2022 14th International Conference on Computational Intelligence and Communication Networks (CICN)最新文献_第9页

A Data Mining Analysis of Cognitive Science and Artificial Intelligence 认知科学与人工智能的数据挖掘分析

2022 14th International Conference on Computational Intelligence and Communication Networks (CICN) Pub Date : 2022-12-04 DOI: 10.1109/CICN56167.2022.10008240

T. Brahimi, Hala Haneya, Asra Yaqub, Fatmah Al Salem, Joudi Bathallath

引用次数: 1

Live Feed Emotion Detection During Project Meetings To Estimate Possible Success of Projects 在项目会议期间进行实时情绪检测，以评估项目的成功可能性

2022 14th International Conference on Computational Intelligence and Communication Networks (CICN) Pub Date : 2022-12-04 DOI: 10.1109/CICN56167.2022.10008311

Zeenat AIKassim

引用次数: 0

Fine Tuning an AraT5 Transformer for Arabic Abstractive Summarization 用于阿拉伯语抽象摘要的AraT5变压器的微调

2022 14th International Conference on Computational Intelligence and Communication Networks (CICN) Pub Date : 2022-12-04 DOI: 10.1109/CICN56167.2022.10008272

Yasmin Einieh, Amal Almansour, A. Jamal

引用次数: 0

The possibility of artificial intelligence to improve self-driving in modern cars: scoping review 人工智能改善现代汽车自动驾驶的可能性:范围审查

2022 14th International Conference on Computational Intelligence and Communication Networks (CICN) Pub Date : 2022-12-04 DOI: 10.1109/CICN56167.2022.10008358

Razan Althubaiti

引用次数: 1

Correlation-based Clustering of Telecommunication Equipment in Smart Grid 智能电网中基于关联的电信设备聚类

2022 14th International Conference on Computational Intelligence and Communication Networks (CICN) Pub Date : 2022-12-04 DOI: 10.1109/CICN56167.2022.10008306

I. Mecheter, J. V. Garcia, Ricardo J. Almeida, Thiago M. Uchoa

引用次数: 0

AI Regulation in Healthcare: New Paradigms for A Legally Binding Treaty Under the World Health Organization 医疗保健领域的人工智能监管:世界卫生组织下具有法律约束力的条约的新范式

2022 14th International Conference on Computational Intelligence and Communication Networks (CICN) Pub Date : 2022-12-04 DOI: 10.1109/CICN56167.2022.10008303

Rabai Bouderhem

引用次数: 0

A New Cybersecurity Assessment Framework for Private Networks 一种新的专网网络安全评估框架

2022 14th International Conference on Computational Intelligence and Communication Networks (CICN) Pub Date : 2022-12-04 DOI: 10.1109/CICN56167.2022.10008317

S. Alshehri, Hashem Alaidaros, M. Arafah, S. H. Bakry

{"title":"A New Cybersecurity Assessment Framework for Private Networks","authors":"S. Alshehri, Hashem Alaidaros, M. Arafah, S. H. Bakry","doi":"10.1109/CICN56167.2022.10008317","DOIUrl":"https://doi.org/10.1109/CICN56167.2022.10008317","url":null,"abstract":"Cybersecurity is becoming of increasing importance, as the use of cyberspace is growing, and as the security challenges facing it are rising. The purpose of this paper is to develop a new cybersecurity assessment framework that provides a quantitative measurement of the cybersecurity state of private networks of organizations and consequently enables its future improvement. The framework is based on considering five domains of private network cybersecurity protection controls on the one hand, and on the quantitative assessment of the implementation state of these controls on the other. On this base, the framework identifies the domains and their protection controls based on recent version of ISO 27002:2022, and considering other international and national cybersecurity standards. Each control is refined into a set of implementation questions that enable providing a quantitative measurement indicator for the state of the control implementation. For providing a multilevel structure of the assessment outcomes, the indicators of the controls are grouped to provide sub-indices for the domains, and an overall index for the cybersecurity implementation state of a targeted network. The framework provides quantitative benchmarks to guide the required improvements of assessed networks. The use of the framework is finally illustrated through an assessment of a Saudi private network in an organization as case study.","PeriodicalId":287589,"journal":{"name":"2022 14th International Conference on Computational Intelligence and Communication Networks (CICN)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129143965","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

