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3rd International Conference on Ubiquitous and Future Networks, ICUFN 2011

作者： Majhi, Sudhan Qian, Hua Xiang, Weidong Addepalli, Sateesh Gao, Zhenguo School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences China Electrical and Computer Engineering University of Michigan Dearborn United States Advanced Architecture and Research Cisco Systems Inc. United States College of Automation Harbin Engineering University Harbin China

ISBN: (纸本)9781457711763

This paper analyzes the outage probability of opportunistic decode-and-forward relaying network over asymmetric fading channels where cooperative nodes are located at distributed locations and signals experience asymmetric and independent Rayleigh and Rician channels. The outage probability of such a wireless relaying network is theoretically derived in high SNR scenarios, which is thereafter verified through Monte-Carlo simulations. It is shown that the variation of the outage probability of a relaying network under different asymmetric channels is independent to the number of relay nodes. © 2011 IEEE.

关键词： Fading channels

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Data-Based Condition Monitoring of an X-Ray Analyzer

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IFAC Proceedings Volumes 2001年第18期34卷 89-94页

作者： Marko Mattila Heikki Hyötyniemi Kari Koskineo Kari Saloheimo Information and Computer Systems in Automation Helsinki University of Technology P.O. Box 5400 FIN-02015 HUT Finland Outokumpu Mintec Oy P.O. Box 84 FIN-02201 Espoo Finland

Fault diagnosis and condition monitoring can be based on analytical process models, explicit knowledge or direct process measurements. When the structure of the process is unknown, the data-based approach based on the measurements is the most practical one. This is the case also with X-ray fluorescence analyzers. Appropriate analyzer calibration is a key factor in obtaining the best performance from the analysis system. As the mineralogy of the processed material is slowly changing the calibration must be maintained over time. The possible indicators for the calibration validity are studied in this paper.

关键词： calibration condition monitoring dynamic modeling fault diagnosis MLR PCA PLS subspace identification

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Transfer Learning for Russian Handwriting Recognition 46

Transfer Learning for Russian Handwriting Recognition

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46th International Conference on Telecommunications and Signal Processing, TSP 2023

作者： Levkov, Andrey Kaplun, Dmitry Safonova, Anastasiia St. Petersburg Electrotechnical University "leti" Depart. of Computer Engineering St. Petersburg Russia St. Petersburg Electrotechnical University "leti" Depart. of Automation and Control Processes St. Petersburg Russia St. Petersburg Electrotechnical University "leti" Depart. of Information Systems St. Petersburg Russia

ISBN: (纸本)9798350303964

Handwriting recognition is one of the most important tasks in computer vision. Despite the variety of methods and algorithms used for text recognition in various languages, the recognition of handwritten Russian words is still a completely unsolved problem, which keeps the relevance of this topic. This paper proposes the application of a convolutional neural network (CNN) to the task of recognizing the 100 most frequently used Russian words, trained on a new unique dataset. A unique algorithm for extracting Russian handwritten words from forms was applied to obtain a new dataset. The paper also presents the results of a comparison of such powerful models as VGG-16, VGG-19, ResNet-50, and ResNet-101, which were trained using transfer learning technology. The best results were shown by VGG-16 with 98.7% accuracy, and the worst results were shown by ResNet-50 with 80% accuracy. © 2023 IEEE.

关键词： Convolutional neural networks

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An Adaptive-Gain Recurrent Neural Network for Solving the Joint-Angle Drift Issues of Redundant Manipulators

An Adaptive-Gain Recurrent Neural Network for Solving the Jo...

