检索结果-南通市图书馆

Malware Detection Using Decision Tree Based SVM Classifier for IoT

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2022年第7期72卷 713-726页

作者： Anwer mustafa Hilal Siwar Ben Haj Hassine Souad Larabi-Marie-Sainte Nadhem Nemri Mohamed K.Nour Abdelwahed Motwakel Abu Sarwar Zamani Mesfer Al Duhayyim Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Computer Science College of Science and ArtsKing Khalid UniversityMahayil AsirSaudi Arabia Department of Computer Science College of Computer and Information SciencesPrince Sultan UniversitySaudi Arabia Department of Computer Science College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia

The development in Information and Communication Technology has led to the evolution of new computing and communication *** revolution with Internet of Things(IoTs)has developed various applications in almost all domains from health care,education to entertainment with sensors and smart *** of the subsets of IoT is Internet of Medical things(IoMT)which connects medical devices,hardware and software applications through *** enables secure wireless communication over the Internet to allow efficient analysis of medical *** these smart advancements and exploitation of smart IoT devices in health care technology there increases threat and malware attacks during transmission of highly confidential medical *** work proposes a scheme by integrating machine learning approach and block chain technology to detect malware during data transmission in *** proposed Machine Learning based Block Chain Technology malware detection scheme(MLBCT-Mdetect)is implemented in three steps namely:feature extraction,Classification and *** extraction is performed by calculating the weight of each feature and reduces the features with less *** Vector Machine classifier is employed in the second step to classify the malware and benign ***,third step uses blockchain to store details of the selected features which eventually improves the detection of malware with significant improvement in speed and ***-BCT-Mdetect achieves higher accuracy with low false positive rate and higher True positive rate.

关键词： Blockchain malware detection classification feature selection internet of medical things

Modeling of Artificial Intelligence Based Traffic Flow Prediction with Weather Conditions

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2022年第5期71卷 3953-3968页

作者： Mesfer Al Duhayyim Amani Abdulrahman Albraikan Fahd N.Al-Wesabi Hiba M.Burbur Mohammad Alamgeer Anwer mustafa Hilal Manar Ahmed Hamza Mohammed Rizwanullah Department of Natural and Applied Sciences College of Community-AflajPrince Sattam Bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11564Saudi Arabia Department of Computer Science College of Science&Arts at MahayilKing Khalid UniversityMuhayel Aseer62529Saudi Arabia Faculty of Computer and IT Sana’a UniversitySana’a61101Yemen Department of Computer Science College of Science and Arts in Al-BukairiyahQassim UniversityAl-Bukairiyah52571Saudi Arabia Department of Information Systems College of Science&Arts at MahayilKing Khalid UniversityMuhayel Aseer62529Saudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam Bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia

Short-term traffic flow prediction (TFP) is an important area inintelligent transportation system (ITS), which is used to reduce traffic congestion. But the avail of traffic flow data with temporal features and periodicfeatures are susceptible to weather conditions, making TFP a challengingissue. TFP process are significantly influenced by several factors like accidentand weather. Particularly, the inclement weather conditions may have anextreme impact on travel time and traffic flow. Since most of the existing TFPtechniques do not consider the impact of weather conditions on the TF, it isneeded to develop effective TFP with the consideration of extreme weatherconditions. In this view, this paper designs an artificial intelligence based TFPwith weather conditions (AITFP-WC) for smart cities. The goal of the AITFPWC model is to enhance the performance of the TFP model with the inclusionof weather related conditions. The proposed AITFP-WC technique includesElman neural network (ENN) model to predict the flow of traffic in smartcities. Besides, tunicate swarm algorithm with feed forward neural networks(TSA-FFNN) model is employed for the weather and periodicity analysis. Atlast, a fusion of TFP and WPA processes takes place using the FFNN modelto determine the final prediction output. In order to assess the enhancedpredictive outcome of the AITFP-WC model, an extensive simulation analysisis carried out. The experimental values highlighted the enhanced performanceof the AITFP-WC technique over the recent state of art methods.

