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1st IEEE International Conference on Cognitive Robotics and Intelligent systems, ICC - ROBINS 2024

作者： Natarajan, Yuvaraj Sri Preethaa, K.R. Pandian, Sasikumar Geetha, Shruti Umapathi Senthilkumar, Sujadharshini Kpr Institute of Engineering and Technology Department of Computer Science and Engineering Coimbatore India Kyungpook National University Department of Robot and Smart System Engineering Daegu41566 Korea Republic of

ISBN: (纸本)9798350372748

In this ever-evolving healthcare landscape, with the integration of cutting-edge technology, this study has exemplified a medical chatbot by harnessing the advanced Llama2 model. This chatbot places significant emphasis on instance training by changing and adding the meta, which enables it to continuously adapt and stay updated with the latest medical developments. Its adaptability also encompasses capabilities such as question-answering and mining knowledge from an extensive meta dataset. By leveraging its extensive ability to learn medical terminology, the chatbot provides precise and real-time responses to medical inquiries by establishing itself as a reliable information source. Access to a specially collected meta dataset further enhances its ability to deliver comprehensive medical insights while self-supervised learning techniques enhance the model efficacy. Consequently, this chatbot reshapes the way individuals access precise medical information by enabling a new era of advanced digital healthcare assistants in the digital age. © 2024 IEEE.

关键词： Supervised learning

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Interference Suppression and Jitter Elimination Ability-Based Adaption Tracking Guidance for Robotic Fishes

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 126-137页

作者： Dongfang Li Jie Huang Rob Law Xin Xu Limin Zhu Edmond Q.Wu IEEE the School of Electrical Engineering and Automation Fuzhou University the Key Laboratory of System Control and Information Processing Ministry of Education the School of Electrical Engineering and Automation Fuzhou University 5G+Industrial Internet Institute Fuzhou University the University of Macau the College of Mechatronics and Automation National University of Defense Technology the School of Mechanical Engineering Shanghai Jiao Tong University the Department of Computer Science and Engineering Shanghai Jiao Tong University

This work presents an adaptive tracking guidance method for robotic fishes. The scheme enables robots to suppress external interference and eliminate motion jitter. An adaptive integral surge line-of-sight guidance rule is designed to eliminate dynamics interference and sideslip issues. Limited-time yaw and surge speed observers are reported to fit disturbance variables in the model. The approximation values can compensate for the system's control input and improve the robots' tracking ***, this work develops a terminal sliding mode controller and third-order differential processor to determine the rotational torque and reduce the robots' run jitter. Then, Lyapunov's theory proves the uniform ultimate boundedness of the proposed method. Simulation and physical experiments confirm that the technology improves the tracking error convergence speed and stability of robotic fishes.

关键词： Adaptive integral surge line-of-sight approximation robotic fish speed observer

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Development of a Raw Oyster Volume Estimation system Based on U²-Net

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Journal of Institute of Control, Robotics and systems 2024年第10期30卷 1110-1121页

作者： Kang, Min Jin Kim, Sung Jae Suh, Jin Ho Department of Intelligent Robot Engineering Pukyong National University Korea Republic of The Industrial Science Technology Research Center Pukyong National University Korea Republic of Mechanical System Engineering Pukyong National University Korea Republic of

This study proposes an advanced image processing algorithm and a volume estimation system for automating the oyster process. Using top and side cameras, our algorithm effectively captures object features under varying moisture and lighting conditions, mitigating light reflection issues. The image processing algorithm consists of object extraction, capturing, feature extraction, and width calculation algorithms. These components accurately extract objects from multiple camera inputs, store the images, and calculate object width using the side camera, providing essential data for volume estimation based on the disc method. Experiments conducted on model and raw oysters demonstrated the system’s robust performance, achieving classification accuracies of 98.5% and 100%, respectively. The system’s high accuracy and reliability across various environmental conditions make it suitable for size classification tasks. © ICROS 2024.

