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Max-Min Fair 3D Trajectory Planning for Solar-Powered UAV-Assisted Data Collection

Max-Min Fair 3D Trajectory Planning for Solar-Powered UAV-As...

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2022 IEEE/CIC International Conference on communications in China, ICCC 2022

作者： Sun, Chao Xiong, Xinxuan Ni, Wei Ohtsuki, Tomoaki Wang, Xin Fudan University Dept. of Communication Science and Engineering Shanghai China Data61 Business Unit Sydney Australia Keio University Dept. of Information and Computer Science Yokohama Japan

ISBN: (数字)9781665484800

ISBN: (纸本)9781665484800

This paper presents a new solar-powered fixed-wing unmanned aerial vehicle (UAV)-assisted data collection technique, where a fixed-wing UAV harvests solar energy to fly and collect data from smart devices (SDs). The minimum of the data upload-ed from any of the SDs is maximized by optimizing the UAV's three-dimensional (3D) trajectory. The key idea is that we develop variable substitution and successive convex approximation (SCA) techniques to convexify the nonconvex data transmission, UAV energy consumption and mobility constraints, as well as the nonconvex energy harvesting constraint. The proposed algorithm guarantees a locally optimal solution satisfying the Karush-Kuhn-Tucker (KKT) conditions. Another important aspect is that an effective set of approximation parameters are identified for accurate approximation of the solar energy harvesting at relatively low altitudes, contributing to the design of efficient 3D trajectories balancing energy harvesting and data collection. Numerical results show that the 3D flight increases uploaded data by 59% as compared to the two-dimensional (2D) flight. © 2022 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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IoT ML Driven Holistic Health Monitoring and Fitness Assessment Empowering Proactive Wellbeing Management

IoT ML Driven Holistic Health Monitoring and Fitness Assessm...

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Students Conference on engineering and systems (SCES)

作者： Sachin Mishra Anurag Singh Dept. of Computer Science and Engineering Government Engineering College Raipur Raipur Chhattisgarh India Dept. of Electronics & Communication Engineering International Institute of Information Technology Chhattisgarh Naya Raipur India

ISBN: (数字)9798350374711

ISBN: (纸本)9798350374728

In recent years, significant advancements in the area of non-invasive and wearable technology have paved the way for widespread applications of personalized and remote health monitoring. Health monitoring enables proactive management of one's well-being, and enhances overall health outcomes. With the advent of such technologies there are lots of platforms developed. But such platforms are not successful in providing the followings: 1) the ability to monitor all major health vitals in one unified application, & 2) the provision of a holistic health score derived from these non-invasive vitals for fitness measurement. In response, this paper presents a novel solution featuring: 1) An IoT-ML enabled platform for self-monitoring of important health vitals, and 2) A fitness assessment score derived through ML algorithm using the health vitals of a person. By integrating data on various health parameters including heart rate, blood oxygen levels, and sleep patterns, advanced machine learning models are developed to analyze this data and predict the fitness score that accurately reflects an individual's overall health and fitness level. The performance of the proposed estimation model is evaluated using R2 and mean square error (MSE) and the best value is achieved using the XGBoost regressor of values 0.967 and 0.0033. This solution empowers individuals to take control of their well-being and improve their overall quality of life. Overall, the integration of non-invasive methods and IoT sensors for health vitals monitoring and fitness assessment presents a novel approach with significant potential to revolutionize health care. By empowering individuals with real-time insights and a comprehensive fitness score, this solution facilitates informed decision-making and enables individuals to proactively manage their health and well-being, ultimately enhancing their overall quality of life.

关键词： Measurement Pediatrics Medical services Mean square error methods Predictive models Prediction algorithms Real-time systems

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Resource Allocation as a Market: A Case Study on Multi-Server Multi-Model Federated Learning

Resource Allocation as a Market: A Case Study on Multi-Serve...

