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MatchPad: Interactive glyph-based visualization for real-time sports performance analysis

MatchPad: Interactive glyph-based visualization for real-tim...

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14th Eurographics Conference on visualization 2012, EuroVis 2012

作者： Legg, P.A. Chung, D.H.S. Parry, M.L. Jones, M.W. Long, R. Griffiths, I.W. Chen, M. Department of Computer Science Swansea University United Kingdom College of Engineering Swansea University United Kingdom Centre of Excellence Welsh Rugby Union United Kingdom E-Research Centre Oxford University United Kingdom

Today real-time sports performance analysis is a crucial aspect of matches in many major sports. For example, in soccer and rugby, team analysts may annotate videos during the matches by tagging specific actions and events, which typically result in some summary statistics and a large spreadsheet of recorded actions and events. To a coach, the summary statistics (e.g., the percentage of ball possession) lacks sufficient details, while reading the spreadsheet is time-consuming and making decisions based on the spreadsheet in real-time is thereby impossible. In this paper, we present a visualization solution to the current problem in real-time sports performance analysis. We adopt a glyph-based visual design to enable coaching staff and analysts to visualize actions and events "at a glance". We discuss the relative merits of metaphoric glyphs in comparison with other types of glyph designs in this particular application. We describe an algorithm for managing the glyph layout at different spatial scales in interactive visualization. We demonstrate the use of this technical approach through its application in rugby, for which we delivered the visualization software, MatchPad, on a tablet computer. the MatchPad was used by the Welsh Rugby Union during the Rugby World Cup 2011. It successfully helped coaching staff and team analysts to examine actions and events in detail whilst maintaining a clear overview of the match, and assisted in their decision making during the matches. It also allows coaches to convey crucial information back to the players in a visually-engaging manner to help improve their performance. © 2012 the Author(s).

关键词： Spreadsheets

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Misconfiguration detection for cloud datacenters using decision tree analysis

Misconfiguration detection for cloud datacenters using decis...

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Asia-Pacific Network Operations and Management symposium (APNOMS)

作者： Tetsuya Uchiumi Shinji Kikuchi Yasuhide Matsumoto Cloud Computing Research Center Fujitsu Laboratories Limited Kawasaki Kanagawa Japan

Since many components comprising large scale cloud datacenters have a great number of configuration parameters (e.g. hostnames, languages, and time zones), it is difficult to keep consistencies in the configuration parameters. In such cases, misconfigured parameters can cause service failures. For this reason, we propose a misconfiguration detection method for large-scale cloud datacenters, which can automatically determine possible misconfigurations by identifying the relations existing among majority of the parameters using statistical decision tree analysis. We have also developed a pattern modification method to improve the accuracy of the decision tree approach. We evaluated the misconfiguration detection performance of the proposed method by using both artificial data and actual data. the results show that we can achieve higher accuracy (78.6% in the actual data) in misconfiguration detection by using the pattern modification.

关键词： Servers Decision trees Cloud computing Accuracy Monitoring IP networks Algorithm design and analysis

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large-scale computational experiments for complex enterprise systems behaviour prediction

Large-scale computational experiments for complex enterprise...

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14th IFAC symposium on Information Control Problems in Manufacturing, INCOM'12

作者： Babiceanu, Radu F. Department of Systems Engineering University of Arkansas at Little Rock Little Rock AR 72204 United States

ISBN: (纸本)9783902661982

this work comes as a contribution to the efforts that are undergoing within engineering systems community to account for the increased complexity of today's manufacturing or service systems. these systems are becoming more and more complicated due to the increase in the number of elements, interconnections within the system, and necessary integration with other systems. Moreover, through the emphasis on self-organization and considering the multi-stakeholders context and objectives, these systems are crossing the line towards complexity. there is a need for developing a framework to be used in modeling, analysis, and integration of systems that operate in uncertain environments, in which characteristics such as adaptation, self-organization and evolution, or in other words behavior prediction, need to be addressed. the proposed complex enterprise systems framework combines knowledge coming from complex systems science and systems engineering domains, and uses computational intelligence and agent-based systems simulation methodologies. the approach requires computational experience in manipulating large amounts of data and building large-scale simulation models. A significant result to be made possible by this research is that systems may no longer have a fixed, life-cycle long, design based on identified requirements;systems will be engineered to evolve and adapt as needed during the operational phase, while respecting their operational environment constraints. © 2012 IFAC.

关键词： Life cycle

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Execution data connected simulation for production operation planning and control

Execution data connected simulation for production operation...

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14th IFAC symposium on Information Control Problems in Manufacturing, INCOM'12

作者： Kádár, B. Pfeiffer, A. Monostori, L. Fraunhofer Project Center on Production Management Informatics Computer and Automation Research Institute Hungarian Academy of Sciences Budapest Hungary Department of Manufacturing Science and Technology Faculty of Mechanical Engineering Budapest University of Technology and Economics Budapest Hungary

ISBN: (纸本)9783902661982

Due to the large number of the resources, the frequent reengineering of manufacturing processes and the often changing product types, the maintenance of the simulation model and the provision of up-to-date input data are almost always difficult. the paper introduces new quantitative analysis method including processing time and batch calculation algorithms applied in the automatic building of discrete-event simulation systems. the simulation model and the mentioned algorithms are both directly interfaced with real execution databases and the overall solution supports the shop-floor managers in making control decisions. the applicability of the elaborated approach is illustrated by the results of experiments relying on real historical data. © 2012 IFAC.

