International Journal of Electrical and Computer 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.
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Institutional smart buildings energy audit
Ali M Baniyounes;
Yazeed Yasin Ghadi;
Ayman Abu Baker
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 2: April 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v9i2.pp783-788
Smart buildings and Fuzzy based control systems used in Buildings Management System (BMS), Building Energy Management Systems (BEMS) and Building Automation Systems (BAS) are a point of interests among researcher and stake holders of buildings’ developing sector due to its ability to save energy and reduce greenhouse gas emissions. Therefore this paper will review, investigates define and evaluates the use of fuzzy logic controllers in smart buildings under subtropical Australia’s subtropical regions. In addition the paper also will define the latest development, design and proposed controlling strategies used in institutional buildings. Furthermore this paper will highlight and discuss the conceptual basis of these technologies including Fuzzy, Neural and Hybrid add-on technologies, its capabilities and its limitation.
Feature selection, optimization and clustering strategies of text documents
A. Kousar Nikhath;
K. Subrahmanyam
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 2: April 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v9i2.pp1313-1320
Clustering is one of the most researched areas of data mining applications in the contemporary literature. The need for efficient clustering is observed across wide sectors including consumer segmentation, categorization, shared filtering, document management, and indexing. The research of clustering task is to be performed prior to its adaptation in the text environment. Conventional approaches typically emphasized on the quantitative information where the selected features are numbers. Efforts also have been put forward for achieving efficient clustering in the context of categorical information where the selected features can assume nominal values. This manuscript presents an in-depth analysis of challenges of clustering in the text environment. Further, this paper also details prominent models proposed for clustering along with the pros and cons of each model. In addition, it also focuses on various latest developments in the clustering task in the social network and associated environments.
Proposed algorithm for image classification using regression-based pre-processing and recognition models
Chanintorn Jittawiriyanukoon
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 2: April 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v9i2.pp1021-1027
Image classification algorithms can categorise pixels regarding to image attributes with the pre-processing of learner’s trained samples. The precision and classification accuracy are complex to compute due to the variable size of pixels (different image width and height) and numerous characteristics of image per se. This research proposes an image classification algorithm based on regression-based pre-processing and the recognition models. The proposed algorithm focuses on an optimization of pre-processing results such as accuracy and precision. To evaluate and validate, recognition model is mapped in order to cluster the digital images which are developing the problem of a multidimensional state space. Simulation results show that compared to existing algorithms, the proposed method outperforms with the optimal number of precision and accuracy in classification as well as results higher matching percentage based upon image analytics.
Operational performance of a PV generator feeding DC shunt and induction motors with MPPT
Mohammed I. Abuashour;
Tha'er O. Sweidan;
Mohammad S. Widyan;
Mohammed M. Hattab;
Mohammed A. Ma'itah
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 2: April 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v9i2.pp771-782
This paper presented the transient and operational behavior of a parallel Combination of DC Shunt Motor and IM fed by a photovoltaic generator at different solar irradiance levels. The maximum power point of current/voltage (I/V) characteristic of the PV generator was achieved for different solar intensities, by utilizing an open circuit voltage method. The nonlinear operational behavior of (I/V) characteristics of the PV generator at various solar intensities and the magnetization curve of the ferromagnetic material of the DC shunt motor were both modeled by high order polynomial mathematical expressions. The study investigated the response of the system at different solar irradiance levels and changing the torque loads for both motors and then following step change in solar intensity levels with fixed loading torques for both motors. All numerical simulations were executed using MATLAB software.
Performance analysis of IEEE 802.11ac based WLAN in wireless communication systems
A. Z. Yonis
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 2: April 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v9i2.pp1131-1136
IEEE 802.11ac based wireless local area network (WLAN) is emerging WiFi standard at 5 GHz, it is new gigabit-per-second standard providing premium services. IEEE 802.11ac accomplishes its crude speed increment by pushing on three distinct measurements firstly is more channel holding, expanded from a maximum of 80 MHz up to 160 MHz modes. Secondly, the denser modulation, now using 256-QAM, it has the ability to increase the data rates up to 7 Gbps using an 8×8 multiple input multiple output (MIMO). Finally, it provides high resolution for both narrow and medium bandwidth channels. This work presents a study to improve the performance of IEEE 802.11ac based WLAN system.
PAOD: a predictive approach for optimization of design in FinFET/SRAM
Girish H;
Shashikumar D. R.
