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Particuology 2024年第7期90卷 364-382页

作者： Barış Gürel Gülşah Karaca Dolgun Osman İpek ali Keçebaş Department of Mechanical Engineering Engineering FacultySüleyman Demirel UniversityÇünürIspartaTurkey Department of Energy systems Engineering Technology FacultyMuğla SıtkıKoçman UniversityKötekliMenteşeMuğlaTurkey

This study delves into the combustion behavior of various lignite types within a circulating fluidized bed boiler(CFBB),with a primary focus on the impact of different bed material sphericity ratios(0.5,0.7,and 0.9).Utilizing bed material with a sphericity ratio of 0.9 sourced from theÇan power plant and verified through experimentation,the research reveals several key ***,furnace temperatures tended to rise with higher sphericity ratios,albeit with variations between lignite types,particularly highlighting the complexity of this relationship in the case of GLI-Tunçbilek *** levels in the combustion chamber remained consistent across different sphericity ratios,indicating minimal influence on pressure *** combustion efficiency,especially at the bottom of the boiler,was observed at lower sphericity levels(0.5 and 0.7)forÇan lignite,as reflected in CO_(2) mole *** NO_(x) emissions generally decreased with lower sphericity,the sensitivity to sphericity varied by lignite type,with Ilgın lignite showcasing low NO_(x) but high sO_(2) emissions,underscoring the intricate interplay between lignite properties,sphericity,and ***,this study advances our understanding of CFBB combustion dynamics,offering insights valuable for optimizing performance and emissions control,particularly in lignite-based power.

关键词： Circulating fluidized bed boiler Computational particle fluid dynamics method Particle sphericity ratios NO_(x)and sO_(2)emissions Energy production efficiency

MV-Honeypot:security Threat Analysis by Deploying Avatar as a Honeypot in COTs Metaverse Platforms

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Computer Modeling in Engineering & sciences 2024年第10期141卷 655-669页

作者： Arpita Dinesh sarang Mohsen ali Alawami Ki-Woong Park sysCore Lab.(Convergence Engineering for Intelligent Drone) Sejong UniversitySeoul05006Republic of Korea Division of Computer Engineering Hankuk University of Foreign StudiesYongin-si17035Republic of Korea Department of Information security Sejong UniversitySeoul05006Republic of Korea

Nowadays,theuse of Avatars that are unique digital depictions has increased by users to access Metaverse—a virtual reality environment—through multiple devices and for various ***,the Avatar and Metaverse are being developed with a new theory,application,and design,necessitating the association of more personal data and devices of targeted users every *** Avatar and Metaverse technology explosion raises privacy and security concerns,leading to cyber ***-Honeypot,or Metaverse-Honeypot,as a commercial off-the-shelf solution that can counter these cyber attack-causing vulnerabilities,should be *** fill this gap,we study user’s engagements with Avatars in Metaverse,analyze possible security vulnerabilities,and create a model named simplified Avatar Relationship Association with Non-linear Gradient(sARANG)that draws the full diagram of infrastructure components and data flow through accessing Metaverse in this *** also determine the most significant threat for each component’s cyberattacks that will affect user data and *** a result,the commercial off-the-shelf(COTs)of the MV-Honeypot must be established.

关键词： Avatar metaverse cybersecurity cloud computing internet of things artificial intelligence security analysis

Multi-trial Vector-based Whale Optimization Algorithm

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Journal of Bionic Engineering 2024年第3期21卷 1465-1495页

作者： Mohammad H.Nadimi-shahraki Hajar Farhanginasab shokooh Taghian ali safaa sadiq seyedali Mirjalili Faculty of Computer Engineering Najafabad BranchIslamic Azad UniversityNajafabad***Iran Big Data Research Center Najafabad BranchIslamic Azad UniversityNajafabad***Iran Department of Computer science Nottingham Trent UniversityNottinghamNG118NSUK Centre for Artificial Intelligence Research and Optimisation Torrens UniversityBrisbane4006Australia

The Whale Optimization Algorithm(WOA)is a swarm intelligence metaheuristic inspired by the bubble-net hunting tactic of humpback *** spite of its popularity due to simplicity,ease of implementation,and a limited number of parameters,WOA’s search strategy can adversely affect the convergence and equilibrium between exploration and exploitation in complex *** address this limitation,we propose a new algorithm called Multi-trial Vector-based Whale Optimization Algorithm(MTV-WOA)that incorporates a Balancing strategy-based Trial-vector Producer(Bs_TVP),a Local strategy-based Trial-vector Producer(Ls_TVP),and a Global strategy-based Trial-vector Producer(Gs_TVP)to address real-world optimization problems of varied degrees of ***-WOA has the potential to enhance exploitation and exploration,reduce the probability of being stranded in local optima,and preserve the equilibrium between exploration and *** the purpose of evaluating the proposed algorithm's performance,it is compared to eight metaheuristic algorithms utilizing CEC 2018 test ***,MTV-WOA is compared with well-stablished,recent,and WOA variant *** experimental results demonstrate that MTV-WOA surpasses comparative algorithms in terms of the accuracy of the solutions and convergence ***,we conducted the Friedman test to assess the gained results statistically and observed that MTV-WOA significantly outperforms comparative ***,we solved five engineering design problems to demonstrate the practicality of *** results indicate that the proposed MTV-WOA can efficiently address the complexities of engineering challenges and provide superior solutions that are superior to those of other algorithms.

