检索结果-南通市图书馆

Arabic Sentiment Analysis of Users’ Opinions of Governmental Mobile Applications

Computers, Materials & Continua 2022年第9期72卷 4675-4689页

作者： mohammed Hadwan mohammed A.al-Hagery mohammed al-sarem Faisal Saeed Department of Information Technology College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Computer Science College of Applied SciencesTaiz UniversityTaizYemen Inteligent Analytic Group College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia College of Computer Science and Engineering Taibah UniversityMedina42353Saudi Arabia Institute for Artificial Intelligence and Big Data Universiti Malaysia KelantanPengkalan ChepaKota Bharu16100KelantanMalaysia

Different types of pandemics that have appeared from time to time have changed many aspects of daily *** governments encourage their citizens to use certain applications to help control the spread of disease and to deliver other services during *** Saudi government has launched several mobile apps to control the pandemic and have made these apps available through Google Play and the app store.A huge number of reviews are written daily by users to express their opinions,which include significant information to improve these *** manual processing and extracting of information from users’reviews is an extremely difficult and time-consuming ***,the use of intelligent methods is necessary to analyse users’reviews and extract issues that can help in improving these *** research aims to support the efforts made by the Saudi government for its citizens and residents by analysing the opinions of people in Saudi Arabia that can be found as reviews on Google Play and the app store using sentiment analysis and machine learning *** the best of our knowledge,this is the first study to explore users’opinions about governmental apps in Saudi *** findings of this analysis will help government officers make the right decisions to improve the quality of the provided services and help application developers improve these applications by fixing potential issues that cannot be identified during application testing phases.A new dataset used for this research includes 8000 user reviews gathered from social media,Google Play and the app *** methods are applied to the dataset,and the results show that the k nearest neighbourhood(KNN)method generates the highest accuracy compared to other implemented methods.

关键词： Arabic sentiment analysis software quality user satisfaction improving online governmental services machine learning intelligent systems mobile app

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

An Ensemble Learning Based Approach for Detecting and Tracking COVID19 Rumors

引用

Computers, Materials & Continua 2022年第1期70卷 1721-1747页

作者： Sultan Noman Qasem mohammed al-sarem Faisal Saeed Computer Science Department College of Computer and Information SciencesAl Imam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia Computer Science Department Faculty of Applied ScienceTaiz UniversityTaiz6803Yemen College of Computer Science and Engineering Taibah UniversityMedinaSaudi Arabia Information System Department Saba’a Region UniversityMareebYemen

Rumors regarding epidemic diseases such as COVID 19,medicines and treatments,diagnostic methods and public emergencies can have harmful impacts on health and political,social and other aspects of people’s lives,especially during emergency situations and health *** huge amounts of content being posted to social media every second during these situations,it becomes very difficult to detect fake news(rumors)that poses threats to the stability and sustainability of the healthcare sector.A rumor is defined as a statement for which truthfulness has not been *** COVID 19,people found difficulty in obtaining the most truthful news easily because of the huge amount of unverified information on social *** methods have been applied for detecting rumors and tracking their sources for COVID 19-related ***,very few studies have been conducted for this purpose for the Arabic language,which has unique ***,this paper proposes a comprehensive approach which includes two phases:detection and *** the detection phase of the study carried out,several standalone and ensemble machine learning methods were applied on the Arcov-19 dataset.A new detection model was used which combined two models:The Genetic algorithm Based Support Vector Machine(that works on users’and tweets’features)and the stacking ensemble method(that works on tweets’texts).In the tracking phase,several similarity-based techniques were used to obtain the top 1%of similar tweets to a target tweet/post,which helped to find the source of the *** experiments showed interesting results in terms of accuracy,precision,recall and F1-Score for rumor detection(the accuracy reached 92.63%),and showed interesting findings in the tracking phase,in terms of ROUGE L precision,recall and F1-Score for similarity techniques.

关键词： Rumor detection rumor tracking similarity techniques COVID-19 social media analytics

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Phishing Websites Detection by Using Optimized Stacking Ensemble Model

引用

Computer Systems Science & Engineering 2022年第4期41卷 109-125页

作者： Zeyad Ghaleb al-Mekhlafi Badiea Abdulkarem mohammed mohammed al-sarem Faisal Saeed Tawfik al-Hadhrami Mohammad T.alshammari Abdulrahman alreshidi Talal Sarheed alshammari College of Computer Science and Engineering University of Ha'ilHa'il81481KSA College of Computer Sciences and Engineering Hodeidah UniversityHodeidah967Yemen College of Computer Science and Engineering Taibah UniversityAl-Madinah42353KSA Nottingham Trent University MansfieldNG185BHUnited Kingdom

