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Comprehensive Self Assessment through BeeBest Mobile Application to Improve Performance 9

Comprehensive Self Assessment through BeeBest Mobile Applica...

引用

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

作者： Indrianti, Yasinta Sasmoko Universitas Agung Podomoro Research Interest Group In Education Technology Entrepreneurship Department Jakarta Indonesia Bina Nusantara University Faculty of Humanities Research Interest Group In Education Technology Primary Teacher Education Department Jakarta Indonesia

ISBN: (纸本)9798350394474

BeeBest mobile application is an artificial intelligence-based application developed as a self-assessment to improve individual performance in their daily lives. This application consists of two domains, namely entrepreneurial mindfulness and Profiling for Aptitude Inventory (P4AI). This research aims to look comprehensively at how the two application domains impact individual performance profiling. The research method used is the Neuroresearch method with a confirmatory stage. The research sample was 192 people and data analysis used Smart PLS. The research results show that entrepreneurial mindfulness has a positive and significant influence and contributes 2,051 to performance. Meanwhile, P4AI also has a positive and significant influence and contributes 4,161 to performance. Both domains together contribute 23.9% to performance. © 2024 IEEE.

关键词： Mobile computing

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Research on the AGV Global Path Planning Algorithm Based on FI-RRT∗ 5

Research on the AGV Global Path Planning Algorithm Based on ...

引用

5th IEEE international conference on Power, Intelligent computing and Systems, ICPICS 2023

作者： Jin, Wuxuan Ma, Xianghua Li, Yangteng School of Electrical and Electronic Engineering Shanghai Institute of Technology Shanghai China

ISBN: (纸本)9798350333442

To address the issue of slow speed for AGV during global planning tasks, we propose the FI-RRT∗ algorithm based on the Informed-RRT∗ algorithm. In the sampling phase of the algorithm, we adjust the distribution probability of randomly sampled points using a Gaussian distribution function, which saves memory and increases node utilization. In the node reselection phase, we adopt an improved elliptical convergence domain strategy to further reduce the size of the convergence domain, thereby enhancing the efficiency of the reselection step. Experimental results obtained through dual-platform experiments using python and ROS demonstrate that the FI-RRT∗ algorithm has a higher planning speed. © 2023 IEEE.

关键词： Motion planning

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Probing the convergence of Vehicular Edge Metaverse and 6G: Blockchain-enabled Framework 18

Probing the Convergence of Vehicular Edge Metaverse and 6G: ...

引用

18th IEEE international conference on Advanced Networks and Telecommunications Systems, ANTS 2024

作者： Kumar, Shree Chaudhary, Rajat Budhiraja, Ishan Bennett University School of Computer Science and Engineering Technology Greater Noida India

ISBN: (纸本)9798350391725

The convergence of vehicular networks and the Meta-verse, referred to as the Vehicular Edge Metaverse is set to revolutionize both transportation and in-car experiences. This paradigm shift envisions vehicles not only as modes of transport but also as immersive gateways to the Metaverse, offering passengers interactive and engaging experiences while on the move. The advent of 6G, with its ultra-fast speeds and minimal latency is crucial in enabling the real-time data synchronization and low-latency communication required for a seamless Vehicular Edge Metaverse experience. Additionally, blockchain technology can play a key role in ensuring secure and transparent data sharing and transactions within this ecosystem, fostering trust and enabling new business models. This paper explores the potential of this convergence, discussing the key enabling technologies such as 6G, edge computing, and blockchain, and their role in addressing the challenges of real-time synchronization, resource management, and security. Furthermore, we discuss the potential applications like augmented reality-enhanced driving assistance and immersive in-car entertainment, highlighting the transformative impact of the Vehicular Edge Metaverse on the future of transportation. © 2024 IEEE.

关键词： Blockchain

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Prediction of Ground-Level Ozone in Bengaluru Using Machine Learning Techniques 9

Prediction of Ground-Level Ozone in Bengaluru Using Machine ...