关键词： Shellfish

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Performance Analysis of Disruptive Instances in Cloud Environment 16

Performance Analysis of Disruptive Instances in Cloud Enviro...

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16th International Conference on COMmunication systems and NETworkS, COMSNETS 2024

作者： Nandy, Pranab Saha, Rounak Satpathy, Anurag Chakraborty, Sandip Addya, Sourav Kanti National Institute of Technology Karnataka Cloud and Smart System Services Lab Department of Computer Science and Engineering Surathkal India Missouri University of Science and Technology Cloud and Smart System Services Lab Department of Computer Science and Engineering United States Indian Institute of Technology Kharagpur Cloud and Smart System Services Lab Department of Computer Science and Engineering India

ISBN: (纸本)9798350383119

Virtualization enables the service providers (SPs) to logically partition the resources into virtual machines (VM) instances. Real-world SPs such as Amazon, Google, Microsoft Azure, IBM, and Oracle provide different flavors of VM instances, such as on-demand, reserved, and low-cost or spot, depending on the type of application hosted. The on-demand instances are short-term and typically incur a higher cost than reserved instances that are provisioned for a longer duration at a discounted rate. Low-cost or spot instances are cost-effective compared to on-demand but are reclaimable by the SPs. The SPs often claim that the on-demand and spot instances achieve similar performance, but it is far from that. This paper studies the performance of spot instances via rigorous experimentation over commercial SPs such as Amazon AWS and Microsoft Azure. Real-world evaluations affirm that spot instances perform poorly compared to their on-demand counterpart concerning memory, CPU, disk read, and write operations. We identify such instances as disruptive and name them so because it does not fulfill the performance, durability, and flexibility expectations like an on-demand instance having the same configuration. We also perform hypothesis testing over the experimental data obtained to corroborate our claim further. © 2024 IEEE.

关键词： Cloud Computing Disruptive Instance On-demand Spot Instance

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Advancing Stimulator technology with Digital Goniometer Feedback: Design and Assessment 10

Advancing Stimulator Technology with Digital Goniometer Feed...

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10th International Conference on Advanced Computing and Communication systems, ICACCS 2024

作者： Praveen, K. Leena Jasmine, A.J. Aathilakshmi, S. Balaji, S. Aravind, E. Sarithra, P. Chennai Institute of Technology Department of Electronics and Communication Engineering Chennai India Vellammal Engineering College Department of Electronics and Communication Engineering Chennai India Center for System Design Chennai Institute of Technology Chennai India

ISBN: (纸本)9798350384369

The primary aim of the work is to create and implement a feedback circuit to enhance the digital goniometer's capabilities in measuring elbow range of motion. This system leverages the bending losses within the optical fiber to precisely measure the elbow's range of motion. The overarching idea is to measure the elbow's range of motion accurately and generate a feedback signal that is proportionate to the measured range. This feedback signal will then be utilized to adjust the intensity of the stimulation current in the functional electrical stimulator. This adaptive approach ensures that the stimulation intensity varies accordingly. Additionally, this project includes a three-validation step where the accuracy of the designed digital goniometer is compared with a recognized gold standard. The accuracy level is reached 99% compare to the existing technique. This research mainly focused on physically challenged people in sports and many varieties. Implementation is done using machine learning algorithm and MATLAB is used for simulation. © 2024 IEEE.

关键词： Optical fibers

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A Study on Trajectory Tracking of an ROV for Underwater Glider Recovery Based on Adaptive Backstepping Control Using a Command Filter

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Journal of Institute of Control, Robotics and systems 2024年第11期30卷 1266-1276页

作者： Lee, Mun Haeng Kim, Sung Jae Lee, Jung Woo Suh, Jin Ho Department of Intelligent Robot Engineering Pukyong National University Korea Republic of The Industrial Science Technology Research Center Pukyong National University Korea Republic of Korea Institute of Robotics & Technology Convergence Korea Republic of Department of Mechanical System Engineering Pukyong National University Korea Republic of

