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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 126 Documents
Search results for , issue "Vol 9, No 4: August 2019" : 126 Documents clear
Business recommendation based on collaborative filtering and feature engineering – aproposed approach Prakash Pandharinath Rokade; Aruna Kumari D
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 4: August 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (463.855 KB) | DOI: 10.11591/ijece.v9i4.pp2614-2619

Abstract

Business decisions for any service or product depend on sentiments by people. We get these sentiments or rating on social websites like twitter, kaggle.  The mood of people towards any event, service and product are expressed in these sentiments or rating. The text of sentiment contains different linguistic features of sentence. A sentiment sentence also contains other features which are playing a vital role in deciding the polarity of sentiments. If features selection is proper one can extract better sentiments for decision making. A directed preprocessing will feed filtered input to any machine learning approach. Feature based collaborative filtering can be used for better sentiment analysis. Better use of parts of speech (POS) followed by guided preprocessing and evaluation will minimize error for sentiment polarity and hence the better recommendation to the user for business analytics can be attained.
Live and Dead Cells Counting from Microscopic Trypan Blue Staining Images using Thresholding and Morphological Operation Techniques Su Mon Aung; Kanyanatt Kanokwiroon; Tonghathai Phairatana; Surapong Chatpun
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 4: August 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1213.676 KB) | DOI: 10.11591/ijece.v9i4.pp2460-2468

Abstract

Cell counting is a required procedure in biomedical experiments and drug testing. Manual cell counting performed with a hemocytometer is time consuming and individual dependence. This study reportedthe development of a computer-assisted program for trypan blue stained-cell counting using digital image analysis. Images of trypan blue-stained breast cancer cells line were obtained by a microscope with a digital camera. Undesired noise and debris were removed by applying a guided image filter. Color space HSV (Hue, Saturation and Value)conversion and grayscale conversion were performed for distinguishing between live and dead cells.  Image thresholding and morphological operators were applied for image segmentation. Live and dead cells were counted after image segmentation and the results were compared with manual counting by three well-experienced counters. The computer-assisted cell counting from thirty-six trypan blue-stained microscopic images had a high correlation coefficient with the live cell results of the experts (r=0.99). The correlation coefficient of the number of dead cells comparing the computer-assisted count and the experts’ count was 0.74. Our approach offers high accuracy (>85%)on counting live cells compared with the experts’ counting. This automated cell counting approach can assist biomedical researchers for both live and dead cells counting.
MILP-Based Short-Term Thermal Unit Commitment and Hydrothermal Scheduling Including Cascaded Reservoirs and Fuel Constraints Mohamed Abdel Moneim Shaaban; Hossein Zeynal; Khalid Nor
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 4: August 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (581.749 KB) | DOI: 10.11591/ijece.v9i4.pp2732-2742

Abstract

Reservoirs are often built in cascade on the same river system, introducing inexorable constraints. It is therefore strategically important to scheme out an efficient commitment of thermal generation units along with the scheduling of hydro generation units for better operational efficiency, considering practical system conditions. This paper develops a comprehensive, unit-wise hydraulic model with reservoir and river system constraints, as well as gas constraints, with head effects, to commit thermal generation units and schedule hydro ones in the short-term. A mixed integer linear programming (MILP) methodology, using the branch and bound & cut (BB&C) algorithm, is employed to solve the resultant problem. Due to the detailed modelling of individual hydro units and cascaded dependent reservoirs, the problem size is substantially swollen. Multithread computing is invoked to accelerate the solution process. Simulation results, conducted on various test systems, reiterate that the developed MILP-based hydrothermal scheduling approach outperforms other techniques in terms of cost efficiency.
An effective approach to develop location-based augmented reality information support Komang Candra Brata; Deron Liang
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 4: August 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (631.846 KB) | DOI: 10.11591/ijece.v9i4.pp3060-3068

