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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 9,226 Documents
 299   300   301   302   303 
Moisture Transfer Models and Drying Characteristics of MSW Containing High Moisture CHEN Shu; Xiao-qian MA; Zeng-ying LIANG
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 3: March 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

The effect of high moisture content on drying characteristics of high moisture municipal solid waste (MSW) material, such as carrot peel and pomelo peel was investigated. The experimental data used to fit the selected published mathematical drying models of samples， were conducted in a thermogravimetric furnace. Weight reduction during drying was measured with a microbalance in the range of 80-140℃. The variations of moisture content and drying rate at different temperature were considered. The results show that with increasing in drying temperature the drying time decreased and the maximum drying rate increased at the beginning of drying process .The effective diffusivity ranged from 1.49×10-9 to 1.25×10-8m2/s with Fick’s diffusion equation. The activation energy value of 17.12kJ/mol and 37.48kJ/mol was determined through Arrhenius equation. The Modified Page model and Weibull distribution model were the most adequate models in describing the drying process of MSW samples. DOI : http://dx.doi.org/10.11591/telkomnika.v12i3.4478
Ultrasonic Wind Velocity Measurement Based on Phase Discrimination Technique Chunyu Yu; Chao Guo; Jia-yi Liang; Tong Wang
Indonesian Journal of Electrical Engineering and Computer Science Vol 10, No 6: October 2012
Publisher : Institute of Advanced Engineering and Science

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Abstract

According to the shortcomings of the existing ultrasonic wind velocity measurement device, for instance, complexity of circuit and difficulty of signal processing, a new ultrasonic wind velocity measurement is put forward based on phase discrimination and a new sensor configuration as well. Thus, a system model is built. Firstly, an equilateral triangle should be constituted by an ultrasonic emission sensor and two ultrasonic receiving sensors. Then by high-precision phase discrimination circuit, the lag between the ultrasonic which is received by two ultrasonic receiving sensors during the traveling time in the upwind and downwind is converted to the phase difference. After that, the wind velocity is measured. Besides, a mathematical model is established among the wind velocity, the ultrasonic velocity, and the structural parameters with ambient temperature. The factors which influence the precision of the wind velocity measurement are analyzed and the solutions are given as well. The experimental results show that in view of the phase discrimination technology, the system has a good numerical stability and the resolution is one order magnitude better than that of the cup anemometer.  DOI:http://dx.doi.org/10.11591/telkomnika.v10i6.1443
Design of Volatility Model in Nifty 50 Index using Thin Plate Spline Regression Poornima B; Vijayalakshmi C; Somasundaram S
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 2: August 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v7.i2.pp426-433

Abstract

The analysis of volatility in stock markets has important consequences for investors and traders. The presence of volatility increases market risks and therefore discourages investment in the stock market. The proper study and understanding of volatility is needed for prudent risk management. In this paper, the market volatility in the National Stock Exchange in India as measured by the India Volatility Index is analyzed. The daily volatility in NIFTY 50 index is regressed on the price to earnings ratio and the volatility of previous day. The market volatility within a period of time is highly correlated and the highly volatile periods coincide with large impact negative events on a national and global scale. The Price to Earnings ratio represent the fundamentals of the market and it also strongly influences the price movements. The nonlinear regression problem is formulated and solved using thin plate spline regression technique. This effectively captures the nonlinear aspect of the problem. Results indicate that volatility has high upward correlation during middle range of P/E ratios than in the upper and lower ranges. Therefore risk management techniques using option derivatives are more important during the middle range of values of P/E ratio.
Object Recognition Inspiring HVS Mohammadesmaeil Akbarpour; Nasser Mehrshad; Seyyed-Mohammad Razavi
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: November 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i2.pp783-793

Abstract

Human recognize objects in complex natural images very fast within a fraction of a second. Many computational object recognition models inspired from this powerful ability of human. The Human Visual System (HVS) recognizes object in several processing layers which we know them as hierarchically model. Due to amazing complexity of HVS and the connections in visual pathway, computational modeling of HVS directly from its physiology is not possible. So it considered as a some blocks and each block modeled separately. One models inspiring of HVS is HMAX which its main problem is selecting patches in random way. As HMAX is a hierarchical model, HMAX can enhanced with enhancing each layer separately. In this paper instead of random patch extraction, Desirable Patches for HMAX (DPHMAX) will extracted.  HVS for extracting patch first selected patches with more information. For simulating this block patches with more variance will be selected. Then HVS will chose patches with more similarity in a class. For simulating this block one algorithm is used. For evaluating proposed method, Caltech 5 and Caltech101 datasets are used. Results show that the proposed method (DPMAX) provides a significant performance over HMAX and other models with the same framework.
Fast surveillance video indexing & retrieval with WiFi MAC address tagging K. L. Tan; K. C. Lim
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 1: October 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i1.pp473-481