This paper presents a path for a remotely operated vehicle (ROV) to retrieve an underwater glider and proposes a backstepping-based control method that utilizes a command filter and an adaptive term for trajectory tracking. The ROV path, which consists of diving, approaching, and ascending to reach the underwater glider while minimizing wave disturbances, is generated using a fifth-order polynomial trajectory generation method. To address the complexity of the backstepping method, the virtual control signal is replaced with a command filter signal. Additionally, a compensation mechanism is configured to suppress filter errors. An adaptive term based on Lyapunov stability is incorporated to compensate for lumped disturbances to enhance system control performance. The stability of the entire control system is proven through Lyapunov stability theory. To verify the performance of the proposed controller, simulations are conducted to track the configured path in a marine environment. This environment includes waves and ocean currents, with wave disturbances modeled based on the movement of water particles in waves. The simulation results demonstrate that the proposed controller achieves superior tracking performance and resilience against disturbances compared with the proportional-integral-differential controller. © 2024, Institute of Control, Robotics and systems. All rights reserved.

关键词： Remotely operated vehicles

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Sagittarius: Floating Self Navigating Robot for Monitor the Water Quality of Rural Reservoirs 6

Sagittarius: Floating Self Navigating Robot for Monitor the ...

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6th International Conference on Advancements in Computing, ICAC 2024

作者： Pedige, Nishan Ilandara Abeywarna, Thaveesha Amarasinge, Randheera Bandara, Menuka Nawarathna Javakody, Anuradha Gamage, Narmada Sri Lanka Institute of Information Technology Department of Computer System Engineering Malabe Sri Lanka

ISBN: (纸本)9798331517878

This paper proposes an optimal solution for monitoring water quality in Sri Lanka, where reservoirs are essential for daily life and agriculture, especially in rural areas. Despite its importance, 3.6 million communities are affected by severe water quality problems, contributing to a high incidence of chronic kidney diseases. While water purification plants are the only solution, high salinity and hardness often make these sources unsuitable. Many rural reservoirs remain unpurified but could potentially provide safe water if properly monitored and maintained. Yet water sources are frequently contaminated by chemical waste and activities associated with agricultural business but effective solutions for continuous water quality monitoring are lacking. This study introduces an autonomous robot equipped with advanced sensors to monitor critical water quality parameters in real-time. By integrating machine learning for data analysis and prediction, Sagittarius enables continuous assessment of reservoir water quality, providing timely insights for public health protection. Field tests demonstrate a prediction accuracy exceeding 98.5%, supporting proactive water management and monitoring. This system has shown potential to aid in early detection of contamination, informing authorities promptly for preventive actions, and enabling sustainable water usage. This solution can significantly contribute to public health protection and informed water resource management decisions. © 2024 IEEE.

关键词： Reservoirs (water)

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Comparison of Machine Learning Methods for Air Quality Prediction Based on Particulate Matter (PM2.5)

Comparison of Machine Learning Methods for Air Quality Predi...

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2025 International Conference on Advancement in Data Science, E-learning and Information system, ICADEIS 2025

作者： Mar'i, Farhanna Marianingsih, Susi Abdillah, Rifqi Elfaiz, Ersha Aisyah Setyo Prayoga, Riza Akhsani Fahmi, Muhamad Universitas Negeri Surabaya Faculty of Engineering Department of Informatics Engineering Surabaya Indonesia Jayapura University of Science and Technology Department of Information System Jayapura Indonesia Universitas Negeri Surabaya Faculty of Engineering Department of Information Technology Education Surabaya Indonesia Universitas Airlangga Faculty of Science and Technology Department of Biomedical Engineering Surabaya Indonesia

ISBN: (纸本)9798331513320

Particulate PM2.5 has a major effect on human health compared to other types of pollutants such as NO2, 03, CO, and SO2. PM2.5 is the worst type of major pollutant for human health that can cause various types of serious diseases and even death. PM2.5 is defined as an ambient air particle, which is one of the particle elements found in the free air of the earth's surface in the troposphere layer, which is very small in size, reaching 2.5 pollutants. The method of predicting air quality index values can be done using machine learning techniques with time series data analysis. This study will compare machine learning methods with two approaches, namely statistical regression with RF and ARIMA and deep learning method, namely LSTM. Based on the research results, the best machine learning method approach is statistical regression, namely the RF method with accuracy evaluation using RMSE, MAE, and MSE, which are respectively with a minimum value of 0.162, 0.108, and 0.026, followed by the LSTM and ARIMA methods. © 2025 IEEE.

