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Transformation from System Design models in SysML to Executable IEC 61499 Function Block models 6

Transformation from System Design Models in SysML to Executa...

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6th International conference on control, Robotics and Cybernetics, CRC 2021

作者： Cao, Yue Liu, Yusheng Huang, Bo Huang, Ganming Ye, Xiaoping Zhejiang University of Technology College of Computer Science and Technology Hangzhou China Zhejiang University State Key Lab. of CADCG Hangzhou China Digital Twin Shanghai Key Laboratory of Aircraft Engine China Lishui University College of Engineering and Design Lishui China

ISBN: (纸本)9781665424370

Designing automation systems requires a joint effort from different domains including the control software and controlled plants. System design is the foundation of the discipline-specific design processes and hence its verification is critical to the success of the whole project. Transforming system design models to simulation models is a common method for system verification. IEC 61499 Function Block (FB) is a feasible target simulation modeling language because of its executable specification nature. However, existing approaches can only generate initial control design from SysML models, which means the generated FB models are not executable. In this study, an approach to transform SysML design models into executable FB models is proposed. First, the execution semantics of hybrid automaton (HA) and execution control chart (ECC), which are the behavior modeling formalisms of SysML and IEC 61499, respectively is analyzed. Then, their semantic similarities and differences are identified. Finally, transformation rules to tackle the semantic differences are proposed so that the missing execution details of FB models can be automatically generated. A CNC bending machine is used as a case study to illustrate the proposed approach. © 2021 IEEE.

关键词： Systems analysis

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Optimal control of Point Sources in Richards-Klute equation 1st

Optimal Control of Point Sources in Richards-Klute equation

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1st International conference on computer science, Engineering and Education Applications, ICCSEEA2018

作者： Tymoshenko, A. Klyushin, D. Lyashko, S. Faculty of Computer Science and Cybernetics Taras Shevchenko National University of Kyiv Kyiv Ukraine

ISBN: (纸本)9783319910079

This article represents an approach to humidity control in porous media, which combines linearization with numerical methods. The main problems and several ideas to solve them are mentioned. The main interest for our research is humidity regulation, described by Richards-Klute equation. The optimization problem is to minimize the difference between a reached state and a desired state. Modelling moisture transport in porous media requires taking into account the processes of heat transfer, chemical and physical processes, as they have a considerable influence on characteristics of the medium. First of all, a mathematical model is developed with a number of simplifications: moisture incompressibility, constant external pressure, limitations on transfer or isothermal requirements. Then, it is often preferable to make a transition to linear problem, as this case is explored and it allows us to use more theoretical background for the research. After that, numerical models and time and space discretization are constructed according to the related problem. When the process is represented in a suitable way, control and optimization problems arise and should be solved. © Springer International Publishing AG, part of Springer Nature 2019.

关键词： Optimization

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1st International conference on computer science, Engineering and Education Applications, ICCSEEA2018

1st International Conference on Computer Science, Engineerin...

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1st International conference on computer science, Engineering and Education Applications, ICCSEEA2018

ISBN: (纸本)9783319910079

The proceedings contain 74 papers. The special focus in this conference is on computer science, Engineering and Education Applications. The topics include: Video shots retrieval with use of pivot points;imbalance data classification via neural-like structures of geometric transformations model: Local and global approaches;information technology of the system control of water use within river basins;data mining for a model of irrigation control using weather web-services;hardware and software complex for automatic level estimation and removal of gaussian noise in images;building a generalized peres gate with multiple control signals;mathematical model of queue management with flows aggregation and bandwidth allocation;planning automation in discrete systems with a given structure of technological processes;Fault-tolerant multiprocessor systems reliability estimation using statistical experiments with GL-models;risk modeling of accidents in the power system of Ukraine with using bayesian network;optimal control of Point Sources in Richards-Klute equation;method of calculation of averaged digital image profiles by envelopes as the conic sections;on formalization of semantics of real-time and cyber-physical systems;optimization of operation regimes of irrigation canals using genetic algorithms;monitoring of laser welding process using its acoustic emission signal;qoS ensuring over probability of timely delivery in multipath routing;icing thickness prediction of overhead power transmission lines using parallel coordinates and convolutional neural networks;prediction of dissolved gas concentration in oil based on fuzzy time series;a comprehensive analysis of the bat algorithm;complex steganalytic method for digital videos;video data compression methods in the decision support systems.

