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Enhancing Renewable Energy Integration:A Gaussian-Bare-Bones Levy Cheetah Optimization Approach to Optimal Power Flow in Electrical Networks

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Computer Modeling in Engineering & Sciences 2024年第8期140卷 1339-1370页

作者： ali S.Alghamdi Mohamed A.Zohdy Saad Aldoihi Department of Electrical Engineering College of EngineeringMajmaah UniversityAl-Majmaah11952Saudi Arabia Electrical and Computer Engineering Department Oakland UniversityRochesterMI48309USA Institute of Earth and Space Science King Abdulaziz City for Science and Technology(KACST)Riyadh11442Saudi Arabia Computer Science and Systems Engineering Institute Polytechnique de ParisPalaiseau CedexFrance

In the contemporary era,the global expansion of electrical grids is propelled by various renewable energy sources(RESs).Efficient integration of stochastic RESs and optimal power flow(OPF)management are critical for network *** study introduces an innovative solution,the Gaussian Bare-Bones Levy Cheetah Optimizer(GBBLCO),addressing OPF challenges in power generation systems with stochastic *** primary objective is to minimize the total operating costs of RESs,considering four functions:overall operating costs,voltage deviation management,emissions reduction,voltage stability index(VSI)and power loss ***,a carbon tax is included in the objective function to reduce carbon *** scrutiny,using modified IEEE 30-bus and IEEE 118-bus systems,validates GBBLCO’s superior performance in achieving optimal *** results demonstrate GBBLCO’s efficacy in six optimization scenarios:total cost with valve point effects,total cost with emission and carbon tax,total cost with prohibited operating zones,active power loss optimization,voltage deviation optimization and enhancing voltage stability index(VSI).GBBLCO outperforms conventional techniques in each scenario,showcasing rapid convergence and superior solution ***,GBBLCO navigates complexities introduced by valve point effects,adapts to environmental constraints,optimizes costs while considering prohibited operating zones,minimizes active power losses,and optimizes voltage deviation by enhancing the voltage stability index(VSI)*** research significantly contributes to advancing OPF,emphasizing GBBLCO’s improved global search capabilities and ability to address challenges related to local *** emerges as a versatile and robust optimization tool for diverse challenges in power systems,offering a promising solution for the evolving needs of renewable energy-integrated power grids.

关键词： Renewable energy integration optimal power flow stochastic renewable energy sources gaussian-bare-bones levy cheetah optimizer electrical network optimization carbon tax optimization

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Optimizing Deep Learning for Computer-Aided Diagnosis of Lung Diseases: An Automated Method Combining Evolutionary Algorithm, Transfer Learning, and Model Compression

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Computer Modeling in Engineering & Sciences 2024年第3期138卷 2519-2547页

作者： Hassen Louati ali Louati Elham Kariri Slim Bechikh College of Information Technology Kingdom UniversityRiffa40434Bahrain SMART Lab University of TunisISGTunisTunisia Department of Information Systems College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia

Recent developments in Computer Vision have presented novel opportunities to tackle complex healthcare issues,particularly in the field of lung disease *** promising avenue involves the use of chest X-Rays,which are commonly utilized in *** fully exploit their potential,researchers have suggested utilizing deep learning methods to construct computer-aided diagnostic ***,constructing and compressing these systems presents a significant challenge,as it relies heavily on the expertise of data *** tackle this issue,we propose an automated approach that utilizes an evolutionary algorithm(EA)to optimize the design and compression of a convolutional neural network(CNN)for X-Ray image *** approach accurately classifies radiography images and detects potential chest abnormalities and infections,including ***,our approach incorporates transfer learning,where a pre-trainedCNNmodel on a vast dataset of chest X-Ray images is fine-tuned for the specific task of detecting *** method can help reduce the amount of labeled data required for the task and enhance the overall performance of the *** have validated our method via a series of experiments against state-of-the-art architectures.

