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Classification of postprandial glycemic patterns in type 1 diabetes subjects under closed-loop control: an in silico study*

Classification of postprandial glycemic patterns in type 1 d...

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Annual international conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Corinna Schröder José Luis Díez Alejandro J. Laguna Jorge Bondia Cristina Tarín Institute of System Dynamics University of Stuttgart Germany Instituto Universitario de Automática e Informàtica Industrial Universitat Politècnica de Valencia Valencia Spain Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM) Madrid Spain

In this contribution we explore some alternatives in order to obtain filtered and low dimension CGM data to provide well processed CGM data to AP systems. The presented approach explores the possible association of certain patient behaviors with certain glucose patterns. We compare the classical clustering algorithms (K-means, and fuzzy C-means), which has shown some limitations for CGM data processing, with a new clustering algorithm (K-means ellipsoid algorithm) more suited to CGM data. We test this new algorithm in a variety of complex scenarios including variabilty in the amount of ingested carbohydrates, absorption time and intrapatient parameters. The new algorithm overcomes the perceived problems and is able to discriminate between normoglycaemic, moderate and severe hyperglycaemic post-prandial behaviour, even with similar amounts of carbohydrates contained in a meal.

关键词： Sugar Clustering algorithms Ellipsoids Absorption Insulin Time series analysis Market research

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WAX DEPOSITION PREDICTION AND control IN WAXY CRUDE OIL TIEBACK FLOWLINES FOR SOUTH CHINA SEA DEEPWATER OIL DEVELOPMENT 37

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37th ASME international conference on Ocean, Offshore and Arctic Engineering

作者： Yu, Xichong Wang, Chunsheng Li, Qingping Li, Yan Zhu, Xiaosong Wang, Qing Cheng, Bing Qing, Yaqi CNOOC Res Inst Beijing Peoples R China China Univ Petr East China Qingdao Peoples R China

ISBN: (纸本)9780791851241

Crude oils are generally very complex chemical systems consisting predominantly of hundreds to thousands of hydrocarbon compounds from simple low-molecular-weight paraffin to high-molecular-weight waxes. There are many factors effecting wax deposition such as the fluid composition, pressure and temperature and so on. Wax deposition is complex dynamic process related to transient heat and mass transfer, therefore it is very difficult to predict wax deposition velocity accumulation amounts on the wall in waxy crude oil tieback flowlines. There exist many waxy crude oil tieback flowlines for South China Sea deepwater oil development, which can cause many flow assurance problems. It is very important to carry out wax deposition prediction calculation and effective measures are adopted to solve flow assurance problems. In this study, based on certain waxy crude oil tieback flowlines for South China Sea deepwater oil development, OLGA software is used to simulate transient flow characteristics in waxy crude oil tieback flowlines such as wax precipitation rate, thickness of wax layer deposited at wall, pigging frequency and so on. OLGA software simulation results is coincident with field pigging operation results, finally obtaining a good simulation methods to predict transient flow characteristics in waxy crude oil tieback flowlines and giving good suggestions to determine pigging periods and frequency. The study results show two 10 inch non-insulation steel flowlines are recommended to develop deepwater waxy crude oil field and pigging periods should comprehensive consider thickness of wax layer deposited at wall and the increase of pressure caused by wax deposition. It is reasonable to 35 days pigging periods during 2 year after put into production, 60 days pigging periods after 2 years. The results show maximum liquid flow rate for a 10 inch flowline is 7000m(3)/d, and it is reasonable that one flowline is used to transport when flow rate is lower than 7000m(3)/d, and

关键词： Deepwater oil field waxy crude oil Tieback flowline Wax deposition Pigging OLGA software

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Cloud-based control Approach in Discrete Manufacturing Using a Self-Learning Architecture

Cloud-based Control Approach in Discrete Manufacturing Using...

