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Science China Mathematics 2024年第2期67卷 315-338页

作者： Shengda Zeng akhtar a.khan Stanislaw Migórski Guangxi Colleges and Universities Key Laboratory of Complex System Optimization and Big Data Processing Yulin Normal UniversityYulin 537000China Faculty of Mathematics and Computer Science Jagiellonian University in Krak´owKrak´ow 30348Poland Center for Applied and Computational Mathematics School of Mathematical SciencesRochester Institute of TechnologyRochesterNY 14623USA College of Sciences Beibu Gulf UniversityQinzhou 535000China

In this paper, we study a generalized quasi-variational inequality (GQVI for short) with twomultivalued operators and two bifunctions in a Banach space setting. A coupling of the Tychonov fixedpoint principle and the Katutani-Ky Fan theorem for multivalued maps is employed to prove a new existencetheorem for the GQVI. We also study a nonlinear optimal control problem driven by the GQVI and givesufficient conditions ensuring the existence of an optimal control. Finally, we illustrate the applicability of thetheoretical results in the study of a complicated Oseen problem for non-Newtonian fluids with a nonmonotone andmultivalued slip boundary condition (i.e., a generalized friction constitutive law), a generalized leak boundarycondition, a unilateral contact condition of Signorini’s type and an implicit obstacle effect, in which themultivalued slip boundary condition is described by the generalized Clarke subgradient, and the leak boundarycondition is formulated by the convex subdifferential operator for a convex superpotential.

关键词： generalized quasi-variational inequality existence theorem optimal control Kakutani-Ky Fan theorem Oseen problem non-Newtonian fluid nonmonotone slip boundary condition

AMachine Learning Approach to User Profiling for Data Annotation of Online Behavior

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Computers, Materials & Continua 2024年第2期78卷 2419-2440页

作者： Moona Kanwal Najeed Akhan Aftab a.khan Computer Science and Information Technology Department NED University of Engineering and TechnologyKarachiPakistan Computer Engineering Department Sir Syed University of Engineering and TechnologyKarachiPakistan College of Education Health and Human ServicesLongwood UniversityFarmvilleVAUSA

The user’s intent to seek online information has been an active area of research in user *** profiling considers user characteristics,behaviors,activities,and preferences to sketch user intentions,interests,and *** user characteristics can help capture implicit and explicit preferences and intentions for effective user-centric and customized content *** user’s complete online experience in seeking information is a blend of activities such as searching,verifying,and sharing it on social ***,a combination of multiple behaviors in profiling users has yet to be *** research takes a novel approach and explores user intent types based on multidimensional online behavior in information *** research explores information search,verification,and dissemination behavior and identifies diverse types of users based on their online engagement using machine *** research proposes a generic user profile template that explains the user characteristics based on the internet experience and uses it as ground truth for data *** feedback is based on online behavior and practices collected by using a survey *** participants include both males and females from different occupation sectors and different *** data collected is subject to feature engineering,and the significant features are presented to unsupervised machine learning methods to identify user intent classes or profiles and their *** techniques are evaluated,and the K-Mean clustering method successfully generates five user groups observing different user characteristics with an average silhouette of 0.36 and a distortion score of *** average is computed to identify user intent type *** user intent classes are then further generalized to create a user intent template with an Inter-Rater Reliability of 75%.This research successfully extracts different user types based on th

关键词： User intent cluster user profile online search information sharing user behavior search reasons

Magnesium-reinforced Electrospun Synthetic-polymer Nanofibers Designed for Promoting Tissue Growth

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Journal of Bionic Engineering 2024年第3期21卷 1412-1426页

作者： Muheeb Rafiq Anjum Hamid Rather Rumysa Saleem khan Taha Umair Wani Haseeb a.khan Abdullah S.Alhomida Faheem A.Sheikh Nanostructured and Biomimetic Lab Department of NanotechnologyUniversity of Kashmir HazratbalSrinagarJammu and Kashmir190006India Non-Clinical Evaluation Center Biomedical Research InstituteJeonbuk National University HospitalJeonjuJeollabuk-do54907South Korea College of Pharmacy and Research Institute of Pharmaceutical Sciences Gyeongsang National UniversityJinju52828South Korea Research Chair for Biomedical Applications of Nanomaterials Department of BiochemistryCollege of ScienceKing Saud UniversityRiyadh11451Saudi Arabia

