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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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Compensation of Voltage Single-Phase SAG and SWELL Using Dynamic Voltage Restorer and Difference Per-Unit Value Method Mohammad Sarvi; Haniyeh Marefatjou
International Journal of Electrical and Computer Engineering (IJECE) Vol 3, No 1: February 2013
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (443.294 KB)

Recently, the demand for high power quality by customers, has increased significantly. Common power equipment to protect sensitive loads against voltage disturbances in distribution networks, which are known by D-FACTS devices include: D-STATCOM , DVR and UPQC. Consequences resulting from industrial processes can be classified into two categories that are, nonlinear and unbalanced loads and high vulnerability to transient faults (such as voltage sag) in distribution systems. DVR is a equipment which was connected in series and adjusting the loading voltage by feeding the voltage in system. The first installation was in 1996. usually DVR installed between sensitive loads feeder and source in distribution system. The main duty, fast support load voltage (by fast detection algorithm) during disturbance to avoid any disconnection. In this paper approaches to compensate for voltage sag and swell as a common disturbance in voltage transmission and distribution networks is presented. A dynamic voltage restorer based on the average detection method for single-phase is discussed, in the other hand this paper describes the effect to using DVR inorder to restoring the voltage sag and swell by difference per-unit value method(average detection) in distribution system. The result of single-phase voltage sag and swell simulation has been presented by SIMULINK/ MATLAB.DOI:http://dx.doi.org/10.11591/ijece.v3i1.2134

Development of portable automatic number plate recognition (ANPR) system on Raspberry Pi S. Fakhar A. G; M. Saad H; A. Fauzan K; R. Affendi H.; M. Aidil A.
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 3: June 2019
Publisher : Institute of Advanced Engineering and Science

ANPR system is used in automating access control and security such as identifying stolen cars in real time by installing it to police patrol cars, and detecting vehicles that are overspeeding on highways. However, this technology is still relatively expensive; in November 2014, the Royal Malaysian Police (PDRM) purchased and installed 20 units of ANPR systems in their patrol vehicles costing nearly RM 30 million. In this paper a cheaper alternative of a portable ANPR system running on a Raspberry Pi with OpenCV library is presented. Once the camera captures an image, image desaturation, filtering, segmentation and character recognition is all done on the Raspberry Pi before the extracted number plate is displayed on the LCD and saved to a database. The main challenges in a portable application include crucial need of an efficient code and reduced computational complexity while offering improved flexibility. The performance time is also presented, where the whole process is run with a noticeable 3 seconds delay in getting the final output.

Using Attribute Oriented Induction High Level Emerging Pattern (AOI-HEP) to Mine Frequent Patterns Harco Leslie Hendric Spits Warnars
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 6: December 2016
Publisher : Institute of Advanced Engineering and Science

Frequent patterns in Attribute Oriented Induction High level Emerging Pattern (AOI-HEP), are recognized when have maximum subsumption target (superset) into contrasting (subset) datasets (contrasting ⊂ target) and having large High Emerging Pattern (HEP) growth rate and support in target dataset. HEP Frequent patterns had been successful mined with AOI-HEP upon 4 UCI machine learning datasets such as adult, breast cancer, census and IPUMS with the number of instances of 48842, 569, 2458285 and 256932 respectively and each dataset has concept hierarchies built from its five chosen attributes. There are 2 and 1 finding frequent patterns from adult and breast cancer datasets, while there is no frequent pattern from census and IPUMS datasets. The finding HEP frequent patterns from adult dataset are adult which have government workclass with an intermediate education (80.53%) and America as native country(33%). Meanwhile, the only 1 HEP frequent pattern from breast cancer dataset is breast cancer which have clump thickness type of AboutAverClump with cell size of VeryLargeSize(3.56%). Finding HEP frequent patterns with AOI-HEP are influenced by learning on high level concept in one of chosen attribute and extended experiment upon adult dataset where learn on marital-status attribute showed that there is no finding frequent pattern.

Estimation of fines amount in syariah criminal offences using adaptive neuro-fuzzy inference system (ANFIS) enhanced with analytic hierarchy process (AHP) Ahmad Fitri Mazlam; Wan Nural Jawahir Hj Wan Yussof; Rabiei Mamat
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 6: December 2019
Publisher : Institute of Advanced Engineering and Science

All syariah criminal cases, especially in khalwat offence have their case-fact, and the judges typically look forward to all the facts which were tabulated by the prosecutors. A variety of criteria is considered by the judge to determine the fines amount that should be imposed on an accused who pleads guilty. In Terengganu, there were ten (10) judges, and the judgments were made by the individual decision upon the trial to decide the case. Each judge has a stake, principles and distinctive criteria in determining fines amount on an accused who pleads guilty and convicted. This research paper presents an Adaptive Neuro-fuzzy Inference System (ANFIS) technique combining with Analytic Hierarchy Process (AHP) for estimating fines amount in Syariah (khalwat) criminal. Datasets were collected under the supervision of registrar and syarie judge in the Department of Syariah Judiciary State Of Terengganu, Malaysia. The results showed that ANFIS+AHP could estimate fines efficiently than the traditional method with a very minimal error.

