Recent Trends in Intensive Computing最新文献_第2页

MISP: Model for IaaS Security and Privacy MISP: IaaS安全和隐私模型

Recent Trends in Intensive Computing Pub Date : 2021-12-01 DOI: 10.3233/apc210222

IndraKumar Sahua, Manisha J Nenea

引用次数: 0

Real Time Human Gesture Recognition: Methods, Datasets and Strategies 实时人类手势识别:方法、数据集和策略

Recent Trends in Intensive Computing Pub Date : 2021-12-01 DOI: 10.3233/apc210202

Rameez Shamalik, S. Koli

引用次数: 3

EyePhone Technology: A Smart Wearable Device 眼听技术:一种智能可穿戴设备

Recent Trends in Intensive Computing Pub Date : 2021-12-01 DOI: 10.3233/apc210231

K. Kharade, S. Kharade, S. R. Ghatage, V. Kumbhar, T. Nandana Ravishankar, K. Vengatesan

{"title":"EyePhone Technology: A Smart Wearable Device","authors":"K. Kharade, S. Kharade, S. R. Ghatage, V. Kumbhar, T. Nandana Ravishankar, K. Vengatesan","doi":"10.3233/apc210231","DOIUrl":"https://doi.org/10.3233/apc210231","url":null,"abstract":"In the past few decades, wearable sensors and devices have evolved into central technologies that have significantly impacted next-generation healthcare solutions in the previous decade. It is an age of incredibly cut-throat competition, even the youth. This technology is Hand-free, eyephone-operated telephone technology. It measures where the user’s eyes are located on the phone’s display employing a camera attached to the device. The typical work the eye bones assigned to eye tracking, eye blinking, detecting, etc., by way of eye-tracking, users can take care of their email, calendar, phone, etc. The leading technologies in use are a Human-Computer Interface (HCI) and a Human Phone Interface (HPI). It helps those with disabilities greatly. The IT Index is an expanded form of HCI. The use of mobile devices like smartphones and tablets is on the rise, and, to some extent, it could displace the use of desktops and laptops. Human-computer interaction is interested in the interaction between people and the computer system and between software and applications. Our focus is on this revolutionary new type of technology called the eye-phone.","PeriodicalId":429440,"journal":{"name":"Recent Trends in Intensive Computing","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123416185","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: 0

A Survey on Mining Cryptocurrencies 关于挖矿加密货币的调查

Recent Trends in Intensive Computing Pub Date : 2021-12-01 DOI: 10.3233/apc210212

Tejaswini Pawar, S. Shirsat, Yaminee Patil, Vijay R. Sonawane, Dhiraj A. Birari

引用次数: 1

Data Privacy Preservation and Security Approaches for Sensitive Data in Big Data 大数据环境下敏感数据的数据隐私保护与安全方法

Recent Trends in Intensive Computing Pub Date : 2021-12-01 DOI: 10.3233/apc210221

Rohit Ravindra Nikam, Rekha Shahapurkar

{"title":"Data Privacy Preservation and Security Approaches for Sensitive Data in Big Data","authors":"Rohit Ravindra Nikam, Rekha Shahapurkar","doi":"10.3233/apc210221","DOIUrl":"https://doi.org/10.3233/apc210221","url":null,"abstract":"Data mining is a technique that explores the necessary data is extracted from large data sets. Privacy protection of data mining is about hiding the sensitive information or identity of breach security or without losing data usability. Sensitive data contains confidential information about individuals, businesses, and governments who must not agree upon before sharing or publishing his privacy data. Conserving data mining privacy has become a critical research area. Various evaluation metrics such as performance in terms of time efficiency, data utility, and degree of complexity or resistance to data mining techniques are used to estimate the privacy preservation of data mining techniques. Social media and smart phones produce tons of data every minute. To decision making, the voluminous data produced from the different sources can be processed and analyzed. But data analytics are vulnerable to breaches of privacy. One of the data analytics frameworks is recommendation systems commonly used by e-commerce sites such as Amazon, Flip Kart to recommend items to customers based on their purchasing habits that lead to characterized. This paper presents various techniques of privacy conservation, such as data anonymization, data randomization, generalization, data permutation, etc. such techniques which existing researchers use. We also analyze the gap between various processes and privacy preservation methods and illustrate how to overcome such issues with new innovative methods. Finally, our research describes the outcome summary of the entire literature.","PeriodicalId":429440,"journal":{"name":"Recent Trends in Intensive Computing","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124836256","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

