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Influence of Temperature-Dependent Thermophysical Properties of TiO2-SiO2-ZnO-Fe2O3/PAO Tetra-Hybrid Nanofluid along a Vertical Porous Surface with Suction

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Open Journal of Fluid Dynamics 2024年第3期14卷 123-146页

作者： Philip Iyiola Farayola Lateefat Olanike Aselebe Kafilat Adebimpe Salaudeen Saheed Dolapo Ogundiran Tajudeen Motunrayo Asiru Department of Mathematics and Computing Science Education Emmanuel Alayande University of Education Oyo Nigeria Department of General Studies Federal School of Surveying Oyo Nigeria Department of Pure and Applied Mathematics Ladoke Akintola University of Technology Ogbomoso Nigeria

The significance of the thermophysical properties of Tetra hybrid nanofluid in enhancing heat transmission in various applications like heat exchangers, automobiles, and solar storage cannot be overstated. These features can be tampered with when nanoparticles are been introduced into the base fluid to produce an improved heat carrier fluid for the system. This study investigates the impact of temperature-dependent properties on the movement of TiO2-SiO2-ZnO-Fe2O3/PAO Tetra hybrid nanofluid along a vertical porous surface with suction. The system of governing Partial Differential Equations (PDEs) was formulated and transformed into the system of coupled nonlinear third-order Ordinary Differential Equations (ODEs) by similarity techniques. The resulting ODEs were solved numerically using the shooting method and fourth order Runge-Kutta method with the aid of Maple 18.0 software. Using numerical and statistical methods, the study analyzes velocity, temperature profiles, skin friction coefficient, and Nusselt number. It was found that as the variable thermal conductivity parameter upsurges both the skin friction coefficient and Nusselt number intensify at the rate of 0.011697519 and 8.043581616 respectively. This study underscores the vital role of Tetra hybrid nanofluid’s thermophysical properties in improving heat transmission for diverse appli cations. By manipulating nanoparticles within the base fluid, the heat carrier fluid’s efficiency can be enhanced, critical for industries like automotive and enewable energy. These insights inform the design of more efficient heat exchange systems, advancing sustainability and performance in real-world scenarios.

关键词： Tetra Hybrid Nanofluid Shooting Technique Numerical Method Skin Friction Nusselt Number Thermophysical Properties

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OLBR: Optimization of Location-Based Routing Protocols in Vehicular Ad Hoc Networks

OLBR: Optimization of Location-Based Routing Protocols in Ve...

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Recent Innovation in Smart and Sustainable technology (ICRISST), International Conference on

作者： Thangam S M Vivek Srikar Reddy Karthik Ullas N Abdul Khadar Jilani K Venkatesh J Jesy Janet Kumari A Saleem Raja Dept. of Computer Science and Engineering Amrita School of Computing Bengaluru Amrita Vishwa Vidyapeetham India IT Department College of Computing and Information Sciences University of Technology and Applied Sciences-Shinas Sultanate of Oman

ISBN: (数字)9798350309140

ISBN: (纸本)9798350309157

The proposed work employs ns-3, SUMO, and NetAnim to create geographical routing in vehicular ad hoc networks (VANETs). The research attempts to assess the performance of three well-known protocols AODV, DSDV, and OLSR in VANET settings. Utilizing SUMO’s realistic mobility models and NS3’s simulation capabilities, the project simulates node communication, protocol behaviour, and vehicle movement. The main purpose is to know how well various routing techniques work in dynamic vehicular situations.

关键词： Technological innovation Roads Vehicular ad hoc networks Packet loss Routing Routing protocols Delays Vehicle dynamics AODV Optimization

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Reseed Skipping of Linear Congruential Generator for Multi-level Image Steganography Security of Financial Data

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SN Computer Science 2023年第2期4卷 124页

作者： Danso, Juliana Mantebea Missah, Yaw Marfo Gyamfi, Enoch Opanin Dankwa, Stephen Kwabena, Sarpong Department of Computer Science Kwame Nkrumah University of Science and Technology (KNUST) Kumasi Ghana School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China Department of Cyber Security and Computer Engineering Technology School of Computing and Information Sciences C.K. Tedam University of Technology and Applied Sciences Upper East Region Navrongo Ghana School of Automation Engineering University of Electronic Science and Technology of China Chengdu China