关键词： Computer-aided diagnosis deep learning evolutionary algorithms deep compression transfer learning

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Unilateral Choanal Atresia in Adults: A Case Series

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International Journal of Otolaryngology and Head & Neck Surgery 2024年第3期13卷 187-193页

作者： Sultan Kadasah abdulaziz Al Qahtani Ghalib Al-Sayed Abdullah Al Helali Saud Aldhabaan Abdullah Musleh ali Asiry Mohammed Asiri Shahd Dlboh Adnan Al-Malki Abdulsalam Alqhtani Mohammed Al-khulban Sahar Al-Otaibi Department of Surgery College of Medicine University of Bisha Bisha Saudi Arabia Department of Otolaryngology Head and Neck Surgery Armed Forces Southern Region Hospital Khamis Mushait Saudi Arabia Department of Otolaryngology Head and Neck Surgery Abha Children&#8217s Hospital Abha Saudi Arabia Department of Surgery College of Medicine King Khalid University Abha Saudi Arabia Department of Otolaryngology Head and Neck Surgery Aseer Central Hospital Abha Saudi Arabia College of Medicine King Khalid University Abha Saudi Arabia

Choanal atresia (CA) is a rare occlusion of the posterior choanae. Unilateral cases have been reported more than bilaterally, and it’s more often right-sided in those patients. According to the literature, mixed bony-membranous atresia is the most common type. There is a high incidence of craniofacial and visceral anomalies associated with congenital choanal atresia. Therefore, investigation for associated congenital anomalies is an important step before the surgery. We report 2 cases of incidental finding of unilateral choanal atresia in a 21- and 17-year-old with nasal discharge being the only complaint in the former and nasal obstruction with headache in the latter. The patients were then scheduled for day-surgery as a case of choanal atresia for transnasal, endoscopic repair and posterior septectomy. The patients were discharged home on the same day with the absence of restenosis or other complications.

关键词： Choanal Atresia Nasal Obstruction Congenital Anomaly

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Modelling and Characterization of Basalt/Vinyl Ester/SiC Micro-and Nano-hybrid Biocomposites Properties Using Novel ANN–GA Approach

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Journal of Bionic Engineering 2024年第2期21卷 938-952页

作者： Yesudhasan Thooyavan Lakshmi Annamali Kumaraswamidhas Robinson Dhas Edwin Raj Joseph Selvi Binoj Bright Brailson Mansingh Antony Sagai Francis Britto Alamry ali Department of Mechanical Engineering Indian Institute of Technology Dhanbad(ISM)DhanbadJharkhand826004India Gati Shakti Vishwavidyalaya(GSV-A Central University Funded By GoI in the Ministry of Railways) LalbaugVadodaraGujarat390004India Institute of Mechanical Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical Sciences(SIMATS)Saveetha UniversityChennaiTamilnadu602105India Metal Joining Research Centre Department of Mechanical EngineeringSri Ramakrishna Engineering CollegeCoimbatoreTamilnadu641022India Department of Mechanical Engineering Rohini College of Engineering and TechnologyPalkulamTamil Nadu629401India Department of Mechanical Engineering College of Engineering in Al-KharjPrince Sattam Bin Abdulaziz University11942Al-KharjSaudi Arabia

Basalt fiber reinforcement in polymer matrix composites is becoming more and more popular because of its environmental friendliness and mechanical qualities that are comparable to those of synthetic *** fiber strengthened vinyl ester matrix polymeric composite with filler addition of nano-and micro-sized silicon carbide(SiC)element spanning from 2 weight percent to 10 weight percent was studied for its mechanical and wear *** application of Artificial Neural Network(ANN)to correlate the filler addition composition for optimum mechanical properties is required due to the non-linear mechanical and tribological features of *** stuffing blend and composition of the composite are optimized using the hybrid model and Genetic Algorithm(GA)to maximize the mechanical and wear-resistant *** predicted and tested ANN–GA optimal values obtained for the composite combination had a tensile,flexural,impact resilience,hardness and wear properties of 202.93 MPa,501.67 MPa,3.460 J/s,43 HV and 0.196 g,respectively,for its optimum combination of filler and *** can be noted that the nano-sized SiC filler particle enhances most of the properties of the composite which diversifies its *** predicted mechanical and wear values of the developed ANN–GA model were in closer agreement with the experimental values which validate the model.

