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检索条件"任意字段=3rd IEEE Intelligent Data Acquisition and Advanced Computing Systems"

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Traffic control assistance in connection nodes: multi-agent applications in urban transport systems

Traffic control assistance in connection nodes: multi-agent ...

引用

ieee International Workshop on intelligent data acquisition and advanced computing systems: Technology and Applications

作者： H. Laichour S. Maouche R. Mandiau Lab. d'Autom. Lille I Univ. Villeneuve d'Ascq France Laboratoire d'Automatique I3D Université des Sciences et Technologies de Lille Villeneuve d'Ascq France LAMIH Universita de Valenciennes et du Hainaut Cambrésis le Mont Houy Valenciennes France

We propose a model for a transport system based on a hierarchical multi-agent system (HMAS). This model can be used in order to design a decision support system (DSS) to facilitate the work of the regulator by proposing various regulation actions in every connection node (SARC: Systeme d'Aide a la Regulation des Correspondances). An optimal organization of the connections is suggested in normal or disturbed conditions, to avoid loss of time for the passengers. Our model includes a supervisor agent (interface), a connection agent (decision) for each connection node and an acquisition agent (perception) for each regulation station. In our research, we have used multi-agent systems (MAS) which adapt themselves perfectly to the distributed systems as in the urban transport networks.

关键词： Traffic control Multiagent systems Regulators Decision support systems Telecommunication traffic Vehicles Computerized monitoring Transportation Delay Scheduling

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Fast Kernel for Calculating Structural Information Similarities

Fast Kernel for Calculating Structural Information Similarit...

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International ieee Conference on intelligent systems, IS

作者： Jin-Mao Wei Shu-Qin Wang Jing Wang Jun-Ping You Institute of Computational Intelligence Northeast Normal University China Open Symbol Computation and Knowledge Engineering Laboratory of State Education Jilin University Changchun Jilin China School of Mathematics & Statistics Northeast Normal University Changchun Jilin China

Structural similarity computation plays a crucial role in many applications such as in searching similar documents, in comparing chemical compounds, in finding genetic similarities, etc. We propose in this paper to use structural information content (SIC) for measuring structural information, considering both the nodes and edges of trees. We utilize a binary encoding approach for assigning the weights of different layer nodes and determining if some tree is a subtree of another tree. By defining a fast kernel and recursively computing SICs, we evaluate the structural information similarities of data trees to pattern trees. In the paper, we present the algorithm for calculating SICs with computation complexity of O(n), and use simple examples to instantiate the performance of the proposed method

关键词： Kernel Chemical compounds Silicon carbide XML Genetics Encoding Clustering algorithms intelligent systems intelligent structures Pattern analysis

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An Online Wear State Identification Method for Axial Piston Pump Key Friction Pair based on FSANN 3

An Online Wear State Identification Method for Axial Piston ...

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3rd International Conference on Sensing, Measurement and data Analytics in the Era of Artificial Intelligence, ICSMD 2022

作者： Wang, Dandan Liu, Shihao Huang, Weidi Zhang, Junhui Xu, Bing Zhejiang University State Key Laboratory of Fluid Power and Mechatronic Systems Hangzhou China

ISBN: (纸本)9781665492812

Wear state identification of the axial piston pump is of great importance to secure the modern hydraulic system. Offline intelligent fault diagnosis methods are significant to solve the wear state identification problems. Nevertheless, these methods cannot meet the demand of real-time wear state identification. In this paper, an accurate and online wear state identification method based on edge computing using feature selected artificial neural network (FSANN) is proposed for the axial piston pump key friction pair. To reduce latency, an edge end node including data collection, signal pre-processing, feature extraction, fault classification is established. To cut down the amount of calculation and transmission while retaining accuracy, features sensitive to the fault are selected. The embedding performance of one-against-all support vector machine (OAA-SVM), artificial neural network (ANN), deep belief network (DBN) is compared and ANN is chosen as the embedded diagnostic model. The experimentally verified accuracy of this method is 99.0%. The single diagnosis time(SDT) is about 0.24s. Compared to transmitting raw data to the host computer, this method cut down the amount of data by about 200 times. The proposed method could diagnose the slipper wear state accurately and quickly and provide a potential way for real-time fault diagnosis for axial piston pump. © 2022 ieee.