This paper proposed a multi-level image steganography model that integrates with image and plaintext encryption schemes. The model starts by partitioning the cover-image pixel positions into two regions of respective purposes, one is reserved to hold the data, and through the implementation of the dynamic difference expansion principle, the other sloughs some parts to the reserved region in responsive to the size of the data to embed. Continuously reseeding and initializing the parameter values of a Linear Congruential Generator (LCG), generate a set of random pixel positions as members of the reserved region. Before data embedding, the region reserved to hold the data as well as the data bits to embed, are then encrypted using AES with respective keys. Encryption keys are randomly generated using a Cryptographically Secure Pseudo-Random Number Generator (CSPRNG), the Fortuna algorithm. Multiplex security nature of using a randomization generator to reserve image region for encryption and encrypting plaintext data before performing steganography still ensures stability in computational complexities better than a logarithmic O(n log n). A visual inspection by evaluators who made 3000 choices to correctly differentiate stego images from its cover-images shows that only 47 choices were correct, 1884 choices were wrong, while 1069 choices were uncertain. An experiment shows an average Embedding Rates (ERs) of 0.00109 bpp and an average PSNR of 72. This concludes, as our integrated steganography and image encryption which implements the dynamic difference expansion principle, outputs encrypted stego mages that can deceive the naked human eyes into identifying them as rather cover-images, its embedding rate is faster (i.e. ER < 0.1), suitably good, and ensures better imperceptibility of cover-image alterations. When comparing these experimental results with existing methods, our proposed model shows significant competitiveness. We even show real-life scenarios on how this

关键词： AES encryption scheme Dynamic difference expansion principle Linear congruential generator Pseudo-random number generator Reserving room before encryption Steganography

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Krishi-Konect: Enhancing Agriculture with Crop Care Solutions

Krishi-Konect: Enhancing Agriculture with Crop Care Solution...

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Networking and Communications (ICNWC), International Conference on

作者： Prashant Tarushi Garg Shaji. K.A. Theodore Sivakumar M. Department of Networking and Communications College of Engineering and Technology SRM Institute of Science and Technology Kattankulathur. Chennai India College of Computing and Information Sciences University of Technology and Applied Sciences Sultanate of Oman

ISBN: (数字)9798350365269

ISBN: (纸本)9798350365276

Agricultural disease detection using convolutional neural networks enhances crop yield by providing early and accurate identification of diseases, mitigating crop losses and boosting productivity. While traditional machine learning techniques are still relevant, deep learning, particularly convolutional neural networks, demonstrates superior performance in image-based disease detection and classification tasks, contingent upon adequate data and computational *** objective of this research is to investigate and evaluate the effectiveness of deep learning techniques, particularly convolutional neural networks (CNNs), in the detection and classification of plant diseases using image-based analysis.

关键词： Smart agriculture Productivity Deep learning Plant diseases Plants (biology) Crops Soil

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applied Linguistics with Mixed Leader Optimizer Based English Text Summarization Model

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Intelligent Automation & Soft computing 2023年第6期36卷 3203-3219页

作者： Hala J.Alshahrani Khaled Tarmissi Ayman Yafoz Abdullah Mohamed Manar Ahmed Hamza Ishfaq Yaseen Abu Sarwar Zamani Mohammad Mahzari Department of Applied Linguistics College of LanguagesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Research Centre Future University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of English College of Science&HumanitiesPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

The term‘executed linguistics’corresponds to an interdisciplinary domain in which the solutions are identified and provided for real-time language-related *** exponential generation of text data on the Internet must be leveraged to gain knowledgeable *** extraction of meaningful insights from text data is crucial since it can provide value-added solutions for business organizations and *** Automatic Text Summarization(ATS)process reduces the primary size of the text without losing any basic components of the *** current study introduces an applied Linguistics-based English Text Summarization using a Mixed Leader-Based Optimizer with Deep Learning(ALTS-MLODL)*** presented ALTS-MLODL technique aims to summarize the text documents in the English *** accomplish this objective,the proposed ALTS-MLODL technique pre-processes the input documents and primarily extracts a set of ***,the MLO algorithm is used for the effectual selection of the extracted *** the text summarization process,the Cascaded Recurrent Neural Network(CRNN)model is exploited whereas the Whale Optimization Algorithm(WOA)is used as a hyperparameter *** exploitation of the MLO-based feature selection and the WOA-based hyper-parameter tuning enhanced the summarization *** validate the perfor-mance of the ALTS-MLODL technique,numerous simulation analyses were *** experimental results signify the superiority of the proposed ALTS-MLODL technique over other approaches.

