2017 International Conference on Emerging Trends in Computing and Communication Technologies (ICETCCT)最新文献_第2页

Improving coverage and connectivity using harmony search algorithm in wireless sensor network 利用和谐搜索算法提高无线传感器网络的覆盖和连通性

2017 International Conference on Emerging Trends in Computing and Communication Technologies (ICETCCT) Pub Date : 2017-11-01 DOI: 10.1109/ICETCCT.2017.8280297

Deepika Sharma, Vrinda Gupta

引用次数: 7

Particle-In-Cell (PIC) simulation of Spatial-Harmonic Magnetron (SHM) 空间谐波磁控管(SHM)的粒子池(PIC)仿真

2017 International Conference on Emerging Trends in Computing and Communication Technologies (ICETCCT) Pub Date : 2017-11-01 DOI: 10.1109/ICETCCT.2017.8280310

R. K. Verma, S. Maurya, Vindhyavasini Prasad Singh

引用次数: 1

A fuzzy AHP methodology for selecting the best microprocessor with respect to battery life, number of cores, threading and throughput 基于电池寿命、核数、线程和吞吐量选择最佳微处理器的模糊层次分析法

2017 International Conference on Emerging Trends in Computing and Communication Technologies (ICETCCT) Pub Date : 2017-11-01 DOI: 10.1109/ICETCCT.2017.8280322

Vaibhav Gupta, Vaibhav Agarwal, V. Bharadwaj, R. Chandna

{"title":"A fuzzy AHP methodology for selecting the best microprocessor with respect to battery life, number of cores, threading and throughput","authors":"Vaibhav Gupta, Vaibhav Agarwal, V. Bharadwaj, R. Chandna","doi":"10.1109/ICETCCT.2017.8280322","DOIUrl":"https://doi.org/10.1109/ICETCCT.2017.8280322","url":null,"abstract":"This era is marked by our complete dependence on electronic gadgets that help make our life easier in many ways. One of the electronic gadgets is a laptop that most of the people use when they need to get their work done in less space and comfort or while traveling. The major industry that uses the laptop on a daily basis is the education industry as almost every student requires to complete an assignment, surf the internet and perform many other tasks. The most primary field that students choose to pursue their graduation in computer science as in this field we get exposure to work and deal with the best. The renowned microprocessor manufacturing giant Intel has managed to take over its rivals and be at the peak of the table. Intel has given the computer industry the best microprocessors to date. The processor that we will be discussing in this paper is: — Intel Broadwell i5-5200U and Intel Haswell i5-4310U. These two have been and will remain a popular processor in the industry because of their efficiency and performance. But in most of the cases, people who go to buy these machines often get confused as to which version of the processor they should go for that can fulfill their needs and demands. An individual can never identify the differences between these two versions of the microprocessor by just looking at them or by carrying out simple tasks. We can only spot the difference between them when both are rendered under high-performance tasks that can get the most out of the processors. This research paper includes the mathematical derivation using Fuzzy AHP approach as to which one is the best for educational purpose. This paper will also help eliminate the confusion in choosing between the two processors. The factors the decision will be based on are: — battery life, number of cores, threading, throughput.","PeriodicalId":436902,"journal":{"name":"2017 International Conference on Emerging Trends in Computing and Communication Technologies (ICETCCT)","volume":" 27","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132159137","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: 1

Predicting parole hearing result using machine learning 利用机器学习预测假释听证结果

2017 International Conference on Emerging Trends in Computing and Communication Technologies (ICETCCT) Pub Date : 2017-11-01 DOI: 10.1109/ICETCCT.2017.8280342

