2015 Fifth International Conference on Advanced Computing & Communication Technologies最新文献_第2页

EEG Signal Analysis for BCI Interface: A Review 脑机接口的脑电信号分析综述

2015 Fifth International Conference on Advanced Computing & Communication Technologies Pub Date : 2015-02-21 DOI: 10.1109/ACCT.2015.72

Swati Vaid, Preeti Singh, Chamandeep Kaur

{"title":"EEG Signal Analysis for BCI Interface: A Review","authors":"Swati Vaid, Preeti Singh, Chamandeep Kaur","doi":"10.1109/ACCT.2015.72","DOIUrl":"https://doi.org/10.1109/ACCT.2015.72","url":null,"abstract":"Brain Computer Interface (BCI) systems are the devices which are proposed to help the disabled, people who are incapable of making motor response to communicate with computer using brain signal. The aim of BCI is to interpret brain activity into digital form which acts as a command for a computer. One key challenge in current BCI research is how to extract features of random time-varying EEG signals and its classification as accurately as possible. Feature extraction techniques are used to extract the features which represent a unique property obtained from pattern of brain signal. Earlier EEG analysis was restricted to visual inspection only. The visual inspection of the signal is very subjective and hardly allows any standardization or statistical analysis. Hence, several different techniques were intended in order to quantify the information of the brain signal. Many linear and non-linear methods for feature extraction exist. The purpose of this paper is to give a brief introduction to the EEG signals and BCI system. The paper also includes a review on the conventional methods that are used for feature extraction of the signal.","PeriodicalId":351783,"journal":{"name":"2015 Fifth International Conference on Advanced Computing & Communication Technologies","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129178644","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: 142

Comparing Data Mining Techniques for Mining Patents 专利挖掘的数据挖掘技术比较

2015 Fifth International Conference on Advanced Computing & Communication Technologies Pub Date : 2015-02-21 DOI: 10.1109/ACCT.2015.119

Nisha Mattas, Smarika, D. Mehrotra

引用次数: 8

Distributed Energy Adaptive Location-Based Cooperative MAC Protocol for Prolonging the Network Lifetime of MANET 基于分布式能量自适应位置的协同MAC协议，延长MANET网络生存期

2015 Fifth International Conference on Advanced Computing & Communication Technologies Pub Date : 2015-02-21 DOI: 10.1109/ACCT.2015.48

P. Das, V. Gulhane

引用次数: 2

SPIN with Cluster for Data Centric Wireless Sensor Networks SPIN与集群的数据中心无线传感器网络

2015 Fifth International Conference on Advanced Computing & Communication Technologies Pub Date : 2015-02-21 DOI: 10.1109/ACCT.2015.76

Ashutosh Tripathi, N. Yadav, R. Dadhich

引用次数: 4

A Study of Conventional and Junctionless MOSFET Using TCAD Simulations 传统和无结MOSFET的TCAD仿真研究

2015 Fifth International Conference on Advanced Computing & Communication Technologies Pub Date : 2015-02-21 DOI: 10.1109/ACCT.2015.51

N. Gupta, J. Patel, A. K. Raghav

引用次数: 12

Load Balancing in Region Based Clustering for Heterogeneous Environment in WSNs Using AI Techniques 基于AI技术的异构环境下基于区域聚类的负载均衡

2015 Fifth International Conference on Advanced Computing & Communication Technologies Pub Date : 2015-02-21 DOI: 10.1109/ACCT.2015.101

K. Singh, A. K. Daniel

引用次数: 4

Channel Management Algorithm for Modeling Network Throughput in IEEE 802.11 WLAN IEEE 802.11 WLAN网络吞吐量建模的信道管理算法

2015 Fifth International Conference on Advanced Computing & Communication Technologies Pub Date : 2015-02-21 DOI: 10.1109/ACCT.2015.15

R. Krishan, V. Laxmi

引用次数: 0

Low Power Memristor Based 7T SRAM Using MTCMOS Technique 基于MTCMOS技术的低功耗记忆电阻7T SRAM

