Proceedings of the 3rd International Conference on Integrated Intelligent Computing Communication & Security (ICIIC 2021)最新文献_第3页

The Nonsplit Resolving Domination Polynomial of a Graph 图的非分裂解析支配多项式

Proceedings of the 3rd International Conference on Integrated Intelligent Computing Communication & Security (ICIIC 2021) Pub Date : 1900-01-01 DOI: 10.2991/ahis.k.210913.006

N. Pushpa, B. V. Dhananjayamurthy

{"title":"The Nonsplit Resolving Domination Polynomial of a Graph","authors":"N. Pushpa, B. V. Dhananjayamurthy","doi":"10.2991/ahis.k.210913.006","DOIUrl":"https://doi.org/10.2991/ahis.k.210913.006","url":null,"abstract":"Metric representation of a vertex v in a graph G with an ordered subset R = {a1, a2, ... , ak} of vertices of G is the kvector r(v|R) = (d(v, a1), d(v, a2), ... , d(v, ak)), where d(v, a) is the distance between v and a in G. The set R is called a Resolving set of G , if any two distinct vertices of G have distinct representation with respect to R . The cardinality of a minimum resolving in G is called a dimension of G, and is denoted by dim(G). In a graph G = (V, E), A subset D ⊆ V is a nonsplit resolving dominating set of G if it is a resolving, and nonsplit dominating set of G. The minimum cardinality of a nonsplit resolving dominating set of Gis known as a nonsplit resolving domination number of G, and is represented by γnsr(G) . In network reliability domination polynomial has found its application [20], a resolving set has diverse applications which includes verification of network and its discovery, mastermind game, robot navigation, problems of pattern recognition, image processing, optimization and combinatorial search [19]. Here, we are introducing nonsplit resolving domination polynomial of G. Some properties of the nonsplit Resolving domination polynomial of Gare studied and nonsplit resolving domination polynomials of some well-known families of graphs are calculated.","PeriodicalId":417648,"journal":{"name":"Proceedings of the 3rd International Conference on Integrated Intelligent Computing Communication & Security (ICIIC 2021)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124715792","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 Study of Communication Protocols for Internet of Things (IoT) Devices: Review 物联网(IoT)设备通信协议研究综述

Proceedings of the 3rd International Conference on Integrated Intelligent Computing Communication & Security (ICIIC 2021) Pub Date : 1900-01-01 DOI: 10.2991/ahis.k.210913.033

M. Jamuna, A. Prakash

引用次数: 2

A Deep Learning Approach to Detect COVID-19 一种检测COVID-19的深度学习方法

Proceedings of the 3rd International Conference on Integrated Intelligent Computing Communication & Security (ICIIC 2021) Pub Date : 1900-01-01 DOI: 10.2991/ahis.k.210913.032

C. Shrada, Balakrishna Gudla, K. Chaithra, T. S. Hassini

{"title":"A Deep Learning Approach to Detect COVID-19","authors":"C. Shrada, Balakrishna Gudla, K. Chaithra, T. S. Hassini","doi":"10.2991/ahis.k.210913.032","DOIUrl":"https://doi.org/10.2991/ahis.k.210913.032","url":null,"abstract":"Covid-19 is a viral disease that has been spreading rapidly infects both human beings and animals. The lifestyle of people, their physical and mental well-being and the economic condition of a country are distressingly disturbed due to the viral disease. Recently, vaccines have been prepared for COVID19 which have quite winning results. Yet we are unsure about the long-term effects of the vaccine. In a clinical study of COVID-19 infected patients shows that the covid patients are more likely to be infected from a lung infection after coming in contact with the virus. Chest x-ray (i.e., radiography) and chest computed tomography (CT) are a more effective imaging technique for diagnosing lung related problems. Yet, a significant chest x-ray is a lower cost process in comparison to chest CT. Adding to the previous statement, a chest X-ray helps to identify unusual and abnormal formations of a large variety of chest diseases such as pneumonia, cystic fibrosis, emphysema, cancer, etc. Deep learning is the most successful technique of machine learning, which provides useful analysis that can detect the COVID-19 virus and differentiate between a healthy lung and a virus infected lung successfully. Medical imaging, such as X-rays and CT scans, can aid in the early diagnosis of COVID-19 patients, allowing for more prompt therapy. For prediction, a Convolutional Neural Network (CNN) extracts information from chest x-ray pictures has been done. In order to classify an image as COVID or normal we need to have a segmented target so as to obtain this we use filters so that we can get the edge of the image. Keras Image Data Generator class is used to generate augmented images. Classification is performed with two classes: COVID-19 and","PeriodicalId":417648,"journal":{"name":"Proceedings of the 3rd International Conference on Integrated Intelligent Computing Communication & Security (ICIIC 2021)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130943993","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

