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Proceeding of the Electrical Engineering Computer Science and Informatics
Published by Institute of Advanced Engineering and Science
ISSN : 2407439X     EISSN : -     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
Proceeding of the Electrical Engineering Computer Science and Informatics publishes papers of the "International Conference on Electrical Engineering Computer Science and Informatics (EECSI)" Series in high technical standard. The Proceeding is aimed to bring researchers, academicians, scientists, students, engineers and practitioners together to participate and present their latest research finding, developments and applications related to the various aspects of electrical, electronics, power electronics, instrumentation, control, computer & telecommunication engineering, signal processing, soft computing, computer science and informatics.
Arjuna Subject : -
Articles 85 Documents
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Search results for , issue "Vol 6: EECSI 2019" : 85 Documents clear
SeizeIT: SEIZURE victims are no longer leashed M.A.J.I. Wimalarathne; K.U.K. Ubeysingha; I.A.D.M. Imbulana; W.A.D.R. Welikala; Koliya Pulasinghe
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 6: EECSI 2019
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v6.2015

Abstract

Seizure considered to be one of the severe and most common type of neurological disorders. Despite the availability of numerous anti-seizure drugs, it is often difficult to control the disease completely and effectively. Lack of close supervision and failure in providing urgent medical care during and after seizure episodes, leads to serious injuries or even death. On the other hand, Use of wireless sensor networks in everyday applications have rapidly increased due to decreased technology costs and improved product reliability. Therefore developing a wearable device to monitor seizure may complete the anamnesis, help medical staff in diagnosing and acute treatment while preventing seizure related accidents. There are number of seizure detection systems available in the market. Still their performance is far from perfect. This paper explores an application of biomedical wireless sensor networks, which attempts to monitor patients in a completely non-invasive and non-intrusive manner. It describes a wearable device together with seizure prediction and alerting system, which is designed to address some issues with seizure detection systems in the market. Its functional block diagram and operating modes are detailed. Possible application areas of the device are also discussed
Controlled Position Navigation of Single Degree Magnetic Levitation Dhiraj Basnet; Anusha Lamichhane; Amrit Panthi; Bipin Lamichhane; Mahammad Badrudoza; Ram Prasad Pandey
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 6: EECSI 2019
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v6.2016

Abstract

A permanent magnet is levitated following the electromagnetic suspension principle using the attractive magnetic force of a wire-wound electromagnet with a hall-effect sensor for position feedback. Taking the hall-effect voltage as an analog parameter and feedback signal to the micro-controller, the strength of the electromagnet is controlled by adjusting the current using the Pulse Width Modulation technique in order to levitate the permanent magnet. The stability of the levitated magnet is enhanced by the use of PID algorithm in the embedded system. Use of Laplace transform for simplification of differential equations and Taylor series for the linearization of system function supports the mathematical computation required for the levitation. Furthermore, by making the feedback signal from hall-effect sensor dependent only on the magnetic field of levitating magnet, an advancement in levitation phenomenon is achieved that aids the levitation with a greater flexibility of changing the position of the levitating magnet along the gravitational axis within a specified range.So the paper depicts about the "Controlled Position Navigation of Single Degree Magnetic Levitation".
Performance improvement of MO surge arrester using high gradient arrester block against VFTOs Kannadasan Raju
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 6: EECSI 2019
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v6.2017

Abstract

It is well known that the metal oxide surge arrester is inoperative against very fast transients overvoltages (VFTOs) because of its strong stray capacitive effect. This stray effect causes a time lag between the peak of residual voltage and peak of the current surge and so there is a delay its response. In order to reduce the stray effect, high gradient material is used for preparing metal oxide arrester blocks with different compositions. For simulation study, the required electrical parameters of high gradient arrester blocks are calculated with estimated height of arrester. This model is simulated using Electromagnetic transient program (EMTP) for different arrester ratings against switching, lightning, steep and very fast transients. The simulated value of residual voltages are compared with experimental values. From the observed results, it is perceived that the newly developed high gradient arrester decreases the delay and so the dynamic performance of the arrester is improved especially against very fast transients.
Determination of Appropriate Overhead Line Insulator in Sumatra due to Contamination Severity Arpan Zaeni; Umar Khayam; Deny Viviantoro
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 6: EECSI 2019
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v6.2018

Abstract

Insulator is one of the important equipment to support electrical power delivery which flow through the transmission line. Considering its very important role, the selection of insulators must be certainly based on deep analysis so that the insulator we choose works properly. There are several standards that can be used in selecting isolators, but in this paper the standards that will be used for case study analysis are IEC and IEEE standards. Case studies that will be used for the selection of insulators are for Sumatra that located in Indonesia which is a tropical country and certainly has special environmental characteristics that can influence the selection parameters of an insulator. There are several parameters that are commonly used in selecting overhead isolators those are power frequency voltage, environmental condition (contamination), switching over voltage, and lightning over voltage. Using environmental condition, it is found that the pollution category of Sumatra area is heavy, which influence the selection of insulation material.
The Feasibility of Credit Using C4.5 Algorithm Based on Particle Swarm Optimization Prediction Siswanto Siswanto; Abdussomad Abdussomad; Windu Gata; Nia Kusuma Wardhani; Grace Gata; Basuki Hari Prasetyo
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 6: EECSI 2019
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v6.2019

Abstract

Credit is a belief that one is given to a person or other entity which is concerned in the future will fulfill all the obligations previously agreed. The objective of research is necessary to do credit analysis to determine the feasibility of a credit crunch, through credit analysis results, it can be seen whether the customer is feasible or not. The methods are is used to predict credit worthiness is by using two models, models classification algorithm C4.5 and C4.5 classification algorithm model based Particle Swarm Optimization (PSO). After testing with these two models found that the result C4.5 classification algorithm generates a value of 90.99% accuracy and AUC value of 0.911 to the level diagnostics Classification Excellent, but after the optimization with C4.5 classification algorithm based on Particle Swarm Optimization accuracy values amounted to 91.18% and the AUC value of 0.913 to the level of diagnosis Excellent Classification. These both methods have different accuracy level of 0.18%.

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