Phishing attacks are security attacks that do not affect only individuals’or organizations’websites but may affect Internet of Things(IoT)devices and *** environment is an exposed environment for such *** may use thingbots software for the dispersal of hidden junk emails that are not noticed by *** and deep learning and other methods were used to design detection methods for these ***,there is still a need to enhance detection *** of an ensemble classiﬁcation method for phishing website(PW)detection is proposed in this study.A Genetic algo-rithm(GA)was used for the proposed method optimization by tuning several ensemble Machine Learning(ML)methods parameters,including Random Forest(RF),AdaBoost(AB),XGBoost(XGB),Bagging(BA),GradientBoost(GB),and LightGBM(LGBM).These were accomplished by ranking the optimized classi-ﬁers to pick out the best classiﬁers as a base for the proposed method.A PW data-set that is made up of 4898 PWs and 6157 legitimate websites(LWs)was used for this study's *** a result,detection accuracy was enhanced and reached 97.16 percent.

关键词： Phishing websites ensemble classiﬁers optimization methods genetic algorithm

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Intelligent Medical Diagnostic System for Hepatitis B

引用

Computers, Materials & Continua 2022年第12期73卷 6047-6068页

作者： Dalwinder Singh Deepak Prashar Jimmy Singla Arfat Ahmad Khan mohammed al-sarem Neesrin ali Kurdi Lovely Professional University Punjab144402India College of Computing Khon Kaen UniversityKhon Kaen40000Thailand College of Computer Science and Engineering Taibah UniversityMedina41477Saudi Arabia Information System Department Sheba Region UniversityMarib14400Yemen

The hepatitis B virus is the most deadly virus,which significantly affects the human *** termination of the hepatitis B virus is mandatory and can be done by taking precautions as well as a suitable cure in its introductory stage;otherwise,it will become a severe problem and make a human liver suffer from the most dangerous diseases,such as liver *** this paper,two medical diagnostic systems are developed for the diagnosis of this life-threatening *** methodologies used to develop thesemodels are fuzzy logic and the neuro-fuzzy *** diverse parameters that assist in the evaluation of performance are also determined by using the observed values from the proposed system for both *** classification accuracy of a multilayered fuzzy inference system is 94%.The accuracy with which the developed medical diagnostic system by using Adaptive Network based Fuzzy Interference System(ANFIS)classifies the result corresponding to the given input is 95.55%.The comparison of both developed models on the basis of their performance parameters has been *** is observed that the neuro-fuzzy technique-based diagnostic system has better accuracy in classifying the infected and non-infected patients as compared to the fuzzy diagnostic ***,the performance evaluation concluded that the outcome given by the developed medical diagnostic system by using ANFIS is accurate and correct as compared to the developed fuzzy inference system and also can be used in hospitals for the diagnosis of Hepatitis B *** other words,the adaptive neuro-fuzzy inference system has more capability to classify the provided inputs adequately than the fuzzy inference system.

关键词： Artificial intelligence fuzzy logic hepatitis B hybrid system medical diagnostic system neural network neuro-fuzzy technique

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

A Novel Explainable CNN Model for Screening COVID-19 on X-ray Images

引用

Computer Systems Science & Engineering 2023年第8期46卷 1789-1809页

作者： Hicham Moujahid Bouchaib Cherradi Oussama El Gannour Wamda Nagmeldin Abdelzahir Abdelmaboud mohammed al-sarem Lhoussain Bahatti Faisal Saeed mohammed Hadwan EEIS Laboratory ENSET of MohammediaHassan II University of CasablancaMohammedia28820Morocco STIE Team CRMEF Casablanca-SettatThe Provincial Section of El JadidaEl Jadida24000Morocco Department of Information Systems College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Department of Information Systems King Khalid UniversityMuhayel Aseer61913Saudi Arabia College of Computer Science and Engineering Taibah UniversityMedina42353Saudi Arabia Department of Computer Science University of Sheba RegionMarib14400Yemen DAAI Research Group Department of Computing and Data ScienceSchool of Computing and Digital TechnologyBirmingham City UniversityBirminghamB47XGUK Department of Information Technology College of ComputerQassim UniversityBuraydah 51452Saudi Arabia Department of Computer Science College of Applied SciencesTaiz UniversityTaiz6803Yemen

