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International Conference on Advanced Cloud and Big Data (CBD)

作者： Jinping Gu Zebin Wu Yonglong Li Yufeng Chen Zhihui Wei Wubin Wang School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China North Automatic Control Technology Institute Taiyuan China

The emergence of hyperspectral remote sensing has greatly promoted the development of the remote sensing technology. Endmember extraction is an important task in hyperspectral data processing. Pixel purity index (PPI)[1] algorithm has been widely used for endmember extraction in hyperspectral images. With the development of hyperspectral sensors, the resolution of hyperspectral images increases and the traditional hyperspectral processing algorithm is highly time consuming as its precision increases asymptotically. In order to process massive hyperspectral data efficiently, this paper proposes a distributed parallel implementation of PPI algorithm (PPI_DP) on cloud computing architecture. The realization of the proposed method using Spark framework and MapReduce model is described and evaluated. Experimental results demonstrate that the proposed method can effectively extract the endmembers of large quantity hyperspectral data.

关键词： Hyperspectral imaging Indexes Sparks Algorithm design and analysis Cloud computing

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A hybrid evolutionary probabilistic forecasting model applied for rainfall and wind power forecast

A hybrid evolutionary probabilistic forecasting model applie...

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IEEE Workshop on Evolving and Adaptive Intelligent Systems (EAIS)

作者： Guilherme G. Netto Alexandre C. Barbosa Mateus N. Coelho Arthur R. L. Miranda Vitor N. Coelho Marcone J. F. Souza Frederico G. Guimarães Agnaldo J. R. Reis Department of Control and Automation Engineering Universidade Federal de Ouro Preto Ouro Preto MG Brazil Graduate Program of Electrical Engineering Univesidade Federal de Minas Gerais Belo Horizonte MG Brazil Department of Computer Science Universidade Federal de Ouro Preto Ouro Preto MG Brazil Departament of Electrical Engineering Univesidade Federal de Minas Gerais Belo Horizonte MG Brazil

Several works in the literature so far have been focused on deterministic point forecasts, which, usually, indicates the conditional mean of future observations. An increasing need for generating the entire conditional distribution of future observations has been required for the new generation of soft sensors. This study aims the probabilistic forecasts, reporting the use of a hybrid fuzzy forecasting model applied in two different forecasting problems. Our adapted model is applied to predict the rain of the city of Vitoria, in the state of Espírito Santo, Brazil. Real data from a wind farm, provided by the Irish EirGrid institute, was used for analyzing the proposal over a real time series with high fluctuations. Due to the stochasticity of the the hybrid model, which is calibrated through the use of an evolutionary metaheuristic, we adapted it in order to generate future using quantile regression. Computational experiments indicated the ability of the model in finding useful probabilistic quantiles, which were flexible enough in order to limit the lower and upper bounds of the historical datasets. While the probabilistic quantiles suggested the probability of rain and its magnitude, they were also able to predict expected ranges of the amount of energy generated from the wind farm.

关键词： Forecasting Predictive models Wind forecasting Probabilistic logic Wind power generation Adaptation models Time series analysis

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Tracking Security Flaws in Cryptographic Protocols Using Witness-Functions

Tracking Security Flaws in Cryptographic Protocols Using Wit...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Jaouhar Fattahi Mohamed Mejri Emil Pricop Department of Computer Science and Software Engineering Laval University Quebec Canada Automatic Control Computers and Electronics Department Petroleum-Gas University of Ploiesti Ploiesti Romania

ISBN: (纸本)9781479986989

In this paper, we use witness-function to capture attack scenarios in cryptographic protocols. A witness-function is a protocol-dependent metric that attributes a reliable security level to every atomic message. We use these functions to prove the protocol correctness with respect to secrecy by proving that the security level of every atomic message never decreases throughout all consecutive receiving and sending steps of the protocol. In this paper, we analyze the defective variant of the Otway-Rees protocol and we demonstrate that the use of witness-functions can be a key element in tracing a well-known type flaw that this protocol involves.

