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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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A Fault-Tolerant Soft/Hard Hybrid control for Fault Diagnosis of Aero-engine Sensors

A Fault-Tolerant Soft/Hard Hybrid Control for Fault Diagnosi...

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第35届中国控制与决策会议

作者： Hang Yang Tao Sun Xian Du Xi-Ming Sun Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology School of Control Science and Engineering Dalian University of Technology Department of Automation Tsinghua University

In this brief paper,a fault-tolerant soft/hard hybrid control scheme based on the Kalman filter is proposed for fault diagnosis of aero-engine *** designed soft fault diagnosis system,in particular,can detect whether a fault exists by residual processing sensor measurement values and a set of Kalman filter estimation values and summing their weighted squares to compare the known *** addition,to determine whether there is a fault,the developed hard fault diagnosis system compares the residual absolute value of the sensor measurement value and the estimated value of a Kalman filter with the known threshold ***,some numerical simulations of the fault of the low-pressure rotor speed sensor of an aero-engine are performed to validate the proposed method's feasibility and fault tolerance.

关键词： Aero-engine sensors fault detection fault-tolerant control hybrid control Kalman filter

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Improved Hybrid Attention Learning System for Remaining Useful Life Prediction

Improved Hybrid Attention Learning System for Remaining Usef...

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第42届中国控制会议

作者： Zhi Li Tao Sun Song Ma Bin Yang Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology School of Control Science and Engineering Dalian University of Technology Department of Automation Tsinghua University

Remaining useful life(RUL) prediction can improve the availability and efficiency of equipment or system by providing timely maintenance suggestions. In this paper, an improved hybrid attention learning system for RUL prediction is developed. By introducing adaptive weighting, a hybrid attention mechanism with self attention and external attention is designed. The mechanism enhances the attention to samples with similar performance degradation patterns, and improves the feature extraction ability of the learning system for sensor data with strong temporal correlation. Finally, we conducted a series of simulation experiments on the commercial modular aviation propulsion system simulation(C-MAPSS) dataset to verify the effectiveness and superiority of the proposed method in RUL prediction.

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Asynchronous Distributed Optimization via ADMM with Efficient Communication

Asynchronous Distributed Optimization via ADMM with Efficien...

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IEEE Conference on Decision and control

作者： Apostolos I. Rikos Wei Jiang Themistoklis Charalambous Karl H. Johansson Department of Electrical and Computer Engineering Division of Systems Engineering Boston University Boston MA US Hong Kong China Department of Electrical and Computer Engineering School of Engineering University of Cyprus Nicosia Cyprus Department of Electrical Engineering and Automation School of Electrical Engineering Aalto University Espoo Finland Division of Decision and Control Systems KTH Royal Institute of Technology Stockholm Sweden

In this paper, we focus on an asynchronous distributed optimization problem. In our problem, each node is endowed with a convex local cost function, and is able to communicate with its neighbors over a directed communication network. Furthermore, we assume that the communication channels between nodes have limited bandwidth, and each node suffers from processing delays. We present a distributed algorithm which combines the Alternating Direction Method of Multipliers (ADMM) strategy with a finite time quantized averaging algorithm. In our proposed algorithm, nodes exchange quantized valued messages and operate in an asynchronous fashion. More specifically, during every iteration of our algorithm each node (i) solves a local convex optimization problem (for the one of its primal variables), and (ii) utilizes a finite-time quantized averaging algorithm to obtain the value of the second primal variable (since the cost function for the second primal variable is not decomposable). We show that our algorithm converges to the optimal solution at a rate of O (1/ k) (where $k$ is the number of time steps) for the case where the local cost function of every node is convex and not-necessarily differentiable. Finally, we demonstrate the operational advantages of our algorithm against other algorithms from the literature.

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The Fully Self-Checking Structures Synthesis Features of Concurrent Checking Systems Implemented on the Boolean Complement Method Basis to the Constant-Weight '2-out-of-4' Code

The Fully Self-Checking Structures Synthesis Features of Con...

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2022 International Conference on Industrial engineering, Applications and Manufacturing, ICIEAM 2022

作者： Efanov, Dmitrii V. Pivovarov, Dmitriy V. Khoroshev, Valerii V. Higher School of Transport Institute of Mechanical Engineering Materials and Transport Peter the Great St. Petersburg Polytechnic University St. Petersburg Russia The Russian University of Transport Department of 'Automation Remote Control and Communication on Railway Transport' Moscow Russia Emperor Alexander i St. Petersburg State Transport University 'Automation and Remote Control on Railways' Department St. Petersburg Russia

ISBN: (纸本)9781665483698

The concurrent checking system structural diagram properties implemented by the Boolean method to the constant-weight '2-out-of-4' code is analyzed. The conditions for the implementation of fully self-checking structures are established. These conditions are stringent and practically feasible in most cases when controlling multi-output discrete devices. In this case, it will be necessary to implement the control logic block in the control system in the form of a circuit with independent outputs. An example of the outputs controllable groups detection is shown. Completely self-checking structures will be obtained by implementing concurrent checking subsystems using this method. © 2022 IEEE.

