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OBSO Based Fractional PID for MPPT-Pitch Control of Wind Turbine Systems

Computers, Materials & Continua 2022年第5期71卷 4001-4017页

作者： Ibrahim M.Mehedi Ubaid M.Al-Saggaf Mahendiran T.Vellingiri Ahmad H.Milyani nordin bin saad Nor Zaihar bin Yahaya Department of Electrical and Computer Engineering(ECE) King Abdulaziz UniversityJeddah21589Saudi Arabia Center of Excellence in Intelligent Engineering Systems(CEIES) King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Electrical&Electronics Engineering Universiti Teknologi PETRONASMalaysia

In recent times,wind energy receives maximum attention and has become a significant green energy source *** wind turbine(WT)entered into several domains such as power electronics that are employed to assist the connection process of a wind energy system and *** turbulent characteristics of wind profile along with uncertainty in the design of WT make it highly challenging for prolific power *** pitch control angle is employed to effectively operate the WT at the above nominal wind ***,the pitch controller needs to be intelligent for the extraction of sustainable secure energy and keep WTs in a safe operating *** achieve this,proportional–integral–derivative(PID)controllers are widely used and the choice of optimal parameters in the PID controllers needs to be properly *** this motivation,this paper designs an oppositional brain storm optimization(OBSO)based fractional order PID(FOPID)design for sustainable and secure energy in WT *** proposed model aims to effectually extract the maximum power point(MPPT)in the low range of weather conditions and save the WT in high wind regions by the use of pitch *** OBSO algorithm is derived from the integration of oppositional based learning(OBL)concept with the traditional BSO algorithm in order to improve the convergence rate,which is then applied to effectively choose the parameters involved in the FOPID *** performance of the presented model is validated on the pitch control of a 5 MW WT and the results are examined under different *** simulation outcomes ensured the promising characteristics of the proposed model over the other methods.

关键词： Wind turbine wind energy pitch control brain storm optimization PID controller maximum power point

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Mechanical and magneto-electronic properties of europium lanthanide-based cubic perovskites EuYO_(3)(Y=Cr, Mn, Fe): An ab initio study

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Journal of Rare Earths 2024年第3期42卷 562-569,I0005页

作者： Hayat Ullah Azra Sarwar Sajad Ali Rabah Khenata Abdelmadjid Bouhemadou saad bin-Omran Department of Physics Women University of Azad Jammu&Kashmir Bagh 10250Pakistan Department of Physics Abdul Wali Khan UniversityMardan23200KPPakistan LPQ3M Laboratory Institute of Science and TechnologyUniversity of Mascara29000MascaraAlgeria Laboratory for Developing New Materials and Their Characterization Farhat Abbas University Setif l19000SetifAlgeria Department of Physics and Astronomy College of ScienceKing Saud UniversityP.O.Box 2455Riyadh11451Saudi Arabia

Computational calculations using density functional theory(DFT) were performed for the first time using the full potential linearized augmented plane wave plus local orbital method(FP-LAPW + LO) to determine the structural, elastic, electronic and magnetic properties of europium-based cubic perovskites EuYO_(3)(Y=Cr, Mn, Fe). The exchange correlation potentials of GGA along with some analytical methods were adopted for the computation of structural and elastic properties. Moreover, the GGA + U formalism was also added for obtaining more precise electronic and magnetic properties, particularly to address the Eu-4f and Y-3d orientations in the spin-polarized double cell symmetry. The observed lattice parameters of these compounds are consistent with experiment. The observed bulk moduli predict that EuCrO_(3) is harder and less compressible than EuMnO_(3) and EuFeO_(3). The calculated tolerance factors of these compounds are within the cubic symmetry range. Our computed critical radius of EuCrO_(3) shows that EuCrO_(3) has a larger migration energy. Based on their elastic properties, these compounds are ductile in nature. We also computed the thermal properties of these compounds. The band structures and density of states show that these compounds are metallic in character. The lowest ground state energy and magnetic moments of these compounds expose their ferromagnetic nature. The metallic nature and strong ferromagnetism of these compounds make them promising applicants for application in spintronic.

