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Radiative Flow of Ag-Fe_(3)O_(4)/Water Hybrid Nanofluids Induced by a Shrinking/Stretching Disk with Influence of Velocity and Thermal Slip Conditions

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computer Modeling in engineering & sciences 2025年第4期143卷 499-513页

作者： Muhammad Zubair Mustafa Sumera Dero Liaquat Ali Lund Mehboob Ul Hassan Umair Khan Institute of Mathematics and Computer Science University of SindhJamshoro Sindh76080Pakistan KCAMS Khairpur Mir’s Sindh Agriculture UniversityTandojam Sindh70060Pakistan Department of Economics College of Business AdministrationKing Saud UniversityRiyadh145111Saudi Arabia Department of Mathematics Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesSaveetha UniversityChennai602105India Department of Mathematics Faculty of ScienceSakarya UniversitySerdivan/Sakarya54050Turkey

This paper discusses the model of the boundary layer(BL)flow and the heat transfer characteristics of hybrid nanofluid(HNF)over shrinking/stretching *** addition,the thermal radiation and the impact of velocity and thermal slip boundary conditions are also *** considered hybrid nano-fluid contains silver(Ag)and iron oxide(Fe_(3)O_(4))nanoparticles dispersed in the water to prepare the Ag-Fe_(3)O_(4)/water-based hybrid *** requisite posited partial differential equations model is converted to ordinary differential equations using similarity *** a numerical solution,the shooting method in Maple is ***,the duality in solutions is achieved for both cases of the disk(stretching(λ>0)and shrinking(λ<0)).At the same time,a unique solution is observed for λ=*** solution is found for them at λ<λ_(c),whereas the solutions are split at the λ=λ_(c).Besides,the value of the λ_(c) is dependent on the φ_(hnf).Meanwhile,the values of f″(0)and -θ′(0)intensified with increasing φ_(hnf).Stability analysis has been applied using bvp4c in MATLAB software due to a dual ***,analysis shows that the first solution is stable and feasible *** the slip parameters,an increase in the velocity slip parameter increases the velocity and shear stress profiles while increasing the temperature profile in the first *** the rise in thermal slip parameter reduces the temperature profile nanoparticle volume fractions increase it.

关键词： Dual solutions slip and radiation hybrid nanofluid shrinking/stretching disk stability analysis

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Algorithmic Perspective of Strongly Possible Keys and Functional Dependencies

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Informatica (Slovenia) 2024年第4期48卷 507-512页

作者： Alattar, Munqath Sali, Attila ITRDC University of Kufa Iraq Alfréd Rényi Institute of Mathematics Budapest Hungary Department of Computer Science Budapest University of Technology and Economics Budapest Hungary

It is common to encounter missing values in database tables. For an incomplete table, a possible world can be obtained by replacing any missed value with a value from the attribute (infinite) domain. A possible key (possible functional dependency) is satisfied in an incomplete table"T" if there exists a possible world of"T" that satisfies the key (the functional dependency) constraint. If all possible worlds of"T" satisfy the key (functional dependency), then we say that"T" satisfies a certain key (functional dependency). The concept of strongly possible worlds was introduced recently that considers only the active domain (the set of values that are already appearing in each attribute in the table), in a way that a strongly possible world is obtained by replacing any missing value with a value from the corresponding attributes active domain. So, a strongly possible key spKey (functional dependency spFD) is satisfied by a table"T" if there exists a strongly possible world that satisfies the key (functional dependency). In this paper, we investigate the approximation measures of spKeys and spFDs when the strongly possible constraint is not satisfied by a given table. The measure g3 represent the ratio of the minimum number of tuples that need to be removed so that the table satisfies the constraint. We introduce a new measure g5, which is the ratio of the minimum number of tuples to be added to the table so the result satisfies the constraint. Where adding new tuples with new values will extend the active domain. We prove that g3 is an upper bound of g5 for a constraint in a table. Furthermore, g3 and g5 are independent of each other, where there exist tables of some large number of tuples that satisfy g3 − g5 = pq for any rational number 0 ≤ pq © 2024 Slovene Society Informatika. All rights reserved.

