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2nd International Conference on Computational Intelligence, Communication Technology and Networking, CICTN 2025

作者： Rajput, Yashendra Razi, M.H. Sharma, Avinash Kumar Department of Computer Science Engineering Sharda University Greater Noida India

ISBN: (纸本)9798331530389

Software effort estimation is a vital component of project management, encompassing the prediction of time, cost, and resources necessary for software development. Accurate effort estimation plays a pivotal role in effective project planning, resource management, and budgeting within the realm of software engineering. However, software effort estimation is challenging due to project complexity, evolving requirements,and the unique nature of each development *** recent years, various machine learning techniques, including regression, fuzzy logic,support vector machines, decision trees, genetic algorithms,artificial neural networks, ensemble methods,clustering, K-nearest neighbors,logistic regression, random forests, and hybrid approaches-have been employed to improve estimation accuracy. This research delivers a comparative evaluation of these machine learning methods, considering performance metrics such as mean absolute error,accuracy, root mean square error, mean relative error, usability, and *** attention is given to ensemble methods, which often outperform individual models in *** findings offer guidance for researchers and practitioners in selecting optimal machine learning techniques for software effort estimation, ultimately enhancing tool development and modeling accuracy for sustainable software development. © 2025 IEEE.

关键词： Budget control

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Music Recommendation System using Python 4

Music Recommendation System using Python

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4th International Conference on Technological Advancements in Computational sciences, ICTACS 2024

作者： Ranjan, Mihir Kumar Thakur, Manikant Sharma, Aman Dhanda, Namrata Amity University Department of Computer Science & Engineering Lucknow India

ISBN: (纸本)9798350387490

Currently, music streaming networks require recommendation algorithms for helping consumers find new music that meets their preferences. Python is preferred by developers because it offers great potential and numerous platforms for building such kinds of systems. One of the most common techniques used to build recommendation system, particularly that for music, is collaborative filtering, a technique which makes individual recommendations based on analysis of the users' behavior and there preferences. The processing and analyzing of user interactions large datasets of music can be done more as easy due to the strong data manipulation that are offered from the packages of Python as Pandas and NumPy as well as Scikit-Iearn. Another crucial factor about music recommendation systems is content based filtering, a method that implies the song recommending according to features such as song genre, tempo, instrumental or vocal and the artist. To fetch Information about music and songs, features which are available from music streaming services like spotify or directly from a music file use spotipy and librosa packages in python. This is true because several machine learning steps are available to enhance the suggestion accuracy. The recommendation models, including neural networks may be developed and trained with simplicity using the Python-based TensorFlow and PyTorch. Streamlit is a machine learning web application framework developed in python which might be used to create musical recommendation systems with graphical interface. These tools and libraries can be used to build very efficient and engaging music recommendation systems that enhances the consumers music listening experience by developers. © 2024 IEEE.

关键词： Python

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Three Eyed Raven: An On-Chip Side Channel Analysis Framework for Run-Time Evaluation

Three Eyed Raven: An On-Chip Side Channel Analysis Framework...

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2025 Design, Automation and Test in Europe Conference, DATE 2025

作者： Dhilipkumar, M. Bagade, Priyanka Roy, Debapriya Basu Indian Institute of Technology Department of Computer Science & Engineering Kanpur India

ISBN: (纸本)9783982674100

Side-channel attacks exploit the physical leakages from hardware components, such as power consumption, to break secure cryptographic algorithms and retrieve their secret key. Evaluating implementations of cryptographic algorithms against such analysis is crucial but traditional frameworks require expensive external devices like oscilloscopes, making the process expensive and time-consuming. Recent advancements in on-chip sensors offer a cost-effective, fully on-chip SCA framework, eliminating the need for external devices. In this paper, we propose Raven, an on-chip SCA framework with hardware implementations of Test Vector Leakage Assessment (TVLA), Correlation Power Analysis (CPA), and Deep Learningbased Leakage Assessment (DL-LA), for run-time evaluation of cryptographic implementations. RAVEN leverages on-chip sensors to efficiently assess side-channel security, without requiring any external measurement devices or any customized evaluation platform. Our proposed hardware implementations of TVLA, CPA, and DL-LA are lightweight and the entire architecture including the sensors can fit within the lightweight and low-cost AMD-Xilinx PYNQ FPGA platform. The proposed framework is verified on an FPGA implementation of AES-128 and the corresponding result of TVLA, CPA, and DL-LA closely matches with these algorithm's software implementation while requiring significantly less time and storage. © 2025 EDAA.

关键词： Leak detection

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Unlocking the Potential of Virtual Pet Ownership - The Impact of Blockchain and Web3 3

Unlocking the Potential of Virtual Pet Ownership - The Impac...

