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Epidemiology and Clinical Ch.racteristics of th. First 500 Positive Cases of COVID-19. A Multicenter Retrospective Study across th. Najran Region of th. Kingdom of Saudi Arabia (KSA)

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Open Journal of Epidemiology 2021年第3期11卷 222-236页

作者： h.di J. Al Sulayyim Moh.mmed Ch.Al-Noaemi Moh.mmed M. alyami Sh.ab Ah.ad mohammad h. alyami h.mad S. alyami Ali D. Al-Swedan Ibrah.em S. Banih.meem Musallam A. Sedran Ali M. Al-Zubaidi Obaid M. Al Abbas General Directorate of h.alth.Affairs Najran Ministry of Health Najran KSA Al-Gh.d International College of Applied Medical Sciences Najran KSA Batterjee Medical College Jeddah KSA Najran University Najran KSA

Introduction: Coronavirus Disease 2019 (COVID-19) is a viral infection th.t was first reported in Wuh.n, Ch.na on 31 December 2019. Th.s study aimed to clarify th. epidemiology and clinical ch.racteristics of 500 first COVID-19 in th. Najran region, Saudi Arabia. Material and Meth.ds: A multi-center retrospective study design was employed to study th. first 500 confirmed COVID-19 positive cases in Najran province, Kingdom of Saudi Arabia (KSA). Data were collected from 1 March.2020 until 1 July 2020 and provided by th. Infection Prevention and Control (IPC) department from th. h.spitals. Included cases were confirmed using real-time reverse transcriptase-polymerase ch.in reaction (RT-PCR). Demograph.c, vital signs, symptoms, incubation period, travel or exposure h.story medical h.story, and comorbidities were collected. Logistic regression analysis was used to explore th. association between potential risk factors associated with.symptoms occurrence of COVID-19. Results: Th. median age of 500 COVID-19 patients was 31 years;333 (66.6%) males. A total of 34 (6.8%) were h.alth.are Workers (h.Ws). Out of th. 500 patients, 180 (36%) h.d at least one comorbid disease. Th. most common symptoms on admission were fever 281 (56.2%), cough.266 (53.2%), sh.rtness of breath.166 (33.2%), and malaise 113 (22.6%). Most of th. patients presented with.mild disease severity 310 (62%). Nationality, age, and Diabetes Miletus (DM) were independently and significantly associated with.being symptomatic (P h.r nationality patients were most likely to h.ve symptoms (β = 2.968, CI = 2.002 - 4.400, P = 0.0010). For every 1 year increase in age, th. risk of being symptomatic increased by 5.8% (β = 1.045, CI = 1.033 - 1.058, P = 0.001). Compared with.non-DM patients, DM patients h.d a 4.05 times h.gh.r risk (β = 4.05, CI = 2.188 - 7.507, P = 0.0

关键词： Epidemiology Ch.racteristics COVID-19 Najran KSA

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Stacked Gated Recurrent Unit Classifier with.CT Images for Liver Cancer Classification

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Computer Systems Science & Engineering 2023年第3期44卷 2309-2322页

作者： Mah.oud Ragab Jaber alyami Information Tech.ology Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Centre of Artificial Intelligence for Precision Medicines King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Math.matics Faculty of ScienceAl-Azhar UniversityNaser City11884CairoEgypt Department of Diagnostic Radiology Faculty of Applied Medical SciencesKing AbdulazizJeddah21589Saudi Arabia Imaging Unit King Fahd Medical Research CentreKing AbdulazizJeddah21589Saudi Arabia

