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International Journal of Electrical and Computer Engineering
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 6,393 Documents
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An approach to assess the quality of honey using partial least square method G. Rajalakshmi; A. Gopal; R. Pandian
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp4991-4998

Abstract

The objective of the present study is to obtain the quantity of honey components such as moisture, glucose, fructose and sucrose in order to access the quality of honey. The tested honey samples are authenticated if the characteristics of a pure honey. The average ratio of 56% fructose to 44% glucose, but the ratios in the individual honeys ranged from a high of 64% fructose and 36% glucose to a low of 50% fructose and 50% glucose. The contents such as fructose and sucrose in honey is due to the presence of invertase enzymes. The organic acids present in the honey is responsible for the flavor and stability against the contamination of honey due to microorganisms. The natural food items are adulterated intentionally to increase the quantity and there by the quality gets affected. The main adulterants added in honey are sucrose, corn syrup, sugar syrup and jaggery syrup. The quantification deals in finding out the amount of basic constituents present in pure honey and adulterated honey using Fourier transform infrared (FTIR) spectrometer with the multivariate analysis and validating the same using chemical analysis method. The partial least square model is used in predicting the constituents of the samples.
Investigation of robust gait recognition for different appearances and camera view angles Chirawat Wattanapanich; Hong Wei; Wijittra Petchkit
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp3977-3987

Abstract

A gait recognition framework is proposed to tackle the challenge of unknown camera view angles as well as appearance changes in gait recognition. In the framework, camera view angles are firstly identified before gait recognition. Two compact images, gait energy image (GEI) and gait modified Gaussian image (GMGI), are used as the base gait feature images. Histogram of oriented gradients (HOG) is applied to the base gait feature images to generate feature descriptors, and then a final feature map after principal component analysis (PCA) operations on the descriptors are used to train support vector machine (SVM) models for individuals. A set of experiments are conducted on CASIA gait database B to investigate how appearance changes and unknown view angles affect the gait recognition accuracy under the proposed framework. The experimental results have shown that the framework is robust in dealing with unknown camera view angles, as well as appearance changes in gait recognition. In the unknown view angle testing, the recognition accuracy matches that of identical view angle testing in gait recognition. The proposed framework is specifically applicable in personal identification by gait in a small company/organization, where unintrusive personal identification is needed.
Predictive model of water stress in tenera oil palm by means of spectral signature methods Angie Marcela Galvez Valencia; Yeison Alberto Garces-Gomez; Erwin Leandro Lemus Rodriguez; Miguel Andres Arango Argoti
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp2680-2687

Abstract

Agriculture as a competitive business, seeks to improve productivity within crops with a more sustainable environmental management. It is important that agriculture includes new technologies that allow it to generate differential, precise and real-time information. In Colombia, the current lack of knowledge about techniques that allow early identification of water stress in African palm could generate a loss in the investment made in the fertilization of the crop, cause an increase in diseases, pests, and susceptibility to compaction or abortions in female flowers that would lead to decreases in production. In this work, a predictive model is established to quantify water stress based on spectral, physiological and soil information in African palm plants. To this end, a study was carried out in an oil palm plantation where treatments were established with 3 ranges of humidity. It was found that the indices with the highest correlation with the biophysical variable soil moisture were: NDVI_1 and NDVI_16 for treatment 1, SR_4 for treatment 2 and NDVI_16 and NDVI_20 for treatment 3. Finally, the third order polynomial regression model that obtained higher correlation coefficients of Pearson R^2=0.73 was selected as the most suitable model to estimate soil moisture content for treatments 2 and 3.
Adaptive photovoltaic solar module based on internet of things and web-based monitoring system Murizah Kassim; Fadila Lazim
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 1: February 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i1.pp924-935

Abstract

This paper presents an intelligent of single axis automatic adaptive photovoltaic solar module. A static solar panel has an issue of efficiency on shading effects, irradiance of sunlight absorbed, and less power generates. This aims to design an effective algorithm tracking system and a prototype automatic adaptive solar photovoltaic (PV) module connected through internet of things (IoT). The system has successfully designated on solving efficiency optimization. A tracking system by using active method orientation and allows more power and energy are captured. The solar rotation angle facing aligned to the light-dependent resistor (LDR) voltage captured and high solar panel voltage measured by using Arduino microcontroller. Real-time data is collected from the dynamic solar panel, published on Node-Red webpage, and running interactive via android device. The system has significantly reduced time. Data captured by the solar panel then analyzed based on irradiance, voltage, current, power generated and efficiency. Successful results present a live data analytic platform with active tracking system that achieved larger power generated and efficiency of solar panel compared to a fixed mounted array. This research is significant that can help the user to monitor parameters collected by the solar panel thus able to increase 51.82% efficiency of the PV module.
Investigating the PageRank and sequence prediction based approaches for next page prediction Da, Nguyen Thon; Hanh, Tan
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp2229-2237

Abstract

Discovering unseen patterns from web clickstream is an upcoming research area. One of the meaningful approaches for making predictions is using sequence prediction that is typically the improved compact prediction tree (CPT+). However, to increase this method's effectiveness, combining it with at least other methods is necessary. This work investigates such PageRank-based methods related to sequence prediction as All-K-Markov, DG, Markov 1st, CPT, CPT+. The experimental results proved that the integration of CPT+ and PageRank is the right solution for next page prediction in terms of accuracy, which is more than a standard method of approximately 0.0621%. Still, the size of the newly created sequence database is reduced up to 35%. Furthermore, our proposed solution has an accuracy that is much higher than other ones. It is intriguing for the next phase (testing one) to make the next page prediction in terms of time performance.
Overall fuzzy logic control strategy of direct driven PMSG wind turbine connected to grid Mhamed Fannakh; Mohamed Larbi Elhafyani; Smail Zouggar; Hassan Zahboune
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp5515-5529

