2021 22nd International Arab Conference on Information Technology (ACIT)最新文献_第5页

A Study of Factors influencing eWoM Credibility among Millennials: A Case Study of Chennai City 千禧一代eom可信度影响因素研究——以金奈市为例

2021 22nd International Arab Conference on Information Technology (ACIT) Pub Date : 2021-12-21 DOI: 10.1109/acit53391.2021.9677097

R. Babu, N. Nawaz, V. Gajenderan

{"title":"A Study of Factors influencing eWoM Credibility among Millennials: A Case Study of Chennai City","authors":"R. Babu, N. Nawaz, V. Gajenderan","doi":"10.1109/acit53391.2021.9677097","DOIUrl":"https://doi.org/10.1109/acit53391.2021.9677097","url":null,"abstract":"The study's purpose is examining whether the factors influencing the Credibility among the Millennial. The study is used in both primary & secondary data. The secondary data obtained from the earlier publications in research papers, magazines, articles, and textbooks related to eWoM Credibility. The Primary data accumulated from the Millennial who is aware of the eWoM Credibility. Data collected with proper development of a structured survey from a sample of 1000 Millennials in Chennai city. The Millennials were chosen randomly throughout Chennai city and different Sectors. Out of 1000 responses, 217 responses are not adequately filled by the millennial. Therefore these responses rejected, and the rest 783 responses used for the final study. The regression model results explain a significant influence of factors towards the eWoM Credibility among the Millennial. Whereas, the model overall its predictors extremely strong to give details the variability related to eWoM credibility. Overall, the factors, namely Quality, Polarity, Logic & Articulation, Sources, and Prior Knowledge, and Expertise, significantly influence eWoM Credibility among Millennials.","PeriodicalId":302120,"journal":{"name":"2021 22nd International Arab Conference on Information Technology (ACIT)","volume":"184 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113981809","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

An Efficient System to Predict Customers’ Satisfaction on Touristic Services Using ML and DL Approaches 利用ML和DL方法预测旅游服务客户满意度的有效系统

2021 22nd International Arab Conference on Information Technology (ACIT) Pub Date : 2021-12-21 DOI: 10.1109/acit53391.2021.9677167

Said Gadri, Sara Ould Mehieddine, K. Herizi, Safia Chabira

{"title":"An Efficient System to Predict Customers’ Satisfaction on Touristic Services Using ML and DL Approaches","authors":"Said Gadri, Sara Ould Mehieddine, K. Herizi, Safia Chabira","doi":"10.1109/acit53391.2021.9677167","DOIUrl":"https://doi.org/10.1109/acit53391.2021.9677167","url":null,"abstract":"In the last decade, neural networks NNs become a favorable solution for many applications in artificial intelligence AI. For instance, the majority of tourism companies have professional websites where customers can book: flights, bus and taxi trips, hotels, restaurants, etc. they can also compare services in terms of prices, locations, services quality, and other interesting criterion. For this purpose, the used dataset consists of a sample of hotel reviews provided by customers who have reserved recently. Analyzing these reviews will help companies to know if their services are suitable for customers, satisfy their needs and what is the degree of this satisfaction. i.e., customers are happy or not? Satisfied or not? Our main objective in this work is to develop an efficient and intelligent system based on NNs which allows us to predict how customers feel about the provided services. To accomplish this work, we have proceeded to the classification task using many machine learning algorithms, including LDA, KNN, CART, NB, and SVM. Then, we proposed in the second stage a deep neural network DNN model to perform the same task. Finally, we established a short comparison between the different algorithms. In the programming stage, we benefited from the large opportunities offered by Python language, as well as Tensorflow and Keras libraries.","PeriodicalId":302120,"journal":{"name":"2021 22nd International Arab Conference on Information Technology (ACIT)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116740674","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

Internet of Robotic Things: Current Technologies and Applications 机器人物联网:当前技术与应用

2021 22nd International Arab Conference on Information Technology (ACIT) Pub Date : 2021-12-21 DOI: 10.1109/ACIT53391.2021.9677407