A GSM Based Assistive Device for Blind, Deaf and Dumb 一种基于GSM的盲人、聋哑人辅助设备

Recent Trends in Intensive Computing Pub Date : 2021-12-01 DOI: 10.3233/apc210267

Lavanya Dhanesh, Monica S, Revathi R, Suganya S, Swetha Lakshmi K N

引用次数: 0

A Compact Disc Shaped Microstrip Patch Antenna Using Inset Fed at 5GHz for Satellite Communications 一种用于5GHz卫星通信的嵌入式馈电光盘微带贴片天线

Recent Trends in Intensive Computing Pub Date : 2021-12-01 DOI: 10.3233/apc210181

A. Pon Bharathi, A. J. Wilson, S. Arun, V. Ramanathan

引用次数: 2

Cascading of Air Quality Detector and Digital Data Transmission with Zero Error in Minimum Duration 空气质量检测器级联与最小持续时间零误差数字数据传输

Recent Trends in Intensive Computing Pub Date : 2021-12-01 DOI: 10.3233/apc210269

Anitha R, Veerasundaram M, Rajarajan S, Jaya Prakash E, NandhaKishore J, Ajay Krishnan S R

引用次数: 0

Chennai Water Resource Management Using GIS 基于GIS的金奈水资源管理

Recent Trends in Intensive Computing Pub Date : 2021-12-01 DOI: 10.3233/apc210220

Saral Purohit, Gadhiya Jay Dipakbhai, G. Abirami

引用次数: 0

Customer Analysis Using Machine Learning Algorithms: A Case Study Using Banking Consumer Dataset 使用机器学习算法的客户分析:使用银行消费者数据集的案例研究

Recent Trends in Intensive Computing Pub Date : 2021-12-01 DOI: 10.3233/apc210263

R. Siva Subramanian, D. Prabha, B. Maheswari, J. Aswini

{"title":"Customer Analysis Using Machine Learning Algorithms: A Case Study Using Banking Consumer Dataset","authors":"R. Siva Subramanian, D. Prabha, B. Maheswari, J. Aswini","doi":"10.3233/apc210263","DOIUrl":"https://doi.org/10.3233/apc210263","url":null,"abstract":"The aim of each enterprise is to achieve high revenue from the business and to stay in a high position from their competitors. To archive high revenue and high position from competitors the need of understanding the business consumers is a crucial one. However the firm business is completely dependent on the consumers the efficient analysis of consumers within the enterprises makes to achieve the business to high position. To perform effective consumer analysis, in this study different machine learning is studied and experimented. ML classifiers make to understand in-depth analysis about the consumer data and further enables to plan wise decision strategies to enhance the business revenue and consumer satisfaction intelligently. The use of different ML classifiers is to sort out how the customer prediction outcome changes accordingly to the ML classifier is applied. This makes to find the best ML classifier for the consumer dataset applied in this study. The experimental procedure is performed using different ML classifiers and the outcome achieved is captured and projected using various validity scores. This work applies different ML classifiers like K-NN, C4.5, Random Forest, Random Tree, LR, MLP and NB for customer analysis. The empirical results illustrate the C4.5 model achieves better accuracy prediction compare to other ML classifiers and also compared with the time complexity NB model works efficiently with running time.","PeriodicalId":429440,"journal":{"name":"Recent Trends in Intensive Computing","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121634962","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