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IEEE Conference on Decision and control

作者： T.J.J. van den Boom B. De Schutter B. Heidergott Control Systems Engineering Faculty of Information Technology and Systems Delft University of Technnology Delft Netherlands Department of Mathematics and Computing Science Eindhovan University of Technology Eindhoven Netherlands

Model predictive control (MPC) is a popular controller design technique in the process industry. Conventional MPC uses linear or nonlinear discrete-time models. Previously, we have extended MPC to a class of discrete event systems that can be described by a model that is "linear" in the max-plus algebra. In our previous work we have considered MPC for the perturbations-free case and for the case with noise and/or modeling errors in a bounded or stochastic setting. In this paper we consider a method to reduce the computational complexity of the resulting optimization problem, based on variability expansion. We show that the computational load is reduced if we decrease the level of 'randomness' in the system.

关键词： Stochastic systems Predictive models Predictive control Electrical equipment industry Industrial control Discrete event systems Algebra Stochastic resonance Computational complexity Optimization methods

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Dipper Throated Algorithm for Feature Selection and Classification in Electrocardiogram

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Computer systems Science & Engineering 2023年第5期45卷 1469-1482页

作者： Doaa Sami Khafaga Amel Ali Alhussan Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Mohamed Saber El-Sayed M.El-kenawy Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science Faculty of Computer and Information SciencesAin Shams University11566CairoEgypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Electronics and Communications Engineering Department Faculty of EngineeringDelta University for Science and TechnologyMansouraEgypt Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt

Arrhythmia has been classified using a variety of *** of the dynamic nature of electrocardiogram(ECG)data,traditional handcrafted approaches are difficult to execute,making the machine learning(ML)solutions more *** with cardiac arrhythmias can benefit from competent monitoring to save their *** arrhythmia classification and prediction have greatly improved in recent *** are a category of conditions in which the heart's electrical activity is abnormally rapid or *** year,it is one of the main reasons of mortality for both men and women,*** the classification of arrhythmias,this work proposes a novel technique based on optimized feature selection and optimized K-nearest neighbors(KNN)*** proposed method makes advantage of the UCI repository,which has a 279-attribute high-dimensional cardiac arrhythmia *** proposed approach is based on dividing cardiac arrhythmia patients into 16 groups based on the electrocardiography dataset’s *** purpose is to design an efficient intelligent system employing the dipper throated optimization method to categorize cardiac arrhythmia *** method of comprehensive arrhythmia classification outperforms earlier methods presented in the *** achieved classification accuracy using the proposed approach is 99.8%.

关键词： Feature selection electrocardiogram metaheuristics dipper throated algorithm

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2024 China Automation Congress, CAC 2024

作者： Lang, Yumin Wu, Jiande Lang, Xun Yu, Wanke Yang, Chuanyan Su, Hongye Department of Electronic Engineering Information School Yunnan University Kunming China Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan University Kunming China School of Automation China University of Geosciences Wuhan China State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China

ISBN: (纸本)9798350368604

Oscillation is a significant indication of the deterioration of control system performance and needs to be carefully monitored to ensure safe and stable process operations. However, industrial processes are often prone to noisy artifacts and nonstationary trends, resulting in low signal-to-noise ratios. In order to tackle this problem, this study introduces a novel framework for enhanced trend removal and noise reduction, which is featured by the following steps:(i) The circulant singular spectrum analysis (CiSSA) is used to decompose oscillation data into several reconstructed components (RCs). (ii) The estimated power spectral density (PSD) ofthese RCs is then smoothed using the Savitzky-Golay filter (SGF) to eliminate noise and identify the RCs corresponding to oscillatory components. (iii) These identified RCs are subsequently reconstructed to produce purified oscillatory data. The effectiveness of the suggested approach is validated using simulations and real-world industrial case studies. The findings indicate that the method notably enhances the quality of oscillatory data. © 2024 IEEE.

关键词： Power spectral density

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Quantification of valve stiction in control loops using adaptive differential evolution algorithm

Quantification of valve stiction in control loops using adap...

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2024 China Automation Congress, CAC 2024

作者： Yang, Dong Lang, Xun Wu, Jiande Yu, Wanke Liu, Songhua Xie, Lei Department of Electronic Engineering Information School Yunnan University Kunming China Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan University Kunming China School of Automation China University of Geosciences Wuhan China State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China

ISBN: (纸本)9798350368604

Accurately and promptly quantifying stiction is crucial for valve maintenance in industrial settings and ensuring the stability of control loop performance. However, current Hammerstein-based stiction quantification methods overlook valve dynamics, potentially leading to inaccurate quantification. Therefore, this paper proposes a novel stiction quantification method based on an adaptive differential evolution algorithm. In addition to considering the impact of valve dynamics on stiction, the proposed method demonstrates a certain level of robustness against the interference of unknown noise. Finally, the effectiveness of the proposed method is demonstrated through a series of simulations and industrial case studies. © 2024 IEEE.

