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INDONESIA
Indonesian Journal of Electrical Engineering and Computer Science
Published by Institute of Advanced Engineering and Science
ISSN : 25024752     EISSN : 25024760     DOI : -
Core Subject :
Arjuna Subject : -
Articles 9,199 Documents
 159   160   161   162   163 
An artificial intelligent approach for the optimization of organic rankine cycle power generation systems JianDing Tan; ChinWai Lim; SiawPaw Koh; SiehKiong Tiong; YingYing Koay
Indonesian Journal of Electrical Engineering and Computer Science Vol 14, No 1: April 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v14.i1.pp340-345

Abstract

The study on Organic Rankine Cycle (ORC) power generation system has gained significant popularity among researchers over the past decade, mainly due to the financial and environmental benefits that the system provides. A good maximum power point tracking (MPPT) mechanism can push the efficiency of an ORC to a higher rate. In this research, a Self-Adjusted Peak Search algorithm (SAPS) is proposed as the MPPT scheme of an ORC system. The SAPS has the ability to perform a relatively detailed search when the convergence reaches the near-optima peak without jeopardizing the speed of the overall convergence process. The SAPS is tested in a simulation to track for a moving maximum power pint (MPP) of an ORC system. Experiment results show that the SAPS outperformed several other well-established optimization algorithm in tracking the moving MPP, especially in term of the solution accuracies. It can thus be concluded that the proposed SAPS performs well as a mean of an MPPT scheme in an ORC system
A Gravitational Edge Detection for Multispectral Images Genyun Sun; Zhenjie Wang
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 7: July 2013
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Gravitational edge detection is one of the new edge detection algorithms that is based on the law of gravity. This algorithm assumes that each image pixel is a celestial body with a mass represented by its grayscale intensity and their interactions are based on the Newtonian laws of gravity. In this article, a multispectral version of the algorithm is introduced. The method uses gravitational techniques in combination with metric tensor to detect edges of multispectral images including color images. To evaluate the performances of the proposed algorithm, several experiments are performed. The experimental results confirm the efficiency of the multispectral gravitational edge detection. DOI: http://dx.doi.org/10.11591/telkomnika.v11i7.2808 
Detection and recognition of brain tumor based on DWT, PCA and ANN Nidhal Khdhair El abbadi; Zahraa Faisal Shoman
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i1.pp56-63

Abstract

Brain tumor is one of more dangerous diesis that affected more than 100 persons every day. The challenge is how to detect and recognise benign and malignant tumor without surgery. In this paper, initially, brain images are filtered to remove unwanted particles, then a new method for automatic segmentation of lesion area is carried out based on mean and standard deviation. Combining both solidity property and morphological operation used to detect only the tumor from segmented image. Mathematical morphology such as close used to join narrow breaks regions in an object, fill the small holes and remove small objects. Features extracted from image by using wavelet transform, followed by applying principle component analysis (PCA) to reduce the dimensions of features. Classification of tumor based on neural network, where the inputs to the network are thirteen statistical features and textural features. The algorithm is trained with 20 of brain MRI images and tested with 45 brain MRI images. Accuracy for this method was encourage and reach near 100% in identifying normal and abnormal tissues from MRI images.
A Noise Removal Algorithm of Color Image WANG Jianwei
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 1: January 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

An algorithm of the color image noise removal algorithm is put forward based on the pixel operations. The idea of the algorithm is to read every pixel in a set order and determine whether the pixel level is consistent with the probability density function of impulse noise or not. If it is similar to noise pixel, the number of impulse noise in a certain mask is counted. If the number is less than the given threshold, the pixel is considered as possible noise. The pixel value is not unchanged. Otherwise it is considered as noise, the result mask operation of the pixel is to replace the pixel value. Otherwise it isn’t considered as noise, the pixel value is also unchanged. The experimental results show that the algorithm is applicable to the gray noisy image and the color noisy image.It has the advantages of higher speed and more stable noise removal effects.DOI : http://dx.doi.org/10.11591/telkomnika.v12i1.3054
A Novel Framework for Evaluating the Software Project Management Efficiency–An Artificial Intelligence Approach Anandhi Govindarajan
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 9: September 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i9.pp7054-7058

Abstract

The main purpose of this work is to find a suitable solution for improving the efficiency of the Software Project Management (SPM). In this work we have used a novel artificial intelligence method, a fuzzy logic approach to evaluate the SPM efficiency. There are many IT organization suffers on managing the SPM, it may be due to several reasons such as project work can’t begin on time, it may have vague requirements, people involved in the project can’t stay within project parameters, unity among the people involved in the projects and improper communication unclear project objectives and goals. All these issues usually may lead to delay in the project and have greater impact on the project failure, which in turn causes the poor Software Project Management efficiency.Fuzzy logic is one of the Artificial Intelligence method helps to solve the problems when there is a SPM with uncertainty and vagueness in it. We used the fuzzy inference system (FIS) to quantify the SPM efficiency under uncertainty and vagueness of the parameters involved in quantifying SPM efficiency. The outcome of the work is really appreciable and encouraging to quantify the Software Project Management efficiency
An Icon Design Approach Based on Symbolic and Users' Cognitive Psychology Sun Qiang; Hu Fei
Indonesian Journal of Electrical Engineering and Computer Science Vol 4, No 3: December 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v4.i3.pp695-706

