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IEEE Conference on Decision and control

作者： A. Daniel Carnerero Daniel R. Ramirez Takeshi Hatanaka Teodoro Alamo Graduate School of Engineering Science Osaka University Toyonaka Japan Departamento de Ingeniería de Sistemas y Automática Universidad de Sevilla Escuela Superior de Ingenieros Camino de los Descubrimientos s/n Sevilla Spain Department of Systems and Control Engineering School of Engineering Tokyo Institute of Technology Tokyo Japan

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

In this paper, we present a data-driven methodology to predict and control the behaviour of nonlinear and non-autonomous systems based on kernel functions. The technique computes the forecasting by means of a linear combination of past data. The weights used to compute the prediction are obtained by solving a convex optimization problem that stems from a novel kriging formulation. A control Lyapunov Function (CLF) based controller using the presented predictor is also built. Finally, numerical examples of both prediction and control are presented, showing the efficacy of the proposed approach.

关键词： Asymptotic stability Noise Convex functions Noise measurement Nonlinear systems Kernel Forecasting Lyapunov methods

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Exploring Child-Robot Interaction in Individual and Group settings in India

arXiv

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arXiv 2024年

作者： Manikutty, Gayathri Potapragada, Sai Ankith Pasupuleti, Devasena Unnithan, Mahesh S. Venugopal, Arjun Prabha, Pranav Arunav, H. Kumar, Vyshnavi Anil Rthuraj, P.R. Bhavani, Rao R. AMMACHI Labs Amrita Vishwa Vidyapeetham Kerala Kollam690525 India Department of Computer Science and Applications Amrita School of Computing Amrita Vishwa Vidyapeetham Amritapuri India Department of Systems Innovation Graduate School of Engineering Science Osaka University Japan Department of Mechanical Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Kerala Kollam690525 India

This study evaluates the effectiveness of child-robot interactions with the HaKsh-E social robot in India, examining both individual and group interaction settings. The research centers on game-based interactions designed to teach hand hygiene to children aged 7-11. Utilizing video analysis, rubric assessments, and post-study questionnaires, the study gathered data from 36 participants. Findings indicate that children in both settings developed positive perceptions of the robot in terms of the robot’s trustworthiness, closeness, and social support. The significant difference in the interaction level scores presented in the study suggests that group settings foster higher levels of interaction, potentially due to peer influence and collaborative dynamics. While both settings showed significant improvements in learning outcomes, the individual setting had more pronounced learning gains. This suggests that personal interactions with the robot might lead to deeper or more effective learning experiences. Consequently, this study concludes that individual interaction settings are more conducive for focused learning gains, while group settings enhance interaction and engagement. © 2024, CC BY.

关键词： Human robot interaction

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Predicting Geckler Classification from Gram Stained Smears Images for Sputum: Image Classification versus Object Detection 14

Predicting Geckler Classification from Gram Stained Smears I...

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14th IIAI International Congress on advanced Applied Informatics, IIAI-AAI 2023

作者： Sugimoto, Hitoshi Funatsu, Ryotaro Hirata, Kouichi Kyushu Institute of Technology Graduate School of Computer Science and Systems Engineering Kawazu 680-4 Iizuka820-8502 Japan Kyushu Institute of Technology Department of Artificial Intelligence Kawazu 680-4 Iizuka820-8502 Japan Softmax Co. Ltd Japan

ISBN: (纸本)9798350324228

A Geckler classification is a criterion how the image is quality based on the number of buccal squamous epithelial (BSE) cells and leukocytes in the Gram stained smears images per 100 × field for sputum. The Geckler classification then determines which of images is valuable to microscope testing for the Gram stained smears images per 1, 000 × field for sputum. In this paper, we predict the Geckler classes by using two methods, image classification and object detection. For the image classification, we predict the Geckler classes from the training images for every Geckler class, without annotating BSE cells and leukocytes. On the other hand, for the object detection, we detect BSE cells and leukocytes from the training images annotated by them and determine the Geckler class by the number of them. Hence, we compare the experimental results of predicting Geckler classes obtained by the image classification with those by the object detection. © 2023 IEEE.

