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Impact of UAV-Based Transmitter Mobility on Physical Layer Security

IEEE Transactions on Information Forensics and Security 2025年 20卷 5604-5619页

作者： Ruby, Rukhsana Elhalawany, Basem M. Pham, Quoc-Viet Wu, Kaishun Wang, Lu Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China Kuwait College of Science and Technology Electronics and Communication Engineering department Block 4 Doha District93004 Kuwait Trinity College School of Computer Science and Statistics Dublin 2 DublinD02 PN40 Ireland

Owing to flexible management and low overhead, wireless physical layer security (PLS) has been applied to support many critical applications (e.g., data dissemination) of unmanned aerial vehicles (UAVs)-based mobile communication networks in emergency scenarios. Although the impact of static network scenarios or receiver mobility on PLS has been well studied, there is no much work that studies the impact of UAV-based transmitter mobility on PLS. To fill this gap, in this paper, we investigate PLS of a scenario, where a random mobile UAV-based transmitter transmits information to a static ground entity under Rayleigh fading channel. More specifically, we consider a communication system, in which a mobile UAV hovers over a region to collect information and then disseminates this information to a static ground network entity in a confidential manner under the presence of an eavesdropper. Because of popularity and practicality, the UAV is assumed to hover following the random way point (RWP) mobility model. We investigate the secrecy characteristics of the UAV under steady running state in terms of ergodic secrecy capacity (ESC), positive secrecy capacity probability (PSCP) and secrecy outage probability (SOP) for the communication between the UAV and the receiver. We then investigate the secrecy performance of the proposed system while considering the pause time of the RWP mobility model adopted by the UAV. We further extend our proposed theoretical model to other realistic scenarios, including the presence of multiple cooperative and non-cooperative eavesdroppers, and study the PSCP and SOP metrics of the corresponding system. Furthermore, we propose three types of secrecy improvement strategies for the considered communication model. We strike a good trade-off between the secrecy improvement and transmit outage probability. Extensive simulations have been conducted to validate our theoretical analysis as well as the effectiveness of the proposed secrecy improvement s

关键词： Drones

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A Review of Various Deep Learning Approaches for Placement Prediction 2

A Review of Various Deep Learning Approaches for Placement P...

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2nd International Conference on Machine Learning and Autonomous Systems, ICMLAS 2025

作者： Bodke, Minal Tiwari, Vishnu Wadhwani, Jayesh Gorbade, Trapti Soundane, Rohan Pimpri Chinchwad College of Engineering and Research dept. Computer Engineering Pune India

ISBN: (纸本)9798331505745

In recent years, predictive analysis for student placement has attracted a lot of attention, and machine learning approaches have shown to be useful in enhancing decision-making and accuracy in higher education. This review paper provides a conceptual framework to improve student placement predictions by using deep learning models with self-attention mechanisms. The aim of this model is to tackle problems related to feature importance selection, imbalanced datasets, and complex data patterns. We suggest a multi-tiered strategy that combines deep learning's ability to identify complex correlations in instructional datasets with ensemble learning techniques for reliable performance. Predictive quality will be thoroughly examined through the use of performance indicators such as accuracy, precision, recall, and F1 score in the evaluation of the models. It is anticipated that this strategy will give educational institutions more accurate forecasting instruments, revealing important factors influencing students' employability while guaranteeing decision-makers can understand the data. This framework intends to make a contribution to the expanding field of educational data mining and placement prediction by improving existing approaches. © 2025 IEEE.

关键词： Deep learning

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Intelligent Beauty Product Recommendation Using Deep Learning 1

Intelligent Beauty Product Recommendation Using Deep Learnin...

