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Smart grid management & visualization: Smart Power Management System

Smart grid management & visualization: Smart Power Managemen...

引用

International conference & Expo on Emerging Technologies for a Smarter World (CEWIT)

作者： Grace Q. Tang Graheroce International Corporation Toronto Canada

This paper presents an innovation Smart Power Management System on Smart Grid. This report consists of 5 major sections: smart power system modeling; real time power system monitoring; system engineering database collection and management; grid condition checking and maintenance; smart grid power system fault analysis. Smart Power Management System enables grid management and visualization to be very effective as it incorporates real time monitoring data and historic engineering data into an integrated system, analyzing scenarios based on various modules and making it possible to collect, monitor and control real time data with accuracy. Smart Power Management System modeling is based on a variety of factors according to regulation policies, grid management requirements and operation rules. Various scenario modules of Smart Power Management System can be developed and modified based on the client's specifications for its grid conditions and operation needs. Neural Networks adds an interesting flavor of intelligent modeling to this integrated system, which provides the most appropriate solution to solve important issues in power system engineering, system design, grid operation, maintenance and management. Intelligent functions of Smart Power Management System can also be modified via wireless channels to cell phones or other mobile devices for maintenance staff. Real time signals of abnormal system indications can be sent out to field maintenance and grid operation as required. Needleless to say, Smart Power Management System makes it possible that all desired functions can be integrated so as to support complete automation control for un-manned power system substations in the future, to monitor real time system information, to update real time system data, to identify grid weakness points, to help field maintenance keep power system facilities in a good working condition, to conduct power systems fault analysis and operator training, to effectively support field ma

关键词： Maintenance engineering Real time systems Smart grids Power system faults Monitoring Power system reliability

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Gradient-based classification and representation of features from volume data

Gradient-based classification and representation of features...

引用

International conference on System Theory, Control, and Computing (ICSTCC)

作者： Marius Gavrilescu Vasile Manta Eduard Gröller Technical University of Iasi Romania Vienna University of Technology Austria Faculty of Automatic Engineering and Computer Control Technical University of Iasi Romania Computer Science Department University of Bergen Norway

The extraction and representation of information from volume data are important research avenues in computer-based visualization. The interpretation of three- or multi-dimensional data from various scanning devices is important to medical imaging, diagnosis and treatment, reliability and sustainability analyses in various industrial branches, and, in more general terms, information visualization. In this paper, we present several approaches for the classification and representation of relevant information from volume data sets. The techniques are based on the gradient vector, a property directly derived from the original volume data. We show how this property can be computed and subsequently used for classification through gradient-based one- and multi-dimensional transfer functions, as well as for the enhancement of surface features. The described techniques are illustrated through images generated using our volume rendering framework, from Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) data sets. The resulting images show how gradient-based techniques are suited for improved volume classification and the better extraction of meaningful information.

关键词： Transfer functions Image color analysis Rendering (computer graphics) Computed tomography Magnetic resonance imaging Skin Support vector machine classification

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Rumor analysis framework in social media

Rumor analysis framework in social media

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IEEE Region 10 International conference TENCON

作者： Takako Hashimoto Tetsuji Kuboyama Yukari Shirota Commerce and Economics Chiba University for Commerce Chiba Japan Computer Center Gakushuin University Tokyo Japan Department of Management Faculty of Economics Gakushuin University Tokyo Japan

When a disaster occurred, people try to acquire information through social media such as electronic bulletin boards, SNSs, and video services. Their decision-making tend to be affected by social media information. Sometimes, social media information is useful, so people can get valuable knowledge. On the other hand, social media information is occasionally unreliable. Harmful rumors spread and cause people to panic. In today's information oriented society, a mechanism to detect rumor information in social media has become very important. This paper proposes a framework to detect the rumor information in social media. Our proposed framework clarifies topics in social media, visualizes topic structures in time series variation. Then it extracts rumor candidates and seeks related information from other media such as TV program, newspapers and so on in order to confirm the reliability of rumor candidates. By our framework, potential rumors will be shown.

关键词： Media Petroleum Reliability Earthquakes Time series analysis visualization data mining

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NetVisia: Heat Map & Matrix visualization of Dynamic Social Network Statistics & Content

NetVisia: Heat Map & Matrix Visualization of Dynamic Social ...

