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Systematic Survey on Big Data Analytics and Artificial Intelligence for COVID-19 Containment

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Computer Systems Science & Engineering 2023年第11期47卷 1793-1817页

作者： saeed m.alshahrani Jameel Almalki Waleed Alshehri Rashid mehmood marwan Albahar Najlaa Jannah Nayyar Ahmed Khan Department of Computer Science College Computing and Information TechnologyShaqra UniversityShaqraSaudi Arabia Department of Computer Science College of Computer in Al-LithUmm Al-Qura UniversityMakkahSaudi Arabia High-Performance Computing Center King Abdulaziz UniversityJeddahSaudi Arabia

Artificial Intelligence(AI)has gained popularity for the containment of COVID-19 pandemic *** AI techniques provide efficient mechanisms for handling pandemic *** methods,protocols,data sets,and various validation mechanisms empower the users towards proper decision-making and procedures to handle the *** so many tools,there still exist conditions in which AI must go a long *** increase the adaptability and potential of these techniques,a combination of AI and Bigdata is currently gaining *** paper surveys and analyzes the methods within the various computational paradigms used by different researchers and national governments,such as China and South Korea,to fight against this *** process of vaccine development requires multiple medical *** process requires analyzing datasets from different parts of the *** learning and the Internet of Things(IoT)revolutionized the field of disease diagnosis and disease *** accurate observations from different datasets across the world empowered the process of drug development and drug *** overcome the issues generated by the pandemic,using such sophisticated computing paradigms such as AI,machine Learning(mL),deep learning,Robotics and Bigdata is essential.

关键词： COVID-19 IoT artificial intelligence big data coronavirus deep learning robotics machine learning

Patterns of Infertility and Abortion in Saudi Arabia: A Cross-Sectional Study

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Open Journal of Obstetrics and Gynecology 2024年第6期14卷 911-922页

作者： majed saeed alshahrani Department of Obstetrics and Gynaecology College of Medicine Najran University Najran Saudi Arabia

Background: Infertility and abortion are significant reproductive health concerns globally, impacting individuals' well-being and healthcare systems. In Saudi Arabia, cultural, social, and religious factors influence perceptions and management of these issues, necessitating research to understand the patterns and associated factors. Study Aim: This cross-sectional study aimed to investigate the patterns of infertility and abortion among 458 women in Saudi Arabia, focusing on demographic profiles, reproductive histories, medical conditions, and lifestyle factors. methodology: Participants were recruited from healthcare facilities, and data on age, BmI, reproductive history, medical conditions, assisted reproduction methods, and lifestyle behaviors were collected. Statistical analyses, including chi-square tests, were conducted to examine associations between variables. Results: The majority of participants were aged 30 - 39 years (47.4%), with 76.9% experiencing secondary infertility. Among those with offspring (76.9%), 31% reported using assisted reproduction methods, primarily ovarian stimulators (54.2%). Abortion history was reported by 39.5% of participants. Significant associations were found between age and infertility type (X2 = 5.8, p = 0.054), having offspring and infertility type (X2 = 458.0, p = 0.001), menstrual irregularity and infertility type (X2 = 11.4, p = 0.001), and abortion history and delayed fertility (X2 = 10.4, p = 0.001). Conclusion: Our study reveals significant associations between demographic, medical, and lifestyle factors with infertility patterns and abortion history among Saudi women. These findings emphasize the need for tailored interventions addressing medical conditions, age-related factors, and access to reproductive healthcare services.