关键词： Smart cities artificial intelligence urban transportation deep learning weather condition TFP

Analysis and Assessment of Wind Energy Potential of Almukalla in Yemen

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2022年第8期72卷 3113-3129页

作者： Murad A.A.Almekhlafi Fahd N.Al-Wesabi Majdy M.Eltahir Anwer mustafa Hilal Amin M.El-Kustaban Abdelwahed Motwakel Ishfaq Yaseen Manar Ahmed Hamza Department of Electrical Engineering–Communication Engineering Sana’a UniversityYemen Department of Computer Science King Khalid UniversityMuhayelAseerSaudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen Department of Information Systems King Khalid UniversityMuhayelAseerSaudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Electronic Department Faculty of EngineeringUniversity of Science and TechnologySana’aYemen

Energy is an essential element for any civilized country’s social and economic development,but the use of fossil fuels and nonrenewable energy forms has many negative impacts on the environment and the *** Republic of Yemen has very good potential to use renewable ***,we find few studies on renewable wind energy in *** the lack of a similar analysis for the coastal city,this research newly investigates wind energy’s potential near the Almukalla area by analyzing wind ***,evaluation,model identification,determination of available energy density,computing the capacity factors for several wind turbines and calculation of wind energy were extracted at three heights of 15,30,and *** wind speeds were obtained only for the currently available data of five recent years,2005–*** study involves a preliminary assessment of Almukalla’s wind energy potential to provide a primary base and useful insights for wind engineers and *** research aims to provide useful assessment of the potential of wind energy in Almukalla for developing wind energy and an efficient wind *** Weibull distribution shows a perfect approximation for estimating the intensity of Yemen’s wind *** on both theWeibullmodel and the results of the annual wind speed data analysis for the study site in Mukalla,the capacity factor for many turbines was also calculated,and the best suitable turbine was *** to the International Wind Energy Rating criteria,Almukalla falls under Category 7,which is,rated“Superb”most of the year.

关键词： Almukalla energy potential Rayleigh distribution Weibull distribution wind power density wind speed

Intelligent Deer Hunting Optimization Based Grid Scheduling Scheme

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2022年第7期72卷 181-195页

作者： Mesfer Al Duhayyim Majdy M.Eltahir Imène Issaoui Fahd N.Al-Wesabi Anwer mustafa Hilal Fuad Ali Mohammed Al-Yarimi Manar Ahmed Hamza Abu Sarwar Zamani Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversityMuhayel Aseer62529Saudi Arabia Department of Natural and Applied Sciences Community CollegeQassim UniversityAl-Bukairiyah52571Saudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia

The grid environment is a dynamic,heterogeneous,and changeable computing system that distributes various services amongst different *** attain the benefits of collaborative resource sharing in Grid computing,a novel and proficient grid resource management system(RMS)is ***,detection of an appropriate resource for the presented task is a difficult *** scientists have presented algorithms for mapping tasks to the *** of them focus on fault tolerance,user fulfillment,and load *** this motivation,this study designs an intelligent grid scheduling scheme using deer hunting optimization algorithm(DHOA),called IGSS-DHOA which schedules in such a way that the makespan gets minimized in the grid *** IGSS-DHOA technique is mainly based on the hunting nature of humans toward *** also derives an objective function with candidate solution(schedule)as input and the outcome is the makespan value denoting the quality of the candidate *** simulation results highlighted the supremacy of the IGSS-DHOA technique over the recent state of art techniques with the minimal average processing cost of 31717.9.

关键词： Grid services grid scheduling resources makespan np hard problem metaheuristics

Optimal Bidirectional LSTM for Modulation Signal Classification in Communication Systems

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2022年第8期72卷 3055-3071页

作者： Manar Ahmed Hamza Siwar Ben Haj Hassine Souad Larabi-Marie-Sainte Mohamed K.Nour Fahd N.Al-Wesabi Abdelwahed Motwakel Anwer mustafa Hilal Mesfer Al Duhayyim Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Computer Science College of Science and ArtsKing Khalid UniversityMahayil AsirSaudi Arabia Department of Computer Science College of Computer and Information SciencesPrince Sultan UniversitySaudi Arabia Department of Computer Science College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia

Modulation signal classification in communication systems can be considered a pattern recognition *** works have focused on several feature extraction approaches such as fractal feature,signal constellation reconstruction,*** recent advent of deep learning(DL)models makes it possible to proficiently classify the modulation *** this view,this study designs a chaotic oppositional satin bowerbird optimization(COSBO)with bidirectional long term memory(BiLSTM)model for modulation signal classification in communication *** proposed COSBO-BiLSTM technique aims to classify the different kinds of digitally modulated *** addition,the fractal feature extraction process takes place by the use of Sevcik Fractal Dimension(SFD)***,the modulation signal classification process takes place using BiLSTM with fully convolutional network(BiLSTM-FCN).Furthermore,the optimal hyperparameter adjustment of the BiLSTM-FCN technique takes place by the use of COSBO *** order to ensure the enhanced classification performance of the COSBO-BiLSTM model,a wide range of simulations were carried *** experimental results highlighted that the COSBO-BiLSTM technique has accomplished improved performance over the existing techniques.

