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International Conference on Transportation Information and Safety (ICTIS)

作者： Xin Su Zhang Wen Bing Wu De-Shan Chen State Key Laboratory of Maritime Technology and Safety(SKL MTS) Wuhan University of Technology Intelligent Transport Systems Research Centre(ITSC) Wuhan University of Technology National Engineering Research Center for Water Transport Safety (WTSC) Wuhan University of Technology Wuhan China Changjiang Waterway Bureau Wuhan China Inland Port and Shipping Industry Research Co. Ltd. of Guangdong Province China Academician Workstation of China COSCO SHIPPING Co. Ltd China Wuhan China

Cooperative control of autonomous underwater vehicles is widely used in many ocean missions. This paper studies the distributed model predictive formation tracking control problem for a group of autonomous underwater vehicles. Firstly, a nonlinear model predictive control method is proposed based on the dynamic characteristics of AUV motion. Secondly, the formation trajectory tracking problem is decomposed into the optimization problem of each individual in the formation, and the corresponding reference trajectories are designed for each individual at each position in the formation. The follower AUV should track the leader according to the specified formation mode. Finally, the optimization problem of each individual is solved in a distributed manner, which effectively reduces the complexity of the calculation problem. At the same time, a cost function is designed to calculate the control input of each individual based on the individual optimization problem, which maintains a balance between computational complexity and control performance, and the control input should depend on the actual constraints. The simulation results verify the effectiveness of the proposed algorithm and theoretical results.

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The Causal Effect of Personality Traits on the Mental Health in Breast Cancer Patients Under the Occurrence of Negative Life Events 18th

The Causal Effect of Personality Traits on the Mental Hea...

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18th EAI International Conference on Pervasive Computing Technologies for Healthcare, PervasiveHealth 2024

作者： Petrakis, Aristeidis Mylona, Eugenia Kourou, Konstantina Manikis, Georgios Kondylakis, Haridimos Marias, Kostas Poikonen-Saksela, Paula Simos, Panagiotis Karademas, Evangelos Mazzocco, Ketti Pat-Horenczyk, Ruth Sousa, Berta Fotiadis, Dimitrios I. Computational Biomedicine Laboratory FORTH-ICS Heraklion Greece Unit of Medical Technology and Intelligent Information Systems Department of Materials Science and Engineering University of Ioannina Ioannina Greece Foundation for Research and Technology-Hellas Institute of Molecular Biology and Biotechnology Department of Biomedical Research Ioannina Greece Helsinki University Hospital Comprehensive Cancer Center and Helsinki University Helsinki Finland School of Medicine University of Crete Heraklion Greece Department of Psychology University of Crete Rethymno Greece Applied Research Division for Cognitive and Psychological Science European Institute of Oncology Milan Italy Department of Oncology and Hemato-oncology University of Milan Milan Italy School of Social Work and Social Welfare The Hebrew University of Jerusalem Jerusalem Israel Breast Unit Champalimaud Clinical Centre/Champalimaud Foundation Champalimaud Research Lisboa Portugal

ISBN: (纸本)9783031855719

Using longitudinal data from Portugal, Italy, Finland, and Israel, this article attempts to explore the causal relationship between mental health and the Big Five personality traits of breast cancer patients with the appearance of adverse life events. The main conclusion is that patients with high scores in the Big Five personality traits index enjoy better mental health status than patients with low scores in that index. In addition, there is a significant negative correlation between mental health deterioration and personality traits as an index and as individual traits. The negative impact on the mental health of cumulative adverse life events is significant and cannot be moderated by personality traits. Single negative life events have a positive correlation with mental health status deterioration, though not all of them are significant and only work-related problems can moderated significantly by high scores in the personality trait index. Moreover, the most important control variable are the state of exercise, which if it changes from active to not active causes a significant drop in the mental health score and cancer stage. Lastly, this causal relationship is validated by the prediction accuracy of AI/ML models. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications engineering 2025.