关键词： Perovskites GGA+U Elastic constants Band structure Magnetic moments Rare earths

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Network Security Enhanced with Deep Neural Network-Based Intrusion Detection System

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Computers, Materials & Continua 2024年第7期80卷 1457-1490页

作者： Fatma S.Alrayes Mohammed Zakariah Syed Umar Amin Zafar Iqbal Khan Jehad saad Alqurni Information Systems Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia College of Computer and Information Sciences King Saud UniversityRiyadh11362Saudi Arabia College of Computer and Information Sciences Prince Sultan UniversityRiyadh11586Saudi Arabia Department of Educational Technologies College of EducationImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia

This study describes improving network security by implementing and assessing an intrusion detection system(IDS)based on deep neural networks(DNNs).The paper investigates contemporary technical ways for enhancing intrusion detection performance,given the vital relevance of safeguarding computer networks against harmful *** DNN-based IDS is trained and validated by the model using the NSL-KDD dataset,a popular benchmark for IDS *** model performs well in both the training and validation stages,with 91.30%training accuracy and 94.38%validation ***,the model shows good learning and generalization capabilities with minor losses of 0.22 in training and 0.1553 in ***,for both macro and micro averages across class 0(normal)and class 1(anomalous)data,the study evaluates the model using a variety of assessment measures,such as accuracy scores,precision,recall,and F1 *** macro-average recall is 0.9422,the macro-average precision is 0.9482,and the accuracy scores are ***,macro-averaged F1 scores of 0.9245 for class 1 and 0.9434 for class 0 demonstrate the model’s ability to precisely identify anomalies *** research also highlights how real-time threat monitoring and enhanced resistance against new online attacks may be achieved byDNN-based intrusion detection systems,which can significantly improve network *** study underscores the critical function ofDNN-based IDS in contemporary cybersecurity procedures by setting the foundation for further developments in this *** research aims to enhance intrusion detection systems by examining cooperative learning techniques and integrating up-to-date threat knowledge.

关键词： Machine-Learning Deep-Learning intrusion detection system security privacy deep neural network NSL-KDD Dataset

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Machine Learning Empowered Security and Privacy Architecture for IoT Networks with the Integration of Blockchain

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Intelligent Automation & Soft Computing 2024年第2期39卷 353-379页

作者： Sohaib Latif M.saad bin Ilyas Azhar Imran Hamad Ali Abosaq Abdulaziz Alzubaidi Vincent Karovic Jr. Department of Computer Science The University of ChenabGujrat50700Pakistan Department of Creative Technologies Air UniversityIslamabad42000Pakistan Computer Science Department College of Computer Science and Information SystemsNajran UniversityNajran66244Saudi Arabia Department of Computer Science Umm Alqura UniversityAlQunfudah28821Saudi Arabia Department of Information Systems Faculty of ManagementComenius University in BratislavaBratislava82005Slovakia

The Internet of Things(IoT)is growing rapidly and impacting almost every aspect of our lives,fromwearables and healthcare to security,traffic management,and fleet management *** has generated massive volumes of data and security,and data privacy risks are increasing with the advancement of technology and network *** access control solutions are inadequate for establishing access control in IoT systems to provide data protection owing to their vulnerability to single-point OF ***,conventional privacy preservation methods have high latency costs and overhead for resource-constrained *** machine learning approaches were also unable to detect denial-of-service(DoS)*** study introduced a novel decentralized and secure framework for blockchain *** avoid single-point OF failure,an accredited access control scheme is incorporated,combining blockchain with local peers to record each transaction and verify the signature to ***-based attribute-based cryptography is implemented to protect data storage privacy by generating threshold parameters,managing keys,and revoking users on the *** innovative contract-based DOS attack mitigation method is also incorporated to effectively validate devices with intelligent contracts as trusted or untrusted,preventing the server from becoming *** proposed framework effectively controls access,safeguards data privacy,and reduces the risk of *** results depict that the suggested framework outperforms the results in terms of accuracy,precision,sensitivity,recall,and F-measure at 96.9%,98.43%,98.8%,98.43%,and 98.4%,respectively.

