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A comprehensive study on the processing of Co:ZnO nanostructured ceramics:Defect chemistry engineering and grain growth kinetics

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Journal of Materials Science & Technology 2023年第7期138卷 221-232页

作者： R.T.da Silva J.M.Morbec g.rahman H.B.de Carvalho Universidade Federal de Ouro Preto-UFOP Ouro PretoMG 35400-000Brazil School of Chemical and Physical Sciences Keele UniversityKeele ST55BGUnited Kingdom Department of Physics Quaid-i-Azam UniversityIslamabad 45320Pakistan Universidade Federal de Alfenas-UNIFAL Alfenas 37130-000Brazi

In this report,we present a systematic study on the preparation of Co:ZnO ceramics via a standard solid-state route from different Co precursors(Co_(3)O_(4),CoO,and metallic Co)and atmospheres(O_(2)and Ar).Particular emphasis is given to defect chemistry engineering and the sintering growth ***-principles calculations based on density functional theory are employed to determine the formation en-ergy of the main point defects in ZnO and Co:ZnO *** on the theoretical results,a set of chemical reactions is *** microstructural characterization is also performed to determine the degree of Co incorporation into the ZnO *** samples prepared in Ar atmosphere and metal-lic Co present the highest Co solubility limit(lower apparent Co incorporation activation energy)due to the incongruent ZnO *** of the parameters of the sintering growth kinetics reveals that Co_(3)O_(4)is the best sintering additive to achieve larger grain sizes,and possible higher densi-ties,in both sintering atmospheres,while metallic Co is the best to achieve the smallest grain size with higher Co concentration and homogeneous spatial distribution for a subsequent reduction of *** results show that the sintering in O_(2)effectively promotes zinc vacancies in the ZnO structure,while the sintering in Ar promotes zinc interstitial *** findings contribute to understanding the preparation of Co-doped ZnO ceramics and the sintering growth kinetics,which may improve the state of the art in processing the material at both bulk and nanometric scales.

关键词： Multifunctionality Zinc oxide Defect engineering growth kinetics

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Optimizing BERT for Bengali Emotion Classification: Evaluating Knowledge Distillation, Pruning, and Quantization

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Computer Modeling in Engineering & Sciences 2025年第2期142卷 1637-1666页

作者： Md Hasibur rahman Mohammed Arif Uddin Zinnat Fowzia Ria Rashedur M.rahman Department of Electrical and Computer Engineering North South UniversityDhaka1229Bangladesh

The rapid growth of digital data necessitates advanced natural language processing(NLP)models like BERT(Bidi-rectional Encoder Representations from Transformers),known for its superior performance in text ***,BERT’s size and computational demands limit its practicality,especially in resource-constrained *** research compresses the BERT base model for Bengali emotion classification through knowledge distillation(KD),pruning,and quantization *** Bengali being the sixth most spoken language globally,NLP research in this area is *** approach addresses this gap by creating an efficient BERT-based model for Bengali *** have explored 20 combinations for KD,quantization,and pruning,resulting in improved speedup,fewer parameters,and reduced memory *** best results demonstrate significant improvements in both speed and *** instance,in the case of mBERT,we achieved a 3.87×speedup and 4×compression ratio with a combination of Distil+Prune+Quant that reduced parameters from 178 to 46 M,while the memory size decreased from 711 to 178 *** results offer scalable solutions for NLP tasks in various languages and advance the field of model compression,making these models suitable for real-world applications in resource-limited environments.

关键词： Bengali NLP black-box distillation emotion classification model compression post-training quantization unstructured pruning

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Modeling and Comprehensive Review of Signaling Storms in 3gPP-Based Mobile Broadband Networks:Causes,Solutions,and Countermeasures

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 123-153页

作者： Muhammad Qasim Khan Fazal Malik Fahad Alturise Noor rahman Department of Computer Science Iqra National UniversityPeshawar25000Pakistan Department of Cybersecurity College of ComputerQassim UniversityBuraydah52555Saudi Arabia Department of Computer Science and Engineering Al-Fayha CollegeAl Jubayl31961Saudi Arabia

Control signaling is mandatory for the operation and management of all types of communication networks,including the Third generation Partnership Project(3gPP)mobile broadband ***,they consume important and scarce network resources such as bandwidth and processing *** have been several reports of these control signaling turning into signaling storms halting network operations and causing the respective Telecom companies big financial *** paper draws its motivation from such real network disaster incidents attributed to signaling *** this paper,we present a thorough survey of the causes,of the signaling storm problems in 3gPP-based mobile broadband networks and discuss in detail their possible solutions and *** provide relevant analytical models to help quantify the effect of the potential causes and benefits of their corresponding *** important contribution of this paper is the comparison of the possible causes and solutions/countermeasures,concerning their effect on several important network aspects such as architecture,additional signaling,fidelity,etc.,in the form of a *** paper presents an update and an extension of our earlier conference *** our knowledge,no similar survey study exists on the subject.