引用

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

作者： Venuka, T. Khare, K. Sangita Nikhil, Masabattula Teja Thakur, Amrita Amrita Vishwa Vidyapeetham Amrita School of Computing Dept. of Computer Science & Engineering Bengaluru India Amrita Vishwa Vidyapeetham Amrita School of Engineering Dept. of Chemistry Bengaluru India

ISBN: (纸本)9798350394474

An increase in surface-level ozone concentration is a spiking issue in today's world. Surface ozone is a secondary polluting agent that forms a mix of primary pollutants, meteorological variables, and volatile organic compounds. People are getting affected due to this pollutant because of its discreet nature. This paper focuses on trend analysis of the precursors with weather parameters and predicting the surface-level ozone concentration for the future. Data has been obtained from the public website Central Pollution Control Board (CPCB) for two stations Silk Board and Jayanagara 5th Block in Bengaluru for study. The dataset has been split into parts to train and test the models. Extreme Gradient Boost provided the best R2 value with an accuracy of 95.7 percent. © 2024 IEEE.

关键词： Ozone

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Edge- AI and Internet of Things for Intelligent Systems: Architectures, Applications and Future Perspectives 15th

Edge- AI and Internet of Things for Intelligent Systems: Arc...

引用

15th international conference on e Infrastructure and e Services for Developing Countries

作者： Diop, Fatou Faye, Babacar Mbaye Niang, Ibrahima Cheikh Anta Diop Univ Dakar Senegal

ISBN: (纸本)9783031815720;9783031815737

In an era where connectivity is ubiquitous and data flows ceaselessly, Edge IoT (Internet of Things) systems have emerged as a pivotal technological paradigm poised to revolutionize the way we interact with the digital world. As the proliferation of IoT devices continues unabated, the traditional cloud-centric model for data processing and decision-making faces significant challenges. Edge IoT systems, by shifting computational intelligence closer to the data source, offer a compelling solution to these challenges, promising greater efficiency, lower latency, and enhanced real-time decision-making capabilities. On the other hand, the convergence of edge computing, artificial intelligence (AI), and the Internet of Things (IoT) has ushered in a new era of intelligent systems with transformative potential across various domains. This includes the development of edge computing infrastructure, AI models optimized for edge deployment, and IoT device architectures that support real-time data processing and analysis. This paper proposes a comprehensive review on Edge computing, AI, and IoT integration for intelligent systems. We focus on the concept of Edge-AI and its potential applications in real-time processing for Internet of Things. The paper introduces Edge-IA technology, explores commonly used networking and messaging protocols in IoT, and discusses the opportunities and challenges of Edge-IA and IoT in various industries, including agriculture and healthcare.

关键词： Internet of things Edge computing Artificial intelligence Edge-AI

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Advanced Latency Compensation Techniques for Seamless Online Gaming Experiences 9

Advanced Latency Compensation Techniques for Seamless Online...

引用

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

作者： Soorya, Vijayakumar Bhat, Suhas S Shaik, Sajjad Rajagopal, Shinu M. Bhaskaran, Sreebha Amrita Vishwa Vidyapeetham Amrita School of Computing Dept. of Computer Science Engineering Bengaluru India

ISBN: (纸本)9798350394474

Online multiplayer games have become increasingly popular in the modern world, attracting a worldwide audience and creating virtual communities that cut across national borders. This research offers strategies for improving multiplayer gaming experiences and addresses the issues of lag and synchronization in networked game environments by introducing a novel combination of latency exposure, latency concealing techniques and prediction models. The use of visual and auditory effects to conceal latency, the display of ping time for player awareness of latency, and the use of algorithms like k-Nearest Neighbors, Decision Trees, and Random Forests for player input prediction in the event of network outages are effective techniques for enhancing gaming experiences. In addition to providing a thorough understanding of the technological nuances of latency control in online multiplayer games, the research presents solutions for scenarios involving real-time gaming. By implementing these techniques, the study demonstrates significant improvements in player experience, characterized by reduced lag, enhanced fairness, and greater responsiveness across various game genres. © 2024 IEEE.

关键词： Decision trees

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Construction and Optimization Strategy of University Teaching Management Platform Based on Big Data technology 3

Construction and Optimization Strategy of University Teachin...

引用

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

作者： Wang, Lili Wuhan Donghu University College of Law and Journalism Wuhan China

ISBN: (纸本)9798350343922

With the continuous development of information technology, big data technology has become an important tool in various industries. In the context of big data, the informatization construction of teaching management in universities has rich connotations. Data mining, mobile learning, and other popular models of teaching management systems have become popular. The application of big data in universities can achieve the digitization and intelligence of teaching management. In view of this, this article delves into the application of big data technology in university teaching management, including data collection, storage, analysis, and visualization. Then, the problems existing in the current university teaching management platform were analyzed, such as low data quality, insufficient data analysis capabilities, and poor user experience. On this basis, a university teaching management platform based on distributed big data technology was designed, and optimization strategies such as implementing data privacy protection, strengthening data management, breaking through traditional constraints, and establishing scientific and unified standards for educational data were proposed. It is expected to provide reference for the construction of university teaching management platforms. © 2023 IEEE.