关键词： Infertility Abortion Saudi Arabia Reproductive Health Assisted Reproduction Cross-Sectional Study

Persuasive Technology for the Future of Smoking Cessation^*

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Advances in Internet of Things 2024年第2期14卷 36-52页

作者： Fatimah Dera m. alshahrani College of Computer Science King Khalid University (KKU) Abha KSA

This paper explores the integration of persuasive technology into smoking cessation efforts through the development and evaluation of a mobile app, “No-Smoke.” Leveraging compelling features like social support, tracking, planning, and motivation, the app aims to augment user engagement and support the process of quitting smoking. The efficacy of these features has been substantiated through both automated testing and user feedback, highlighting their potential to enhance awareness, motivation, and behavior modification. Despite notable successes, limitations, including a limited user base and uncertainties regarding long-term efficacy, have been acknowledged, stemming from the inherent complexities of smoking cessation. Nevertheless, based on user experiences and feedback, “No-Smoke” represents a promising advancement in the use of technology for public health interventions, particularly in the realm of smoking cessation. To address existing challenges, future research is recommended to encompass a comprehensive, long-term study involving a larger and more diverse user base. Additionally, further investigation should focus on personalization enhancements and the integration of machine learning algorithms to better understand and respond to user behavior.

关键词： Persuasive Technology Smoking Cessation mobile App

Coupling of RANS and BEm Solvers for Simulation of Propeller Behind the Hull in Full Appended model

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China Ocean Engineering 2024年第3期38卷 424-438页

作者： saeed NAJAFI mehdi POURmOSTAFA LIU Peng-fei Iranian National Institute for Oceanography and Atmospheric Science(INIOAS) Tehran 14155-4781Iran Department of maritime Engineering Amir Kabir University of TechnologyTehran 15875-4413Iran marine Offshore and Subsea TechnologySchool of EngineeringNewcastle UniversityNewcastle upon TyneNE17RUUK

To design a propeller for ship power plant,the interaction between ship hull and propeller must be taken into *** main concern is to apply the wake effect of ship stern on the propeller *** this paper,a coupled BEm(Boundary Element method)/RANS(Renolds-Averaged Navier−Stokes)solver is used to simulate propeller behind the hull in the self-propulsion *** motivation of this work is to develop a practical tool to design marine propulsion system without suffering long computational *** unsteady boundary element method which is also known as panel method is chosen to estimate the propeller *** wakes are treated using a time marching wake alignment ***,a RANS code coupled with VoF equation is developed to consider the ship motions and wake field effects in the problem.A coupling algorithm is developed to interchange ship wake field to the potential flow solver and propeller thrust to the RANS *** on the difference between hull resistance and the propeller thrust,a PI controller is developed to compute the propeller RPm in every time *** of the solver is carried out using the towing tank test report of a 50 m oceanography research *** factor and trust deduction coefficient are estimated ***,the wake rollup pattern of the propeller in open water is compared with the propeller in real wake field.

关键词： RANS BEm coupled method ship propeller self-propulsion wake sheet pattern

Studying the effect of surfactant assisted low-salinity water flooding on clay-rich sandstones

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Petroleum 2024年第2期10卷 306-318页

作者： saeed Khezerloo-ye Aghdam Alireza Kazemi mohammad Ahmadi Department of Petroleum Engineering Amirkabir University of Technology (AUT) Department of Petroleum and Chemical Engineering College of Engineering Sultan Qaboos University

Sandstone reservoirs often contain clay particles that can cause damage and reduce permeability during low-salinity water flooding. In this study, the effect of surfactants on fine migration in clay-rich sandstones and its impact on oil recovery was ***, the impact of surfactants on interparticle forces in fine-matrix, fine-fine, and oil-matrix systems was modeled. The results showed that both CTAB(cetyltrimethyl ammonium bromide) and QS(quillaja saponin) cause EDL compaction, weakening the repulsive forces. However, SDS(sodium dodecyl sulfate)and TX(triton X-100) do not affect the EDL. Next, the effect of surfactants on IFT reduction and wettability alteration was experimentally investigated. All surfactants reduced IFT due to the surface excessive concentration mechanism. The wettability alteration experiment illustrated that although QS and CTAB compact EDL around oil and matrix particles leading to attraction force augmentation, they both alter wettability through adsorption on matrix and carboxylic groups present in crude oil, *** aqueous solutions were then injected into various clay-rich sandstone sanpacks, which resulted in increased oil recovery. However, the mechanisms leading to enhanced oil recovery variedby surfactant type. CTAB increased recovery by 10% through IFT reduction and wettability alteration, while SDS and TX increased recovery by 12% and 9%, respectively, through wettability alteration and extreme fine migration. In contrast, partial fine migration in the QS flooding experiment reached a recovery increase of 18%. Permeability trends through experiments were also recorded. During CTAB injection,permeability did not reduce, while QS aqueous solution reduced rock permeability to 5 m D. SDS and TX reduced the magnitude of permeability to 2 m *** conclusion, this study demonstrates that surfactants can effectively improve oil recovery in clay-rich sandstones by altering the interparticle forces, reducing IFT, a