关键词： Signaling storm problems control signaling load analytical modeling 3gPP networks smart devices diameter signaling mobile broadband data access data traffic mobility management signaling network architecture 5g mobile communication

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A Synergistic Multi-Attribute Decision-Making Method for Educational Institutions Evaluation Using Similarity Measures of Possibility Pythagorean Fuzzy Hypersoft Sets

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 501-530页

作者： Khuram Ali Khan Saba Mubeen Ishfaq Atiqe Ur rahman Salwa El-Morsy Department of Mathematics University of SargodhaSargodha40100Pakistan Department of Mathematics University of Management and TechnologyLahore54000Pakistan Department of Mathematics College of ScienceQassim UniversityBuraydah51452Saudi Arabia

Due to the numerous variables to take into account as well as the inherent ambiguity and uncertainty,evaluating educational institutions can be *** concept of a possibility Pythagorean fuzzy hypersoft set(pPyFHSS)is more flexible in this regard than other theoretical fuzzy set-like models,even though some attempts have been made in the literature to address such *** study investigates the elementary notions of pPyFHSS including its set-theoretic operations union,intersection,complement,OR-and *** results related to these operations are also modified for ***,the similarity measures between pPyFHSSs are formulated with the assistance of numerical examples and ***,an intelligent decision-assisted mechanism is developed with the proposal of a robust algorithm based on similarity measures for solving multi-attribute decision-making(MADM)problems.A case study that helps the decision-makers assess the best educational institution is discussed to validate the suggested *** algorithmic results are compared with the most pertinent model to evaluate the adaptability of pPyFHSS,as it generalizes the classical possibility fuzzy set-like theoretical ***,while considering significant evaluating factors,the flexibility of pPyFHSS is observed through structural comparison.

关键词： Hypersoft set Pythagorean fuzzy hypersoft set computational complexity multi-attribute decision-making optimization similarity measures uncertainty

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global Piecewise Analysis of HIV Model with Bi-Infectious Categories under Ordinary Derivative and Non-Singular Operator with Neural Network Approach

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 609-633页

作者： ghaliah Alhamzi Badr Saad TAlkahtani Ravi Shanker Dubey Mati ur rahman Department of Mathematics and Statistics College of ScienceImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh13318Saudi Arabia Department of Mathematics College of ScienceKing Saud UniversityRiyadh11989Saudi Arabia Department of Mathematics Amity School of Applied SciencesAmity University RajasthanJaipur302002India School of Mathematical Sciences Jiangsu UniversityZhenjiang212013China Department of Computer Science and Mathematics Lebanese American UniversityBeirut13-5053Lebanon

This study directs the discussion of HIV disease with a novel kind of complex dynamical generalized and piecewise operator in the sense of classical and Atangana Baleanu(AB)derivatives having arbitrary *** HIV infection model has a susceptible class,a recovered class,along with a case of infection divided into three sub-different levels or categories and the recovered *** total time interval is converted into two,which are further investigated for ordinary and fractional order operators of the AB derivative,*** proposed model is tested separately for unique solutions and existence on bi *** numerical solution of the proposed model is treated by the piece-wise numerical iterative scheme of Newtons *** proposed method is established for piece-wise derivatives under natural order and non-singular Mittag-Leffler *** cross-over or bending characteristics in the dynamical system of HIV are easily examined by the aspect of this research having a memory effect for controlling the said *** study uses the neural network(NN)technique to obtain a better set of weights with low residual errors,and the epochs number is considered *** obtained figures represent the approximate solution and absolute error which are tested with NN to train the data accurately.

关键词： HIV infection model qualitative scheme approximate solution piecewise global operator neural network

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Solid Waste Management:A MADM Approach Using Fuzzy Parameterized Possibility Single-Valued Neutrosophic Hypersoft Expert Settings

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 531-553页

作者： Tmader Alballa Muhammad Ihsan Atiqe Ur rahman Noorah Ayed Alsorayea Hamiden Abd El-Wahed Khalifa Department of Mathematics College of SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia 2 Department of Mathematics University of Management and TechnologyLahore54000Pakistan Department of Mathematics College of ScienceQassim UniversityBuraydah51452Saudi Arabia

