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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 6,301 Documents

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An Optimal LFC in Two-Area Power Systems Using a Meta-heuristic Optimization Algorithm Mushtaq Najeeb; Muhamad Mansor; Hameed Feyad; Esam Taha; Ghassan Abdullah
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 6: December 2017
Publisher : Institute of Advanced Engineering and Science

In this study, an optimal meta-heuristic optimization algorithm for load frequency control (LFC) is utilized in two-area power systems. This meta-heuristic algorithm is called harmony search (HS), it is used to tune PI controller parameters ( ) automatically. The developed controller (HS-PI) with LFC loop is very important to minimize the system frequency and keep the system power is maintained at scheduled values under sudden loads changes. Integral absolute error (IAE) is used as an objective function to enhance the overall system performance in terms of settling time, maximum deviation, and peak time. The two-area power systems and developed controller are modelled using MATLAB software (Simulink/Code). As a result, the developed control algorithm (HS-PI) is more robustness and efficient as compared to PSO-PI control algorithm under same operation conditions.

A Novel automatic voice recognition system based on text-independent in a noisy environment Motaz Hamza; Touraj Khodadadi; Sellappan Palaniappan
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Automatic voice recognition system aims to limit fraudulent access to sensitive areas as labs. Our primary objective of this paper is to increase the accuracy of the voice recognition in noisy environment of the Microsoft Research (MSR) identity toolbox. The proposed system enabled the user to speak into the microphone then it will match unknown voice with other human voices existing in the database using a statistical model, in order to grant or deny access to the system. The voice recognition was done in two steps: training and testing. During the training a Universal Background Model as well as a Gaussian Mixtures Model: GMM-UBM models are calculated based on different sentences pronounced by the human voice (s) used to record the training data. Then the testing of voice signal in noisy environment calculated the Log-Likelihood Ratio of the GMM-UBM models in order to classify user's voice. However, before testing noise and de-noise methods were applied, we investigated different MFCC features of the voice to determine the best feature possible as well as noise filter algorithm that subsequently improved the performance of the automatic voice recognition system.

Modified honey encryption scheme for encoding natural language message Abiodun Esther Omolara; Aman Jantan
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 3: June 2019
Publisher : Institute of Advanced Engineering and Science

Conventional encryption schemes are susceptible to brute-force attacks. This is because bytes encode utf8 (or ASCII) characters. Consequently, an adversary that intercepts a ciphertext and tries to decrypt the message by brute-forcing with an incorrect key can filter out some of the combinations of the decrypted message by observing that some of the sequences are a combination of characters which are distributed non-uniformly and form no plausible meaning. Honey encryption (HE) scheme was proposed to curtail this vulnerability of conventional encryption by producing ciphertexts yielding valid-looking, uniformly distributed but fake plaintexts upon decryption with incorrect keys. However, the scheme works for only passwords and PINS. Its adaptation to support encoding natural language messages (e-mails, human-generated documents) has remained an open problem. Existing proposals to extend the scheme to support encoding natural language messages reveals fragments of the plaintext in the ciphertext, hence, its susceptibility to chosen ciphertext attacks (CCA). In this paper, we modify the HE schemes to support the encoding of natural language messages using Natural Language Processing techniques. Our main contribution was creating a structure that allowed a message to be encoded entirely in binary. As a result of this strategy, most binary string produces syntactically correct messages which will be generated to deceive an attacker who attempts to decrypt a ciphertext using incorrect keys. We evaluate the security of our proposed scheme.

