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检索条件"任意字段=International Conference on Engineering of Reconfigurable Systems and Algorithms"

共 89784 条记录，以下是331-340 订阅

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A deep dive into building an ecommerce website using recommender systems 4th

A deep dive into building an ecommerce website using recomme...

引用

4th international conference on Computational Methods in Science and Technology, ICCMST 2024

作者： Rathore, Ashu Parshotam Shiwangi, Shreya Srivastava, Abhijeet Ranjan Nandan, Nand Murti, Srishti Computer Science and Engineering Lovely Professional University Punjab India

ISBN: (纸本)9781032911571

The shopping scenario of the contemporary world is filled with choices, empowering consumers but risking information overload. This paper explores user-based collaborative filtering and intelligent algorithms that create personalized shopping experiences as on user data. These systems assess user activity using filters according to content and machine learning to convert user data into personalized suggestions. The study investigates how these solutions might transform the consumer journey by reducing information overload and serving as digital guides across the complicated product environment. Also, the role of user-generated content in enhancing recommendation accuracy and increasing consumer confidence is investigated. This research also focuses on the potential approach for businesses. It investigates how consumer dispersion, guided by user-driven recommendation system data, may personalize the e-commerce experience. This insight enables organizations to strengthen consumer interactions and generate opportunities for growth in the e-commerce area. © 2025 the Author(s).

关键词： Marketplaces

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AI-Driven Personalized Dietary Recommendation System Leveraging Regional Cuisine 3

AI-Driven Personalized Dietary Recommendation System Leverag...

引用

3rd international conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Divya, J. Aakash, G. Bevincent Edward, E. St. Joseph’s College of Engineering Chennai India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527549

Diet related health issues are a growing concern, with individuals often struggling to make informed dietary choices. Existing dietary recommendation systems rarely include regional foods, making it difficult for users to access or prepare the recommended meals. Despite the availability of a diverse array of nutritious local foods, this gap necessitates the development of a system that provides culturally relevant and accessible dietary recommendations. In this project, an AI based dietary recommendation system is designed to cater to regional needs. Using machine learning algorithms, the system calculates daily caloric requirements based on factors such as age, BMI, and individual health goals. Personalized meal plans are generated from regional foods, ensuring they are culturally appealing, nutritionally balanced, and aligned with seasonal availability. The outcome of this research is to bridge the gap in existing systems by generating meal plans rooted in regional foods, empowering users to achieve healthier diets through accessible and culturally resonant recommendations. © 2025 IEEE.

关键词： Food ingredients

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A Novel Key Generation Algorithm Utilizing Lattice-Based Cryptography Principles 3rd

A Novel Key Generation Algorithm Utilizing Lattice-Based Cry...

引用

3rd international conference on Computing and Communication Networks, ICCCN 2023

作者： Arul, Rajakumar Sivaselvam, B. Choudhary, Ankush Centre for Smart Grid Technologies Vellore Institute of Technology Chennai India Department of Computer Science and Engineering IIITDM Kancheepuram Chennai India School of Computer Science and Engineering Vellore Institute of Technology Chennai India

ISBN: (纸本)9789819726707

Technology advancement is inevitable, and it has created a revolution in all the sectors creating huge opportunities. Artificial intelligence and machine learning have boosted the advancement of all the sectors making the life easier and comfortable. On the other hand, these advancements highly depend on the connectivity through which all the terminals are communicating. Thus, all the technology developments depend on the communication paradigm, particularly on the wireless medium. Securing the information and infrastructure is crucial, and it demands highly complex problems that cannot be breached with high computation machines like quantum computer. The emergence of quantum computer has made all the existing cryptographic algorithms vulnerable creating a space for advanced algorithms that are safe from quantum computer attacks. Key generation is the foundational process of any cryptographic algorithm, and in this research, we propose a novel key generation mechanism based on lattice using mathematical functions. The proposal is evaluated using theoretical assumptions, and it is found to be safe and secure. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Encryption algorithms

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Machine Learning in Healthcare: A Review of Applications, Opportunities and Challenges 2

Machine Learning in Healthcare: A Review of Applications, Op...

