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Forecasting Mental Stress Using Machine Learning Algorithms

Computers, Materials & Continua 2022年第9期72卷 4945-4966页

作者： Elias Hossain Abdulwahab Alazeb Naif Almudawi Sultan Almakdi mohammed alshehri M.Gazi Golam Faruque Wahidur Rahman Department of Software Engineering Daffodil UniversityDhakaBangladesh Collage of Computer Science and Information System University of NajranNajranSaudi Arabia Department of Computer Science and Engineering Khwaja Yunus Ali UniversitySirajganj 6751Bangladesh

Depression is a crippling affliction and affects millions of individuals around the *** general,the physicians screen patients for mental health disorders on a regular basis and treat patients in collaboration with psychologists and other mental health experts,which results in lower costs and improved patient ***,this strategy can necessitate a lot of buy-in from a large number of people,as well as additional training and logistical ***,utilizing the machine learning algorithms,patients with depression based on information generally present in a medical file were analyzed and *** methodology of this proposed study is divided into six parts:Proposed Research Architecture(PRA),Data Pre-processing Approach(DPA),Research Hypothesis Testing(RHT),Concentrated Algorithm Pipeline(CAP),Loss Optimization Stratagem(LOS),and Model Deployment Architecture(MDA).The Null Hypothesis and Alternative Hypothesis are applied to test the *** addition,Ensemble Learning Approach(ELA)and Frequent Model Retraining(FMR)have been utilized for optimizing the loss ***,the Features Importance Interpretation is also delineated in this *** forecasts could help individuals connect with expert mental health specialists more quickly and *** to the findings,71%of people with depression and 80%of those who do not have depression can be appropriately *** study obtained 91%and 92%accuracy through the Random Forest(RF)and Extra Tree *** after applying the Receiver operating characteristic(ROC)curve,79%accuracy was found on top of RF,81%found on Extra Tree,and 82%recorded for the eXtreme Gradient Boosting(XGBoost)***,several factors are identified in terms of predicting depression through statistical data *** the additional effort is needed to develop a more accurate model,this model can be adjustable in the healthcare sector for diagnosing depression.

关键词： Depression analysis mental health machine learning model deployment XGBoost ROC-AUC

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Identification of potential inhibitors for Sterol C-24 reductase of Leishmania donovani through virtual screening of natural compounds

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BIOCELL 2021年第6期45卷 1601-1610页

作者： FAZLUR RAHMAN SHAMS TABREZ RAHAT ALI SAJJADUL KADIR AKAND mohammed AALAIDAROUS mohammed ALSAWEED BADER mohammed alshehri SAEED BANAWAS ABDUR RUB ABDUL AZIZ BIN DUKHYIL Infection and Immunity Laboratory(414) Department of BiotechnologyJamia Millia Islamia-A Central UniversityNew Delhi110025India Department of Medical Laboratory Sciences College of Applied Medical SciencesMajmaah UniversityAl Majmaah11952Saudi Arabia Health and Basic Sciences Research Center Majmaah UniversityAl Majmaah11952Saudi Arabia

Leishmaniasis is a vector-borne parasitic neglected tropical disease caused by a group of about 30 different species of the genus *** is transmitted by the bite of female phlebotomies sand *** main clinical manifestations of leishmaniasis include cutaneous,visceral,and mucocutaneous *** leishmaniasis(VL)caused by Leishmania donovani,is an infection of reticuloendothelial system and fatal if ***,a sterol that is prominent in the mammalian cell membranes whereas stigmasterol and ergosterol are more prevalent in plants,yeast,and protozoa,*** which is absent in human being,is an important constituent of parasite *** C-24 reductase(LdSR)enzyme catalyzes the final step in the ergosterol biosynthesis *** inhibition of biosynthesis of ergosterol may lead to decreased cell viability and ***,we performed the molecular docking-based virtual screening of a library of natural ligands against LdSR to identify a potential inhibitor to fight ***,prenyletin,flavan-3-ol,resveratrol,and gingerol showed the top binding affinity towards *** upon ADME properties and bioactivity score,gingerol showed the best lead-likeness and drug-likeness ***,we further annotated its leishmanicidal *** found that gingerol inhibited the growth and proliferation of promastigotes as well as intra-macrophagic *** exerted its antileishmanial action through the induction of reactive oxygen species(ROS)in concentration-dependent *** induced ROS led to ***,this study described that gingerol would act as possible inhibitor to LdSR.