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IEEE International conference on and IEEE International Confernece on Social Computing (SocialCom) Privacy, Security, Risk and Trust (PASSAT)

作者： Robert Gove Nick Gramsky Rose Kirby Emre Sefer Awalin Sopan Cody Dunne Ben Shneiderman Meirav Taieb-Maimon University of Maryland at College Park College Park MD US Department of Computer Science University of Maryland College Park MD USA Ben-Gurion University of the Negev Beersheva Israel Human-Computer Interaction Laboratory University of Maryland College Park MD USA

visualizations of static networks in the form of node-link diagrams have evolved rapidly, though researchers are still grappling with how best to show evolution of nodes over time in these diagrams. This paper introduces NetVisia, a social network visualization system designed to support users in exploring temporal evolution in networks by using heat maps to display node attribute changes over time. NetVisia's novel contributions to network visualizations are to (1) cluster nodes in the heat map by similar metric values instead of by topological similarity, and (2) align nodes in the heat map by events. We compare NetVisia to existing systems and describe a formative user evaluation of a NetVisia prototype with four participants that emphasized the need for tool tips and coordinated views. Despite the presence of some usability issues, in 30-40 minutes the user evaluation participants discovered new insights about the data set which had not been discovered using other systems. We discuss implemented improvements to NetVisia, and analyze a co-occurrence network of 228 business intelligence concepts and entities. This analysis confirms the utility of a clustered heat map to discover outlier nodes and time periods.

关键词： Heating Measurement Social network services Layout Training Image color analysis Usability

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Multiresolution Streamline Placement for 2D Flow Fields

Multiresolution Streamline Placement for 2D Flow Fields

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International conference on Computational Intelligence and Security

作者： Wenyao Zhang Manrui Zhang Bo Sun School of Computer Science and Technology Beijing Institute of Technology Beijing China

ISBN: (纸本)9781457720086

Streamline is a popular choice to visualize flow fields, but it not easy to determine the number and the distribution of streamlines. In this paper, a multiresolution streamline placement method is presented to visualize 2D flow fields at different levels of detail. Each level has different number of streamlines that are uniformly distributed in the field at different resolutions. This method is implemented by constructing a hierarchy of control grids to manipulate the procedure of placement. The top level of the hierarchy is the coarsest control grid whose cell size is predefined. Using this grid and a centroid-based seeding strategy, a sparse placement is obtained, where streamlines are evenly-spaced. Then, this sparse placement is changed into the next lower level by adding some new streamlines within the gaps of all existing streamlines under the control of a finer control grid. Although the total number of streamlines is increased, the original uniformity is not destroyed. The resolution and the density of streamlines are both improved from one level to its next lower level. This refinement between adjacent levels can be repeated until a suitable placement is obtained. Corresponding to the control grids, a hierarchy of streamline placements with different resolutions is also built up during the multiresolution analysis. It gives an opportunity to select suitable streamline placements with desired resolutions. And it also provides a new way to have an insight into the flow field at different scales. Test results show that this multiresolution streamline placement is valid and efficient.

关键词： Streaming media Image resolution visualization Multiresolution analysis data visualization Current control Spirals

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Eavesdropping on echolocation: Recording the bat's auditory experience

Eavesdropping on echolocation: Recording the bat's auditory ...

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

作者： Kevin B. Austin Paul R. Moosman Howard H. Thomas Computer Science Department Fitchburg State University Fitchburg MA USA Biology Department Virginia Military Institute Lexington VA USA Biology Department Fitchburg State University Fitchburg MA USA

Insectivorous bats are able to locate and capture insects in complete darkness while flying at high speeds. They may consume hundreds of insects each night while avoiding obstacles in a complex environment. To investigate the processes associated with bat echolocation, we have developed instrumentation that allows us to record and visualize what a bat hears while flying through its natural environment. Recordings were made using a miniaturized radio telemetry system mounted directly on the back of the bat. This paper describes the design and testing of the components of this system, presents echolocation data collected from bats and discusses issues associated with the visualization and analysis of echoes recorded in a natural setting from the bat's point-of-view. It presents a new tool for visualizing a bat's experience by generating call sequence sonograms (CSSs) based on various signal parameters. CSSs based on time series amplitude, band-limited spectral magnitude and Q-factor are presented. This work demonstrates that CSSs based on Q-factor (computed by dividing a peak frequency estimate by a bandwidth estimate) provides a relatively clear representation of the objects producing echoes encountered by a bat during a continuous flight.

关键词： Microphones Cascading style sheets Sonogram Wireless communication visualization Time series analysis

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A comparative study of spatial, temporal and content-based patterns emerging in YouTube and Flickr

A comparative study of spatial, temporal and content-based p...