关键词： Artificial neural network Axial piston pump Edge computing Feature selection Wear state identification

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The cyclic services in an industrial network

The cyclic services in an industrial network

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ieee International Conference on Embedded and Real-Time computing systems and Applications (RTCSA)

作者： M. Li Computer Engineering Department Swiss Federal Institute of Technology Lausanne Switzerland

In Profibus master stations poll data from slave stations using the cyclic service-CSrd (Cyclic Send and Request data with Reply). Because the polling-interval determines the data sampling interval, it is important for the Profibus user to be able to know the maximum polling-interval of a cyclic service. In this paper we develop a formula for determining the maximum polling-interval of a cyclic service. Furthermore, if the polling-interval of a cyclic service cannot be met, then we can repeat the corresponding cyclic service in a poll list to reduce the polling-interval. However, how are the repeated cyclic services to be positioned in the poll list? The approach we use is an equi-distance one.

关键词： intelligent networks Sampling methods Master-slave data communication Sensor phenomena and characterization data engineering Field buses Feedback control Actuators Sensor systems

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Robust total least squares based optic flow computation 3rd

Robust total least squares based optic flow computation

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3rd Asian Conference on Computer Vision, ACCV 1998

作者： Bab-Hadiashar, Alireza Suter, David Intelligent Robotics Research Centre Department of Electrical and Computer Systems Engineering Monash University ClaytonVIC3168 Australia

ISBN: (纸本)3540639306

This paper considers the problem of finding a robust solution to the optic flow problem. The optical flow field is recovered by solving a system of over-determined linear equations with all the data matrices containing both outliers and noise. Here, we present a novel and very effective solution for this problem called weighted total least squares. The weights for this method are computed using a new robust statistical method named least median of squares orthogonal distances. Unlike the total least squares which is only robust to noise, this method is extremely robust to both noise and outliers and can tolerate up to 50% of equations in the system to be contaminated by outliers. The proposed weighting method is fast and the total computation remains inexpensive. To demonstrate the performance of the proposed algorithm, we compare the accuracy of our algorithm for computing optic flow field for a number of synthetic and real image sequences and show that the proposed method, despite being very simple and straightforward, out performs all methods used for comparison. © Springer-Verlag Berlin Heidelberg 1997.

关键词： Flow fields

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An open affective platform

An open affective platform

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ieee International Conference on Networked Embedded systems for Enterprise Applications

作者： Nik Thompson Terry Koziniec Tanya McGill School of Information Technology Murdoch University Perth Australia

ISBN: (纸本)9781467347211

Affective computer interfaces improve human-computer interaction by enabling the communication of the user's emotional state. To this end, subtle non-verbal methods of communication provide a rich source of information which may provide valuable affective context to the human-computer interaction. Of particular note are physiological indicators of affective state, as these are objective in nature and have been demonstrated to be successful in many studies. Physiological computing may be viewed as a data acquisition and signal processing task whereby the electrical impulses or biopotentials created by the body are captured, analyzed and recorded in a suitable format for later communication. Whilst there are a number of commercially available hardware platforms to support physiological data acquisition, these all possess limitations in a few distinct areas. Not least of these is the physical form factor. For such devices to be embedded and integrated into the next generation of computer interfaces, an open physiological platform is required. This will enable future development to build upon this foundation and concentrate on novel and unique form factors and implementation environments. This paper describes the development and implementation of an open affective platform. This hardware and software solution provides the necessary functionality to measure and describe the users underlying affective state in terms of its component dimensions. This data may then be communicated to other application software, or modules within a larger affective computing application.

关键词： Sensors Physiology Skin Hardware data acquisition Software Electrodes

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Emergency Forecasting on the Basis of the Bifurcation Analysis Practice-Oriented to Local Climate Dynamics

Emergency Forecasting on the Basis of the Bifurcation Analys...

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ieee International Conference on intelligent data acquisition and advanced computing systems

作者： Yury Kolokolov Anna Monovskaya Orel State University

ISBN: (纸本)9781728140704

Specialized data processing aimed to the emergency forecasting on local climate dynamics over last century from the bifurcation analysis viewpoint can suppose analytics on specific phenomena which were out of considerations until recently. The paper discusses a pilot version of the computer software, where one of such phenomena (namely, so-called interannual temperature variability) is involved into the consideration in daily terms for time and temperature coordinates. Cycling is organized per a local climate system, where five logically independent procedures operate with specialized 3D-structure. Each 3D-structure consists of 20-50 thousands samples of the meteorological observations on land surface air temperature daily means. The theoretical base is provided by the conceptual model on local climate dynamics (so-called HDS-model), where both the amplitude quantization (limited by the temperature Hysteresis) and the time quantization (the Double Synchronization) compete. Thus alternations between three elementary dynamical processes with the same period (one year) and different patterns of annual warming-cooling cycles exist instead of traditional trend estimations calculated for the annual and/or monthly means. We believe that the results could be interesting for scientists and specialists in the research and practical fields connected with consequences of the climate changes.

