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

作者： Pin-Yu Huang Yung-Han Lu Chun-Ting Lin Bo-Xian He Tun-Wen Pai Dept. of Computer Science and Information Engineering Taipei Taiwan

In an aging society, the rate of dementia would be dramatically increased. It is urgent to provide intelligent facilitative devices and appropriate medical care for those who with dementia symptoms, especially for the elders. Accordingly, the primary research target of this study is to automatically detect and monitor behavior of the elderly suffered from dementia. Although previous research has been conducted to identify various human movement patterns, the experimental data were all received from cameras. Furthermore, these related applications are not specifically designed to identify the behavior of the elderly with dementia. In order to improve previous research methods, our study adopted wearable multi-axis sensors to collect corresponding motion data with protected privacy. In addition to collecting raw data containing time series signals, frequency and spatial domain features were applied to detect human behaviors, and Random Forest algorithm was applied to construct a motion prediction model. The classification system for real-time motion recognition contained two main actions of users including holding/putting hand gestures and walking model. Finally, an additional camera on the chest was designed to be triggered and to take a shot according to previous settings. It could enhance practical applicability of the proposed intelligent system to assist the elderly with dementia to find her/his lost objects. This study developed an app for recording individual behaviors, checking the location and time of lost objects, and even recording activity information to provide healthcare professionals with decision-making suggestions for subsequent precision medical care.

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Play Everywhere: A Temporal Logic based Game Environment Independent Approach for Playing Soccer with Robots

arXiv

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arXiv 2024年

作者： Suriani, Vincenzo Musumeci, E. Nardi, D. Bloisi, D.D. Dept. of Computer Control and Management Engineering Sapienza University of Rome Rome Italy Dept. of Mathematics Computer Science and Economics University of Basilicata Potenza Italy

Robots playing soccer often rely on hard-coded behaviors that struggle to generalize when the game environment change. In this paper, we propose a temporal logic based approach that allows robots’ behaviors and goals to adapt to the semantics of the environment. In particular, we present a hierarchical representation of soccer in which the robot selects the level of operation based on the perceived semantic characteristics of the environment, thus modifying dynamically the set of rules and goals to apply. The proposed approach enables the robot to operate in unstructured environments, just as it happens when humans go from soccer played on an official field to soccer played on a street. Three different use cases set in different scenarios are presented to demonstrate the effectiveness of the proposed approach. © 2024, CC BY.

关键词： Temporal logic

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Blockchain-Based Medical Image Processing Mechanism 4

Blockchain-Based Medical Image Processing Mechanism

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4th International Conference on Cybernetics, Cognition and Machine Learning Applications, ICCCMLA 2022

作者： Berwer, Rajiv Kumar Indora, Sanjeev Atal, Dinesh Kumar Deenbandhu Chhotu Ram University of Science and Technology Dept. of Computer Science and Engineering Murthal Sonipat India Deenbandhu Chhotu Ram University of Science and Technology Dept. of Biomedical Engineering Murthal Sonipat India

ISBN: (数字)9781665462464

ISBN: (纸本)9781665462464

Blockchain is an emerging technology that provides privacy and security to the user data, ultimately leading to user trust. This paper consists of basic key features of blockchain technology, various kinds of blockchain technology, basic blockchain technology, and the use of a cryptographic function. The blockchain uses a cryptographic hash function that converts an arbitrary size into a fixed-length example: MD5, SHA-256, etc., and proof-of-work to validate the block creation. The blockchain is a decentralized architecture with various applications, such as sharing medical data in healthcare, voting mechanism, personal identity security, supply chain, and cross-border transactions. Blockchain is not limited to only digital currency examples: Bitcoin (BTC), but also has massive applications in the medical field and health sector. The paper's primary purpose is to explore the current work of blockchain in a medical image. Blockchain deals with the privacy and security issues in transmitting, storing or retrieving medical photos. © 2022 IEEE.

关键词： Blockchain

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Automated Wound Segmentation using Attention Mechanism based on Enhanced MobileNetV2

Automated Wound Segmentation using Attention Mechanism based...