关键词： Surfactant flooding Smart water Fine migration Recovery factor

macrophage modulation with dipeptidyl peptidase-4 inhibitors:A new frontier for treating diabetic cardiomyopathy?

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World Journal of Diabetes 2024年第9期15卷 1847-1852页

作者： saeed mohammadi Ahmed Al-Harrasi Natural and medical Sciences Research Center University of NizwaNizwa 616Oman Department of Biological Sciences and Chemistry University of NizwaNizwa 616Oman

This editorial introduces the potential of targeting macrophage function for diabetic cardiomyopathy(DCm)treatment by dipeptidyl peptidase-4(DPP-4)*** et al studied teneligliptin,a DPP-4 inhibitor used for diabetes management,and its potential cardioprotective effects in a diabetic mouse *** suggested teneligliptin administration may reverse established markers of DCm,including cardiac hypertrophy and compromised *** also inhibited the NLRP3 inflammasome and reduced inflammatory cytokine production in diabetic *** play crucial roles in DCm *** hyperglycemia disturbs the balance between pro-inflammatory(m1)and antiinflammatory(m2)macrophages,favoring a pro-inflammatory state contributing to heart ***,we highlight the potential of DPP-4 inhibitors to modulate macrophage function and promote an anti-inflammatory *** compounds may achieve this by elevating glucagon-like peptide-1 levels and potentially inhibiting the NLRP3 *** studies on teneligliptin in combination with other therapies targeting different aspects of DCm could be suggested for developing more effective treatment strategies to improve cardiovascular health in diabetic patients.

关键词： Diabetic cardiomyopathy macrophage Dipeptidyl peptidase-4 inhibitor Teneligliptin NLRP3 inflammasome Glucagon-like peptide-1

Temperature-jump tensile tests to induce optimized TRIP/TWIP effect in a metastable austenitic stainless steel

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International Journal of minerals,metallurgy and materials 2024年第9期31卷 2025-2036页

作者： mohammad Javad Sohrabi Hamed mirzadeh saeed Sadeghpour Abdol Reza Geranmayeh Reza mahmudi School of metallurgy and materials Engineering College of EngineeringUniversity of Tehran14395-515TehranIran Centre for Advanced Steels Research Materials and Mechanical EngineeringUniversity of Oulu90014 OuluFinland

In the present work,plastic deformation mechanisms were initially tailored by adjusting the deformation temperature in the range of 0 to 200℃ in AISI 304L austenitic stainless steel,aiming to optimize the strength-ductility *** was shown that the combined twinning-induced plasticity(TWIP)/transformation-induced plasticity(TRIP)effects and a wider strain range for the TRIP effect up to higher strains by adjusting the deformation temperature are good strategies to improve the strength-ductility synergy of this metastable stainless *** this regard,by consideration of the observed temperature-dependency of plastic deformation,the controlled sequence of TWIP and TRIP effects for archiving superior strength-ductility trade-off was intended by the pre-designed temperature jump tensile ***,the optimum tensile toughness of 846 mJ/m^(3) and total elongation to 133% were obtained by this strategy via exploiting the advantages of the TWIP effect at 100℃ and the TRIP effect at 25℃ at the later stages of the ***,a deformation-temperature-transformation(DTT)diagram was developed for this metastable ***,based on work-hardening analysis,it was found that the main phenomenon constraining further improvement in the ductility and strengthening was the yielding of the deformation-induced α′-martensite.