关键词： Fault detection

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Distance-based Multiple Non-cooperative Ground Target Encirclement for Complex Environments

arXiv

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arXiv 2024年

作者： Liu, Fen Yuan, Shenghai Cao, Kun Meng, Wei Xie, Lihua School of Electrical and Electronic Engineering Nanyang Technological University Singapore639798 Singapore Department of Control Science and Engineering College of Electronics and Information Engineering Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai200000 China Guangdong Provincial Key Laboratory of Intelligent Decision and Cooperative Control School of Automation Guangdong University of Technology Guangzhou510006 China

This paper proposes a comprehensive strategy for complex multi-target-multi-drone encirclement in an obstacle-rich and GPS-denied environment, motivated by practical scenarios such as pursuing vehicles or humans in urban canyons. The drones have omnidirectional range sensors that can robustly detect ground targets and obtain noisy relative distances. After each drone task is assigned, a novel distance-based target state estimator (DTSE) is proposed by estimating the measurement output noise variance and utilizing the Kalman filter. By integrating anti-synchronization techniques and pseudo-force functions, an acceleration controller enables two tasking drones to cooperatively encircle a target from opposing positions while navigating obstacles. The algorithm’s effectiveness for the discrete-time double-integrator system is established theoretically, particularly regarding observability. Moreover, the versatility of the algorithm is showcased in aerial-to-ground scenarios, supported by compelling simulation results. Experimental validation demonstrates the effectiveness of the proposed approach. © 2024, CC BY.

关键词： Drones

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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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Robust optimization-based fusion of GNSS and Visual-Inertial-Wheel Odometry

Robust optimization-based fusion of GNSS and Visual-Inertial...

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2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022

作者： Hou, Jake Jie Wu, Xinrui Shan, Jiwei Li, Dun Wang, Hesheng Shanghai Jiao Tong University Department of Automation China Shanghai Karlang Industrial Nantong Intelligent Technology Co. Ltd China Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Department of Automation Shanghai200240 China

ISBN: (纸本)9781665481090

SLAM is significant to autonomous mobile robots. In order to realize drift-free state estimation and provide accurate localization results for the subsequent navigation, we develop an optimization-based framework consisting of a high-frequency Inertial-Wheel Odometry(IWO), Visual-Inertial-Wheel Odometry(VIWO) and a global fusion module. To fuse the local state with the position provided by GNSS, we perform ternary edge in factor graph optimization to estimate the transformation between the local frame and ENU coordinate. Thanks to the tightly-coupled VIWO, the localization property of the odometry presents more robustness, and improve the accuracy of global fusion. A noise repropagation strategy is introduced to ensure the consistency of the IMU and wheel odometer. We evaluate the proposed system on public datasets and test it in real-world scenario. The experimental results show that our system achieves accurate pose estimation in outdoor environments. © 2022 IEEE.

关键词： Frequency estimation

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Synthesis of Temporally-Robust Policies for Signal Temporal Logic Tasks using Reinforcement Learning

Synthesis of Temporally-Robust Policies for Signal Temporal ...

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IEEE International Conference on Robotics and automation (ICRA)

作者： Siqi Wang Shaoyuan Li Li Yin Xiang Yin Department of Automation and Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai China Institute of Systems Engineering Macau University of Science and Technology Taipa China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

This paper investigates the problem of designing control policies that satisfy high-level specifications described by signal temporal logic (STL) in unknown, stochastic environments. While many existing works concentrate on optimizing the spatial robustness of a system, our work takes a step further by also considering temporal robustness as a critical metric to quantify the tolerance of time uncertainty in STL. To this end, we formulate two relevant control objectives to enhance the temporal robustness of the synthesized policies. The first objective is to maximize the probability of being temporally robust for a given threshold. The second objective is to maximize the worst-case spatial robustness value within a bounded time shift. We use reinforcement learning to solve both control synthesis problems for unknown systems. Specifically, we approximate both control objectives in a way that enables us to apply the standard Q-learning algorithm. Theoretical bounds in terms of the approximations are also derived. We present case studies to demonstrate the feasibility of our approach.

关键词： Measurement Uncertainty Q-learning Approximation algorithms Robustness Logic Task analysis

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Bayesian optimization for active flow control

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Acta Mechanica Sinica 2021年第12期37卷 1786-1798页

作者： Antoine B.Blanchard Guy Y.Cornejo Maceda Dewei Fan Yiqing Li Yu Zhou Bernd R.Noack Themistoklis P.Sapsis Department of Mechanical Engineering Massachusetts Institute of TechnologyCambridgeMA 02139USA Universit′e Paris-Saclay CNRSLaboratoire Interdisciplinaire des Sciences du Num′erique91400 OrsayFrance Center for Turbulence Control Harbin Institute of TechnologyShenzhen 518058China School of Mechanical Engineering and Automation Harbin Institute of TechnologyShenzhen 518058China

A key question in flow control is that of the design of optimal controllers when the control space is high-dimensional and the experimental or computational budget is *** address this formidable challenge using a particular flavor of machine learning and present the first application of Bayesian optimization to the design of open-loop controllers for fluid *** consider a range of acquisition functions,including the recently introduced output-informed criteria of Blanchard and Sapsis(2021),and evaluate performance of the Bayesian algorithm in two iconic configurations for active flow control:computationally,with drag reduction in the fluidic pinball;and experimentally,with mixing enhancement in a turbulent *** these flows,we find that Bayesian optimization identifies optimal controllers at a fraction of the cost of other optimization strategies considered in previous *** optimization also provides,as a by-product of the optimization,a surrogate model for the latent cost function,which can be leveraged to paint a complete picture of the control *** proposed methodology can be used to design open-loop controllers for virtually any complex flow and,therefore,has significant implications for active flow control at an industrial scale.

关键词： Bayesian optimization Flow control Drag reduction Turbulence

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