G. Samara, Abla Hussein, Israa Abdullah Matarneh, Mohammed Alrefai, Maram Y. Al-Safarini

{"title":"Internet of Robotic Things: Current Technologies and Applications","authors":"G. Samara, Abla Hussein, Israa Abdullah Matarneh, Mohammed Alrefai, Maram Y. Al-Safarini","doi":"10.1109/ACIT53391.2021.9677407","DOIUrl":"https://doi.org/10.1109/ACIT53391.2021.9677407","url":null,"abstract":"The Internet of Robotic Things (IoRT) is a new domain that aims to link the IoT environment with robotic systems and technologies. IoRT connects robotic systems, connects them to the cloud, and transfers critical information as well as knowledge exchange to conduct complicated and intricate activities that a human cannot readily perform. The pertinent notion of IoRT has been discussed in this paper, along with the issues that this area faces on a daily basis. Furthermore, technological applications have been examined in order to provide a better understanding of IoRT and its current development phenomenon. The study describes three layers of IoRT infrastructure: network and control, physical, and service and application layer. In the next section, IoRT problems have been presented, with a focus on data processing and the security and safety of IoRT technological systems. In addition to discussing the difficulties, appropriate solutions have been offered and recommended. IoRT is regarded as an essential technology with the ability to bring about a plethora of benefits in smart society upon adoption, contributing to the generation and development of smart cities and industries in the near future.","PeriodicalId":302120,"journal":{"name":"2021 22nd International Arab Conference on Information Technology (ACIT)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114742113","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

Multilevel Classification of Pakistani News using Machine Learning 使用机器学习的巴基斯坦新闻多层次分类

2021 22nd International Arab Conference on Information Technology (ACIT) Pub Date : 2021-12-21 DOI: 10.1109/acit53391.2021.9677431

Anum Ilyas, S. Obaid, N. Bawany

{"title":"Multilevel Classification of Pakistani News using Machine Learning","authors":"Anum Ilyas, S. Obaid, N. Bawany","doi":"10.1109/acit53391.2021.9677431","DOIUrl":"https://doi.org/10.1109/acit53391.2021.9677431","url":null,"abstract":"The availability of innumerable sources of online news has benefitted the masses as they have opportunity to gather news from a diverse set of sources. However, classification of this huge data being generated on regular basis has never been a simple task. This textual information can be invaluable only when it is processed to maximize its usefulness which is possible with automated text classification. Natural Language Processing (NLP) and Machine learning techniques have been extensively applied in this particular domain to address this challenge. Text classification is helpful in several scenarios such as product mining, emotions or sentiment analysis, etc. News classification is one of its applications through which content of news is processed and analyzed to assign predefined label(s). This research is focused on classification of Pakistani news obtained from dataset available on Open Data Pakistan. We have applied various machine learning algorithms including Logistic Regression, Random Forest, Support Vector Machine, and Naïve Bayes for first-level classification and Logistic Regression for multilevel classification. Comparative analysis of these algorithms is also presented. We achieved a maximum of 97.8% accuracy through Support Vector Machine in single-level classification and 83% through Logistic Regression in multilevel text classification.","PeriodicalId":302120,"journal":{"name":"2021 22nd International Arab Conference on Information Technology (ACIT)","volume":"731 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128293200","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

Improving VANET's Performance by Incorporated Fog-Cloud Layer (FCL) 利用雾云层(FCL)改善VANET的性能

2021 22nd International Arab Conference on Information Technology (ACIT) Pub Date : 2021-12-21 DOI: 10.1109/ACIT53391.2021.9677345

G. Samara, Mohammed Rasmi, Nael A. Sweerky, E. A. Daoud, A. A. Salem

引用次数: 2

Matching Applicants with Positions for Better Allocation of Employees in the Job Market 将申请人与职位配对，以便在就业市场上更好地分配员工

2021 22nd International Arab Conference on Information Technology (ACIT) Pub Date : 2021-12-21 DOI: 10.1109/acit53391.2021.9677374

Ziad Elgammal, Abdullah Barmu, Hamza Hassan, K. Elgammal, Tansel Özyer, R. Alhajj

引用次数: 2

DiscimusRW: An E-Learning Web Application for Classifying Random Walks with Machine Learning DiscimusRW:一个基于机器学习的随机漫步分类电子学习Web应用

2021 22nd International Arab Conference on Information Technology (ACIT) Pub Date : 2021-12-21 DOI: 10.1109/acit53391.2021.9677258