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2023 International Annual Conference on Complex systems and Intelligent Science, CSIS-IAC 2023

作者： Zheng, Boyu Li, Chunquan Zhang, Zhijun Yu, Junzhi Liu, P.X. School of Information Engineering Nanchang University Nanchang330031 China School of Automation Science and Engineering South China University of Technology Guangzhou510640 China College of Engineering Peking University Beijing100871 China Carleton University Department of Systems and Computer Engineering OttawaONK1S 5B6 Canada

ISBN: (纸本)9798350309003

This paper proposes a new adaptive-gain recurrent neural network (AG-RNN) to effectively cope with the joint-angle drift issues in redundant manipulators. Specifically, a joint-angle drift-free with the feedback control of the velocity layer motion equation (JADF-FC) is proposed via an optimization criterion for synchronously optimizing linear terms and quadratic. Then, the JADF-FC is reasonably formulated into a standard quadratic programming (QP) issue. Different from the previous recurrent neural networks (RNNs), the AG-RNN proposed in this paper constructs an error-based differential equation with a new adaptive-gain. It should be noted that the proposed adaptive-gain does not gradually approach infinity as time increases, which is more in line with actual hardware implementation requirements than the existing time-variant-gain. The adaptive-gain can reduce the joint-angle drift errors of the redundant manipulator. Therefore, the proposed AG-RNN can solve the QP problem of the manipulator more effectively and quickly. To validate the performance of the proposed AG-RNN, it is compared with representative RNNs. The experimental results indicate that smaller joint-angle drift errors can be get by the proposed AG-RNN solving JADF-FC scheme than the other solutions when solving the joint-angle drift issues. © 2023 IEEE.

关键词： Quadratic programming

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Frequency Domain Identification of the MIT Interferometer Testbed in Generalized Orthogonal Basis

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IFAC Proceedings Volumes 1997年第11期30卷 1631-1635页

作者： J. Bokor M. Athans Systems and Control Laboratory Computer and Automation Institute Hungarian Academy of Sciences Budapest XI. Kende u. 13-17. H-1111 Hungary Laboratory for Information and Decision systems Massachusetts Institute of Technology Cambridge MA 02139 USA

This paper presents a new approach for approximate identification under the H 2 criterion where the model is parametrized in a basis generated by apriori knowledge on the location of system poles. A frequency domain i... 详细信息

关键词： Generalized Fourier series Generalized othogonal basis Lightly damped structures H 2 -identification

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Integration of ANN for Accurate Estimation and Control in Wastewater Treatment 28

Integration of ANN for Accurate Estimation and Control in Wa...

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28th IEEE International Conference on Emerging Technologies and Factory automation, ETFA 2023

作者： Ţiru, Andreea Elena Vasiliev, Iulian Diaconu, Larisa Vilanova, Ramon Voipan, Daniel Ratnaweera, Harsha Dunǎrea de Jos University of Galaţi Department of Automatic Control and Electrical Engineering Galaţi Romania Autonomous University of Barcelona Department of Automation Systems and Advanced Control Research Barcelona Spain Dunǎrea de Jos University of Galaţi Department of Computer Science and Information Technology Galaţi Romania Ås Norway

ISBN: (纸本)9798350339918

The management of wastewater is a significant global concern that calls for innovative solutions to lessen its negative effects on the environment. Conventional techniques of treating wastewater need improvement in order to deal with newly discovered contaminants, which highlights the importance of providing precise estimates of process performance and resource requirements. The worsening water shortage situation requires a paradigm shift in which wastewater is viewed as a useful resource. It is possible to create an economy that is both sustainable and circular by treating and recycling wastewater, putting less pressure on freshwater supplies, and leaving as little of an environmental footprint as possible. This study investigates the use of Artificial Neural Networks (ANNs) as software estimators in the treatment of wastewater, with a particular emphasis on predicting ammonium concentrations in effluent. In order to deal with imbalanced time-series data, the research introduces innovative data pretreatment strategies. These techniques include a Sliding Window protocol, Data Normalization, and a K-Fold training scheme. This illustrates the potential of ANNs to revolutionize wastewater treatment procedures and drive developments in this field. The suggested method demonstrates higher performance when estimating pollutant concentrations, showing the ability of ANNs to do so. © 2023 IEEE.