The creation of 3D nanofibers offering desirable functions for bone regeneration is developed due to the latest improvisations to the electrospinning *** polymers are among the best choices for medical usage due to their lower costs,high tensile properties,and ease of spinnability compared to natural *** this communication,we report a series of interventions to polymers modified with Mg-based fillers for ideal tissue engineering *** literature survey indicated that these filler materials(e.g.,nano-sized particles)enhanced biocompatibility,antibacterial activity,tensile strength,and anti-corrosive *** review discusses electrospinning parameters,properties,and applications of the poly(ε-caprolactone),poly(lactic acid),poly(3-hydroxybutyric acid-co-3-hydroxy valeric acid),polyurethane,and poly(vinyl pyrrolidone)nanofibers when modified with Mg-based *** report encourages researchers to use synthetic polymers with Mg as fillers and validate them for tissue engineering applications.

关键词： Bone regeneration Magnesium Nanofibers Tissue engineering

A Systematic Literature Review of Machine Learning and Deep Learning Approaches for Spectral Image Classification in Agricultural Applications Using Aerial Photography

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Computers, Materials & Continua 2024年第3期78卷 2967-3000页

作者： Usman khan Muhammad Khalid khan Muhammad Ayub Latif Muhammad Naveed Muhammad Mansoor Alam Salman a.khan Mazliham Mohd Su’ud College of Computing and Information Sciences Karachi Institute of Economics and TechnologyKarachi75190Pakistan Faculty of Computing and Informatics(FCI) Multimedia UniversityCyberjaya63100Malaysia Faculty of Computing Riphah International UniversityIslamabad46000Pakistan Faculty of Engineering and Information Technology School of Computer ScienceUniversity of Technology SydneySydneyAustralia

Recently,there has been a notable surge of interest in scientific research regarding spectral *** potential of these images to revolutionize the digital photography industry,like aerial photography through Unmanned Aerial Vehicles(UAVs),has captured considerable *** encouraging aspect is their combination with machine learning and deep learning algorithms,which have demonstrated remarkable outcomes in image *** a result of this powerful amalgamation,the adoption of spectral images has experienced exponential growth across various domains,with agriculture being one of the prominent *** paper presents an extensive survey encompassing multispectral and hyperspectral images,focusing on their applications for classification challenges in diverse agricultural areas,including plants,grains,fruits,and *** meticulously examining primary studies,we delve into the specific agricultural domains where multispectral and hyperspectral images have found practical ***,our attention is directed towards utilizing machine learning techniques for effectively classifying hyperspectral images within the agricultural *** findings of our investigation reveal that deep learning and support vector machines have emerged as widely employed methods for hyperspectral image classification in ***,we also shed light on the various issues and limitations of working with spectral *** comprehensive analysis aims to provide valuable insights into the current state of spectral imaging in agriculture and its potential for future advancements.

关键词： Machine learning deep learning unmanned aerial vehicles multi-spectral images image recognition object detection hyperspectral images aerial photography

The Application of Artificial Intelligence in Alzheimer’s Research

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Tsinghua Science and Technology 2024年第1期29卷 13-33页

作者： Qing Zhao Hanrui Xu Jianqiang Li Faheem akhtar Rajput Liyan Qiao Faculty of Information Technology Beijing University of TechnologyBeijing 100124China School of Medicine Tsinghua UniversityBeijing 100084China Department of Computer Science Sukkur IBA UniversitySukkur 65200Pakistan Department of Neurology Tsinghua University Yuquan HospitalBeijing 100040China

Alzheimer's disease(AD)is an irreversible and neurodegenerative disease that slowly impairs memory and neurocognitive function,but the etiology of AD is still *** the explosive growth of electronic health data,the application of artificial inteligence(Al)in the healthcare setting provides excellent potential for exploring etiology and personalized treatment approaches,and improving the disease's diagnostic and prognostic *** paper first briefly introduces Al technologies and applications in medicine,and then presents a comprehensive review of Al in *** simple,it includes etiology discovery based on genetic data,computer-aided diagnosis(CAD),computer-aided prognosis(CAP)of AD using multi-modality data(genetic,neuroimaging and linguistic data),and pharmacological or non-pharmacological approaches for treating ***,some popular publicly available AD datasets are introduced,which are important for advancing Al technologies in AD ***,core research challenges and future research directions are discussed.