Effect of Functionally Graded Material of Disc Spacer with Presence of Multi-Contaminating Particles on Electric Field inside Gas Insulated Bus Duct Mousa Awad Allah Abd Allah; Sayed Abo El Saood Ward; Amr Ameen Youssef
International Journal of Electrical and Computer Engineering (IJECE) Vol 3, No 6: December 2013
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2056.515 KB)

Solid insulators play a crucial role of electrical insulation in gas insulated power equipment. In order to improve the insulation performance of the solid insulators, two technical points should be considered, the first is the improvement of the insulation performance and the second is the control of the electric field distribution in and around the solid insulating spacers. Practically the insulation performance around the spacer can be improved by various techniques, such as; controlling the spacer shape, adding shield electrodes for electric field relaxation, the introduction of an embedded electrode, etc. These techniques lead to a more complicated structure of the equipment and increase the manufacturing cost. Thus, it is necessary to propose a new concept on solid spacers with keeping their simple structure and configuration. In this paper, a functionally graded material (FGM) is proposed to minimize the electric field distribution around the spacer, specially, on triple junction point, which was one of the important factors dominating a long-term insulating property of solid delectric. Finite Element Method (FEM) has been used throughout this work, for its favorable accuracy, to calculate the electric field distribution inside the bus duct. The Electric field distribution around earthed particle contamination which adhered to uniform and FGM of disc-spacer is presented. The effect of distance between particle and spacer on the electric field values is investigated. The effect of hemi-spherical radius and length of particle on maximum electric field at triple junction point is also discussed. Electric field relaxation effect (EFGM/Euniform) by introduction of the U-shape FGM spacer is also presented. The electric field distribution along the surface of FGM of disc spacer with presence of multi-contaminating particles at various positions is presented.DOI:http://dx.doi.org/10.11591/ijece.v3i6.4354

Recommender Systems in Light of Big Data Khadija A. Almohsen; Huda Al-Jobori
International Journal of Electrical and Computer Engineering (IJECE) Vol 5, No 6: December 2015
Publisher : Institute of Advanced Engineering and Science

The growth in the usage of the web, especially e-commerce website, has led to the development of recommender system (RS) which aims in personalizing the web content for each user and reducing the cognitive load of information on the user. However, as the world enters Big Data era and lives through the contemporary data explosion, the main goal of a RS becomes to provide millions of high quality recommendations in few seconds for the increasing number of users and items. One of the successful techniques of RSs is collaborative filtering (CF) which makes recommendations for users based on what other like-mind users had preferred. Despite its success, CF is facing some challenges posed by Big Data, such as: scalability, sparsity and cold start. As a consequence, new approaches of CF that overcome the existing problems have been studied such as Singular value decomposition (SVD). This paper surveys the literature of RSs and reviews the current state of RSs with the main concerns surrounding them due to Big Data. Furthermore, it investigates thoroughly SVD, one of the promising approaches expected to perform well in tackling Big Data challenges, and provides an implementation to it using some of the successful Big Data tools (i.e. Apache Hadoop and Spark). This implementation is intended to validate the applicability of, existing contributions to the field of, SVD-based RSs as well as validated the effectiveness of Hadoop and spark in developing large-scale systems. The implementation has been evaluated empirically by measuring mean absolute error which gave comparable results with other experiments conducted, previously by other researchers, on a relatively smaller data set and non-distributed environment. This proved the scalability of SVD-based RS and its applicability to Big Data.

Automatic summarization of Malayalam documents using clause identification method Sunitha C; A Jaya; Amal Ganesh
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 6: December 2019
Publisher : Institute of Advanced Engineering and Science

Text summarization is an active research area in the field of natural language processing. Huge amount of information in the internet necessitates the development of automatic summarization systems. There are two types of summarization techniques: Extractive and Abstractive. Extractive summarization selects important sentences from the text and produces summary as it is present in the original document. Abstractive summarization systems will provide a summary of the input text as is generated by human beings. Abstractive summary requires semantic analysis of text. Limited works have been carried out in the area of abstractive summarization in Indian languages especially in Malayalam. Only extractive summarization methods are proposed in Malayalam. In this paper, an abstractive summarization system for Malayalam documents using clause identification method is proposed. As part of this research work, a POS tagger and a morphological analyzer for Malayalam words in cricket domain are also developed. The clauses from input sentences are identified using a modified clause identification algorithm. The clauses are then semantically analyzed using an algorithm to identify semantic triples - subject, object and predicate. The score of each clause is then calculated by using feature extraction and the important clauses which are to be included in the summary are selected based on this score. Finally an algorithm is used to generate the sentences from the semantic triples of the selected clauses which is the abstractive summary of input documents.