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1st International Conference on Cognitive, Green and Ubiquitous Computing, IC-CGU 2024

作者： Hanchinal, Tainiyat K Bhavani, Vaishali D Mindolli, Veena B Jain College Of Engineering And Research Department of Computer Science and Engineering Belgaum India

ISBN: (纸本)9798350361780

Skin care is a vital component of one's health and well-being, and there are many products on the market that report different skin problems. People's methods for skin issues have changed dramatically as a result of technological revolutions in the skin care industry and artificial intelligence (AI). The traditional approach of navigating multiple brand websites and overwhelming product choices has prompted the need for a more streamlined and intelligent solution. The AI-driven web application system is proposed to suggest appropriate skin care items depending on a particular skin type. It is an innovative system that brings product recommendations from several brands and websites, as well as cross-platform price comparisons, together in a single, customized area. It also provides a link to the particular platform so that customers may purchase products based on the quality and quantity of products. By using deep learning, which uses convolutional neural networks (CNNs) to understand complex patterns within skin data, users provide the system with an image along with additional information about their skin type, worries, and preferences, and help the system understand and recover appropriate data. The proposed system verifies user knowledge before and after system use, while experts examine rules and designs. By analyzing this data, the deep learning algorithm is able to recognize different skin outlines and certain disorders such as pigmentation, age, dryness, sensitivity, or acne. Also, a trained dataset is used to check for the training and validation accuracy of the system. © 2024 IEEE.

关键词： Deep learning

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Leveraging K-means clustering for enhanced detection of network traffic attacks 3

Leveraging K-means clustering for enhanced detection of netw...

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3rd International Conference on Power Electronics and IoT Applications in Renewable Energy and its Control, PARC 2024

作者： Dwivedi, Devanshi Bhushan, Aditya Singh, Ashutosh Kumar Snehlata United College of Engineering & Research Department of Computer Science and Engineering Prayagraj India

ISBN: (纸本)9798350309409

With the expansion of network traffic and the increasing experiences of cyber threats, the need for flexible as well as systematic network traffic attack detection systems has become foremost. Conventional signature-based methods often struggle to identify novel or previously unknown attacks, making it essential to explore alternative techniques for enhancing network security. This research presents a novel approach for enhancing network traffic attack detection using K-means clustering, a popular unsupervised machine learning algorithm. The proposed system employs K-means clustering to group network traffic data into clusters based on their similarity. By identifying anomalous patterns within these clusters, the system can effectively detect network attacks. The approach is evaluated using a real-world network traffic dataset, and the results demonstrate its effectiveness in improving the accuracy and efficiency of attack detection. Additionally, the approach shows promise in the detection of zero-day attacks, thus enhancing network security in the face of evolving threats. This research contributes to the field of network security by offering a data-driven and proactive approach to attack detection that can adapt to emerging threats and minimize false positives. © 2024 IEEE.

关键词： Cybersecurity

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Bidirectional Sign Language Translation System 8

Bidirectional Sign Language Translation System

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8th IEEE International Conference on Computing, Communication, Control and Automation, ICCUBEA 2024

作者： Mahjan, Aditya Hendre, Pradnya Mankhair, Gauri Satpute, Shubhangi Chaudhari, Deepti A. Nutan College of Engineering and Research Department of Computer Science and Engineering Pune India

ISBN: (纸本)9798350391770

Sign language is an essential form of communication for the deaf and hard-of-hearing community. The creation of Bidirectional Sign Language Translation Systems (BSLTS) has drawn a lot of attention as technology has advanced. The first section of the article gives a general review of the difficulties in translating and recognising sign language, highlighting the urgent need for precise and timely solutions. After that, it explores the fundamental ideas of CNN and Sign language, emphasising their advantages. The survey discusses different architectures and techniques used for feature extraction and classification, and it thoroughly evaluates the body of research on CNN's use in sign language recognition. Additionally, the study investigates how the cutting-edge object detection technology YOLO3 improves the spatial comprehension of sign language gestures. This investigation investigates how real-time object identification capabilities of YOLO3 can enhance the accuracy and efficiency of BSLTS, enabling smooth communication between sign language users and non-signers. Sign language is a communication method used by people with speech and hearing impairments to interact with others who are not handicapped. Normal people don't use sign language very often, and it takes a lot of time and effort to understand signs. People with hearing impairments are cut off from the outside world and seldom engage in social interactions due to this communication gap. A system for converting text to sign and sign to text is required to tackle this issue and facilitate communication. For system training, a variety of methods have been employed, including Sign language and Convolutional Neural Networks (CNN). © 2024 IEEE.

