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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 6,301 Documents
Change Detection from Remotely Sensed Images Based on Stationary Wavelet Transform Abhishek Sharma; Tarun Gulati
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 6: December 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (638.341 KB) | DOI: 10.11591/ijece.v7i6.pp3395-3401

Abstract

The major issue of concern in change detection process is the accuracy of the algorithm to recover changed and unchanged pixels. The fusion rules presented in the existing methods could not integrate the features accurately which results in more number of false alarms and speckle noise in the output image. This paper proposes an algorithm which fuses two multi-temporal images through proposed set of fusion rules in stationary wavelet transform. In the first step, the source images obtained from log ratio and mean ratio operators are decomposed into three high frequency sub-bands and one low frequency sub-band by stationary wavelet transform. Then, proposed fusion rules for low and high frequency sub-bands are applied on the coefficient maps to get the fused wavelet coefficients map. The fused image is recovered by applying the inverse stationary wavelet transform (ISWT) on the fused coefficient map. Finally, the changed and unchanged areas are classified using Fuzzy c means clustering. The performance of the algorithm is calculated in terms of percentage correct classification (PCC), overall error (OE) and Kappa coefficient (Kc). The qualitative and quantitative results prove that the proposed method offers least error, highest accuracy and Kappa value as compare to its preexistences.
Deep-learning based single object tracker for night surveillance Zulaikha Kadim; Mohd Asyraf Zulkifley; Nabilah Hamzah
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (879.699 KB) | DOI: 10.11591/ijece.v10i4.pp3576-3587

Abstract

Tracking an object in night surveillance video is a challenging task as the quality of the captured image is normally poor with low brightness and contrast. The task becomes harder for a small object as fewer features are apparent. Traditional approach is based on improving the image quality before tracking is performed. In this paper, a single object tracking algorithm based on deep-learning approach is proposed to exploit its outstanding capability of modelling object’s appearance even during night. The algorithm uses pre-trained convolutional neural networks coupled with fully connected layers, which are trained online during the tracking so that it is able to cater for appearance changes as the object moves around. Various learning hyperparameters for the optimization function, learning rate and ratio of training samples are tested to find optimal setup for tracking in night scenarios. Fourteen night surveillance videos are collected for validation purpose, which are captured from three viewing angles. The results show that the best accuracy is obtained by using Adam optimizer with learning rate of 0.00075 and sampling ratio of 2:1 for positive and negative training data. This algorithm is suitable to be implemented in higher level surveillance applications such as abnormal behavioral recognition.
Memetic chicken swarm algorithm for job shop scheduling problem Soukaina Cherif Bourki Semlali; Mohammed Essaid Riffi; Fayçal Chebihi
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 3: June 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (269.568 KB) | DOI: 10.11591/ijece.v9i3.pp2075-2082

Abstract

This paper presents a Memetic Chicken swarm optimization (MeCSO) to solve job shop scheduling problem (JSSP). The aim is to find a better solution which minimizes the maximum of the completion time also called Makespan. In this paper, we adapt the chicken swarm algorithm which take into consideration the hierarchical order of chicken swarm while seeking for food. Moreover, we integrate 2-opt method to improve the movement of the rooster. The new algorithm is applied on some instances of ORLibrary. The empirical results show the forcefulness of MeCSO comparing to other metaheuristics from literature in term of run time and quality of solution.
Fault Detection Approaches to Power System: State-of-the-Art Article Reviews for Searching a New Approach in the Future Pituk Bunnoon
International Journal of Electrical and Computer Engineering (IJECE) Vol 3, No 4: August 2013
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (150.962 KB)

Abstract

This paper proposes the state-of-the-art of fault detection approach a power system. Severalarticles presented it in each implementation and method from the last to present (2013). Theadvantage of the approach would be developed to the new detection in the future. Manyinterested topics used for detection of fault in the power system. In this research can beclassified into two types interesting in fault detection. This review of many paper will beused to develop the research or find the new method for an appropriate fault detection in thepower system.DOI:http://dx.doi.org/10.11591/ijece.v3i4.3195
Power Quality Enhancement of Integration Photovoltaic Generator to Grid under Variable Solar Irradiance Level using MPPT-Fuzzy Amirullah Amirullah; Agus Kiswantono
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 6: December 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1044.067 KB) | DOI: 10.11591/ijece.v6i6.pp2629-2642

Abstract

The paper presents power quality enhancement on low voltage of three phase grid caused by PV generator integration under variabel solar irradiance level on constant temperature and load. MPPT Fuzzy helps to generate duty cycle to control DC/DC boost converter of PV generators. This model was expected to improve power quality due to unbalance voltage and current, low voltage and current harmonics, and low input power factor. There were eigth scenarios PV generator connected to three phase grid using MPPT Fuzzy and compared with MPPT P and O. The research results that application of two methods on different irradiance and PV generator integration level produces unbalanced voltage value stable at 0%. At the same conditions, the use of MPPT Fuzzy results unbalanced current was greater than MPPT P and O. On solar irradiance level fixed, the greater number of PV generator connected to three-phase grid, then value of average voltage and current harmonics (THD) will increases. At the level of solar radiation increases, average grid voltage and current THD also have increased. The average grid voltage and current THD was reduced after using MPPT Fuzzy. The application of MPPT Fuzzy was able to enhance profile of grid voltage and current THD due to integration of a number of PV generator to three phase grid corresponding with IEEE Standard 519-1992. MPPT Fuzzy was capable to improve input power factor better than MPPT P and O.
An implementation of optimal control methods (LQI, LQG, LTR) for geostationary satellite attitude control Farid Djaballah; M. A. Si Mohammed; Nabil Boughanmi
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 6: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1029.813 KB) | DOI: 10.11591/ijece.v9i6.pp4728-4737

