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Smartphones and traffic signals:A quantitative assessment for phone usage behavior on performance of signalized intersections

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Journal of Traffic and Transportation Engineering(English Edition) 2023年第4期10卷 611-632页

作者： Wael ElDessouki abdulrahman alManeea Department of Transportation and Traffic Engineering Imam Abdulrahman Bin Faisal UniversityDammam 31441Kingdom of Saudi Arabia

Modern smartphones differ vastly from classic cellphones with enormous capabilities,changing cellphones from making phone calls and short messages to pocket-sized computers with full internet *** downside of modern phone evolution is changing drivers’behavior and phone usage *** researchers have investigated the safety implications of phone usage while driving on accidents ***,the effect of phone usage on the performance of traffic facilities did not receive equal ***,this research aims to study the impact of smartphone usage on traffic signal *** parameters considered in the study were drivers’activity while waiting at the signal,startup lost time,and saturation flow *** study team covered 25 intersections in the study area,observed the activities of over 6800 drivers while waiting at the signal,and recorded their corresponding discharge *** study team then supplemented field data with a behavioral survey questionnaire for drivers living in the study area to interpret field ***,the collected data were processed and analyzed,resulting in mathematical models for the relationship between the reduction in saturation flow rate and the red time *** team found two primary *** study’s first finding was that the traditional concept for estimating startup lost time adopted by the highway capacity manual(HCM)appears *** field results revealed that the lost times caused by other distracted drivers upstream in the queue were comparable to the estimated startup lost time following the HCM method for estimating startup lost *** second finding was that the reduction in saturation flow rate at the traffic signal is an exponential function of the red time interval,reducing the overall capacity for the intersection and increasing the average ***,the authors suggest mitigating the problem and making recommendations for future research.

关键词： Signals Smartphone Saturation Flow Discharge Headway

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Liver transplantation for hepatitis B virus: Decreasing indication and changing trends

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World Journal of Gastroenterology 2015年第26期21卷 8140-8147页

作者： Waleed al-hamoudi Hussien Elsiesy abdulrahman Bendahmash Nasser al-masri Safiyya ali Naglaa allam Mohammed al Sofayan Hamad al Bahili Mohammed al Sebayel Dieter Broering Sammy Saab Faisal Abaalkhail Gastroenterology Unit Department of MedicineCollege of MedicineKing Saud University Department of Liver Transplantation and Hepatobiliary Surgery King Faisal Specialist Hospital and Research Center National Liver Institute Menoufeya University David Geffen School of Medicine UCLA

AIM: To evaluate the indication and outcome of hepatitis B virus(HBV)-related liver transplantation(LT) in the era of newer antiviral ***: We collected data on all patients who underwent transplantation at King Faisal Specialist Hospital and Research *** data included demographic,perioperative and long-term postoperative follow-up data including viral serological markers,HBV DNA,and repeated liver *** January 1990 and January 2012,133 patients(106 males and 27 females) underwent LT for HBV-related cirrhosis at our *** patients were followed up frequently during the first year following transplantation,according to our standard protocol; follow-up visits occurred every 3-6 mo *** infection was definedas re-emergence of HBV-DNA or hepatitis B surface antigen(HBs Ag) while on *** patients transplanted prior to 1992 did not receive immediate posttransplant anti-HBV prophylaxis; all other patients were treated with HBIG and at least one nucleos(t)ide ***: One hundred and thirty-three patients underwent LT for HBV and were followed for a median of 82 mo(range: 1-274).The rates of post-LT survival and HBV recurrence during the follow-up period were 89% and 11%,*** following factors were associated with disease recurrence: younger age(44.3 ± 16.2 years vs 51.4 ± 9.9 years,P = 0.02),positive pretransplant hepatitis B e antigen(HBe Ag)(60% vs 14%,P al of 64 transplants were performed,including 46(72%) for decompensated HBV cirrhosis,12(19%) for decompensated cirrhosis complicated by HCC and 6(10%) for compensated cirrhosis complicated by ***

关键词： Hepatitis B Hepatitis C Non-alcoholicsteatohepatitis Liver transplantation Hepatocellularcarcinoma

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Artificial Intelligence Based Solar Radiation Predictive Model Using Weather Forecasts

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Computers, Materials & Continua 2022年第4期71卷 109-124页

