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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 75 Documents

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Search results for , issue "Vol 8, No 4: August 2018" : 75 Documents clear

Optimization of Modified Sliding Mode Controller for an Electro-hydraulic Actuator System with Mismatched Disturbance Siti Marhainis Othman; M. F. Rahmat; S. M. Rozali; Zulfatman Has; A. F. Z. Abidin
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 4: August 2018
Publisher : Institute of Advanced Engineering and Science

This paper presents the design of the modified sliding mode controller (MSMC) for the purpose of tracking the nonlinear system with mismatched disturbance. Provided that the performance of the designed controller depends on the value of control parameters, gravitational search algorithm (GSA), and particle swarm optimization (PSO) techniques are used to optimize these parameters in order to achieve a predefined system’s performance. In respect of system’s performance, it is evaluated based on the tracking error present between reference inputs transferred to the system and the system output. This is followed by verification of the efficiency of the designed controller in simulation environment under various values, with and without the inclusion of external disturbance. It can be seen from the simulation results that the MSMC with PSO exhibits a better performance in comparison to the performance of the similar controller with GSA in terms of output response and tracking error.

Evaluation of a Multiple Regression Model for Noisy and Missing Data Chanintorn Jittawiriyanukoon
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 4: August 2018
Publisher : Institute of Advanced Engineering and Science

The standard data collection problems may involve noiseless data while on the other hand large organizations commonly experience noisy and missing data, probably concerning data collected from individuals. As noisy and missing data will be significantly worrisome for occasions of the vast data collection then the investigation of different filtering techniques for big data environment would be remarkable. A multiple regression model where big data is employed for experimenting will be presented. Approximation for datasets with noisy and missing data is also proposed. The statistical root mean squared error (RMSE) associated with correlation coefficient (COEF) will be analyzed to prove the accuracy of estimators. Finally, results predicted by massive online analysis (MOA) will be compared to those real data collected from the following different time. These theoretical predictions with noisy and missing data estimation by simulation, revealing consistency with the real data are illustrated. Deletion mechanism (DEL) outperforms with the lowest average percentage of error.

Study and Dimensioning of the Tanks Dedicated to a Compressed Air Storage System (CAES) Ilham Rais; H. Mahmoudi
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 4: August 2018
Publisher : Institute of Advanced Engineering and Science

The fundamental idea of storage is to transfer available energy During periods of low demand, using only a fraction of the fuel that would be consumed by the standard production machine (gas turbine, thermal engine, etc.). The main role of energy storage is therefore to introduce an energy degree of freedom to decouple Consumers and the producer by supplying or Delivering the difference between these two powers. In this paper is this paper presents a brief study and dimensioning of compressed air storage tanks to a hybrid system wind-PV . adopts the CAES system as a storage agent. Starting with the technical criteria on which the choice of reservoirs is based and the mechanical constraints that must be taken into consideration for dimensioning of the reservoirs

Spectral Clustering and Vantage Point Indexing for Efficient Data Retrieval Pushpalatha R.; K. Meenakshi Sundaram
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 4: August 2018
Publisher : Institute of Advanced Engineering and Science

Data mining is an essential process for identifying the patterns in large datasets through machine learning techniques and database systems. Clustering of high dimensional data is becoming very challenging process due to curse of dimensionality. In addition, space complexity and data retrieval performance was not improved. In order to overcome the limitation, Spectral Clustering Based VP Tree Indexing Technique is introduced. The technique clusters and indexes the densely populated high dimensional data points for effective data retrieval based on user query. A Normalized Spectral Clustering Algorithm is used to group similar high dimensional data points. After that, Vantage Point Tree is constructed for indexing the clustered data points with minimum space complexity. At last, indexed data gets retrieved based on user query using Vantage Point Tree based Data Retrieval Algorithm. This in turn helps to improve true positive rate with minimum retrieval time. The performance is measured in terms of space complexity, true positive rate and data retrieval time with El Nino weather data sets from UCI Machine Learning Repository. An experimental result shows that the proposed technique is able to reduce the space complexity by 33% and also reduces the data retrieval time by 24% when compared to state-of-the-art-works.

K-NN Classification of Brain Dominance Khairul Amrizal Abu Nawas; Mahfuzah Mustafa; Rosdiyana Samad; Dwi Pebrianti; Nor Rul Hasma Abdullah
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 4: August 2018
Publisher : Institute of Advanced Engineering and Science

The brain dominance is referred to right brain and left brain. The brain dominance can be observed with an Electroencephalogram (EEG) signal to identify different types of electrical pattern in the brain and will form the foundation of one’s personality. The objective of this project is to analyze brain dominance by using Wavelet analysis. The Wavelet analysis is done in 2-D Gabor Wavelet and the result of 2-D Gabor Wavelet is validated with an establish brain dominance questionnaire. Twenty-one samples from University Malaysia Pahang (UMP) student are required to answer the establish brain dominance questionnaire has been collected in this experiment. Then, brainwave signal will record using Emotiv device. The threshold value is used to remove the artifact and noise from data collected to acquire a smoother signal. Next, the Band-pass filter is applied to the signal to extract the sub-band frequency components from Delta, Theta, Alpha, and Beta. After that, it will extract the energy of the signal from image feature extraction process. Next the features were classified by using K-Nearest Neighbor (K-NN) in two ratios which 70:30 and 80:20 that are training set and testing set (training: testing). The ratio of 70:30 gave the highest percentage of 83% accuracy while a ratio of 80:20 gave 100% accuracy. The result shows that 2-D Gabor Wavelet was able to classify brain dominance with accuracy 83% to 100%.