Abstract

This paper investigates a new strategy for geostationary satellite attitude control using Linear Quadratic Gaussian (LQG), Loop Transfer Recovery (LTR), and Linear Quadratic Integral (LQI) control techniques. The sub-system satellite attitude determination and control of a geostationary satellite in the presence of external disturbances, the dynamic model of sub-satellite motion is firstly established by Euler equations. During the flight mission at 35000 Km attitude, the stability characteristics of attitude motion are analyzed with a large margin error of pointing, then a height performance-order LQI, LQG and LTR attitude controller are proposed to achieve stable control of the sub-satellite attitude, which dynamic model is linearized by using feedback linearization method. Finally, validity of the LTR order controller and the advantages over an integer order controller are examined by numerical simulation. Comparing with the corresponding integer order controller (LQI, LQG), numerical simulation results indicate that the proposed sub-satellite attitude controller based on LTR order can not only stabilize the sub-satellite attitude, but also respond faster with smaller overshoot. 
A Deterministic Eviction Model for Removing Redundancies in Video Corpus Jyoti Malhotra; Jagdish Bakal
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 5: October 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (321.432 KB) | DOI: 10.11591/ijece.v8i5.pp3221-3231

Abstract

The traditional storage approaches are being challenged by huge data volumes. In multimedia content, every file does not necessarily get tagged as an exact duplicate; rather they are prone to editing and resulting in similar copies of the same file. This paper proposes the similarity-based deduplication approach to evict similar duplicates from the archive storage, which compares the samples of binary hashes to identify the duplicates. This eviction is done by initially dividing the query video into dynamic key frames based on the video length. Binary hash codes of these frames are then compared with existing key frames to identify the differences. The similarity score is determined based on these differences, which decides the eradication strategy of duplicate copy. Duplicate elimination goes through two levels, namely removal of exact duplicates and similar duplicates. The proposed approach has shortened the comparison window by comparing only the candidate hash codes based on the dynamic key frames and aims the accurate lossless duplicate removals. The presented work is executed and tested on the produced synthetic video dataset. Results show the reduction in redundant data and increase in the storage space. Binary hashes and similarity scores contributed to achieving good deduplication ratio and overall performance.
Failure prediction of e-banking application system using adaptive neuro fuzzy inference system (ANFIS) Yuwono Abdillah; Suharjito Suharjito
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 1: February 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1199.981 KB) | DOI: 10.11591/ijece.v9i1.pp667-675

Abstract

Problems often faced by IT operation unit is the difficulty in determining the cause of the failure of an incident such as slowing access to the internet banking url, non-functioning of some features of m-banking or even the cessation of the entire e-banking service. The proposed method to modify ANFIS with Fuzzy C-Means Clustering (FCM) approach is applied to detect four typical kinds of faults that may happen in the e-banking system, which are application response times, transaction per second, server utilization and network performance. Input data is obtained from the e-banking monitoring results throughout 2017 that become data training and data testing. The study shows that an ANFIS modeling with FCM optimized input has a RMSE 0.006 and  increased accuracy by 1.27% compared to ANFIS without FCM optimization.
Novel Optimization to Reduce Power Drainage in Mobile Devices for Multicarrier-based Communication Shalini Prasad; S Balaji
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 5: October 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (431.005 KB) | DOI: 10.11591/ijece.v7i5.pp2401-2410

Abstract

With increasing adoption of multicarrier-based communications e.g. 3G and 4G, the users are significantly benefited with impressive data rate but at the cost of battery life of their mobile devices. We reviewed the existing techniques to find an open research gap in this regard. This paper presents a novel framework where an optimization is carried out with the objective function to maintain higher level of equilibrium between maximized data delivery and minimized transmit power. An analytical model considering multiple radio antennae in the mobile device is presented with constraint formulations of data quality and threshold power factor. The model outcome is evaluated with respect to amount of power being conserved as performance factor. The study was found to offer maximum energy conservation and the framework also suits well with existing communication system of mobile networks.
Improved handoff mechanism for infiltrating user equipments in composite networks Venkata Vara Prasad Padyala; K.V.D. Kiran
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (686.478 KB) | DOI: 10.11591/ijece.v10i3.pp2600-2606

Abstract

The wireless technology and communication plays a vital role in our daily life. The end users are expecting more Quality of Experience (QOE) rather than the Quality of Service (QOS). In order to provide full signal coverage the entire cellular network coverage is divided in to small cells called as femtocells, those femtocells are covered with femtocell antennas which are very small in size compared with regular antennas. With these femtocell coverage problem is solved but when a user moves from one location to another location the user has to switch from one base station to so many base station which cannot be maintained with present handoff methods. The present hand off methods working on distance calculation approach, the proposed method is based on the velocity and device direction calculated based on GPS location toward the Base Station (BS) of the device which may ping pong handoff effect.

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