关键词： big data optimization strategy teaching management teaching management platform universities

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Application of a Voting-Based Ensemble Method for Recognizing Seven Basic Emotions in Real-Time Webcam Video Images 9

Application of a Voting-Based Ensemble Method for Recognizin...

引用

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

作者： Sanli, Ahmet Tunahan Saran, Murat Cankaya University Information Technology Program Ankara Turkey Cankaya University Computer Engineering Department Ankara Turkey

ISBN: (纸本)9798350394474

This study examines the automatic recognition of human emotions in real-time through facial expressions from webcams. Real-time emotion recognition is a crucial element in human-computer interaction and emotional computing. The study evaluates the effectiveness of various techniques in real-time facial emotion recognition using a custom CNN model, creating an ensemble with a voting mechanism, and integrating the system for real-time emotion recognition. The CNN model was trained on the FER2013 dataset, which consists of facial images labeled with different emotional states. It achieved a remarkable accuracy of 95%. In this study, we developed a dataset named ATS-FER2024, which consists of 184 images depicting seven distinct emotions. The tests conducted on this dataset yielded an accuracy rate of 89%. Despite its small size, the dataset's accuracy is noteworthy. The findings contribute to academic knowledge on developing emotion recognition systems, enhancing empathy, and creating context-sensitive interactions in real-world applications. © 2024 IEEE.

关键词： Emotion Recognition

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Federated learning on non-IID data with reinforcement learning and quantifying historical contribution 4

Federated learning on non-IID data with reinforcement learni...

引用

4th international conference on Internet of Things and Smart City, IoTSC 2024

作者： Li, Mingchu Zeng, Jianchi Xiong, Yi School of Software Technology Dalian University of Technology Dalian116620 China

ISBN: (纸本)9781510681767

In recent years, machine learning related techniques are widely used in edge computing scenarios. This has led to an increase in privacy concern due to the huge amount of data in end devices. To resolve this issue, federated learning (FL) has been proposed. Multiple participating devices perform distributed training locally, keeping training data local to train global neural network model. However, Limited network connectivity restricts parallel model updates and aggregation in federated learning across all devices. Additionally, the presence of non-Independent and Identically Distributed (non-IID) on diverse devices further slow the convergence of FL due to increased local and global model discrepancies. In this paper, we propose Federated learning on non-IID data with Reinforcement learning and Quantifying historical contribution (FedRQ), a non-IID FL framework. The framework aims to intelligently select clients to participate in each round in order to balance the bias introduced by non-IID data and promote model convergence. We evaluated this FedRQ under various FL tasks and verified that this framework outperforms other benchmark methods. © 2024 SPIE.

关键词： Federated learning

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Collaborative Positioning technology Based on Iridium/UWB 14

Collaborative Positioning Technology Based on Iridium/UWB

引用

14th IEEE international conference on Signal Processing, Communications and computing, ICSPCC 2024

作者： Zhao, Yuan Liu, Yangyang Lei, Lei Chen, Guanbo Dan, Zesheng Tang, Chengkai School of Information Engineering Xi'an Mingde Institute Technology Xi'an China School of Electronics and Information Northwestern Polytechnical University Xi'an China

ISBN: (纸本)9798350366556

Low earth orbit (LEO) satellites have low orbit altitude, strong landing signal power, and strong anti-interference ability, which is an attractive way to provide available navigation and positioning services for GNSS-challenged environments. This work studies Iridium signals and establishes a mathematical model for Iridium Doppler positioning by extracting instantaneous Doppler information from iridium opportunity signals. Then, UWB is used to perform peer-to-peer ranging measurement and communication between agent nodes. Finally, a collaborative positioning technology based on Iridium/UWB is proposed. Simulation results show that compared with iridium satellite opportunity signal positioning, the proposed method can significantly improve the convergence speed and positioning accuracy of the algorithm. © 2024 IEEE.

关键词： Iridium

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