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Annual Conference on Wireless On Demand Network systems and Services (WONS)

作者： Maria Diamanti Aisha B Rahman Panagiotis Charatsaris Eirini Eleni Tsiropoulou Symeon Papavassiliou Institute of Communication and Computer Systems School of Electrical and Computer Engineering National Technical University of Athens Athens Greece Dept. of Electrical and Computer Engineering University of New Mexico Albuquerque NM USA

ISBN: (数字)9783903176713

ISBN: (纸本)9798331522025

6G networks envision a seamless integration of data and AI into their core operations, marking a new era where distributed client devices actively engage in intelligent processes, supported by a diverse ecosystem of AI service providers. This shift necessitates approaching traditional resource allocation problems from a market perspective, transparently reflecting the gains and losses of clients and providers within the ecosystem. In this paper, we use a multi-server, multi-model Federated Learning (FL) network as a case study to propose a market-based resource allocation framework. The framework models the joint problem of client resource allocation and pricing as a Fisher market, where servers compete to attract clients with private data and local computing resources for distributed model training. The joint problem is formulated as a convex program, aiming to maximize the total server utility related to their model’s accuracy, while incorporating clients’ total computing resource constraints and servers’ budget constraints. An analytical solution to the convex program is derived concluding the so-called Market Equilibrium (ME) point, where market clearance is achieved. The effectiveness of the proposed market-based resource allocation framework is validated through comparisons with established resource allocation and sharing schemes from the literature.

关键词： Federated learning Computational modeling Biological system modeling Ecosystems Distributed databases Pricing Data models Resource management Servers Artificial intelligence

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A CPW-Fed Broadband Oval-Ring Slot Circularly Polarized Antenna

A CPW-Fed Broadband Oval-Ring Slot Circularly Polarized Ante...

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IEEE International Symposium on Intelligent Signal Processing and communication systems (ISPACS)

作者： Hsin-Lung Su Chien-Hung Chen Meng-Huai Yang Chiung-Lin Tsai Dept. Computer and Communication National Pingtung University Pingtung City Taiwan Dept. of Avionics Engineering ROC Air Force Academy Kaohsiung Taiwan

ISBN: (数字)9798350389210

ISBN: (纸本)9798350389227

This article proposed a broadband oval-ring slot CP (circularly polarized) antenna. This oval-ring slot antenna was fed by a 50-ohm CPW (coplanar waveguide). The antenna size is 72 mm $\times$ 68 mm. The antenna operates within a frequency range of 3.31 to 4.81 GHz and with a 3-dB AR (axial ratio) spanning from 3.55 to 4.45 GHz (22.5%).

关键词： Slot antennas Bandwidth Signal processing Broadband communication Coplanar waveguides Broadband antennas

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Facial Age Synthesis by StyleGAN2 with Attention

Facial Age Synthesis by StyleGAN2 with Attention

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IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Tung-Ke Hsieh Tsung-Jung Liu Kuan-Hsien Liu Dept. of Electrical Engineering and Graduate Institute of Communication Engineering National Chung Hsing University Taiwan Dept. of Computer Science and Information Engineering National Taichung University of Science and Technology Taiwan

ISBN: (数字)9798350386844

ISBN: (纸本)9798350386851

The task of age synthesis involves capturing the changing appearance of a person over time. Efficiently representing such complex transformations on facial images is very challenging. We utilize the attention mechanism for enhanced feature extraction combined with expressive semantic latent space of StyleGAN2, which facilitates additional refinement and editing of the generated images, In addition, we incorporate an identity discriminator so that the identity of the generated images can be preserved. Finally, through qualitative and quantitative evaluations, we demonstrate that our method achieves better age synthesis accuracy compared to state-of-the-art methods.

关键词： Accuracy Attention mechanisms Semantics Feature extraction Vectors Consumer electronics

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An earlier serial lactate determination analysis of cardiac arrest patients using a medical machine learning model

An earlier serial lactate determination analysis of cardiac ...