The dramatic rise in the number of people living in cities has made many environmental and social problems *** search for a productive method for disposing of solid waste is the most notable of these *** scholars have referred to it as a fuzzy multi-attribute or multi-criteria decision-making problem using various fuzzy set-like approaches because of the inclusion of criteria and anticipated *** goal of the current study is to use an innovative methodology to address the expected uncertainties in the problem of solid waste site *** characteristics(or sub-attributes)that decision-makers select and the degree of approximation they accept for various options can both be indicators of these *** tackle these problems,a novel mathematical structure known as the fuzzy parameterized possibility single valued neutrosophic hypersoft expert set(ρˆ-set),which is initially described,is integrated with a modified version of Sanchez’s *** this,an intelligent algorithm is *** steps of the suggested algorithm are explained with an example that explains *** compatibility of solid waste management sites and systems is discussed,and rankings are established along with detailed justifications for their *** study’s strengths lie in its application of fuzzy parameterization and possibility grading to effectively handle the uncertainties embodied in the parameters’nature and alternative approximations,*** uses specific mathematical formulations to compute the fuzzy parameterized degrees and possibility grades that are missing from the prior *** is simpler for the decisionmakers to look at each option separately because the decision is *** the computed results,it is discovered that they are consistent and dependable because of their preferred properties.

关键词： Hypersoft expert set Sanchez’s method decision making optimization solid waste management possibility grade fuzzy parameterization

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Oversampling-Enhanced Feature Fusion-Based Hybrid ViT-1DCNN Model for Ransomware Cyber Attack Detection

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Computer Modeling in Engineering & Sciences 2025年第2期142卷 1667-1695页

作者： Muhammad Armghan Latif Zohaib Mushtaq Saifur rahman Saad Arif Salim Nasar Faraj Mursal Muhammad Irfan Haris Aziz Department of Computer and Information System Cleveland State UniversityOhio44115USA Department of Electrical Electronics and Computer SystemsCollege of Engineering and TechnologyUniversity of SargodhaSargodha40100Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Department of Mechanical Engineering College of EngineeringKing Faisal UniversityAl Ahsa31982Saudi Arabia Department of Mechanical Industrial and Energy System EngineeringUniversity of SargodhaSargodha40100Pakistan

Ransomware attacks pose a significant threat to critical infrastructures,demanding robust detection *** study introduces a hybrid model that combines vision transformer(ViT)and one-dimensional convolutional neural network(1DCNN)architectures to enhance ransomware detection *** common challenges in ransomware detection,particularly dataset class imbalance,the synthetic minority oversampling technique(SMOTE)is employed to generate synthetic samples for minority class,thereby improving detection *** integration of ViT and 1DCNN through feature fusion enables the model to capture both global contextual and local sequential features,resulting in comprehensive ransomware *** on the UNSW-NB15 dataset,the proposed ViT-1DCNN model achieved 98%detection accuracy with precision,recall,and F1-score metrics surpassing conventional *** approach not only reduces false positives and negatives but also offers scalability and robustness for real-world cybersecurity *** results demonstrate the model’s potential as an effective tool for proactive ransomware detection,especially in environments where evolving threats require adaptable and high-accuracy solutions.

关键词： Ransomware attacks cybersecurity vision transformer convolutional neural network feature fusion encryption threat detection

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Deep Learning and Artificial Intelligence-Driven Advanced Methods for Acute Lymphoblastic Leukemia Identification and Classification: A Systematic Review

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Computer Modeling in Engineering & Sciences 2025年第2期142卷 1199-1231页

作者： Syed Ijaz Ur rahman Naveed Abbas Sikandar Ali Muhammad Salman Ahmed Alkhayat Jawad Khan Dildar Hussain Yeong Hyeon gu Department of Computer Science Islamia CollegePeshawar25120Pakistan Department of Information Technology The University of HaripurHaripur22620Pakistan College of Technical Engineering The Islamic UniversityNajaf100986Iraq School of Computing Gachon UniversitySeongnam13120Republic of Korea Department of AI and Data Science Sejong UniversitySeoul05006Republic of Korea

Automatic detection of Leukemia or blood cancer is one of the most challenging tasks that need to be addressed in the healthcare *** of white blood cells(WBCs)in the blood or bone marrow microscopic slide images play a crucial part in early identification to facilitate medical *** Acute Lymphocytic Leukemia(ALL),the most preferred part of the blood or marrow is to be analyzed by the experts before it spreads in the whole body and the condition becomes *** researchers have done a lot of work in this field,to demonstrate a comprehensive analysis few literature reviews have been published focusing on various artificial intelligence-based techniques like machine and deep learning detection of *** systematic review has been done in this article under the PRISMA guidelines which presents the most recent advancements in this *** image segmentation techniques were broadly studied and categorized from various online databases like google Scholar,Science Direct,and PubMed as image processing-based,traditional machine and deep learning-based,and advanced deep learning-based models were *** Neural Networks(CNN)based on traditional models and then the recent advancements in CNN used for the classification of ALL into its subtypes.A critical analysis of the existing methods is provided to offer clarity on the current state of the ***,the paper concludes with insights and suggestions for future research,aiming to guide new researchers in the development of advanced automated systems for detecting life-threatening diseases.

