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Automatic Facial Asymmetry Analysis for Elderly Stroke Detection by using Cosine Similarity 19

Automatic Facial Asymmetry Analysis for Elderly Stroke Detec...

19th International Conference on Electrical engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2022

作者： Kaewmahanin, Watchara Rassameecharoenchai, Teerameth Jutharee, Wisanu Tongskulroongruang, Thienrawit Wiphunawat, Paphatchaya Jennawasin, Tanagorn Kaewkamnerdpong, Boonserm Naresuan University Faculty of Allied Health Sciences Department of Cardiothoracic Technology Phitsanulok Thailand King Mongkut's University of Technology Thonburi Institute of Field Robotics and Automation Bangkok Thailand Mongkut's University of Technology Thonburi Department of Control Systems and Instrumentation Engineering Bangkok Thailand King Mongkut's University of Technology Thonburi Biological Engineering Program Faculty of Engineering Bangkok Thailand

ISBN: (纸本)9781665485845

For acute stroke patients, time to recognize the stroke symptom onset is crucial for the lifesaving treatment. The automatic detection of stroke signs has been increasingly developed for practical use. The better timely classification results could allow better detection of the symptoms and avoid morbidity and mortality. In this study, we proposed using cosine similarity between the left and right sides of the face as a part of features for classifying the stroke elderly patients from healthy elderly participants. We employed our method on images from the Toronto NeuroFace dataset. The results showed high classification accuracy (the average accuracy of 97.8998% from 6 classification methods). These results indicate that the cosine similarity features can be useful to detect facial asymmetry and pose very promising potential for elderly stroke detection. © 2022 IEEE.

关键词： Patient treatment

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Comparative Study on Fall Detection using Machine Learning Approaches 19

Comparative Study on Fall Detection using Machine Learning A...

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19th International Conference on Electrical engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2022

作者： Tongskulroongruang, Thienrawit Wiphunawat, Paphatchaya Jutharee, Wisanu Kaewmahanin, Watchara Rassameecharoenchai, Teerameth Jennawasin, Tanagorn Kaewkamnerdpong, Boonserm King Mongkut's University of Technology Thonburi Department of Control Systems and Instrumentation Engineering Bangkok Thailand Institute of Field Robotics and Automation King Mongkut's University of Technology Thonburi Bangkok Thailand Naresuan University Faculty of Allied Health Sciences Department of Cardiothoracic Technology Phitsanulok Thailand King Mongkut's University of Technology Thonburi Biological Engineering Program Faculty of Engineering Bangkok Thailand

ISBN: (纸本)9781665485845

Falls are one of the most dangerous problems for the elderly. A reliable fall detection system can aid in reducing the harmful repercussions of an unintentional fall. The focus of this paper is on a dataset that includes signals from portable devices. We propose a simple feature selection approach to reduce the number of effective input attributes based on a voting strategy. The dataset is classified into three categories, i.e., pre-fall, fall and post-fall using various machine learning approaches. The computational time is significantly reduced for most of the classification algorithms, and the relative reduction reaches to 66.67% with decision tree algorithm. Classification accuracy can reach as high as 95.17% when using neural network, while the relative reductions on the classification accuracy due to the feature selection do not exceed 1.50%. © 2022 IEEE.

关键词： Decision trees

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A population randomization-based multi-objective genetic algorithm for gesture adaptation in human-robot interaction

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Science China(Information Sciences) 2021年第1期64卷 188-200页

作者： Luefeng CHEN Wanjuan SU Min LI Min WU Witold PEDRYCZ Kaoru HIROTA School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Department of Electrical and Computer Engineering University of Alberta Tokyo Institute of Technology

In recent years, vision-based gesture adaptation has attracted great attention from many experts in the field of human-robot interaction, and many methods have been proposed and successfully applied, such as particle swarm optimization and genetic algorithm. However, the reduction of the error and energy consumption of a robot while paying attention to more subtle attitude changes is very important and *** view of these problems, we propose a population randomization-based multi-objective genetic *** gesture signal is processed with a slight change by imitating the biological evolution mechanisms. In the proposed algorithm, a random out-of-order matrix is added in the process of population evolution synthesis to prevent the premature grouping convergence of the new population. The weights of the objective function and the elite retention strategy are adopted, and the most adaptable individuals in each generation are inherited directly in the next generation without any recombination or mutation. To verify the effectiveness of the algorithm, preliminary application experiments are performed on the gesture adaptation of a robotic arm. The results are compared with the original signal, and the comparison shows that by using the proposed method, the energy consumption is reduced, and the end error is decreased to less than 3 mm while ensuring the tracking effect of the robotic arm. These obtained results meet the communication requirements for human-robot interactions such as handshakes. Moreover, the proposed method has better performance, uses less energy, and has a smaller tracking error than the particle swarm optimization, the single-objective genetic algorithm, and the traditional multi-objective genetic algorithm. A preliminary application experiment indicates that the robotic arm can adapt to human gestures in real time.