Exploiting 2-Dimensional Source Correlation in Channel Decoding with Parameter Estimation Muhammad Izzat Amir Mohd Nor; Mohd Azri Mohd Izhar; Norulhusna Ahmad; Hazilah Md. Kaidi
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 4: August 2018
Publisher : Institute of Advanced Engineering and Science

Traditionally, it is assumed that source coding is perfect and therefore, the redundancy of the source encoded bit-stream is zero. However, in reality, this is not the case as the existing source encoders are imperfect and yield residual redundancy at the output. The residual redundancy can be exploited by using Joint Source Channel Coding (JSCC) with Markov chain as the source. In several studies, the statistical knowledge of the sources has been assumed to be perfectly available at the receiver. Although the result was better in terms of the BER performance, practically, the source correlation knowledge were not always available at the receiver and thus, this could affect the reliability of the outcome. The source correlation on all rows and columns of the 2D sources were well exploited by using a modified Bahl-Cocke-Jelinek-Raviv (BCJR) algorithm in the decoder. A parameter estimation technique was used jointly with the decoder to estimate the source correlation knowledge. Hence, this research aims to investigate the parameter estimation for 2D JSCC system which reflects a practical scenario where the source correlation knowledge are not always available. We compare the performance of the proposed joint decoding and estimation technique with the ideal 2D JSCC system with perfect knowledge of the source correlation knowledge. Simulation results reveal that our proposed coding scheme performs very close to the ideal 2D JSCC system.

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%.

Incorporating Index of Fuzziness and Adaptive Thresholding for Image Segmentation Umi Salamah; Riyanarto Sarno; Agus Zainal Arifin; Anto Satriyo Nugroho; Ismail Eko Prayitno Rozi; Puji Budi Setia Asih
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 4: August 2018
Publisher : Institute of Advanced Engineering and Science

Binary Segmentation of an image played an important role in many image processing application. An image that was having no bimodal (or nearly) histogram accompanied by low-contrast was still a challenging segmentation problem to address. In this paper, we proposed a new segmentation strategy to images with very irregular histogram and had not significant contrast using index of fuzziness and adaptive thresholding. Index of fuzziness was used to determine the initial threshold, while adaptive thresholding was used to refine the coarse segmentation results. The used data were grayscale images from related papers previously. Moreover, the proposed method would be tested on the grayscale images of malaria parasite candidates from thickblood smear that had the same problem with this research. The experimental results showed that the proposed method achieved higher segmentation accuracy and lower estimation error than other methods. The method also effective proven to segment malaria parasite candidates from thickblood smears image.

Low Noise Amplifier using Darlington Pair At 90nm Technology Rashmi Singh; Rajesh Mehra
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 4: August 2018
Publisher : Institute of Advanced Engineering and Science

The demand of low noise amplifier (LNA) has been rising in today’s communication system. LNA is the basic building circuit of the receiver section satellite. The design concept demonstrates the design trade off with NF, gain, power consumption. This paper reports on with analysis of wideband LNA. This paper shows the schematic of LNA by using Darlington pair amplifier. This LNA has been fabricated on 90nm CMOS process. This paper is focused on to make comparison of three stage and single stage LNA. Here, the phase mismatch between these patameters is quantitavely analyzed to study the effect on gain and noise figure (NF). In this paper, single stage LNA has shown the 23 dB measured gain, while the three stages LNA has demonstrated 29 dB measured gain. Here, LNA designed using darlington pair shows low NF of 3.3-4.8 dB, which comparable to other reported single stage LNA designs and appreciably low compared to the three stages LNA. Hence, findings from this paper suggest the use of single stage LNA designed using Darlington pair in transceiver satellite applications.

Instruction Set Extension of a Low-End Reconfigurable Microcontroller in Bit-Sorting Implementation Sani Irwan Md Salim; Yewguan Soo; Sharatul Izah Samsudin
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 4: August 2018
Publisher : Institute of Advanced Engineering and Science

The microcontroller-based system is currently having a tremendous boost with the revelation of platforms such as the Internet of Things. Low-end families of microcontroller architecture are still in demand albeit less technologically advanced due to its better I/O better application and control. However, there is clearly a lack of computational capability of the low-end architecture that will affect the pre-processing stage of the received data. The purpose of this research is to combine the best feature of an 8-bit microcontroller architecture together with the computationally complex operations without incurring extra resources. The modules’ integration is implemented using instruction set architecture (ISA) extension technique and is developed on the Field Programmable Gate Array (FPGA). Extensive simulations were performed with the and a comprehensive methodology is proposed. It was found that the ISA extension from 12-bit to 16-bit has produced a faster execution time with fewer resource utilization when implementing the bit-sorting algorithm. The overall development process used in this research is flexible enough for further investigation either by extending its module to more complex algorithms or evaluating other designs of its components.

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Home Page

OAI Link

Editorial Team

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Reviewer

Google Scholar

Contact Name Tole Sutikno

Contact Email ijece@iaesjournal.com

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Journal Mail Official ijece@iaesjournal.com

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Location Kota yogyakarta, Daerah istimewa yogyakarta INDONESIA

Abstract

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Abstract

Abstract

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