quantization steps was used to achieve an optimal threshold value. The results show that our proposed multiple watermarks scheme exhibit robustness against signal processing attacks. The proposed scheme demonstrates that the watermark recovery from chrominance blue was resistant against different types of attacks.
A Comprehensive Survey on Exiting Solution Approaches towards Security and Privacy Requirements of IoT Rajani Chetan; Ramesh Shahabadkar
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 4: August 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (365.193 KB) | DOI: 10.11591/ijece.v8i4.pp2319-2326

Abstract

‘Internet of Things (IoT)’emerged as an intelligent collaborative computation and communication between a set of objects capable of providing on-demand services to other objects anytime anywhere. A large-scale deployment of data-driven cloud applications as well as automated physical things such as embed electronics, software, sensors and network connectivity enables a joint ubiquitous and pervasive internet-based computing systems well capable of interacting with each other in an IoT. IoT, a well-known term and a growing trend in IT arena certainly bring a highly connected global network structure providing a lot of beneficial aspects to a user regarding business productivity, lifestyle improvement, government efficiency, etc. It also generates enormous heterogeneous and homogeneous data needed to be analyzed properly to get insight into valuable information. However, adoption of this new reality (i.e., IoT) by integrating it with the internet invites a certain challenges from security and privacy perspective. At present, a much effort has been put towards strengthening the security system in IoT still not yet found optimal solutions towards current security flaws. Therefore, the prime aim of this study is to investigate the qualitative aspects of the conventional security solution approaches in IoT. It also extracts some open research problems that could affect the future research track of IoT arena.
A Passive Islanding Detection Method for Neutral point clamped Multilevel Inverter based Distributed Generation using Rate of Change of Frequency Analysis Ch. Rami Reddy; K. Harinadha Reddy
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 4: August 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (799.764 KB) | DOI: 10.11591/ijece.v8i4.pp1967-1976

Abstract

Presently renewable energies have taken a special place in the world and most of the Distributed Generations (DGs) used in the interconnected power system are utilized, renewable energy resources. Due to the DG’s advantages, including use of renewable energy such as, clean nature, does not pollute environment and having endless nature the use of these renewable resources to produce electrical energy in the world are increasing in day to day life. One problem with such Distributed generators is an unintentional islanding phenomenon. Islanding occurs when a Distributed Generation continues to energize an isolated part of a power system even after it was disconnected from the main grid, which is surrounded by unpowered lines. Since islanding can cause hazardous conditions for people and equipment which is connected to it. As per IEEE 1547 DG Interconnection standards, islanding should be quickly detected within 2 seconds, by protective relays and inverters that are part of the DG system. In this paper, a new passive method to identify islanding states has been proposed, based on the rate of change of frequency analysis (ROCOF) for a multilevel inverter based solar distributed generation systems. This method is efficient for both connecting DGs to the network with or without the Inverter. This method is more efficient than the existing methods and reducing the Non Detection Zone (NDZ), which is the disadvantage of existing passive methods and also clearly differentiating between the Islanding and Non-islanding events. The simulation results, which are carried on the MATLAB/Simulink environment shows the performance of the proposed method.
Services Modeling based on SOA and BPM for Information System Flexibility Improvement Ahmad Nurul Fajar; Nilo Legowo
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 4: August 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (264.458 KB) | DOI: 10.11591/ijece.v8i4.pp2451-2455

Abstract

The lack of  identify services mechanism which is related to the development of information systems could be impact in wasting time, over budget and can not adapt to the changing environment. This phenomenon is happened by the belief that lack of capturing user requirement. This is due to consider the business environment is always running normally. In fact, the development of the system needs a way to anticipate the business environment that unpredictable changes.Therefore, the phenomenon on the need for modeling services can able to respond to the changing needs of users still have a chancein this study. It explores modeling services to synergize SOA and BPM.Several previous studies generally use a business driven approach, technical partially driven to develop the service modeling. This leads to the question of how a service should be modeled so that it can be applied in different contexts and business processes also. It is support user needs in diversity and heterogeneous system environments. This Conditions occurs in corporate university. The case studies in this research is a Learning Management System (LMS) in Academic Enterprise System (EAS). The research stages are: (1) Analysis of Synergy in SOA and BPM, (2) Analysis of User Experience in LMS Academic Enterprise System (L-EAS), (3) Analysis of Modeling Framework, (4) Proposed Framework that aligning SOA and BPM. The result of this study is proposed system framework based on services to increase the flexibility of information systems at LMS Academic Enterprise System (L-EAS).
Real-Time Video Processing using Contour Numbers and Angles for Non-urban Road Marker Classification Zamani Md Sani; Hadhrami Abd Ghani; Rosli Besar; Azizul Azizan; Hafiza Abas
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 4: August 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (580.324 KB) | DOI: 10.11591/ijece.v8i4.pp2540-2548

Abstract

Road users make vital decisions to safely maneuver their vehicles based on the road markers, which need to be correctly classified. The road markers classification is significantly important especially for the autonomous car technology. The current problems of extensive processing time and relatively lower average accuracy when classifying up to five types of road markers are addressed in this paper. Two novel real time video processing methods are proposed by extracting two formulated features namely the contour number, , and angle, ???? to classify the road markers. Initially, the camera position is calibrated to obtain the best Field of View (FOV) for identifying a customized Region of Interest (ROI). An adaptive smoothing algorithm is performed on the ROI before the contours of the road markers and the corresponding two features are determined. It is observed that the achievable accuracy of the proposed methods at several non-urban road scenarios is approximately 96% and the processing time per frame is significantly reduced when the video resolution increases as compared to that of the existing approach.

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