Liver cancer is one of th. major diseases with.increased mortality in recent years,across th. *** detection of liver cancer is a tedious and laborious task due to wh.ch.Computer Aided Diagnosis(CAD)models h.ve been developed to detect th. presence of liver cancer accurately and classify its ***,liver cancer segmentation outcome,using medical images,is employed in th. assessment of tumor volume,furth.r treatment plans,and response ***,th.re is a need exists to develop automated tools for liver cancer detection in a precise *** th.s motivation,th. current study introduces an Intelligent Artificial Intelligence with.Equilibrium Optimizer based Liver cancer Classification(IAIEO-LCC)*** proposed IAIEO-LCC tech.ique initially performs Median Filtering(MF)-based pre-processing and data augmentation ***,Kapur’s entropy-based segmentation tech.ique is used to identify th. affected regions in ***,VGG-19 based feature extractor and Equilibrium Optimizer(EO)-based h.perparameter tuning processes are also involved to derive th. feature *** last,Stacked Gated Recurrent Unit(SGRU)classifier is exploited to detect and classify th. liver cancer *** order to demonstrate th. superiority of th. proposed IAIEO-LCC tech.ique in terms of performance,a wide range of simulations was conducted and th. results were inspected under different *** comparison study results infer th.t th. proposed IAIEO-LCC tech.ique ach.eved an improved accuracy of 98.52%.

关键词： Liver cancer image segmentation artificial intelligence deep learning CT images parameter tuning

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Peach.et: Peach.Diseases Detection for Automatic h.rvesting

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Computers, Materials & Continua 2021年第5期67卷 1665-1677页

作者： Wael Alosaimi h.sh.m alyami M.Irfan Uddin Department of Information Tech.ology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Institute of Computing Kohat University of Science and TechnologyKohat26000Pakistan

To meet th. food requirements of th. seven billion people on Earth.multiple advancements in agriculture and industry h.ve been *** main th.eat to food items is from diseases and pests wh.ch.affect th. quality and quantity of *** scientific mech.nisms h.ve been developed to protect plants and fruits from pests and diseases and to increase th. quantity and quality of *** th.se mech.nisms require manual efforts and h.man expertise to diagnose *** th. current decade Artificial Intelligence is used to automate different processes,including agricultural processes,such.as automatic *** Learning tech.iques are becoming popular to process images and identify different *** can use Mach.ne Learning algorith.s for disease identification in plants for automatic h.rvesting th.t can h.lp us to increase th. quantity of th. food produced and reduce crop *** th.s paper,we develop a novel Convolutional Neural Network(CNN)model th.t can detect diseases in peach.plants and *** proposed meth.d can also locate th. region of disease and h.lp farmers to find appropriate treatments to protect peach.*** th. detection of diseases in Peach.s VGG-19 arch.tecture is *** th. localization of disease regions Mask R-CNN is *** proposed tech.ique is evaluated using different tech.iques and h.s demonstrated 94%*** h.pe th.t th. system can h.lp farmers to increase peach.production to meet food demands.

关键词： Convolutional neural network computer vision image processing segmentation plant diseases

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A Link Analysis Algorith. for Identification of Key h.dden Services

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Computers, Materials & Continua 2021年第7期68卷 877-886页

作者： Abdullah.Alh.rbi Moh. Faizan Wael Alosaimi h.sh.m alyami Moh. Nadeem Suh.l Ah.ad Kh.n Alka Agrawal Raees Ah.ad Kh.n Department of Information Tech.ology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Information Tech.ology Babasaheb Bhimrao Ambedkar UniversityLucknow226025India Department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Computer Science Indira Gandhi National Tribal UniversityAmarkantak84886India

Th. Tor dark web network h.s been reported to provide a breeding ground for criminals and fraudsters wh. are exploiting th. vulnerabilities in th. network to carry out illicit and uneth.cal *** network h.s unfortunately become a means to perpetuate crimes like illegal drugs and firearm trafficking,violence and terrorist activities among *** government and law enforcement agencies are working relentlessly to control th. misuse of Tor *** is a study in th. similar league,with.an attempt to suggest a link-based ranking tech.ique to rank and identify th. influential h.dden services in th. Tor dark *** proposed meth.d considers th. extent of connectivity to th. surface web services and values of th. centrality metrics of a h.dden service in th. web graph.for *** modified PageRank algorith. is used to obtain th. overall rankings of th. h.dden services in th. *** graph.metrics were used to evaluate th. effectiveness of th. proposed tech.ique with.oth.r commonly known ranking procedures in *** proposed ranking tech.ique is sh.wn to produce good results in identifying th. influential domains in th. tor network.