关键词： Alzheimer's disease artificial intelligence etiology discovery computer-aided diagnosis computer-aided prognosis treatment

Sentiment Analysis of Low-Resource Language Literature Using Data Processing and Deep Learning

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Computers, Materials & Continua 2024年第4期79卷 713-733页

作者： Aizaz Ali Maqbool khan Khalil khan Rehan Ullah khan Abdulrahman Aloraini Department of IT and Computer Science Pak-Austria Fachhochschule:Institute of Applied Sciences and TechnologyHaripur22620Pakistan Software Competence Center Hagenberg Softwarepark 32aHagenberg4232Austria Department of Computer Science School of Engineering and Digital SciencesNazarbayev UniversityAstana010000Kazakhstan Department of Information Technology College of ComputerQassim UniversityP.O.Box 1162BuraydahSaudi Arabia

Sentiment analysis, a crucial task in discerning emotional tones within the text, plays a pivotal role in understandingpublic opinion and user sentiment across diverse *** numerous scholars conduct sentiment analysisin widely spoken languages such as English, Chinese, Arabic, Roman Arabic, and more, we come to grapplingwith resource-poor languages like Urdu literature which becomes a challenge. Urdu is a uniquely crafted language,characterized by a script that amalgamates elements from diverse languages, including Arabic, Parsi, Pashtu,Turkish, Punjabi, Saraiki, and more. As Urdu literature, characterized by distinct character sets and linguisticfeatures, presents an additional hurdle due to the lack of accessible datasets, rendering sentiment analysis aformidable undertaking. The limited availability of resources has fueled increased interest among researchers,prompting a deeper exploration into Urdu sentiment analysis. This research is dedicated to Urdu languagesentiment analysis, employing sophisticated deep learning models on an extensive dataset categorized into fivelabels: Positive, Negative, Neutral, Mixed, and Ambiguous. The primary objective is to discern sentiments andemotions within the Urdu language, despite the absence of well-curated datasets. To tackle this challenge, theinitial step involves the creation of a comprehensive Urdu dataset by aggregating data from various sources such asnewspapers, articles, and socialmedia comments. Subsequent to this data collection, a thorough process of cleaningand preprocessing is implemented to ensure the quality of the data. The study leverages two well-known deeplearningmodels, namely Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), for bothtraining and evaluating sentiment analysis performance. Additionally, the study explores hyperparameter tuning tooptimize the models’ efficacy. Evaluation metrics such as precision, recall, and the F1-score are employed to assessthe effectiv

关键词： Urdu sentiment analysis convolutional neural networks recurrent neural network deep learning natural language processing neural networks

A novel fractional case study of nonlinear dynamics via analytical approach

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Applied Mathematics(A Journal of Chinese Universities) 2024年第2期39卷 276-290页

作者： Hassan khan Adnan khan Rasool Shah Dumitru Baleanu Department of Mathematics Abdul Wali khan UniversityMardan 23200Pakistan Department of Mathematics Faculty of Arts and SciencesCankaya UniversityAnkara 06530Turkey Institute of Space Sciences Magurele-BucharestRomania

The present work describes the fractional view analysis of Newell-Whitehead-Segal equations,using an innovative *** work is carried with the help of the Caputo operator of fractional *** analytical solutions of some numerical examples are presented to confirm the reliability of the proposed *** derived results are very consistent with the actual solutions to the problems.A graphical representation has been done for the solution of the problems at various fractional-order ***,the solution in series form has the desired rate of convergence and provides the closed-form *** is noted that the procedure can be modified in other directions for fractional order problems.

关键词： Homotopy Perturbation method Shehu transform Newell-Whitehead-Segel Equation Caputo operator

Tuning structural,electrical,dielectric and magnetic properties of Mg-Cu-Co ferrites via dysprosium(Dy^(3+))doping

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Journal of Rare Earths 2024年第1期42卷 137-146,I0005页

作者： Maria akhtar M.S.Hasan Nasir Amin N.A.Morley Muhammad Imran Arshad Department of Physics Government College UniversityFaisalabad38000Pakistan Department of Physics The University of Lahore53700Pakistan Department of Materials Science and Engineering The University of SheffieldS13JDUK Department of Physics&Astronomy University College LondonUK