关键词： Convolutional neural networks

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Anomaly Detection Model for Convolutional Image Transformation Networks 3

Anomaly Detection Model for Convolutional Image Transformati...

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3rd International Conference on Power Electronics and IoT Applications in Renewable Energy and its Control, PARC 2024

作者： Bhushan, Aditya Singh, Ashutosh Kumar Dwivedi, Vijay Kumar United College of Engineering & Research Department of Computer Science and Engineering Allahabad India

ISBN: (纸本)9798350309409

In the realm of Convolutional Image Transformation Networks (CITN), this study addresses the critical need for robust anomaly detection. The motivation stems from the escalating importance of reliable image classification models in various domains, where identifying anomalies is paramount. Grounded in this context, our hypothesis posits that an enhanced convolutional network can effectively discern anomalies within images. Leveraging innovative methods, we augment traditional Convolutional Neural Networks with specialized transformation techniques. Through extensive experimentation and evaluation, our results demonstrate the model's superior performance in detecting anomalies, surpassing existing benchmarks. This research contributes a novel approach to bolstering image transformation networks for anomaly detection, offering valuable insights for applications in diverse fields. In conclusion, the proposed methodology showcases promising strides in advancing the capabilities of CITN for heightened anomaly detection accuracy. © 2024 IEEE.

关键词： Convolution

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Music Player System Using Real-Time Facial Expression Detection 8

Music Player System Using Real-Time Facial Expression Detect...

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8th IEEE International Conference on Computing, Communication, Control and Automation, ICCUBEA 2024

作者： Nikam, Swati Chobe, Santosh Singh, Simardeep Dixit, Tejas Dhayagude, Aditya Raheja, Himanshu Pimpri Chinchwad College of Engineering & Research Department of Computer Engineering Pune India

ISBN: (纸本)9798350391770

In today's society, stress has become an escalating concern, aggravated by economic uncertainties and rising living costs. Listening to music is a widely recognized stress-relief strategy. The existing music player applications lack the sophistication to select songs tailored to the user's emotional state. This limitation restricts the therapeutic potential of music. Effective stress relief is closely tied to aligning the music with the user's current mood. To address this critical issue, we propose developing a groundbreaking Music Player System that leverages real-time facial expression detection to provide music recommendations. In this project, Python and Flask will be utilized to develop a user-friendly and responsive platform for the users. It uses the Convolutional Neural Network (CNN) algorithm to provide real-time analysis of the user's facial expressions captured via a camera. This unique approach is intended to transform the music experience of the user by providing a dynamic playlist that is generated by processing the facial expressions of the user. Moreover, the system is designed to provide a smooth and personalized music experience, ensuring each song matches the user's emotions. This way, the system aims to relieve the stress of the user by providing emotion-based music recommendations. © 2024 IEEE.

关键词： Convolutional neural networks

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Optimising liquid impingement jet arrays for concentrated heat sources 9

Optimising liquid impingement jet arrays for concentrated he...

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9th European Thermal Sciences Conference, EUROTHERM 2024

作者： Elliott, J.W. Byrne, G. Robinson, A.J. AMBER Research Centre Trinity College Dublin Dublin Ireland Department of Mechanical Manufacturing & Biomedical Engineering Trinity College Dublin Ireland

This work seeks to investigate jet array impingement liquid cooling of CPU processors that utilise Integrated Heat Spreaders. In this study, single and centralised heat sources of various sizes (10 mm to 20 mm) were investigated, and a series of single and multi-objective optimisation studies were carried out to determine the optimum arrangement of microjets for different heat source sizes based on variable geometric inputs of the jet orifice plate. The results indicated that the design of the optimum jet orifice strongly depends on the size of the heat source as well as whether the target optimisation strategy is to achieve minimum thermal resistance, or both minimum thermal resistance and minimum pumping power simultaneously. A clustering of quite different orifice designs in optimal zones is observed, where approximately the same hydraulic and/or thermal performance is observed. © Published under licence by IOP Publishing Ltd.