关键词： Polycyclic aromatic hydrocarbons

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A reliable method for data aggregation on the industrial internet of things using a hybrid optimization algorithm and density correlation degree

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Cluster Computing 2024年第6期27卷 7521-7539页

作者： Heidari, Arash Shishehlou, Houshang Darbandi, Mehdi Navimipour, Nima Jafari Yalcin, Senay Department of Software Engineering Haliç University Istanbul34060 Turkey Department of Computer Engineering Tabriz Branch Islamic Azad University Tabriz Iran Pôle Universitaire Léonard de Vinci Paris France Department of Computer Engineering Kadir Has University Istanbul Turkiye and Future Technology Research Center National Yunlin University of Science and Technology Yunlin Douliou64002 Taiwan Department of Energy System Engineering School of Engineering and Natural Sciences Bahçeşehir University Istanbul Turkey

The Internet of Things (IoT) is a new information technology sector in which each device may receive and distribute data across a network. Industrial IoT (IIoT) and related areas, such as Industrial Wireless Networks (IWNs), big data, and cloud computing, have made significant strides recently. Using IIoT requires a reliable and effective data collection system, such as a spanning tree. Many previous spanning tree algorithms ignore failure and mobility. In such cases, the spanning tree is broken, making data delivery to the base station difficult. This study proposes an algorithm to construct an optimal spanning tree by combining an artificial bee colony, genetic operators, and density correlation degree to make suitable trees. The trees’ fitness is measured using hop count distances of the devices from the base station, residual energy of the devices, and their mobility probabilities in this technique. The simulation outcomes highlight the enhanced data collection reliability achieved by the suggested algorithm when compared to established methods like the Reliable Spanning Tree (RST) construction algorithm in IIoT and the Hop Count Distance (HCD) based construction algorithm. This proposed algorithm shows improved reliability across diverse node numbers, considering key parameters including reliability, energy consumption, displacement probability, and distance. © The Author(s) 2024.

关键词： Reliability

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Backup subscription scheme for differential protection using IEC61850-9-2 sampled values

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Energy Informatics 2024年第1期7卷 110页

作者： Katoulaei, Mohammad Khalili Rahmani, Aamir Høidalen, Hans Kristian Oleinikova, Irina Mork, Bruce Department of energy systems Norwegian University of Science and Technology Trondheim Norway Department of electrical power system Michigan Technical University Michigan United States Department of Electrical Power Engineering Norwegian University of Science and Technology Trondheim Norway Department of Electrical and Computer Engineering Michigan Technological University HoughtonMI49931 United States

In IEC-61850-based digital substations, the protection IED’s performance is dependent on merging unit’s vendor implementation, communication networks, and measurement circuit’s health conditions. As the process bus Sampled Value(SV) enables the availability of all sensor data on a communication network, this paper proposes a Backup Subscription scheme (BSS) for a transformer differential protection (87T, PDIF) function. BSS utilizes sensor data in digital substations to achieve a flexible protection scheme using a dynamic subscription feature. Thus, in case of failure of one sensor, differential protection would be maintained. The paper presents the implementation and verification of a prototyped scheme using a Hardware-in-the-loop simulation test bed. The main result is that BSS integration into differential protection ensures its dependability and security. Moreover, delay compensation and seamless switching feature increases the availability of differential protection. © The Author(s) 2024.

关键词： Hardware-in-the-loop simulation

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