关键词： Neural networks

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Classifying patent images

Classifying patent images

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2011 Cross Language Evaluation Forum Conference, CLEF 2011

作者： Morzinger, Roland Horti, Andras Thallinger, Georg Bhatti, Naeem Hanbury, Allan Joanneum research digital Institute for Information and Communication Technologies Steyrergasse 17 Graz8010 Austria Institute for Computer-Aided Automation Vienna University of Technology Favoritenstr. 9-11/183 Vienna1040 Austria Institute for Software Technology and Interactive Systems Vienna University of Technology Favoritenstr. 9-11/188 Vienna1040 Austria

This report presents the work carried out for the image classification task in the course of the CLEF-IP 2011 competition. Based on the visual content, patent images are automatically classified into several drawing types, such as abstract drawings, tables, flow chart and graphs. For that purpose, a series of SVM classifiers, multi-modal fusion schemes and a variety of content-based low-level features for black and white images were used. The overall reported performance was promising. Our best runs achieved a true positive rate of over 66% and the reported average area under curve is over 0.9.

关键词： Image classification

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A conceptual framework for semantic case-based safety analysis

A conceptual framework for semantic case-based safety analys...

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International Conference on Emerging Technologies and Factory automation (ETFA)

作者： Olawande Daramola Tor Stålhane Thomas Moser Stefan Biffl Department of Computer and Information Science Norwegian University of Science and Technology Norway Christian Doppler Laboratory for Software Engineering Integration for Flexible Automation Systems Vienna University of Technology Austria

Hazard and Operability (HAZOP) Analysis and Failure Mode and Effect Analysis (FMEA) are among the most widely used safety analysis procedures in the development of safety-critical and embedded systems. These analyses are generally perceived as complex and time-consuming, hindering an effective reuse of previous results or experiences. In this paper we present a conceptual semantic case-based framework for safety analysis, which facilitates the reuse of previous HAZOP and FMEA experiences in order to reduce the time and effort associated with these analyses. We present the core technologies of the conceptual framework and evaluated a prototype of the framework, KROSA, in an experiment with domain experts at ABB Norway. Initial results confirm the viability of the conceptual framework for industrial application.

关键词： Ontologies Semantics Natural language processing Libraries Hazards Humans

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Multitarget Tracking Applications of the Bi-i Platform: Attention-selection, Tracking and Navigation

Multitarget Tracking Applications of the Bi-i Platform: Atte...

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IEEE International Workshop on Cellular Nanoscale Networks and their Applications, (CNNA)

作者： Gergely Timar Csaba Rekeczky Analogic and Neural Computing Systems Laboratory of the Computer and Automation Institute of the Hungarian Academy of Sciences Budapest Hungary Information Technology Department Pazmany Peter Catholic University Budapest Hungary

A multitarget tracking framework implemented on the Bi-i platform is presented. The demonstration applications include a target tracking system with laser actuation, an attention-selection algorithm and a laser dot de... 详细信息

关键词： Navigation Target tracking Cellular neural networks Application software computer networks Laser theory Circuits and systems Circuit testing Laboratories automation

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Software Evolution of I4.0 Digital Twins with Semantic Patching

Software Evolution of I4.0 Digital Twins with Semantic Patch...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Nico Braunisch Sebastian Heppner Igor Garmaev Marko Ristin Torben Miny Tobias Kleinert Hans Wernher Van De Venn Martin Wollschlaeger Institute of Applied Computer Science TU Dresden Dresden Germany Chair of Information and Automation Systems RWTH Aachen University Aachen Germany Institute of Mechatronic Systems Zurich University of Applied Sciences (ZHAW) Zurich Switzerland

ISBN: (数字)9798350394085

ISBN: (纸本)9798350394092

We examine semantic patching, an important technique of software evolution, that allows us to automate to a large extent the adaption of external open-source libraries for Digital Twins with a high degree of correctness. While this technique is widely known in specialized software engineering circles, we aim to popularize it among the automation community. We evaluate and compare its advantages against other adaptation methods in three practical use cases where the widely-used aas-core Software Development Kit is adapted for different lighthouse projects in Industrie 4.0, written in Python, C#, and Java, respectively. The results highlight the effectiveness of semantic patching in automating the process, minimizing errors and ensuring a seamless transition.

关键词： Industries Industrial electronics Java Semantics Software Libraries Digital twins

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