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A Multisensorial Socially Assistive Robot for Therapies with Children with Autism Spectrum Disorder and Down Syndrome Using Serious Games 9th

A Multisensorial Socially Assistive Robot for Therapies wit...

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9th Latin American Congress on Biomedical engineering, CLAIB 2022 and 28th Brazilian Congress on Biomedical engineering, CBEB 2022

作者： Panceri, J.A.C. Freitas, E.V.S. Schreider, S.L. Souza, J.C. Caldeira, E.M.O. Bastos-Filho, T.F. Postgraduate Program in Electrical Engineering Federal University of Espirito Santo Vitória Brazil Automation and Control Engineering Department Federal Institute of Espirito Santo Linhares Brazil Electrical Engineering Department Federal University of Espirito Santo Vitória Brazil Postgraduate Program in Biotechnology Federal University of Espirito Santo Vitória Brazil

ISBN: (纸本)9783031494062

Much of the data obtained by health professionals for diagnosis and therapies applied to children with Autistic Spectrum Disorder (ASD) and Down Syndrome (DS) depend on visual observations and interviews with family members and clinical assessments. Therefore, the use of sensors has the potential of complementing this process by generating quantitative data. This work demonstrates that the use of sensors embedded in a Socially Assistive Robot (SAR) developed at UFES/Brazil, termed Mobile Autonomous Robot for Interaction with Autistics and Trisomy 21 (MARIA T21), can be used as a centralized tool to quantify more objective measures of children’s spatial, postural and social behavior during the interaction with the robot through Serious Games (SG) projected on the floor by the robot. The information generated can help therapists in the application of more efficient therapies, as well as monitor the evolution of the children submitted to the protocol with the robot. The results demonstrates the feasibility of using these sensors and evidence the requirements to be evolved. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Serious games

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Research on workflow recognition for liver rupture repair surgery

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Mathematical Biosciences and engineering 2024年第2期21卷 1844-1856页

作者： Men, Yutao Zhao, Zixian Chen, Wei Wu, Hang Zhang, Guang Luo, Feng Yu, Ming Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China Medical Support Technology Research Department Systems Engineering Institute Academy of Military Sciences People’s Liberation Army Tianjin300161 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin300384 China

Liver rupture repair surgery serves as one tool to treat liver rupture, especially beneficial for cases of mild liver rupture hemorrhage. Liver rupture can catalyze critical conditions such as hemorrhage and shock. Surgical workflow recognition in liver rupture repair surgery videos presents a significant task aimed at reducing surgical mistakes and enhancing the quality of surgeries conducted by surgeons. A liver rupture repair simulation surgical dataset is proposed in this paper which consists of 45 videos collaboratively completed by nine surgeons. Furthermore, an end-to-end SA-RLNet, a self attention-based recurrent convolutional neural network, is introduced in this paper. The self-attention mechanism is used to automatically identify the importance of input features in various instances and associate the relationships between input features. The accuracy of the surgical phase classification of the SA-RLNet approach is 90.6%. The present study demonstrates that the SA-RLNet approach shows strong generalization capabilities on the dataset. SA-RLNet has proved to be advantageous in capturing subtle variations between surgical phases. The application of surgical workflow recognition has promising feasibility in liver rupture repair surgery. ©2024 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons.

关键词： Image classification

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Semi-Autonomous Navigation Based on Local Semantic Map for Mobile Robot

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Journal of Shanghai Jiaotong university(Science) 2025年第1期30卷 27-33页

作者： ZHAO Yanfei XIAO Peng WANG Jingchuan GUO Rui Department of Automation Institute of Medical RoboticsShanghai Jiao Tong UniversityShanghai200240China State Key Laboratory of System Control and Information Processing Ministry of Education of ChinaShanghai200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240China State Grid Intelligence Technology Co. Ltd.Jinan250013China

Mobile robots represented by smart wheelchairs can assist elderly people with mobility *** paper proposes a multi-mode semi-autonomous navigation system based on a local semantic map for mobile robots,which can assist users to implement accurate navigation(e.g.,docking)in the environment without prior *** order to overcome the problem of repeated oscillations during the docking of traditional local path planning algorithms,this paper adopts a mode-switching method and uses feedback control to perform docking when approaching semantic *** last,comparative experiments were carried out in the real *** show that our method is superior in terms of safety,comfort and docking accuracy.