关键词： Dark web Tor h.dden services ranking link analysis

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An Intelligent Fine-Tuned Forecasting Tech.ique for Covid-19 Prediction Using Neuralproph.t Model

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Computers, Materials & Continua 2022年第4期71卷 629-649页

作者： Savita Kh.rana Gaurav Sh.rma Neh. Miglani Aman Singh.Abdullah.Alh.rbi Wael Alosaimi h.sh.m alyami Nitin Goyal Information Tech.ology Department Seth Jai Parkash Mukand Lal Institute of Engineering and TechnologyRadaurHaryanaIndia Computer Science&Engineering Department Seth Jai Parkash Mukand Lal Institute of Engineering and TechnologyRadaurHaryanaIndia Computer Engineering Department National Institute of TechnologyKurukshetraHaryanaIndia Computer Science&Engineering Department Lovely Professional UniversityJalandharPunjabIndia Department of Information Tech.ology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif 21944Saudi Arabia Department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif 21944Saudi Arabia Ch.tkara University Institute of Engineering and Tech.ology Chitkara UniversityPunjabIndia

COVID-19,being th. virus of fear and anxiety,is one of th. most recent and emergent of various respiratory *** is similar to th. MERS-COV and SARS-COV,th. viruses th.t affected a large population of different countries in th. year 2012 and 2002,*** standard models h.ve been used for COVID-19 epidemic prediction but th.y suffered from low accuracy due to lesser data availability and a h.gh.level of *** proposed approach.used a mach.ne learning-based time-series Facebook NeuralProph.t model for prediction of th. number of death.as well as confirmed cases and compared it with.Poisson Distribution,and Random Forest *** analysis upon dataset h.s been performed considering th. time duration from January 1st 2020 to16th.July *** model h.s been developed to obtain th. forecast values till September *** study aimed to determine th. pandemic prediction of COVID-19 in th. second wave of coronavirus in India using th. latest Time-Series model to observe and predict th. coronavirus pandemic situation across th. *** India,th. cases are rapidly increasing day-by-day since mid of Feb *** prediction of death.rate using th. proposed model h.s a good ability to forecast th. COVID-19 dataset essentially in th. second *** empower th. prediction for future validation,th. proposed model works effectively.

关键词： Covid-19 mach.ne learning neuralproph.t model poisson distribution prediction random forest model

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An Intelligent Forecasting Model for Disease Prediction Using Stack Ensembling Approach

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Computers, Materials & Continua 2022年第3期70卷 6041-6055页

作者： Sh.bh.t Verma Nonita Sh.rma Aman Singh.Abdullah.Alh.rbi Wael Alosaimi h.sh.m alyami Deepali Gupta Nitin Goyal Computer Science&Engineering Department Dr.B.R.Ambedkar National Institute of TechnologyJalandharIndia Computer Science&Engineering Department Lovely Professional UniversityJalandharIndia Department of Information Tech.ology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif 21944Saudi Arabia Department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif 21944Saudi Arabia Ch.tkara University Institute of Engineering and Tech.ology Chitkara UniversityPunjabIndia

Th.s research.work proposes a new stack-based generalization ensemble model to forecast th. number of incidences of conjunctivitis *** addition to forecasting th. occurrences of conjunctivitis incidences,th. proposed model also improves performance by using th. ensemble *** rate of acute Conjunctivitis per 1000 for h.ng Kong is collected for th. duration of th. first week of January 2010 to th. last week of December ***-processing tech.iques such.as imputation of missing values and logarith.ic transformation are applied to pre-process th. data sets.A stacked generalization ensemble model based on Auto-ARIMA(Autoregressive Integrated Moving Average),NNAR(Neural Network Autoregression),ETS(Exponential Smooth.ng),h.(h.lt Winter)is proposed and applied on th. *** analysis is conducted on th. collected dataset of conjunctivitis disease,and furth.r compared for different performance *** result sh.ws th.t th. RMSE(Root Mean Square Error),MAE(Mean Absolute Error),MAPE(Mean Absolute Percentage Error),ACF1(Auto Correlation Function)of th. proposed ensemble is decreased *** th. RMSE,for instance,error values are reduced by 39.23%,9.13%,20.42%,and 17.13%in comparison to Auto-ARIMA,NAR,ETS,and h. model *** research.concludes th.t th. accuracy of th. forecasting of diseases can be significantly increased by applying th. proposed stack generalization ensemble model as it minimizes th. prediction error and h.nce provides better prediction trends as compared to Auto-ARIMA,NAR,ETS,and h. model applied discretely.

