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A Weighted multi-Layer Analytics Based model for Emoji Recommendation

Computers, materials & Continua 2024年第1期78卷 1115-1133页

作者： Amira m.Idrees abdul Lateef marzouq Al-Solami Faculty of Computers and Information Technology Future University in EgyptCairo11835Egypt Alkamil College of Science and Arts University of JeddahJeddah21959Saudi Arabia

The developed system for eye and face detection using Convolutional Neural Networks(CNN)models,followed by eye classification and voice-based assistance,has shown promising potential in enhancing accessibility for individuals with visual *** modular approach implemented in this research allows for a seamless flow of information and assistance between the different components of the *** research significantly contributes to the field of accessibility technology by integrating computer vision,natural language processing,and voice *** leveraging these advancements,the developed system offers a practical and efficient solution for assisting blind *** modular design ensures flexibility,scalability,and ease of integration with existing assistive ***,it is important to acknowledge that further research and improvements are necessary to enhance the system’s accuracy and ***-tuning the CNN models and expanding the training dataset can improve eye and face detection as well as eye classification ***,incorporating real-time responses through sophisticated natural language understanding techniques and expanding the knowledge base of ChatGPT can enhance the system’s ability to provide comprehensive and accurate ***,this research paves the way for the development of more advanced and robust systems for assisting visually impaired *** leveraging cutting-edge technologies and integrating them into amodular framework,this research contributes to creating a more inclusive and accessible society for individuals with visual *** work can focus on refining the system,addressing its limitations,and conducting user studies to evaluate its effectiveness and impact in real-world scenarios.

关键词： Social networks text analytics emoji prediction features extraction information retrieval

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Acceleration of solar wind particles due to inertial Alfvén waves

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Communications in Theoretical Physics 2024年第6期76卷 137-141页

作者： Kiran Batool Imran A Khan m Shamir abdul Kabir S Ayaz Theoretical Physics Department National Centre for PhysicsIslamabad 44000Pakistan Department of Space Sciences Institute of Space TechnologyIslamabad 44000Pakistan Space and Astrophysics Research Lab(SARL) National Center of GIS and Space Applications(NCGSA)Islamabad 44000Pakistan Salam Chair Department of PhysicsGC University LahoreKatchery RoadLahorePunjab 54000Pakistan Department of Space Science and CSPAR University of Alabama in HuntsvilleHuntsvilleAL 35899United States of America

Gaining an understanding of the effects and dynamics of the solar wind is crucial for the study of space weather,Earth's magnetosphere,spacecraft protection,the dynamics of the Solar System,and various other *** show that Alfvén waves effectively transfer energy to resonant *** study demonstrates how inertial Alfvén waves deliver their energy to resonant plasma particles in different solar environments under certain *** analysis shows that inertial Alfvén waves experience more rapid damping with increasing parallel wavenumber,ambient magnetic field strength,and particle number density,coupled with a decrease in *** rate of energy transfer to resonant particles intensifies with higher temperatures and reduced parallel wavenumber and particle number *** with higher initial velocities actively participate in Landau damping,especially in regions with a stronger ambient magnetic field.

关键词： solar wind inertial Alfven waves resonant particles

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Adaptable and Dynamic Access Control Decision-Enforcement Approach Based on multilayer Hybrid Deep Learning Techniques in BYOD Environment

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Computers, materials & Continua 2024年第9期80卷 4663-4686页

作者： Aljuaid Turkea Ayedh m Ainuddin wahid abdul wahab mohd Yamani Idna Idris Faculty of Computer Science and Information Technology Universiti MalayaKuala Lumpur50603Malaysia Faculty of Computer Science and Information Technology Shaqra UniversityShaqra11961Saudi Arabia Center for mobile Cloud Computing Faculty of Computer Science and Information TechnologyUniversiti MalayaKuala Lumpur50603Malaysia

Organizations are adopting the Bring Your Own Device(BYOD)concept to enhance productivity and reduce ***,this trend introduces security challenges,such as unauthorized *** access control systems,such as Attribute-Based Access Control(ABAC)and Role-Based Access Control(RBAC),are limited in their ability to enforce access decisions due to the variability and dynamism of attributes related to users and *** paper proposes a method for enforcing access decisions that is adaptable and dynamic,based on multilayer hybrid deep learning techniques,particularly the Tabular Deep Neural Network Tabular DNN *** technique transforms all input attributes in an access request into a binary classification(allow or deny)using multiple layers,ensuring accurate and efficient access *** proposed solution was evaluated using the Kaggle Amazon access control policy dataset and demonstrated its effectiveness by achieving a 94%accuracy ***,the proposed solution enhances the implementation of access decisions based on a variety of resource and user attributes while ensuring privacy through indirect communication with the Policy Administration Point(PAP).This solution significantly improves the flexibility of access control systems,making themmore dynamic and adaptable to the evolving needs ofmodern ***,it offers a scalable approach to manage the complexities associated with the BYOD environment,providing a robust framework for secure and efficient access management.