关键词： Hybrid polymer composite Prediction Process modelling Artificial neural networks Genetic algorithm

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Inclusion of CoTiO_(3) to ameliorate the re/dehydrogenation properties of the Mg–Na–Al system

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Journal of Magnesium and Alloys 2024年第3期12卷 1215-1226页

作者： N.A.ali N.Y.Yusnizam N.A.Sazelee Sami-ullah Rather Haizhen Liu M.Ismail Energy Storage Research Group Faculty of Ocean Engineering TechnologyUniversiti Malaysia Terengganu21030 Kuala NerusTerengganuMalaysia Department of Chemical and Materials Engineering King Abdulaziz UniversityP.O.Box80204Jeddah 21589Saudi Arabia Guangxi Novel Battery Materials Research Center of Engineering Technology School of Physical Science and TechnologyGuangxi UniversityNanning 530004China State Key Laboratory of Featured Metal Materials and Life-Cycle Safety for Composite Structures Nanning 530004China

For the first time,the MgH_(2)–NaAlH_(4)(ratio 4:1)destabilized system with CoTiO_(3) addition has been *** CoTiO_(3)-doped MgH_(2)–NaAlH_(4) sample begins to dehydrogenate at 130℃,which is declined by 40℃ compared to the undoped MgH_(2)–NaAlH_(4).Moreover,the de/rehydrogenation kinetics characteristics of the CoTiO_(3)-doped MgH_(2)–NaAlH_(4) were greatly *** the inclusion of CoTiO_(3),the MgH_(2)–NaAlH_(4) composite absorbed 5.2 wt.%H_(2),higher than undoped MgH_(2)–NaAlH_(4).In the context of dehydrogenation,the CoTiO_(3)-doped MgH_(2)–NaAlH_(4) sample desorbed 2.6 wt.%H_(2),almost doubled compared to the amount of hydrogen desorbed from the undoped MgH_(2)–NaAlH_(4) *** activation energy obtained by the Kissinger analysis for MgH_(2) decomposition was significantly lower by 35.9 kJ/mol than the undoped MgH_(2)–NaAlH_(4) *** reaction mechanism demonstrated that new phases of MgCo and AlTi_(3) were generated in situ during the heating process and are likely to play a substantial catalytic function and be useful in ameliorating the de/rehydrogenation properties of the destabilized MgH_(2)–NaAlH_(4) system with the inclusion of CoTiO_(3).

关键词： Destabilize system Magnesium hydride Sodium alanate Hydrogen storage Additive.

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Efficient and Secure IoT Based Smart Home Automation Using Multi-Model Learning and Blockchain Technology

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Computer Modeling in Engineering & Sciences 2024年第6期139卷 3387-3415页

作者： Nazik Alturki Raed Alharthi Muhammad Umer Oumaima Saidani Amal Alshardan Reemah M.Alhebshi Shtwai Alsubai ali Kashif Bashir Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadhSaudi Arabia Department of Computer Science and Engineering University of Hafr Al-BatinHafar Al-BatinSaudi Arabia Department of Computer Science&Information Technology The Islamia University of BahawalpurBahawalpurPakistan Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Computer Science College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-KharjSaudi Arabia Department of Computing and Mathematics Manchester Metropolitan UniversityManchesterUK Woxsen School of Business Woxsen UniversityHyderabadIndia Department of Computer Science and Mathematics Lebanese American UniversityBeirutLebanon

The concept of smart houses has grown in prominence in recent *** challenges linked to smart homes are identification theft,data safety,automated decision-making for IoT-based devices,and the security of the device *** home automation systems try to address these issues but there is still an urgent need for a dependable and secure smart home solution that includes automatic decision-making systems and methodical *** paper proposes a smart home system based on ensemble learning of random forest(RF)and convolutional neural networks(CNN)for programmed decision-making tasks,such as categorizing gadgets as“OFF”or“ON”based on their normal routine in *** have integrated emerging blockchain technology to provide secure,decentralized,and trustworthy authentication and recognition of IoT *** system consists of a 5V relay circuit,various sensors,and a Raspberry Pi server and database for managing *** have also developed an Android app that communicates with the server interface through an HTTP web interface and an Apache *** feasibility and efficacy of the proposed smart home automation system have been evaluated in both laboratory and real-time *** is essential to use inexpensive,scalable,and readily available components and technologies in smart home automation ***,we must incorporate a comprehensive security and privacy-centric design that emphasizes risk assessments,such as cyberattacks,hardware security,and other cyber *** trial results support the proposed system and demonstrate its potential for use in everyday life.

