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E-Health and Bioengineering Conference (EHB)

作者： Elena-Claudia Maftei Otilia Zvorişteanu Hariton-Nicolae Costin Silviu Bejinariu Florin Rotaru Vasile Manta Ramona Luca Dept. of Computer Science and Engineering Faculty of Automatic Control and Computer Engineering “Gheorghe Asachi” Technical University of Iaşi Institute of Computer Science Romanian Academy Iaşi Branch Iaşi Romania

ISBN: (数字)9798331532147

ISBN: (纸本)9798331532154

Human gait analysis provides qualitative and quantitative information concerning different characteristics of walking of a certain person. Cloud computing proves to be a modern and valuable technology when dealing with data scalability, security and efficiency of processing and storage. Also, this paradigm has some key-benefits like real-time data sharing, fast computation as well as collaborative research. The applications gamut which uses cloud computing is getting bigger and bigger, and healthcare sector is an important domain in this respect. Our approach proposed a cloud-based service designed for the automated assessment of medical rehabilitation of human gait by using video processing. We have chosen this processing technology because it is marker-less, allows fast computation and offers a very good precision of the gait analysis. Cloud computing approach proved to be encouraging and underscores remarkable advantages in comparison with traditional on-site video processing. In this way the patient, after a short training session, can himself/herself make tests and assessments of his/her mobility status, avoiding many consultations of medical or kineto-therapeutic staff.

关键词： Legged locomotion Training Cloud computing Scalability Medical services Gain measurement People with disabilities Real-time systems Security Personnel

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Learning Reduced-Order Linear Parameter-Varying Models of Nonlinear Systems ⁎

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IFAC-PapersOnLine 2024年第15期58卷 265-270页

作者： Patrick J.W. Koelewijn Rajiv Singh Peter Seiler Roland Tóth Sioux Technologies B.V. Eindhoven The Netherlands Control Systems Group Eindhoven University of Technology Eindhoven The Netherlands The MathWorks Inc. Natick USA Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor USA Systems and Control Laboratory HUN-REN Institute for Computer Science and Control Budapest Hungary

In this paper, we consider the learning of a Reduced-Order Linear Parameter-Varying Model (ROLPVM) of a nonlinear dynamical system based on data. This is achieved by a two-step procedure. In the first step, we learn a projection to a lower dimensional state-space. In step two, an LPV model is learned on the reduced-order state-space using a novel, efficient parameterization in terms of neural networks. The improved modeling accuracy of the method compared to an existing method is demonstrated by simulation examples.

关键词： Reduced-order modeling Neural Networks Linear Parameter-Varying Models

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Flexible Manufacturing Concept at Bosch: A low-cost implementation of an Industry 4.0 concept 19

Flexible Manufacturing Concept at Bosch: A low-cost implemen...

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19th IMEKO TC10 Conference on MACRO meets NANO in Measurement for Diagnostics, Optimization and control

作者： Fükő, László Szaller, Ádám Colangelo, Eduardo Nick, Gábor Kádár, Botond Bosch Power Tool Ltd. Miskolc3526 Hungary Institute for Computer Science and Control Budapest1111 Hungary Fraunhofer Institute for Manufacturing Engineering and Automation IPA Stuttgart70569 Germany EPIC InnoLabs Nonprofit Ltd. Budapest1111 Hungary

ISBN: (纸本)9781713884125

Nowadays production companies are in a difficult situation since batch sizes are decreasing, the number of product variants is growing, and the demand is difficult to forecast. New technologies enable to design more complex production systems capable of handling these challenges, but these "Industry 4.0 solutions" are often very expensive and hard to implement. In Bosch Power Tool Ltd. (Hungary), a flexible manufacturing concept was implemented, which enables to produce efficiently even with batch size one, requires much less space from the shop floor, prevents disruptions in production, and last but not least realized in from a relatively small budget. The concept introduced in this paper can be used as a best practice for manufacturing companies facing similar challenges. © 2023 19th IMEKO TC10 Conference "MACRO meets NANO in Measurement for Diagnostics, Optimization and control".

