2017 14th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)最新文献_第3页

Romanized Thai input method editor 罗马化泰语输入法编辑器

2017 14th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON) Pub Date : 2017-06-01 DOI: 10.1109/ECTICON.2017.8096229

Supawan Tasanaprasert, Wimonsiri Pokasame, Sittan Rattanaliam

引用次数: 0

Electroencephalographic study of Jenga game brain training 叠叠游戏脑训练的脑电图研究

2017 14th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON) Pub Date : 2017-06-01 DOI: 10.1109/ECTICON.2017.8096159

Kittika Sarikavanich, Vichit Boonyahotra, Phakkharawat Sittiprapaporn

引用次数: 0

Spatial abilities improve brain-computer interface performance indexed by electroencephalography 空间能力提高脑机接口性能由脑电图指标

2017 14th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON) Pub Date : 2017-06-01 DOI: 10.1109/ECTICON.2017.8096166

Phassaramon Promsorn, Vichit Boonyahotra, Phakkharawat Sittiprapaporn

引用次数: 3

An adaptive pulse charging algorithm for lithium batteries 锂电池自适应脉冲充电算法

2017 14th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON) Pub Date : 2017-06-01 DOI: 10.1109/ECTICON.2017.8096212

S. M. I. Niroshana, S. Sirisukprasert

引用次数: 10

Four-phase isolated DC-DC converter 四相隔离DC-DC变换器

2017 14th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON) Pub Date : 2017-06-01 DOI: 10.1109/ECTICON.2017.8096348

F. Ebrahimzadeh, E. Babaei, Carlo Cecati, C. Buccella

引用次数: 1

Electrical conductivity and pH adjusting system for hydroponics by using linear regression 基于线性回归的水培电导率和pH调节系统

2017 14th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON) Pub Date : 2017-06-01 DOI: 10.1109/ECTICON.2017.8096350

Theeramet Kaewwiset, T. Yooyativong

引用次数: 15

Vehicle classification using neural network 基于神经网络的车辆分类

2017 14th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON) Pub Date : 2017-06-01 DOI: 10.1109/ECTICON.2017.8096269

Nou Sotheany, C. Nuthong

{"title":"Vehicle classification using neural network","authors":"Nou Sotheany, C. Nuthong","doi":"10.1109/ECTICON.2017.8096269","DOIUrl":"https://doi.org/10.1109/ECTICON.2017.8096269","url":null,"abstract":"Traffic congestion is one of the major problems in the big cities. Many systems are proposed to solve this problem, for example, Intelligent Transportation System(ITS). In general, ITS consists of many subsystems including traffic monitoring. The monitoring system can provide the information of vehicles that pass through the monitoring area. This information can suggests about the status of the traffic. For this reason, developing a system that can classify vehicle with high accuracy plays important role to support ITS. The proposed system of vehicle classification using neural network presents in this paper includes other techniques i.e. vehicle detection and vehicle occlusion handling. Furthermore, Back-propagation neural network and Radial basis function network are implemented for vehicle classification. The training dataset of these two neural network classifiers is taken from a traffic video while the testing dataset is taken from another traffic video. The experimental results show that both techniques can classify vehicles only 71% accuracy because the different size of detected vehicles in those two videos. In order to solve this problem, affine transform function is implemented to scale the object of the testing video. After implementing affine transformation to the system, the accuracy of Back-propagation technique increases to 86% while Radial basis function remains the same. The experimental results illustrate that Back-propagation neural network can classify vehicles with higher accuracy and better performance than Radial basis function network.","PeriodicalId":273911,"journal":{"name":"2017 14th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)","volume":"89 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133110521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

WSN-based reconfigurable water quality monitoring system in IoT environment 物联网环境下基于wsn的可重构水质监测系统

2017 14th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON) Pub Date : 2017-06-01 DOI: 10.1109/ECTICON.2017.8096345

Cho Zin Myint, Lenin Gopal, Y. Aung

{"title":"WSN-based reconfigurable water quality monitoring system in IoT environment","authors":"Cho Zin Myint, Lenin Gopal, Y. Aung","doi":"10.1109/ECTICON.2017.8096345","DOIUrl":"https://doi.org/10.1109/ECTICON.2017.8096345","url":null,"abstract":"In internet of things (IT) environment, a sensor interface device is essential for data collection in wireless sensor network (WSN) system for water quality monitoring (WQM) as the water pollution is a critical issue globally. This paper presents the design of a WSN based reconfigurable smart sensor interface device for WQM system in an IoT environment. The system consists of Field Programmable Gate Array (FPGA) design board, sensors, ZigBee based wireless communication module and personal computer (PC). The FPGA board performs as the heart of the proposed WQM system and it is programmed in very high speed integrated circuit hardware description language (VHDL) and C++ using Qsys tool and Nios-II SBT for Eclipse in Quartus II software. The proposed system collects the data of water quality such as water pH, water level, turbidity, carbon dioxide (CO2) on the surface of water and water temperature in parallel and in real-time basis with high speed from five different sensor nodes. The performance of the proposed reconfigurable WSN system is verified through computer simulation and laboratory experiments.","PeriodicalId":273911,"journal":{"name":"2017 14th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133214326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 29

Design and smulation of sensorless BLDC motor drive using DTC and SWF 无传感器无刷直流电动机驱动的设计与仿真

2017 14th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON) Pub Date : 2017-06-01 DOI: 10.1109/ECTICON.2017.8096382

A. Movahedi, G. Shahgholian

引用次数: 1

Reactive power compensation for solving voltage problems in PV farm based upon IEC — 61850 基于IEC - 61850的解决光伏电站电压问题的无功补偿

2017 14th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON) Pub Date : 2017-06-01 DOI: 10.1109/ECTICON.2017.8096246

Suntichai Uaroon, P. Khemmook, S. Khomfoi

引用次数: 1