关键词： semi-autonomous navigation mobile robot semantic map voice interaction

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Unified control and detection framework and its applications: a review, some new results, and future perspectives

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Journal of systems engineering and Electronics 2021年第5期32卷 995-1013页

作者： DING Steven Xianchuan LI Linlin JIANG Bin Institute for Automatic Control and Complex Systems University of Duisburg-EssenDuisburg 47057Germany School of Automation and Electrical Engineering University of Science and Technology BeijingBeijing 100083China College of Automation Engineering Nanjing University of Aeronautics and AstronauticsNanjing 210016China

Initiated three decades ago,integrated design of controllers and fault detectors has continuously attracted research *** recent development of the unified control and detection framework with an observer-based residual generator in its core gives a more general form of the previous *** applications to residual centred modelling of uncertain control systems,fault detection in feedback control systems with uncertainties,fault-tolerant control(FTC)as well as control performance degradation monitoring,detection and recovery are *** conclusion,some future perspectives are proposed.

关键词： unified framework of control and detection observer-based residual generator Youla parameterisation detection of additive and multiplicative faults in control loop fault-tolerant control(FTC) loop performance degradation(LPD)monitoring and recovery

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PVTimesNet: A Hybrid Deep Learning Method for Enhancing Ultra-short-term PV Power Forecasting

PVTimesNet: A Hybrid Deep Learning Method for Enhancing Ultr...

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2024 China automation Congress, CAC 2024

作者： Wu, Ji Wang, Kai Ma, Wenwen Zhang, Jingxin Wang, Shibo China Electric Power Research Institute Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing210096 China State Grid Shandong Electric Power Research Institute Jinan China

ISBN: (纸本)9798350368604

Accurate ultra-short-term photovoltaic (PV) power forecasting is crucial for the real-time scheduling of grid systems. However, the inherent variability of solar energy makes this task extremely challenging. To enhance PV power forecasting, this paper introduces a novel hybrid model named PVTimesNet, designed to harness the strengths of Convolutional Neural Network (CNN) and Long Short-Term Memory Network (LSTM) for effective feature extraction. PVTimesNet consists of two parallel branches: the CNN1d branch, which captures correlations between multiple variables and adjacent time steps, and the LSTM branch, which learns the temporal dependencies within the PV power sequences. The features extracted by both branches are then concatenated and passed through a fully connected layer to generate multi-step PV power forecasts. Experimental results demonstrate that for forecast horizons of 1 to 4 hours, the proposed model significantly outperforms individual models and other CNN-LSTM hybrid structures. Additionally, it exhibits superior performance compared to related methods for longer forecast horizons. © 2024 IEEE.

关键词： Hybrid power

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Structural Coverability for Intelligent automation systems 19

Structural Coverability for Intelligent Automation Systems

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19th IEEE International Conference on automation Science and engineering, CASE 2023

作者： Eros, Endre Bengtsson, Kristofer Åkesson, Knut Chalmers University of Technology Automation Research Group Electrical Engineering Systems and Control Department Gothenburg Sweden Research and Technology Development Volvo Group Smart and Connected Operations Gothenburg Sweden

ISBN: (纸本)9798350320695

In order to be flexible and handle complex scenarios, intelligent automation systems might benefit from automated planning techniques which rely on specifications and models describing their behavior. However, due to the presence of message passing, latency, jitter, timeouts, failures, and error handling, the verification of such behavior models using formal methods is often unfeasible. Therefore, testing has emerged as an approach to evaluating the behavior of intelligent automation systems. This paper presents a way to analyze structural coverability of behavior models for intelligent automation systems, which is inspired by the modified condition/decision coverage (MC/DC) criterion. This is paired with a testing procedure that enables each test case to influence both the controller and the simulated environment by injecting some specific state. As a result, the proposed coverability criterion can effectively identify segments of the behavior model that have not been adequately tested and suggest additional test cases to improve coverability. An example use case is presented to demonstrate the effectiveness of this approach. © 2023 IEEE.