关键词： flexible manufacturing Industry 4.0 smart manufacturing

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Hierarchical Retrieval of High-Resolution Fingerprints Based on Pore Feature

Hierarchical Retrieval of High-Resolution Fingerprints Based...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Jing Ma Yuanrong Xu Suyu Dong Wei Wang School of Computer Science and Technology Harbin Institute of Technology Shenzhen China School of Computer Science and Technology Harbin Institute of Technology Weihai China College of Computer and Control Engineering Northeast Forestry University Harbin China

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

Faced with an escalating number of fingerprint images, most existing retrieval approachs suffer from a common problem: diminishing computational efficiency. This paper presents a hierarchical retrieval system tailored for high-resolution fingerprint images that utilizes abundant pore features and robust recognizability to improve retrieval performance. The framework comprises two core components. Firstly, a CNN-based feature extraction network is established, incorporating an attention mechanism to capture pore features in fingerprint images comprehensively. Subsequently, a hierarchical fingerprint retrieval approach is introduced, involving connection graph construction and a hierarchy of jump table structures for efficient retrieval of query pores. Empirical experiments conducted on high-resolution fingerprint image datasets underscore the system’s effectiveness. Compared with other advanced pore-based fingerprint retrieval methods, the proposed method exhibits a notable rise in the hit rate with reduced penetration rates, significantly reducing the retrieval time.

关键词： Accuracy Image recognition Attention mechanisms Image matching Fingerprint recognition Feature extraction Robustness Computational efficiency Bioinformatics

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Identification of coexistence of biological and non-biological aerosol particles with DAPI (4′,6-diamidino-2-phenylindole) stain

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Particuology 2023年第1期72卷 49-57页

作者： Ting Liu Jiaquan Zhang Junji Cao Han Zheng Changlin Zhan Hongxia Liu Lili Zhang Kai Xiao Shan Liu Dong Xiang Daizhou Zhang School of Environmental Science and Engineering Hubei Polytechnic UniversityHubei Key Laboratory of Mine Environmental Pollution Control and RemediationHuangshi 435003China Institute of Atmospheric Physics Chinese Academy of SciencesBeijing 100029China School of Computer Science and Artificial Intelligence Wuhan University of TechnologyWuhan 430063China Faculty of Environmental and Symbiotic Sciences Prefectural University of KumamotoKumamoto 862-8502Japan

The fluorescent dye 4′,6-diamidino-2-phenylindole (DAPI) has been widely used to stain microorganisms in various environment media. We applied DAPI fluorescence enumeration to airborne microorganisms and found that non-biological particles, including organic compounds, minerals, and soot, were also visible upon exposure to UV excitation under fluorescence microscope. Using laboratory-prepared biological particles as the control, we investigated the feasibility of identifying both biological and non-biological particles in the same sample with DAPI staining. We prepared biological (bacterial, fungi, and plant detritus) and non-biological (biochar, soot, mineral, metal, fly ash, salt) particles in the laboratory and enumerated the particles and their mixture with DAPI. We found that mineral particles were transparent, and biochar, soot, metals and fly ash particles were black under a filter set at excitation 350/50 nm and emission 460/50 nm bandpass (DAPI-BP), while biological particles were blue, as expected. Particles of the water-soluble salts NaCl and (NH_(4))_(2)SO_(4) were yellow under a filter set at excitation 340–380 nm and emission 425 nm long pass (DAPI-LP). Case studies with samples of dustfall, atmospheric aerosols and surface soils could allow for the quantification of the relative number of different types of particles and particles with organic matter or salt coating as well. Fluorescence enumeration with DAPI stain is thus able to identify the co-existence of biological and non-biological particles in the air, at least to the extent of those examined in this study.