Afrah Mahmoud Mousa, Thorsten Auth, A. Samara, Suhail M. Odeh

{"title":"DiscimusRW: An E-Learning Web Application for Classifying Random Walks with Machine Learning","authors":"Afrah Mahmoud Mousa, Thorsten Auth, A. Samara, Suhail M. Odeh","doi":"10.1109/acit53391.2021.9677258","DOIUrl":"https://doi.org/10.1109/acit53391.2021.9677258","url":null,"abstract":"Random walks are key for many fundamental processes, including the diffusion of substances in solvents, epidemics’ spread, and financial markets’ development. Machine learning applications have not only revolutionized research in various areas, such as image processing and protein structure prediction, but are also abundant in daily life. For example, machine learning enables us to develop self-driving cars and helps us to improve online shopping suggestions. Both random walks and machine learning are often taught theoretically in schools and universities because of the lack of means to provide experiential learning opportunities. However, the absence of experiential learning may cause low educational attainment rates of students in courses that address these topics. Here, we discuss a web-based online system based on Django web technology to support teaching random walks and machine learning. The application uses machine learning models to classify 2D random walks that a user can provide. In a teaching setting, the application can—for example—be applied to determine the sizes of spherical particles that diffuse based on their trajectories.","PeriodicalId":302120,"journal":{"name":"2021 22nd International Arab Conference on Information Technology (ACIT)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129173435","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

Enhancing Flood Prediction using Ensemble and Deep Learning Techniques 利用集成和深度学习技术增强洪水预测

2021 22nd International Arab Conference on Information Technology (ACIT) Pub Date : 2021-12-21 DOI: 10.1109/acit53391.2021.9677084

Isaac Kofi Nti, O. Nyarko-Boateng, S. Boateng, F. U. Bawah, P. Agbedanu, N. S. Awarayi, P. Nimbe, Adebayo Felix Adekoya, B. Weyori, V. Akoto-Adjepong

{"title":"Enhancing Flood Prediction using Ensemble and Deep Learning Techniques","authors":"Isaac Kofi Nti, O. Nyarko-Boateng, S. Boateng, F. U. Bawah, P. Agbedanu, N. S. Awarayi, P. Nimbe, Adebayo Felix Adekoya, B. Weyori, V. Akoto-Adjepong","doi":"10.1109/acit53391.2021.9677084","DOIUrl":"https://doi.org/10.1109/acit53391.2021.9677084","url":null,"abstract":"Though flooding is seen as a common environmental threat globally, it has dramatically increased recently due to climate change, impacting underdeveloped and developing countries dangerously. For example, in most developing countries like Ghana, flooding has affected over four million people in terms of property damage, loss of lives, income and spread of diseases, resulting in economic harm beyond USD780 million. At least one major flood disaster does occur yearly. The recurring incidences of flooding and associated calamitous socio-economic risks and anticipated increase of its prevalence soon in cities of developing countries such as Ghana have necessitated an intelligence system to offer efficient and early warning of its occurrence. In this study, we explore the potential of the machine learning (ML) computing paradigm to propose a flooding prediction model. Specifically, four state-of-the-art ML algorithms, namely long short-term memory (LSTM), extreme gradient boosting (XGBoost), random forest (RF) and extremely randomised trees (Extra Trees), are used to implement four different flood prediction models. We measure the performance of our developed models with multiple statistical performance evaluators. The experimental results show the potential of the developed models for efficient and effective prediction of flooding. The merit of this study lies in the fact that it is the first to the best of our knowledge to use a combination of environmental factors from Ghana and machine learning algorithms to develop intelligent flood models to help stakeholders make informed decisions.","PeriodicalId":302120,"journal":{"name":"2021 22nd International Arab Conference on Information Technology (ACIT)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129592333","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

An Empirical Study of Evaluating the Correlation between Class Stability and Bad Smells 班级稳定性与不良气味相关性评价的实证研究

2021 22nd International Arab Conference on Information Technology (ACIT) Pub Date : 2021-12-21 DOI: 10.1109/acit53391.2021.9677443

Mohammad H. Yahia, M. Amro, M. Alshayeb

引用次数: 0

A New Hybrid Approach of Gravitational Search Algorithm with Spiral-Shaped Mechanism-based RBF Neural Network 基于螺旋机构的RBF神经网络与重力搜索算法混合的新方法

2021 22nd International Arab Conference on Information Technology (ACIT) Pub Date : 2021-12-21 DOI: 10.1109/acit53391.2021.9677424

Zohaib Y Ahmad, Muhammad Qasim Memon, Aasma Memon, Parveen Munshi, M. J. Memon

引用次数: 0