关键词： Heat resistance

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Exploring the Potential of Prompt engineering: A Comprehensive Analysis of Interacting with Large Language Models 8

Exploring the Potential of Prompt Engineering: A Comprehensi...

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8th IEEE International Conference on Computing, Communication, Control and Automation, ICCUBEA 2024

作者： Pawar, Vaidehi Gawande, Manvi Kollu, Archana Bile, Aditya Sudhir Pimpri Chinchwad College Of Engineering And Research Department of Computer Engineering Ravet India

ISBN: (纸本)9798350391770

This article focused on exploring the core principles of prompt engineering, aiming to provide a comprehensive understanding of how to effectively interact with and instruct large language models (LLMs) using prompts. The article extensively covered various aspects of prompt engineering, including an analysis of its fundamental components, different types of prompts, ethical considerations in the prompting process, and the wide-ranging applications of prompt engineering. Additionally, the study conducted a comparative analysis between two conversational AI bots, ChatGPT 3.5 and BardAI, by subjecting them to similar prompts. The results of this comparison indicated a high level of similarity in their performances, suggesting that both bots are comparable in their capabilities. The study also highlighted the immense potential for further advancements in the field of prompt engineering. By investigating the intricacies of prompt design, ethical implications, and showcasing the promising applications, this article contributes significantly to the knowledge base surrounding prompt engineering. The findings not only shed light on the current state of the technology but also point towards numerous opportunities for future articles and development in this domain. © 2024 IEEE.

关键词： Bot (Internet)

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A numerical investigation of stress, strain, and bone density changes due to bone remodelling in the talus bone following total ankle arthroplasty

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Journal of Medical engineering and Technology 2024年第1期48卷 1-11页

作者： Mondal, Subrata MacManus, David B. Ghosh, Rajesh Banagunde, Abhishek Dunne, Nicholas Mechanical Engineering Department University of Bath United Kingdom School of Mechanical and Materials Engineering University College Dublin Ireland School of Engineering Indian Institute of Technology Mandi Himachal Pradesh India Powertrain Durability Mahindra and Mahindra Ltd Tamilnadu Mahindra World City Chennai India School of Mechanical and Manufacturing Engineering Dublin City University Ireland Centre for Medical Engineering Research Dublin City University Ireland School of Pharmacy Queen’s University Belfast Belfast United Kingdom Department of Mechanical and Manufacturing Engineering School of Engineering Trinity College Dublin Ireland School of Mechanical and Manufacturing Engineering Dublin City University Dublin 9 Ireland Trinity College Dublin Dublin 2 Ireland Trinity Centre for Biomedical Engineering Trinity Biomedical Sciences Institute Trinity College Dublin Dublin 2 Ireland Advanced Processing Technology Research Centre Dublin City University Dublin 9 Ireland Biodesign Europe Dublin City University Dublin 9 Ireland

Total ankle arthroplasty is the gold standard surgical treatment for severe ankle arthritis and fracture. However, revision surgeries due to the in vivo failure of the ankle implant are a serious concern. Extreme bone density loss due to bone remodelling is one of the main reasons for in situ implant loosening, with aseptic loosening of the talar component being one of the primary reasons for total ankle arthroplasty revisions. This study is aimed at determining the performance and potential causes of failure of the talar component. Herein, we investigated the stress, strain, and bone density changes that take place in the talus bone during the first 6 months of bone remodelling due to the total ankle arthroplasty procedure. Computed tomography scans were used to generate the 3D geometry used in the finite element (FE) model of the Intact and implanted ankle. The Scandinavian Total Ankle Replacement (STAR™) CAD files were generated, and virtual placement within bone models was done following surgical guidelines. The dorsiflexion physiological loading condition was investigated. The cortical region of the talus bone was found to demonstrate the highest values of stress (5.02 MPa). Next, the adaptive bone remodelling theory was used to predict bone density changes over the initial 6-month post-surgery. A significant change in bone density was observed in the talus bone due to bone remodelling. The observed quantitative changes in talus bone density over 6-month period underscore potential implications for implant stability and fracture susceptibility. These findings emphasise the importance of considering such biomechanical factors in ankle implant design and clinical management. © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

关键词： Arthroplasty

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