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10th International Symposium on Advanced Topics in Electrical engineering, ATEE 2017

作者： Andriniriniaimalaza, Philibert Fanambinantsoa Andrianantenaina, Tsiory Patrick Razafinjaka, Nirinarison Jean Digital Control Laboratory of Electrical Drive Systems Electrical Engineering Faculty University Politehnica Bucharest Romania Automatic Laboratory Department of Electricity Higher Polytechnic School University of Antsiranana Madagascar

ISBN: (纸本)9781479975143

Currently, variable gain PI (VGPI) controllers are used in several applications. Its structure is built around PI controller tuning and usually an entire number is chosen for the order or degree. This paper deals with a study of a VGPI with fractional order (VGPIFO). For the PI controller tuning, a method called general method (MG) is adopted. Then, the VGPI one is established. The proposed controller is applied on a doubly fed induction generator (DFIG) inserted in a chain of wind power conversion. Simulation results show that this new controller leads to good performances as test tracking, disturbance rejection and robustness with respect to system operation variation and parameters variation. © 2017 IEEE.

关键词： Wind power

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Formative assessment application with social media integration using computer adaptive testing techniques 12

Formative assessment application with social media integrati...

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12th International Conference on e-Learning, ICEL 2017

作者： Dascalu, Maria-Luliana Nitu, Melania Alecu, Gabriel Bodea, Constanta-Nicoleta Moldoveanu, Alin Dragos Bogdan Department of Engineering in Foreign Languages Faculty of Engineering in Foreign Languages University Politehnica of Bucharest Romania Department of Economic Informatics and Cybernetics Faculty of Economic Cybernetics Statistics and Informatics Bucharest University of Economic Studies Romania Computer Science and Engineering Department Faculty of Automatic Control and Computers University Politehnica of Bucharest Romania

ISBN: (纸本)9781911218357

Individual instruction is recognized as an effective learning method which is highly supported by the so-called personalized, intelligent or adaptive systems. The main purpose of this learning method is to offer customized content, experience or tools, based on the learning profile of students (learning style, gender, prior knowledge, learning goals and so on), so as to improve the learning outcomes. There are two wide-known adaption techniques implemented by learning systems to provide individual instruction: adaptability and adaptivity. The first one allows the students to take control, e.g. The learning system provides choices to let the students adapt the steps, sequences, difficulty level, preferences, while the second empowers the system, which is able to build a student model and to provide learning support based on that model. The current paper presents PoliCAT-A learning system based on Computer Adaptive Testing (CAT) principle, which implements the second adaption technique (adaptivity) to provide individual instruction. Furthermore, the proposed web-based application supports the new learning paradigms, e.g. student-centered learning, communities of practice, and constructivism in general and relies on the current technologies-Web 2.0 and social Web, as students are able to share one's results on social media. The system is described as a useful tool for self-regulated learning, answering thus at the question whether assessment may have a strong formative role in learning or not. Besides highlighting the key features of the application, the paper provides experimental results from a web programming course for forth year students enrolled in an engineering degree program, who used the developed system as a learning tool during one semester. Students reported that they succeeded in strengthening their study skills and monitoring their academic progress through the learning analytics features. The available personalized feedback PoliCAT, as well as the possi

关键词： Students

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A new decomposition method for attractor detection in large synchronous Boolean networks 3rd

A new decomposition method for attractor detection in large ...

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3rd International Symposium on Dependable Software engineering: Theories, Tools and Applications, SETTA 2017

作者： Mizera, Andrzej Pang, Jun Qu, Hongyang Yuan, Qixia Faculty of Science Technology and Communication University of Luxembourg Luxembourg Luxembourg Interdisciplinary Centre for Security Reliability and Trust University of Luxembourg Luxembourg Luxembourg Department of Automatic Control and Systems Engineering University of Sheffield Sheffield United Kingdom

ISBN: (纸本)9783319694825

Boolean networks is a well-established formalism for modelling biological systems. An important challenge for analysing a Boolean network is to identify all its attractors. This becomes challenging for large Boolean networks due to the well-known state-space explosion problem. In this paper, we propose a new SCC-based decomposition method for attractor detection in large synchronous Boolean networks. Experimental results show that our proposed method is significantly better in terms of performance when compared to existing methods in the literature. © 2017, Springer International Publishing AG.