关键词： swarm intelligence algorithms Metaheuristic algorithms Optimization Engineering design problems Whale optimization algorithm

Robust Machine Learning Mapping of sEMG signals to Future Actuator Commands in Biomechatronic Devices

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Journal of Bionic Engineering 2024年第1期21卷 270-287页

作者： ali Nasr sydney Bell Rachel L.Whittaker Clark R.Dickerson John McPhee systems Design Engineering University of WaterlooWaterloo N2L 3G1Canada Kinesiology and Health sciences University of WaterlooWaterloo N2L3G3Canada

A machine learning model for regression of interrupted surface Electromyography(sEMG)signals to future control-oriented signals(e.g.,robot’s joint angle and assistive torque)of an active biomechatronic device for high-level myoelectric-based hierarchical control is proposed.A Recurrent Neural Network(RNN)was trained using output data,initially obtained from offline optimization of the biomechatronic(human–robot)device and shifted by the prediction *** input of the RNN consisted of interrupted sEMG signals(to mimic signal disconnections)and previous kinematic signals of the assistive *** RNN with a 0.1-s prediction horizon could predict the control-oriented joint angle and assistive torque with 92%and 86.5%regression accuracy,respectively,for the test *** proposed approach permits a fast,predictive,and direct estimation of control-oriented signals instead of an iterative process that optimizes assistive torque in the inverse dynamic simulation of a multibody human–robot *** with these interrupted input signals significantly improves the regression accuracy in the case of sEMG signal *** Robust Predictive Control-oriented Machine Learning(Robust-MuscleNET)model can support volitional high-level myoelectric-based control of biomechatronic devices,such as exoskeletons,prostheses,and assistive/resistive *** work should study the application to prosthesis control as well as the repeatability of the high-level controller with electrode *** low-level hierarchical controller that manages the human–robot interaction,the assistance/resistance strategy,and the actuator coordination should also be studied.

关键词： Myoelectric-based control-surface electromyography Machine learning Multibody system dynamics Exoskeleton Bionic

Boron Nitride-Integrated Lithium Batteries: Exploring Innovations in Longevity and Performance

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ENERGY & ENVIRONMENTAL MATERIALs 2024年第6期7卷 13-40页

作者： Angizi, shayan Alem, sayed ali Ahmad Torabian, Mahdi Khalaj, Maryam Golberg, Dmitri Pakdel, Amir McMaster Univ Dept Chem Engn 1280 Main St W Hamilton ON L8S 4L7 Canada Montan Univ Leoben Inst Chem Polymer Mat Otto Glockel Str 2 A-8700 Leoben Austria Politecn Milan Dept Chem Mat & Chem Engn Piazza Leonardo Vinci 32 I-20133 Milan Italy Northwestern Univ Dept Mat Sci & Engn Evanston IL 60208 USA Queensland Univ Technol QUT Ctr Mat Sci 2 George Brisbane Qld 4000 Australia Queensland Univ Technol QUT Sch Chem & Phys 2 George Brisbane Qld 4000 Australia Natl Inst Mat sci NIMs Res Ctr Mat Nanoarchitecton MANA Namiki 1 Ibaraki 3050044 Japan Univ Dublin Trinity Coll Dublin Dept Mech Mfg & Biomed Engn Dublin D02PN40 Ireland

The current global warming, coupled with the growing demand for energy in our daily lives, necessitates the development of more efficient and reliable energy storage devices. Lithium batteries (LBs) are at the forefront of emerging power sources addressing these challenges. Recent studies have shown that integrating hexagonal boron nitride (h-BN) nanomaterials into LBs enhances the safety, longevity, and electrochemical performance of all LB components, including electrodes, electrolytes, and separators, thereby suggesting their potential value in advancing eco-friendly energy solutions. This review provides an overview of the most recent applications of h-BN nanomaterials in LBs. It begins with an informative introduction to h-BN nanomaterials and their relevant properties in the context of LB applications. subsequently, it addresses the challenges posed by h-BN and discusses existing strategies to overcome these limitations, offering valuable insights into the potential of BN nanomaterials. The review then proceeds to outline the functions of h-BN in LB components, emphasizing the molecular-level mechanisms responsible for performance improvements. Finally, the review concludes by presenting the current challenges and prospects of integrating h-BN nanomaterials into battery research. Integrating h-BN into lithium batteries enhances safety, longevity, and mechanical integrity of battery components by mitigating dendritic growth and side reactions. Its high ionic and thermal conductivities improve lithium transference and heat management, enhancing performance and reliability. image