Wave File Features Extraction using Reduced LBP Aws Al-Qaisi; Saleh A. Khawatreh; Ahmad A. Sharadqah; Ziad A. Alqadi
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 5: October 2018
Publisher : Institute of Advanced Engineering and Science

In this work, we present a novel approach for extracting features of a digital wave file. This approach will be presented, implemented and tested. A signature or a key to any wave file will be created. This signature will be reduced to minimize the efforts of digital signal processing applications. Hence, the features array can be used as key to recover a wave file from a database consisting of several wave files using reduced Local binary patterns (RLBP). Experimental results are presented and show that The proposed RLBP method is at least 3 times faster than CSLBP method, which mean that the proposed method is more efficient.

Negative image amplifier technique for performance enhancement of ultra wideband LNA Kishor G. Sawarkar; Kushal R. Tuckley
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 1: February 2019
Publisher : Institute of Advanced Engineering and Science

The paper aims at designing of two stage cascaded ultra-wideband (UWB) low noise amplifier (LNA) by using negative image amplifier technique. The objective of this article is to show the performance improvement using negative image amplifier technique and realization of negative valued lumped elements into microstrip line geometry. The innovative technique to realize the negative lumped elements are carried out by using Richard’s Transformation and transmission line calculation. The AWR microwave office tool is used to obtain characteristics of UWB LNA design with hybrid microwave integrated circuit (HMIC) technology. The 2-stage cascaded LNA design using negative image amplifier technique achieves average gain of 23dB gain and low noise figure of less than 2dB with return loss less than -8dB for UWB 3-10GHz. The Proper bias circuit is extracted using DC characteristics of transistor at biasing point 2V, 20mA and discussed in detail with LNA layout. The negative image matching technique is applied for both input and output matching network. This work will be useful for all low power UWB wireless receiver applications.

Single Channel Speech Enhancement using Wiener Filter and Compressive Sensing Amart Sulong; Teddy Surya Gunawan; Othman O Khalifa; Mira Kartiwi; Hassan Dao
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 4: August 2017
Publisher : Institute of Advanced Engineering and Science

The speech enhancement algorithms are utilized to overcome multiple limitation factors in recent applications such as mobile phone and communication channel. The challenges focus on corrupted speech solution between noise reduction and signal distortion. We used a modified Wiener filter and compressive sensing (CS) to investigate and evaluate the improvement of speech quality. This new method adapted noise estimation and Wiener filter gain function in which to increase weight amplitude spectrum and improve mitigation of interested signals. The CS is then applied using the gradient projection for sparse reconstruction (GPSR) technique as a study system to empirically investigate the interactive effects of the corrupted noise and obtain better perceptual improvement aspects to listener fatigue with noiseless reduction conditions. The proposed algorithm shows an enhancement in testing performance evaluation of objective assessment tests outperform compared to other conventional algorithms at various noise type conditions of 0, 5, 10, 15 dB SNRs. Therefore, the proposed algorithm significantly achieved the speech quality improvement and efficiently obtained higher performance resulting in better noise reduction compare to other conventional algorithms.

Botnet detection using ensemble classifiers of network flow Zahraa M. Algelal; Eman Abdulaziz Ghani Aldhaher; Dalia N. Abdul-Wadood; Radhwan Hussein Abdulzhraa Al-Sagheer
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Recently, Botnets have become a common tool for implementing and transferring various malicious codes over the Internet. These codes can be used to execute many malicious activities including DDOS attack, send spam, click fraud, and steal data. Therefore, it is necessary to use Modern technologies to reduce this phenomenon and avoid them in advance in order to differentiate the Botnets traffic from normal network traffic. In this work, ensemble classifier algorithms to identify such damaging botnet traffic. We experimented with different ensemble algorithms to compare and analyze their ability to classify the botnet traffic from the normal traffic by selecting distinguishing features of the network traffic. Botnet Detection offers a reliable and cheap style for ensuring transferring integrity and warning the risks before its occurrence.

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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