关键词： Biological systems

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Biomass estimation using LiDAR data

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International Journal of Sustainable Energy Planning and Management 2018年 17卷 79-90页

作者： Torretojal, Leyre Espeso, Javier Maria Sanchez Bastarrika, Aitor Lopezguede, Jose Manuel Department of Mining and Metallurgical Engineering and Materials Science Faculty of Engineering University of the Basque Country UPV/EHU Nieves Cano 12 VitoriaGasteiz01006 Spain Department of Geographic Engineering and Graphic Expression Techniques School of Civil Engineering University of Cantabria Avda. de los Castros 44 Santander39005 Spain Department of Systems Engineering and Automatic Control Faculty of Engineering University of the Basque Country UPV/EHU Nieves Cano 12 VitoriaGasteiz01006 Spain

Forest ecosystems play a very important role in carbon cycle because they suppose one of the biggest carbon reservoirs and sinks. Estimating the aboveground forest biomass is critical to understand the global carbon storage process. Different models to estimate aboveground biomass in the Pinus radiata specie in a specific region of Spain have been developed, using, exclusively, public and accessible data with low point density gathered periodically from Light Detection and Ranging (LiDAR) flights. The point clouds data were processed to obtain metrics considered as predictive variables and afterwards, the multiple regression technique has been applied to generate the biomass estimation models. The best models explain 76% of its variability with a standard error of 0.26 ton/ha in logarithmic units. The methodology can be considered as highly automated and extensible to other territories with similar characteristics. Our results support the use of this approach for more sustainable management of forest areas. © 2018, Aalborg University press. All rights reserved.

关键词： Multiple linear regression

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An assessment on the accuracy of high precision 3D positioning using planar fiducial markers 21

An assessment on the accuracy of high precision 3D positioni...

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21st International Conference on System Theory, control and Computing, ICSTCC 2017

作者： Popescu, Dragos C. Cernaianu, Mihail O. Ghenuche, Petru Dumitrache, Ioan Horia Hulubei National Institute of Physics and Nuclear Engineering Reactorului St. 30 PO Box MG-6 Bucharest-Magurele077125 Romania Faculty of Automatic Control and Computers University Politehnica of Bucharest 313 Spl. Independenei Bucharest060042 Romania

ISBN: (纸本)9781538638422

High-accuracy remote position measurements are regarded in applications where different systems or components need to be placed in precise configurations. There are some cases in which it is impossible to define an absolute, precise reference frame and the application should rely only on relative measurements. In recent years, fiducial markers began to provide an interesting alternative to standard industrial positioning systems, which are very expensive and very difficult to integrate in various applications. This paper provides a study concerning the accuracy for measuring the position of fiducial markers and experimental results obtained using an imaging setup. This paper also presents a solution for calibrating a fiducial marker cube which extends the working space up to 360 degrees. © 2017 IEEE.

关键词： Cameras Image edge detection Manipulators Noise measurement Integrated optics Optical imaging Image resolution

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Variable speed control in wells turbine-based oscillating water column devices: optimum rotational speed

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IOP Conference Series: Earth and Environmental Science 2018年第1期136卷

作者： J Lekube A J Garrido I Garrido Automatic Control Group (ACG). Institute of Research and Development of Processes (IIDP). Department of Automatic Control and Systems Engineering Faculty of Engineering of Bilbao University of the Basque Country (UPV/EHU) Bilbao Spain

The effects of climate change and global warming reveal the need to find alternative sources of clean energy. In this sense, wave energy power plants, and in particular Oscillating Water Column (OWC) devices, offer a huge potential of energy harnessing. Nevertheless, the conversion systems have not reached a commercially mature stage yet so as to compete with conventional power plants. At this point, the use of new control methods over the existing technology arises as a doable way to improve the efficiency of the system. Due to the non-uniform response that the turbine shows to the rotational speed variation, the speed control of the turbo-generator may offer a feasible solution for efficiency improvement during the energy conversion. In this context, a novel speed control approach for OWC systems is presented in this paper, demonstrating its goodness and affording promising results when particularized to the Mutriku's wave power plant.

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A new object recognition framework based on PCA, LDA, and K-NN 11

A new object recognition framework based on PCA, LDA, and K-...