关键词： 4',6-diamidino-2-phenylindole(DAPI) Biological particles Nonbiological particles Atmospheric aerosols

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On the Systematic Construction of Lyapunov Functions for Polynomial Systems

On the Systematic Construction of Lyapunov Functions for Pol...

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92nd Annual Meeting of the International Association of Applied Mathematics and Mechanics (GAMM)

作者： Natkowski, Lars Gerbet, Daniel Robenack, Klaus Fraunhofer Institute for Transportation and Infrastructure Systems IVI ZeunerstraBe 38 Dresden01069 Germany Institute of Control Theory Faculty of Electrical and Computer Engineering TU Dresden Georg-Schumann-StraBe 7A Dresden01187 Germany

Lyapunov functions are a widely used tool to evaluate stability properties of nonlinear dynamical systems’ equilibria. In this paper quantifier elimination is used to construct Lyapunov functions for polynomial systems from a parametric ansatz. Because the existing algorithms for quantifier elimination are inherently computationally expensive, a strategy is to simplify the quantifier elimination problem beforehand. A method is presented that may help simplifying the problem of finding suitable Lyapunov functions by deriving easier to evaluate necessary conditions. Finally, the introduced method is applied to an example system to show local asymptotic stability of an equilibrium point by constructing a Lyapunov function. © 2023 The Authors.

关键词： Lyapunov functions

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Keynote Talk: Qualitative model based diagnosis of complex systems using decomposition 22

Keynote Talk: Qualitative model based diagnosis of complex s...

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Proceedings of the 7th International Conference on Sustainable Information engineering and Technology

作者： Katalin M. Hangos Systems and Control Laboratory Institute for Computer Science and Control Hungary and Department of Electrical Engineering and Information Systems University of Pannonia Hungary

ISBN: (纸本)9781450397117

Decomposition offers the potential to reduce the complexity of model-based optimization, prediction, control and diagnosis by accounting for the structure and sparsity of the describing model. Motivated by this fact, a rich and powerful collection of decomposition methods are available for model based diagnosis of large-scale complex dynamic systems, too. At the same time, one usually does not have enough information about a large-scale complex dynamic system to construct its precise enough model, so a kind of qualitative dynamic model is often used for the diagnosis [1]. Two structural decomposition based qualitative diagnostic methods are presented in this lecture, together with their component-driven system decomposition ***, a model-based diagnostic method is described that is able to detect and isolate non-technical losses (illegal loads) in low voltage electrical grids of one transformer area [2]. As a preliminary off-line step of the diagnosis, a powerful electrical decomposition method is proposed, which breaks down the overall network to subsystems with one feeder layout enabling to make the necessary computations efficient. The diagnostic method is based on analyzing the differences between the measured and model-predicted voltages. The uncertainty in the model parameters together with the measurement uncertainties are also taken into account to make the approach applicable in real-world cases. The proposed method is able to detect and localize multiple illegal loads, and the amount of the illegal consumption can also be *** a second case study, a high level decomposition approach for process system fault diagnosis using event traces is given [3], [4]. Using a simple component graph model behind the process system and the measured trace applied for the diagnosis, the method can find the root cause(s) of propagating failures between separate components. The method can connect individually operating lower-level component-specific diag

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Attention-enhanced Relation Network for Few-shot Image Classification 23

Attention-enhanced Relation Network for Few-shot Image Class...