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3rd IFAC conference on Embedded systems, Computational Intelligence and Telematics in control (CESCIT)

作者： Lindemann, Benjamin Karadogan, Celalettin Jazdi, Nasser Liewald, Mathias Weyrich, Michael Univ Stuttgart Inst Ind Automat & Software Engn D-70569 Stuttgart Germany Univ Stuttgart Inst Met Forming Technol D-70174 Stuttgart Germany

Process anomalies and fluctuations in product quality are widespread problems in discrete manufacturing. There have been various control approaches to tackle the challenge. This paper presents a cross-process control approach that combines engineering knowledge and data analytics techniques. An initial rule basis is generated by experts using simulation models. To achieve a data driven enhancement concerning process and product quality, a PLC-based connector is developed to record and unify real process data from heterogeneous data sources. The data is processed in the cloud and inferred using online modeling techniques. Neural networks with autoencoder structure are applied to extract unknown features, to iteratively refine the knowledge base and thus to optimize quality control. (C) 2018, IFAC (international Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Data fusion and data mining Process control manufacturing Intelligent systems and instrumentation (smart systems, sensors, actuators and distributed systems)

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Learning and Adaptation of Inverse Dynamics Models: A Comparison

Learning and Adaptation of Inverse Dynamics Models: A Compar...

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IEEE-RAS international conference on Humanoid Robots

作者： Kevin Hitzler Franziska Meier Stefan Schaal Tamim Asfour Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology Karlsruhe Germany Max-Planck-Institute of Intelligent Systems Germany and Computational Learning and Motor Control Lab University of Southern California USA

ISBN: (数字)9781538676301

ISBN: (纸本)9781538676318

Performing tasks with high accuracy while interacting with the real world requires a robot to have an exact representation of its inverse dynamics that can be adapted to new situations. In the past, various methods for learning inverse dynamics models have been proposed that combine the well-known rigid body dynamics with model-based parameter estimation, or learn directly on measured data using regression. However, there are still open questions regarding the efficiency of model-based learning compared to data-driven approaches as well as their capabilities to adapt to changing dynamics. In this paper, we compare the state-of-the-art inertial parameter estimation to a purely data-driven and a model-based approach on simulated and real data, collected with the humanoid robot Apollo. We further compare the adaptation capabilities of two models in a pick and place scenario while a) learning the model incrementally and b) extending the initially learned model with an error model. Based on this, we show the gap between simulation and reality and verify the importance of modeling nonlinear effects using regression. Furthermore, we demonstrate that error models outperform incremental learning regarding adaptation of inverse dynamics models.

关键词： Adaptation models Robots Mathematical model Inverse problems Dynamics Data models Parameter estimation

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An investigation of parameter tuning in the random adaptive grouping algorithm for LSGO problems 10th

An investigation of parameter tuning in the random adaptive ...

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10th international Joint conference on Computational Intelligence, IJCCI 2018

作者： Sopov, Evgenii Vakhnin, Alexey Department of System Analysis and Operations Research Reshetnev Siberian State University of Science and Technology Krasnoyarsk Russia

ISBN: (纸本)9789897583278

Large-scale global optimization (LSGO) is known as one of the most challenging problem for many search algorithms. Many well-known real-world LSGO problems are not separable and are complex for comprehensive analysis, thus they are viewed as the black-box optimization problems. The most advanced algorithms for LSGO are based on cooperative coevolution with problem decomposition using grouping methods. The random adaptive grouping algorithm (RAG) combines the ideas of random dynamic grouping and learning dynamic grouping. In our previous studies, we have demonstrated that cooperative coevolution (CC) of the Self-adaptive Differential Evolution (DE) with Neighborhood Search (SaNSDE) with RAG (DECC-RAG) outperforms some state-of-the-art LSGO algorithms on the LSGO benchmarks proposed within the IEEE CEC 2010 and 2013. Nevertheless, the performance of the RAG algorithm can be improved by tuning the number of subcomponents. Moreover, there is a hypothesis that the number of subcomponents should vary during the run. In this study, we have performed an experimental analysis of parameter tuning in the RAG. The results show that the algorithm performs better when using subcomponents of larger size. In addition, some improvement can be done by applying dynamic group sizing. Copyright © 2018 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved.