关键词： Object detection

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Parametric Transformation of Timed Weighted Marked Graphs:Applications in Optimal Resource Allocation

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IEEE/CAA Journal of Automatica Sinica 2021年第1期8卷 179-188页

作者： Zhou He Ziyue Ma Zhiwu Li Alessandro Giua the College of Mechanical and Electrical Engineering Shaanxi University of Science and TechnologyXi’an 710021China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of TechnologyXi’an 710048China the School of Electro-Mechanical Engineering Xidian UniversityXi’an 710071China Institute of Systems Engineering Macao University of Science and TechnologyTaipa 999078MacaoChina the Department of Electrical and Electronic Engineering University of CagliariCagliari 09124Italy

Timed weighted marked graphs are a subclass of timed Petri nets that have wide applications in the control and performance analysis of flexible manufacturing *** to the existence of multiplicities(i.e.,weights)on edges,the performance analysis and resource optimization of such graphs represent a challenging *** this paper,we develop an approach to transform a timed weighted marked graph whose initial marking is not given,into an equivalent parametric timed marked graph where the edges have unitary *** order to explore an optimal resource allocation policy for a system,an analytical method is developed for the resource optimization of timed weighted marked graphs by studying an equivalent ***,we apply the proposed method to a flexible manufacturing system and compare the results with a previous heuristic *** analysis shows that the developed approach is superior to the heuristic approach.

关键词： Discrete event system resource allocation timed Petri net weighted marked graph

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Convex Reformulation of LMI-Based Distributed controller Design with a Class of Non-Block-Diagonal Lyapunov Functions

arXiv

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arXiv 2024年

作者： Watanabe, Yuto Fushimi, Sotaro Sakurama, Kazunori The Department of Systems Science Graduate School of Informatics Kyoto University Yoshida-Honmachi Sakyo-ku Kyoto606–8501 Japan The Department of System Innovation Graduate School of Engineering Science Osaka University 1-3 Machikaneyama Toyonaka Osaka560-8531 Japan

This study addresses a distributed state feedback controller design problem for continuous-time linear time-invariant systems by means of linear matrix inequalities (LMI). As the exact convexification is still open, the block-diagonal relaxation of Lyapunov functions has been prevalent despite its conservatism. In this work, we target a class of non-block-diagonal Lyapunov functions that has the same sparsity as distributed controllers. By leveraging a block-diagonal factorization of sparse matrices and Finsler’s lemma, we first present a (nonlinear) matrix inequality for stabilizing distributed controllers with such Lyapunov functions, which boils down to a necessary and sufficient condition for such controllers if the sparsity pattern is chordal. As a relaxation of the inequality, we derive an LMI that completely covers the conventional relaxation and then provide analogous results for H∞ control. Lastly, numerical examples underscore the efficacy of our results. © 2024, CC BY-NC-ND.

关键词： Linear matrix inequalities

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A DRL-enabled Adaptive Sparsity Promoting Wide-area Damping controller for Power System with Time-delay and Packet Dropout

A DRL-enabled Adaptive Sparsity Promoting Wide-area Damping ...

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2023 Panda Forum on Power and Energy, PandaFPE 2023

作者： Cao, Di Zhang, Guozhou Hu, Jiaxiang Hu, Weihao Huang, Yuehui Chen, Zhe State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems China Electric Power Research Institute Chengdu China School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu China Aalborg University Department of Energy Technology Aalborg Denmark

ISBN: (纸本)9798350321173

This paper proposes a deep reinforcement learning (DRL) based adaptive sparsity promoting wide-area damping controller for power system. Different from traditional fixed wide-area control structure, the proposed method employs DRL algorithm to identify the optimal sparsity promoting control structure and obtain corresponding parameter settings under different operating conditions considering the time-delay and packet drop. Simulation are carried out on 10-machine 39-bus system to demonstrate the effectiveness of the proposed approach. © 2023 IEEE.

关键词： Time delay

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New Measure for Network controllability Robustness Based on controllable Subspace

New Measure for Network Controllability Robustness Based on ...

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IEEE International Symposium on Circuits and systems (ISCAS)

作者： Yanwen Liu Jie Ding Xiang Li Department of Electronic Engineering School of Information Science and Engineering Adaptsdive Networks and Control Lab Fudan University Shanghai China Institute of Complex Networks and Intelligent Systems Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China

ISBN: (数字)9798350330991

ISBN: (纸本)9798350331004

In this paper, we propose a new criteria to measure network controllability robustness based on generic dimension of controllable subspace given a network. Generic dimension curve and controllabillity robustness index are introduced to show network controllability robustness from different aspects. 12 different attack methods are carried out for six network models. It is found that the multiloop structure is useful to maintain network robustness under attacks. Moreover, the networks with single backbone structure are fragile under attacks. Besides, both the increase and protection of driver nodes can enhance the controllability robustness of networks.

关键词： Analytical models Circuits and systems Complex networks controllability Robustness Indexes Protection

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NONINVASIVE VISUALIZATION OF MUSCLES DURING SWALLOWING USING A MUSCLE DEFORMATION SENSOR 18

NONINVASIVE VISUALIZATION OF MUSCLES DURING SWALLOWING USING...