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6th International Conference on Image and Graphics Processing, ICIGP 2023

作者： Li, Jinyang Tong, Jiahui Gao, Guangyu Xu, Wenbin School of Computer Science and Technology Beijing Institute of Technology China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-Mechanical Engineering Institute Beijing China Science and Technology on Optical Radiation Laboratory Beijing Institute of Environmental Characteristics Beijing100854 China

ISBN: (纸本)9781450398572

Traditional deep learning models firmly rely on a large amount of labeled data during pre-training. Whereas it lacks generalization in the face of unfamiliar categories. Recently, few-shot learning is a hot topic in computer vision to classify unseen classes with limited labels. A representative approach is to extract features from the support and query sets, respectively, and compare similarities via metric learning. However, convolutional neural networks often focus only on a local region and ignore the global region, which severely reduces the accuracy of the matching. Specifically, in this paper, we pile lightweight attention-based blocks in the embedding module, which combines an adaptive kernel size 2D convolutional network with a cross-channel attention mechanism to encode multi-scale features and implicitly increase the receptive field. The SE-relation module chooses to construct learnable non-linear comparators to compare the relationship utilizing channel information. Finally, we show experimental results on standard few-shot testing benchmarks such as mini-ImageNet and tiered-ImageNet to demonstrate effectiveness. © 2023 ACM.

关键词： Image classification

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OPENPATCH: A 3D PATCHWORK FOR OUT-OF-DISTRIBUTION DETECTION

arXiv

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arXiv 2023年

作者： Rabino, Paolo Alliegro, Antonio Borlino, Francesco Cappio Tommasi, Tatiana Department of Control and Computer Engineering Politecnico di Torino Italy Italian Institute of Technology Italy

Moving deep learning models from the laboratory setting to the open world entails preparing them to handle unforeseen conditions. In several applications the occurrence of novel classes during deployment poses a significant threat, thus it is crucial to effectively detect them. Ideally, this skill should be used when needed without requiring any further computational training effort at every new task. Out-of-distribution detection has attracted significant attention in the last years, however, the majority of the studies deal with 2D images ignoring the inherent 3D nature of the real-world and often confusing between domain and semantic novelty. In this work, we focus on the latter, considering the objects’ geometric structure captured by 3D point clouds regardless of the specific domain. We advance the field by introducing OpenPatch which builds on a large pretrained model and simply extracts from its intermediate features a set of patch representations that describe each known class. For any new sample, we obtain a novelty score by evaluating whether it can be recomposed mainly by patches of a single known class or rather via the contribution of multiple classes. We present an extensive experimental evaluation of our approach for the task of semantic novelty detection on real-world point cloud samples when the reference known data are synthetic. We demonstrate that OpenPatch excels in both the full and few-shot known sample scenarios, showcasing its robustness across varying pre-training objectives and network backbones. The inherent training-free nature of our method allows for its immediate application to a wide array of real-world tasks, offering a compelling advantage over approaches that need expensive retraining efforts. © 2023, CC BY.

关键词： Semantics

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A UAV-based compressive algorithm for minimizing the energy consumption of large-scale WSNs 2

A UAV-based compressive algorithm for minimizing the energy ...

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2023 2nd International Symposium on Intelligent Unmanned Systems and Artificial Intelligence, SIUSAI 2023

作者： Lv, Cuicui Yang, Linchuang Zhang, Xinxin Wang, Peijin Du, Zhenbin Li, Xiangming Wang, Peng School of Computer and Control Engineering YanTai University YanTai264005 China Central Research Institute Yantai Jereh Oilfield Services Group Co. Ltd. YanTai264003 China School of Environment and Materials Engineering YanTai University YanTai264005 China

In large-scale environmental monitoring, massive sensor nodes regularly collect data and transmit them over long distances, which burdens the network and leads to the increased energy consumption. To deal with this problem, we develop an Unmanned Aerial Vehicle (UAV)-based compressive algorithm. In this algorithm, the network clustering technologies and Compressive Sensing are exploited to decrease the amount of data throughout the network. Monte Carlo method is used to group sensor nodes into clusters. The UAV is dispatched as a mobile agent to collect data from the cluster heads. Compared with the benchmark algorithms, the simulations demonstrate that the algorithm proposed in this paper can decrease the network's energy consumption and obtain better environmental monitoring results. © Published under licence by IOP Publishing Ltd.

关键词： Energy utilization

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