关键词： BYOD security access control access control decision-enforcement deep learning neural network techniques TabularDNN multilayer dynamic adaptable flexibility bottlenecks performance policy conflict

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Development of a Novel Noise Reduction Algorithm for Smart Checkout RFID System in Retail Stores

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Computers, materials & Continua 2024年第7期80卷 1277-1304页

作者： Shazielya Shamsul mohammed A.H.Ali Salwa Hanim abdul-Rashid Atef m.Ghaleb Fahad m.Alqahtani Department of mechanical Engineering Faculty of EngineeringUniversiti MalayaKuala Lumpur50603Malaysia Centre for Sustainable and Smart manufacturing(CSSm) Faculty of EngineeringUniversiti MalayaKuala Lumpur50603Malaysia Department of Industrial Engineering College of EngineeringAlfaisal UniversityRiyadh11533Saudi Arabia Department of Industrial Engineering College of EngineeringKing Saud UniversityP.O.Box 800Riyadh11421Saudi Arabia

This paper presents a smart checkout system designed to mitigate the issues of noise and errors present in the existing barcode and RFID-based systems used at retail stores’checkout *** is achieved by integrating a novel AI algorithm,called Improved Laser Simulator Logic(ILSL)into the RFID *** enhanced RFID system was able to improve the accuracy of item identification,reduce noise interference,and streamline the overall checkout *** potential of the systemfor noise detection and elimination was initially investigated through a simulation study usingmATLAB and ILSL ***,it was deployed in a small-scale environment to validate its real-world *** show that RFID with the proposed new algorithm ILSL and AI basket is capable of accurately detecting the related itemswhile eliminating noise originating fromunrelated objects,achieving an accuracy rate of 88%.

关键词： Smart checkout system RFID technology improved laser simulator logic(ILSL) reduce noise checkout process

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Radiative capture of proton through the ^(14)N(p,γ)^(15)O reaction at low energy

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Chinese Physics C 2024年第4期48卷 183-192页

作者： B.F.Irgaziev abdul Kabir Jameel-Un Nabi National University of Uzbekistan Tashkent 100174Uzbekistan Space and Astrophysics Research lab National Centre of GIS and Space ApplicationsDepartment of Space ScienceInstitute of Space TechnologyIslamabad 44000Pakistan University of wah Quaid AvenueWah Cantt 47040PunjabPakistan

The CNO cycle is the main source of energy in stars more massive than our *** process defines the energy production,the duration of which can be used to determine the lifetime of massive *** cycle is an important tool for determining the age of globular *** proton capture via p+^(14)N→^(15)O+γ,at energies of astrophysical interest,is an important process in the CNO *** this project,we apply a potential model to describe both non-resonant and resonant reactions in the channels where radiative capture occurs through electric E1 *** employed the R-matrix method to describe the ongoing reactions via m1 resonant transitions,when it was not possible to correctly reproduce the experimental data using the potential *** partial components of the astrophysical S-factor are calculated for all possible electric and magnetic dipole transitions in ^(15)*** linear extrapolated S-factor at zero energy(S(0))agrees well with earlier reported values for all transition types considered in this *** on the value of the total astrophysical S-factor,depending on the collision energy,we calculate the nuclear reaction rates for p+^(14)N→^(15)O+γ.The computed rates agree well with the results reported in the NACRE II Collaboration and most recent existing measurements.

关键词： CNO cycle potential model R-matrix method cross-section astrophysical S-factor nuclear rates.

