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15th Asian Conference on computer Vision, ACCV 2020

作者： He, Zewen Wu, Rui Zhang, Dingqian Institute of Automation Chinese Academy of Sciences Beijing China School of Computer and Control Engineering University of Chinese Academy of Science Beijing China Horizon Robotics Beijing China

ISBN: (纸本)9783030695347

Recently, data augmentation techniques for training conv-nets emerge one after another, especially focusing on image classification. They’re always applied to object detection without further careful design. In this paper we propose COG, a general domain migration scheme for augmentation. Specifically, based on a particular augmentation, we first analyze its inherent inconsistency, and then adopt an adaptive strategy to rectify ground-truths of the augmented input images. Next, deep detection networks are trained on the rectified data to achieve better performance. Our extensive experiments show that our method COG’s performance is superior to its competitor on detection and instance segmentation tasks. In addition, the results manifest the robustness of COG when faced with hyper-parameter variations, etc. © 2021, Springer Nature Switzerland AG.

关键词： Object detection

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A Single-Cell Clustering Algorithm Based on Structure Perturbation Non-Negative Matrix Factorization

A Single-Cell Clustering Algorithm Based on Structure Pertur...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Jiang, Hanjing Wang, Meineng Zhang, Luping Huang, Yu-An Li, Yangyuan Huang, Yabing Huazhong University of Science and Technology Key Laboratory of Image Information Processing and Intelligent Control Education Ministry of China Institute of Artificial Intelligence School of Artificial Intelligence and Automation Hubei Wuhan430074 China China University of Mining and Technology School of Computer Science and Technology Xuzhou221116 China Yichun University School of Mathematics and Computer Science Yichun336000 China East China University of Technology School of Information Engineering Nanchang330013 China Northwestern Polytechnical University School of Computer Science Xi'an710129 China Renmin Hospital Wuhan University Department of Pathology Wuhan430060 China

ISBN: (纸本)9798350386226

The advent of single-cell RNA sequencing (scRNA-seq) has facilitated the acquisition of high-resolution data regarding cell heterogeneity across various tissues. A fundamental and critical step in the analysis of scRNA-seq data is cell type identification. An appropriate graph construction strategy can reflect the topological structure between cells and allows for detailed exploration of the relationships between cells and genes. Given the sparsity of scRNA-seq data and the pronounced noise generated by shallow sequencing, choosing an appropriate graph construction strategy has become a significant challenge. In this paper, we propose a single-cell clustering method, named Sc-PNNMF, based on structural perturbation of nonnegative matrix factorization. Sc-PNNMF employs a structural perturbation algorithm to optimize the gene expression matrix. The optimized matrix guides the matrix factorization process, effectively overcoming the impact of data sparsity and significant noise in gene expression data on the graph construction strategy. We compared the clustering abilities of Sc-PNNMF with five other methods on ten real datasets. © 2024 IEEE.

关键词： Non-negative matrix factorization

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Finite-time robust performance improvement for non-linear systems in the presence of input non-linearity and external disturbance

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IET control Theory and Applications 2023年第6期17卷 672-682页

作者： Wang, Haoping Ghaffari, Valiollah Mobayen, Saleh Bartoszewicz, Andrzej Fekih, Afef Assawinchaichote, Wudhichai School of Automation Nanjing University of Science and Technology Nanjing China Department of Electrical Engineering Persian Gulf University Bushehr Iran Graduate School of Intelligent Data Science National Yunlin University of Science and Technology Yunlin Douliou Taiwan Institute of Automatic Control Lodz University of Technology Lodz Poland Department of Electrical and Computer Engineering University of Louisiana at Lafayette LafayetteLA United States Department of Electronic and Telecommunication Engineering Faculty of Engineering King Mongkut's University of Technology Thonburi Bangkok Thailand

The main focus of this research is on improving the performance of dynamic systems with actuator non-linearities and time-varying disturbances. To this end, using the concept of finite-time stability, a novel observer is presented to estimate the disturbances in systems with input non-linearities. Then, introducing an innovative sliding manifold, a robust observer-based technique is derived to guarantee the finite-time stability of the sliding surface. Hence, the closed-loop system would be stable in the presence of hard non-linearities and time-varying disturbances. The performance of the proposed approach was assessed in using a simulation study of two numerical examples. The obtained results and comparison with a conventional method confirmed the benefits of the suggested approach. © 2022 The Authors. IET control Theory & Applications published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.

关键词： Closed loop systems

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Towards a Test Framework for Reactive (Type 2) Asset Administration Shell Implementations

Towards a Test Framework for Reactive (Type 2) Asset Adminis...