关键词： Text summarization deep learning hyperparameter tuning applied linguistics multi-leader optimizer

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A Review of Effectiveness and Efficiency Methodology of Decision Support System for Selecting Suppliers 1

A Review of Effectiveness and Efficiency Methodology of Deci...

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1st International Conference on Computer Science and Emerging Technologies, CSET 2023

作者： Alzoubi, Sharaf Amayreh, Khalid Thaher Farea, Mazen Mohammed Baker El-Ebiary, Yousef A. Ahmad Saany, Syarilla Iryani Bisht, Neeraj Information Technology Department Jordan Irbid National University Faculty of Finance Science and Business Business Administration Department Jordan Al-Madinah International University Faculty of Finance & Administrative Sciences Malaysia UniSZA Faculty of Informatics and Computing Malaysia Birla Institute of Applied Sciences Bhimtal India

ISBN: (纸本)9798350341737

In today's highly competitive global business environment, effective supplier selection plays a crucial role in the success and sustainability of organizations. Decision Support Systems (DSS) have emerged as powerful tools to aid in this complex process by providing valuable insights and data-driven recommendations for selecting suppliers. This research paper presents a comprehensive review of the methodologies used to assess the effectiveness and efficiency of Decision Support Systems employed in supplier selection processes. The primary objective of this study is to evaluate and compare the various methodologies applied in Decision Support Systems, focusing on their effectiveness and efficiency in assisting decision-makers during supplier selection. The research critically analyzes a range of published literature, academic papers, and case studies to highlight the strengths and limitations of different DSS methodologies in this context. The paper commences by elucidating the fundamental concepts of supplier selection and the significance of Decision Support Systems in streamlining this multifaceted process. Subsequently, a systematic review of existing literature is conducted to identify the key methodologies employed in DSS frameworks. Furthermore, the research explores the novel integration of emerging technologies, such as Artificial Intelligence, Machine Learning, and Big Data analytics, within Decision Support Systems for supplier selection. This investigation aims to discern how these advanced techniques contribute to the enhancement of decision-making precision and the overall efficiency of the selection process. By critically analyzing and comparing the effectiveness and efficiency of various Decision Support System methodologies, this research seeks to provide valuable insights for both academics and practitioners in supply chain management. The findings of this study will enable decision-makers to make informed choices regarding the adoption and customiz

关键词： Decision support systems

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Churn Rate Prediction System using Logistic Regression, SVM, and Random Forest Models 2

Churn Rate Prediction System using Logistic Regression, SVM,...

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2nd IEEE Global Conference on Communications and Information Technologies, GCCIT 2024

作者： Jain, Paras Gupta, Vishan Kumar Pandey, Priyank Anupriya Ghai, Kapil Singh, Ajay Vit Bhopal University School of Computing Engineering and Artificial Intelligence Kothri Kalan MP Bhopal India Amity University Punjab Amity School of Engineering and Technology Punjab Mohali India Graphics Era Deemed to be University Department of Cse Dehradun India Graphic Era Hill University School of Computing Dehradun India Graphic Era Hill University Department of Chemistry Dehradun India Uttaranchal University School of Applied and Life Sciences Uttarakhand Dehradun248007 India

ISBN: (纸本)9798350388916

Customers are the life blood of any business, and their importance cannot be overstated. Customers are a business's primary source of revenue. Retaining and gaining new clients is crucial to profitability. Over time, repeat customers typically spend more, and gaining new customers is frequently more expensive than keeping current ones. Consequently, establishing a foundation of devoted clients might boost revenue. Without customers purchasing products or services, there would be no income to sustain the business operations or drive growth. It might have several detrimental implications, such as a decline in market share, loss of revenue, bad impact on staff morale, etc. To tackle this problem supervised learning algorithms are trained on historical data, where the input features and corresponding churn labels are known. The goal is to learn patterns from the data that can help and predict churn accurately for newly unseen data. These algorithms guarantee a high degree of accuracy when forecasting customer attrition, allowing businesses to precisely identify consumers who pose a danger. Businesses frequently use focused tactics, such as re-engagement campaigns with discounts or offers that are specifically catered to the requirements and interests of each churned consumer, to entice and re-engage these customers through individualized communication. © 2024 IEEE.

关键词： Random forests

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Improving Existing VANETs by Incorporating UAVS Using Ant Colony and PSO Algorithms

Improving Existing VANETs by Incorporating UAVS Using Ant Co...

