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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
 108   109   110   111   112 
Influence of annealing temperature on the sensitivity of nickel oxide nanosheet films in humidity sensing applications N. Parimon; M. H. Mamat; A. S. Ismail; I. B. Shameem Banu; M. K. Ahmad; A. B. Suriani; M. Rusop
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.pp284-292

Abstract

Nickel oxide (NiO) nanosheet films were successfully grown onto NiO seed-coated glass substrates at different annealing temperatures for humidity sensing applications. NiO seed layers and NiO nanosheet films were prepared using a sol-gel spin coating and sonicated sol-gel immersion techniques, respectively. The properties of NiO nanosheet films at as-deposited, 300 ℃, and 500 ℃-annealed were examined by X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), ultraviolet-visible (UV-vis) spectroscopy, and humidity sensor measurement system. The XRD patterns demonstrate that the grown NiO films have crystalline cubic structures at temperature of 300 ℃ and 500 ℃. The FESEM images show that the large porous nanosheet network spread over the layers as the annealing temperature increased. The UV-vis spectra revealed that all the nanosheet films have the average transmittance below than 50% in the visible region, with absorption edges ~ 350 nm. The optical band gap energy was evaluated in ranges of 3.39 to 3.61 eV. From the obtained humidity sensing results, it shows that 500 ℃-annealed film exhibited the best sensitivity of 257, as well as the slowest response time, and the fastest recovery time compared with others.
A Control Packet Minimized Routing Protocol for Ad-hoc Wireless Networks Youn-Sik Hong
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: February 2014
Publisher : Institute of Advanced Engineering and Science

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

Abstract

AODV routing protocol is intended for use by mobile nodes in ad-hoc wireless networks. As the degree of node mobility becomes high, however, the number of RREQ and RREP messages during the route discovery process increase so rapidly. The unexpected increases in the number of control packets cause the destination node to decrease the packet receiving rate. Besides, the overall energy consumption for the network can be increased. Thus, we propose a novel method of adaptively controlling the occurrences of the control packets based on AIAD (additive increase additive decrease) under a consideration of the current network status. We have tested our proposed method with both the conventional AODV and the method using timestamp based on the three performance metrics; i.e., node mobility, node velocity, and node density, to compare their performances. DOI : http://dx.doi.org/10.11591/telkomnika.v12i2.4179
Research on Rock Burst Monitoring and Early Warning Technology Based on RBF Neural Network Yong Zhang; Hui Cai; Yunfu Cheng
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.pp7478-7485

Abstract

China is one of the most serious coal mine accidents inthe countries of the world. All of the accidents, rock burst is one of them. Therock burst in coal and rock mass, refers to the sudden power failure, release alarge number of catastrophic dynamic phenomena of energy. It can be destroy theroadway roof, cause other mine disasters, casualties and so on. In China, themine number with rock burst dangerous accounted for more than 20% of the total,Shandong QufuXing cun coal mine among them. In order to prevent to the happen of accident,the coal mine enterprise had been install all kinds of monitoring system, suchas SOS micro seismic system , Fully mechanized working face resistance ofsupport system and so on. Using sensors measuring and computer technology, thedata had been getting from the underground 1000 meters. According to the internal link ofpressure behavior between the basic regularity and variable, RBF neural networkhad been set up. From the model, it can forecast the risk index of rock burst,reveal the superincumbent stratum roof movement; master the process of stateand changes in the laws of underground pressure. It is important significanceto guide safe production of coal mine enterprises.
Optimal Power Flow using the Moth Flam Optimizer: A Case Study of the Algerian Power System Bachir Bentouati; Lakhdar Chaib; Saliha Chettih
Indonesian Journal of Electrical Engineering and Computer Science Vol 1, No 3: March 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v1.i3.pp431-445

Abstract

In this paper, a new technique of optimization known as Moth-Flam Optimizer (MFO) has been proposed to solve the problem of the Optimal Power Flow (OPF) in the interconnected power system, taking into account the set of equality and inequality constraints. The proposed algorithm has been presented to the Algerian power system network for a variety of objectives. The obtained results are compared with recently published algorithms such as; as the Artificial Bee Colony (ABC), and other meta-heuristics. Simulation results clearly reveal the effectiveness and the robustness of the proposed algorithm for solving the OPF problem. 
Electric Insulation Detection Method for High-voltage Insulators Wang Jiajun; Hong Bin; Wang Hongmei
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 7: July 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

The principle of partial discharge detection is that through partial bridged discharge under high voltage electric field, it detects the inner air-filled cavity of high-voltage insulators. And it is a nondestructive detection method based on discharge magnitude to judge the insulation quality. The detecting system that adopts the partial discharge detection is more rigorous than testing system for electricity products, which must have small discharge capacity and higher sensitivity. This paper describes the principles of partial discharge detection and analysis insulation detection. DOI: http://dx.doi.org/10.11591/telkomnika.v11i7.2862
Arrhythmia Classification Based on Combined Chaotic and Statistical Feature Extraction Jayagopi G; Pushpa S
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 1: October 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i1.pp127-136