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Robotics, Automation, Artificial-intelligence and Internet-of-Things (RAAICON), 2019 IEEE International Conference on

作者： Dewan Ahmed Muhtasim Monirul Islam Pavel Arindrajit Paul Abdul Wadud Shakib Sanji Sahlan Gazi Md. Mahfujul Hasan Dept. of Computer Science and Engineering Metropolitan University Sylhet Bangladesh STEM University of South Australia Australia Dept. of Computer Science University of Colorado Boulder Boulder United States

ISBN: (数字)9798331534400

ISBN: (纸本)9798331534417

Wound healing is a morphogenetic reaction to injury that restores physiological and anatomical function. It is crucial in fields like obesity treatment, cancer, trauma, burns, and diabetic foot ulcer (DFU) care. Wound care experts rely on affordable, high-resolution cell phone cameras for image documentation; however, lack of information can hinder proper wound management, documentation, and diagnosis, highlighting the need for improved therapeutic techniques and better automated image segmentation methods. Recent deep learning approaches for automatic feature extraction from images face challenges due to limited training data and low neural networks dept.s, which hinder accuracy by failing to capture complex patterns. This research introduces an improved MobileNetV2 model which utilized transfer learning, two additional dense layers, and fusion with spatial attention mechanism to improve the accuracy of the wound segmentation task. The proposed approach achieved a dice score of 92.40% on the Foot Ulcer Dataset and 96.92% on the Medetec Wound Dataset. In comparison to existing state-of- the-art deep learning-based VGG16, SegNet, U-Net, and MobileNetV2+CCL techniques, the proposed attention-based MobileNetV2 technique obtained the highest dice score.

关键词： Deep learning Image segmentation Attention mechanisms Accuracy Transfer learning Training data Documentation Wounds Feature extraction Diabetes

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Performance Evaluation of Synthetic Aperture Radar Images 8

Performance Evaluation of Synthetic Aperture Radar Images

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8th International Conference on Signal Processing and Communication, ICSC 2022

作者： Upadhyay, Kritika Kumar, Sandeep Bharti, Manisha Agarwal, Prabhakar National Institute of Technology Delhi Dept. of Electronics and Communication Engineering Delhi India National Institute of Technology Delhi Dept. of Computer Science and Engineering Delhi India

ISBN: (纸本)9781665454308

Synthetic Aperture Radar (SAR) imaginary is used extensively for Military applications in the modern era of technology. In this work, we have evaluated the performance of SAR images for Radar Systems. The SAR length, Resolution, and Footprint of SAR networks have been compared by varying the parameters of Radar signals like Bandwidth, Operating Frequency, and Satellite Altitude. From the results, it was observed that Antenna Footprints vary inversely with the Operating Frequency and Grazing Angle of Radar © 2022 IEEE.

关键词： Synthetic aperture radar

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A Machine Learning Model for Predicting Internet Addiction in Teenage and Young Students

A Machine Learning Model for Predicting Internet Addiction i...

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Applied Intelligence and Computing (AIC), IEEE World Conference on

作者： Geetika Johar Ravindra Patel Dept. of Computer Science & Engineering University Institute of Technology RGPV Bhopal India Dept. of Computer Applications University Institute of Technology RGPV Bhopal India

ISBN: (数字)9798350384598

ISBN: (纸本)9798350384604

Internet addiction is becoming one of the critical issues among teenagers and young university students. This habit not only negatively impacts the student’s learning performance, but also affects the student’s physical and mental health. This paper is focusing on designing a Machine Learning (ML) model for accurately identifying internet addiction. The model incorporates data preprocessing and feature selection techniques for reducing the computational complexity. Next, five different ML algorithms have been implemented and compared to identify appropriate ML algorithms. The identified ML model has been trained using the behavioral features of the students for predicting internet addiction. The experiments have been carried out and the performance of the models has been measured. The results demonstrate that a random forest classifier provides 83% accurate detection for university students and 96% accurate results are provided by an SVM-based classifier for teenager internet addiction detection. Therefore, by using the entire observation of experiments it is found that the proposed model can successfully identify internet addiction in students by analyzing the student's behavioral features.