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Data Engineering and Communication Systems (ICDECS), International Conference on

作者： S Thangam Aniket Dixit Alok Kumar Karn Arnav Thakur Cg Arunbalaji J Jesy Janet Kumari A. Saleem Raja Dept. of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India IT Department College of Computing and Information Sciences University of Technology and Applied Sciences-Shinas Sultanate of Oman

Vehicular Ad Hoc Networks (VANETs) are a type of wireless communication network that enable vehicles to communicate with each other and with roadside infrastructure in a peer-to-peer fashion; despite their vast applications, they come with several shortcomings. The key challenges in their real-world implementation include scalability, connectivity, and coverage issues. Unmanned Aerial Vehicles (UAVs), also known as drones, can complement existing VANETs in several ways to enhance their functionality and address some of their limitations. This paper studies the incorporation of UAVs in VANETs to overcome the challenges faced by the present networks. The approach is based on the dynamic deployment of UAVs in the most optimal positions, found by utilizing Particle Swarm Optimization (PSO) and Ant Colony algorithms which analyze the vehicle density, and previous coverage information in the network. The deployment of UAVs is intended to provide a seamless network coverage for ground vehicles. The impact of dynamic UAV mobility in communicating VANETs is comparatively studied. The simulation is done using Network Simulator-3 (NS3) simulator to evaluate the performance of 4 VANET protocols, AODV, DSR, OLSR, and DSDV, in terms of packet delivery ratio (PDR), Average End-to-End Delay, Throughput, Average Throughput per Packet, Packet Drop Rate, and Normalized Routing Load after incorporating the proposed modification designs. The paper concludes that the incorporation of Ant Colony is better suited to enhance VANETs than PSO.

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Adaptive Strategies for Scalable and Heterogeneous VANET Network

Adaptive Strategies for Scalable and Heterogeneous VANET Net...

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Intelligent Communication Technologies and Virtual Mobile Networks (ICICV), International Conference on

作者： S Thangam Priyanshu Jha Jawed Hawari Nabin Kumar Sah Nikunj Jain J Jesy Janet Kumari A.Saleem Raja Dept. of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India IT Department College of Computing and Information Sciences University of Technology and Applied Sciences Shinas Sultanate of Oman

Despite technological advancements, Vehicular Ad-hoc Networks (VANETs) continue to face challenges related to reliability and high-speed mobility. This study focuses on enhancing scalability, improving mobility, and addressing network heterogeneity in the context of data dissemination. Data dissemination involves the distribution or transmission of statistical data to users. Tools like NS3, SUMO utilizing OSM for realistic traffic simulations, MATLAB for Data Analysis and evaluation of various protocols like ADHOC, Dynamic Source Routing (DSR), Optimized Link State Routing Protocol (OLSR), Destination Sequenced Distance Vector Routing (DSDV). The research aimed to refine VANET simulations for effective decision making, as its primary objective data dissemination i.e. distribution or transmission of statistical data to users, forming the central focus of this investigation.

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Smart Traffic Management in Green VANETs: Ant-Inspired Routing Strategies with Local Search Optimization

Smart Traffic Management in Green VANETs: Ant-Inspired Routi...

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Recent Innovation in Smart and Sustainable technology (ICRISST), International Conference on

作者： Thangam S Jahnavi M Chandana K Dheeraj K J Jesy Janet Kumari A Saleem Raja Dept. Of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India IT Department College of Computing and Information Sciences University of Technology and Applied Sciences-Shinas Sultanate of Oman

ISBN: (数字)9798350309140

ISBN: (纸本)9798350309157

Green Vehicular Ad-hoc Networks (VANETs) are gaining significance in smart mobility because of growing concerns about the environment. The research introduces a novel method for managing traffic in such networks by combining ant-inspired routing methods with local search optimization approaches. The solution, which draws inspiration from the efficient path-finding abilities of ants, facilitates decentralized communication and sharing of traffic data among cars. It allows rapid adaptation to changing traffic circumstances and environmental elements. Local search optimization enhances routing decisions by considering the near vicinity of each vehicle. Extensive simulations demonstrate notable enhancements in traffic efficiency, decreased congestion, and improved energy conservation as compared to conventional routing methods. The suggested solutions also enhance the development of environmentally friendly and enduring transportation networks.

关键词： Technological innovation Costs Green products Energy conservation Vehicular ad hoc networks Transportation Routing Sustainable development Optimization Pattern matching

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