Abstract

The fuzzy logic strategies reported in the literature about the control of direct drive permanent magnet synchronous generator (PMSG) connected to grid are limited in terms of inclusiveness and efficiency. So an overall control based on fuzzy logic and anti-windup compensation is proposed in this paper. Aiming at the inadequate of hill climb search (HCS) MPPT with fixed step size, the fuzzy logic is introduced in the stage of "generating rotor speed reference" to overcome the oscillations and slowness in traditional method. PI controllers are replaced by anti-windup fuzzy logic controllers in the "machine side control" stage and in "grid side control" stage to pertinently regulate the reference parameters. Then comparison tests with classical methods are implemented under varying climatic conditions. The results obtained demonstrate that the developed control is superior to other methods in response time (less than 4.528E-04 s), precision (an overshoot about 0.41%) and quality of produced energy (efficiency is 91%). The study verifying the feasibility and effectiveness of this algorithm in PMSG wind turbine connected to grid.
Extended of TEA: A 256 bits block cipher algorithm for image encryption Abeer F. Shimal; Baydaa H. Helal; Ashwaq T. Hashim
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp3996-4007

Abstract

This paper introduces an effective image encryption approach that merges a chaotic map and polynomial with a block cipher. According to this scheme, there are three levels of encryption. In the first level, pixel positions of the image are scuffled into blocks randomly based on a chaotic map. In the second level, the polynomials are constructed by taking N unused pixels from the permuted blocks as polynomial coefficients. Finally, the third level a proposed secret-key block cipher called extended of tiny encryption algorithm (ETEA) is used. The proposed ETEA algorithm increased the block size from 64-bit to 256-bit by using F-function in type three Feistel network design. The key schedule generation is very straightforward through admixture the entire major subjects in the identical manner for every round. The proposed ETEA algorithm is word-oriented, where wholly internal operations are executed on words of 32 bits. So, it is possible to efficiently implement the proposed algorithm on smart cards. The results of the experimental demonstration that the proposed encryption algorithm for all methods are efficient and have high security features through statistical analysis using histograms, correlation, entropy, randomness tests, and the avalanche effect.
Compressor based approximate multiplier architectures for media processing applications Uppugunduru Anil Kumar; Syed Ershad Ahmed
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i4.pp2953-2961

Abstract

Approximate computing is an attractive technique to gain substantial improvement in the area, speed, and power in applications where exact computation is not required. This paper proposes two improved multiplier designs based on a new 4:2 approximate compressor circuit to simplify the hardware at the partial product reduction stage. The proposed multiplier designs are targeted towards error-tolerant applications. Exhaustive error and hardware analysis has been carried out on the existing and proposed multiplier designs. The results prove that the proposed approximate multiplier architecture performs better than the existing architectures without significant compromise on quality metrics. Experimental results show that die-area and power consumed are reduced upto 28%, and 25.29% respectively in comparison with the existing designs without significant compromise on accuracy.
MTVRep: A movie and TV show reputation system based on fine-grained sentiment and semantic analysis Abdessamad Benlahbib; El Habib Nfaoui
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 2: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i2.pp1613-1626

Abstract

Customer reviews are a valuable source of information from which we can extract very useful data about different online shopping experiences. For trendy items (products, movies, TV shows, hotels, services . . . ), the number of available users and customers’ opinions could easily surpass thousands. Therefore, online reputation systems could aid potential customers in making the right decision (buying, renting, booking . . . ) by automatically mining textual reviews and their ratings. This paper presents MTVRep, a movie and TV show reputation system that incorporates fine-grained opinion mining and semantic analysis to generate and visualize reputation toward movies and TV shows. Differently from previous studies on reputation generation that treat the task of sentiment analysis as a binary classification problem (positive, negative), the proposed system identifies the sentiment strength during the phase of sentiment classification by using fine-grained sentiment analysis to separate movie and TV show reviews into five discrete classes: strongly negative, weakly negative, neutral, weakly positive and strongly positive. Besides, it employs embeddings from language models (ELMo) representations to extract semantic relations between reviews. The contribution of this paper is threefold. First, movie and TV show reviews are separated into five groups based on their sentiment orientation. Second, a custom score is computed for each opinion group. Finally, a numerical reputation value is produced toward the target movie or TV show. The efficacy of the proposed system is illustrated by conducting several experiments on a real-world movie and TV show dataset.
Performance analysis of massive multiple input multiple output for high speed railway Maharshi K. Bhatt; Bhavin S. Sedani; Komal Borisagar
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp5180-5188

Abstract

This paper analytically reviews the performance of massive multiple input multiple output (MIMO) system for communication in highly mobility scenarios like high speed Railways. As popularity of high speed train increasing day by day, high data rate wireless communication system for high speed train is extremely required. 5G wireless communication systems must be designed to meet the requirement of high speed broadband services at speed of around 500 km/h, which is the expected speed achievable by HSR systems, at a data rate of 180 Mbps or higher. Significant challenges of high mobility communications are fast time-varying fading, channel estimation errors, doppler diversity, carrier frequency offset, inter carrier interference, high penetration loss and fast and frequent handovers. Therefore, crucial requirement to design high mobility communication channel models or systems prevails. Recently, massive MIMO techniques have been proposed to significantly improve the performance of wireless networks for upcoming 5G technology. Massive MIMO provide high throughput and high energy efficiency in wireless communication channel. In this paper, key findings, challenges and requirements to provide high speed wireless communication onboard the high speed train is pointed out after thorough literature review. In last, future research scope to bridge the research gap by designing efficient channel model by using massive MIMO and other optimization method is mentioned.

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