2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)最新文献

Assisting Information Systems students to Engage with the Internet of Things (IoT) 协助信息系统学生参与物联网(IoT)

2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence) Pub Date : 2020-01-01 DOI: 10.1109/Confluence47617.2020.9057849

Marita Turpin, M. Matthee, S. Kruger, Jean-Paul Van Belle

{"title":"Assisting Information Systems students to Engage with the Internet of Things (IoT)","authors":"Marita Turpin, M. Matthee, S. Kruger, Jean-Paul Van Belle","doi":"10.1109/Confluence47617.2020.9057849","DOIUrl":"https://doi.org/10.1109/Confluence47617.2020.9057849","url":null,"abstract":"The Fourth Industrial Revolution (4IR) will dramatically change our work and personal lives. New developments in the fields of artificial intelligence, big data and the internet of things (IoT) hold big promise but also present challenges to our entire society. However, only a very small fraction of the population is sufficiently versed in the new technologies to be able to make informed decisions on matters that will affect all our future lives. In addition, many people feel threatened and fear that they will lose their jobs. Even students in the fields of Information Systems (IS) and IT management do not feel familiar with and confident about their ability to navigate the world of 4IR. This study reports on a series of projects that have been undertaken in South Africa to encourage IS/IT students and professionals to embrace IoT technologies and to upskill themselves in this field. The projects have been undertaken from 2016 to 2019 at a South African university, by making use of a makerspace as well as a maker philosophy. Results indicate that the students and professionals were able to increase their skills as well as their confidence and attitude to engage with IoT technology. The contribution of this study is to suggest good practices for the use of IoT and a maker philosophy to prepare students and professionals for the world of 4IR.","PeriodicalId":180005,"journal":{"name":"2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117065268","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

Performance Evaluation of Load Balancing Algorithms Using Cloud Analyst 基于云分析的负载均衡算法性能评估

2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence) Pub Date : 2020-01-01 DOI: 10.1109/Confluence47617.2020.9058017

Archana Singh, R. Kumar

引用次数: 9

Age-Gender Analysis of Coronary Artery Calcium (CAC) Score to predict early Cardiovascular Diseases 冠状动脉钙(CAC)评分预测早期心血管疾病的年龄-性别分析

2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence) Pub Date : 2020-01-01 DOI: 10.1109/Confluence47617.2020.9058151

A. Bhatt, S. Dubey, A. Bhatt

引用次数: 0

Disease Prediction using Hybrid Optimization Methods based on Tuning Parameters 基于调优参数的混合优化方法的疾病预测

2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence) Pub Date : 2020-01-01 DOI: 10.1109/Confluence47617.2020.9058029

M. Anbarasi, K. S. Sendhil Kumar, R. Balamurugan, Thejasswini

引用次数: 0

Anti-Predatory NIA Based Approach for Optimizing Basic COCOMO Model 基于反掠夺性NIA的基本COCOMO模型优化方法

2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence) Pub Date : 2020-01-01 DOI: 10.1109/Confluence47617.2020.9058033

Rohit Kumar Sachan, D. S. Kushwaha

{"title":"Anti-Predatory NIA Based Approach for Optimizing Basic COCOMO Model","authors":"Rohit Kumar Sachan, D. S. Kushwaha","doi":"10.1109/Confluence47617.2020.9058033","DOIUrl":"https://doi.org/10.1109/Confluence47617.2020.9058033","url":null,"abstract":"Software Effort Estimation (SEE) is an important activity during development and production of software projects. The estimated effort is directly associated with the various planning and financial activities. It is also directly associated with business success. Constructive Cost Model (COCOMO) is a widely accepted SEE model. But in the current development scenario, existing parameters of COCOMO don't give realistic results. In the recent past, many researchers improved the performance of COCOMO by optimizing the parameters with the help of various Nature-Inspired Algorithms (NIAs). In this paper, a recently proposed NIA which is based on the frog's anti-predator behavior is used for the optimizing the parameters of basic COCOMO for SEE of 18 software projects listed in NASA data set. The performance of the Anti-Predatory NIA (APNIA) based proposed approach is also evaluated on NASA18 software data set in terms of the Mean Absolute Error (MAE). The result obtained shows 93.41% improvement in terms of MAE as compared to the basic COCOMO, 40.69% improvement as compared to Genetic Algorithm (GA) and 0.93% improvement as compared to Particle Swarm optimization (PSO) with inertia weight in effort estimation by proposed approach.","PeriodicalId":180005,"journal":{"name":"2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129503627","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