关键词： Machine learning internet of things blockchain data privacy security Industry 4.0

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CNN Channel Attention Intrusion Detection SystemUsing NSL-KDD Dataset

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Computers, Materials & Continua 2024年第6期79卷 4319-4347页

Intrusion detection systems(IDS)are essential in the field of cybersecurity because they protect networks from a wide range of online *** goal of this research is to meet the urgent need for small-footprint,highly-adaptable Network Intrusion Detection Systems(NIDS)that can identify *** NSL-KDD dataset is used in the study;it is a sizable collection comprising 43 variables with the label’s“attack”and“level.”It proposes a novel approach to intrusion detection based on the combination of channel attention and convolutional neural networks(CNN).Furthermore,this dataset makes it easier to conduct a thorough assessment of the suggested intrusion detection ***,maintaining operating efficiency while improving detection accuracy is the primary goal of this ***,typical NIDS examines both risky and typical behavior using a variety of *** the NSL-KDD dataset,our CNN-based approach achieves an astounding 99.728%accuracy rate when paired with channel *** to previous approaches such as ensemble learning,CNN,RBM(Boltzmann machine),ANN,hybrid auto-encoders with CNN,MCNN,and ANN,and adaptive algorithms,our solution significantly improves intrusion detection ***,the results highlight the effectiveness of our suggested method in improving intrusion detection precision,signifying a noteworthy advancement in this *** efforts will focus on strengthening and expanding our approach in order to counteract growing cyberthreats and adjust to changing network circumstances.

关键词： Intrusion detection system(IDS) NSL-KDD dataset deep-learning machine-learning CNN channel Attention network security

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Impact of carbimazole combined with vitamin E on testicular injury induced by experimental hyperthyroidism in adult albino rats:oxidative/inflammatory/apoptotic pathways

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Asian Journal of Andrology 2024年第4期26卷 396-401页

作者： Ramadan S Hussein Moustafa M Eyada Rashad M Mostafa Samah M Elaidy Shereen H Elsayed Hany M saad Department of Dermatology College of Medicine Prince Sattam Bin Abdulaziz UniversityAl-Kharj 16242Saudi Arabia Department of Dermatology Andrology and STDsAssiut Police HospitalAssiut 71525Egypt Department of Dermatology Venereology and AndrologyFaculty of MedicineSuez Canal UniversityIsmailia 41522Egypt Department of Andrology and Sexology Faculty of MedicineSuez Canal UniversityIsmailia 41511Egypt Department of Clinical Pharmacology Faculty of MedicineSuez Canal UniversityIsmailia 41511Egypt Department of Rehabilitation Sciences Faculty of Health and Rehabilitation SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh 12271Saudi Arabia.

Thyroid hormones play essential roles in spermatogenesis,but their effects on infertile males remain poorly *** study aimed to evaluate the impact of combining carbimazole(CBZ)with vitamin E(VE)on testicular injury induced by experimental hyperthyroidism in adult albino rats,focusing on oxidative,inflammatory,and apoptotic *** this experimental study,64 adult male albino Wistar rats were divided into eight groups:Group I(control-untreated),Group II(CBZ-control),Group III(VE-control),Group IV(CBZ+VE-control),Group V(levothyroxine-induced testicular injury),Group VI(levothyroxine+CBZ-treated),Group VII(levothyroxine+VE-treated),and Group VIII(levothyroxine+CBZ+VE-treated).The study was conducted in the Faculty of Medicine,Suez Canal University(Ismailia,Egypt).After cervical decapitation,both testes and epididymis were examined histopathologically and *** differences were observed among groups concerning malondialdehyde(MDA),glutathione(GSH),superoxide dismutase(SOD),and catalase(CAT;all P<0.001).Polymerase chain reaction analysis showed significant differences in tumor necrosis factor-α(TNF-α),interleukin-10(IL-10),Bcl-2-associated X protein(BAX),B-cell lymphoma 2 protein(Bcl2),p53,Caspase-3,Caspase-8,Caspase-9,and nuclear factor-kappa B(NF-κB)mRNA levels(all P<0.001).Hyperthyroid group treated with CBZ alone(Group VI)exhibited testicular side effects,affecting seminiferous tubules and ***,the Group VIII showed improved spermatogenesis and a decrease in testicular side *** addition of VE to the treatment of hyperthyroid rats with CBZ reduced testicular side effects and seminiferous tubular affection when potentially improving *** research is needed to elucidate the underlying mechanisms fully.