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 2: April 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v9i2.pp960-966
The evolutions in the modern memory units are comeup with FinFET/SRAM which can be utilized over high scaled computing units and in other devices. Some of the recent systems were surveyed through which it is known that existing systems lags with improving the performance and optimization of FinFET/SRAM design. Thus, the paper introduces an optimized model based on Search Optimization mechanism that uses Predictive Approach to optimize the design structure of FinFET/SRAM (PAOD). Using this can achieve significant fault tolerance under dynamic cumpting devices and applications. The model uses mathematical methodology which helps to attain less computational time and significant output even at more simulation iteration. This POAD is cost effective as it provides better convergence of FinFET/SRAM design than recursive design.
Paddy field classification with MODIS-terra multi-temporal image transformation using phenological approach in Java Island
Muhammad Dimyati;
Kustiyo Kustiyo;
Ratih Dewanti Dimyati
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 2: April 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v9i2.pp1346-1358
This paper presents the paddy field classification model using the approach based on periodic plant life cycle events and how these elevations in climate as well as habitat factors, such as elevation. The data used are MODIS-Terra two tiles of H28v09 and H29v09 of 2016, consist of 46 series of 8-daily data, with 500 meter resolution in Java region. The paddy field classification method based on the phenological model is done by Maximum Likelihood on the transformed annual multi-temporal image of the reflectance data, index data, and the combination of reflectance and index data. The results of the study showed that, with the reference of the Paddy Field Map from the Ministry of Agriculture (MoA), the overall accuracies of the paddy field classification results using the combination of reflectance and index data provide the highest (85.4%) among the reflectance data (83.5%) and index data (81.7%). The accuracy levels were varied; these depend on the slope and the types of paddy fields. Paddy fields on the slopes of 0-2% could be well identified by MODIS-Terra data, whereas it was difficult to identify the paddy fields on the slope >2%. Rain-fed lowland paddy field type has a lower user accuracy than irrigated paddy fields. This study also performed correlation (r2) between the analysis results and the statistical data based on district and provincial boundaries were >0.85 and >0.99 respectively. These correlations were much higher than the previous study results, which reached 0.49-0.65 (hilly-flat areas of county-level), and 0.80-0.88 (hilly-flat areas of provincial level) for China, and reached 0.44 for Indonesia.
Music fingerprinting based on bhattacharya distance for song and cover song recognition
Riyanarto Sarno;
Dedy Rahman Wijaya;
Muhammad Nezar Mahardika
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 2: April 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v9i2.pp1036-1044
People often have trouble recognizing a song especially, if the song is sung by a not original artist which is called cover song. Hence, an identification system might be used to help recognize a song or to detect copyright violation. In this study, we try to recognize a song and a cover song by using the fingerprint of the song represented by features extracted from MPEG-7. The fingerprint of the song is represented by Audio Signature Type. Moreover, the fingerprint of the cover song is represented by Audio Spectrum Flatness and Audio Spectrum Projection. Furthermore, we propose a sliding algorithm and k-Nearest Neighbor (k-NN) with Bhattacharyya distance for song recognition and cover song recognition. The results of this experiment show that the proposed fingerprint technique has an accuracy of 100% for song recognition and an accuracy of 85.3% for cover song recognition.
Using real interpolation method for adaptive identification of nonlinear inverted pendulum system
Phu Tran Tin;
Tran Hoang Quang Minh;
Tran Thanh Trang;
Nguyen Quang Dung
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 2: April 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v9i2.pp1078-1089
In this paper, we investigate the inverted pendulum system by using real interpolation method (RIM) algorithm. In the first stage, the mathematical model of the inverted pendulum system and the RIM algorithm are presented. After that, the identification of the inverted pendulum system by using the RIM algorithm is proposed. Finally, the comparison of the linear analytical model, RIM model, and nonlinear model is carried out. From the results, it is found that the inverted pendulum system by using RIM algorithm has simplicity, low computer source requirement, high accuracy and adaptiveness in the advantages.
A hybrid bacterial foraging and modified particle swarm optimization for model order reduction
Hadeel N. Abdullah
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 2: April 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v9i2.pp1100-1109
This paper study the model reduction procedures used for the reduction of large-scale dynamic models into a smaller one through some sort of differential and algebraic equations. A confirmed relevance between these two models exists, and it shows same characteristics under study. These reduction procedures are generally utilized for mitigating computational complexity, facilitating system analysis, and thence reducing time and costs. This paper comes out with a study showing the impact of the consolidation between the Bacterial-Foraging (BF) and Modified particle swarm optimization (MPSO) for the reduced order model (ROM). The proposed hybrid algorithm (BF-MPSO) is comprehensively compared with the BF and MPSO algorithms; a comparison is also made with selected existing techniques.