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Research on UAV Ad Hoc Network Coverage Optimization Strategy 24

Research on UAV Ad Hoc Network Coverage Optimization Strateg...

引用

4th international conference on Artificial Intelligence, Automation and High Performance computing, AIAHPC 2024

作者： Wang, Yijun Chen, Jiaqi Zhuang, Dawei School of Electronic Information Engineering Changchun University of Science and Technology China

ISBN: (纸本)9798400710049

In order to improve the coverage of UAV AD hoc network, reduce the loss of UAV in operation and the number of UAV involved, a network coverage optimization algorithm based on improved moth extinguishing algorithm is proposed. Firstly, the artificial potential energy method is applied to avoid obstacles before the global search, secondly, the nonlinear dynamic adaptive step factor is introduced to expand the moth search range at the beginning of the search stage, and finally, the dynamic adjustment strategy of flight direction is integrated to improve the global optimization ability during the search process, and then the optimal solution is modified by Cauchy. The simulation results show that the convergence and stability of the proposed algorithm are superior to the other four algorithms, and the connectivity between UAV nodes is improved, and the coverage rate is 18.32%, 5.48%, 5.09% and 10.6% higher than that of the other four algorithms, respectively, which effectively reduces the loss and the number of UAVs used and reduces the cost. © 2024 Copyright held by the owner/author(s).

关键词： Optimization algorithms

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A Straggler-resilient Federated Learning Framework for Non-IID Data Based on Harmonic Coding 19

A Straggler-resilient Federated Learning Framework for Non-I...

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19th international conference on Mobility, Sensing and Networking (MSN)

作者： Tang, Weiheng Chen, Lin Chen, Xu Sun Yat Sen Univ Sch Comp Sci & Engn Guangzhou Peoples R China

ISBN: (纸本)9798350358261;9798350358278

Federated learning (FL) has recently emerged as a promising learning paradigm, that enables local gradient update and global model aggregation and synchronization. With the advantages of data privacy protection and communication overhead reduction, FL has been widely adopted in a multitude of edge intelligence and IoT applications. However, except the benefits, FL also suffers from stragglers effect and non-IID data, leading to unpredictable training delay and unstable convergence. Meanwhile, coding theory-based approaches have been proposed for stragglers mitigation in distributed computing, i.e., coded computing. Motivated by coded computing, there are several works introduce coding techniques into federated learning. In this paper, to further exploit the potential of coded federated learning, we propose HarFL, a stragglers resilient federated learning framework for non-IID data based on harmonic coding, which is suitable for general machine learning model with multivariate polynomial gradients and achieves a better stragglers mitigation than former coded federated learning schemes with the same coded computation redundancy. We first describe the basic harmonic coded federated learning framework with two phases: encoded data sharing and gradient results decoding. Moreover, we formulate an optimization problem aiming to maximize the successful probability of decoding, which is proved to be NP-hard. An efficient approximate algorithm with theoretical performance guarantee is also developed to mathematically solve the formulated problem. Finally, simulation results demonstrate the superiority of HarFL over several compared schemes.

关键词： Federated learning Coded computing Stragglers effect Non-IID data

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Controlled Face Generation Using Conditional GAN

Controlled Face Generation Using Conditional GAN

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2025 international conference on computing for Sustainability and Intelligent Future, COMP-SIF 2025

作者： Srujana, S.N. Veena, N. Karthik, S.A. Vijaya Shetty, S. Bms Institute of Technology and Management Department of Information Science and Engineering Bengaluru India Manipal Institute of Technology Manipal Academy of Higher Education Department of Information Technology Bengaluru India Nitte Meenakshi Institute of Technology Department of Cse Bangalore India

ISBN: (数字)9798331538538

ISBN: (纸本)9798331538538

The Conditional GAN generates the human faces with certain conditions applied to its features. In Conditional GANs, the generator and discriminator networks are extended to take in additional conditional information during the training process. The generator network synthesizes faces with specific attributes. The discriminator is also conditioned on the same external information which helps it learn not only to differentiate between real and fake samples but also to recognize and potentially control specific attributes in the generated data. By altering the conditionally labelled data supplied to the discriminator and generator, the characteristics of the created faces can be modified. The conditional attributes include hair color, gender, face shape, expression, and age. Applying the conditions while keeping the random noise constant leads to generating faces that exhibit those specific attributes. The convergence occurs while the discriminator can no longer reliably distinguish between real and fake images. This point indicates that the generator has successfully learned to produce realistic-looking images that resemble the real data distribution. The trained generator network can be used to create new, artificial faces when the GAN has converged. © 2025 IEEE.