关键词： Message passing

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DriveRP: RAG and Prompt engineering Embodied Parallel Driving in Cyber-Physical-Social Spaces 4

DriveRP: RAG and Prompt Engineering Embodied Parallel Drivin...

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4th IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2024

作者： Huang, Jun Ma, Hao Zhang, Tengchao Lin, Fei Ma, Siji Wang, Xiao Wang, Fei-Yue Macau University of Science and Technology Faculty of Innovation Engineering China Anhui University School of Artificial Intelligence Hefei China Chinese Academy of Sciences State Key Laboratory for Management and Control of Complex Systems Institute of Automation Beijing China

ISBN: (纸本)9798350349252

In recent years, numerous technological advancements in Artificial Generative Intelligences (AGIs) have demonstrated significant potential to transform the intelligence acquisition mechanisms in connected autonomous vehicles (CAVs). Integrating technologies like ChatGPT into CAVs can enhance human-machine interactions. However, the emergence of such new traffic entities may introduce unforeseen hallucinations and complex risks that surpass our current understanding. To address these challenges, Retrieval-Augmented Generation (RAG) and prompt engineering technologies are being explored to enhance the reliability and safety of autonomous driving systems. RAG retrieves relevant contextual information, such as driving experiences and real-time road network status, from external databases to ensure that foundation models have access to accurate and timely data for informed decision-making. Prompt engineering optimizes the performance of large language models in autonomous driving systems by designing and refining prompts that guide the models' responses, thereby improving their relevance and accuracy in various driving scenarios. Together, these technologies enhance the robustness and trustworthiness of autonomous driving systems. This paper proposes DriveRP, a framework that integrates RAG and prompt engineering within the Descriptive-Predictive-Prescriptive Intelligence framework of Parallel Driving theory. DriveRP aims to enhance the safety and interpretability of autonomous vehicle trajectory planning, decision-making, and motion control, ultimately achieving the "6S"goals. Grounded in Digital Twins and Metaverse-embodied parallel driving theory, DriveRP provides the infrastructure and foundational intelligence for parallel driving with Multi-modal Large Lange Models(MLLMs). Additionally, the paper discusses future trends and potential research directions, focusing on the "6S"goals of parallel driving: Smart, Safe, Secure, Sensitive, Sustainable, and Serviceable. © 2

关键词： Intelligent systems

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An Ensemble of UNet Frameworks for Lung Nodule Segmentation 1

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International Conference on Actual Problems of Applied Mathematics and Computer systems, APAMCS 2022

作者： Gautam, Nandita Basu, Abhishek Kaplun, Dmitry Sarkar, Ram Department of Computer Science and Engineering Jadavpur University Kolkata India Department of Computer Science and Engineering National Institute of Technology Durgapur Durgapur India Department of Automation and Control Processes Saint Petersburg Electrotechnical University "LETI" Saint Petersburg Russia

ISBN: (数字)9783031341274

ISBN: (纸本)9783031341267

One of the most common types of cancer in the world is lung cancer, which is a cause of increasing mortality. It is most often discovered in the middle and later stages as it does not have obvious symptoms due to which its treatment is often missed. Studies show that most lung cancers are in the form of lung nodules, which can be categorized as benign or malignant. Thus, accurate early identification of malignant lung nodules that might later become cancerous is essential for the prevention of lung cancer. Computed Tomography (CT) images can be useful for identifying and segmenting these nodules. In this paper, we propose an ensemble model, called BUS-UNet++, to segment lung nodules using CT images. We use a combination of the ConvLSTM up-sampling architecture from BUS-UNet and skip connections in aggregation blocks from the UNet++ model to build the BUS-UNet++ ensemble. The dataset for this study is collected from the Lung Image Database Consortium Image Database Resource Initiative (LIDC-IDRI), where we have selected the modality of these images as CT images. These are further preprocessed to obtain nodule masks and nodule images, which constitute the Region of Interest (RoI). The accuracy achieved with the Adam Optimizer is 0.9731, the Intersection over Union (IoU) of about 0.8439, and the dice score coefficient (DSC) of about 0.958 are obtained by the proposed system. This ensemble model outperforms several state-of-the-art models used for the same purpose. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Image segmentation

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A Real-time Local Planner Design for Smart Wheelchairs Based on Koopman Bilinear Model Predictive control

A Real-time Local Planner Design for Smart Wheelchairs Based...