Tribhuwan Singh, Yashvardhan Jain, Vaibhav Kumar

{"title":"Predicting parole hearing result using machine learning","authors":"Tribhuwan Singh, Yashvardhan Jain, Vaibhav Kumar","doi":"10.1109/ICETCCT.2017.8280342","DOIUrl":"https://doi.org/10.1109/ICETCCT.2017.8280342","url":null,"abstract":"Machine learning is the science of getting computers to learn without being explicitly programmed. Tom Mitchell gives a formal definition of machine learning according to which, “A computer program is said to learn from experience ‘E’ with respect to some class of tasks ‘T’ and performance measure ‘P’, if its performance at tasks in ‘T’, as measured by ‘P’, improves with experience ‘E’ “. Thousands of parole eligible criminals are denied release every year. We need to consider what effect different factors have on the decision of parole commissioners so that we can know the probability of a prisoner being released from prison. We aim to train a machine learning model with training data of about 20,000 criminals in New York State that would then be able to predict whether a criminal would be granted parole or not. The model would take into consideration various attributes of each criminal like age, gender, race, charges, interview facility, etc. We assume that all these factors are considered by the parole commissioners when taking a decision. The raw data is taken and cleaned before it can be fed to a machine learning algorithm. We convert the string values of our data into numeric values by assigning a unique numeric value to each unique string value. Once we have a dataset with only numeric values, we normalize each attribute. T h e n we feed the normalized data to the Neural Network backpropagation algorithm and the graphical visualizations of the results are obtained using MATLAB. We are able to develop a model that can predict the result based on the attributes with an accuracy of 76.8%.","PeriodicalId":436902,"journal":{"name":"2017 International Conference on Emerging Trends in Computing and Communication Technologies (ICETCCT)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116521951","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: 1

Design and performance analysis for the reversible realization of adder/subtractor circuit 加/减电路可逆实现的设计与性能分析

2017 International Conference on Emerging Trends in Computing and Communication Technologies (ICETCCT) Pub Date : 2017-11-01 DOI: 10.1109/ICETCCT.2017.8280324

Vandana Shukla, O. Singh, G. Mishra, R. K. Tiwari

引用次数: 3

Machine vision based detection of ageratum enation virus infection using light microscopic images of poppy plants cells 利用罂粟植物细胞的光镜图像，基于机器视觉检测萎蔫病毒感染

2017 International Conference on Emerging Trends in Computing and Communication Technologies (ICETCCT) Pub Date : 2017-11-01 DOI: 10.1109/ICETCCT.2017.8280306

Namita Sengar, A. Srivastava, M. Dutta

引用次数: 2

Study of temporal variation of vertical TEC using NavIC data 利用NavIC资料研究垂直TEC的时间变化

2017 International Conference on Emerging Trends in Computing and Communication Technologies (ICETCCT) Pub Date : 2017-11-01 DOI: 10.1109/ICETCCT.2017.8280317

Sharat Chandra Bhardwaj, A. Vidyarthi, B. Jassal, A. Shukla

引用次数: 12

A comparative study of PID based temperature control of CSTR using Genetic Algorithm and Particle Swarm Optimization 基于遗传算法和粒子群算法的PID CSTR温度控制的比较研究

2017 International Conference on Emerging Trends in Computing and Communication Technologies (ICETCCT) Pub Date : 2017-11-01 DOI: 10.1109/ICETCCT.2017.8280312

Swapnadeep Baruah, L. Dewan

引用次数: 12

Benefits of using particle swarm optimization and Voronoi diagram for coverage in wireless sensor networks 利用粒子群优化和Voronoi图对无线传感器网络进行覆盖的好处

2017 International Conference on Emerging Trends in Computing and Communication Technologies (ICETCCT) Pub Date : 2017-11-01 DOI: 10.1109/ICETCCT.2017.8280300

Manish Kumar, Vrinda Gupta

引用次数: 6

Characteristics and properties of audio signal and noise cancellation techniques: A theoretical review 音频信号和噪声消除技术的特点和特性:理论综述

2017 International Conference on Emerging Trends in Computing and Communication Technologies (ICETCCT) Pub Date : 2017-11-01 DOI: 10.1109/ICETCCT.2017.8280292

Janak Kapoor, G. Mishra, M. Rai

引用次数: 4