关键词： Leishmania Gingerol Sterol C-24 reductase Molecular docking ROS

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A Lightweight Deep Learning-Based Model for Tomato Leaf Disease Classification

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Computers, Materials & Continua 2023年第12期77卷 3969-3992页

作者： Naeem Ullah Javed Ali Khan Sultan Almakdi mohammed S.alshehri Mimonah Al Qathrady Eman Abdullah Aldakheel Doaa Sami Khafaga Department of Software Engineering University of Engineering and TechnologyTaxila4400Pakistan Department of Computer Science Faculty of PhysicsEngineeringand Computer ScienceUniversity of HertfordshireHatfieldAL109ABUK Department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia Departments of Information Systems College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia

Tomato leaf diseases significantly impact crop production,necessitating early detection for sustainable *** Learning(DL)has recently shown excellent results in identifying and classifying tomato leaf ***,current DL methods often require substantial computational resources,hindering their application on resource-constrained *** propose the Deep Tomato Detection Network(DTomatoDNet),a lightweight DL-based framework comprising 19 learnable layers for efficient tomato leaf disease classification to overcome *** Convn kernels used in the proposed(DTomatoDNet)framework is 1×1,which reduces the number of parameters and helps in more detailed and descriptive feature extraction for *** proposed DTomatoDNet model is trained from scratch to determine the classification success rate.10,000 tomato leaf images(1000 images per class)from the publicly accessible dataset,covering one healthy category and nine disease categories,are utilized in training the proposed DTomatoDNet *** specifically,we classified tomato leaf images into Target Spot(TS),Early Blight(EB),Late Blight(LB),Bacterial Spot(BS),Leaf Mold(LM),Tomato Yellow Leaf Curl Virus(YLCV),Septoria Leaf Spot(SLS),Spider Mites(SM),Tomato Mosaic Virus(MV),and Tomato Healthy(H).The proposed DTomatoDNet approach obtains a classification accuracy of 99.34%,demonstrating excellent accuracy in differentiating between tomato *** model could be used on mobile platforms because it is lightweight and designed with fewer *** farmers can utilize the proposed DTomatoDNet methodology to detect disease more quickly and easily once it has been integrated into mobile platforms by developing a mobile application.

关键词： CNN deep learning DTomatoDNet tomato leaf disease classification smart agriculture

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Dm-Health App:Diabetes Diagnosis Using Machine Learning with Smartphone

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Computers, Materials & Continua 2022年第7期72卷 1713-1746页

作者： Elias Hossain mohammed alshehri Sultan Almakdi Hanan Halawani Md.Mizanur Rahman Wahidur Rahman Sabila Al Jannat Nadim Kaysar Shishir Mia Department of Software Engineering Daffodil International UniversityDhaka1207Bangladesh Department of Computer Science Najran UniversityNajran55461Saudi Arabia Department of Computer Science and Engineering Rajshahi University of Engineering and TechnologyRajshahi6204Bangladesh Department of Computer Science and Engineering Mawlana Bhashani Science and Technology UniversitySantoshTangail1902Bangladesh Department of Computer Science and Engineering BRAC UniversityDhaka1212Bangladesh Department of Computer Science and Engineering World University BangladeshDhaka1230Bangladesh

Diabetes Mellitus is one of the most severe diseases,and many studies have been conducted to anticipate *** research aimed to develop an intelligent mobile application based on machine learning to determine the diabetic,pre-diabetic,or non-diabetic without the assistance of any physician or medical *** study’s methodology was classified into two the Diabetes Prediction Approach and the Proposed System Architecture *** Diabetes Prediction Approach uses a novel approach,Light Gradient Boosting Machine(LightGBM),to ensure a faster *** Proposed System ArchitectureDesign has been combined into sevenmodules;the Answering Question Module is a natural language processing Chabot that can answer all kinds of questions related to *** Doctor Consultation Module ensures free treatment related to *** this research,90%accuracy was obtained by performing K-fold cross-validation on top of the K nearest neighbor’s algorithm(KNN)&*** evaluate the model’s performance,Receiver Operating Characteristics(ROC)Curve and Area under the ROC Curve(AUC)were applied with a value of 0.948 and 0.936,*** manuscript presents some exploratory data analysis,including a correlation matrix and survey ***,the proposed solution can be adjustable in the daily activities of a diabetic patient.