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International Conference on Emerging Technologies and Factory automation (ETFA)

作者： Torben Miny Sebastian Heppner Igor Garmaev Marko Ristin Björn Otto Nico Braunisch Michael Jacoby Tobias Kleinert Hans Wernher van de Venn Martin Wollschlaeger Chair of Information and Automation Systems RWTH Aachen University Aachen Germany Institute of Mechatronic Systems Zurich University of Applied Sciences (ZHAW) Zurich Switzerland Institute for Automation and Communication Otto von Guericke University Magdeburg Germany Institute of Applied Computer Science TU Dresden Dresden Germany Department Information Management and Production Control (ILT) Fraunhofer IOSB Karlsruhe Germany

ISBN: (数字)9798350361230

ISBN: (纸本)9798350361247

As Industrie 4.0 (I4.0) technologies continue to advance, ensuring the reliability and robustness of emerging standards like Asset Administration Shells (AAS) becomes paramount. This paper introduces a comprehensive testing approach for reactive (a.k.a. Type 2) AAS implementations, addressing the challenges posed by their intricate and dynamic nature. Our methodology adopts a design-by-contract approach to formalize API behavior. We design the client as a test oracle, where code contracts extensively validate the AAS operations, their interactions and effects. The related test cases cover various operation chains, including superpaths, service specifications, and serialization modifiers. The objective of this approach is to enhance the reliability and effectiveness of testing in the evolving landscape of AAS Type 2 implementations.

关键词： Industries Codes Robustness Standards Manufacturing automation Contracts Testing

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Approximate state estimation with large-scale sensor networks under event-based sensor scheduling strategy

Approximate state estimation with large-scale sensor network...

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IEEE Conference on Decision and control

作者： Xinhui Liu Meiqi Cheng Dawei Shi Ling Shi MIIT Key Laboratory of Servo Motion System Drive and Control School of Automation Beijing Institute of Technology Beijing China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Kowloon Hong Kong China

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

In this paper, we investigate the issues of real-time sensor scheduling and state estimator design within large-scale sensor network systems. Specifically, data redundancy sometimes occurs in large-scale sensor arrays due to the excessive proximity of sensing units in the spatial domain, leading to high similarity in their measurement data. Currently, it is difficult to account for such redundancy in sensor scheduling algorithms found in existing literature, where the optimal subset of sensors is generally selected by optimizing objective functions formulated from certain performance criteria. To tackle this problem, we introduce an event-based sensor scheduling strategy, the triggering condition of which is designed founded on the similarity of sensor data, so as to identify the most informative subset of sensors for state estimation. To evaluate the impact of the sensor scheduling protocol on system observability, we propose a new notion of $\mathscr{E}(\varepsilon)$-observability, based on which an observability criterion is derived. In addition, we have designed a set-valued state estimation algorithm, which takes into account the intricate measurement information structure inherent within the sensor selection mechanism. The performance enhancement of the proposed estimator is also investigated. Finally, numerical experiments are conducted to validate the effectiveness of the proposed estimation algorithm and to verify the performance improvement.

关键词： Protocols Event detection Scheduling algorithms Redundancy Approximation algorithms Real-time systems Sensors State estimation Observability Sensor arrays

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On the Complexity of Computing the Maximal Positive Invariant Set

On the Complexity of Computing the Maximal Positive Invarian...

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European control Conference (ECC)

作者： Bogdan Gheorghe Florin Stoican Ionela Prodan Faculty of Automation Control and Computer Science National University of Science and Technology Politehnica Bucharest Romania Grenoble INP LCIS Univ. Grenoble Alpes Institute of Engineering and Management Univ. Grenoble Alpes Valence France

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

Computing the maximal (robust) positive invari-ant (M(R)PI) set for linear dynamics and a polyhedral constraint set is well-known in the literature but, the effects and limitations of the different methods employed are not sufficiently clear, especially for high dimensional systems. In this paper we propose a systematic analysis of the existing techniques as well as the application of new ideas to accelerate the computation of the MPI set. This includes new stop conditions for the set recurrence that spans it. We analyze and compare these variations over a dynamical system whose dimension can be arbitrarily increased to draw conclusions about their relative strengths and weaknesses.

关键词： Systematics Europe Complexity theory Dynamical systems Predictive control

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Designing a Secure Smart Remote Patient Monitoring and Warning System using Big Data and Internet of Things Ecosystems 10

Designing a Secure Smart Remote Patient Monitoring and Warni...

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17th INDIACom;2023 10th International Conference on Computing for Sustainable Global Development, INDIACom 2023

作者： Ramesh, S.P. Abdulwahid, Ali Hadi Anjum, Afsana Venkatesh, N. Singh, Rajesh Chakravarthi, M. Kalyan Amet University Department of Computer Science and Engineering Tamil Nadu Kanathur India Southern Technical University Engineering Technical College Department of Control and Automation Basra Iraq Jazan University Department of Information Technology and Security Jazan Saudi Arabia School of Computer Science and Artificial Intelligence Sr University Telangana Warangal India Uttaranchal Institute of Technology Uttaranchal University India School of Electronics Engineering VIT-AP University Amaravathi India