关键词： Blockchain Internet of Things(IoT) smart home automation cybersecurity

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Physical properties and maximum allowable mass-radius relation of complexity-free compact stellar objects within modified f(R,T)gravity formalism

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Chinese Physics C 2024年第7期48卷 273-288页

作者： M.K.Jasim S.K.Maurya Abdelghani Errehymy ali Khalid Jassim Kottakkaran Sooppy Nisar Abdel-Haleem Abdel-Aty Department of Mathematical and Physical Sciences College of Arts and SciencesUniversity of NizwaNizwa 616Sultanate of Oman Astrophysics Research Centre School of MathematicsStatistics and Computer ScienceUniversity of KwaZulu-NatalPrivate Bag X54001Durban 4000South Africa Electrical Engineering Department College of EngineeringMustansiriyah UniversityBaghdadIraq Department of Mathematics College of Science and Humanities in AlkharjPrince Sattam bin Abdulaziz UniversityAl KharjSaudi Arabia Department of Physics College of SciencesUniversity of BishaP.O.Box 344Bisha 61922Saudi Arabia

This paper investigates the physical properties and predicted radii of compact stars generated by the Tolman-IV complexity-free model within the background of modified gravity theory,particularly the f(R,T)-gravity theory,under complexity formalism for a spherically symmetric spacetime proposed by ***[Phys Rev D 97:044010,2018].By solving the resulting set of differential equations,we obtain the explicit forms of the energy-momentum(EM)tensor components,including the density,radial pressure,and tangential *** influence of the parameterχon various physical properties of the star is thoroughly *** model undergoes a series of rigorous tests to determine its physical *** findings indicate that the model exhibits regularity,stability,and a surface with vanishing *** boundary of this surface is determined by carefully selecting the parameter *** complexity method employed in f(R,T)gravity offers an interesting approach for developing astrophysical models that are consistent with observable events as demonstrated by recent *** this regard,we use observational data from the GW190814 event,detected by the LIGO and Virgo observatories,to investigate the validity of the Tolman-IV model in f(R,T)*** analysis includes comparing the model's predictions with the observed characteristics of the compact object involved in the *** addition,data from two-millisecond pulsars,PSR J1614-2230 and PSR J0952-0607,are incorporated to further constrain the theoretical ***,we present a diagram depicting the relationship between the total mass and radius of the compact object candidates for different values ofχ.

关键词： complexity modified gravity compact Stars

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Accurate Phase Detection for ZigBee Using Artificial Neural Network

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Intelligent Automation & Soft Computing 2023年第6期36卷 2505-2518页

作者： ali Alqahtani abdulaziz A.Alsulami Saeed Alahmari Mesfer Alrizq Department of Networks and Communications Engineering College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Science College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Information Systems College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia

The IEEE802.15.4 standard has been widely used in modern industry due to its several benefits for stability,scalability,and enhancement of wireless mesh *** standard uses a physical layer of binary phase-shift keying(BPSK)modulation and can be operated with two frequency bands,868 and 915 *** frequency noise could interfere with the BPSK signal,which causes distortion to the signal before its arrival at ***,filtering the BPSK signal from noise is essential to ensure carrying the signal from the sen-der to the receiver with less ***,removing signal noise in the BPSK signal is necessary to mitigate its negative sequences and increase its capability in industrial wireless sensor ***,researchers have reported a posi-tive impact of utilizing the Kalmen filter in detecting the modulated signal at the receiver side in different communication systems,including ***-while,artificial neural network(ANN)and machine learning(ML)models outper-formed results for predicting signals for detection and classification *** paper develops a neural network predictive detection method to enhance the performance of BPSK ***,a simulation-based model is used to generate the modulated signal of BPSK in the IEEE802.15.4 wireless personal area network(WPAN)***,Gaussian noise was injected into the BPSK simulation *** reduce the noise of BPSK phase signals,a recurrent neural networks(RNN)model is implemented and integrated at the receiver side to esti-mate the BPSK’s phase *** evaluated our predictive-detection RNN model using mean square error(MSE),correlation coefficient,recall,and F1-score *** result shows that our predictive-detection method is superior to the existing model due to the low MSE and correlation coefficient(R-value)metric for different signal-to-noise(SNR)*** addition,our RNN-based model scored 98.71%and 96.34%based on recall and F1-score,respectively.