作者： Sathish Babu Pandu A.Sagai Francis Britto Pudi Sekhar P.Vijayarajan Amani abdulrahman albraikan Fahd N.al-Wesabi Mesfer al Duhayyim Department of Electrical and Electronics Engineering University College of EngineeringPanruti607106India Department of Mechanical Engineering Rohini College of Engineering&TechnologyPalkulam629401India Department of Electrical and Electronics Engineering Vignan’s Institute of Information TechnologyAndra Pradesh530046India Department of Electrical and Electronics Engineering University College of EngineeringBIT CampusTiruchirappalli620024India Department of Computer Science College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversitySaudi Arabia Department of Computer Science King Khalid UniversityMuhayel AseerSaudi Arabia&Faculty of Computer and ITSana’a UniversitySana’aYemen Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia

Solar energy has gained attention in the past two decades,since it is an effective renewable energy source that causes no harm to the *** Irradiation Prediction(SIP)is essential to plan,schedule,and manage photovoltaic power plants and grid-based power generation *** models have been proposed for SIP in the literature while such studies demand huge volumes of weather data about the target location for a lengthy period of *** this scenario,commonly available Artificial Intelligence(AI)technique can be trained over past values of irradiance as well as weatherrelated parameters such as temperature,humidity,wind speed,pressure,and ***,in current study,the authors aimed at developing a solar irradiance prediction model by integrating big data analytics with AI models(BDAAI-SIP)using weather forecasting *** order to perform long-term collection of weather data,Hadoop MapReduce tool is *** proposed solar irradiance prediction model operates on different ***,data preprocessing take place using various sub processes such as data conversion,missing value replacement,and data ***,Elman Neural Network(ENN),a type of feedforward neural network is also applied for predictive *** is divided into input layer,hidden layer,loadbearing layer,and output *** overcome the insufficiency of ENN in choosing the value of weights and hidden layer neuron count,Mayfly Optimization(MFO)algorithm is *** order to validate the performance of the proposed model,a series of experiments was *** experimental values infer that the proposed model outperformed other methods used for comparison.

关键词： Solar irradiation prediction weather forecast artificial intelligence Elman neural network mayfly optimization

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Sudden death in the southern region of Saudi Arabia:A retrospective study

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World Journal of Clinical Cases 2023年第20期11卷 4843-4851页

作者： Ahmed Mohamed Ahmed al-Emam abdulrahman Dajam Mohammed alrajhi Waleed alfaifi Mubarak al-Shraim Ahmed Mohamed Helaly Department of Pathology College of MedicineKing Khalid UniversityAsir 61421Saudi Arabia Forensic Medicine and Clinical Toxicology Mansoura UniversityMansoura 35516Egypt Medical School King Khalid UniversityAsir 61421Saudi Arabia Clinical Science Faculty of MedicineYarmouk UniversityIrbid 21163Jordan

BACKGROUND Sudden death is unanticipated,non-violent death taking place within the first 24 h after the onset of *** is a major public health problem ***,the effects of living at moderate altitude on mortality are poorly *** To retrospectively report the frequency and the main causes of sudden deaths in relation to total deaths at Asir Central Hospital,2255 m above sea level,in the southern region of Saudi Arabia over a period of 4 years from 2013 to *** The medical records of 1821 deaths were examined and showed 353 cases(19.4%)of sudden *** The highest incidence of sudden death was among the elderly(51%),whereas,the lowest was among children and adolescents(6.5%).With regard to gender,the incidence of sudden death was higher in males(54.4%)compared to 45.6% in *** this study,we found that the most common direct causes of sudden death were cardiovascular diseases(29.2%),respiratory disease(22.7%),infectious disease(12.2%),cancer(9.4%)and hematological diseases(6.2%).With respect to seasonal variation,the highest incidence was during winter(31.32%)followed by summer(25.8%).CONCLUSION The results of this study will help emergency physicians and health care providers to exercise due care to reduce the incidence of sudden death and raise public awareness about the impact of sudden death.

关键词： Sudden death High altitude Cardiovascular Gender distribution Age Seasonal variation

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The SARS-CoV-2 pandemic course in Saudi Arabia:A dynamic epidemiological model

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Infectious Disease Modelling 2020年第1期5卷 766-771页

作者： Abdullah Murhaf al-Khani Mohamed Abdelghafour Khalifa abdulrahman almazrou Nazmus Saquib College of Medicine Sulaiman Al Rajhi UniversityP.O.Box 777BukairyahAl-Qassim51941Saudi Arabia

Objective:Saudi Arabia ranks second in the number of coronavirus disease 2019(COVID-19)cases in the Eastern Mediterranean *** houses the two most sacred religious places for Muslims:Mecca and *** is important to know what the trend in case numbers will be in the next 4e6 months,especially during the Hajj pilgrimage ***:Epidemiological data on COVID-19 were obtained from the Saudi Arabian Ministry of Health.A susceptible-exposed-infectious-recovered(SEIR)prediction model was constructed to predict the trend in COVID-19 in Saudi Arabia in the next 6 ***:The model predicts that the number of active cases will peak by 22 May *** cumulative infected cases are predicted to reach 70,321 at that *** total number of infected individuals is estimated reach to 114,580 by the end of the ***:Our estimates show that by the time the Hajj season commences in Saudi Arabia,the pandemic will be in the midst of its deceleration phase(phase 3).This information will likely be useful to policymakers in their management of the outbreak.