关键词： Machine learning diabetes-prediction support vector machine(SVM) LightGBM eHealth ROC-AUC

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Exploring Metal Based Nanoparticles for Boosting Plant Tolerance to Heavy Metals and Trace Element Contamination

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Phyton-International Journal of Experimental Botany 2024年第11期93卷 2683-2705页

作者： Abdul Ghafoor Maria Latif Shafaqat Ali Muhammad Munir Muhammad Naeem Sattar mohammed Ali alshehri Water and Environmental Study Centre King Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Environmental Sciences Government College University FaisalabadFaisalabad38000Pakistan Department of Biological Sciences and Technology China Medical UniversityTaichung40402Taiwan Date Palm Research Center of Excellence King Faisal UniversityAl-Ahsa31982Saudi Arabia Central Laboratories King Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Biology Faculty of ScienceUniversity of TabukTabuk71491Saudi Arabia

Heavy metal pollution in agricultural soils is a signiﬁcant challenge for global food production and human health with the increasing industrialization and *** is a concern about introducing innovative techni-ques that are eco-friendly,cost-effective,and have the potential to alleviate metals,enhance crop growth,and pro-tect plants against various environmental *** this,nanotechnology is one of the promising solutions having various applications in almost everyﬁeld of *** review explores various nano-based strategies that use nanoparticles(NPs)to lessen the harmful effects that heavy metals have on *** literature including published research and review papers from the year 2015 to *** review paper gives a thorough review of the current situation regarding heavy metal contamination in agricultural soils and how it affects plant *** necessity ofﬁnding practical and eco-friendly ways to address these issues is emphasized,paving the way for the introduction of ***,it highlighted the mechanistic route of heavy metal toxicity alleviation in plants by their application as well as their long-term efﬁciency and *** review also elaborated on var-ious synthesis methods(physical,chemical,and green),but the emphasis on the green synthesis of NPs by utiliz-ing plant extract offers dependable and sustainable beneﬁts over traditional physicochemical *** trace element stress,NPs application enhances plant antioxidant defense system,ameliorating structural changes,immobilizing trace elements in growth media,and improving the physio-chemical properties of soil as ***-ever,there are still numerous limitations present on how these materials are synthesized,applied,and appropri-ately absorbed by plant *** is recommended to promote and fund long-term research to assess the long-term effects of using NPs on plant development,soil health,and possible environmental repercussions.

关键词： Nanotechnology heavy metals toxicity agriculture physio-chemical attributes crop yield

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Cyberattack Detection Framework Using Machine Learning and User Behavior Analytics

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Computer Systems Science & Engineering 2023年第2期44卷 1679-1689页

作者： Abdullah alshehri Nayeem Khan Ali Alowayr mohammed Yahya Alghamdi Information Technology Department Faculty of Computer Science and Information TechnologyAl Baha UniversityAl Baha65799Saudi Arabia Computer Science Department Faculty of Science and Arts at BuljurashiAl Baha UniversityAl Baha65799Saudi Arabia

This paper proposes a novel framework to detect cyber-attacks using Machine Learning coupled with User Behavior *** framework models the user behavior as sequences of events representing the user activities at such a *** represented sequences are thenﬁtted into a recurrent neural network model to extract features that draw distinctive behavior for individual ***,the model can recognize frequencies of regular behavior to proﬁle the user manner in the *** subsequent procedure is that the recurrent neural network would detect abnormal behavior by classifying unknown behavior to either regu-lar or irregular *** importance of the proposed framework is due to the increase of cyber-attacks especially when the attack is triggered from such sources inside the *** detecting inside attacks are much more challenging in that the security protocols can barely recognize attacks from trustful resources at the network,including ***,the user behavior can be extracted and ultimately learned to recognize insightful patterns in which the regular patterns reﬂect a normal network workﬂ*** contrast,the irregular patterns can trigger an alert for a potential *** framework has been fully described where the evaluation metrics have also been *** experimental results show that the approach performed better compared to other approaches and AUC 0.97 was achieved using RNN-LSTM *** paper has been concluded with pro-viding the potential directions for future improvements.