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3rd IEEE International Conference on Intelligent Techniques in Control, Optimization and Signal Processing, INCOS 2024

作者： Godha, Rohan Singh, Kunal Devi, Priyanka Bhardwaz, Saumyamani Chandigarh University Department of Computer Science and Engineering Mohali India

ISBN: (纸本)9798350361186

Virtual pet ownership has witnessed significant advancements with the emergence of blockchain and Web3 technology. This research paper delves into the transformative impact of integrating blockchain in virtual pet platforms, focusing on the case study of Meta-Pet. Through a comprehensive literature review and critical analysis of 17 relevant papers, this study examines the potential of decentralized technology in redefining ownership, care, and trading mechanisms for digital pets. The methodology involves a detailed exploration of the implementation process, followed by a thorough analysis of the implications and challenges associated with the adoption of blockchain and Web3 in the Meta-Pet platform. The findings underscore the enhanced user engagement and the potential for fostering trust and transparency in virtual pet communities. The research highlights the significance of this integration and provides insights into the future-prospects of blockchain and Web3 in the virtual pet landscape. © 2024 IEEE.

关键词： Blockchain

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Detection and Navigation of Unmanned Vehicles in Wooded Environments Using Light Detection and Ranging Sensors

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Sensors and Materials 2023年第11期35卷 3637-3654页

作者： Zhang, Zhiwei Jhang, Jyun-Yu Lin, Cheng-Jian School of Electronic Information Engineering Hebei University of Technology Tianjin300401 China Department of Computer Science and Information Engineering National Taichung University of Science and Technology Taichung404 Taiwan Department of Computer Science & Information Engineering National Chin-Yi University of Technology Taichung411 Taiwan

With the advancement of automatic navigation, navigation control has become an indispensable core technology in the movement of unmanned vehicles. In particular, research on navigation control in outdoor wooded environments, which are more complex, less controlled, and more unpredictable than indoor environments, has received widespread attention. To realize the movement control and obstacle avoidance of unmanned vehicles in unknown environments, in this study, we use light detection and ranging (LiDAR) sensors to sense the surrounding environment. By plane meshing the point cloud reflected from LiDAR, we can instantly establish feasible regions. At the same time, using the artificial potential field algorithm, a stable obstacle avoidance and navigation path is planned for use in an unknown environment. In an actual woods navigation experiment to evaluate our proposed LiDAR detection method, we used an independently developed unmanned vehicle with Ackermann steering geometry. Experimental results indicate that the proposed method can effectively detect obstacles. The accuracy requirement is within 30 cm from the navigation target, and the experimental results show that the average navigation success rate of the proposed method is as high as 85%. The experimental results demonstrate that the system can stably and safely navigate in scenarios with different unknown environments. © MYU K.K.

关键词： Navigation

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The Role of Features in Image Retrieval System: A Survey

The Role of Features in Image Retrieval System: A Survey

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2025 International Conference on Visual Analytics and data Visualization, ICVADV 2025

作者： Gowmari, M. Murugeswari, G. Venkatalakshmi, K. Manonmaniam Sundaranar University Department of Computer Science and Engineering Tirunelveli India

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521394

In recent years, digital images have gained a significant role through the growth of computer technology and multimedia information systems. Image retrieval systems assist in retrieving images similar to query images from vast databases. However, retrieving similar images from a large database remains a challenging task, highlighting the demand for successful image retrieval techniques. The effectiveness of such systems depends on the features and techniques employed for retrieval. In this paper, the existing works on image retrieval systems are analyzed and present a survey addressing three key aspects: features, datasets, and performance metrics. The features used in image retrieval systems are discussed under various categories, including Content Based Image Retrieval (CBIR), Text Based Image Retrieval (TBIR), and Semantic Based Image Retrieval (SBIR) systems. Additionally, the datasets utilized for image retrieval and the performance metrics used to evaluate these systems are also presented. © 2025 IEEE.

关键词： Content based retrieval

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Energy Efficiency Techniques in 5G/6G Networks: Green Communication Solutions 2nd

Energy Efficiency Techniques in 5G/6G Networks: Green Commun...