Due to the rapid propagation characteristic of the Coronavirus(COVID-19)disease,manual diagnostic methods cannot handle the large number of infected individuals to prevent the spread of ***,new automated diagnostic methods have been brought on board,particularly methods based on artificial intelligence using different medical data such as X-ray *** imaging,for example,produces several image types that can be processed and analyzed by machine and deep learning methods.X-ray imaging materials widely exist in most hospitals and health institutes since they are affordable compared to other imaging *** this paper,we propose a novel Convolutional Neural Network(CNN)model(COV2Net)that can detect COVID-19 virus by analyzing the X-ray images of suspected *** model is trained on a dataset containing thousands of X-ray images collected from different *** model was tested and evaluated on an independent *** order to approve the performance of the proposed model,three CNN models namely Mobile-Net,Residential Energy Services Network(Res-Net),and Visual Geometry Group 16(VGG-16)have been implemented using transfer learning *** experiment consists of a multi-label classification task based on X-ray images for normal patients,patients infected by COVID-19 virus and other patients infected with *** proposed model is empowered with Gradient-weighted Class Activation Mapping(Grad-CAM)and Grad-Cam++techniques for a visual explanation and methodology debugging *** finding results show that the proposed model COV2Net outperforms the state-of-the-art methods.

关键词： Artificial intelligence intelligent diagnostic systems decisionmaking COVID-19 convolutional neural network

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Measuring Reliability of A Web Portal Based on Testing Profile

引用

Computers, Materials & Continua 2023年第3期74卷 6641-6663页

作者： Malik Muhammad ali Shahid Shahida Sulaiman mohammed al-sarem Aqeel Ur Rahman Salman Iqbal Rab Nawaz Bashir Arfat Ahmad Khan Momen M.alrawi Rashiq R.Marie Settawit Poochaya COMSATS University Islamabad Vehari Vehari61100Pakistan Universiti Teknologi Malaysia Johor Bahru81310Malaysia College of Computer Science and Engineering Taibah UniversityMedina41477Saudi Arabia Information System Department Sheba Region UniversityMarib14400Yemen Suranaree University of Technology Nakhon Ratchasima30000Thailand Khon Kaen University Khon Kaen40000Thailand Umm al-Qura University Mecca24382Saudi Arabia Taibah University Medina42353Saudi Arabia

Conventionally,the reliability of a web portal is validated with generalized conventional methods,but they fail to provide the desired ***,we need to include other quality factors that affect reliability such as usability for improving the reliability in addition to the conventional reliability ***,the primary objectives of web portals are to provide interactive integration of multiple functions confirming diverse requirements in an efficient *** this paper,we employ testing profiles tomeasure the reliability through software operational profile,input space profile and usability profile along with qualitative measures of reliability and ***,the case study used for verification is based on aweb application that facilitates information and knowledge sharing among its online *** proposed scheme is compared with the conventional reliability improvement method in terms of failure detection and *** final results unveil that the computation of reliability by using the traditional method(utilizing failure points with the assistance of Mean Time Between Failures(MTBF)and Mean Time To Failure(MTTF)becomes ineffective under certain *** such situations,the proposed scheme helps to compute the reliability in an effective ***,the outcomes of the study provide insight recommendations about the testing and measurement of reliability for Web based software or applications.

关键词： Software usability software reliability web portals software testing software testing profile

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Enhancing Parkinson’s Disease Prediction Using Machine Learning and Feature Selection Methods

引用

Computers, Materials & Continua 2022年第6期71卷 5639-5657页

作者： Faisal Saeed Mohammad al-sarem Muhannad al-Mohaimeed Abdelhamid Emara Wadii Boulila mohammed alasli Fahad Ghabban College of Computer Science and Engineering Taibah UniversityMedina41477Saudi Arabia School of Computing and Digital Technology Birmingham City UniversityBirminghamB47XGUnited Kingdom Information System Department Saba’a Region UniversityMareebYemen Computers and Systems Engineering Department Al-Azhar UniversityCairo11884Egypt RIADI Laboratory National School of Computer SciencesUniversity of ManoubaManouba2010Tunisia

Several millions of people suffer from Parkinson’s disease ***’s affects about 1%of people over 60 and its symptoms increase with *** voice may be affected and patients experience abnormalities in speech that might not be noticed by listeners,but which could be analyzed using recorded speech *** the huge advancements of technology,the medical data has increased dramatically,and therefore,there is a need to apply data mining and machine learning methods to extract new knowledge from this *** classification methods were used to analyze medical data sets and diagnostic problems,such as Parkinson’s Disease(PD).In addition,to improve the performance of classification,feature selection methods have been extensively used in many *** paper aims to propose a comprehensive approach to enhance the prediction of PD using several machine learning methods with different feature selection methods such as filter-based and *** dataset includes 240 recodes with 46 acoustic features extracted from3 voice recording replications for 80 *** experimental results showed improvements when wrapper-based features selection method was used with K-NN classifier with accuracy of 88.33%.The best obtained results were compared with other studies and it was found that this study provides comparable and superior results.

关键词： Filter-based feature selection methods machine learning parkinson’s disease wrapper-based feature selection methods

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：