关键词： Active learning

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The impact of ground control points for the 3D study of grapevines in steep slope vineyards

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Procedia Computer Science 2024年 239卷 2301-2307页

作者： Oiliam Stolarski José Martinho Lourenço Emanuel Peres Raul Morais Joaquim J. Sousa Luís Pádua Centre for the Research and Technology of Agro-Environmental and Biological Sciences (CITAB) University of Trás-os-Montes e Alto Douro (UTAD) 5000-801 Vila Real Portugal Departamento de Geologia e Pólo do Centro de Geociências (CGeo) UTAD 5000-801 Vila Real Portugal Engineering Department School of Science and Technology UTAD 5000-801 Vila Real Portugal Institute for Innovation Capacity Building and Sustainability of Agri-Food Production UTAD 5000-801 Vila Real Portugal Centre for Robotics in Industry and Intelligent Systems (CRIIS) INESC Technology and Science (INESC-TEC) 4200-465 Porto Portugal

Data acquisition through unmanned aerial vehicles (UAVs) has become integral to the study of agricultural crops, especially for multitemporal analyses spanning the entire growing season. Ensuring accurate data alignment is essential not only to maintain data quality but also to leverage the continuous monitoring of the same area over time. Ground control points (GCPs) play a critical role in geolocating UAV data. Their absence can lead to planimetric and altimetric discrepancies, which are particularly impactful in 3D plant-level studies. This study is centered on the examination of misalignment effects in a challenging steep slope vineyard environment and their impacts on 3D alignment accuracy. For this purpose, a UAV equipped with an RGB camera to capture imagery at two distinct flight heights. Various scenarios, each involving a different number of GCPs, were assessed to evaluate their impact on alignment precision. The methodology employed holds potential for assessing geolocation accuracy in complex 3D environments, providing value insights for vineyard monitoring.

关键词： unmanned aerial vehicles photogrammetric processing point clouds geolocation precision viticulture

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A Memristor Based Chaotic Oscillator for Weak Signal Detection and Its Circuitry Realization

Research Square

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research Square 2021年

作者： Dong, Kaifeng Xu, Kun Zhou, Youyou Zuo, Chao Wang, Leimin Zhang, Chuanke Jin, Fang Song, Junlei Mo, Wenqin Hui, Yajuan School of Automation China University of Geosciences Wuhan430074 China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China Wuhan Second Ship Design and Research Institute Wuhan430064 China

A new type of weak signal detection system that combines the memristor and Van der pol-Duffing chaotic system has been proposed in this paper, and the dynamic characteristics of the system are studied. It is observed that the system can change from a chaotic state to a periodic state under different driving force amplitudes. Moreover, as compared with several classical chaotic oscillators, the numerical simulation results show that the system has stronger anti-noise performance with the detectable signal-to-noise ratio reaches -163dB, and has a wider detection range. Its detection accuracy is up to 1 × 10−9. More importantly, this paper provides the circuit implementation scheme of the system, and the weak signal can be detected with our designed circuit. This may offer a possible way for weak signal detection system with good performance in anti-noise performance, detection range and accuracy. © 2021, CC BY.

关键词： Memristors

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A Machine Learning-Based Bayesian Model for the Development of Highly-Effect Port State control Inspection Policy

SSRN

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SSRN 2022年

作者： Yang, Zhisen Yu, Qing Yang, Zaili Wan, Chengpeng College of Urban Transportation and Logistics Shenzhen Technology University Shenzhen China Intelligent Transportation Systems Research Center Wuhan University of Technology Wuhan China National Engineering Research Centre for Water Transport Safety Wuhan China School of Navigation Jimei University Xiamen China Research Institute Liverpool John Moores University Liverpool United Kingdom