关键词： multi-objective genetic algorithm gesture adaptation human-robot interaction

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Dynamic grouping of heterogeneous agents for exploration and strike missions

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Frontiers of Information Technology & Electronic engineering 2022年第1期23卷 86-100页

作者： Chen CHEN Xiaochen WU Jie CHEN Panos M.PARDALOS Shuxin DING School of Automation Beijing Institute of TechnologyBeijing100081China Department of Control Science and Engineering Tongji UniversityShanghai200092China Center for Applied Optimization Department of Industrial and Systems EngineeringUniversity of FloridaGainesvilleFL32611USA Signal and Communication Research Institute China Academy of Railway Sciences Corporation LimitedBeijing100081China

The ever-changing environment and complex combat missions create new demands for the formation of mission groups of unmanned combat *** study aims to address the problem of dynamic construction of mission groups under new *** are heterogeneous,and a group formation method must dynamically form new groups in circumstances where missions are constantly being *** our method,a group formation strategy that combines heuristic rules and response threshold models is proposed to dynamically adjust the members of the mission group and adapt to the needs of new *** degree of matching between the mission requirements and the group’s capabilities,and the communication cost of group formation are used as indicators to evaluate the quality of the *** response threshold method and the ant colony algorithm are selected as the comparison algorithms in the *** results show that the grouping scheme obtained by the proposed method is superior to those of the comparison methods.

关键词： Multi-agent Dynamic missions Group formation Heuristic rule Networking overhead

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Bio-inspired control by overlapping adaptive clusters: a vehicle platoon case study

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IFAC-PapersOnLine 2023年第2期56卷 1460-1465页

作者： Ovidiu Pauca Anca Maxim José M. Maestre Constantin F. Caruntu “Gheorghe Asachi” Technical University of Iasi Department of Automatic Control and Applied Informatics Blvd. D. Mangeron 27 700050 Iasi Romania University of Seville Department of Systems and Automation Engineering Camino Descubrimientos S/N.- Isla Cartuja 41092 Seville Spain

Clustering vehicles in a platoon by exchanging information through communication networks leads to an improvement in their performance with a moderate cooperation effort. In particular, in this paper, a bio-inspired methodology for overlapping coalitions of vehicles is proposed, which optimizes communication and control performance. The results obtained using the proposed adaptive clusters method are compared with the ones obtained by a conventional coalitional control strategy, and the comparison illustrates the improved efficiency of the proposed method.

关键词： Bio-inspired control coalitional control overlapping topology vehicle platoon

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Fault localization for intelligent automation systems

Fault localization for intelligent automation systems

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International Conference on Emerging Technologies and Factory automation (ETFA)

作者： Endre Erős Kristofer Bengtsson Knut Åkesson Electrical Engineering Systems and Control Department Automation Research Group Chalmers University of Technology Gothenburg Sweden Research and Technology Development Volvo Group as Senior Researcher for Smart and Connected Operations Gothenburg Sweden

Conventional programming of explicit control code is unsuitable for flexible and collaborative production systems. A model-based approach, which focuses on defining capabilities of a system, instead of specifying how to achieve them, provides an alternative for creating complex, scalable, and reliable systems. This is accomplished through the use of behavior models, and tools such as planning, synthesis, verification, and testing. However, developing such models is not without challenges, as it is possible to overlook or incorrectly specify potential behavior and constraints. This can result in unsolvable planning problems or plans that are invalid for other reasons. When plans are unobtainable, developers receive no feedback, which makes model adjustments a difficult and time-intensive task. This paper recognizes these challenges as crucial barriers for adopting model-based development of intelligent automation systems. To facilitate the development of such systems, an approach for detecting and localizing faults in behavior models is presented. Drawing inspiration from software fault localization techniques, the proposed method involves identifying suspicious resources, variables, and operations. The effectiveness of this approach is illustrated with an example use case.

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Data-Driven Learning and control with Event-Triggered Measurements

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IEEE Transactions on Automatic control 2025年

作者： Feng, Shilun Shi, Dawei Chen, Tongwen Shi, Ling Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems MIIT Key Laboratory of Servo Motion System Drive and Control School of Automation Beijing100081 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 1H9 Canada Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Clear Water Bay Kowloon Hong Kong

Event-triggered control has attracted considerable attention for its effectiveness in resource-restricted applications. To make event-triggered control as an end-to-end solution, a key issue is how to effectively learn unknown system dynamics from event-triggered measurements and consequently, develop a learning-based event-triggered controller. Existing works learn system dynamics based on periodic time-triggered measurements, and it is yet to know how to learn a controller with performance guarantee based on event-triggered measurements. To address this issue, we consider the problem of learning an event-triggered state feedback controller for an unknown linear system based on event-triggered state measurements in this work. In particular, we first analyze the event-triggered measurements within a set-membership framework. We prove that the estimation error belongs to a bounded ellipsoid determined by the historical measurements and the event-triggering condition. Subsequently, we demonstrate that all admissible systems compatible with the collected data samples can be explicitly represented in the form of quadratic matrix inequalities using the state estimates. With the acquired set of admissible systems, a co-design problem for the data-driven controller and event-triggering condition is solved using the linear matrix inequality technique, with guaranteed closed-loop stability and L2-gain performance. Finally, numerical examples and comparisons are provided to illustrate the effectiveness of the proposed event-triggered learning and control approach. © 1963-2012 IEEE.