ISBN: (纸本)9789380544472

The demand on healthcare is growing as a result of the expanding global population, rising demands for successful treatment, and an underlying improvement in life quality. Consequently, healthcare remains one of the most significant social and economic problems in the world, necessitating the development of new and more sophisticated scientific and technological treatments.E-health services are provided via personalised healthcare systems to meet the medical and support needs of the ageing population. An important development in the Big Data age is the Internet of Things, which facilitates several real-time engineering solutions through improved services. Healthcare systems are now using analytics over IoT data streams as a stream of user data to find new information, forecast rapid recognition, and make decisions on life-threatening situations. In this study, researchers have carried out a thorough review of the hottest recent revolutionary technologies in bespoke healthcare systems, with a focus on hypervisor, cloud infrastructure, big data analytic, the Web of Things, and smartphone apps. In order to make early disease detection and diagnosis possible, it is important to develop a better healthcare system. We have examined these problems and suggested potential solutions while offering secure e-health services. The purpose of this study is to design a smart and secure remote monitoring and warning system using the latest emerging technologies in 21stcentury such as big data analytics and Internet of Things (IoT) ecosystems. In this study the researchers discussed a detailed research methodology to meet the outcomes of the reerach. All the relevant findings and analysis are explained in descriptive manner. Moreover, this study highlights the constantly expanding requirements for better medical systems in the present and offers potential directions for future research. © 2023 Bharati Vidyapeeth, New Delhi.

关键词： Internet of things

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Language-driven Grasp Detection with Mask-guided Attention

arXiv

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arXiv 2024年

作者： Van Vo, Tuan Vu, Minh Nhat Huang, Baoru Vuong, An Le, Ngan Vo, Thieu Nguyen, Anh FPT Software AI Center Viet Nam Automation & Control Institute TU Wien Austria GmbH Austria Imperial College London United Kingdom Department of Computer Science & Computer Engineering University of Arkansas United States National University of Singapore Singapore Department of Computer Science University of Liverpool United Kingdom

Grasp detection is an essential task in robotics with various industrial applications. However, traditional methods often struggle with occlusions and do not utilize language for grasping. Incorporating natural language into grasp detection remains a challenging task and largely unexplored. To address this gap, we propose a new method for language-driven grasp detection with mask-guided attention by utilizing the transformer attention mechanism with semantic segmentation features. Our approach integrates visual data, segmentation mask features, and natural language instructions, significantly improving grasp detection accuracy. Our work introduces a new framework for language-driven grasp detection, paving the way for language-driven robotic applications. Intensive experiments show that our method outperforms other recent baselines by a clear margin, with a 10.0% success score improvement. We further validate our method in real-world robotic experiments, confirming the effectiveness of our approach. © 2024, CC BY.

关键词： Semantic Segmentation

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Dynamic model of tissue electroporation on the basis of biological dispersion and Joule heating

arXiv

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arXiv 2023年

作者： Guedert, R. Andrade, D.L.L.S. Silva, J.R. Pintarelli, G.B. Suzuki, D.O.H. Institute of Biomedical Engineering Federal University of Santa Catarina SC Florianópolis Brazil Department of Control Automation and Computer Engineering Federal University of Santa Catarina SC Blumenau Brazil

Electroporation is a complex, iterative, and nonlinear phenomenon that is often studied by numerical simulations. In recent years, tissue electroporation simulations have been performed using static models. However, the results of a static model simulation are restricted to a fixed protocol signature of the pulsed electric field. This paper describes a novel dynamic model of tissue electroporation that also includes tissue dispersion and temperature to allow time-domain simulations. We implemented the biological dispersion of potato tubers and thermal analysis in a commercial finite element method software. A cell electroporation model was adapted to account for the increase in tissue conductivity. The model yielded twelve parameters, divided into three dynamic states of electroporation. Thermal analysis describes the dependence of tissue conductivity on temperature. The model parameters were evaluated using experiments with vegetal tissue (Solanum tuberosum) under electrochemotherapy protocols. The proposed model can accurately predict the conductivity of tissue under electroporation from 10 kV/m to 100 kV/m. A negligible thermal effect was observed at 100 kV/m, with a 0.89 ◦C increase. We believe that the proposed model is suitable for describing the electroporation current on a tissue scale and also for providing a hint on the effects on the cell membrane. © 2023, CC BY-NC-SA.

关键词： Iterative methods

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Event-Based control of Mobile Objects over an Unreliable Network

Event-Based Control of Mobile Objects over an Unreliable Net...

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IEEE Conference on Decision and control

作者： Michael Schwung Jan Lunze Institute of Automation and Computer Control Ruhr University Bochum Germany

ISBN: (纸本)9781665436601

This paper extends an event-based method for the cooperative control of two mobile objects to cope with unknown signal delays induced by the communication network and the computation times of the controllers. The objects are locally controlled and move autonomously along their planned trajectories. The first object called the stand-on object can freely change its trajectory at any time. The second object named the give-way object has to adapt its trajectory to avoid collisions by invoking communication at event time instants. It is provided with an event-based control unit introduced in a previous paper. Whereas the signal delays were neglected in earlier publications, in this paper these delays are considered and the event generation is improved accordingly. An event-based delay estimator generates an estimate of the signal delays, which is utilised for the event generation by using a two-state Markov model that represents the properties of the network. The event-based approach is derived by combining methods from communication technology and control theory. A simulation study with two quadrotors shows the benefits of the method.

关键词： Delay effects Conferences Packet loss Markov processes Generators Data models Delays

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