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11th International Conference on Computer engineering and systems, ICCES 2016

作者： Hagar, Asmaa A.M. Alshewimy, Mahmoud A.M. Saidahmed, Mohamed T. Faheem Computers and Automatic Control Dept. Faculty of Engineering Tanta University Egypt

ISBN: (纸本)9781509032679

In this paper, a new object recognition framework is presented. The framework includes a variety of object recognition approaches based on Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), and the K-nearest neighbor (K-NN). A color image vector representation model is also introduced. Based on the representation model, color Eigenspace is constructed using PCA and LDA for feature extraction. The K-NN is adopted as a mechanism for classification. The object recognition framework approaches were tested on Columbia Object Image Library (COIL-100) and Amsterdam Library of Object Images (ALOI) color object databases. Experimental results on these databases evinced the effectiveness of the proposed work with high recognition rates in comparison with the results of previous works in the literature. The recognition rate has reached in some cases 100%. © 2016 IEEE.

关键词： Feature extraction

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Improving BDD-based attractor detection for synchronous Boolean networks

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Science China(Information Sciences) 2016年第8期59卷 7-22页

作者： Qixia YUAN Hongyang QU Jun PANG Andrzej MIZERA Faculty of Science Technology and Communication University of Luxembourg Department of Automatic Control & Systems Engineering University of Sheffield Interdisciplinary Centre for Security Reliability and Trust University of Luxembourg

Boolean networks are an important formalism for modelling biological systems and have attracted much attention in recent years. An important challenge in Boolean networks is to exhaustively find attractors,which represent steady states of a biological network. In this paper, we propose a new approach to improve the efficiency of BDD-based attractor detection. Our approach includes a monolithic algorithm for small networks,an enumerative strategy to deal with large networks, a method to accelerate attractor detection based on an analysis of the network structure, and two heuristics on ordering BDD variables. We demonstrate the performance of our approach on a number of examples and on a realistic model of apoptosis in hepatocytes. We compare it with one existing technique in the literature.

关键词： Boolean networks systems biology binary decision diagram attractor verification algorithms

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Sensorless nonlinear control of fed-batch Escherichia coli cultivation bioprocess using the state-dependent approach 12th

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12th Portuguese Conference on automatic control, controlO 2016

作者： Iratni, Abdelhamid Araújo, Rui Rastegar, Saeid Mostefai, Mohammed Faculty of Science and Technology Electrical Engineering Department University of Bordj Bou Arreridj El Anasser Algeria Department of Electrical and Computer Engineering Institute for Systems and Robotics University of Coimbra Coimbra Portugal Automatic Control Laboratory of Setif Electrical Engineering Department Faculty of Technology University of Setif1 Sétif Algeria

ISBN: (纸本)9783319436708

The cultivation of Escherichia coli bacteria is widely used by geneticists and biopharmaceuticals to produce medicines and vaccines. In such industries, Bioprocesses are known by their harsh environment and very expensive physical sensors. This paper deals with nonlinear estimation and control of fed-batch Escherichia coli bioprocess. Enhancing the process performance and maximizing its efficiency by optimizing the control of Escherichia coli cultures depends on the availability of appropriate online sensors for the main culture components. In this study, an innovative method for nonlinear estimation and control of bioprocesses is designed and assessed. The new algorithm for control and estimation of Escherichia coli bioprocess states, based on the State-Dependent Riccati Equation technique, is validated by numerical simulation. The results obtained clearly demonstrate the effectiveness of the proposed technique for Biosystems in measuring, monitoring, and control of their natural nonlinear dynamics. © Springer International Publishing Switzerland 2017.

关键词： Extended Kalman filters

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Information-theoretic active contour model for microscopy image segmentation using texture 1

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13th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2016

作者： Biga, Veronica Coca, Daniel Faculty of Biology Medicine and Health The University of Manchester Oxford Rd ManchesterM13 9PL United Kingdom Department of Automatic Control and Systems Engineering The University of Sheffield Mappin Street SheffieldS1 3JD United Kingdom

ISBN: (数字)9783319678344

ISBN: (纸本)9783319678337

High throughput technologies have increased the need for automated image analysis in a wide variety of microscopy techniques. Geometric active contour models provide a solution to automated image segmentation by incorporating statistical information in the detection of object boundaries. A statistical active contour may be defined by taking into account the optimisation of an information-theoretic measure between object and background. We focus on a product-type measure of divergence known as Cauchy-Schwartz distance which has numerical advantages over ratio-type measures. By using accurate shape derivation techniques, we define a new geometric active contour model for image segmentation combining Cauchy-Schwartz distance and Gabor energy texture filters. We demonstrate the versatility of this approach on images from the Brodatz dataset and phase-contrast microscopy images of cells. © Springer International Publishing AG 2017.

关键词： Image segmentation

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