关键词： Evolutionary algorithms

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Real-Time Realization of a Family of Optimal Infinite-Memory Non-Causal systems

Real-Time Realization of a Family of Optimal Infinite-Memory...

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6th international-Federation-of-Automatic-control (IFAC) conference on Nonlinear-Model-Predictive-control (NMPC)

作者： Tanovic, Omer Megretski, Alexandre MIT Dept Elect Engn & Comp Sci Cambridge MA 02139 USA

In this paper, we consider a problem of designing discrete-time systems which are optimal in frequency-weighted least squares sense subject to a maximal output amplitude constraint. It can be shown for such problems, in general, that the optimality conditions do not provide an explicit way of generating the optimal output as a real-time implementable transformation of the input, due to instability of the resulting dynamical equations and sequential nature in which criterion function is revealed over time. In this paper, we show that, under some mild assumptions, the optimal system has exponentially fading memory. We then propose a causal and stable finite-dimensional nonlinear system which, under an L1 dominance assumption about the equation coefficients, returns high-quality approximations to the optimal solution. The fading memory of the optimal system justifies the receding horizon assumption and suggests that such approach can serve as a cheaper alternative to standard MPC-based algorithms. The result is illustrated on a problem of minimizing peak-to-average-power ratio of a communication signal, stemming from power-efficient transceiver design in modern digital communication systems. (C) 2018, IFAC (international Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Model approximation non-causal systems non-linear systems model predictive control linear optimal control state space realization

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Application of shuffled frog-leaping algorithm in regional air pollution control 1st

引用

1st international conference on Soft Computing: Theories and Applications, SoCTA 2016

作者： Prakash, Divya Tripathi, Anurag Sharma, Tarun Kumar Amity School of Engineering and Technology Amity University Rajasthan Jaipur303007 India Arya Institute of Engineering and Technology Jaipur India

ISBN: (纸本)9789811056987

Shuffled frog-leaping algorithm (SFLA), a memetic algorithm modeled on the foraging behavior of natural species called frogs. SFLA embeds the features of both particle swarm optimization (PSO) and shuffled complex evolution (SCE) algorithm. It is well documented in the literature that SFLA is an efficient algorithm to solve nontraditional optimization problems. In this study, SFLA has been applied to a real-world problem of air pollution control. The results are at par with the state of the art of algorithm. © 2018, Springer Nature Singapore Pte Ltd.

关键词： Global optimization

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Energy management in WSN: IEEE 802.15.4 unslotted mode 15

Energy management in WSN: IEEE 802.15.4 unslotted mode

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15th international Multi-conference on systems, Signals and Devices, SSD 2018

作者： Ayadi, Hayfa Zouinkhi, Ahmed Boussaid, Boumedyen Naceur Abdelkrim, M. Val, Thierry MACS Laboratory: Modeling Analysis and Control of Systems University of Gabes Tunisia Institut de Recherche en Informatique de Toulouse UMR5505-CNRS Universite de Toulouse IUT Blagnac BP60073 Blagnac CedexF-31703 France

ISBN: (纸本)9781538653050

Wireless Sensor Networks suffer from many problems but energy efficient always presents the most critical trouble in this field. Many approaches and technologies were invented in order to reduce the energy consumed such as the IEEE 802.15.4. The IEEE 802.15.4 is invented for low power and Low Rate Wireless Personal Area Networks (LRWPANs). It has been updated many times in order to provide a suitable solution for this problem. It presents two different modes which are the beacon enabled mode and the non beacon enabled mode. This work is interested in the non beacon enabled mode. The paper proposes a new model to compute the energy consumed by the node in the CSMA/CA protocol specially in the unslotted algorithm. Then an auto-adaptation process is enabled. So the last quantity of energy in the battery is adapted to the activity period of the node in the network by intervening in its duty cycle in order to postpone its death. The simulation results prove both the efficiency of our consumption energy model in addition to the performance of our intervention which lead to reduce the consumed energy by node and to increase its lifetime. © 2018 IEEE.