关键词： antithyroid drugs testicular injury thyroid gland vitamin E

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Bullous Pemphigoid Induced by Doxycycline: Case Report and Literature Review

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Case Reports in Clinical Medicine 2024年第5期13卷 187-192页

作者： Mishal Al Mebayadh Rahaf Aldawish Sohail A. Butt Abdulrahman saad Aljahhan Dermatology Department Imam Abdulrahman Bin Faisal University-National Guard Hospital Dammam Saudi Arabia Dermatology Department Al Rass General Hospital Al-Qassim Saudi Arabia Pathology Department Dammam Regional Laboratory & Blood Bank MOH Dammam Saudi Arabia Clinical Documentation Improvement (CDI) Dammam Health Network Dammam Saudi Arabia

Bullous pemphigoid (BP) is the most prevalent autoimmune sub-epidermal blistering disease that affects mainly the elderly and could lead to serious morbidity. It has numerous risk factors and triggers, including an aging population with several comorbidities and drug exposure. In the published paper, we reported a case about a 32 years old male patient with unknown medical conditions who presented with erythematous patches and plaques on the scalp, face, and trunk with scattered blisters two weeks after initiating doxycycline treatment for folliculitis. The exact pathogenesis of the drug-reaction in drug- associated bullous pemphigoid (DABP) remains controversial. In conclusion, it is crucial for clinicians to be aware of DABP when prescribing doxycycline. The purpose of this case report is to raise awareness of the possible association between bullous pemphigoid and doxycycline.

关键词： Bullous Pemphigoid Doxycycline Drug-Associated Bullous Pemphigoid

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Spinal dural arteriovenous fistula:a comprehensive review of the history,classification systems,management,and prognosis

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Chinese Neurosurgical Journal 2024年第1期10卷 48-56页

作者： Ali Alkhaibary Ahoud Alharbi Nada Alnefaie Hajar Alammar Alshaymaa M.Arishy Noor Alghanim Yazeed M.Aldhfyan Arwa Albaiahy Yahya H.Khormi Wael Alshaya saad AlQahatani Ahmed Aloraidi Ahmed Alkhani Sami Khairy College of Medicine King Saud Bin Abdulaziz University for Health SciencesRiyadhSaudi Arabia King Abdullah International Medical Research Center RiyadhSaudi Arabia Division of Neurosurgery Department of SurgeryKing Abdulaziz Medical CityMinistry of National Guard-Health AffairsRiyadhSaudi Arabia Department of Neurosurgery National Neurosciences InstituteKing Fahad Medical CityRiyadhSaudi Arabia College of Medicine Jazan UniversityJazanSaudi Arabia Department of Neurosurgery King Faisal Specialist Hospital and Research CenterRiyadhSaudi Arabia Department of Surgery Faculty of MedicineJazan UniversityJazanSaudi Arabia

Spinal dural arteriovenous fistulas account for the majority of spinal vascular *** are typically located in the thoracolumbar region and are diagnosed in the middle-aged and elderly *** spinal dural arteriovenous fistulas have been postulated to be acquired,their exact development remains ***,the arteriovenous shunt is situated close to the spinal nerve root,inside the dura mater,where the blood from the radiculomeningeal artery and radicular vein *** history,there have been multiple classification systems of spinal arteriovenous shunts since *** were mainly based on the evolution of diagnostic studies as well as the treatment of these *** classification systems have undergone significant changes over the *** intracranial dural arteriovenous fistula,spinal dural arteriovenous fistula is progressive in *** neurological manifestations,due to venous congestion,tend to be insidious as well as *** include sensory deficits,such as paresthesia,bilateral and/or unilateral radicular pain affecting the lower limbs,and gait *** dural arteriovenous fistulas can be suspected on magnetic resonance imaging/magnetic resonance angiography and confirmed by digital subtraction angiography(DSA).The management includes surgery,endovascular therapy,and in selected cases,*** treatment goal of spinal dural arteriovenous fistula is to halt the progression of the *** prognosis depends on both the duration of symptoms as well as the clinical condition prior to *** present article comprehensively reviews the pathophysiology,changes in classification systems,natural history,clinical manifestations,radiological features,management,and prognosis.