PSC inspections are of great importance for port authorities to improve vessel quality and ensure maritime safety around the world. However, the increasing rate and duration of ship detention indicates that serious deficiencies of visiting vessels still largely exist and the relevant scientific solutions are highly demanded. This research aims to improve the inspection efficiency and reduce the duration of detention through developing a data-driven machine learning (ML) based BN model. New risk variables influencing the duration of ship detention, especially deficiency types, are identified based on the established database containing detention records within the jurisdiction of Paris MoU from January 2015 to March 2022. Thorough analysis via the developed model enables to identify the deficiency types with significant effects on the duration of detention, reveal the mutual dependencies among these deficiency types, as well as clarify the major and abnormal deficiency types in different port states. Managerial suggestions and insights for port authorities, i.e., high priority is given on deficiency types with a huge effect on duration of detention, different countries should conduct specific actions on major and abnormal deficiency types identified within their jurisdiction, are given based on the analysis results obtained from the proposed model to stimulate the rational formation of corresponding inspection regulations. This research will provide good reference for effectively reducing the duration of ship detention, improving vessel quality, and ensuring maritime safety. © 2022, The Authors. All rights reserved.

关键词： Bayesian networks

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Design of intelligent Meridian Magnetotherapy instrument and Monitoring system based on TCM

Design of Intelligent Meridian Magnetotherapy instrument and...

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6th International Conference on intelligent Computing and Signal Processing (ICSP)

作者： Shuheng Ren Dongsong Yan Xu Yang Yuqian Liao Wenlong Yang Zhihao Liu School of International Energy Jinan University Zhuhai City Guangdong Province Guangdong elcctrical and intelligent control engineering technology research centre Zhuhai City Guangdong Province

An intelligent acupoint magnetotherapy instrument, used in physiotherapy as well as simultaneous magnetotherapy acupoint with multiple acupoints, and its monitoring system are developed. Based on TCM meridian theory, it can be designed patterns of health preservation, self-defined magnetotherapy, auxiliary medical treatment for common diseases and stuff. Through the recommendation of accurate acupoints, the instrument meets the needs of different groups and reduces the threshold of magnetotherapy equipment. At the same time, through the five elements music accompanied with the course of treatment, this instrument realizes the comprehensive treatment of magnetic and Wuyin Therapy and finally improve the effect of physiotherapy. At the same time, according to the data uploaded by the instrument, the monitoring system, with the functions of displaying real-time parameter, analyzing magnetotherapy instrument and course of treatment, which increases the user experience. A questionnaire is also used to design the course recommendation based on the user's own situation, improves the intelligence of the instrument. Therefore, the design has the characteristics of safety, convenience, simplification and intelligence. As it can well meet the needs of health preservation, it also has a good application prospect in the field of intelligent medical devices.

关键词： Medical devices Instruments Medical treatment Magnetic devices Signal processing Real-time systems User experience

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Double Deep Q-learning for Anti-saturation Attack Problem of Warship Group

Double Deep Q-learning for Anti-saturation Attack Problem of...

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Digital Twins and Parallel Intelligence (DTPI), IEEE International Conference on

作者： Wei Li Gang Xiong Hao Tao Yunjun Han Fang Wang Xisong Dong Zhen Shen State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences School of Artificial Intelligence University of Chinese Academy of Sciences Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences China China Ship Development and Design Center Wuhan China School of Control Science and Engineering (CSE) Shandong University Jinan China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan China

Anti-saturation attack (ASA) strategy is vital for the survival of a warship group, and attracts the focus of many researchers. In this paper, the dynamics of ASA is formulated as a Markov Decision Process (MDP) with an enhanced states space since those characters are involved, such as the formation and detection and interception areas of warship group. A reinforcement learning method (Double Deep Q-leaning, DDQN) is developed to solve the problem and deal with the curse of dimensionality whereby the cost-to-go value is calculated by a marine engagement simulation system. A heuristic defense algorithm guided by field expert knowledge is designed for comparison. The experimental results show that the DDQN method performs better in anti-saturation attack scenarios.

关键词： Industries Heuristic algorithms Digital twin Conferences Knowledge based systems Reinforcement learning Markov processes

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A B-Spline Global Optimization Algorithm for Optimal Power Flow Problem 6th

A B-Spline Global Optimization Algorithm for Optimal Power F...