引用

2nd international conference on Machine Learning and Autonomous systems, ICMLAS 2025

作者： Thute, Trupti Saratkar, Saniya Chaudhari, Aarti Raut, Rohini Thakare, Gayatri Datta Meghe Institute of Higher Education and Research Faculty of Engineering and Technology Department of Artificial Intelligence and Data Science Maharashtra Wardha442001 India

ISBN: (纸本)9798331505745

This article explores the potential of machine learning (ML) in transforming healthcare. It provides an overview of ML and its various categories, highlighting how supervised and unsupervised learning algorithms can be utilized for tasks like disease diagnosis, treatment personalization, and resource allocation. The article delves into specific applications of ML in healthcare, including image analysis for early disease detection, visualization of complex medical data, and personalized medicine approaches. It further explores the exciting opportunities presented by ML, such as improved diagnostics and treatment, increased efficiency and cost reduction, and advancements in research and development. However, the article also acknowledges the challenges associated with implementing ML in healthcare, including data privacy concerns, real-time data requirements, and the complexity of certain models. Overall, the article emphasizes the multifaceted landscape of ML in healthcare, showcasing its potential to revolutionize the industry while acknowledging the hurdles that need to be addressed for successful integration. © 2025 IEEE.

关键词： Theranostics

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A Robust and Highly Accurate Super-Resolution Time Delay Estimation Method in the Underwater Acoustic Channel 24

A Robust and Highly Accurate Super-Resolution Time Delay Est...

引用

18th ACM international conference on Underwater Networks and systems, WUWNET 2024

作者： Wu, Jie Deng, Jinhao Cui, Hongyu Zhang, Ke Harbin Engineering University China

ISBN: (纸本)9798400711602

In the underwater acoustic (UWA) channel, the time-delay estimation is a critical issue in the underwater acoustic measurements, localization, detection, and so on. However, the available bandwidth of UWA signals is narrow, the delay estimation accuracy of conventional matched filtering method is limited. Many existing time-delay super-resolution estimation algorithms perform poorly due to high computational complexity and poor robustness. In this paper, a modified Hybrid-WRELAX method is proposed to deal with the above problem. By changing the initialization parameters and the convergence conditions of the cost function, the computational complexity of the algorithm is reduced, and using the multi-parameter data fusion method to improve the robustness in the actual experimental data processing. Numerical simulations show that the modified method can resolve multipath time delay less than 0.3 times the Rayleigh limit, and the delay estimation accuracy is close to the maximum likelihood estimation in the AWGN environment. Finally, the experimental data analysis is presented to demonstrate the usability of the proposed algorithm. © 2024 Copyright held by the owner/author(s).

关键词： Delay estimation

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Metrics-Based Refactoring Prediction Using Boosting Algorithm 5

Metrics-Based Refactoring Prediction Using Boosting Algorith...

引用

5th international conference on Emerging systems and Intelligent Computing, ESIC 2025

作者： Patnaik, Archana Padhy, Neelamadhab Kumar, Lov Panigrahi, Rasmita Giet University Department of Computer Science and Engineering Gunupur India Nit Kurukshetra Department of Computer Science and Engineering Kurukshetra India

ISBN: (纸本)9798331522100

Software quality enhancement can be done by identifying the refactoring scope of the existing open-source projects in real time. The refactoring mechanism alters the internal structure of the code base without changing the external result. Objectives: In this work, we have assured the project quality by considering different source code metrics as input that helps to evaluate the refactoring score. Methodology: Software metrics used are NOI, SLOC, LOC, WMC, and CCL are considered as input parameters and implemented five different types of boosting algorithms. Result Analysis: As there are many extra features, we have selected 20 relevant features out of 115 using Recursive Feature Elimination (RFE). It is observed that Extreme Gradient Boosting (XGB) is best suitable for identifying refactoring opportunities with an accuracy of 99%.Conclusion: A comparison of projects is performed and Titan projects highly required refactoring as it contains more dirty code. © 2025 IEEE.

关键词： Software quality

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Electric Vehicle Fault Battery Analyzer Using Internet of Things

Electric Vehicle Fault Battery Analyzer Using Internet of Th...

引用

2025 international conference on Multi-Agent systems for Collaborative Intelligence, ICMSCI 2025

作者： Kamatchi Kannan, V. Muniraj, C. Sankarganesh, R. Parimalsundar, E. Thrinath, B.V. Sai Ponmurugan, P. Knowledge Institute of Technology Salem India K.S.R. College of Engineering Tiruchengode India Mohan Babu University Tirupati India Chennai600078 India

ISBN: (纸本)9798331509828

This research work focuses on a comprehensive solution that evaluates and monitors the health of electric vehicle batteries in real time is the Internet of Things (IoT)-based Electric Vehicle (EV) Battery Fault Analyzer. A micro controller, an IoT module, sensors, a cloud platform, and a user interface are all included in the framework to facilitate efficient data collection, investigation, and client alerting. The core components are individual battery cell management and monitoring, a micro controller for data acquisition, and an Internet of Things module for seamless cloud connectivity. A few of the sensors that provide crucial information about the state of the battery include accelerometers, voltage, current, and temperature. After this, data has been securely transmitted, the condition of the battery is evaluated by fault detection algorithms and data analysis processes on a cloud platform. © 2025 IEEE.