Abstract

Using location-based augmented reality (AR) for pedestrian navigation can greatly improve user action to reduce the travel time. Pedestrian navigation differs in many ways from the conventional navigation system used in a car or other vehicles. A major issue with using location-based AR for navigation to a specific landmark is their quality of usability, especially if the active screen is overcrowded with the augmented POI markers which were overlap each other at the same time. This paper describes the user journey map approach that led to new insights about how users were using location-based AR for navigation. These insights led to a deep understanding of challenges that user must face when using location-based AR application for pedestrian navigation purpose, and more generally, they helped the development team to appreciate the variety of user experience in software requirement specification phase. To prove our concept, a prototype of intuitive location-based AR was built to be compared with existing standard-location based AR. The user evaluation results reveal that the overall functional requirements which are gathered from user journey have same level of success rate criteria when compared with standard location-based AR. Nevertheless, the field study participants highlighted the extended features in our prototype could significantly enhance the user action on locating the right object in particular place when compared with standard location-based AR application (proved with the required time).
Bayesian distance metric learning and its application in automatic speaker recognition systems Satyanand Singh
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 4: August 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (398.656 KB) | DOI: 10.11591/ijece.v9i4.pp2960-2967

Abstract

This paper proposes state-of the-art Automatic Speaker Recognition System (ASR) based on Bayesian Distance Learning Metric as a feature extractor. In this modeling, I explored the constraints of the distance between modified and simplified i-vector pairs by the same speaker and different speakers. An approximation of the distance metric is used as a weighted covariance matrix from the higher eigenvectors of the covariance matrix, which is used to estimate the posterior distribution of the metric distance. Given a speaker tag, I select the data pair of the different speakers with the highest cosine score to form a set of speaker constraints. This collection captures the most discriminating variability between the speakers in the training data. This Bayesian distance learning approach achieves better performance than the most advanced methods. Furthermore, this method is insensitive to normalization compared to cosine scores. This method is very effective in the case of limited training data. The modified supervised i-vector based ASR system is evaluated on the NIST SRE 2008 database. The best performance of the combined cosine score EER 1.767% obtained using LDA200 + NCA200 + LDA200, and the best performance of Bayes_dml EER 1.775% obtained using LDA200 + NCA200 + LDA100. Bayesian_dml overcomes the combined norm of cosine scores and is the best result of the short2-short3 condition report for NIST SRE 2008 data.
Effects of downscaling channel dimensions on electrical characteristics of InAs-FinFET transistor Ahmed Mahmood; Waheb A. Jabbar; Yasir Hashim; Hadi Bin Manap
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 4: August 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (781.718 KB) | DOI: 10.11591/ijece.v9i4.pp2902-2909

Abstract

In this paper, we present the impact of downscaling of nano-channel dimensions of Indium Arsenide Fin Feld Effect Transistor (InAs- FinFET) on electrical characteristics of the transistor, in particular; (i) ION/IOFF ratio, (ii) Subthreshold Swing (SS), Threshold voltage (VT), and Drain-induced barrier lowering (DIBL). MuGFET simulation tool was utilized to simulate and compare the considered characteristics based on variable channel dimensions: length, width and oxide thickness. The results demonstrate that the best performance of InAs- FinFET was achieved with channel length = 25 nm, width= 5 nm, and oxide thickness between 1.5 to 2.5 nm according to the selected scaling factor (K = 0.125).
Feasibility study of achieving reliable electricity supply using hybrid power system for rural primary schools in Iraq: a case study with umm qasr primary school Hussam M. Almukhtar; Zaid H. Al-Tameemi; Karrar M. Al-Anbary; Mohammed K. Abbas; Dr. Hung-Yao Hsu; Dalya H. Al-Mamoori
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 4: August 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (638.948 KB) | DOI: 10.11591/ijece.v9i4.pp2822-2830