A Study of Mobile User Movements Prediction Methods J. Venkata Subramanian; S. Govindarajan
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 5: October 2018
Publisher : Institute of Advanced Engineering and Science

For a decade and more, the Number of smart phone users count increasing day by day. With the drastic improvements in Communication technologies, the prediction of future movements of mobile users needs also have important role. Various sectors can gain from this prediction. Communication management, City Development planning, and locationbased services are some of the fields that can be made more valuable with movement prediction. In this paper, we propose a study of several Location Prediction Techniques in the following areas

Flow regulation at constant head in feedwater pumps in a sugar industry Julio R. Gómez; Vladimir Sousa; Mario S. Quintana; Percy R. Viego; Hernán Hernández; Enrique C. Quispe
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 2: April 2019
Publisher : Institute of Advanced Engineering and Science

In this paper the feasibility of energy saving by implementing flow regulation at constant load in feedwater pumps in a sugar industry is studied. As regulation strategy, the use of a variable speed drive in the hydraulic system is proposed. For the project evaluation, the Net Present Value and Payback Period techniques are used. Among the variables considered are the price of energy, the equipment useful life, financial data and those related to environmental impact. As a result, it was found that if only a commercial approach is considered, the energy saving strategy is profitable but not attractive, because investment is recovered in a period close to the useful life of technology. However, if a government focus that encourages the implementation of these energies saving strategies is considered, the investment of the project recovers in a short time.

Comparative Analysis of common Edge Detection Algorithms using Pre-processing Technique R. Vijaya Kumar Reddy; K. Prudvi Raju; M. Jogendra Kumar; L. Ravi Kumar; P Ravi Prakash; S. Sai Kumar
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 5: October 2017
Publisher : Institute of Advanced Engineering and Science

Edge detection is the process of segmenting an image by detecting discontinuities in brightness. So far, several standard segmentation methods have been widely used for edge detection. However, due to inherent quality of images, these methods prove ineffective if they are applied without any preprocessing. In this paper, an image preprocessing approach has been adopted in order to get certain parameters that are useful to perform better edge detection with the standard edge detection methods. The proposed preprocessing approach involves median filtering to reduce the noise in image and then Edge Detection technique is carried out. And atlast Standard edge detection methods can be applied to the resultant preprocessing image and its Simulation results are show that our preprocessed approach when used with a standard edge detection method enhances its performance.

An exploratory research on grammar checking of Bangla sentences using statistical language models M. D. Riazur Rahman; M. D. Tarek Habib; M. D. Sadekur Rahman; Gazi Zahirul Islam; M. D. Abbas Ali Khan
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

N-gram based language models are very popular and extensively used statistical methods for solving various natural language processing problems including grammar checking. Smoothing is one of the most effective techniques used in building a language model to deal with data sparsity problem. Kneser-Ney is one of the most prominently used and successful smoothing technique for language modelling. In our previous work, we presented a Witten-Bell smoothing based language modelling technique for checking grammatical correctness of Bangla sentences which showed promising results outperforming previous methods. In this work, we proposed an improved method using Kneser-Ney smoothing based n-gram language model for grammar checking and performed a comparative performance analysis between Kneser-Ney and Witten-Bell smoothing techniques for the same purpose. We also provided an improved technique for calculating the optimum threshold which further enhanced the the results. Our experimental results show that, Kneser-Ney outperforms Witten-Bell as a smoothing technique when used with n-gram LMs for checking grammatical correctness of Bangla sentences.

Identification of Faults in HVDC System using Wavelet Analysis Satya Narayana; Bonigala Ramesh; Saheb Hussain
International Journal of Electrical and Computer Engineering (IJECE) Vol 2, No 2: April 2012
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (254.109 KB)

The identification and classification of faults is important for safe and optimal operation of power systems. For secure operation of a system a feasible approach is to monitor signals so that accurate and rapid classification of fault is possible for making correct protection control.To identify HVDC faults by using pure frequency or pure time domain based method is difficult. The pure frequency domain based methods are not suitable for time varying transients and the pure time domain based methods are very easily influenced by noise.Wavelet analysis is one of the methods used for providing discriminative features with small dimensions to classify different disturbances in HVDC transmission system. This paper explores the application of wavelet based Multi-Resolution Analysis (MRA) for signal decomposition to monitor some faults in HVDC system. The faults in HVDC system can be classified by monitoring the signals both on AC and DC sides of the HVDC system. The fault classifier can be developed from these monitored signals which show promising features to classify different disturbances in the HVDC system.DOI:http://dx.doi.org/10.11591/ijece.v2i2.179

Conceptual Sentiment Analysis Model Kranti Vithal Ghag; Ketan Shah
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 4: August 2018
Publisher : Institute of Advanced Engineering and Science

Bag-of-words approach is popularly used for Sentiment analysis. It maps the terms in the reviews to term-document vectors and thus disrupts the syntactic structure of sentences in the reviews. Association among the terms or the semantic structure of sentences is also not preserved. This research work focuses on classifying the sentiments by considering the syntactic and semantic structure of the sentences in the review. To improve accuracy, sentiment classifiers based on relative frequency, average frequency and term frequency inverse document frequency were proposed. To handle terms with apostrophe, preprocessing techniques were extended. To focus on opinionated contents, subjectivity extraction was performed at phrase level. Experiments were performed on Pang & Lees, Kaggle’s and UCI’s dataset. Classifiers were also evaluated on the UCI’s Product and Restaurant dataset. Sentiment Classification accuracy improved from 67.9% for a comparable term weighing technique, DeltaTFIDF, up to 77.2% for proposed classifiers. Inception of the proposed concept based approach, subjectivity extraction and extensions to preprocessing techniques, improved the accuracy to 93.9%.

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Home Page

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Contact Name Tole Sutikno

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Location Kota yogyakarta, Daerah istimewa yogyakarta INDONESIA

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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