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18th International Conference on Interfaces and Human Computer Interaction 2024, IHCI 2024, the 17th International Conference on Game and Entertainment Technologies 2024, GET 2024 and the 18th International Conference on Computer Graphics, Visualization, Computer Vision and Image Processing 2024, CGVCVIP 2024, Part of the 18th Multi Conference on Computer science and Information systems 2024, MCCSIS 2024

作者： Shimabukuro, Satoshi Arashiro, Ryouta Tamaki, Emi Graduate School of Science and Engineering The University of the Ryukyus 1 Senbaru Nishihara Town Okinawa Japan Okinawa Rehabilitation Welfare College 1380-1 Itashiki Yonabaru Town- Shimajiri-gun Okinawa Japan Department of Systems Innovation School of Engineering The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan H2L Inc. 3-4-21 Roppongi Minato-ku Tokyo Japan

ISBN: (纸本)9789898704580

Mealtime is one of the pleasures of daily life and an important factor in ensuring the quality of life. Aging and brain and neurological diseases often complicate eating. In particular, the ability to swallow food directly, such as in dysphagia, has a significant impact on eating. In this study, a new observation method was proposed for the cricopharyngeal muscles, which are important for swallowing. Experiments were conducted on two healthy participants. A muscle deformation sensor was used to observe the cricopharyngeal muscles. The results showed that the contraction and relaxation of the cricopharyngeal muscle during swallowing can be visualized noninvasively and easily using muscle deformation sensors in healthy subjects. Based on this experiment, the possibility of its clinical application in patients with dysphagia is suggested. © 2024 Interfaces and Human Computer Interaction. All Rights Reserved.

关键词： Visualization

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Spiking neural networks: Towards bio-inspired multimodal perception in robotics

arXiv

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arXiv 2024年

作者： Oikonomou, Katerina Maria Balaska, Vasiliki Tsintotas, Konstantinos A. Mavridis, Christos N. Kansizoglou, Ioannis Gasteratos, Antonios The Department of Production and Management Engineering Laboratory of Robotics and Automation Democritus University of Thrace Xanthi Greece The Department of Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden

Spiking neural networks (SNNs) have captured apparent interest over the recent years, stemming from neuroscience and reaching the field of artificial intelligence. However, due to their nature SNNs remain far behind in achieving the exceptional performance of deep neural networks (DNNs). As a result, many scholars are exploring ways to enhance SNNs by using learning techniques from DNNs. While this approach has been proven to achieve considerable improvements in SNN performance, we propose another perspective: enhancing the biological plausibility of the models to leverage the advantages of SNNs fully. Our approach aims to propose a brain-like combination of audio-visual signal processing for recognition tasks, intended to succeed in more bio-plausible human-robot interaction applications. © 2024, CC BY-NC-SA.

关键词： Adversarial machine learning

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Mapping dengue susceptibility in Dhaka city: a geospatial multi-criteria approach integrating environmental and demographic factors

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Spatial Information Research 2025年第4期33卷 1-16页

作者： Hoque, Muhammad Al-Amin Sardar, Md. Limon Mukul, Sharif A. Pradhan, Biswajeet Department of Geography and Environment Jagannath University Dhaka Bangladesh Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS) School of Civil and Environmental Engineering Faculty of Engineering & IT University of Technology Sydney Ultimo Australia Department of Environment and Development Studies United International University Dhaka Bangladesh School of Science Technology and Engineering (SSTE) University of the Sunshine Coast Maroochydore DC Australia Department of Earth and Environment Florida International University Miami USA

Dengue, a rapidly spreading mosquito-borne disease, poses a serious public health threat in tropical cities like Dhaka, Bangladesh—one of the world’s most densely populated megacities. In 2023 alone, Dhaka experienced its worst outbreak, recording 321,179 cases and 1,705 deaths. This study aims to assess dengue susceptibility across Dhaka using a geospatial Multi-Criteria Decision-Making (MCDM) approach. Fourteen environmental and demographic factors were selected, and thematic raster layers were developed and weighted using the Analytical Hierarchy Process (AHP). These layers were integrated to generate spatial dengue susceptibility maps, highlighting risk zones across the city. Findings reveal that southern and southeastern Dhaka, particularly under the South City Corporation, are highly susceptible based on environmental factors. Demographic analysis shows moderate to very high susceptibility in central and southern wards, with population density and proximity to waterlogged areas identified as key drivers. The model was validated through field surveys with 80 stakeholders, with 67.5% agreeing with the susceptibility classifications. This study provides a scalable and transferable framework for dengue risk assessment and can inform targeted interventions in other endemic regions. The results offer critical guidance for urban health planning, vector control, and resource allocation to mitigate dengue and similar vector-borne diseases.

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