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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
 447   448   449   450   451 
Calculating algorithm of service quality statistical parameters for asynchronous network subscribers Kemelbekova Zh. S.; Sembiyev O. Z.; Umarova Zh. R
Indonesian Journal of Electrical Engineering and Computer Science Vol 20, No 3: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v20.i3.pp1485-1494

Abstract

It is often necessary to determine statistical parameters that characterize the quality of service on the network by managing when designing computer networks using the concept of virtual connections with bypass directions. In many ways, the attainable level of quality of the services provided is determined at the stage of network design, when decisions was made regarding the subscriber capacity of stations, the capacity of bundles of trunk lines, the composition and volume of telecommunication services provided. Despite constant progress in the field of network technologies, the problem of determining the necessary amount of network resources and ensuring the quality of user service remains relevant. In this regard, this article discusses a broadband digital network with service integration, based on an asynchronous network in which an iterative method implemented. Here the flow distribution is determined by the route matrix, and the load distribution between the nodes of each pair of nodes made through the path tree obtained on the matrix of routes when calculating this pair. At the same time, an algorithm has been built for allow optimal allocation of channel resources between circuit switching and packet switching subnets within an asynchronous network.
Product Form Identification Technology Based on Cognitive Thinking Shutao Zhang; Jianning Su; Chibing Hu; Peng Wang
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 10: October 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

In this paper, based on the analyzing of the selecting and distinguishing characteristics of cognitive thinking, the product design elements are analyzed with the theories of Kansei Engineering, and the corresponding mathematic model for the analysis is developed based on the quantification-I theory to quantitatively discuss the relationship between product form design elements and the psychological kansei image of the users. With foregoing investigation result, practicable program software has been developed as a solver tool to subsequent design. Finally, a practical application of testing machine is presented, and the results show that the method is reasonable and feasible as well. DOI: http://dx.doi.org/10.11591/telkomnika.v11i10.3422 
Multimodal biometrics with serial, parallel and hierarchical mode at decision level fusion Priti Shivaji Sanjekar; J. B. Patil
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 3: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i3.pp1303-1310

Abstract

Biometric based personal authentication is playing a vital role in various security based applications. This paper presents the effective fusion of fingerprint, palmprint and iris traits at decision level. Combining different traits at the decision level is a challenging task due to less information available at this level. The focus of the work is to examine the performance of multimodal biometrics at decision level fusion in three different i.e. serial, parallel and hierarchical modes of operation. Serial mode is performed by taking unimodals serially while parallel mode of operation is carried out by processing all modals simulatenously using Majority Voting Rule and the hierarchical mode of operation is performed with proper combination of traits in parallel and serial mode using AND and OR rule. The experiments are performed on 100 different users from publically available FVC2006 fingerprint database, CASIA V1 palmprint database and IITD iris database. The experimental results suggest that proper fusion of different traits in hierarchical way can give best performance even at decision level fusion as compared to serial and parallel mode of operation.
Design of Information Retrieval System Using Rough Fuzzy Set Yuemin Wang
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 1: January 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

DOI : http://dx.doi.org/10.11591/telkomnika.v12i1.3541
Liquid slosh control by implementing model-free PID controller with derivative filter based on PSO Mohd Zaidi Mohd Tumari; Amar Faiz Zainal Abidin; A Shamsul Rahimi A Subki; Ab Wafi Ab Aziz; Muhammad Salihin Saealal; Mohd Ashraf Ahmad
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 2: May 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i2.pp750-758

Abstract

Conventionally, the control of liquid slosh system is done based on model-based techniques that challenging to implement practically because of the chaotic motion of fluid in the container. The aim of this article is to develop the tuning technique for model-free PID with derivative filter (PIDF) parameters for liquid slosh suppression system based on particle swarm optimization (PSO). PSO algorithm is responsible to find the optimal values for PIDF parameters based on fitness functions which are Sum Squared Error (SSE) and Sum Absolute Error (SAE) of the cart position and liquid slosh angle response. The modelling of liquid slosh in lateral movement is considered to justify the design of control scheme. The PSO tuning method is compared by heuristic tuning method in order to show the effectiveness of the proposed tuning approach. The performance evaluations of the proposed tuning method are based on the ability of the tank to follow the input in horizontal motion and liquid slosh level reduction in time domain. Based on the simulation results, the suggested tuning method is capable to reduce the liquid slosh level in the same time produces fast input tracking of the tank without precisely model the chaotic motion of the fluid.
The Study of Comprehensive Evaluation of Power Industry Energy Saving and Emission Reduction Based on the Improved Osculating Value Method SONG Xiao-hua; CHEN Ling-qing; ZU Pi-e; MU Lan
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 4: April 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