关键词： Fault detection

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Design and Implementation of Adaptive Architecture for Complex algorithms

Design and Implementation of Adaptive Architecture for Compl...

引用

2024 international conference on Mechatronics and Intelligent Control, ICMIC 2024

作者： Zhu, Ping Zou, Weiming Lv, Pohua Shi, Jin Jiang, Xuetao Ma, Yirong Beijing Broad Network & Information Company Limited Beijing101111 China Beijing Tellhow Intelligent Engineering Company Limited Beijing101111 China

ISBN: (数字)9781510686847

ISBN: (纸本)9781510686830

Generally, large-scale or intelligent software development has the programming characteristics of complex algorithm, such as uncertain requirements, complex workflows, and frequent modifications. Under the constraint of limited perspective, studying progressive logic refinement and adaptive architecture have great significance for complex algorithm development. Starting from the analysis of the task characteristics, the big decision tree theory was proposed to solve complex algorithm development problems, and the methods for constructing, expanding, and running big decision trees were introduced. Focusing on the dynamic addition or modification of logic conditions, adaptive running mechanism, and running of big decision tree systems, this paper proposed the adaptive architecture and its implementation techniques. Taking the technique implementation of state monitoring and robust debugging as examples, the implementation methods of adaptive architecture were introduced. Finally, the future directions were summarized. © 2025 SPIE.

关键词： Program debugging

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A Comparative Analysis Between Support Vector Machine and Linear Regression for Improving Accuracy of Medal Tally in Asian Games

A Comparative Analysis Between Support Vector Machine and Li...

引用

2025 international conference on Multi-Agent systems for Collaborative Intelligence, ICMSCI 2025

作者： Muthulingam, Gurusigaamani Ayyanar Ponnuchamy, Kardeepa Kumar, Gulla Pavan Mahesh, Jalla Karthik, G.N.H.B. Krishna, J. Venkata Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Tamilnadu Krishnankoil India

ISBN: (纸本)9798331509828

Medal Prediction is a kind of art to predict the future champion with the aid of various past performing competitors. This prediction has so hard to find a world champion in terms of different categories of medals such as gold, silver, and bronze. The process and analysis function has efficiently evolved with the usage of Machine learning algorithms. Support Vector Machine (SVM) and Linear Regression (LR) are the best examples of deep machine learning approaches to improve the accuracy and efficacy of the proposed system. This proposed system has refined the accuracy difference between the SVM and LP with the high rate of datasets. The Global medal prediction has changed into more successful with the aid of two faces of machine learning processes. The various parameters of comparative studies have proven in an effective manner. © 2025 IEEE.

关键词： Support vector regression

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Performance Analysis of Multipath TCP Congestion Control algorithms 14

Performance Analysis of Multipath TCP Congestion Control Alg...

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14th IEEE international conference on Communication systems and Network Technologies, CSNT 2025

作者： Biswal, Subhra Priyadarshini Chatterjee, Akash Alanam, Khair Patel, Sanjeev Department of Computer Science and Engineering National Institute of Technology Rourkela Odisha 769008 India

ISBN: (纸本)9798331531935

In modern high-speed networks, providing reliable and high-quality Internet services is essential. However, maintaining consistent network performance in dynamic environments with varying scenarios presents significant challenges. To address these, Multipath TCP (Transmission Control Protocol) offers a viable solution by aggregating multiple network paths, resulting in improved bandwidth utilization, higher throughput, and reduced delay. This approach overcomes the limitations of traditional single-path TCP by enhancing responsiveness, friendliness, and reducing window oscillation. Moreover, MPTCP incorporates congestion control mechanisms that couple several subflows, ensuring efficient traffic distribution across multiple paths, thereby improving overall network performance and fairness. In this paper, we analyze the performance of LIA (Linked Increases Algorithm), OLIA (Opportunistic Linked Increases Algorithm), and BALIA (Balanced Linked Adaptation) congestion control algorithms using the ns-3 network simulator. The results show that BALIA achieves 21% higher throughput compared to LIA. © 2025 IEEE.

关键词： Transmission control protocol

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