关键词： approximate dependencies approximate keys database key Functional dependencies missing values

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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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Registration of CT Images of Lung Using Fireworks Algorithm 1

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2nd International Conference on Human-Centric Smart Computing, ICHCSC 2023

作者： Nayak, Somen Mondal, Subhodip Obaid, Ahmed J. Department of Computer Application University of Engineering and Management Rajasthan Jaipur India Department of Computer Science and Engineering University of Engineering and Management Rajasthan Jaipur India Department of Computer Science and Mathematics Department of Computer Science University of Kufa Najaf Iraq

ISBN: (数字)9789819977116

ISBN: (纸本)9789819977109

The acquisition of medical images from various modalities can provide a number of practical challenges that can be addressed through medical image registration. Intensity-based registration methods, which are used in multi-modal registration, merge multiple images with the same content into a single representation by applying image transformation. It is essential to edit photographs as best as you can. It is highly important to improve the similarity measure between the various photographs. We introduce a new method for registering lung’s CT image affected with COVID-19 in this work since the image registration process is fundamentally an improvement problem. Lung computed tomography image registration is a technique for aligning pre- and post-contrast images for analysis the effect of COVID-19 virus in the lung. A meta-heuristics-based optimization technique called FWA-IATF was explored for registering lung CT images. Following that, the FWA-IATF algorithm successfully registers the images. The results of registration based on the FWA-IATF method and PSO approach are compared. The results indicate that the FWA-IATF-based registration methods outperform the PSO-based registration approach while registering lung CT images. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： COVID-19

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A Two-Step Modulus-Based Matrix Splitting Iteration Method Without Auxiliary Variables for Solving Vertical Linear Complementarity Problems

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Communications on Applied mathematics and Computation 2024年第4期6卷 2475-2492页

作者： Hua Zheng Xiaoping Lu Seakweng Vong School of Mathematics and Statistics Shaoguan UniversityShaoguan 512005GuangdongChina School of Computer Science and Engineering Macao University of Science and TechnologyMacaoChina Department of Mathematics University of MacaoMacaoChina

In this paper,a two-step iteration method is established which can be viewed as a generalization of the existing modulus-based methods for vertical linear complementarity problems given by He and Vong(***.134:108344,2022).The convergence analysis of the proposed method is established,which can improve the existing *** examples show that the proposed method is efficient with the two-step technique.

关键词： Vertical linear complementarity problem Modulus-based matrix splitting Two-step metho

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D2LFS2Net:Multi-class skin lesion diagnosis using deep learning and variance-controlled Marine Predator optimisation:An application for precision medicine

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CAAI Transactions on Intelligence Technology 2025年第1期10卷 207-222页

作者： Veena Dillshad Muhammad Attique Khan Muhammad Nazir Oumaima Saidani Nazik Alturki Seifedine Kadry Department of Computer Science HITEC UniversityTaxilaPakistan Department of Computer Science and Mathematics Lebanese American UniversityBeirutLebanon Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia Department of Electrical and Computer Engineering Lebanese American UniversityByblosLebanon

In computer vision applications like surveillance and remote sensing,to mention a few,deep learning has had considerable *** imaging still faces a number of difficulties,including intra-class similarity,a scarcity of training data,and poor contrast skin lesions,notably in the case of skin *** optimisation-aided deep learningbased system is proposed for accurate multi-class skin lesion *** sequential procedures of the proposed system start with preprocessing and end with *** preprocessing step is where a hybrid contrast enhancement technique is initially proposed for lesion identification with healthy *** of flipping and rotating data,the outputs from the middle phases of the hybrid enhanced technique are employed for data augmentation in the next ***,two pre-trained deep learning models,MobileNetV2 and NasNet Mobile,are trained using deep transfer learning on the upgraded enriched ***,a dual-threshold serial approach is employed to obtain and combine the features of both *** next step was the variance-controlled Marine Predator methodology,which the authors proposed as a superior optimisation *** top features from the fused feature vector are classified using machine learning *** experimental strategy provided enhanced accuracy of 94.4%using the publicly available dataset ***,the proposed framework is evaluated compared to current approaches,with remarkable results.