关键词： Machine learning algorithms Accuracy Addiction Computational modeling Focusing Mental health Predictive models Prediction algorithms Internet Random forests

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Optimization Effects of Rotating Transmitarray for Direction-of-Arrival Estimation with a Single Antenna

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IEICE Communications Express 2025年第6期14卷 210-213页

作者： Ryusuke Sunagawa Hibiki Shiiba Makoto Sano Ryuji Kuse Takeshi Fukusako Dept. of Computer Science and Electrical Engineering Kumamoto University Kumamoto Japan Faculty of Advanced Science and Technology Kumamoto University Kumamoto Japan

This paper discusses the optimization effects of a transmitarray on a direction-of-arrival (DOA) estimation using the transmitarray and a single receiving antenna. The transmitarray consists of 1-bit elements with 0° and 180° transmission phases. The transmission phase distribution was optimized using a genetic algorithm and compared to a random distribution. The optimized transmitarray achieves a DOA estimation accuracy comparable to that of a conventional system using a 3-element linear array antenna. The root mean square error (RMSE) of the optimized system exhibits a decreasing trend as the signal-to-noise ratio (SNR) increases. Notably, at an SNR of 20 dB, the RMSE is 20° lower than that of the 3-element linear array antenna.

关键词： Estimation Direction-of-arrival estimation Linear antenna arrays Accuracy Antenna radiation patterns Transmitting antennas Optimization Signal to noise ratio Receiving antennas Vectors

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COVID-19 Image Retrieval Using Siamese Deep Neural Network and Hashing Technique

COVID-19 Image Retrieval Using Siamese Deep Neural Network a...

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Conference on Information and Knowledge Technology

作者： Farsad Zamani Boroujeni Doryaneh Hossien Afshari Fatemeh Mahmoodi Dept. of Computer Engineering Science and Research Branch Tehran Iran Dept. of Computer Engineering Isfahan (Khorasgan) Branch Isfahan Iran

Medical images are crucial for early diagnosis and are increasingly important in modern medicine. This study presents a medical image retrieval system using a Siamese neural network with 13 layers. The system uses the Minimum Redundancy Maximum Relevance (mRMR) technique to extract deep features from the Siamese, and then uses binary hashing to retrieve similar images using Hamming distance. The experimental results on Covid-19 dataset show that the proposed method improves lung image retrieval by over 6% compared to previous methods, achieving an average accuracy of 93.83% and 92.73% in 5 and 10 retrieved images, respectively.

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Orchestration-Aware Optimization of ROS2 Communication Protocols

Orchestration-Aware Optimization of ROS2 Communication Proto...

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Design, Automation and Test in Europe Conference and Exhibition

作者： Mirco De Marchi Nicola Bombieri Dept. of Engineering for Innovation Medicine University of Verona Italy Dept. of Computer Science University of Verona Italy

ISBN: (数字)9783981926385

ISBN: (纸本)9798350348606

The robot operating system (ROS) standard has been extended with different communication mechanisms to address real-time and scalability requirements. On the other hand, containerization and orchestration platforms like Docker and Kubernetes are increasingly being adopted to strengthen platform-independent development and automatic software deployment. In this paper, we quantitatively analyze the impact of topology, containerization, and edge-cloud distribution of ROS nodes on the efficiency of the ROS2 communication protocols. We then present a framework that automatically binds the most efficient ROS protocol for each node-to-node communication by considering the architectural characteristics of both software and edge-cloud computing platforms. The framework is available at https://***/PARCO-LAB/ros4k.

关键词： Protocols Service robots Scalability Operating systems Software Real-time systems Topology

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Enhancing Human Safety Through IoT-Integrated Smart Helmet Technology

Enhancing Human Safety Through IoT-Integrated Smart Helmet T...

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Expert Clouds and Applications (ICOECA), International Conference on

作者： Venkatesh K Harshitha Jodu Sree Kanthi P Yatheesh Kumar Reddy K Sumalatha R Dept. Computer Science and Engineering (Data Science) Srinivasa Ramanujan Institute of Technology Anantapur India

ISBN: (数字)9798350385793

ISBN: (纸本)9798350385809

The smart helmet's characteristics are meant to identify and report whether or not a wearer has consumed alcohol while donning a helmet. Road accidents are increasing as a result of riders drinking alcohol and not wearing helmets. In the modern world, thousands of people lose their lives in auto accidents each year. Wearing a smart helmet can typically lower the number of accidents. The primary objective of this research study is to create a wearable helmet that can both detect alcohol and prevent accidents without the need for a helmet. Whether the user is wearing a helmet is determined by the limit switch. The rider's breath is tested by the Gas sensor to determine whether alcohol is present. If the rider has ingested alcohol or is not wearing a helmet, the bike will not start. Only when a helmet is on and there are no indications of intoxication can the bike be started. System construction is done by sensor actions.

关键词： Cloud computing Head Road accidents Switches Alcoholic beverages Position measurement Safety

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