Abstract

Conventional public safety surveillance video camera systems required 24/7 monitoring of security officers with video wall display installed in the control room. When a crime or incident is reported, all the recorded surveillance video streams nearby the incident area are playback simultaneously on video wall to help locate the target person. The security officers can fast forward the video playback to speed up the video search, but it requires massive manpower if there are hundreds of video streams required to be examined on the video wall. One of the possible solutions is through a suitable video indexing and retrieval technique to prioritize the video frames that need to be processed. This paper presents a WiFi sniffer enabled surveillance camera, with 3-stage WiFi frame inspection filter and the use of collected WiFi signal strength for filtering, to tag the collected WiFi MAC addresses to the surveillance video frames according to the time of the MAC address is sniffed. Additional metadata (WiFi MAC address of smartphone) collected during the occurrence of the incident can be used to prioritize the retrieving of surveillance video frames for subsequent image processing. 
Research on Backlash Nonlinearity in AC Servo-driven Precision Transmission System Wei Zhou; Ling Zhao; Xiaolun Li; Lihong Lin
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 6: June 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

AC servo-driven precision transmission system is mainly composed of AC servo motor, mechanical transmission parts and control parts. Because of mutual coupling between various parts, particularly transmission system in mechanical coupling vibration in non-smooth transition, it will be of great harm to safe operation of the system. This paper made some overview and built the model of AC servo-driven precision transmission system mainly from the perspective of backlash nonlinear characteristic and with simulation tool of Matlab/Simulink to analyze the influence of backlash on the precision of servo system, and then corresponding simulation curve and conclusions were shown in this paper. Do hope the work above will have certain reference significance to actual engineering application. DOI : http://dx.doi.org/10.11591/telkomnika.v12i6.5394
The research of railway freight statistics system and statistical methods Wu Hua-Wen; Wang Fu-Zhang
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 3: March 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

EXT is a JavaScript framework for developing Web interfaces, this paper describes the Ext framework and its application in railway freight statistical and analyzing system and Statistical methods. the paper also analyzes the design, function, implementation and so on of the system in detail. As information technology and the requirements of railway transportation organization and operation continue to improve, railway freight statistical and analyzing system improves obviously in the index system, decision analysis and other aspects, better meeting the work requirements. It will play a more important role in the railway transport organization, management, passenger and freight marketing. DOI: http://dx.doi.org/10.11591/telkomnika.v11i3.2206
Indonesian online travel agent sentiment analysis using machine learning methods Abimanyu Dharma Poernomo; Suharjito Suharjito
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.pp113-117

Abstract

Many companies use social media to support their business activities. Three leading online travel agent such as Traveloka, Tiket.com, and Agoda use Facebook for supporting their business as customer service tool. This study is to measure customer satisfaction of Traveloka, Tiket.com, and Agoda by analyzing Facebook posts and comments data from their fan pages. That data will be analyzed with three machine learning algorithms such as K-Nearest Neighbors (KNN), Naïve Bayes, and Support Vector Machine (SVM) to determine the sentiment.  From the classification results, data will be selected with the highest f-score to be used to calculate the Net Sentiment Score used to measure customer satisfaction. The result shows that KNN result better than Naive Bayes and SVM based on f-score. Based on Net Sentiment Score shows companies that get the highest satisfaction value of Traveloka followed by Tiket.com and Agoda
Efficiency of Flat File Database Approach in Data Storage and Data Extraction for Big Data Mohd Kamir Yusof; Mustafa Man
Indonesian Journal of Electrical Engineering and Computer Science Vol 9, No 2: February 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v9.i2.pp460-473

Abstract

Big data is the latest industry buzzword to describe large volume of structured and unstructured data that can be difficult to process and analyze. Most of organization looking for the best approach to manage and analyze the large volume of data especially in making a decision. XML and JSON are chosen by many organization because of powerful approach during retrieval and storage processes. However, these approaches, the execution time for retrieving large volume of data are still considerably inefficient due to several factors. In this contribution, three databases approaches namely Extensible Markup Language (XML), Java Object Notation (JSON) and Flat File database approach were investigated to evaluate their suitability for handling thousands records of publication data. The results showed flat file is the best choice for query retrieving speed and CPU usage. These are essential to cope with the characteristics of publication’s data. Whilst, XML, JSON and Flat File database approach technologies are relatively new to date in comparison to the relational database. Indeed, Text File Format technology demonstrates greater potential to become a key database technology for handling huge data due to increase of data annually.
Ozone prediction based on support vector machine M. Tanaskuli; Ali N. Ahmed; Nuratiah Zaini; Samsuri Abdullah; Abdoulhdi A. Borhana; N. A. Mardhiah; Mathivanan Mathivanan
Indonesian Journal of Electrical Engineering and Computer Science Vol 17, No 3: March 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v17.i3.pp1461-1466

Abstract

The prediction of tropospheric ozone concentrations is very important due to negative effects of ozone on human health, atmosphere and vegetation. Ozone Prediction is an intricate procedure and most of the conventional models cannot provide accurate prediction. Machine Learning techniques have been widely used as an effective tool for prediction. This study is investigating the implementation of Support vector Machine-SVM to predict Ozone concentrations. The results show that the SVM is capable in predicting ozone concentrations with acceptable level of accuracy. Sensitivity analysis has been conducted to show what is the most effective parameters on the proposed model.

Page 301 of 923 | Total Record : 9226

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