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International conference on Computational Aspects of Social Networks, CASON

作者： Milan Mirkovic Dubravko Culibrk Symeon Papadopoulos Christos Zigkolis Yiannis Kompatsiaris Gavin McArdle Vladimir Crnojevic Faculty of Technical Sciences University of Novi Sad Novi Sad Serbia Informatics and Telematics Institute Centre of Research and Technology Hellas Thessaloniki Greece National Centre of Geocomputation National University of Ireland Maynooth Dublin Ireland

Due to the recent advances and wide adoption of Web 2.0 technologies, there is an abundance of publicly available user generated content, which can be a valuable resource for researchers, enabling them to apply sophisticated analysis methods on data of unprecedented scale. This paper focuses on the detection and comparison of spatial, temporal and content-based patterns from user-generated content available through two major content-sharing services YouTube and Flickr aiming to explain some of the observed differences. In particular, we use different clustering approaches and visualization techniques to discover interesting spots in a city using the publicly available content (images, videos and associated metadata), we then classify them as either landmarks or events, and compare their ranking for each of the respective service. Based on that ranking, we confirm the expected pattern that people tend to take pictures of still objects (monuments, sights) and make videos of events. We also consider the temporal aspect of the data, and extract movement trajectories of users. Lastly, we discover that even single users can generate noticable patterns, and that people find diverse uses of these content- sharing services.

关键词： YouTube Cities and towns Videos Heating visualization Springs Optics

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Design and implementation of data function and management system for EUMETCast

Design and implementation of data function and management sy...

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2011 International conference on Computer Science and Service System, CSSS 2011

作者： Xie, Hongquan Wei, Hua Su, Yingfeng School of Geodesy and Geomatics Engineering Huaihai Institute of Technology Lianyungang China Department of Resource and Environment Baoding University Baoding China Beijing Ultrasoft Information Technology Co. Ltd. Beijing China

ISBN: (纸本)9781424497638

EUMETCast data has higher real-time, and its products have been widely due to numerical weather prediction model. Although the National Satellite Meteorological Center has been authorized to receive data, because of various data formats, file slice distribution, for data management and application are very inconvenient. Therefore, the establishment of a business application system EUMETCast automatic data processing and standardization of storage, visualization sharing become an urgent problem. In this paper, the core business processes to system analysis and description, based on the overall technical architecture describes the system operating environment and system design. Four aspects of the functionality of the system were described in detail, and finally the four sub-systems to achieve results of EUMETCast data Management System were introduced. At present, the business system is stable, EUMETCast meteorological and environmental data for the majority of researchers analyzed the daily operations and scientific research has brought greatly facilitated. © 2011 IEEE.

关键词： Information management

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Exploiting observers' judgements for nonverbal group interaction analysis

Exploiting observers' judgements for nonverbal group interac...

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International conference on Automatic Face and Gesture Recognition

作者： Gokul Chittaranjan Oya Aran Daniel Gatica-Perez Idiap Research Institute Martigny Switzerland Ecole Polytechnique Federale de Lausanne Switzerland

Incorporating annotators' knowledge into a machine-learning framework for detecting psychological traits using multimodal data is an open issue in human communication and social computing. We present a model that is designed to exploit the subjective judgements of multiple annotators on a social trait labeling task. Our two-stage model first estimates a ground truth by modeling the annotators using both the annotations and annotators' self-reported confidences. In the second stage, we train a classifier using the estimated ground truth as labels. We also define ways to verify the consistency of our model and validate it using annotations and nonverbal cues for a dominance estimation task in a group interaction scenario on the publicly available DOME corpus, in addition to synthetically generated data. Our models give satisfactory results, outperforming the commonly used majority voting as well as other approaches in the literature.

关键词： visualization Computational modeling Estimation Feature extraction Mathematical model Sensitivity data models

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Assessing Media Relevance via Eye Tracking

Assessing Media Relevance via Eye Tracking

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International conference on Advances in Social Network analysis and Mining, ASONAM

作者： Cheng-Ta Yang Wen-Sheng Chang Fan-Ning Cheng Wei-Guang Teng Department of Psychology and Institute of Cognitive Science National Cheng Kung University Tainan Taiwan Department of Engineering Science National Cheng Kung University Tainan Taiwan

To ease the problem of data overloading, it is crucial to understand the user behavior when s/he interacts with online contents, or more specifically, a web page containing several entries for further exploration. We devise to estimate the relevance of an entry to the user goal by observing eye movements as implicit feedback. Specifically, this study proposes a framework that assumes eye movement measures can be used to infer a user's cognition. A rating task was conducted in which subjects were required to judge whether an image was relevant to a word. Results showed that the total fixation duration and the fixation count can be used to discriminate between the relevant and irrelevant conditions, in contrast, the first fixation duration cannot. In addition, the subjective rating and relevancy manipulation interacted on the total fixation duration. Converging evidence verifies the assumption we have proposed.

关键词： Distribution functions visualization Search engines Time factors Cognition Tracking

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