关键词： Adaptive algorithms

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Developing an optimized application hosting framework in Clouds

Developing an optimized application hosting framework in Clo...

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作者： Shi, Xuanhua Jiang, Hongbo He, Ligang Jin, Hai Wang, Chonggang Yu, Bo Chen, Xueguang Service Computing Technology and Systems Lab School of Computer Huazhong University of Science and Technology China Department of Electronics and Information Engineering Huazhong University of Science and Technology China Department of Computer Science University of Warwick United Kingdom InterDigital Communications Corp. United States Department of Automation Control and Engineering Huazhong University of Science and Technology China

A Cloud system, which is also often called a data center, may host a large number of application servers (termed as applications for short in this paper) that consume various types of resource, such as CPU, memory, and I/O. In such a scenario, the application placement strategy, which specifies how to host applications across the physical servers in the Cloud, is critical to achieve good system- and/or client-oriented performance. The existing application placement algorithms in literature assume that the consumption of system resources is proportional to the level of workloads submitted to the system. In this paper, we reveal that it may not be the case in some circumstances. Based on this observation, we design and implement an application placement framework, called EAPAC, for Clouds. The developed framework is able to achieve the optimized performance by judiciously allocating to the applications a proper mixture of different types of application request as well as an appropriate number of requests in each type. Further, we investigate the issue of resource conflicts among different applications when there exist concurrent requests in the system. We have conducted extensive experiments to evaluate the performance of the developed framework. The experiment results show that compared with the existing method in literature, EAPAC can improve the performance by 35% in terms of the reply rate. © 2013 Elsevier Inc.

关键词： Application placement Cloud Resource conflicts

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Engineering of trustworthy smart grids implementing service level agreements

Engineering of trustworthy smart grids implementing service ...

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International Conference on Intelligent systems Applications to Power systems (ISAP)

作者： Rune Gustavsson Shahid Hussain Lars Nordström School of Computing Blekinge Institute of Technology Karlskrona Sweden Department of Industrial Information and Control Systems Royal Institute of Technology (KTH) Stockholm Sweden

Future Smart Grids have to meet high expectations from our societies on improved energy efficiency and sustainability. However, system uptake and acceptance will to a large extent depend on the perceived trust by different stakeholders. In the paper we address issues related to engineering of trustworthy systems. This type of Engineering will be grounded in reliable models of interoperability. A key issue is here interoperability of information exchange and sharing. Based on analysis of trust concerns, we propose a model of coordinating and monitoring by Service Level Agreements (SLAs) between stakeholders to ensure trustworthiness of system performance and behavior. We illustrate our methods on case related to trustworthy inclusion of DERs in Smart Grids.

关键词： Smart grids Quality of service Business Middleware Mechanical factors Monitoring Density estimation robust algorithm

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Gain-constrained filtering with probabilistic sensor delays and correlated noises

Gain-constrained filtering with probabilistic sensor delays ...

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International Conference on Automation and computing (ICAC)

作者： Jun Hu Zidong Wang Bo Shen Huijun Gao Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin China Department of Information Systems and Computing Brunel University Uxbridge Middlesex UK Institute for Automatic Control and Complex Systems University of Duisburg-Essen Duisburg Germany

In this paper, the gain-constrained recursive filtering problem is investigated for a class of time-varying stochastic systems with probabilistic sensor delays and correlated noises. The phenomenon of probabilistic sensor delays is modeled by introducing a diagonal matrix composed of Bernoulli distributed random variables taking values of 1 or 0, which means that the sensors may experience randomly occurring delays with individual delay characteristics. The process noise is finite-step auto-correlated. The purpose of the addressed gain-constrained filtering problem is to design a filter such that, for all probabilistic sensor delays, gain constraint as well as correlated noises, the cost function concerning the filtering error is minimized at each sampling instant, where the filter gain satisfies a certain equality constraint. A new recursive filtering algorithm is developed that ensures both the local optimality and the unbiasedness of the designed filter at each sampling instant which achieving the pre-specified filter gain constraints. A simulation example is provided to illustrate the effectiveness of the proposed filter design approach.

关键词： Delay Filtering Noise Filtering algorithms Probabilistic logic Cost function Random variables

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Assimilation of Wireless Sensor Networks and remote microcomputer laboratories

Assimilation of Wireless Sensor Networks and remote microcom...