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6th World Congress on Global Optimization, WCGO 2019

作者： Gawali, Deepak D. Patil, Bhagyesh V. Zidna, Ahmed Nataraj, Paluri S. V. Vidyavardhini’s College of Engineering and Technology Palghar India Cambridge Centre for Advanced Research and Education In Singapore Singapore Singapore John Deere Technology Centre Magarpatta City Pune India LGIPM University of Lorraine Metz France Systems and Control Engineering Indian Institute of Technology Bombay Mumbai India

ISBN: (纸本)9783030218027

This paper addresses a nonconvex optimal power flow problem (OPF). Specifically, a new B-spline approach in the context of OPF problem is introduced. The applicability of this new approach is shown on a real-world 3-bus power system. The numerical results obtained with this new approach for this problem a 3-bus system reveal a satisfactory improvement in terms of optimality when compared against traditional interior-point method based MATPOWER toolbox. Similarly, the results are also found to be satisfactory with respect to the global optimization solvers like BARON and GloptiPoly. © 2020, Springer Nature Switzerland AG.

关键词： Constrained optimization

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Robotic Single-Micropipette Enucleation Method for Zona-free Oocytes

Robotic Single-Micropipette Enucleation Method for Zona-free...

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Chinese control Conference (CCC)

作者： Yidi Zhang Yaowei Liu Minghui Li Dong Sun Xin Zhao Institute of Robotics and Automatic Information System (IRAIS) and the Tianjin Key Laboratory of Intelligent Robotic (tjKLIR) Nankai University Tianjin China Department of Biomedical Engineering City University of Hong Kong Hong Kong SAR China Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Shenzhen China Centre for Robotics and Automation Shenzhen Research Institute City University of Hong Kong Shenzhen China

Somatic cell nuclear transfer is a mammalian cloning method that involves replacing the oocyte nucleus with a somatic cell nucleus. One of the most critical steps in this process is the efficient production of large numbers of enucleated oocytes. While a single-micropipette-based manual enucleation method has been widely used in manual cloning, it is still a manual operation that requires exceptional technical skills and experience. Additionally, it is difficult to accurately control the amount of enucleation and to meet the demand for high-throughput enucleation. Therefore, we propose a robotic enucleation method using a single micropipette for zona-free oocytes, which allows for the detection and control of the amount of enucleation, as well as continuous enucleation on a large scale. A single oocyte enucleation can be completed in less than 13 seconds. This robotic enucleation method provides a solution for enhancing the operational efficiency of robotic somatic cell nuclear transfer.

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Fuzzy Logic Based Approach for Navigation Obstruction Risk of shipwreck in Yangtze River

Fuzzy Logic Based Approach for Navigation Obstruction Risk o...

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International Conference on Transportation Information and Safety (ICTIS)

作者： Xiaohe Dong Zhang Wen Bing Wu State Key Laboratory of Maritime Technology and Safety(SKL MTS) Wuhan University of Technology Intelligent Transport Systems Research Centre(ITSC) Wuhan University of Technology Wuhan China National Engineering Research Center for Water Transport Safety (WTSC) Wuhan University of Technology Wuhan China Changjiang Waterway Bureau Wuhan China State Key Laboratory of Maritime Technology and Safety(SKL MTS) Wuhan University of Technology Inland Port and Shipping Industry Research Co. Ltd. of Guangdong Province China Acadmician Workstation of China COSCO SHIPPING CO. Ltd China Wuhan China

In order to effectively prevent accidents caused by shipwreck, this paper proposes a fuzzy logic approach for navigation obstruction risk of shipwreck. Firstly, the historical accidents in the Yangtze River are analyzed to identify the influencing factors for navigation obstruction of shipwreck. These factors are classified into four categories, which are ship conditions, traffic environment, distance from the sensitive areas and natural environment. Secondly, after fuzzifying the influencing factors based on theoretical analysis and statistical data, a fuzzy rule base is established and the crisp values for navigation obstruction risk of shipwreck are obtained by defuzzification. Thirdly, the proposed approach is applied to the navigation obstruction risk assessment of several historical shipwrecks in Yangtze River. The assessment conclusions derived from the approach are consistent with historical evaluation experience, demonstrating the feasibility and practicality of the approach.

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