关键词： Context Cryptographic protocols Encryption computer science

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A two-layer transformation for characterizing the zeros of a network input-output dynamics 54

A two-layer transformation for characterizing the zeros of a...

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54th IEEE Conference on Decision and control, CDC 2015

作者： Torres, Jackeline Abad Roy, Sandip Department of Control and Industrial Automation Escuela Politécnica Nacional Quito170517 Ecuador School of Electrical Engineering and Computer Science Washington State University United States

ISBN: (纸本)9781479978861

Many networks can be modeled as collections of subsystems with complex internal dynamics, which are dynamically coupled according to a weighted digraph. This article characterizes the input-output behavior of a network of coupled homogeneous single-input single-output subsystems, in the case where external actuation and measurement are each applied at a single (but possibly different) component. Precisely, a two-layer transformation of the network's dynamics is undertaken, which makes explicit the roles of 1) the local subsystem model, 2) the network's global interconnections (graph), and 3) the input and output locations, in determining the zeros of the input-output model. The analysis of the zeros via this special-coordinate-basis decomposition shows a parallel with the spectral analysis of the coupled-subsystem model, and directly gives insight into the network's input-output dynamics and its feedback control. © 2015 IEEE.

关键词： Spectrum analysis

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Big Data Analytics in MOOCs

Big Data Analytics in MOOCs

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International Conference on computer and Information Technology (CIT)

作者： Yanyan Zheng Beibei Yin Department of Computer Science Beihang Univercity Lishui Beijing China Department of Automatic Control Beihang Univercity Beijing China

Large amounts of heterogeneous education data have emerged in MOOC, which are provided by various educational organizations and universities. In this paper, we present an overview of state-of-art research framework an... 详细信息

关键词： Big data Education Videos Correlation Industries Data models Proposals

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An ultra-high-density 256-channel/25mm2 neural sensing microsystem using TSV-embedded neural probes

An ultra-high-density 256-channel/25mm2 neural sensing micro...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Yu-Chieh Huang Po-Tsang Huang Shang-Lin Wu Yu-Chen Hu Yan-Huei You Ming Chen Yan-Yu Huang Hsiao-Chun Chang Yen-Han Lin Jeng-Ren Duann Tzai-Wen Chiu Wei Hwang Kuan-Neng Chen Ching-Te Chuang Jin-Chern Chiou Institute of Electrical Control Engineering National Chiao Tung University Hsinchu Taiwan Department of Electrical and Computer Engineering National Chiao Tung University Hsinchu Taiwan Department of Electronics Engineering National Chiao Tung University Hsinchu Taiwan National Chiao Tung University Hsinchu TW BME R&D Center China Medical University Taiwan Department of Biological Science and Technology National Chiao Tung University Hsinchu Taiwan

ISBN: (纸本)9781479953424

Highly integrated neural sensing microsystems are crucial to capture accurate signals for brain function investigations. In this paper, a 256-channel/25 mm2 neural sensing microsystem is presented based on through-silicon-via (TSV) 2.5D integration. This microsystem composes of dissolvable μ-needles, TSV-embedded μ-probes, 256-channel neural amplifiers, 11-bit area-power-efficient SAR ADCs and serializers. Based on the dissolvable μ-needles and TSV 2.5D integration, this microsystem can detect 256 ECoG/LFP signals within the small area of 5mm × 5mm. Additionally, the neural amplifier realizes 57.8dB gain with only 9.8μW for each channel, and the 9.7-bit ENOB of the SAR ADC at 32kS/s can be achieved with 0.42μW and 0.036 mm2. The overall power of this microsystem is only 3.79mW for 256-channel neural sensing.

关键词： Sensors Through-silicon vias Voltage control Bonding Probes Tuning Power demand

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Realization theory of linear hybrid systems

Lecture Notes in Control and Information Sciences

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Lecture Notes in control and Information sciences 2015年 457卷 59-101页

作者： Petreczky, Mihaly Department of Automatic Control and Computer Science Ecole des Mines de Douai 941 rue Charles Bourseul Douai59508 France

This chapter presents a survey on realization theory for linear hybrid systems. Recall that for linear systems, realization theory addresses the problem of existence and minimality of a linear time-invariant state-space representation of an input-output map (transfer function). The results of linear realization theory have turned out to be useful for control synthesis, model reduction, and system identification. In this chapter, we address a similar problem for linear hybrid systems and linear switched systems. We will also discuss the implications of realization theory for estimation and control of hybrid systems. © 2015, Springer International Publishing Switzerland.