关键词： contrast enhancement deep learning dermoscopic images features optimization fusion skin cancer

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Arbitrary style transfer system with split-and-transform scheme

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Multimedia Tools and Applications 2024年第23期83卷 62497-62517页

作者： Tu, Ching-Ting Lin, Hwei Jen Tsai, Yihjia Lin, Zi-Jun Department of Applied Mathematics National Chung Hsing University Taichung Taiwan Department of Computer Science and Information Engineering Tamkang University New Taipei Taiwan

For the subject of arbitrary image style transfer, there have been some proposed architectures that directly compute the transformation matrix of the whitening and coloring transformation (WCT) to obtain more satisfactory transformation results. However, calculating the transformation matrix of WCT is time-consuming. Li et al. trained a linear transformation module to generate a WCT transformation matrix for any pair of images, i.e., content image and style image, to avoid complex calculations and improves time efficiency. In this work, we introduce a flexible arbitrary image style transfer framework based on the LST, which uses deep neural networks to train a linear transformation matrix as the standard matrix for WCT. For the first part, inverse relationship between the Whitening matrix and the Coloring matrix w.r.t. the same image is enforced during the training of the linear transformation matrix, so that the resulting matrix will be more accurate and closer to the standard matrix of WCT. For the second part, a split-and-transform scheme is proposed. Unlike LST, which transforms the block of feature maps as a whole, the split-and-transform scheme divides the feature block into several smaller blocks and transforms them individually, so that the transformation is more localized, and the more the number of divided blocks, the more localized. In addition, the proposed split-and-transform scheme allows users to determine the number of divided blocks to flexibly control the locality of the transformations. Experimental results demonstrate the effectiveness and flexibility of the proposed framework by the high-quality stylized images and adjustable balance between globality and locality of transformations. The use of the split-and-transform scheme can reduce the computational time while preserving or even improving the stylization results. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Linear transformations

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Problems in Video Conferencing-Mediated Teaching: Experiences of Three User Roles of a University in Bangladesh

Problems in Video Conferencing-Mediated Teaching: Experience...

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2024 International Conference on Advances in Computing, Communication, Electrical, and Smart Systems, iCACCESS 2024

作者： Mansoor, Nafees Rozario, Anatte Kibria, Muhammad Golam Khalid, Md Saifuddin University of Liberal Arts Department of Computer Science and Engineering Bangladesh Department of Applied Mathematics and Computer Science Kongens Lyngby Denmark

ISBN: (纸本)9798350350289

Video-conferencing systems (VCS) became a defacto tool for online and hybrid teaching during COVID-19 and the gradual return to physical classrooms. As part of the EdViCon Erasmus+ project, towards defining the scenarios for improving teaching with additional portable tools by university teachers, this study reports users' problems in the context of the University of Liberal Arts Bangladesh (ULAB). Classroom observations, problem-tree analysis, interviews, and focus-group discussions with academics, e-learning and IT consultants, and students provide different perspectives on the central problems, underlying causes, and the effects of VCS use during live teaching sessions. While teachers emphasized the lack of resources and technical barriers, students' problem statement focused on the reduced quality of interactions due to the differences between VCS-mediated and physical classrooms, and the IT & e-learning professionals emphasized technological issues (audio, tone, lack of facial expression etc.), lack of collaboration, and differences in expectations among participants. The central contribution of this paper is three diagrams showing problem tree analysis from the perspectives of the three roles. Each of the causes, effects, and problem statements will be considered as point-of-view statements for generating ideas for supporting hardware and software tools and training on technology and pedagogy, © 2024 IEEE.

关键词： Students

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Enhanced Cybercrime Detection on Twitter Using Aho-Corasick Algorithm and Machine Learning Techniques

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Informatica (Slovenia) 2024年第18期48卷 97-108页

作者： Rawat, Romil Raj, A. Samson Arun Chakrawarti, Rajesh Kumar Sankaran, Krishnan Sakthidasan Sarangi, Sanjaya Kumar Rawat, Hitesh Rawat, Anjali Department of Computer Science Engineering Shri Vaishnav Institute of Information Technology Shri Vaishnav Vidyapeeth Vishwavidyalaya Indore India Division of Computer Science and Engineering School of Computer Science and Technology Karunya Institute of Technology and Sciences Tamil Nadu Coimbatore India MP Indore India Department od Electronics and Communication Engeneering Hindustan Institute of Technology and Science Chennai India Department of Computer Science and Engineering Utkal University Bhubaneswar India Department of Business Management and Economics University of Extremadura Spain Department of Computer and Communication Technology University of Extremadura Spain