关键词： Neural networks RNN BPSK phasedetection WPAN IEEE802.15.4 signal demodulation

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Predicting Violence-Induced Stress in an Arabic Social Media Forum

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Intelligent Automation & Soft Computing 2023年第2期35卷 1423-1439页

作者： Abeer abdulaziz AlArfaj Nada ali Hakami Hanan Ahmed Hosni Mahmoud Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Science College of Computer Science and Information TechnologyJazan UniversityJazanSaudi Arabia

Social Media such as Facebook plays a substantial role in virtual com-munities by sharing ideas and ideologies among different populations over *** interaction analysis aids in deﬁning people’s emotions and aids in assessing public attitudes,towards different issues such as violence against women and *** this paper,we proposed an Arabic language prediction model to identify the issue of Violence-Induced Stress in social *** searched for Arabic posts of many countries through Facebook application programming interface(API).We discovered that the stress state of a battered woman is usually related to her friend’s stress states on *** applied a large real database from Facebook platforms to analytically investigate the correlation of violence-induced stress states and the victim interactions on social *** extracted a set of tex-tual,spatial,and interaction attributes from various ***,we are proposing a hybrid model–an interaction graph model incorporated in a deep learning neural model to leverage post content and interaction data for vio-lence-induced stress *** depict that our proposed hybrid mod-el can enhance the prediction performance by 10%in ***,considering the user interaction information can learn an interesting phenomenon,where,the sparse social interactions of violence-induced stress stressed victims is higher by around 15%percent non-battered users,signifying that the structure of the friends of such victims is less connected than non-stressed users.

关键词： Arabic language analysis violence-induced stress detection hybrid model deep learning

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FlowBreakdown of Hybrid Nanofluid on a Rigid Surface with Power Law Fluid as Lubricated Layers

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Computer Modeling in Engineering & Sciences 2024年第2期138卷 1485-1499页

作者： Mirza Naveed Jahangeer Baig NadeemSalamat Sohail Nadeem NaeemUllah Mohamed Bechir Ben Hamida Hassan ali Ghazwani Sayed M.Eldin A.S.Al-Shafay Instituite of Mathematics Khwaja Fareed University of Engineering and Information TechnologyRahim yar Khan64200Pakistan Department of Mathematics Quaid-I-Azam UniversityIslamabad44000Pakistan Department of Mathematics Wenzhou UniversityWenzhou325035China College of Engineering Department of Mechanical EngineeringImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11564Saudi Arabia Research Laboratory of Ionized Backgrounds and Reagents Studies(EMIR) Preparatory Institute for Engineering Studies of Monastir(IPEIM)University of MonastirMonastir5060Tunisia Higher School of Sciences and Technology of Hammam Sousse Department of PhysicsJazan82511Kingdom of Saudia Arabia Department of Mechanical Engineering Faculty of engineeringJazan UniversityP.O.Box 45124JazanKingdom of Saudia Arabia Center of Research Faculty of EngineeringFuture University in EgyptNew Cairo11835Egypt Department of Mechanical Engineering College of EngineeringPrince Sattam bin Abdulaziz UniversityAlkharj16436Saudi Arabia

Thiswork investigates an oblique stagnation point flowof hybrid nanofluid over a rigid surface with power lawfluidas lubricated layers. Copper (Cu) and Silver (Ag) solid particles are used as hybrid particles acting in water H2O asa base fluid. The mathematical formulation of flow configuration is presented in terms of differential systemthat isnonlinear in nature. The thermal aspects of the flow field are also investigated by assuming the surface is a heatedsurface with a constant temperature T. Numerical solutions to the governing mathematical model are calculatedby the RK45 algorithm. The results based on the numerical solution against various flow and thermal controllingparameters are presented in terms of line graphs. The specific results depict that the heat flux increases over thelubricated-indexed parameter.

关键词： Oblique stagnation point flow hybrid nanofluid lubricated layer magnetohydrodynamics

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