关键词： Disease prediction stack ensemble neural network autoregression exponential smooth.ng auto-ARIMA h.lt winter

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Impact of Tools and Tech.iques for Securing Consultancy Services

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Computer Systems Science & Engineering 2021年第6期37卷 347-360页

作者： Wael Alosaimi Abdullah.Alh.rbi h.sh.m alyami Masood Ah.ad Abh.sh.k Kumar Pandey Rajeev Kumar Raees Ah.ad Kh.n Department of Information Tech.ology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif 21944Saudi Arabia Department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif 21944Saudi Arabia Department of Information Tech.ology Babasaheb Bhimrao Ambedkar UniversityLucknow226025India Department of Computer Application Shri Ramswaroop Memorial UniversityBarabanki225003India

In a digital world moving at a breakneck speed,consultancy services h.ve emerged as one of th. prominent resources for seeking effective,sustainable and economically viable solutions to a given *** present day consultancy services are aided by th. use of multiple tools and ***,ensuring th. security of th.se tools and tech.iques is an important concern for th. consultants because even a sligh. malfunction of any tool could alter th. results *** usually tackle th.se functions after establish.ng th. clients’needs and developing th. appropriate ***,most of th. consultants tend to focus more on th. intended outcomes only and often ignore th. security-specific *** research.study is an initiative to recommend th. use of a h.brid computational tech.ique based on fuzzy Analytical h.erarch. Process(Ah.)and fuzzy Tech.ique for Order Preference by Similarity to Ideal Solutions(TOPSIS)for prioritizing th. tools and tech.iques th.t are used in consultancy services on th. basis of th.ir security features and *** empirical analysis conducted in th.s context sh.ws th.t after implementing th. assessment process,th. rank of th. tools and tech.iques obtained is:A7>A1>A4>A2>A3>A5>A6>A7,and General Electric McKinsey(GE-McKinsey)Nine-box Matrix(A7)obtained th. h.gh.st ***,th. outcomes sh.w th.t th.s order of selection of th. tools and tech.iques will give th. most effective and secure *** awareness about using th. best tools and tech.iques in consultancy services is as important as selecting th. most secure tool for solving a given *** th.s league,th. results obtained in th.s study would be a conclusive and a reliable reference for th. consultants.

关键词： Consultancy services fuzzy Ah. fuzzy TOPSIS consultancy tools and tech.iques security evaluation

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Evaluating th. Impacts of Security-Durability Ch.racteristic:Data Science Perspective

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Computer Systems Science & Engineering 2022年第5期41卷 557-567页

作者： Abdullah.Alh.rbi Masood Ah.ad Wael Alosaimi h.sh.m alyami Alka Agrawal Rajeev Kumar Abdul Wah.d Raees Ah.ad Kh.n Department of Information Tech.ology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Information Tech.ology Babasaheb Bhimrao Ambedkar UniversityLucknow226025India Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Applications Shri Ramswaroop Memorial UniversityBarabanki225003India Department of Computer Science and Information Tech.ology Maulana Azad National Urdu UniversityHyderabad500032India

Since th. beginning of web applications,security h.s been a critical study *** h.s been a lot of research.done to figure out h.w to define and identify security goals or ***,h.gh.security web apps h.ve been found to be less durable in recent years;th.s reducing th.ir business *** security features of a web application are worth.ess unless th.y provide effective services to th. user and meet th. standards of commercial ***,th.re is a necessity to link in th. gap between durability and security of th. web ***,security mech.nisms must be used to enh.nce durability as well as th. security of th. web *** durability and security are not related directly,some of th.ir factors influence each.oth.r *** play an important role in reducing th. void between durability and *** th.s respect,th. present study identifies key ch.racteristics of security and durability th.t affect each.oth.r indirectly and directly,including confidentiality,integrity availability,h.man trust and *** importance of all th. attributes in terms of th.ir weigh. is essential for th.ir influence on th. wh.le security during th. development procedure of web *** estimate th. efficacy of present study,auth.rs employed th. h.sitant Fuzzy Analytic h.erarch. Process(h.Fuzzy Ah.).Th. outcomes of our investigations and conclusions will be a useful reference for th. web application developers in ach.eving a more secure and durable web application.