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New soliton solutions of Dual mode Sawada Kotera equation using a new form of modified Kudryashov method and the finite difference method

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Journal of Ocean Engineering and Science 2024年第3期9卷 207-215页

作者： Khalid K.Ali m.S.mehanna Abdel-Haleem Abdel-Aty abdul-m.jid wa.wa. Department of mathematics Faculty of ScienceAl-Azhar UniversityNasr City 11884CairoEgypt Faculty of Engineering MTI UniversityCairoEgypt Department of Physics College of SciencesUniversity of BishaPO Box 344Bisha 61922Saudi Arabia Physics Department Faculty of ScienceAl-Azhar UniversityAssiut 71524Egypt Department of mathematics Saint Xavier UniversityChicagoIL 60655USA

In this article,we suggest a new form of modified Kudryashov’s method(NmK)to study the Dual-mode Sawada Kotera *** know very well that the more the solutions depend on many constants,the easier it is to study the model better by observing the change in the constants and what their impact is on the *** this point of view,we developed the modified Kudryashov method and put it in a general form that contains more than one controllable *** have studied the model in this way and presented figures showing the correctness of what we hoped to reach from the proposed *** addition to the results we reached,they were not sufficient,so we presented an extensive numerical study of this model using the finite differences *** also came up with the local truncation error for the difference scheme is h^(6) k^(2)(1+k^(2)).In addition,the analytical solutions we reached were compared with the numerical solutions,and we presented many forms that show that the results we reached are a clear contribution to this field.

关键词： Soliton solution A new form of analytical method Local truncation error Numerical solutions

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Gradient Optimizer Algorithm with Hybrid Deep Learning Based Failure Detection and Classification in the Industrial Environment

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Computer modeling in Engineering & Sciences 2024年第2期138卷 1341-1364页

作者： mohamed Zarouan Ibrahim m.mehedi Shaikh abdul Latif md.masud Rana 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 Nuclear Engineering King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Electrical and Electronic Engineering Rajshahi University of Engineering and TechnologyRajshahiBangladesh

Failure detection is an essential task in industrial systems for preventing costly downtime and ensuring the seamlessoperation of the system. Current industrial processes are getting smarter with the emergence of Industry ***, various modernized industrial processes have been equipped with quite a few sensors to collectprocess-based data to find faults arising or prevailing in processes along with monitoring the status of *** diagnosis of rotating machines serves a main role in the engineering field and industrial production. Dueto the disadvantages of existing fault, diagnosis approaches, which greatly depend on professional experienceand human knowledge, intellectual fault diagnosis based on deep learning (DL) has attracted the researcher’sinterest. DL reaches the desired fault classification and automatic feature learning. Therefore, this article designs a Gradient Optimizer Algorithm with Hybrid Deep Learning-based Failure Detection and Classification (GOAHDLFDC)in the industrial environment. The presented GOAHDL-FDC technique initially applies continuous wavelettransform (CWT) for preprocessing the actual vibrational signals of the rotating machinery. Next, the residualnetwork (ResNet18) model was exploited for the extraction of features from the vibration signals which are thenfed into theHDLmodel for automated fault detection. Finally, theGOA-based hyperparameter tuning is performedtoadjust the parameter valuesof theHDLmodel *** experimental result analysis of the GOAHDL-FD Calgorithm takes place using a series of simulations and the experimentation outcomes highlight the better resultsof the GOAHDL-FDC technique under different aspects.

关键词： Fault detection Industry 4.0 gradient optimizer algorithm deep learning rotating machineries artificial intelligence

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microalgae cultivation in photobioreactors: sustainable solutions for a greener future

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Green Chemical Engineering 2024年第4期5卷 418-439页

作者： Shaikh Abdur Razzak Khairul Bahar K.m.Oajedul Islam abdul Khaleel Haniffa mohammed Omar Faruque S.m.Zakir Hossain mohammad m.Hossain Chemical Engineering Department King Fahd University of Petroleum and Minerals Center for Refining and Advanced Chemicals King Fahd University of Petroleum & Minerals Department of Chemical Engineering University of Bahrain

microalgae cultivation in photobioreactors（PBRs） has emerged as a promising and sustainable approach to address various environmental and energy challenges, offering a multitude of benefits across diverse *** developments in microalgae cultivation in photobioreactors have contributed substantially to the development and optimization of sustainable bioprocesses. This review presents a comprehensive analysis of recent innovations and breakthroughs in the field of microalgae cultivation, with a specific focus on their application in photobioreactors, aimed at paving the way for a greener future. This study in-depth examines the advantages of microalgae cultivation in photobioreactors, concentrating on its effectiveness in wastewater treatment, CO2bioremediation, and the production of biofuels and high-value products. The review evaluates the effects of light,solar irradiation, temperature, nitrogen and phosphorus concentrations in culture media, CO2concentrations, and pH on microalgae growth performance, including specific growth and biomass productivity. The study also examines open systems like unstirred ponds, raceway ponds, and circular ponds and closed systems like horizontal tubular, vertical bubble-column, airlift, flat panel, and plastic-bag photobioreactors, comparing their pros and cons. To optimize microalgae cultivation, key factors in photobioreactor design, including photosynthetic efficiencies, light/dark（L/D） cycles, CO2concentrations, mass transfer, hydrodynamics behavior, and p H, are extensively investigated. In addition, the review outlines recent developments in large-scale photobioreactors and highlights the challenges and opportunities associated with photobioreactor scale-up and design parameter optimization, including genetic engineering and economic feasibility. This article is a vital resource for researchers, engineers, and industry professionals seeking sustainable bioprocesses and the application of microalgae-based technol