A Study on Machine Learning Based Anomaly Detection Approaches in Wireless Sensor Network 基于机器学习的无线传感器网络异常检测方法研究

2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence) Pub Date : 2020-01-01 DOI: 10.1109/Confluence47617.2020.9058311

Rajendra Kumar Dwivedi, Arun Kumar Rai, Rakesh Kumar

引用次数: 9

Recent Advances in Generative Adversarial Networks: An Analysis along with its outlook 生成对抗网络的最新进展:分析与展望

2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence) Pub Date : 2020-01-01 DOI: 10.1109/Confluence47617.2020.9058040

Priyanka Mahajan

{"title":"Recent Advances in Generative Adversarial Networks: An Analysis along with its outlook","authors":"Priyanka Mahajan","doi":"10.1109/Confluence47617.2020.9058040","DOIUrl":"https://doi.org/10.1109/Confluence47617.2020.9058040","url":null,"abstract":"From the past few years, Generative adversarial networks (GANs) have gained more and more interest of researchers of Artificial Intelligence and this is only due to the reliability on huge amount of data, well designed network architectures and smart training techniques because of which they produce highly realistic pieces of content of images, texts and sounds. The inspirational idea of working in GANs has been derived from game theory, named as the zero–sum game. GANs consist of two components-a generator as well as a discriminator both of which act like two players of the game playing in opposition with each other. This paper focuses on the basic theory and principle mechanism of GANs. Next, the paper discusses few variants based on architecture as well as loss functions of some kinds. Finally, the last section of paper presents few other variants of GANs which are implemented in the field of computer vision and other real world problems. It is found that this area has a wider scope in terms of virtual real interaction and integration along with parallel learning. So it is considered as new implementation area for GANs in the coming future.","PeriodicalId":180005,"journal":{"name":"2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121478115","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

Autonomic Resource Provisioning Framework for Service-based Cloud Applications: A Queuing-Model Based Approach 基于服务的云应用的自主资源供应框架:基于排队模型的方法

2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence) Pub Date : 2020-01-01 DOI: 10.1109/Confluence47617.2020.9058266

Tushar Bhardwaj, Himanshu Upadhyay, S. Sharma

{"title":"Autonomic Resource Provisioning Framework for Service-based Cloud Applications: A Queuing-Model Based Approach","authors":"Tushar Bhardwaj, Himanshu Upadhyay, S. Sharma","doi":"10.1109/Confluence47617.2020.9058266","DOIUrl":"https://doi.org/10.1109/Confluence47617.2020.9058266","url":null,"abstract":"The user’s request changes dynamically in service-based cloud applications, which requires optimal amount of computing resources to meet service-level agreements (SLAs). The existing server-side resource allocation mechanisms have limitations in provisioning the required resources to handle the incoming load on the basis of user’s requests. To overcome the aforementioned situation, cloud computing provides ample amount of computing resources to meet the SLAs. There are possibilities that cloud resources might not be properly utilized and might suffer over and under utilization. In this study, the authors have proposed an autonomic resource allocation framework, that automatically provisions (allocate and deallocate) the required computing resources as per the load. In this study, the proposed model leverages the queuing model to optimize the resource allocation process. The primary goal of this study is to improve the virtual resource utilization and response time with respect to the existing methods. Finally, the results have shown that the response time and resource utilization have been improved.","PeriodicalId":180005,"journal":{"name":"2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130684790","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: 4

Smart Protective Protection Equipment for an accessible work environment and occupational hazard prevention 智能防护设备，提供无障碍的工作环境和职业危害预防

2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence) Pub Date : 2020-01-01 DOI: 10.1109/Confluence47617.2020.9058188

M. Sánchez, Sergio, Corchado Rodríguez, J. Manuel

引用次数: 6

Neuro-Fuzzy Approach to Explosion Consequence Analysis 爆炸后果分析的神经模糊方法

2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence) Pub Date : 2020-01-01 DOI: 10.1109/confluence47617.2020.9058024

Lakshya Tyagi, Abhishek Singhal

引用次数: 0