关键词： Connection Endovascular Myelopathy Vascular

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Threefold Optimized Forecasting of Electricity Consumption in Higher Education Institutions

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Computers, Materials & Continua 2022年第11期73卷 2351-2370页

作者： Majida Kazmi Hashim Raza Khan Lubaba Mohammad Hashir bin Khalid saad Ahmed Qazi Faculty of Electrical and Computer Engineering NED University of Engineering and TechnologyKarachi75270Pakistan Neurocomputation Lab National Center of Artificial IntelligenceKarachi75270Pakistan

Energy management benefits both consumers and utility companiesalike. Utility companies remain interested in identifying and reducing energywaste and theft, whereas consumers’ interest remain in lowering their energyexpenses. A large supply-demand gap of over 6 GW exists in Pakistan asreported in 2018. Reducing this gap from the supply side is an expensiveand complex task. However, efficient energy management and distributionon demand side has potential to reduce this gap economically. Electricityload forecasting models are increasingly used by energy managers in takingreal-time tactical decisions to ensure efficient use of resources. Advancementin Machine-learning (ML) technology has enabled accurate forecasting ofelectricity consumption. However, the impact of computation cost affordedby these ML models is often ignored in favour of accuracy. This studyconsiders both accuracy and computation cost as concurrently significantfactors because together they shape the technology environment as well ascreate economic impact. Thus, a three-fold optimized load forecasting modelis proposed which includes (1) application specific parameters selection, (2)impact of different dataset granularities and (3) implementation of specificdata preparation. It deploys and compares the widely used back-propagationArtificial Neural Network (ANN) and Random Forest (RF) models for theprediction of electricity consumption of buildings within a university. In addition to the temporal and historical power consumption date as input parameters, the study also embeds weather data as well as university operationalcalendars resulting in improved performance. The outcomes are indicativethat the granularity i.e. the scale of details in data, and set of reduced and fullinput parameters impact performance accuracies differently for ANN and RFmodels. Experimental results show that overall RF model performed betterboth in terms of accuracy as well as computational time for a 1-min, 15-minand 1-h dataset

关键词： Electricity forecasting short term higher educational institution artificial neural network random forest accuracy computational time

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Blockchain and IIoT Enabled Solution for Social Distancing and Isolation Management to Prevent Pandemics

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Computers, Materials & Continua 2023年第7期76卷 687-709页

作者： Muhammad saad Maaz bin Ahmad Muhammad Asif Muhammad Khalid Khan Toqeer Mahmood Elsayed Tag Eldin Hala Abdel Hameed College of Computing and Information Sciences Karachi Institute of Economics&TechnologyKarachiPakistan Department of Computer Science Lahore Garrison UniversityLahorePakistan Department of Computer Science National Textile UniversityFaisalabad37610Pakistan Faculty of Engineering and Technology Future University in Egypt New Cairo11835Egypt Faculty of Computer and Information Systems Fayoum UniversityFaiyumEgypt Khaybar Applied College Taibah UniversityMedinaSaudi Arabia

Pandemics have always been a nightmare for humanity,especially in developing *** lockdowns are considered one of the effective ways to deal with spreading such ***,developing countries cannot afford such solutions because these may severely damage the country’s ***,this study presents the proactive technological mechanisms for business organizations to run their standard business processes during pandemic-like situations *** novelty of this study is to provide a state-of-the-art solution to prevent pandemics using industrial internet of things(IIoT)and blockchain-enabled *** to existing studies,the immutable and tamper-proof contact tracing and quarantine management solution is *** use of advanced technologies and information security is a critical area for practitioners in the internet of things(IoT)and corresponding ***,this study also emphasizes information security,end-to-end solution,and experimental ***,a wearable wristband is proposed,incorporating 4G-enabled ultra-wideband(UWB)technology for smart contact tracing mechanisms in industries to comply with standard operating procedures outlined by the world health organization(WHO).Secondly,distributed ledger technology(DLT)omits the centralized dependency for transmitting contact tracing ***,a privacy-preserving tracing mechanism is discussed using a public/private key cryptography-based authentication ***,based on geofencing techniques,blockchain-enabled machine-to-machine(M2M)technology is proposed for quarantine *** step-by-step methodology and test results are proposed to ensure contact tracing and quarantine *** existing research studies,the security aspect is also considered in the realm of *** practical implementation of the proposed solution also obtains the *** results indicate the successful implementation of blockchain-enabled contac

关键词： Blockchain contact tracing distributed ledger technology geo-fencing internet of things industrial internet of things isolation management social distancing ultra-wideband

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