关键词： IEEE Standards

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Primary control of current frequency in energy system based on a two-circuit NPP using a heat accumulation system 14

Primary control of current frequency in energy system based ...

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14th international Scientific and Technical conference on problems of Energy systems and Thermal Power complexes, PESPC 2018

作者： Aminov, R.Z. Yurin, V.E. Murtazov, M.A. Saratov Scientific Center Russian Academy of Sciences 24 Rabochaya str. Saratov410028 Russia

A principle schema of an energy complex, including a two-circuit nuclear power plant, a heat phase transition accumulator and an additional steam turbine was developed and investigated. In the course of the work, well-known systems containing phase transition accumulators were analyzed. The known devices are designed only for heating hot water and can not be used to generate steam. To ensure the operation of the heat accumulation system under the required conditions, the design of a heat accumulator with a phase-transition material has been developed. The technical result of the development is to ensure the constructive capability of phase transition accumulators to operate in the steam generation mode. Investigations have shown that the development of heat accumulation systems at nuclear power plants will make it possible for NPP to perform the requirements of System operator of Unified Energy System of Russia about involved in primary control of current frequency, without reduce in the coefficient of the reactor power utilization. This will help to increase the efficiency of energy generating capacities structure, with the possibility of increasing the share of powerful nuclear power units in power systems, and to increase the competitiveness of nuclear power plants in the electricity market. © 2018 IOP Publishing Ltd.

关键词： Nuclear power plants

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A NEW SEQUENTIAL ROBUST APPROACH FOR MDO problems UNDER MIXED INTERVAL AND PROBABILISTIC UNCERTAINTIES

A NEW SEQUENTIAL ROBUST APPROACH FOR MDO PROBLEMS UNDER MIXE...

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38th American-Society-of-Mechanical-Engineers (ASME) Computers and Information in Engineering (CIE) conference in conjunction with the international Design Engineering Technical Conferes (IDETC)

作者： Xia, Tingting Li, Mian Shanghai Jiao Tong Univ Univ Michigan Shanghai Jiao Tong Univ Joint Inst Shanghai 200240 Peoples R China

ISBN: (纸本)9780791851760

In the design process of complex multidisciplinary systems, uncertainties in parameters or variables cannot be ignored. Robust multidisciplinary design optimization methods (RMDOs) can treat uncertainties as specified probabilistic distributions when enough statistical information is available. RMDOs need to assign intervals for nondeterministic variables since some design quantities may not have enough information to obtain statistical distributions, especially in the early stage of a design optimization process. Both types of uncertainties are very likely to appear simultaneously. In order to obtain robust solutions for multidisciplinary design optimization problems under mixed interval and probabilistic uncertainties, this work proposed a new sequential robust MDO approach, mixed SR-MDO. First, the robust optimization problem in a single discipline under mixed uncertainties is formulated and solved. Then, following the SR-MDO framework in our early work, MDO problems under mixed uncertainties are solved by handling probabilistic and interval uncertainties sequentially in decomposed subsystem problems. Interval uncertainties are handled by using the worst-case sensitivity analysis and fixing probabilistic uncertainties at their mean first, and then the influence of probabilistic uncertainties in objectives, constraints as well as in discipline analysis models is characterized by corresponding mean and variance. The applied SR-MDO framework allows subsystems in its full autonomy robust optimization and sequential robust optimization stages to run independently in parallel. This makes mixed SR-MDO be efficient for independent disciplines to work simultaneously and be more time-saving. Computational complexity of the proposed approach mainly relates to the double-loop optimization process in the worst-case interval uncertainties analysis. Examples are presented to demonstrate the applicability and efficiency of the mixed SR-MDO approach.

关键词： Robust multidisciplinary design optimization mixed interval and probabilistic uncertainty SR-MDO framework Taylor expansion

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