关键词： electrode electrolyte hexagonal boron nitride lithium battery separator METAL BATTERIEs H-BN ION BATTERIEs 2-DIMENsIONAL MATERIALs POLYMER ELECTROLYTE HIGH-TEMPERATURE ANODEs NANOsHEETs DENDRITE FUNCTIONaliZATION

Facial Image-Based Autism Detection:A Comparative study of Deep Neural Network Classifiers

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Computers, Materials & Continua 2024年第1期78卷 105-126页

作者： Tayyaba Farhat sheeraz Akram Hatoon sAlsagri Zulfiqar ali Awais Ahmad Arfan Jaffar Faculty of Computer science and Information Technology The Superior UniversityLahore54600Pakistan Intelligent Data Visual Computing Research(IDVCR) Faculty of Computer Science and Information TechnologyThe Superior UniversityLahore54600Pakistan Information systems Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh12571Saudi Arabia school of Computer science and Electronic Engineering(CsEE) University of EssexWivenhoe ParkColchesterCO43SQUK

Autism spectrum Disorder(AsD)is a neurodevelopmental condition characterized by significant challenges in social interaction,communication,and repetitive *** and precise AsD detection is crucial,particularly in regions with limited diagnostic resources like *** study aims to conduct an extensive comparative analysis of various machine learning classifiers for AsD detection using facial images to identify an accurate and cost-effective solution tailored to the local *** research involves experimentation with VGG16 and MobileNet models,exploring different batch sizes,optimizers,and learning rate *** addition,the“Orange”machine learning tool is employed to evaluate classifier performance and automated image processing capabilities are utilized within the *** findings unequivocally establish VGG16 as the most effective classifier with a 5-fold cross-validation ***,VGG16,with a batch size of 2 and the Adam optimizer,trained for 100 epochs,achieves a remarkable validation accuracy of 99% and a testing accuracy of 87%.Furthermore,the model achieves an F1 score of 88%,precision of 85%,and recall of 90% on test *** validate the practical applicability of the VGG16 model with 5-fold cross-validation,the study conducts further testing on a dataset sourced fromautism centers in Pakistan,resulting in an accuracy rate of 85%.This reaffirms the model’s suitability for real-world AsD *** research offers valuable insights into classifier performance,emphasizing the potential of machine learning to deliver precise and accessible AsD diagnoses via facial image analysis.

关键词： Autism Autism spectrum Disorder(AsD) disease segmentation features optimization deep learning models facial images classification

Photon orbits and phase transition for Letelier Ads black holes immersed in perfect fluid dark matter

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Chinese Physics C 2024年第6期48卷 247-259页

作者： Ashima sood Md sabir ali J.K.singh sushant G.Ghosh Department of Mathematics Netaji Subhas University of TechnologyNew Delhi-110078India Centre for Theoretical Physics Jamia Millia IslamiaNew Delhi 110025India Department of Physics Mahishadal Raj CollegePurba MedinipurWest Bengal721628India Institute of Theoretical Physics&Research Center of Gravitation Lanzhou UniversityLanzhou 730000China Key Laboratory of Quantum Theory and Applications of MoE Lanzhou UniversityLanzhou 730000China Lanzhou Center for Theoretical Physics&Key Laboratory of Theoretical Physics of Gansu Province Lanzhou UniversityLanzhou 730000China Astrophysics and Cosmology Research Unit School of MathematicsStatistics and Computer ScienceUniversity of KwaZulu-NatalPrivate Bag X54001Durban 4000South Africa

We obtain an exact solution for spherically symmetric Letelier Ads black holes immersed in perfect fluid dark matter(PFDM).Considering the cosmological constant as the positive pressure of the system and volume as its conjugate variable,we analyze the thermodynamics of our black holes in the extended phase *** to the background clouds of strings parameter(a)and the parameter endowed with PFDM(β),we analyze the Hawking temperature,entropy,and specific ***,we investigate the relationship between the photon sphere radius and phase transition for the Letelier Ads black holes immersed in *** the analysis,with a particular condition,non-monotonic behaviors are found between the photon sphere radius,impact parameter,PFDM parameter,temperature,and *** can regard the changes in both the photon sphere radius and impact parameter before and after phase transition as the order parameter;their critical exponents near the critical point are equal to the same value,1/2,similar to that in ordinary thermal *** indicates that a universal relation of gravity may exist near the critical point for a black hole thermodynamic system.