关键词： Emergency forecasting Bifurcation analysis Instrumental observations data processing Stability margin Uncertainty Dynamic system with a variable structure Interannual variability Local climate change local climate stability margin Automatic data processing data processing time quantization Basis computer software Uncertainty BIFURCATION Cycling meteorological observations Emergencies

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MCAR: multi-class classification based on association rule

MCAR: multi-class classification based on association rule

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ACS/ieee International Conference on Computer systems and Applications

作者： F. Thabtah P. Cowling Y. Peng Modelling Optimisation Scheduling and Intelligent Control Research Centre University of Bradford UK Department of Computing University of Bradford UK

Summary form only given. Constructing fast, accurate classifiers for large data sets is an important task in data mining and knowledge discovery. In this research paper, a new classification method called multi-class classification based on association rules (MCAR) is presented. MCAR uses an efficient technique for discovering frequent items and employs a rule ranking method which ensures detailed rules with high confidence are part of the classifier. After experimentation with fifteen different data sets, the results indicated that the proposed method is an accurate and efficient classification technique. Furthermore, the classifiers produced are highly competitive with regards to error rate and efficiency, if compared with those generated by popular methods like decision trees, RIPPER and CBA.

关键词： Association rules data mining Classification tree analysis Decision trees Processor scheduling intelligent control Error analysis Marketing and sales Transaction databases Promotion - marketing

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Evaluation of Adaptive computing Concepts for Classical ERP systems and Enterprise Services

Evaluation of Adaptive Computing Concepts for Classical ERP ...

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ieee International Conference on e-Commerce Technology (CEC)

作者： M. Wimmer V. Nicolescu D. Gmach M. Mohr A. Kemper H. Krcmar Technische Universität München Munich Germany

To ensure the operability and reliability of large scale enterprise resource planning systems (ERP), a peak-load oriented hardware sizing is often used. Better utilization can be achieved by employing an adaptive infrastructure based on smaller computational units in combination with an intelligent allocation management. The SAP University Competence Center (German SAP HCC) at the Technische Universitat Munchen provides support for 55 ERP training systems. The evaluation of the historical load data revealed that many applications exhibit cyclical resource consumption. In this paper we show the extraction of load patterns and present self-organizing controlling concepts in the context of the SAP HCC

关键词： Enterprise resource planning Hardware Sun data mining Quality of service Blades Large-scale systems Computational intelligence Management training Application software

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A Survey on Privacy Preserving Time-Series data Mining

A Survey on Privacy Preserving Time-Series Data Mining

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The 3rd International Conference on intelligent Computational systems(ICICS’2013);The 3rd International Conference on Mechanical,Automotive and Materials Engineering(ICMAME’2013);The 3rd International Conference on Electronics,Biomedical Engineering and its Applications(ICEBEA’2013);The 3rd International Conference on Ecological,Environmental and Biological Sciences(ICEEBS’2013);The 3rd International Conference on Business,Economics,Management and BehavioralSciences 2013(ICBEMBS’2013);The 3rd International Conference on Applied Mathematics and Pharmaceutical Sciences(ICAMPS’2013)

作者： Sun-Kyong Hong Kuldeep Gurjar Hea-Suk Kim Yang-Sae Moon the Dept. of Computer Science Kangwon National University

Recently, privacy preserving issues have been actively studied on the time-series data widely used in variety of applications such as financial, medical, and weather analysis. In this paper, we survey and analyze the recent work of privacy preserving data mining (PPDM) on time-series data. For this, we first investigate what is the privacy in time-series data. We then survey various perturbation techniques on time-series data in the centralized computing environment. We next investigate secure multi-party computation (SMC) and encryption techniques in the distributed computing environment. Social network and cloud computing applications incur a large volume of sensitive (time-series) data, and thus, privacy preserving techniques for exploiting those sensitive data have become much more substantial in many research areas. Our survey results can be used for developing efficient and robust time-series data-based PPDM techniques that can be applied to new computing environments.

关键词： privacy preserving, time-series data, data perturbation, secure multi-party computation

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