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Methodologies for continuous life-long machine learning for AI systems

Methodologies for continuous life-long machine learning for ...

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2018 International conference on Artificial Intelligence, ICAI 2018 at 2018 World Congress in computer science, computer Engineering and Applied Computing, CSCE 2018

作者： Crowder, James A. Carbone, John N. Colorado Engineering Inc. Colorado SpringsCO80920 United States Electrical and Computer Engineering Dept. Southern Methodist University DallasTX75205 United States

ISBN: (纸本)1601324804

Current machine learning architectures, strategies, and methods are typically static and non-interactive, making them incapable of adapting to changing and/or heterogeneous data environments, either in real-time, or in near-real-time. Typically, in real-time applications, large amounts of disparate data must be processed, learned from, and actionable intelligence provided in terms of recognition of evolving activities. Applications like Rapid Situational Awareness (RSA) used for support of critical systems (e.g., Battlefield Management and control) require critical analytical assessment and decision support by automatically processing massive and increasingly amounts of data to provide recognition of evolving events, alerts, and providing actionable intelligence to operators and analysts [2 and 4]. Herein we prescribe potential methods and strategies for continuously adapting, life-long machine learning within a self-learning and self-evaluation environment to enhance real-time/near real-time support for mission critical systems. We describe the notion of continuous adaptation, which requires an augmented paradigm for enhancing traditional probabilistic machine learning. Specifically, systems which must more aptly operate in harsh/soft unknown environments without the need of a priori statistically trained neural networks nor fully developed learning rules for situations that have never been thought of yet. This leads to a hypothesis requiring new machine learning processes, in which abductive learning is applied. We utilize varying unsupervised/self-supervised learning techniques, statistical/fuzzy models for entities, relationships, and descriptor extraction. We also involve topic and group discovery and abductive inference algorithms. to expand system aperture in order to envision what outlying factors could have also caused current observations. Once extended plausible explanations are found, we will show how a system uses the afore mentioned implements to poten

关键词： Real time systems

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Data-driven Causal Association Discovery in Manufacturing Industries 41

Data-driven Causal Association Discovery in Manufacturing In...

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第41届中国控制会议

作者： Yiming Li Jia Xu Li Li Benoit Iung Department of Control Science & Engineering Tongji University Shanghai Research Institute for Intelligent Autonomous Systems Nancy Research Center for Automatic Control (CRAN CNRS UMR 7039)Lorraine University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

With the development of smart sensors,information storage,processing technology and computer performance,large amounts of operating data collected from production process provide opportunities as well as challenges in remaining useful life(RUL) *** one hand,data-driven analysis approaches are experiencing a fast *** the other hand,the collected variables may be redundant,noisy and high-dimensional for ***,data dimension reduction is applied for eliminating useless *** from correlation-based methods,causal inference methods can obtain reliable models reflecting causal relationships among interesting ***,the latter is more suitable in data dimension *** this study,we use PCMCI+,a causal discovery method based on graph model,that handles both lagged and contemporaneous relationships in multi-variable time *** validate this method on time series data extracted directly from a medium frequency quenching *** obtained results confirm that PCMCI+is able to recognize causal associations among various sensor *** instance,variables in the same process have relatively larger causal relationships than those in different processes.

关键词： causal discovery manufacturing equipment PCMCI+ multi-sensor

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A model oriented approach for managing traceability of biological samples and tests of patients in assisted reproduction clinics 14

A model oriented approach for managing traceability of biolo...