关键词： metastable stainless steels transformation-induced plasticity twinning-induced plasticity stacking fault energy mechanical properties

machine Learning Based Cybersecurity Threat Detection for Secure IoT Assisted Cloud Environment

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Computer Systems Science & Engineering 2023年第10期47卷 855-871页

作者： Z.Faizal Khan saeed m.alshahrani Abdulrahman Alghamdi Someah Alangari Nouf Ibrahim Altamami Khalid A.Alissa Sana Alazwari mesfer Al Duhayyim Fahd N.Al-Wesabi Department of Computer Engineering College of Computing and Information TechnologyShaqra UniversityShaqraSaudi Arabia Department of Computer Science College of Computing and Information TechnologyShaqra UniversityShaqraSaudi Arabia Department of Computer Science College of Science and Humanities DawadmiShaqra UniversityShaqraSaudi Arabia Department of mathematics College of EducationShaqra UniversityShaqraSaudi Arabia Saudi Aramco Cybersecurity Chair Networks and Communications DepartmentCollege of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif P.O.Box 11099Taif21944Saudi Arabia Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversityAlaflaj16828Saudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia

The Internet of Things(IoT)is determine enormous economic openings for industries and allow stimulating innovation which obtain between domains in childcare for eldercare,in health service to energy,and in developed to *** develops a difficult problem in IoT platform whereas the presence of cyber-attack requires that *** progress of automatic devices for cyber-attack classifier and detection employing Artificial Intelligence(AI)andmachine Learning(mL)devices are crucial fact to realize security in IoT *** can be required for minimizing the issues of security based on IoT devices ***,this research proposal establishes novel mayfly optimized with Regularized Extreme Learning machine technique called as mFO-RELm model for Cybersecurity Threat classification and detection fromthe cloud and IoT *** proposed mFORELm model provides the effective detection of cybersecurity threat which occur in the cloud and IoT *** accomplish this,the mFO-RELm technique pre-processed the actual cloud and IoT data as to meaningful ***,the proposed models will receive the pre-processing data and carry out the classifier *** boosting the efficiency of the proposed models,themFOtechnique was utilized to *** experiential outcome of the proposed technique was tested utilizing the standard CICIDS 2017 dataset,and the outcomes are examined under distinct aspects.

关键词： mayfly optimization machine learning artificial intelligence cybersecurity threat detection

Forecasting the Academic Performance by Leveraging Educational Data mining

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Intelligent Automation & Soft Computing 2024年第2期39卷 213-231页

作者： mozamel m.saeed Department of Computer Science Prince Sattam bin Abdulaziz UniversityAl Kharj11912Saudi Arabia

The study aims to recognize how efficiently Educational Datamining(EDm)integrates into Artificial Intelligence(AI)to develop skills for predicting students’*** study used a survey questionnaire and collected data from 300 undergraduate students of Al Neelain *** first step’s initial population placements were created using Particle Swarm Optimization(PSO).Then,using adaptive feature space search,Educational Grey Wolf Optimization(EGWO)was employed to choose the optimal attribute *** second stage uses the SVmclassifier to forecast classification *** classifiers were utilized to evaluate the performance of *** to the results,it was revealed that AI could forecast the final grades of students with an accuracy rate of 97%on the test ***,the present study showed that successful students could be selected by the Decision Tree model with an efficiency rate of 87.50%and could be categorized as having equal information ratio gain after the *** the random forest provided an accuracy of 28%.These findings indicate the higher accuracy rate in the results when these models were implemented on the data set which provides significantly accurate results as compared to a linear regression model with accuracy(12%).The study concluded that the methodology used in this study can prove to be helpful for students and teachers in upgrading academic performance,reducing chances of failure,and taking appropriate steps at the right time to raise the standards of *** study also motivates academics to assess and discover EDm at several other universities.

关键词： Academic achievement AI algorithms classifiers data mining deep learning