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作者： Fudurić, Darko Cmuk, Drago Knežević, Petar Mrvoš, Saša Department of Control and Computer Engineering University of Zagreb Faculty of Electrical Engineering and Computing Unska 3 Zagreb Croatia Konar - Electronics and Informatics Inc. Fallerovo etalite 22 Zagreb Croatia Department of Fundamentals of Electrical Engineering and Measurements University of Zagreb Faculty of Electrical Engineering and Computing Unska 3 Zagreb Croatia Department of Electronic Systems and Information Processing University of Zagreb Faculty of Electrical Engineering and Computing Unska 3 Zagreb Croatia

ISBN: (纸本)9789532330670

Emergence of Web 2.0 technologies became a trigger for a revolution that goes far beyond the Web. For an average student Web was transformed from a steady, accessible source of information into a place of action and viable exchange of knowledge a kind of a virtual classroom. Students started to look for experience and a touch to reality online, and this is where remote laboratories come in place. Such laboratories became an inevitable need in electrical and computer engineering courses dealing with microcomputers. This paper presents an overview of available architectures of microcomputer laboratories used today and addresses their most important limitations. Moreover, an important extension of such architecture is proposed allowing support for remote Wireless Sensor Network (WSN) laboratory. Different aspects of compatibility between microcomputer laboratories and WSNs have been examined to allow creation of an general extension model. With additional effort and adaptation, WSN nodes may serve remote clients as an economic and accessible microcomputer laboratory providing invaluable hands-on experience and a motivation for a course using it. © 2011 MIPRO.

关键词： Embedded systems

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Al-Biruni Based Optimization of Rainfall Forecasting in Ethiopia

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Computer systems Science & Engineering 2023年第6期45卷 2885-2899页

作者： El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Fadwa Alrowais Mostafa Abotaleb Abdelhameed Ibrahim Doaa Sami Khafaga Department of Communications and Elecronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Department of Computer Science F aculty of Computer and Infomation SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of System Progamming South Ual State UniversityChelyabinsk454080Russia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt

Rainfall plays a significant role in managing the water level in the *** unpredictable amount of rainfall due to the climate change can cause either overflow or dry in the *** individuals,especially those in the agricultural sector,rely on rain *** rainfall is challenging because of the changing nature of the *** area of Jimma in southwest Oromia,Ethiopia is the subject of this research,which aims to develop a rainfall forecasting *** estimate Jimma's daily rainfall,we propose a novel approach based on optimizing the parameters of long short-term memory(LSTM)using Al-Biruni earth radius(BER)optimization algorithm for boosting the fore-casting accuracy.N ash-Sutcliffe model eficiency(NSE),mean square error(MSE),root MSE(RMSE),mean absolute error(MAE),and R2 were all used in the conducted experiments to assess the proposed approach,with final scores of(0.61),(430.81),(19.12),and(11.09),***,we compared the proposed model to current machine-learning regression models;such as non-optimized LSTM,bidirectional LSTM(BiLSTM),gated recurrent unit(GRU),and convolutional LSTM(ConvLSTM).It was found that the proposed approach achieved the lowest RMSE of(19.12).In addition,the experimental results show that the proposed model has R-with a value outperforming the other models,which confirms the superiority of the proposed *** the other hand,a statistical analysis is performed to measure the significance and stability of the proposed approach and the recorded results proved the expected perfomance.

关键词： Rainfall prediction long short-term memory Al-Biruni earth radius algorithm meta-heuristic optimization

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Deepfake Detection Analysis Based on Video Face Analysis

Deepfake Detection Analysis Based on Video Face Analysis

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International Computer Sciences and information Technologies (CSIT)

作者： Oleh Pitsun Nazar Melnyk Khrystyna Lipianina-Honcharenko Department of Computer Engineering West Ukrainian National University Ternopil Ukraine Department for Information-Computing Systems and Control West Ukrainian National University Ternopil Ukraine

ISBN: (数字)9798331542634

ISBN: (纸本)9798331542641

The article examines the detection of manipulation of multimedia content, in particular in the form of videos and photos. The concept of deepfake is considered, the means and technologies involved in deepfake are analyzed, current and promising methods of detecting and preventing fake multimedia content are evaluated. Approaches to the methods of creating fakes on videos with elements of manipulation of the human face are defined. Faceswap and Deepfakes Web are found to be the most powerful solutions used to generate deepfakes. An analysis of tools for detecting deepfakes on the face was carried out, which made it possible to highlight the main technologies, libraries, and datasets used to search for fakes. The DeepFake Detection Challenge (DFDC) Model, Forensically, and others have been found to have significant potential and sample size to accurately detect human-faced fakes. This paper proposes a generalized approach to the detection of deep fakes on the human face using machine learning and computer vision technologies

关键词： Training Deep learning Deepfakes Recurrent neural networks Computational modeling Streaming media Libraries Software tools information technology Faces

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