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Intelligent systems for communication, IoT and Security (ICISCoIS), International Conference on

作者： Mehmood Ali Mohammed Murtuza Ali Mohammed Vazeer Ali Mohammed J. Logeshwaran Nasmin Jiwani Dept. of Information Technology University of The Cumberlands Williamsburg KY USA Dept.of Computer & Information System Lewis University Illinois USA Dept. of Electronics and Communication Engineering Sri Eshwar College of Engineering Coimbatore INDIA

In general, cardiac arrest results in an inability to pump enough blood for the body's needs. Through this, the organs and tissues get enough oxygen and nutrients for their metabolic needs, and excess fluid accumulates. This further increases the severity of the patient's problems. Cardiac arrest is the leading cause of hospitalization in people over 65 and is therefore considered a significant public health problem. It is a pathology linked to an increase in average life expectancy, and its incidence is increasing every year due to the general ageing of the population. In this paper, an earlier serial lactate determination analysis of cardiac arrest patients using a medical machine learning algorithm. It can occur following an episode of cardiac arrest or inadequate treatment of chronic diseases, including diabetes and hypertension. Adopting lifestyle habits that prevent the onset of these conditions is an essential strategy for preventing heart failure. The proposed approach has achieved 91.58% accuracy, 87.96% precision, 84.62% recall, and 85.23% F1-score results compared to other methods.

关键词： Heart Proteins Sociology Pumps Cardiac arrest Security Statistics

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Speech Recognition Paradigms: A Comparative Evaluation of SpeechBrain, Whisper and Wav2Vec2 Models

Speech Recognition Paradigms: A Comparative Evaluation of Sp...

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International Conference for Convergence of Technology (I2CT)

作者： Dhanvanth Reddy Yerramreddy Jayasurya Marasani Ponnuru Sathwik Venkata Gowtham Guduru Harshit Anjali Dept. of Computer Science and Engineering Amrita School Of Computing Amrita Vishwa Vidyapeetham Amritapuri India Dept. of Electronics & Communication Engineering School of Engineering Amrita Vishwa Vidyapeetham Amritapuri India

ISBN: (数字)9798350394474

ISBN: (纸本)9798350394481

Speech recognition plays a pivotal role in the realm of natural language processing that deals in converting the language into the written text, providing human-computer interaction and enables us to use it widely for applications starting with voice assistants and delving upto the transcription services. Due to the complexity present in performing the task of speech recognition has led to the development of various models to enhance accuracy and efficiency. Our project mainly delves into three prominent speech recognition models that are Whisper, Wav2Vec2 and Speechbrain each of them representing distinct approaches of transcribing spoken language. The significance of the models used lies in their potential to perform better for realtime applications by improving the accuracy and reliability of speech recognition. To evaluate the best model that performs effectively, an array of metrics are used including levenshtein distance and it’s similarity percentage, jaccard similarity along with semantic similarity that provides an additional layer of evaluation describing the model’s understanding of contextual meaning in spoken language. Out of the three models, Speech Brain model outperformed all the other models through the calculation of Word Error Rate (WER), Character Error rate (CER) and BLEU score. The results have shown the model’s efficiency in converting spoken language(audio files) into precise and contextually relevant text. The results shows that these models contribute to the field of speech recognition highlighting the strengths of each approach and among them considering speechbrain as an ideal solution for accurate and meaningful transcription.

关键词： Measurement Human computer interaction Adaptation models Technological innovation Error analysis Semantics Speech recognition

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Research on Intelligent Network Operation Management system Based on Anomaly Detection and Time Series Forecasting Algorithms

Research on Intelligent Network Operation Management System ...

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2022 IEEE Conference on Telecommunications, Optics and computer Science, TOCS 2022

作者： Guo, Jian Guo, Hua Zhang, Zhong Tianjin University of Technology Dept. of Information Management and Information System Tianjin China Tianjin Polytechnic University Dept. of Communication Engineering Tianjin China Tianjin University Div. of Science and Technology Tianjin China

ISBN: (纸本)9781665470537

The research try to implements an intelligent network operation management system for enterprise networks. First, based on Flask-state software architecture, the system adapt to Phytium CPU and Galaxy Kylin operating system successfully. Second, using the Isolation Forest algorithm, the system implements the anomaly detection of host data such as CPU usage. Third, using the Holt-winters seasonal prediction model, the system can predict time series data such as network I/O. The results show that the system can realizes anomaly detection and time series data prediction more precisely and intelligently. © 2022 IEEE.

关键词： Anomaly detection

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Indoor Real-Time Location system for Efficient Location Tracking Using IoT

Indoor Real-Time Location System for Efficient Location Trac...