Cybersecurity Vulnerabilities and Defence Techniques in Aviation Industry 航空工业的网络安全漏洞与防御技术

Proceedings of the 3rd International Conference on Integrated Intelligent Computing Communication & Security (ICIIC 2021) Pub Date : 1900-01-01 DOI: 10.2991/ahis.k.210913.071

Shazah Ishtiaq, Nor Azlina Abd Rahman

引用次数: 0

Quality Attributes for an LMS Cognitive Model for User Experience Design and Evaluation of Learning Management Systems 面向学习管理系统用户体验设计与评价的LMS认知模型的质量属性

Proceedings of the 3rd International Conference on Integrated Intelligent Computing Communication & Security (ICIIC 2021) Pub Date : 1900-01-01 DOI: 10.2991/ahis.k.210913.029

Emmanuel O. C. Mkpojiogu, O. E. Okeke-Uzodike, E. I. Emmanuel

引用次数: 7

Implementation of IoT in Patient Health Monitoring and Healthcare for Hospitals 物联网在医院患者健康监测和医疗保健中的实施

Proceedings of the 3rd International Conference on Integrated Intelligent Computing Communication & Security (ICIIC 2021) Pub Date : 1900-01-01 DOI: 10.2991/ahis.k.210913.059

Liew Yi Kent, I. F. Kamsin

引用次数: 3

A Comprehensive Review on Smart IoT Applications 智能物联网应用综述

Proceedings of the 3rd International Conference on Integrated Intelligent Computing Communication & Security (ICIIC 2021) Pub Date : 1900-01-01 DOI: 10.2991/ahis.k.210913.069

Shimon Nathaniel Koshy, I. F. Kamsin, N. Zainal

引用次数: 1

Predicting Growth and Trends of COVID-19 by Implementing Machine Learning Algorithms 通过实施机器学习算法预测COVID-19的增长和趋势

Proceedings of the 3rd International Conference on Integrated Intelligent Computing Communication & Security (ICIIC 2021) Pub Date : 1900-01-01 DOI: 10.2991/ahis.k.210913.075

D. M. Vistro, M. Farooq, A. Rehman, M. O. Aftab

{"title":"Predicting Growth and Trends of COVID-19 by Implementing Machine Learning Algorithms","authors":"D. M. Vistro, M. Farooq, A. Rehman, M. O. Aftab","doi":"10.2991/ahis.k.210913.075","DOIUrl":"https://doi.org/10.2991/ahis.k.210913.075","url":null,"abstract":"Artificial Intelligence has absolutely revolutionized the world in which we live, and with the passing of time it advances exponentially. The applications of AI are tremendous like healthcare and medical solutions, disease diagnostics, agriculture, developing security infrastructures, Autonomous vehicles, intelligent systems, industrial manufacturing, robotics and so much more. COVID19 is a deadly virus that started from china in 2019 and started to spread rapidly and within time spread throughout various countries of world and in 2020 the world went to a huge pandemic and many lives were lost due to this deadly virus causing to a major health hazard. Moreover, in 2021 many countries experience other new forms of the Covid19 that are faster to spread and more deadly. The spread and growth need to me monitored and evaluated to control the spread. The paper states the proposed methodology to evaluate insights of the growth rate or number of cases along with the death rate of COVID19 to getter better visualization to impose lockdown and area evacuation for population safety. We have applying popular Machine Learning algorithms for the forecast of COVID19 including Naive Bayes, Bayes Net, Decision Tree, Random Forest, Logistic Regression. Moreover, the technique will help to evaluate the trend to get better insights for behaviour analysis of COVID19. This study would aid policymakers in taking the required steps in advance, such as preparing isolation wards, ensuring the supply of drugs and paramedical staff, deciding partial or complete lockdown strategies, recruiting volunteers, and developing economic strategies. Out of all techniques, Random Forest algorithm outstands others with the highest accuracy of 87.28% with precision and recall of 89% and 85% respectively.","PeriodicalId":417648,"journal":{"name":"Proceedings of the 3rd International Conference on Integrated Intelligent Computing Communication & Security (ICIIC 2021)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130097873","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

ASD Classification in Adolescent and Adult Utilizing Deep Neural Network 基于深度神经网络的青少年和成人ASD分类

Proceedings of the 3rd International Conference on Integrated Intelligent Computing Communication & Security (ICIIC 2021) Pub Date : 1900-01-01 DOI: 10.2991/ahis.k.210913.025

A. Mohanty, Priyadarsan Parida, K. C. Patra

引用次数: 0

IoT-based Child Security Monitoring System 基于物联网的儿童安全监控系统

Proceedings of the 3rd International Conference on Integrated Intelligent Computing Communication & Security (ICIIC 2021) Pub Date : 1900-01-01 DOI: 10.2991/ahis.k.210913.058

Lai Yi Heng, I. F. Kamsin

引用次数: 1