关键词： Ads black holes perfect fluid dark matter Letelier spacetime photon orbit extended phase space thermodynamics correlation of photon orbit and thermodynamics

Artificial Intelligence for Global Health: Difficulties and Challenges: A Narrative Review

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Open Journal of Epidemiology 2024年第1期14卷 122-130页

作者： Nazia s. sadat Maryam s. shuttari Mir sadat-ali Department of Applied Nutrition University of New England Portland USA Department of Us Consultancy for Applied Research Lombard USA Department of Haifa Medical Center AlKhobar Saudi Arabia

Global health (GH) aims to improve healthcare for all people on the planet and eradicate all avoidable diseases and deaths. The inception of Artificial Intelligence (AI) is innovating healthcare practices and improving patient outcomes by shuffling enormous volumes of health data—from health records and clinical studies to genetic information analyzing it much faster than humans. AI also helps in the improvement of medical imaging and medical diagnosis. There is an increased optimism regarding the use of applications of AI locally but can these facets be translated globally in the advancement and delivery of healthcare with the help of AI. At present majority of AI developments and applications in health care provide to the needs of developed countries and there is little effort to develop programs which could help to improve healthcare delivery globally. We performed this narrative review to assess the difficulties and discrepancies in implementing AI in global health delivery and find ways to improve.

关键词： Artificial Intelligence Global Health Implementation Pitfalls

A Game-Theoretic Approach to safe Crowd Evacuation in Emergencies

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Computers, Materials & Continua 2024年第4期79卷 1631-1657页

作者： Maria Gul Imran ali Khan Gohar Zaman Atta Rahman Jamaluddin Mir sardar Asad ali Biabani May IssaAldossary Mustafa Youldash Ashraf saadeldeen Maqsood Mahmud Asiya Abdus salam Dania Alkhulaifi Abdullah AlTurkey31Department of Computer science COMSATS University IslamabadAbbottabad CampusAbbottabad22010Pakistan Department of Computer science Abbottabad University of Science and TechnologyAbbottabad22010Pakistan Department of Computer science College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia science and Technology Unit Umm Al-Qura UniversityMakkah21955Saudi Arabia Deanship of scientific Research Umm Al-Qura UniversityMakkah21955Saudi Arabia Department of Computer Information systems College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Department of Computer Engineering College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Department of Computer science Faculty of Computer Science and Information TechnologyOmdurman Islamic UniversityOmdurman14415Sudan Business Analytic Program Department of Management and MarketingCollege of Business AdministrationUniversity of BahrainSakhir32038Bahrain

Obstacle removal in crowd evacuation is critical to safety and the evacuation system efficiency. Recently, manyresearchers proposed game theoreticmodels to avoid and remove obstacles for crowd evacuation. Game theoreticalmodels aim to study and analyze the strategic behaviors of individuals within a crowd and their interactionsduring the evacuation. Game theoretical models have some limitations in the context of crowd evacuation. Thesemodels consider a group of individuals as homogeneous objects with the same goals, involve complex mathematicalformulation, and cannot model real-world scenarios such as panic, environmental information, crowds that movedynamically, etc. The proposed work presents a game theoretic model integrating an agent-based model to removethe obstacles from exits. The proposed model considered the parameters named: (1) obstacle size, length, andwidth, (2) removal time, (3) evacuation time, (4) crowd density, (5) obstacle identification, and (6) route *** proposed work conducts various experiments considering different conditions, such as obstacle types, obstacleremoval, and several obstacles. Evaluation results show the proposed model’s effectiveness compared with existingliterature in reducing the overall evacuation time, cell selection, and obstacle removal. The study is potentially usefulfor public safety situations such as emergency evacuations during disasters and calamities.

关键词： safe crowd evacuation public safety emergency transition probability cooperation

Using the Hg_xMg_(1-x)Te ternary compound as a room temperature photodetector: The electronic structure, charge transport, and response function of the energetic electromagnetic radiation

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Chinese Physics B 2018年第5期27卷 143-149页

作者： ghasemi Hasan Mokhtari ali Department of Physics Faculty of SciencesShahrekord University

In the present work, firstly, a first-principles study of the structural, electronic, and electron transport properties of the HgxMg1-xTe（HMT） ternary compound is performed using the ABINIT package and the results are compared with Cd0.9Zn0.1 Te（CZT） as a current room-temperature photodetector. Next, the response functions of Hg0.6Mg0.4Te and Cd0.9Zn0.1Te under electromagnetic irradiation with 0.05 Me V, 0.2 MeV, 0.661 MeV and 1.33 MeV energies are simulated by using the MCNP code. According to these simulations, the Hg0.6Mg0.4Te ternary compound is suggested as a good semiconductor photodetector for use at room temperature.

关键词： band gap charge-carrier transport photodetector density functional theory