Abstract

In order to explore the usability and ease of use of icon design, the icon design method based on the combination of semiotics and user cognitive psychology is raised. Based on the principle of matching the icon design knowledge and user knowledge, the icon design process is analyzed from four dimensions, namely the semantic expression of elements, the structure of elements, the interface and cultural context, and the user cognitive characteristics. An icon assistant design system CDIPV1.0 is structured, it can realize knowledge sharing, rapid icon designing, and professional evaluation based on the combination of semiotics and users’ cognitive psychology. The theory is verified through it.
A Radio Signal Strength Based Localization Error Optimization Technique for Wireless Sensor Network Sudha H. Thimmaiah; Mahadevan G
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i3.pp839-847

Abstract

Wireless Sensor Networks (WSN) is useful in collecting data from various sensor devices that are distributed over a network which is generally positioned in a stationary manner. Wireless sensor based communication system is an ever growing sector in the industry of communication. Wireless infrastructure is a network that enables correspondence between various devices associated through an infrastructure protocol. Finding the position or location of sensor node (Localization) is an important factor in sensor network for proving efficient service to end user. The existing technique proposed so for adopt AOA (Angle of Arrival), TOA (Time of Arrival) etc… suffers in estimating the likelihood of localization error and induces high cost of deployment. To cater this in this work the author proposes a cost effective RSS (Received signal strength) based localization technique and also proposes an adaptive information estimation to reduce or approximate the localization error in wireless sensor network. The author compares our proposed localization model with existing protocol and analyse its efficiency.
Exploration of the best performance method of emotions classification for arabic tweets Mohammed Abdullah Al-Hagery; Manar Abdullah Al-assaf; Faiza Mohammad Al-kharboush
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 2: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i2.pp1010-1020

Abstract

Arab users of social media have significantly increased, thus increasing the opportunities for extracting knowledge from various areas of life such as trade, education, psychological health services, etc. The active Arab presence on Twitter motivates many researchers to classify and analysis Arabic tweets from numerous aspects. This study aimed to explore the best performance scenarios in the classification of emotions conveyed through Arabic tweets. Hence, various experiments were conducted to investigate the effects of feature extraction techniques and the N-gram model on the performance of three supervised machine learning algorithms, which are support vector machine (SVM), naïve bayes (NB), and logistic regression (LR). The general method of the experiments was based on five steps; data collection, preprocessing, feature extraction, emotion classification, and evaluation of results. To implement these experiments, a real-world Twitter dataset was gathered. The best result achieved by the SVM classifier when using a bag of words (BoW) weighting schema (with unigrams and bigrams or with unigrams, bigrams, and trigrams) exceeded the best performance results of other algorithms.
Positioning of light shelves to enhance daylight illuminance in office rooms Badri Narayan Mohapatra; M. Ravi Kumar; Sushanta Kumar Mandal
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 1: July 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i1.pp168-177

Abstract

This paper aims to improve daylighting by using light shelves. Horizontal light shelf is found to increase the illuminance in the interior of office rooms. By tilting external light shelf more illuminance can be achieved. For uniformity of illuminance tiltable light shelf is the best choice instead of horizontal light shelf. The performance of light shelves was examined through simulations on DIALux and compared with experimental values obtained from a prototype. Substantial improvement in illuminance is obtained in the experimental studies with tilted light shelves on the prototype.
JADE Multi-agent Middleware Applied to Contribute to Certificate Management of Students Fatiha Aityacine; Badr Hssina; Belaid Bouikhalene
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 1: October 2015
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i1.pp176-181

Abstract

In this article, we present a multi-agent approach that aims to design, modeling and implementation of an application "smart school". Indeed Several institutions adopt the computerized management of education to meet the needs of students using multi-agent systems. They have the ability to act simultaneously in a shared environment. The purpose of this approach is to automate some administrative services of education, based on the theory of distributed artificial intelligence (DAI) and multi-agent systems (MAS). This multi-agent application integrates entities called agents that cooperate and communicate them to perform specific tasks. Our system is based on the middleware JADE (Java Agent DEvelopment Framework) used for the implementation and agents management. This model based on multi-agent systems is tested on the personal data of an experiment conducted with the students of Sultan Moulay Slimane University in Beni Mellal.

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