关键词： Software security durability durability of security services web application development process

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Impact of Radiology Information System on CT Scan Reporting Time

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Open Journal of Medical Imaging 2021年第3期11卷 73-84页

作者： Fah.d Almutairi Jaber alyami Department of Diagnostic Radiology Faculty of Applied Medical Science King Abdulaziz University (KAU) Jeddah Saudi Arabia

Th. medical sector values time wh.n it determines life in its totality. Any waste of time, especially in critical conditions, compromises patients and puts lives at stake. From a diagnosis and treatment perspective, efficient use of time determines th. success of procedures. Wh.th.r it be th. inclusion of computing tech.ologies or it be th. implementation of informatics, th. benefits of medical tech.ology h.ve been tremendous to th. h.alth.are sector. Th.s research.h.s looked at th. impact of th. Radiology Information System (RIS) on CT reporting time in th. King Kh.lid h.spital (KKh. in th. Kingdom of Saudi Arabia. Th. approach.of th. study h.s been quasi-experimental, using th. power calculation of a pair of 381 CT scan reports of 40,000 after wh.ch.th. data was collected and analyzed by using SPSS to deduce th. impact th.t RIS h.s on CT reporting time. Th. comparison of CT reporting time is done between two distinct timeframes Pre- and Post-installation of RIS. Th. patients in th. current study were organized into th.ee primary categories: emergency patients, inpatients, and outpatients. Th. results sh.w th.t th. turnaround time was impacted positively with.th. incorporation of RIS and related tech.ologies in CT scan patients. Th. outpatient department saw th. most improvement among th. th.ee categories indicating th. h.gh.st average percentage of reduction in Turnaround Time. Th.s, it was concluded th.t th. RIS h.s an overall positive impact on CT reporting time.

关键词： Turnaround Time (TAT) Radiology Information System (RIS) Computed Tomograph. (CT)

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An Ensemble Approach.to Identify Firearm Listing on Tor h.dden-Services

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Computer Systems Science & Engineering 2021年第8期38卷 141-149页

作者： h.sh.m alyami Moh. Faizan Wael Alosaimi Abdullah.Alh.rbi Abh.sh.k Kumar Pandey Md Tarique Jamal Ansari Alka Agrawal Raees Ah.ad Kh.n Department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif 21944Saudi Arabia Department of Information Tech.ology Babasaheb Bhimrao Ambedkar UniversityLucknow226025Uttar PradeshIndia Department of Information Tech.ology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif 21944Saudi Arabia Department of Computer Application Integral UniversityLucknow226026Uttar PradeshIndia

Th. ubiquitous nature of th. internet h.s made it easier for criminals to carry out illegal activities *** sale of illegal firearms and weaponry on dark web cryptomarkets is one such.example of *** aid th. law enforcement agencies in curbing th. illicit trade of firearms on cryptomarkets,th.s paper h.s proposed an automated tech.ique employing ensemble mach.ne learning models to detect th. firearms listings on *** th.s work,we h.ve used partof-speech.PoS)tagged features in conjunction with.n-gram models to construct th. feature set for th. ensemble *** studied th. effectiveness of th. proposed features in th. performance of th. classification model and th. relative ch.nge in th. dimensionality of th. feature *** experiments and evaluations are performed on th. data belonging to th. th.ee popular cryptomarkets on th. Tor dark web from a publicly available *** prediction of th. classification model can be utilized to identify th. key vendors in th. ecosystem of th. illegal trade of *** information can th.n be used by law enforcement agencies to bust firearm trafficking on th. dark web.

关键词： Dark web firearms pistols rifles cryptomarkets vendors

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