Abstract

Electrical power is considered as a significant part of contemporary life, and an essential element for development. Fossil fuels have been utilized since the beginning of the twentieth century for electricity generation. However, fossil fuels depletion at the escalating pace as well as their formidable negative implications upon ecosystem contributed to increasing interest in harnessing renewable energy sources for producing electric power to meet the growing demand worldwide. In Iraq, the electrical supply is not sufficient to supply 12 hours a day of electricity. Many rural areas, particularly their schools are suffering from the electricity shortage such as Umm Qasr Primary School that located 20 km away from the city centre of Karbala city in the middle of Iraq. In order to overcome this issue, this paper proposes a hybrid system which relies on renewable resources and the local grid to electrify Umm Qasr Primary School. Various combinations of energy resources have been analysed by using HOMER software to estimate an optimum hybrid system. The analysis illustrates that the optimal configuration of the projected system is composed of 22.4 kW PV modules, 59 batteries, and 5738kWh purchased from the local grid which has reduced the net present cost(NPC)from US$ 163791 the current situation to US$60,420 for the proposed system. The simulation findings also demonstrate that detrimental emissions have been reduced significantly.
Impact of Crack Length into Pipe Conveying Fluid Utilizing Fast Fourier transform Computer Algorithm Radhwan Hussein Abdulzhraa AL-Sagheer; K. I. Mohammed; Alaa Abdul Hussein Mezher; Karrar Abdullah Mohammed Habeeban
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 4: August 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (700.959 KB) | DOI: 10.11591/ijece.v9i4.pp2541-2547

Abstract

One of the most prominent problems experienced by the oil facilities is leakage of oil from the pipes. This problem caused 55% of oil refineries to be shut off. Oil leakage is a common problem that often results in oil waste, damage, and hazard to public health. Therefore, it is necessary to use Modern technologies to reduce this phenomenon and avoid them in advance. Pipes that convey fluids have many uses in various industries and living facilities. Risk increases when the fluid inside the pipe is flammable. In this work, main case that cause damage to the pipe, longitudinal crack is investigate.This work presents a new experimental model based on computer applications with a Fast Fourier transform (FFT) algorithm for testing the effect of longitudinal crack length by frequency and ultrasonic measurements to measure fluid velocity. The method is used for plastic pipe with 2 cm internal diameter, 3 cm external diameter, and 1 m length. The modulus of elasticity of the material is 800 N/mm2 according to the ISO 178 test method. The pipe conveys oil with simply supported ends. The results show that FFT model shows better features compared with other ways that depends on visual inspection or localized measurements which gave an external perception of pipeline damage. FFT model offers a reliable and cheap style for ensuring pipeline integrity and warning the risks before its occurrence. From the observations made the fundamental natural frequency (FNF) decreases by increasing of crack length in the pipe that conveys fluid
Hybrid Cryptography security in public cloud using TwoFish and ECC algorithm Siva Sankaran P.; Kirubanand V B
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 4: August 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (729.777 KB) | DOI: 10.11591/ijece.v9i4.pp2578-2584

Abstract

Cloud computing is a structure for rendering service to the user for free or paid basis through internet facility where we can access to a bulk of shared resources which results in saving managing cost and time for large companies, The data which are stored in the data center may incur various security, damage and threat issues which may result in data leakage, insecure interface and inside attacks. This paper will demonstrate the implementation of hybrid cryptography security in public cloud by a combination of Elliptical Curve Cryptography and Twofish algorithm, which provides an innovative solution to enhance the security features of the cloud so that we can improve the service thus results in increasing the trust over the technology.    
Autonomous Abnormal Behaviour Detection Using Trajectory Analysis Muhammed Shuaau; Ka Fei Thang; Nai Shyan Lai
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 4: August 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (977.626 KB) | DOI: 10.11591/ijece.v9i4.pp2403-2415

Abstract

Abnormal behaviour detection has attracted signification amount of attention in the past decade due to increased security concerns around the world. The amount of data from surveillance cameras have exceeded human capacity and there is a greater need for anomaly detection systems for crime monitoring. This paper proposes a solution to this problem in a reception area context by using trajectory extraction through Gaussian Mixture Models and Kalman Filter for data association. Here, trajectory analysis was performed on extracted trajectories to detect four different anomalies such as entering staff area, running, loitering and squatting down. The developed anomaly detection algorithms were tested on videos captured at Asia Pacific University’s reception area. These algorithms were able to achieve a promising detection accuracy of 89% and a false positive rate of 4.52%.

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