关键词： Hybrid systems

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A Virtual and Remote Lab of the Two Electric Coupled Drives System in the University Network of Interactive Laboratories

A Virtual and Remote Lab of the Two Electric Coupled Drives ...

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American control Conference

作者： Jacobo Saenz Jesus Chacon Luis de la Torre Antonio Visioli Sebastian Dormido Department of Computer Science and Automatic Control Computer Science School UNED Juan del Rosal 16 Madrid Spain Department of Mechanical and Industrial Engineering University of Brescia Via Branze 38 Brescia Italy

ISBN: (纸本)9781479917730

This paper describes all the details on the latest addition to the University Network of Interactive Laboratories: a virtual and a remote laboratory of a two electric coupled drives system. This two new activities allow performing control practices in a 2×2 MIMO system. The virtual and the remote labs are accessible for anyone in a new open course that contains several other experiments in the automatic control field.

关键词： Remote laboratories control Methods automatic control multiple input multiple output systems Virtual Interactive Electricity Remote universities

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An approach for a distributed world model with QoS-based perception algorithm adaptation

An approach for a distributed world model with QoS-based per...

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： S. Blumenthal N. Hochgeschwender E. Prassler H. Voos H. Bruyninckx Department of Mechanical Engineering Katholieke Universiteit Belgium Automatic Control Laboratory University of Luxembourg Luxembourg Department of Computer Science Bonn-Rhein-Sieg University Germany

This paper presents a distributed world model that is able to adapt to changes in the Quality of Service (QoS) of the communication layer by online reconfiguration of perception algorithms. The approach consists of (a) a mechanism for storage, exchange and processing of world model data and (b) a feedback loop that incorporates reasoning techniques to adapt to QoS changes immediately. The latter introduces a Level of Detail (LoD) metric based on a spatial resolution in order to infer an upper bound for the amount of data that can be transmitted without violating an application specific transmission delay. Experiments have been performed with Octree-based subsampling techniques applied to data originating from a RGB-D camera using simulated and real-world data sets for timevarying bandwidth values as employed QoS measure.

关键词： Quality of service Data models Adaptation models Robots Measurement Three-dimensional displays Monitoring

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A Convergent and Fully Distributable SVMs Training Algorithm

A Convergent and Fully Distributable SVMs Training Algorithm

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International Joint Conference on Neural Networks

作者： Andrea Manno Simone Sagratella Lorenzo Livi Dipartimento di Elettronica Informazione e Bioingegneria of the Politecnico Milano via Ponzio 34/5 20133 Italy Department of Computer Control and Management Engineering Antonio Ruberti Sapienza University of Rome Via Ariosto 25 00185 Roma Italy Department of Computer Science Ryerson University 350 Victoria Street Toronto ON M5B 2K3 Canada

ISBN: (纸本)9781509006212

The Support Vector Machines (SVMs) dual formulation has a non-separable structure that makes the design of a convergent distributed algorithm a very difficult task. Recently some separable and distributable reformulations of the SVM training problem have been obtained by fixing one primal variable. While this strategy seems effective for some applications, in certain cases it could be weak since it drastically reduces the overall final performance. In this work we present the first fully distributable algorithm for SVMs training that globally converges to a solution of the original (non-separable) SVMs dual formulation. Besides a detailed convergence analysis, we provide a simple demonstrative example showing the advantages of the original SVMs dual formulation with respect to the weak separable one and highlights the practical effectiveness of our method. We report further tests to show practical convergence of the proposed method on real-world datasets.

关键词： Training Support vector machines Distributed algorithms Convergence Optimization Algorithm design and analysis Supervised learning

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