关键词： Networked control systems

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Design of Supervisory Model Predictive control for Building HVAC System Subject to Time-Varying Operating Points

Design of Supervisory Model Predictive Control for Building ...

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International Conference on control, automation and systems ( ICCAS)

作者： Sitthiphat Promchaiwattana David Banjerdpongchai Department of Electrical Engineering Faculty of Engineering Intelligent Control Automation of Process Systems Research Unit Chulalongkorn University 254 Phayathai Road Pathumwan Bangkok Thailand

This paper presents the design of supervisory model predictive control for HVAC systems with consideration of peak demand shaving and thermal comfort. In this work, we analyze the operating points with the thermal comfort requirement. Afterwards, we linearize the nonlinear dynamic model to a linear time-varying model. In particular, we specify that the operating point of the open-loop HVAC system satisfies the thermal comfort condition. This makes the predicted mean vote (PMV) equal to zero or nearly to zero. Subsequently, we calculate the zone temperature, the zone humidity ratio, and the volumetric flow rate. When considering the time-varying disturbance profiles, it appears that the operating points are time-varying. We observe that the coefficient of performance (COP) and the operating points are time-varying which lead to time-varying model. Moreover, we design supervisory control (SC) and model predictive control (MPC) for linear time-varying model. In the SC design, we aim to find the optimal reference zone temperature which is used as the reference signal for MPC. In the MPC design, the objectives are twofold. First, the zone temperature tracks the reference signal. Second, both electrical energy cost and deviation of desired thermal comfort are minimized. The computer simulation shows that MPC of time-varying HVAC system yields the best reference tracking. In addition, it reduces total electrical energy cost the most. We conclude that the optimal temperature reference can be effectively applied to the building HVAC systems while the occupants feel comfortable and the total electrical energy cost is the lowest.

关键词： HVAC Costs Input variables Buildings Predictive models Supervisory control Thermal analysis

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Hazard Analysis of Collaborative automation systems: A Two-layer Approach based on Supervisory control and Simulation

Hazard Analysis of Collaborative Automation Systems: A Two-l...

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IEEE International Conference on Robotics and automation (ICRA)

作者： Tom P. Huck Yuvaraj Selvaraj Constantin Cronrath Christoph Ledermann Martin Fabian Bengt Lennartson Torsten Kröger Intelligent Process Automation and Robotics Lab Institute of Anthropomatics and Robotics (IAR-IPR) Karlsruhe Institute of Technology India Department of Electrical Engineering Division of Systems and Control Chalmers University of Technology Gothenburg Sweden

Safety critical systems are typically subjected to hazard analysis before commissioning to identify and analyse potentially hazardous system states that may arise during operation. Currently, hazard analysis is mainly based on human reasoning, past experiences, and simple tools such as checklists and spreadsheets. Increasing system complexity makes such approaches decreasingly suitable. Furthermore, testing-based hazard analysis is often not suitable due to high costs or dangers of physical faults. A remedy for this are model-based hazard analysis methods, which either rely on formal models or on simulation models, each with their own benefits and drawbacks. This paper proposes a two-layer approach that combines the benefits of exhaustive analysis using formal methods with detailed analysis using simulation. Unsafe behaviours that lead to unsafe states are first synthesised from a formal model of the system using Supervisory control Theory. The result is then input to the simulation where detailed analyses using domain-specific risk metrics are performed. Though the presented approach is generally applicable, this paper demonstrates the benefits of the approach on an industrial human-robot collaboration system.

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Molecular Imprinted Polymer on Optical Fiber Sensor for Ethanol Vapor Biomarker Detection

Molecular Imprinted Polymer on Optical Fiber Sensor for Etha...

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IEEE SENSORS

作者： Pannathorn Jitpratak Akhilesh Kumar Pathak Kankan Swargiary Charusluk Viphavakit Department of Biomedical Engineering Faculty of Engineering Chulalongkorn University Bangkok Thailand Department of Mechanical Engineering Center for Smart Structures and Materials Northwestern University Evanston IL USA Faculty of Engineering International School of Engineering (ISE) Intelligent Control Automation of Process Systems Research Unit Chulalongkorn University Bangkok Thailand

An optical fiber sensor with a single mode-multimode-single mode (SMS) structure is proposed to detect ethanol vapor ranging between 100–500 ppm via the evanescent field interaction at the interface between the optical fiber and ethanol vapor. The proposed optical fiber sensor offers real-time and non-invasive monitoring of ethanol vapor, which is one of the biomarkers of diabetes. Molecular imprinted polymer (MIP) is coated at a multimode fiber region, which is considered to be a sensing area, to improve the selectivity of the ethanol biomarker. The sensor works based on wavelength interrogation by detecting the change in wavelength due to the change in vapor concentration. The fabricated sensor has a sensitivity of 0.0013 nm/ppm, which suggests the potential to be used as a monitoring device for breath analysis.

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