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14th International conference on Web Information Systems and Technologies, WEBIST 2018

作者： Morales-Trujillo, L. De La Paz Furest, V. Cid Enríquez, J.G. Navarro, José Computer Languages and Systems Department University of Seville Avenida Reina Mercedes s/n Sevilla41010 Spain Assisted Reproduction Clinic - Inebir Hospital Victoria Eugenia Avenida la Cruz Roja 1 Sevilla41009 Spain

ISBN: (纸本)9789897583247

Assisted reproduction has become a service that more and more people access. Current problems such as the delay in the age of motherhood, single-parent couples, etc. they have proliferated the options and the different treatments that are put at the service of society. A fundamental part of these processes lies in the work of laboratories, in the samples that are handled in clinical processes and then be implanted in future mothers. The management of the samples is a critical aspect that requires all the opportune mechanisms that guarantee the traceability of said samples, avoiding fatal errors. The correct identification, monitoring and control of them is a fundamental aspect and of special relevance. However, the systems currently offered to clinics present important problems. On the one hand, they offer little security, are very expensive or very independent of a specific provider, so that the traceability system cannot be connected to the hospital central management system, or they are very intrusive control systems in the daily work of the laboratory technicians. In this paper a software solution based on the definition of automatic models and protocols is proposed. It includes the appropriate devices, to manage the traceability of the samples in parallel to the work of the laboratory technician. Copyright © 2018 by SCITEPRESS - science and Technology Publications, Lda. All rights reserved

关键词： Cell proliferation

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Hydrological modeling of murray river basin using the hydrological simulation program-FORTRAN model 7

Hydrological modeling of murray river basin using the hydrol...

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7th IEEE conference on Systems, Process and control, ICSPC 2019

作者： Heydari, Salimeh Malekpour Aris, Teh Noranis Mohd Yaakob, Razali Hamdan, Hazlina Faculty of Computer Science and Information Technology UPM Department of Computer Science Serdang Selangor Malaysia

ISBN: (纸本)9781728118260

Snow Water Equivalent can be a field for modeling runoff in mountainous catchments. In this regard, the use of satellite data and distributed hydrological models has grown dramatically to simulate runoff from snow water. Accordingly, the HSPF (Hydrological Simulation Program - FORTRAN) model has been used for a mountainous catchment area in Australia to show that it can overcome the lack of conventional snow data such as depth and density of snow using a combination of index-snow temperature and precipitation-runoff models. This model is based on a physical and semi-distributed model for simulating hydrological processes in the catchment area. Therefore, the satellite data and images in UTM image system for inference of land cover and land use, DEM (Digital Elevation Model) and SCA (Snow Cover Area) are used. The model was able to simulate the amount of runoff in the catchment as well as the annual changes in water equivalent to snow reasonably. Hence, The parameter of snow water can be applied on multi resolution analysis using wavelets (WNF) approach to increase the forecast accuracy. The results showed that reliable estimation of the snow water equivalent and simulation of runoff from snow water can be done using distributed hydrological models and satellite data of snow cover area. © 2019 IEEE.

关键词： Runoff

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Management of data value chains, a value monitoring capability maturity model 20

Management of data value chains, a value monitoring capabili...

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20th International conference on Enterprise Information Systems, ICEIS 2018

作者： Brennan, Rob Attard, Judie Helfert, Markus ADAPT Centre School of Computer Science and Statistics O'Reilly Institute Trinity College Dublin I-Dublin-2 Ireland Lero Centre ADAPT Centre School of Computer Applications Dublin City University I-Dublin-9 Ireland

ISBN: (纸本)9789897582981

This paper identifies management capabilities for data value chains as a gap in current data value research. It specifies a data value management capability framework and a first data value monitoring capability maturity model (CMM). This framework and CMM will enable organisations to identify and measure the current state of their data value monitoring processes, and show how to take steps to enhance value monitoring in order to exploit the full data value potential in their organisation. This new approach to data value management is needed since, despite the success of Big Data and the appeal of the data-driven enterprise, there is little evidence-based guidance for maximising data value creation. To date, most data value optimisation has focused on technological gains such as data platforms or analytics, without bridging the gap to organisational knowledge or human factors research. The evidence of best practice gathered here from the state of the art shows that there is a hierarchy of data value dimensions for data value monitoring, starting with cost and peaking with utility (understanding value creation). The models are validated by a case study of three organisations that are managing data value and using it to support strategic decisionmaking. © 2018 by SCITEPRESS - science and Technology Publications, Lda. All rights reserved.