Email Security: Concept, Formulation, and Applications 电子邮件安全:概念、配方和应用

2022 14th International Conference on Computational Intelligence and Communication Networks (CICN) Pub Date : 2022-12-04 DOI: 10.1109/CICN56167.2022.10008382

A. Al-Ghushami, Dabeeruddin Syed, Ameema Zainab, Haya Abdelshahid, Haneen Al-Eshaq, Fatima Alsayed, Noora Al-Marri, Reem Alkuwari

引用次数: 2

Accurate Estimate of Autism Spectrum Disorder in Children Utilizing Several Machine Learning Techniques 利用几种机器学习技术准确估计儿童自闭症谱系障碍

2022 14th International Conference on Computational Intelligence and Communication Networks (CICN) Pub Date : 2022-12-04 DOI: 10.1109/CICN56167.2022.10008285

Narinderpal Kaur, Ganesh Gupta, Abdul Hafiz

{"title":"Accurate Estimate of Autism Spectrum Disorder in Children Utilizing Several Machine Learning Techniques","authors":"Narinderpal Kaur, Ganesh Gupta, Abdul Hafiz","doi":"10.1109/CICN56167.2022.10008285","DOIUrl":"https://doi.org/10.1109/CICN56167.2022.10008285","url":null,"abstract":"Autism Disorder is a neurologically proven disorder in which children have impaired communication and interaction abilities. Children with autism spectrum disorders are characterised by a lack of social engagement, repetitive behaviour, and unchanging interests. It is very important to diagnose it in the early stages of life. Nowadays, machine learning helps health care for such diagnoses, which also reduces the cost and time. The main goal of this research work is to imply different algorithms of machine learning in order to predict autism. In this study, the different classification methods for diagnosing ASD were used on children aged 4 to 11 years. The present study proposes the Support Vector Machine, K nearest neighbor, Decision Tree, and Linear Discriminant Analysis algorithms of machine learning to classify the autism spectrum disorder. A number of features are extracted from the data set using an algorithm and statistically analyzed. The dataset was separated into 70:30 ratios. A comparison of various performance measures was done after applying the mentioned algorithm. It is observed that decision trees and SVM give a higher accuracy of 99 percentage than KNN and LDA, with 70 percentage and 97 percentage, respectively. Python, which is commonly used for machine learning classifications, is used to calculate classifier performance.","PeriodicalId":287589,"journal":{"name":"2022 14th International Conference on Computational Intelligence and Communication Networks (CICN)","volume":"212 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117295898","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

Synchronization Techniques for Multi-threaded Web Server: A Comparative Study 多线程Web服务器同步技术的比较研究

2022 14th International Conference on Computational Intelligence and Communication Networks (CICN) Pub Date : 2022-12-04 DOI: 10.1109/CICN56167.2022.10008307

Hussah Albinali, Maha Alharbi, Randah Alharbi, M. Aljabri

{"title":"Synchronization Techniques for Multi-threaded Web Server: A Comparative Study","authors":"Hussah Albinali, Maha Alharbi, Randah Alharbi, M. Aljabri","doi":"10.1109/CICN56167.2022.10008307","DOIUrl":"https://doi.org/10.1109/CICN56167.2022.10008307","url":null,"abstract":"With the exponential growth and advancement of the internet and network technologies, the number of active internet users is expected to exceed 5 billion worldwide by 2025. As a result, designing high performance multi-threaded web server capable of concurrently handling thousands of incoming requests per second is in high demand. To achieve this goal, it is essential for the multi-threaded web server to utilize synchronization algorithm to coordinate the simultaneous use of resources by clients; avoid data inconsistency and still provide timely responses. The aim of this study is to compare and evaluate the performance of different traditional and modern synchronization algorithms adopted by multi-threaded web servers. An empirical experiment is conducted that simulates a file synchronization problem in distributed systems to evaluate how the performance of a multi-threaded web server is affected by those synchronization algorithms. Mutex locks, Spinlocks, Semaphore, and WebR2sync are evaluated, and the performance of each synchronization algorithm is measured using three performance metrics: Synchronization Time, Failure Rate, and Scalability. Results show that Semaphore has the fastest synchronization time, WebR2sync has the lowest failure rate, and Mutex excels at scalability. Such findings help with the decision of which synchronization algorithms to utilize for multi-threaded web servers based on the requirements.","PeriodicalId":287589,"journal":{"name":"2022 14th International Conference on Computational Intelligence and Communication Networks (CICN)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132435452","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