关键词： Discriminators

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Advanced Knee Osteoarthritis Detection using Deep Learning 9

Advanced Knee Osteoarthritis Detection using Deep Learning

引用

9th IEEE international conference for convergence in technology, I2CT 2024

作者： Krishna, Chetlapalli Amritha Bhuvaneswari, R. Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science And Engineering Chennai India

ISBN: (纸本)9798350394474

This present research investigates the use of machine learning and deep learning models for the detection of knee osteoarthritis using the X-Ray images in depth. knee osteoarthritis is one of the most common joint disorders which affects numerous percentages of people across the world. And its detection of it at an early stage is very critical for effective management. This paper presents valuable dataset of X-ray images with a dual focus on detection of knee joint and KellgrenLawrence grading [kl]. The methodology which is proposed in this paper includes basic steps such as data loading and preprocessing. It also includes feature extraction and utilization of models of both machine and deep learning. In the phase of machine learning models which are used are Decision tree, KNN, MLP, Random Forest and ensemble methods. While in deep learning models used for evaluation are Nasnetmobile, VGG19, Darknet53, Darknet19 and Googlenet. The output of all the above-mentioned models are compared and evaluated based on four most important metrics of performance. The final output of the research shows that Random Forest and the Ensemble methods have outperformed in the phase of machine learning and when it comes to deep learning Googlenet and Darknet53 have done well in comparison. This study helps in the early detection of the knee osteoarthritis and also helps in management of it by giving valuable insights to medical practitioners and researchers. © 2024 IEEE.

关键词： Grading

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Development of Deepfake Detection Techniques for Protecting Multimedia Information using Deep Learning 3

Development of Deepfake Detection Techniques for Protecting ...

引用

3rd international conference on Applied Artificial Intelligence and computing, ICAAIC 2024

作者： Siva Rama Lingham, N. Devakanth, J Jude Moses Anto Raj, Gowtham Gayathri, K. Janani, R. Dhanapal, R. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Chennai India Acharya Institute of Technology Department of Computer Science and Engineering Bangalore India Bannari Amman Institute of Technolgy Department of Information Technology Erode India Sri Krishna College of Engineering and Technology Department of Computer Science and Engineering Coimbatore India Karpagam Academy of Higher Education Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350375190

The development of proposed deepfake detection techniques plays a prominent role in the safeguarding the multimedia information. The various challenges are addressed using the aid of deep learning techniques. This involves hybrid optimization techniques such as particle swarm optimization and genetic algorithms. This helps to improve the accuracy and efficiency in the detection of deepfake. PSO helps in optimizing the weights and parameters of the neural network to obtain faster convergence. GA helps in obtaining potential solutions to obtain the robust deepfake detection model. The integration of deep learning with hybrid optimization involves the collection and preprocessing of the multimedia information and proceeds to an optimization algorithm. The manipulated content in the online platform are detected during the training process. The hybrid optimization tcehniques helps in obtaining model generability and achieving resilience in various attacks occurring in the deepfake generation. The integration of PSO and GA helps in the accurate detection of deepfake content through continuous training and evaluation. Thus the proposed system forms a safeguarding tool for multimedia content and helps to eliminate various risks. © 2024 IEEE.

关键词： Genetic algorithms

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Construction of Immersive Learning Environment for College English Speaking Based on Virtual Reality technology 3

Construction of Immersive Learning Environment for College E...

引用

3rd international conference on Intelligent computing, Communication and convergence, ICI3C 2023

作者： Cai, Zheng Hubei Three Gorges Polytechnic Yichang China

ISBN: (纸本)9798350343922

Spoken English is an important component of English learning. The traditional oral learning environment is limited by time and space, making it difficult to provide good objective conditions for students' oral learning. Traditional oral learning is limited by venues and resources, making it difficult to provide diverse contextual changes, and there are certain shortcomings in providing realism, personalization, interactivity, real-time feedback, and other aspects. In order to improve students' oral learning level and enrich oral learning resources, this article combined virtual reality (VR) technology to conduct in-depth research on the construction of an immersive learning environment for college English oral communication. This article first determined the goals of college English oral education, and then used VR technology to design scene organization, scenario design, and interaction design, achieving the construction of an immersive learning environment for college English oral education. To verify the effectiveness of immersive learning environment for college English oral communication based on VR technology, this article took first-year students majoring in marketing from a certain university as a sample and conducted learning practice on them. The results showed that compared to students who learned oral English in traditional classroom environments, students who learned oral English in an immersive learning environment based on VR technology achieved an average increase of 3.33 points in oral expression, 1.31 points in vocabulary and grammar, and 1.81 points in English language and cultural awareness test results. The conclusion indicates that an immersive learning environment for college English oral communication based on VR technology can help improve students' oral learning level and provide a new perspective for college English oral communication learning. © 2023 IEEE.

关键词： Virtual environments

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Optimal Estimation of Entangled States in Classical Quantum Simulator 13

Optimal Estimation of Entangled States in Classical Quantum ...