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2022 IEEE World Conference on Applied Intelligence and Computing, AIC 2022

作者： Verma, Sunny Raj, Tej Joshi, Kapil Raturi, Preeti Anandaram, Harishchander Gupta, Ashulekha Dev Bhoomi Uttarakhand University Dept. of Electronics & Communication Engineering Dehradun India Uttaranchal University Dept. of Computer Science & Engineering Dehradun India Tula's Institute of Technology Dept. of Computer Science & Engineering Dehradun India Amrita Vishwa Vidyapeetham Centre for Excellence in Computational Engineering and Networking Tamil Nadu Coimbatore India Graphic Era University Dept. of Management Studies Dehradun India

ISBN: (数字)9781665479882

ISBN: (纸本)9781509050017

Researchers have broadened the focus of RFID technology development because to the growing need for low-cost edge devices to bridge the physical-digital gap. In addition to item identification, researchers have explored the use of RFID tags for low-power wireless sensing, localization, and activity inference. A security system utilized today is not powerful enough to provide a real-time alert after identifying a problem. Movement detection is a technology for detecting a change in the environment relative to an object. Sensor-based applications can be used to watch activity and receive alerts when movement is detected, which solves the issue and saves time and money. RFID technology is used to track the location of people or things in an interior setting in real time. A reader and several tags, each of which can house a number of sensors, make up an RFID system. In this research, we present the iLocate framework for the IoT, a recently developed real-time locating framework using dynamic RFID for resource the board in indoor settings. iLocate used ubidots to assist with a broad range RFID organization. Our exploratory findings and the actual project have both shown the prevalence. Location tracking indoors will be more effective using this iLocate framework. © 2022 IEEE.

关键词： Internet of things

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Wearable Sensor-Based Gait Analysis: Advanced Feature Extraction Techniques

Wearable Sensor-Based Gait Analysis: Advanced Feature Extrac...

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International Conference on Advances in Information Technology (ICAIT)

作者： Karthik K Preethi Salian Ranjith H D Supriya Salian Jayashree K Annapoorneshwari Shetty Dept. of Electronics and Communication Engineering Nitte (Deemed to be University) NMAM Institute of Technology Nitte Udupi India Dept. of Information Science and Engineering Nitte (Deemed to be University) NMAM Institute of Technology Nitte Udupi India Dept. of Electronics and Communication Engineering Mangalore Institute of Technology and Engineering Moodabidri India Dept. of Computer Science and Engineering St. Joseph Engineering College Mangaluru India Dept. of Computer Science and Engineering NM Institute of Technology Bangalore India Dept. of Master of Computer Applications AIMIT St. Aloysius (Deemed to be University) Mangalore India

ISBN: (数字)9798350383867

ISBN: (纸本)9798350383874

Gait irregularities among adults are common in clinical settings and can result in severe consequences such as falls and injuries, leading to increased healthcare costs. Presently, gait evaluation primarily relies on subjective assessments using standardized clinical tools. Although motion capture systems like Qualisys and Vicon offer more objective analysis, they depend on costly, intricate equipment in specialized gait laboratories. Due to limited accessibility, involving factors like equipment scarcity, demand for technical expertise, in-person patient visits, complex procedures, and high costs, these methods remain largely inaccessible. Consequently, there is a pressing need for a more objective and cost-effective gait assessment solution. The proposed work introduces an economical automated feature extraction approach to address this issue. Leveraging Inertial Measurement Unit (IMU) sensors, comprising a three-axis gyroscope and accelerometer system captures precise foot position and orientation data crucial for comprehensive gait analysis. IMU sensors have gained popularity due to their adaptability in clinical environments and non-clinical settings like patient residences or community spaces. With the help of a microcontroller mounted on the barefoot, the IMU sensor collects raw gyroscope and accelerometer data for gait analysis. These data are wirelessly transmitted via Bluetooth to a computer for subsequent in-dept. analysis, enabling effective feature extraction for comprehensive gait assessment.

关键词： Legged locomotion Accelerometers Costs Microcontrollers Pressing Feature extraction Sensor systems Motion capture Sensors Gyroscopes

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