关键词： Complex systems communication system signal processing modulation signals classification artificial intelligence deep learning parameter tuning

Clinicopathological Study on the Effects of <i>Momordica charantia</i>on Streptozotocin-Induced Diabetic Wistar Rats

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Open Journal of Veterinary Medicine 2017年第5期7卷 49-62页

作者： Mohammed Salem Moqbel Fahad Abdullah Al-Hizab Seif mustafa Barakat Department of Pathology College of Veterinary Medicine King Faisal University Al-Hassa KSA

Momordica charantia (MC) a traditional medicine used for the treatment of many disorders was fed to streptozotocin (STZ)-induced diabetic male Wistar rats at 2, 5 and 10% of the standard diet. Rats were then observed for 12 weeks before sacrificed. Immediately, tissues from liver, kidney and pancreas were taken for histopathological examination. Serum samples were analyzed to evaluate liver, kidney and pancreatic functions. In addition, blood samples were collected to analyze hematology parameters. The results of the present study indicate that oral doses of MC at 5% and 10% of the daily diet resulted in alleviation of the pancreatic, hepatic and renal dysfunction induced by diabetes. The improved pancreatic, hepatic and renal functions were judged by histopathological, hematological and serobiochemical parameters. In conclusion, the MC fruits may be used as an antidiabetic herbal medicine.

关键词： Momordica charantia Antidiabetic Hematology Serobiochemistry Histopathology

Association between Pentraxin-3 and Cardiac Troponin-I with Left Ventricular Systolic Function in Patients with Anterior ST-Segment Elevation Myocardial Infarction: Evaluation by Speckle Tracking Echocardiography

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

World Journal of Cardiovascular Diseases 2019年第2期9卷 57-68页

作者： Mousa Alharbi Mohamed Yahia mustafa Rashed Omar S. El-Masry Department of Internal Medicine College of Medicine Imam Abdulrahman Bin Faisal University Dammam KSA Department of Cardiology College of Medicine University of Menoufia Shebin-Alkoum Egypt Department of Cardiac Technology College of Applied Medical Sciences Imam Abdulrahman Bin Faisal University Dammam KSA Department of Clinical Laboratory Sciences College of Applied Medical Sciences Imam Abdulrahman Bin Faisal University Dammam KSA

Background: Pentraxin 3 is an inflammatory biomarker whose serum level is increased during acute myocardial infarction (AMI). The aim of this study was to measure the serum pentraxin-3 level in anterior ST-segment elevation myocardial infarction (STEMI), to investigate correlation with the left ventricular (LV) systolic function assessed by speckle tracking echocardiography, and compare with the well-established cardiac biomarkers of myocardial injury such as troponin-I. Methods: Serum pentraxin-3 level was measured by ELISA in 50 patients with anterior STEMI. LV strain was measured by speckle tracking echocardiography. The results were compared to twenty sex- and age-matched persons who had history of stable angina and normal LV ejection fraction (LVEF). Results: Serum level of pentraxin-3 was significantly higher in STEMI patients in comparison to the control group (8.3 ± 3.1 versus 3.4 ± 1.2 ng/ml, p 0.001). Average LV global longitudinal strain (GLS) was reduced in STEMI patients in comparison to control subjects (11.2 ± 2.4 versus 20.2 ± 2.1, p 0.001). In addition, there was a significant negative correlation between serum pentraxin-3 level and LVEF (r = -0.557, p 0.001) and the average LVGLS (r =-0.529, p 0.001). Serum pentraxin-3 cutoff value > 8.3 ng/ml had sensitivity of 81.8% and specificity of 86.4% to detect LVEF less than 50% (p 0.001). While, peak cardiac troponin-I level > 34 ng/ml was 86% sensitive to detect LVEF less than 50% with specificity of 90.9%. Conclusions: The elevated serum level of pentraxin-3 and cardiac troponin-I in STEMI patients and their association with both LVEF and GLS support the concept that the magnitude of these biomarkers correlates to the severity of myocardium injury.