引用

13th international conference on Information and Communication technology convergence, ICTC 2022

作者： Jin, Ki-Sung Cha, Gyu-Il Cloud Computing Sw Research Section Electronics and Telecommunications Research Institute Daejeon Korea Republic of

ISBN: (数字)9781665499392

ISBN: (纸本)9781665499392

Estimating the entanglement of qubits without measurement is a critical problem in quantum computing. Quantum algorithms using many qubits entail a substantial computational load as the quantum state increases exponentially. A mathematical tool like Schmidt's decomposition is virtually impossible to apply directly to such an algorithm. We propose a novel method for estimating entanglement states more precisely and quickly without measurement using a classical state vector quantum simulator. The fundamental principle of our idea is to project the state of the desired qubit from the entire quantum state into classical bits. Our concept can work independently of the exponential problem in classical quantum computers, ensuring faster-estimating entanglement relationships with fewer computing resources. In this paper, we present the verification results of our ideas using QPlayer, a special-purpose classical quantum simulator. © 2022 IEEE.

关键词： Qubits

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UX Elements in Inviting Elderly People to the Metaverse: A Focus on AR Glasses Service for Air Pollution 11th

UX Elements in Inviting Elderly People to the Metaverse: A F...

引用

11th international conference on Culture and computing (C&C) part of the 25th international conference on Human-Computer Interaction (HCI)

作者： Zhou, Ye Ahn, Sunghee IDAS HongIk Univ Seoul South Korea HongIk Univ Sch Design Convergence Sejong South Korea

ISBN: (纸本)9783031347313;9783031347320

With the rapid industrialization of cities, air pollution has become an increasingly serious problem. Fine pollutants in the air brake through our body's defenses and penetrate deep into our respiratory and circulatory systems, damaging our lungs, hearts, and brains. Of all people, this hazard affects the elderly the most. At the same time, the development of technology is rapid, as is the popularity of the metaverse, but the elderly do not have a good grasp of technology. In this paper, we propose a senior-friendly AIR Navigation that identifies the categories and concentrations of ozone, PM2.5, NOx (motor vehicle exhaust) and SOx (factory and coal combustion) can be identified respectively. With AIR Navigation, users can visualize the air index by color differentiation and can see safe routes to help them reach their destinations. The aim of this project is designed to be user-friendly and easy to use, making it suitable for a wide range of users. The system not only provides a solution to help the elderly avoid air pollution and keep healthy, but also invites middle-aged and elderly to the metaverse world and can have a good use technology in a friendly way.

关键词： Air Pollution AR Glasses Service Elderly Healthcare Socially Responsible Metaverse

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Exploring Regression Models for Youtube Views Prediction with Interpretable Insights 9

Exploring Regression Models for Youtube Views Prediction wit...

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9th IEEE international conference for convergence in technology, I2CT 2024

作者： Prachi Siddhi Deepa Manju Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science And Engineering Bangalore India

ISBN: (数字)9798350394474

ISBN: (纸本)9798350394474

This computer age has changed content consumption, every individual can access infinite collection of information at their fingertips. The change from conventional media to internet-based media has enabled consumers to select content, nurturing a varied and worldwide informational panorama and entertainment. The rise of trendsetters and community-driven content has more enhanced the effect of social media, generating new types of internet-based celebrity and modifying the way users and enterprises involve their viewers. YouTube has progressed into a massive video-sharing medium, presenting content covering from entertainment and tutorial to comprehensive informative materials. YouTube's easy to use interface and computational suggestions produce customized viewing experience, contributing to platform's accomplishment within its enormous user base. Revenue-generating initiatives on YouTube aid to a noteworthy financial source for content creators, cultivating the creation of varied and high-quality videos that captivate to both specific spectators and worldwide viewer base. The drive behind conducting view count prediction exists in its capability to enable content creators, marketers and platform planners. We use broad variety of attributes in this predictive analysis challenge to project the number of views on YouTube videos. The dataset is imported from kaggle. Features used are likes, view-velocity, comments, subscribers, total views, categories, tags. © 2024 IEEE.

关键词： Predictive analytics

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Changes in Communication Networks and computing for Intelligent IoT Services from Cloud to Edge 13

Changes in Communication Networks and Computing for Intellig...

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13th international conference on Information and Communication technology convergence, ICTC 2022

作者： Kyung, Yeunwoong Ko, Haneul Kongju National University Division of Information & Communication Engineering Cheonan Korea Republic of Kyung Hee University Department of Electronic Engineering Yongin Korea Republic of

ISBN: (数字)9781665499392

ISBN: (纸本)9781665499392

Initially, users use internet of things (IoT) services to remotely monitor or control things through the internet. However, according to the development of IoT technologies, there have been various IoT services which require some strict requirements such as real-time response or high computing processing. In addition, the intelligent computing for the services has been needed in these days. To cover these services, the communication networks and computing paradigms have been changed. Conventionally, IoT services have been usually supported in the cloud. Then, the edge cloud or computing has been considered for the real-time response. Finally, the computing in the device by itself such as a tiny machine learning concept has been recently introduced. Therefore, this paper reviews the changes in communications networks and computing paradigms from the cloud to the edge and device computing for the intelligent IoT services. © 2022 IEEE.

关键词： Internet of things

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