This paper expounded the meaning of energy saving and emission reduction of power industry and analyzed the main factors of energy saving and emission reduction of power industry of low-carbon economy by combining low-carbon economy and development demand of power industry. We constructed evaluation index system and evaluation model of energy saving and emission reduction in power industry under the background of low-carbon economy. Then we carried on the empirical analysis. These provided the theoretical reference of the energy saving and emission reduction in power industry under the background of low-carbon economy for the government agencies, the electricity regulatory departments and other relevant units. DOI: http://dx.doi.org/10.11591/telkomnika.v11i4.2402
A Fault Detection Mechanism Based on Artificial Neural Network Distributed in Tunnel Liu Liu; Ma Chengqian
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 10: October 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i10.pp7337-7342

Abstract

This paper has made a qualitative and quantitative analysis by establishing the tunnel fault tree and giving the minimal cut sets of the faults in tunnel, and tested the data in tunnel combined with artificial neural network. The fault detection mechanism in this article has been simulated by MatLab and processed a lot of the actual data through the tunnel operating history. Experimental results show that: This fault detection mechanism is effective.
Sanitizer Dosing Decoupling Control Based on IMC-NN Inverse System Xie Peizhang; Zhou Xingpeng
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 9: September 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

Multi tunnels multi pools (MTMP) structure is very common in tap-waterworks, MTMP structure sanitizer dosing system is a complicated system with coupling, large time delay and inertial. Internal model control decoupling based on wavelet neural networks inverse system is introduced to solve the problems. First  order inverse system is identified using wavelet neural networks, this inverse system cascades the original system so that pseudo-linearization system can be obtained, and then this MIMO system can be transformed to SISO system with no coupling. In addition time delay and model error can be overcome by internal model control. Practical application shows that the coupling, time delay and inertial of MTMP sanitizer dosing system is overcome, also this method is able to resist the disturbance and improve the robustness.DOI: http://dx.doi.org/10.11591/telkomnika.v11i9.3247
Neuro-physiological porn addiction detection using machine learning approach Norhaslinda Kamaruddin; Abdul Wahab; Yasmeen Rozaidi
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 2: November 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i2.pp964-971

Abstract

Pornography is a portrayal of sexual subject contents for the exclusive purpose of sexual arousal that can lead to addiction. The availability and easy accessibility of the Internet connectivity have created unprecedented opportunities for sexual education, learning, and growth for adolescences to be in the rise. Hence, the risk of porn addiction developed by teenagers has also increased due to highly prevalent porn consumption. To date, the only available means of detecting porn addiction is through questionnaire. However, while answering the questions, participants may suppress or exaggerate their answers because porn addiction is considered taboo in the community. Hence, the purpose of this project is to develop an engine with multiple classifiers to recognize porn addiction using electroencephalography (EEG) signals and to compare classifiers performance. In the experimental study, the neuro-physiological signals of EEG data were collected previously in Indonesia among students age 9 to 13 years old by researchers from the International Islamic University Malaysia (IIUM). The EEG data were pre-processed, and relevant features are extracted using Mel-Frequency Cepstral Coefficients (MFCC). Then, the features are classified to produce the outputs of valance and arousal. Subsequently, three different classifiers of Multilayer Perceptron (MLP), Naive Bayesian (NB), and Random Forest (RF) are employed to determine whether the participant is a porn addict or otherwise. The experimental results show that the MLP classifier yields slightly better accuracy compared to Naïve Bayes and Random Forest classifiers making the MLP classifier preferable for porn addiction recognition. Although this work is still at infancy stage, it is envisaged for the work to be expanded for comprehensive porn addiction recognition system so that early intervention and appropriate support can be given for the teenagers with pornography addiction problem.
Transformer Fault Diagnosis Method Based on Information Fusion Xin bo Huang; Tong Song; Ya na Wang
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 5: May 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

According to the characteristics and current situation of power transformer fault diagnosis , information fusion technology is introduced into this field of fault diagnosis of power transformer. By studying the general framework of information fusion fault diagnosis process, combined with the dissolved gas and electrical tests data,it is proposed a fault diagnosis method of information fusion which is based on fuzzy coding boundary and Bias regularization Levenberg Marquardt (LM) network. The algorithm uses a Bias approach to determine the hyper parameters, making the neural network adaptively adjust the parameter in the training process and getting the optimization parameters of the objective function . Combined with fuzzy coding boundary for feature attribute reduction to improve the accuracy of fault diagnosis .The contrast analysis of twice fusion results shows that the  fault diagnosis model of the transformer accurate rate is 89.83%. Finally , it proves the validity and practicability of this new diagnosis method. DOI : http://dx.doi.org/10.11591/telkomnika.v12i5.4054

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