In current research work,Dy3+substituted Mg0.5Cu0.25Co0.25Fe2-xDyxO4(0.0≤x≤0.04 with the step interval of 0.01)soft ferrites were synthesized by the sol-gel auto combustion *** prepared samples were characterized by the techniques using X-ray diffraction(XRD),scanning electron microscopy(SEM),energy dispersive X-ray spectroscopy(EDS),Fourier transform infrared(FTIR)spectroscopy,curre nt-voltage(Ⅰ-Ⅴ)measurement,LCR meter,vibrating sample magnetometer(VSM)and *** data reveal that the average crystallite size is 49.71 nm and the lattice constant is 0.83703 nm for sample x=*** non-uniform grain growth was demonstrated by micrographs and impurity-free elemental composition was observed from EDX *** DC resistivity has an increasing and decreasing trend in ferromagnetic and paramagnetic regions with an increase in ***,the high resistivity is observed with the order of 1010Ω·cm,and the activation energy is 0.944 eV for samples x=*** dielectric parameters including dielectric constant,dielectric losses,and impedance gradually decrease with the increase in frequency from 8 Hz to 8 *** minimum dielectric loss at high frequency is found for sample x=*** coercivity(Hc)and saturation magnetization(Ms)are found in the ranges of 520.82-544.02 Oe and 20.5841-21.1473 emu/g,*** observations confirm that dysprosium(x=0.03)doped MCC-soft ferrites may be applicable in transformer cores,microwave absorbance,and telecommunication devices.

关键词： Soft ferrites DC resistivity Dielectric loss Impedance Coercivity Rare earths

Electronic and thermoelectric properties of YbMg_(2)X_(2)(X=P,As,Sb,Bi)zintl compounds by first-principles method

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Journal of Rare Earths 2024年第1期42卷 147-154,I0006页

作者： Sajid khan Dil Faraz khan R.Neffati Tariq Usman Muhammad Waqar Ahsraf Shamim khan Saeed Ullah Jan G.Murtaza Department of Physics University of Science&Technology BannuBannu28100Pakistan Department of Physics Faculty of ScienceKing Khalid UniversityP.O.Box 9004AbhaSaudi Arabia Laboratoire de Physique de La Matiere Condensee Departement de PhysiqueFaculte des Sciences de TunisUniversite Tunis El ManarCampus Universitaire1060TunisTunisia Department of Physics Shaoxing UniversityShaoxing312000China Department of Mathematics&Natural Sciences Prince Mohammad Bin Fahd UniversityAlkhobar31952Saudi Arabia Materials Modeling Lab Department of PhysicsIslamia College Peshawar25120KhyberPakhtunkhwaPakistan

In this work the structural,electronic and thermoelectric properties of YbMg_(2)X_(2)(X=P,As,Sb,Bi)zintl compounds were investigated comprehensively using first principles *** electronic properties were studied using PBE GGA,TB-mBJ and hybrid(YS-PBE0)*** the structural parameters of optimized structures are in harmonious agreement to the available *** band structure study illustrates that the titled materials manifest metallic and semi metallic nature using PBE and TB-mBJ potentials while they show wide band gap semiconducting behavior by following hybrid(YS-PBE0)*** density of states(TDOS)and partial density of states(PDOS)were also calculated to glimpse the contribution of orbitals of atoms in the formation of *** properties were studied by using BoltzTraP2 code employed to *** get enormous values of Seebeck coefficient(S),power factor(PF)and thermoelectric figure of merit(ZT)for all the samples YbMg_(2)X_(2)(X=P,As,Sb,Bi),Moreover,the overwhelming transport properties for the titled compounds indicate the optimum level of carriers’concentration which pinpoints these materials to be better thermoelectrics in the 1-2-2 zintl family.

关键词： Zintl compounds Hybrid functional Band structure Thermoelectrics Rare earths

Performance of Text-Independent Automatic Speaker Recognition on a Multicore System

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Tsinghua Science and Technology 2024年第2期29卷 447-456页

作者： Rand Kouatly Talha Ali khan Faculty of Tech and Software Engineering University of Europe for Applied SciencesPotsdam 14469Germany

This paper studies a high-speed text-independent Automatic Speaker Recognition(ASR)algorithm based on a multicore system's Gaussian Mixture Model(GMM).The high speech is achieved using parallel implementation of the feature's extraction and aggregation methods during training and testing *** memory parallel programming techniques using both OpenMP and PThreads libraries are developed to accelerate the code and improve the performance of the ASR *** experimental results show speed-up improvements of around 3.2 on a personal laptop with Intel i5-6300HQ(2.3 GHz,four cores without hyper-threading,and 8 GB of RAM).In addition,a remarkable 100%speaker recognition accuracy is achieved.

关键词： Automatic Speaker Recognition(ASR) Gaussian Mixture Model(GMM) shared memory parallel programming PThreads OpenMP