Abstract

Obvious information content in Electro cardio graph has become mandatory to reveal the abnormalities in the heart functions. Arrhythmia is commonly seen heart disorder and results in fatal end, if not identified and treated properly within time limits. The straight forward scene in such diagnosis is to detect the salient features from the Electro cardio graph data using signal processing methods followed by proper classification methods.  16 classes of Arrhythmia had been classified in this work by adopting the traditional method of abnormality detection while introducing a novelty in the type of features to be extracted. Lyapunov Exponents, Kolmogorov Sinai Entropy Density, Kolmogorov Sinai Entropy Universality and R-R interval features based on Kurtosis and Skewness had been used to classify the heart beats from the benchmark MIT-Arrhythmia database. Since alternative features had been utilized, common Support Vector Machines based classification could produce an accuracy of 98.95% in the proposed work with just 13 features.
Mammogram Analysis using League Championship Algorithm Optimized Ensembled FCRN Classifier Saraswathi D; Srinivasan E
Indonesian Journal of Electrical Engineering and Computer Science Vol 5, No 2: February 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v5.i2.pp451-461

Abstract

An intelligent mammogram diagnosis system can be very helpful for radiologist in detecting the abnormalities earlier than typical screening techniques. This paper investigates a new classification approach for detection of breast abnormalities in digital mammograms using League Championship Algorithm Optimized Ensembled Fully Complex valued Relaxation Network (LCA-FCRN). The proposed algorithm is based on extracting curvelet fractal texture features from the mammograms and classifying the suspicious regions by applying a pattern classifier. The whole system includes steps for pre-processing, feature extraction, feature selection and classification to classify whether the given input mammogram image is normal or abnormal. The method is applied to MIAS database of 322 film mammograms. The performance of the CAD system is analysed using Receiver Operating Characteristic (ROC) curve. This curve indicates the trade-offs between sensitivity and specificity that is available from a diagnostic system, and thus describes the inherent discrimination capacity of the proposed system. The result shows that the area under the ROC curve of the proposed algorithm is 0.985 with a sensitivity of 98.1% and specificity of 92.105%. Experimental results demonstrate that the proposed method can form an effective CAD system, and achieve good classification accuracy.
The statistical analysis of random-valued impulse noise detection techniques based on the local image characteristic: ROAD, ROLD and RORD Vorapoj Patanavijit; Kornkamol Thakulsukanant
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 2: August 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i2.pp794-803

Abstract

Advances in local image statistical analysis have made possible the random-valued impulse noise detection but the current noise detections based on ROAD (Rank-Ordered Absolute Differences), ROLD (Rank-Ordered Logarithmic Differences) and RORD (Rank-Ordered Relative Differences), which are the most three effective and practical detections using the local image statistical characteristic, operates effectively on different noise density and different image statistical characteristic. To address these issues, this paper proposes the comparative analysis on the noise detections based on ROAD, ROLD and RORD. Therefore, the first contribution is the comparative statistical distribution of these three noise detections. By comprehensive experiment at each noise density, the optimized detected threshold is later determined from four benchmark data: Lena, Girl, Pepper and Airplane. Moreover, the maximum detection accuracy for each case is comparatively demonstrated by using the noise detections based on ROAD, ROLD and RORD with the optimized detected threshold.
Modeling and Control PV-Wind Hybrid System Based On Fuzzy Logic Control Technique Doaa M. Atia
Indonesian Journal of Electrical Engineering and Computer Science Vol 10, No 3: July 2012
Publisher : Institute of Advanced Engineering and Science

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Abstract

As energy demands around the world increase, the need for a renewable energy sources that will not harm the environment is increased. The overall objective of renewable energy systems is to obtain electricity that is cost competitive and even advantageous with respect to other energy sources. The optimal design of the renewable energy system can significantly improve the economical and technical performance of power supply. This paper presents the power management control using fuzzy logic control technique. Also, a complete mathematical modeling and MATLAB SIMULINK model for the proposed the electrical part of an aquaculture system is implemented to track the system performance. The simulation results show that, the feasibility of control technique. DOI: http://dx.doi.org/10.11591/telkomnika.v10i3.603
Electricity Consumption Prediction Based on SVR with Ant Colony Optimization Haijiang Wang; Shanlin Yang
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 11: November 2013
Publisher : Institute of Advanced Engineering and Science

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

Abstract

Accurate forecasting of electric load has always been the most important issues in the electricity industry, particularly for developing countries. Due to the various influences, electric load forecasting reveals highly nonlinear characteristics. This paper creates a system for power load forecasting using support vector machine and ant colony optimization. The method of colony optimization is employed to process large amount of data and eliminate. The SVR model with ant colony optimization is proposed according to the characteristics of the nonlinear electricity consumption data. Then ACO-SVR model is applied to the electricity consumption prediction of Jiangsu province. The result shows better than the ANNs method and improves the accuracy of the prediction. DOI: http://dx.doi.org/10.11591/telkomnika.v11i11.3557

Page 110 of 920 | Total Record : 9199

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