关键词： Epidemiology Infectious disease Outbreaks Surveillance Modelling

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Therapeutic benefits of zinc sulfate on neonatal hyperbilirubinemia

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World Journal of Pediatrics 2022年第4期18卷 300-304页

作者： abdulrahman al-Matary Abdullah alGhamdi Bandar alenaze Rasha Abdulaziz Mandili Dhuha Abdulaziz alhawsawi Duha Magzoub Ahmed Abu-Zaid Department of Neonatology King Fahad Medical CityRiyadhSaudi Arabia Department of Pediatrics King Abdullah Specialized Children HospitalKing Abdulaziz Medical CityMinistry of National GuardHealth AffairsRiyadhSaudi Arabia King Abdullah International Research Medical Research Center RiyadhSaudi Arabia King Saud Bin Abdulaziz University for Health Sciences RiyadhSaudi Arabia College of Medicine Umm Al-Qura UniversityMeccaSaudi Arabia School of Public Health University of MemphisMemphisTNUSA Department of Pharmacology College of Graduate Health SciencesUniversity of Tennessee Health Science CenterMemphisTN 38163USA College of Medicine Alfaisal UniversityRiyadhSaudi Arabia

Neonatal hyperbilirubinemia is a common phenomenon shortly after birth and a frequent cause of prolonged hospitalization[1].Increased enterohepatic circulation of indirect bilirubin is one of the elucidated mechanisms implicated in the pathophysiology of neonatal hyperbilirubinemia[2,3].According to various in vitro and in vivo evidence from animal[3]and human[2]trials,zinc salts have been depicted to reduce bilirubin levels.

关键词： neonatal hepatic Therapeutic

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Global research production pertaining to gastrointestinal involvement in COVID-19:A bibliometric and visualised study

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World Journal of Gastrointestinal Surgery 2022年第5期14卷 494-505页

作者： Sa'ed H Zyoud Samah W al-Jabi Moyad Jamal Shahwan Ammar abdulrahman Jairoun Department of Clinical and Community Pharmacy College of Medicine and Health SciencesAn-Najah National UniversityNablus 44839Palestine Poison Control and Drug Information Center College of Medicine and Health SciencesAn-Najah National UniversityNablus 44839Palestine Clinical Research Centre An-Najah National University HospitalNablus 44839Palestine Department of Clinical Sciences College of Pharmacy and Health SciencesAjman UniversityAjman 346United Arab Emirates Centre of Medical and Bio-allied Health Sciences Research Ajman UniversityAjman 346United Arab Emirates Department of Health and Safety Dubai MunicipalityDubai 67United Arab Emirates

BACKGROUND Coronavirus disease 2019(COVID-19)is a global pandemic that can cause diarrhoea,nausea/vomiting,and abdominal pain,among other gastrointestinal(GI)*** To perform a bibliometric analysis of the global research production pertaining to GI involvement in *** The Scopus database was used to search the global literature on GI involvement in COVID-19 during 2020.A bibliometric review of these publications was also performed using *** Scopus had published 95615 documents on COVID-19 in all areas of research at the time of data *** total,1267 publications on the topic of GI and COVID-19 were *** articles(n=606;47.83%),letters(293;23.13%),and reviews(186;14.68%)were the most popular types of *** most productive countries and institutions in this field were the United States and Huazhong University of Science and *** most cited paper was Xiao et al,which was published in Gastroenterology as a brief communication,with 798 *** paper provides evidence for GI infection of COVID-19 and its possible faecal–oral transmission *** the term cluster analysis,there were two frontiers in this field:GI manifestations among COVID-19 patients and the implications of COVID-19 for the *** GI manifestations among COVID-19 patients and implications of COVID-19 for gastroenterologists were of interest,especially in the early stages of the pandemic.