关键词： Cybersecurity deep learning machine learning user behavior analytics

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International Standard Certification and Firms' Export Performance:Evidence from Saudi Arabia

International Standard Certification and Firms' Export Perfo...

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作者： alshehri.SULTAN mohammed A 南京农业大学

学位级别：硕士

自1987年引入ISO 9000标准以来,无论是在发达国家还是在发展中国家,寻求注册和认证的公司数量都有了巨大的增长。虽然发达国家和一些发展中国家对ISO 9000实施的研究已有大量文献,但目前对沙特制造业影响ISO9000实施因素的研究资料相对... 详细信息

自1987年引入ISO 9000标准以来,无论是在发达国家还是在发展中国家,寻求注册和认证的公司数量都有了巨大的增长。虽然发达国家和一些发展中国家对ISO 9000实施的研究已有大量文献,但目前对沙特制造业影响ISO9000实施因素的研究资料相对较少。这一课题没有得到足够的重视,中东国家也确实缺乏这方面的研究。因此,本研究旨在探讨、识别及分析影响沙特制造业推行ISO 9000标准的因素。通过世界银行企业调查对沙特阿拉伯制造业企业进行了实证研究,旨在通过国际质量标准认证对沙特企业出口绩效的影响来研究沙特制造业企业的出口绩效。在数据分析方面,运用回归分析法和后文的PSM方法,分析了国际质量标准认证对沙特企业/企业出口行为的影响。数据分析是这项研究的贡献,它有助于提高沙特阿拉伯制造/出口组织对ISO的了解。本文以世界银行2005年企业调查的相关数据为基础,运用回归分析和PSM方法,分析了国际质量标准认证对沙特企业出口行为的影响。研究表明,出口扩张的国际质量标准认证对企业出口机会的边际概率有显著影响。随着国际质量标准认证的实施,企业出口量不断增加;国际质量标准认证对企业出口利润率也有着显著的影响,有助于扩大企业的出口销售规模。用PSM方法得到的结果表明了鲁棒性的有效性。

关键词： ISO9000 制造业沙特阿拉伯出口

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Falkner-Skan aspects of a radiating(50%ethylene glycol D 50%water)-based hybrid nanofluid when Joule heating as well as Darcy-Forchheimer and Lorentz forces affect significantly

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Propulsion and Power Research 2023年第3期12卷 428-442页

作者： Ghulam Rasool A.Wakif Xinhua Wang Ahmed alshehri Abdulkafi mohammed Saeed Institute of Intelligent Machinery Faculty of Materials and ManufacturingBeijing University of TechnologyBeijing 100124China Department of Mechanical Engineering Lebanese American UniversityBeirutLebanon Laboratory of Mechanics Faculty of Sciences Aïn ChockHassan II UniversityCasablancaMorocco Department of Mathematics Faculty of SciencesKing Abdulaziz UniversityJeddah 21589Saudi Arabia Department of Mathematics College of ScienceQassim UniversityBuraydah 51452Saudi Arabia

Falkner-Skan aspects are revealed numerically for a non-homogeneous hybrid mixture of 50%ethylene glycol-50%water,silver nanomaterials Ag,and molybdenum disul-fide nanoparticles MoS2 during its motion over a static wedge surface in a DarcyForchheimer porous medium by employing the modified Buongiorno *** Brownian and thermophoresis mechanisms are included implicitly along with the thermophysical properties of each phase via the mixture theory and some efficient phenomenological *** present simulation also accounts for the impacts of nonlinear radiative heat flux,magnetic forces,and Joule ***,the generalized differential quadrature method and Newton-Raphson technique are applied successfully for solving the resulting nonlinear boundary layer *** a limiting case,the obtained findings are validated accurately with the existing literature *** behaviors of velocity,temperature,and nanoparticles volume fraction are discussed comprehensively against various governing *** crucial results,it is revealed that the temperature is enhanced due to magnetic field,linear porosity,radiative heat flux,Brownian motion,thermophoresis,and Joule heating ***,it is depicted that the hybrid nanoliquids present a higher heat flux rate than the monotype nanoliquids and liquids ***,the surface frictional impact is minimized via the linear porosity ***,the surface heat transfer rate receives a prominent improvement due to the radiative heat flux inclusion.