关键词： Monitoring

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New On-line Algorithms for Modelling, Identification and Simulation of Dynamic Systems Using Modulating Functions and Non-asymptotic State Estimators: Case Study for a Chosen Physical Process 21st

New On-line Algorithms for Modelling, Identification and Sim...

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21st International conference on Computational science, ICCS 2021

作者： Byrski, Witold Drapala, Michal Byrski, Jędrzej Department of Automatic Control and Robotics AGH University of Science and Technology Al. Mickiewicza 30 Kraków30-059 Poland Department of Applied Computer Science AGH University of Science and Technology Al. Mickiewicza 30 Kraków30-059 Poland

ISBN: (纸本)9783030779696

The paper presents an advanced application of computation methodology with complicated algorithms and calculation methods dedicated to optimal identification and simulation of dynamic processes. These models may have an unknown structure (the order of a differential equation) and unknown parameters. The presented methodology uses non-standard algorithms for identification of such continuous-time models that can represent linear and non-linear physical processes. Typical approaches, presented in the literature, most often utilize discrete-time models. However, for the case of continuous-time differential equation models, in which both, the parameters and the derivatives of the output variable are unknown, the solution is not easy. In the paper, for the solution of the identification task, the convolution transformation of the differential equation with a special Modulating Function will be used. Also, to be able to properly simulate the behaviour of the process based on the obtained model, the exact state integral observers with minimal norm will be used for the reconstruction of the exact value of the initial conditions (not their estimate). For multidimensional process case, with multiple control signals (many inputs), additional problems arise that make continuous identification and observation of the vector state (and hence simulation) impossible by the use of the standard methods. Application of the above-mentioned methods for solving this problem will be also presented. Both algorithms, for the parameter identification and the state observation, will be implemented on-line in two independent but cooperating windows that will simultaneously move along the time axis. The presented algorithms will be tested using data collected during the heat exchange process in an industrial glass melting installation. © 2021, Springer Nature Switzerland AG.

关键词： Differential equations

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Fast numerical evaluation of periodic solutions for a class of nonlinear systems and its applications for parameter estimation problems 7th

Fast numerical evaluation of periodic solutions for a class ...

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7th International conference on Optimization Problems and Their Applications, OPTA 2018

作者： Tyukin, Ivan Y. Al-Ameri, Jehan Mohammed Gorban, Alexander N. Levesley, Jeremy Terekhov, Valery A. Department of Mathematics University of Leicester Leicester United Kingdom College of Science Department of Mathematics University of Basrah Basrah Iraq Department of Automation and Control Processes Saint-Petersburg State Electrotechnical University Saint-Petersburg Russia Lobachevsky State University of Nizhny Novgorod Russia

ISBN: (纸本)9783319937991

Fast numerical evaluation of forward models is central for a broad range of inverse problems. Here we propose a method for deriving computationally efficient representations of periodic solutions of parameterized systems of nonlinear ordinary differential equations. These representations depend on parameters of the system explicitly, as quadratures of parameterized computable functions. The method applies to systems featuring both linear and nonlinear parametrization, and time-varying right-hand side. In addition, it opens possibilities to invoke scalable parallel computations and suitable function approximation schemes for numerical evaluation of solutions for various parameter values. Application of the method to the problem of parameter estimation of nonlinear ordinary differential equations is illustrated with a numerical example for the Morris–Lecar system. © Springer International Publishing AG, part of Springer Nature 2018.

关键词： Parameter estimation

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