关键词： Anterior MI Pentraxin-3 Speckle Tracking Echocardiography

The Relationship between Financial Reporting System and Project Success: A Case of Construction Projects in UAE

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Modern Accounting and Auditing 2020年第8期16卷 360-375页

作者： Shatha mustafa Hussain faisal Khan Muhamad M.S.Jumaa Sharif Ullah Jan City University College of Ajman AjmanUnited Arab Emirates(UAE) Federally Administered Tribal Areas(FATA)University Darra Adam KhelPakistan

The purpose of this paper is to deliver a better perception of the project success,and how reporting system might increase the probability of project success in construction projects in ***,it aims at exploring the relationship between effective reporting system in terms of the characteristic of its outputs(mainly effectiveness of financial reporting system)and project ***-structured interviews with a number of interior auditors,accountants,and chief financial officers(CFOs)from different corporations in construction sector in UAE in order to recognize how effective reporting system in terms of the characteristic of its outputs(broad scope,timeliness,aggregation,and integration)might contribute to increase the probability of project *** are several success factors in construction projects in UAE,thus it is very hard to capture all these factors in one ***,this paper is not considering all project success factors rather it focuses on the characteristic of outputs of the reporting system generally and the financial reporting system particularly(broad scope,timeliness,aggregation,and integration),as most of the studies in the literature considered the reporting system as a key factor of project *** paper adds to both project management and accounting research by evidencing results from an exploration how effective reporting might impact the project success,with valuable implications for standard officials,customers,investors,stakeholders,sponsors,shareholders,CFOs,project developer,consultants,internal auditors,and accounting *** effective reporting system in United Arab Emirates(UAE)construction projects enables possessors,customers,and contractors of projects to get timely information about the progress of project in a brief and significant format which in turn improve the decision-making process and contribute to project *** paper implies a contribution for both project management literature and accounti

关键词： effective reporting system construction projects in UAE project success qualitative study

Improved Whale Optimization with Local-Search Method for Feature Selection

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2023年第4期75卷 1371-1389页

作者： Malek Alzaqebah Mutasem KAlsmadi Sana Jawarneh Jehad Saad Alqurni Mohammed Tayfour Ibrahim Almarashdeh Rami mustafa A.Mohammad Fahad A.Alghamdi Nahier Aldhafferi Abdullah Alqahtani Khalid A.Alissa Bashar A.Aldeeb Usama A.Badawi Maram Alwohaibi Hayat Alfagham Department of Mathematics College of ScienceImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Basic&Applied Scientific Research Center Imam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Department of MIS College of Applied Studies and Community ServiceImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Department of Computer Science Community CollegeImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Department of Educational Technology College of EducationImam Abdulrahman Bin Faisal UniversityP.O.Box 1982DammamSaudi Arabia Department of Computer Information Systems College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Department of Computer Science College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Deanship of Information and Communication Technology Imam Abdulrahman bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia

Various feature selection algorithms are usually employed to improve classification models’overall *** algorithms typically accompany such algorithms to select the optimal set of *** the most currently attractive trends within optimization algorithms are hybrid *** present paper presents two Stages of Local Search models for feature selection based on WOA(Whale Optimization Algorithm)and Great Deluge(GD).GD Algorithm is integrated with the WOA algorithm to improve exploitation by identifying the most promising regions during the *** version is employed using the best solution found by the WOA algorithm and exploited by the GD *** addition,disruptive selection(DS)is employed to select the solutions from the population for local *** is chosen to maintain the diversity of the population via enhancing low and high-quality ***(15)standard benchmark datasets provided by the University of California Irvine(UCI)repository were used in evaluating the proposed approaches’***,a comparison was made with four population-based algorithms as wrapper feature selection methods from the *** proposed techniques have proved their efficiency in enhancing classification accuracy compared to other wrapper ***,the WOA can search effectively in the feature space and choose the most relevant attributes for classification tasks.

关键词： Optimization whale optimization algorithm great deluge algorithm feature selection and classification