关键词： Ethylene glycol-water hybrid fluid Hybrid nanofluid Falkner-Skan flow Nonlinear radiation Modified Buongiorno nanofluid model

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Automated Speech Recognition System to Detect Babies’ Feelings through Feature Analysis

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Computers, Materials & Continua 2022年第11期73卷 4349-4367页

作者： Sana Yasin Umar Draz Tariq Ali Kashaf Shahid Amna Abid Rukhsana Bibi Muhammad Irfan mohammed A.Huneif Sultan A.Almedhesh Seham M.Alqahtani Alqahtani Abdulwahab mohammed Jamaan Alzahrani Dhafer Batti alshehri alshehri Ali Abdullah Saifur Rahman Faculty of Computing University of OkaraOkara57000Pakistan Department of Computer Science University of SahiwalSahiwal57000PunjabPakistan Computer Science Department COMSATS University IslamabadLahore Campus57000Pakistan Department of Computer Science CUISahiwal CampusSahiwal57000Pakistan Electrical Engineering Department College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia Pediatric Department Medical CollegeNajran University Saudi ArabiaNajran61441Saudi Arabia Consultant of ORL&HNs and Facial Plastic Surgery College of MedicineNajran University Saudi ArabiaNajran61441Saudi Arabia

Diagnosing a baby’s feelings poses a challenge for both doctors and parents because babies cannot explain their feelings through expression or *** the emotions of babies and their associated expressions during different sensations such as hunger,pain,etc.,is a complicated *** infancy,all communication and feelings are propagated through cryspeech,which is a natural *** clinical methods can be used to diagnose a baby’s diseases,but nonclinical methods of diagnosing a baby’s feelings are *** such,in this study,we aimed to identify babies’feelings and emotions through their cry using a nonclinical *** in the cry sound can be identified using our method and used to assess the baby’s *** considered the frequency of the cries from the energy of the *** feelings represented by the infant’s cry are judged to represent certain sensations expressed by the child using the optimal frequency of the recognition of a real-world audio *** used machine learning and artificial intelligence to distinguish cry tones in real time through feature *** experimental group consisted of 50%each male and female babies,and we determined the relevancy of the results against different *** application produced real-time results after recognizing a child’s cry *** novelty of our work is that we,for the first time,successfully derived the feelings of young children through the cry-speech of the child,showing promise for end-user applications.

关键词： Cry-to-speak machine learning artificial intelligence cry speech detection babies

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Connection between dermatomyositis and montelukast sodium use: A case report

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World Journal of Dermatology 2022年第2期10卷 10-16页

作者： mohammed H Aly Abdulrahman A alshehri Abdelgaffar mohammed Murouj Adnan Almaghrabi Malek M Alharbi Department of Internal Medicine Security Forces HospitalMakkah 21599Saudi Arabia Department of Rheumatology Security Forces HospitalMakkah 21599Saudi Arabia College of Medicine Umm Al-Qura UniversityMakkah 24382Saudi Arabia

BACKGROUND Montelukast or Singulair is a leukotriene receptor antagonist that reduces inflammation and relaxes the smooth *** is known to be a safe and tolerable drug;nevertheless,it might be associated with several mild to severe adverse effects,one of which is *** is a rare acquired autoimmune myositis of unknown cause affecting adults and *** literature has infrequently reported the association between dermatomyositis and montelukast *** SUMMARY The current study reports a case of a 48-year-old black woman with a previous history of bronchial asthma and allergic rhinosinusitis who presented with typical signs and symptoms of dermatomyositis which were confirmed by *** developing dermatomyositis,the patient was prescribed montelukast for atopy and consumed the drug for five *** administration of prednisolone,the patient had a significant improvement and is still being followed *** Even though montelukast is widely used and believed to be a safe drug for managing several conditions,the present case report highlights the possibility of adverse effects of ***,future studies with advanced study designs are highly recommended to investigate the association between dermatomyositis and montelukast use.

关键词： Montelukast Singulair Adverse effects Dermatomyositis Asthma medication Case report

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