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2nd International Conference on Advances in data-driven Computing and Intelligent Systems, ADCIS 2023

作者： Maiti, Souvik Juneja, Sonam Department of Computer Science and Engineering Chandigarh University Gharuan India

ISBN: (纸本)9789819995233

This study delves into strategies for enhancing energy efficiency in 5G and 6G networks, focusing on network optimization, radio access techniques, and management. It examines research articles to pinpoint important strategies. Among the notable optimizations are the comparison of the energy efficiency of deploying small cells in various microcell topologies, resource allocation strategies for wireless energy transmission, and dynamic base station napping to preserve power during low traffic. Hybrid beamforming (HBF) and adaptive sectorization are presented as ways to reduce energy consumption and boost network capacity. In order to save energy and increase throughput, network topology management techniques including route diversity and inactive base station modes are investigated. Although these methods have the potential to significantly reduce energy consumption and improve network performance, further study and development are necessary to maximize the benefits of energy-efficient wireless communications in the future. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Sensor nodes

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Predicting Preterm Birth Among South-Asian Women Using Machine Learning

Predicting Preterm Birth Among South-Asian Women Using Machi...

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2024 IEEE International Conference on Computing, Applications and Systems, COMPAS 2024

作者： Alif, Meheruba Hasin Main Bhuyan, Farah Tajrin, Radhika Brac University Department of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798331529765

Preterm Birth remains one of the preventable yet large contributors to child and maternal mortality. Despite progress in reducing infant mortality, South Asia continues to report a significant number of preterm birth-related deaths annually. Moreover, those who survive have to bear the long-term impact of physical and neurological disabilities - especially low-income households who are unable to afford healthcare. This study aims to offer a prediction model that can predict preterm birth using social, physical and health records of South-Asian women. Traditional models such as Decision Trees, Random Forest, Support Vector Machines, Logistic Regression and neural network-based deep learning models such as Multilayer Perceptron are used to compare the models' AUC, F1 scores and accuracy points. Random Forest generated the highest accuracy and F1 score (89%), whereas Multilayer Perceptron generated the best AUC score (88%) and had an overall consistent performance. Further analysis revealed the main factors contributing to preterm birth were weight before pregnancy, age and BMI of the mother. © 2024 IEEE.

关键词： Logistic regression

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Music Therapy-Driven Mood-Based Music Recommendation System Integrating User Emotion, Song Lyrics, and Health Reflections

Music Therapy-Driven Mood-Based Music Recommendation System ...

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2025 AI-Driven Smart Healthcare for Society 5.0, AdSoc5.0 2025

作者： Narayanan, Vyshnav S. Tarafdar, Anurina Department of Computer Science and Engineering Heritage Institute of Technology Kolkata India

ISBN: (纸本)9798331536336

The rapid development of digital media has enabled users to access a colossal choice of music through the internet and electronic devices. Music recommendations are given mostly based on the user’s past listening history and artist preferences. While this approach is effective to some extent, it overlooks the importance of the user’s current mood which is governed by circumstantial as well as health conditions. Music therapy recently is a topic of major interest. This work aims to bridge the gap between music and emotions which is a reflection of health condition and mental state, in music recommendation systems and enhance how people connect with music. The proposed mood-based music recommendation system uses sentiment analysis to assess song lyrics, an interactive chatbot to determine user emotions, and a Random Forest model to categorize song moods based on audio characteristics. Recommendations for music are specifically designed to offer therapeutic advantages, such as stress relief, improved relaxation, or catharsis. The proposed system makes dynamic song recommendations based on the changing emotions of the user, thereby aiding in better absorbance of music. Experimental results demonstrate the system’s high accuracy and potential for improving mental well-being, making it a valuable addition to music streaming platforms and mental health applications. © 2025 IEEE.

关键词： Aseptic conditions

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Navigating the Digital Marketplace A Study of Furniture E-Commerce Platforms 2

Navigating the Digital Marketplace A Study of Furniture E-Co...

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2nd International Conference on Advanced Computing and Communication Technologies, ICACCTech 2024

作者： Muckerji, Ishani Yadav, Narinder Abhishek Shrivastava, Yashika Yashasvi Raj, Rishu Chandigarh University Computer Science Engineering Department Mohali India

ISBN: (纸本)9798331519056

Rapid digitalization and increasing mobile usage have been changing the furniture world by placing e-commerce platforms as important tools for sellers and buyers alike. This paper, Navigating the Digital Marketplace: A Study of Furniture E-commerce Platforms, has probed into the current state of furniture e-commerce by delineating some of the key challenges in the same: high costs incurred in shipping, return issues, and a lack of personalization. This study shows the merits and drawbacks of existing platforms by conducting a comparative analysis, in various subsectors. This study offers a solution of formulating a strategy for creating a more efficient, user- friendly platform that caters to a huge audience. This paper also shows glimpses of how emerging technologies like Artificial Intelligence (AI), Augmented Reality (AR), and Virtual Reality (VR) can be used to improve customer experience and operational efficiency. © 2024 IEEE.

关键词： Marketplaces

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