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2024 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2024

作者： Yu, Guanfeng Zhang, Han Wang, Zehao Wang, Jingchuan Shanghai Jiao Tong University Institute of Medical Robotics Department of Automation China Ministry of Education of China Key Laboratory of System Control and Information Processing China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

ISBN: (纸本)9798350372601

The paper introduces a Koopman bilinear model predictive control (KBMPC) as a local planner for smart wheelchair systems. This approach leverages the Koopman Operator to streamline the nonlinear terms in MPC, aiming to achieve superior real-time performance. In particular, we employ the Extended Dynamic Mode Decomposition (EDMD) method to approximate the infinite dimensional Koopman operator. To tackle the challenge of designing lifting functions, we systematically utilize the derivatives of known nonlinear structures to methodically derive lifting functions. This systematic approach facilitates the identification of a precise bilinear model. Next, we formulate the corresponding Koopman bilinear MPC problem. Finally, an iterative algorithm is employed to efficiently solve the KBMPC problem. This method linearizes the bilinear model around estimations and iteratively solves the resulting quadratic programming problem to refine estimations. This allows KBMPC to function as a real-time local planner for smart wheelchairs. The prediction of nonlinear terms shows that the identified Koopman bilinear model increases the prediction accuracy. Furthermore, experiments demonstrate the advantages of the designed KBMPC local planner, highlighting its superior real-time performance and predictive capabilities. © 2024 IEEE.

关键词： Iterative methods

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Aβ-Aggregation-Generated Blue Autofluorescence Illuminates Senile Plaques as well as Complex Blood and Vascular Pathologies in Alzheimer’s Disease

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Neuroscience Bulletin 2024年第8期40卷 1115-1126页

作者： Hualin Fu Jilong Li Chunlei Zhang Peng Du Guo Gao Qiqi Ge Xinping Guan Daxiang Cui Institute of Nano Biomedicine and Engineering School of Sensing Science and EngineeringSchool of Electronic Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghai 200240China Institute of Marine Equipment Shanghai Jiao Tong UniversityShanghai 200240China National Center for Translational Medicine Shanghai Jiao Tong UniversityShanghai 200240China Department of Colorectal Surgery School of MedicineXinhua HospitalShanghai Jiao Tong UniversityShanghai 200092China Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China The Key Laboratory of System Control and Information Processing Ministry of EducationShanghai 200240China

Senile plaque blue autofluorescence was discovered around 40 years ago,however,its impact on Alzheimer’s disease(AD)pathology has not been fully *** analyzed senile plaques with immunohistochemistry and fluorescence imaging on AD brain sections and also Aβ aggregation in *** DAPI or Hoechst staining,the nuclear blue fluorescence could only be correctly assigned after subtracting the blue plaque *** flower-like structures wrapping dense-core blue fluorescence formed by cathepsin D staining could not be considered central-nucleated neurons with defective lysosomes since there was no nuclear staining in the plaque core when the blue autofluorescence was *** Aβ self-oligomers and Aβ/hemoglobin heterocomplexes generated blue *** Aβ amyloid blue autofluorescence not only labels senile plaques but also illustrates red cell aggregation,hemolysis,cerebral amyloid angiopathy,vascular plaques,vascular adhesions,and *** summary,we conclude that Aβ-aggregation-generated blue autofluorescence is an excellent multi-amyloidosis marker in Alzheimer’s disease.

关键词： Senile plaque Blue autofluorescence Aβ Amyloid aggregation Hemoglobin Cathepsin D.Microaneurysm Alzheimer's disease

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