关键词： COVID-19 Gastrointestinal Symptoms Bibliometric Scopus

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Modeling of Artificial Intelligence Based Traffic Flow Prediction with Weather Conditions

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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

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Automated Disassembly Sequence Prediction for Industry 4.0 Using Enhanced Genetic algorithm

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Computers, Materials & Continua 2021年第11期69卷 2531-2548页

作者： Anil Kumar Gulivindala M.V.A.Raju Bahubalendruni R.Chandrasekar Ejaz Ahmed Mustufa Haider Abidi abdulrahman al-Ahmari Department of Mechanical Engineering Industrial Robotics and Manufacturing Automation LaboratoryNational Institute of TechnologyKariakal609609India Department of Computer Science Engineering National Institute of TechnologyKariakal609609India Raytheon Chair for Systems Engineering Advanced Manufacturing InstituteKing Saud UniversityRiyadh11421Saudi Arabia Industrial Engineering Department College of EngineeringKing Saud UniversityRiyadh11421Saudi Arabia

The evolution of Industry 4.0 made it essential to adopt the Internet of Things(IoT)and Cloud Computing(CC)technologies to perform activities in the new age of *** technologies enable collecting,storing,and retrieving essential information from the manufacturing *** collected at sites are shared with others where execution automatedly *** obtained information must be validated at manufacturing to avoid undesirable data losses during the de-manufacturing ***,information sharing from the assembly level at the manufacturing stage to disassembly at the product end-of-life state is a major *** current research validates the information optimally to offer a minimum set of activities to complete the disassembly *** optimal disassembly sequence plan(DSP)can possess valid information to organize the necessary actions in ***,finding an optimal DSP is complex because of its combinatorial *** genetic algorithm(GA)is a widely preferred artificial intelligence(AI)algorithm to obtain a near-optimal solution for the DSP *** converging nature at local optima is a limitation in the traditional *** study improvised the GA workability by integrating with the proposed priori crossover *** optimality function is defined to reduce disassembly effort by considering directional changes as *** enhanced GA method is tested on a real-time product to evaluate the *** obtained results reveal that diversity control depends on the operators employed in the disassembly *** proposed method’s solution can be stored in the cloud and shared through IoT devices for effective resource allocation and disassembly for maximum recovery of the *** effectiveness of the proposed enhanced GA method is determined by making a comparative assessment with traditional GA and other AI methods at different population sizes.

关键词： Automation internet of things disassembly sequence planning priori cross over operator enhanced GA disassembly predicates

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Design of Machine Learning Based Smart Irrigation System for Precision Agriculture

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Computers, Materials & Continua 2022年第7期72卷 109-124页

作者： Khalil Ibrahim Mohammad Abuzanouneh Fahd N.al-Wesabi Amani abdulrahman albraikan Mesfer al Duhayyim M.al-Shabi Anwer Mustafa Hilal Manar Ahmed Hamza Abu Sarwar Zamani K.Muthulakshmi Department of Information Technology College of ComputerQassim UniversityAl-Bukairiyah52571Saudi Arabia Department of Computer Science King Khalid UniversityMuhayel Aseer62529Saudi Arabia&Faculty of Computer and ITSana’a UniversitySana’a61101Yemen Department of Computer Science College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11564Saudi Arabia Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Department of Management Information System College of Business and AdministrativeTaibah UniversityMedina42353Saudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Department of Electronics and Communication Engineering Dr.N.G.P Institute of TechnologyCoimbatore641048India

Agriculture 4.0,as the future of farming technology,comprises numerous key enabling technologies towards sustainable *** use of state-of-the-art technologies,such as the Internet of Things,transform traditional cultivation practices,like irrigation,to modern solutions of precision *** achieve effectivewater resource usage and automated irrigation in precision agriculture,recent technologies like machine learning(ML)can be *** this motivation,this paper design an IoT andML enabled smart irrigation system(IoTML-SIS)for precision *** proposed IoTML-SIS technique allows to sense the parameters of the farmland and make appropriate decisions for *** proposed IoTML-SIS model involves different IoT based sensors for soil moisture,humidity,temperature sensor,and ***,the sensed data are transmitted to the cloud server for processing and decision ***,artificial algae algorithm(AAA)with least squares-support vector machine(LS-SVM)model is employed for the classification process to determine the need for ***,the AAA is applied to optimally tune the parameters involved in the LS-SVM model,and thereby the classification efficiency is significantly *** performance validation of the proposed IoTML-SIS technique ensured better performance over the compared methods with the maximum accuracy of 0.975.

关键词： Automatic irrigation precision agriculture smart farming machine learning cloud computing decision making internet of things

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