The proposed work objective is to adapt Online social networking (OSN) is a type of interactive computer-mediated technology that allows people to share information through virtual networks. The microblogging feature of Twitter makes cyberspace prominent (usually accessed via the dark web). The work used the datasets and considered the Scrape Twitter Data (Tweets) in Python using the SN-Scrape module and Twitter 4j API in JAVA to extract social data based on hashtags, which is used to select and access tweets for dataset design from a profile on the Twitter platform based on locations, keywords, and hashtags. The experiments contain two datasets. The first dataset has over 1700 tweets with a focus on location as a keypoint (hacking-for-fun data, cyber-violence data, and vulnerability injector data), whereas the second dataset only comprises 370 tweets with a focus on reposting of tweet status as a keypoint. The method used is focused on a new system model for analysing Twitter data and detecting terrorist attacks. The weights of susceptible keywords are found using a ternary search by the Aho-Corasick algorithm (ACA) for conducting signature and pattern matching. The result represents the ACA used to perform signature matching for assigning weights to extracted words of tweet. ML is used to evaluate Twitter data for classifying patterns and determining the behaviour to identify if a person is a terrorist. SVM (Support Vector Machine) proved to be a more accurate classifier for predicting terrorist attacks compared to other classifiers (KNN- K-Nearest Neighbour and NB-Naïve Bayes). The 1st dataset shows the KNN-Acc. -98.38% and SVM Accuracy as 98.85%, whereas the 2nd dataset shows the KNN-Acc. -91.68% and SVM Accuracy as 93.97%. The proposed work concludes that the generated weights are classified (cyber-violence, vulnerability injector, and hacking-for-fun) for further feature classification. Machine learning (ML) [KNN and SVM] is used to predict the occurrence and

关键词： Tweets

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Predicting Student Behavior Using a Neutrosophic Deep Learning Model

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Neutrosophic Sets and Systems 2025年 76卷 288-310页

作者： Shitaya, Ahmed Mohamed Wahed, Mohamed El Syed Abd El Khalek, Saied Helemy Ismail, Amr Shams, Mahmoud Y. Salama, A.A. Department of Mathematics and Computer Science Faculty of Science Port Said University Egypt Department of Computer Science Faculty of computer and information sciences Suez Canal University Egypt Department. of Communication and Computer Engineering Air Defense University Egypt Department of Cybersecurity College of Engineering and Information Technology Buraydah Private Colleges Buraydah51418 Saudi Arabia Faculty of Artificial Intelligence Kafrelsheikh University Kafrelsheikh33516 Egypt

We developed an information system using an object-oriented programming language and a distributed database (DDB) consisting of multiple interconnected databases across a computer network, managed by a distributed database management system (DDBMS) for easy access. An intelligent system was designed to assess the difficulty level of preliminary exams and select top-performing advanced students using a Neutrosophic Deep Learning Model. The dataset was randomly split into training (80%) and testing (20%) sets, and the model, trained with the Adam optimizer at a 0.001 learning rate over 50 epochs, incorporated early stopping based on validation loss. This system, implemented at a traditional Egyptian university, achieved a 95% accuracy in predicting student dropout. Student behavior, influenced by personal, environmental, and academic factors, is often evaluated subjectively, leading to inconsistent results. Traditional machine learning approaches struggle with the inherent uncertainty in behavioral data. To address this, we combined neutrosophic theory—a mathematical framework that accounts for truth, falsity, and indeterminacy—with deep learning, which excels at learning complex data relationships, to predict student outcomes such as dropout rates. Evaluating the model on student data, including attendance and grades, showed superior accuracy, achieving a determination coefficient of 0.95, demonstrating the approach's potential for identifying at-risk students and enabling targeted interventions. © 2025, University of New Mexico. All rights reserved.

关键词： Contrastive Learning

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