关键词： Acute lymphoblastic bone marrow segmentation classification machine learning deep learning convolutional neural network

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A Comprehensive Survey on Federated Learning Applications in Computational Mental Healthcare

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 49-90页

作者： Vajratiya Vajrobol geetika Jain Saxena Amit Pundir Sanjeev Singh Akshat gaurav Savi Bansal Razaz Waheeb Attar Mosiur rahman Brij B.gupta Institute of Informatics and Communication University of DelhiDelhi110021India Maharaja Agrasen College University of DelhiDelhi110096India Computer Engineering Ronin InstituteMontclairNJ 07043USA Department of Research and Innovation Insights2TechinfoJaipur302001India University Centre for Research and Development(UCRD) Chandigarh UniversityChandigarh140413India Management Department College of Business AdministrationPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia CCRI&Department of Computer Science and Information Engineering Asia UniversityTaichung413Taiwan Symbiosis Centre for Information Technology(SCIT) Symbiosis International UniversityPune411057India Center for Interdisciplinary Research University of Petroleum and Energy Studies(UPES)Dehradun248007India

Mental health is a significant issue worldwide,and the utilization of technology to assist mental health has seen a growing *** aims to alleviate the workload on healthcare professionals and aid *** applications have been developed to support the challenges in intelligent healthcare ***,because mental health data is sensitive,privacy concerns have *** learning has gotten some *** research reviews the studies on federated learning and mental health related to solving the issue of intelligent healthcare *** explores various dimensions of federated learning in mental health,such as datasets(their types and sources),applications categorized based on mental health symptoms,federated mental health frameworks,federated machine learning,federated deep learning,and the benefits of federated learning in mental health *** research conducts surveys to evaluate the current state of mental health applications,mainly focusing on the role of Federated Learning(FL)and related privacy and data security *** survey provides valuable insights into how these applications are emerging and evolving,specifically emphasizing FL’s impact.

关键词： Depression emotional recognition intelligent healthcare systems mental health federated learning stress detection sleep behaviour

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Unveiling Effective Heuristic Strategies: A Review of Cross-Domain Heuristic Search Challenge Algorithms

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Computer Modeling in Engineering & Sciences 2025年第2期142卷 1233-1288页

作者： Mohamad Khairulamirin Md Razali MasriAyob Abdul Hadi Abd rahman Razman Jarmin Chian Yong Liu Muhammad Maaya Azarinah Izaham graham Kendall Faculty of Information Science and Technology Universiti Kebangsaan MalaysiaBangi43600SelangorMalaysia Center for Artificial Intelligence Technology Universiti Kebangsaan MalaysiaBangi43600SelangorMalaysia Faculty of Medicine Universiti Kebangsaan Malaysia Medical CentreCheras56000Kuala LumpurMalaysia School of Engineering and Computing MILA UniversityNilai71800Negeri SembilanMalaysia School of Computer Science University of Nottingham-Malaysia CampusSemenyih43500SelangorMalaysia

The Cross-domain Heuristic Search Challenge(CHeSC)is a competition focused on creating efficient search algorithms adaptable to diverse problem *** hyper-heuristics are a class of algorithms that dynamically choose heuristics during the search *** selection hyper-heuristics have different imple-mentation ***,comparisons between them are lacking in the literature,and previous works have not highlighted the beneficial and detrimental implementation methods of different *** question is how to effectively employ them to produce an efficient search ***,the algorithms that competed in the inaugural CHeSC have not been collectively *** work conducts a review analysis of the top twenty competitors from this competition to identify effective and ineffective strategies influencing algorithmic performance.A summary of the main characteristics and classification of the algorithms is *** analysis underlines efficient and inefficient methods in eight key components,including search points,search phases,heuristic selection,move acceptance,feedback,Tabu mechanism,restart mechanism,and low-level heuristic parameter *** review analyzes the components referencing the competition’s final leaderboard and discusses future research directions for these *** effective approaches,identified as having the highest quality index,are mixed search point,iterated search phases,relay hybridization selection,threshold acceptance,mixed learning,Tabu heuristics,stochastic restart,and dynamic *** are also compared with recent trends in *** work enhances the understanding of selection hyper-heuristics,offering valuable insights for researchers and practitioners aiming to develop effective search algorithms for diverse problem domains.

关键词： Hyper-heuristics search algorithms optimization heuristic selection move acceptance learning diversification parameter control

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