2020 Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA)最新文献_第4页

Study of Evolution By Automating Hardy Weinberg Equilibrium With Machine Learning Techniques In TensorFlow And Keras 用机器学习技术在TensorFlow和Keras中自动化Hardy Weinberg平衡的进化研究

2020 Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA) Pub Date : 2020-07-01 DOI: 10.1109/ACCTHPA49271.2020.9213202

Karthika Balan, M. Santora, M. Faied, V. Carmona-Galindo

{"title":"Study of Evolution By Automating Hardy Weinberg Equilibrium With Machine Learning Techniques In TensorFlow And Keras","authors":"Karthika Balan, M. Santora, M. Faied, V. Carmona-Galindo","doi":"10.1109/ACCTHPA49271.2020.9213202","DOIUrl":"https://doi.org/10.1109/ACCTHPA49271.2020.9213202","url":null,"abstract":"Evolution transpires in organism populations and includes population diversity, heredity and varying survival. One way to study evolution is to study how the frequency of a population’s allele varies from generation to generation. An allele is a type of gene variant. In other words, rather than looking at two parental species, evolution should be investigated by looking at the population as a whole. The only way to do this is therefore to investigate how allele frequencies shift in populations and how these shifts will predict what will happen to a population in the future. Throughout biology, there are basic equations which are used to model this theory basically termed as Hardy-Weinberg principle. This paper describes a new method that integrates Ecology and Engineering by automating the Hardy-Weinberg model using ADAM Optimization technique. The neural network trained based on Keras and Tensorflow has been deployed using python for the study of evolution. The developed model is tested with standard allele frequency database “ALFRED” to prove the efficiency.","PeriodicalId":191794,"journal":{"name":"2020 Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130167830","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: 3

Decision Tree approach to Identify Vision Disorder for lazy Eye 判定弱视视力障碍的决策树方法

2020 Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA) Pub Date : 2020-07-01 DOI: 10.1109/ACCTHPA49271.2020.9213204

P. K. Pant, Devendra Singh, Himanshu Pant, Ayush Kapri

引用次数: 0

Sentiment Analysis for Predicting Customer Reviews using a Hybrid Approach 使用混合方法预测顾客评论的情感分析

2020 Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA) Pub Date : 2020-07-01 DOI: 10.1109/ACCTHPA49271.2020.9213236

A. Rajeswari, M. Mahalakshmi, R. Nithyashree, G. Nalini

{"title":"Sentiment Analysis for Predicting Customer Reviews using a Hybrid Approach","authors":"A. Rajeswari, M. Mahalakshmi, R. Nithyashree, G. Nalini","doi":"10.1109/ACCTHPA49271.2020.9213236","DOIUrl":"https://doi.org/10.1109/ACCTHPA49271.2020.9213236","url":null,"abstract":"Sentiment Analysis is a widely used text classification technique. It breaks down any given text or comments and classify the text either as positive or negative based on the views conveyed in it. Previous works done on sentiment classification used either lexicon based approach or machine learning techniques. Likewise, the major drawback of the existing systems was the focus on only binary classification of review such as positive or negative. Ignorance of the neutral review will result in misinterpretation of a customer’s opinion about a product or movie, which will degrade the business or trend. In case of using only lexicon based approach, the system highly depends on the selection of lexicon resource and dictionary. In case of system built only using machine learning approach, the performance of the system depends on the algorithms chosen. This work presents a hybrid model to resolve the neutral class too. The proposed work combines a lexical approach (SentiWordNet) with the machine learning algorithms such as Support Vector Machine, Decision Tree, Logistic Regression and Naive Bayes for sentiment analysis to resolve the neutral opinions beyond the binary categorization of the customer’s review. We have also compared the performance of these four machine learning algorithms along with the lexicon approach. The results proved that Support Vector Machine and Logistic Regression algorithms outperform the other two algorithms with an accuracy of about 80% which is on average differs by 6% to 10% when compared to other algorithms.","PeriodicalId":191794,"journal":{"name":"2020 Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA)","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126309510","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: 7

ACCTHPA 2020 TOC Accthpa 2020 toc

2020 Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA) Pub Date : 2020-07-01 DOI: 10.1109/accthpa49271.2020.9213189

引用次数: 0

Digital Twin in Smart Farming: A Categorical Literature Review and Exploring Possibilities in Hydroponics 智能农业中的数字孪生:分类文献综述和探索水培法的可能性

2020 Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA) Pub Date : 2020-07-01 DOI: 10.1109/ACCTHPA49271.2020.9213235

T R Sreedevi, M. B. Santosh Kumar

引用次数: 23

Smart Servomotor for Robotics and its Cyber security 机器人智能伺服电机及其网络安全

2020 Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA) Pub Date : 2020-07-01 DOI: 10.1109/ACCTHPA49271.2020.9213226

K. Eswaran, Mada Sunil Sai Kumar, Deepa Thangavelusamy, Vinodharani Murugadoss

引用次数: 2

An Improved Upper Bound for Genome Rearrangement by Prefix Transpositions 基因组前缀转位重排的改进上界

2020 Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA) Pub Date : 2020-07-01 DOI: 10.1109/ACCTHPA49271.2020.9213217

Pramod P. Nair, Rajan Sundaravaradhan

引用次数: 2

Inverse Synthetic-Aperture Radar(ISAR) Images Recognition Using Deep Learning 基于深度学习的逆合成孔径雷达(ISAR)图像识别

2020 Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA) Pub Date : 2020-07-01 DOI: 10.1109/ACCTHPA49271.2020.9213223

Abhishek Avadhani, Sayli Chaudhari, Pehlaj Gacheria, Stuti Ahuja

引用次数: 2

Framework for Cloud based Messaging System using MQTT 使用MQTT的基于云的消息传递系统框架

2020 Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA) Pub Date : 2020-07-01 DOI: 10.1109/ACCTHPA49271.2020.9213215

J. Patil, Jairaj Vijay Bhiste, D. Pawar, M. V. Pawar

引用次数: 0

GAN Based Photo-Realistic Image Generation from Sketch using Nested U-Net 基于GAN的基于嵌套U-Net的素描真实感图像生成

2020 Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA) Pub Date : 2020-07-01 DOI: 10.1109/ACCTHPA49271.2020.9213230

T. Mahendran, S. Sharmilan

引用次数: 1