2015 Fifth International Conference on Advanced Computing & Communication Technologies Pub Date : 2015-02-21 DOI: 10.1109/ACCT.2015.58

Vijay Singh Baghel, S. Akashe

{"title":"Low Power Memristor Based 7T SRAM Using MTCMOS Technique","authors":"Vijay Singh Baghel, S. Akashe","doi":"10.1109/ACCT.2015.58","DOIUrl":"https://doi.org/10.1109/ACCT.2015.58","url":null,"abstract":"In recent years demand of low power devices is increasing and the reason behind this is scaling of CMOS technology. Due to the scaling, size of the chip decreases and number of transistor in system on chip (SOC) increases and this phenomenon also apply on memories that are used in SOC. Generally the number of transistors used in chip to store data is more as compared to the number of transistors used for other function. So in future the need of low power memories is increasing and to design low power memories leakage power is attentive parameter to design low power devices because it plays a major role in increasing the total power consumption of the devices. In this paper, 7T simple SRAM and technique based 7T SRAM has been designed and parameters like total power and leakage power has been calculated. SRAM (Static Random Access Memory) is a type of memory that provide a link with CPU and designing of SRAM is very critical because it takes large part of power and area therefore to achieve low power SRAM we have designed Memristor based SRAM. Memristor is a forth missing non-linear resistor which acts as memory and it improves the power and speed. It is invented in 1971 by L. O. Chua and in this paper MTCMOS (Multi Threshold CMOS) technique is used, recently it is very famous in academia and industry. It is a power reducing technique that helps in reducing leakage power in the SRAM by turning of the inactive circuit domains. Designing and calculation of parameters of simple SRAM, Memristor based SRAM and MTCMOS based Memristor SRAM has been done with cadence virtuoso tool and that was done at 45 nm technology with the operating voltage of 0.7 volt.","PeriodicalId":351783,"journal":{"name":"2015 Fifth International Conference on Advanced Computing & Communication Technologies","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132538153","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: 26

Design of Full Adder Circuit Using Double Gate MOSFET 双栅MOSFET全加法器电路的设计

2015 Fifth International Conference on Advanced Computing & Communication Technologies Pub Date : 2015-02-21 DOI: 10.1109/ACCT.2015.37

J. K. Sahani, Shiwani Singh

引用次数: 6

Facial Behavior Recognition Using Soft Computing Techniques: A Survey 基于软计算技术的面部行为识别研究进展

2015 Fifth International Conference on Advanced Computing & Communication Technologies Pub Date : 2015-02-21 DOI: 10.1109/ACCT.2015.132

Khyati J. Kantharia, Ghanshyam I. Prajapati

{"title":"Facial Behavior Recognition Using Soft Computing Techniques: A Survey","authors":"Khyati J. Kantharia, Ghanshyam I. Prajapati","doi":"10.1109/ACCT.2015.132","DOIUrl":"https://doi.org/10.1109/ACCT.2015.132","url":null,"abstract":"Human facial behaviour recognition can be defined as the process of identifying human internal feelings or mood from the classification of facial expression and gesture. Human facial expression and gesture recognition have a many real world applications such as Human Machine Intelligent Interaction (HMII), Smart rooms, Advance Driver Assistance Systems (ADAS), Intelligent Robotics, Monitoring and Surveillance, Gaming, Research on pain and depression, Health support appliances. Facial Expression Recognition is challenging problem up till now because of many reasons, moreover, it consists of three sub challenging tasks face detection, facial feature extraction and expression classification. Soft computing is a computer science field that applies to the problem whose solution is unpredictable or inexact. Digital image processing works effectively together with soft computing techniques to improve efficiency of recognizing human facial behaviour through machine. This paper gives a review on the mechanisms of human facial behavior recognition using soft computing techniques, which includes a brief detail on framework, literature survey and key issues in facial behaviour recognition using soft computing.","PeriodicalId":351783,"journal":{"name":"2015 Fifth International Conference on Advanced Computing & Communication Technologies","volume":"168 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114599119","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: 11