关键词： microalgae biomass CO 2 biofixation wastewater treatment Biofuel Photobioreactors

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Treadmill training in Parkinson's disease:possible role of prefrontal modifications in the improved cortical-subcortical network function

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Neural Regeneration Research 2024年第2期19卷 407-408页

作者： Hao Ding Amgad Droby abdul Rauf Anwar Jeffrey m.Hausdorff Bahman Nasseroleslami Anat mirelman Inbal maidan muthuraman muthuraman Department of Neurology University Hospital WürzburgWürzburgGermany Academic Unit of Neurology Trinity College Dublinthe University of DublinDublinIreland Department of Neurology Sackler Faculty of MedicineTel Aviv UniversityTel AvivIsrael Sagol School of Neuroscience Tel Aviv UniversityTel AvivIsrael Biomedical Engineering Centre UET Lahore(KSK Campus)LahorePakistan Laboratory for Early markers of Neurodegeneration(LEmON) Center for the Study of MovementCognitionand Mobility(CMCM)Neurological InstituteTel Aviv Sourasky Medical CenterTel AvivIsrael Department of Physical Therapy Sackler Faculty of MedicineTel Aviv UniversityTel AvivIsrael Rush Alzheimer’s Disease Center and Department of Orthopaedic Surgery Rush University Medical CenterChicagoILUSA

Parkinson’s disease(PD)is a complex neurodegenerative disorder characterized by a range of motor symptoms such as bradykinesia,resting tremor,rigidity,and postural instability,as well as non-motor symptoms,such as de... 详细信息

关键词： rigidity fatigue

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Artificial Intelligence:A new era for spatial modelling and interpreting climate-induced hazard assessment

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Geoscience Frontiers 2024年第4期15卷 1-13页

作者： Abhirup Dikshit Biswajeet Pradhan Sahar S.matin Ghassan Beydoun m.Santosh Hyuck-Jin Park Khairul Nizam abdul maulud Centre for Advanced modelling and Geospatial Information Systems(CAmGIS) School of Civil&Environmental EngineeringFaculty of Engineering and ITUniversity of Technology SydneyNSW 2007Australia Earth Observation Center Institute of Climate ChangeUniversiti Kebangsaan Malaysia43600 UKM BangiSelangorMalaysia Department of Energy and mineral Resources Engineering Sejong UniversityChoongmu-gwan209 Neungdong-roGwangjin-guSeoul 05006Republic of Korea School of Earth Sciences and Resources China University of Geosciences BeijingXueyuan RoadBeijing 100083China Department of Earth Sciences University of AdelaideAdelaideSouth AustraliaAustralia Faculty of Science Kochi UniversityKochi 780-8520Japan

The application of Artificial Intelligence in various fields has witnessed tremendous progress in the recent *** field of geosciences and natural hazard modelling has also benefitted immensely from the introduction of novel algorithms,the availability of large quantities of data,and the increase in computational *** enhancement in algorithms can be largely attributed to the elevated complexity of the network architecture and the heightened level of abstraction found in the network's later *** a result,AI models lack transparency and accountability,often being dubbed as"black box"*** AI(XAI)is emerging as a solution to make AI models more transparent,especially in domains where transparency is *** discussion surrounds the use of XAI for diverse purposes,as researchers explore its applications across various *** the growing body of research papers on XAI case studies,it has become increasingly important to address existing gaps in the *** current literature lacks a comprehensive understanding of the capabilities,limitations,and practical implications of *** study provides a comprehensive overview of what constitutes XAI,how it is being used and potential applications in hydrometeorological natural *** aims to serve as a useful reference for researchers,practitioners,and stakeholders who are currently using or intending to adopt XAI,thereby contributing to the advancements for wider acceptance of XAI in the future.

关键词： Artificial Intelligence Explainable AI(XAI) Climate change Spatial modelling Natural hazards

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