关键词： Manufacture

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Parallel Implementation and Performance analysis of a 3D Oil Reservoir data visualization Tool on the Cell Broadband Engine and CUDA GPU

Parallel Implementation and Performance Analysis of a 3D Oil...

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IEEE International Conference on High Performance Computing and Communications (HPCC)

作者： Fadi N. Siba Saadullah Mohammad Hashir Karim Kidwai Bibrak Qamar Falah Awwad Saudi Aramco R&D Center Dhahran Saudi Arabia IBM Cell Center of Competency and Faculty of Information Technology UAE University Al Ain United Arab Emirates

ISBN: (纸本)9781467321648

Usefulness of graphically visualizing and manipulating large data sets in oil and gas exploration and production is as important as ever. this paper describes the development and parallelization of a multi-phase 3D oil-water reservoir visualization tool on the IBM Cell computer and CUDA enabled GPU. An independent Oil reservoir simulator described in [1] was used to generate the pressure and oil / water saturation values over a certain period of time. the oil reservoir visualization tool displays data grids in a 3D environment and allows the user to interact with it. Due to large speed requirements, our aim is to parallelize the computations required to interact with and visualize the grid, mainly transformation [2], zooming, camera movement [3] and compute intensive lighting model [4][5]. this tool also allows the user to playback the simulation results over a time duration and fetches data values upon mouse click at a particular grid point on a particular day. the development environments are nVIDIA CUDA and IBM Cell SDK 3.0 along with QT and OpenGL libraries. Various experiments were run on an ×86 computer with nVIDIA Quadro FX 5800 GPU, and on an IBM Cell BE computer with 1 QS20 Cell blade containing two 9-core Cell processor packages. Our results indicate that the nVIDIA GPU provides on average, speed up of 67× over serial implementation and IBM Cell BE with 16 SPE SIMD implementation 32× over the serial implementation.

关键词： Graphics processing unit Vectors Image color analysis Lighting data visualization Reservoirs Cameras

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Practical Optimizations for Perceptron Algorithms in large Malware dataset

Practical Optimizations for Perceptron Algorithms in Large M...

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International symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)

作者： Dragos Gavrilut Razvan Benchea Cristina Vatamanu Faculty of Computer Science Al. I. Cuza University of Iaşi Romania Romania Bitdefender Anti-virus Res. Lab. Gh. Asachi Univ. of Iasi Iasi Romania

Due to the increasing number of malware samples in the past 4 years, machine learning algorithms emerged as an important tool in automated malware detection. this approach to create the detection model requires, however, a lot of time with a continually growing data-set. Often changes in malware families and the increasing training time makes the model less efficient and increases the probability of false alarms. this paper approaches this matter by reducing the time needed to create a detection model on very large databases and suggests three different optimization techniques. First, the perceptron algorithm was adjusted to use the map-reduce paradigm in order to make it run in a distribute manner. Second, hardware specific optimizations were applied for faster mathematical computations. Finally, a cache system was used to reduce the quantity of data processed by the algorithm. Even if these methods were designed and tested for malware databases they can easily be adjusted for other databases as well.

关键词： Training Optimization Algorithm design and analysis Malware Machine learning algorithms databases Adaptation models

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An Autonomic Reliability Improvement System for Cyber-Physical Systems

An Autonomic Reliability Improvement System for Cyber-Physic...

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IEEE International Symposim on High Assurance Systems Engineering

作者： Leon Wu Gail Kaiser Department of Computer Science Columbia University New York USA

System reliability is a fundamental requirement of cyber-physical systems. Unreliable systems can lead to disruption of service, financial cost and even loss of human life. Typical cyber-physical systems are designed to process large amounts of data, employ software as a system component, run online continuously and retain an operator-in-the-loop because of human judgment and accountability requirements for safety-critical systems. this paper describes a data-centric runtime monitoring system named ARIS (Autonomic Reliability Improvement System) for improving the reliability of these types of cyber-physical systems. ARIS employs automated online evaluation, working in parallel with the cyber-physical system to continuously conduct automated evaluation at multiple stages in the system workflow and provide real-time feedback for reliability improvement. this approach enables effective evaluation of data from cyber-physical systems. For example, abnormal input and output data can be detected and flagged through data quality analysis. As a result, alerts can be sent to the operator-in-the-loop, who can then take actions and make changes to the system based on these alerts in order to achieve minimal system downtime and higher system reliability. We have implemented ARIS in a large commercial building cyber-physical system in New York City, and our experiment has shown that it is effective and efficient in improving building system reliability.

关键词： Buildings Software Support vector machines Software reliability Time series analysis Reliability engineering

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Real-Time Anomaly Detection in Streams of Execution Traces

Real-Time Anomaly Detection in Streams of Execution Traces

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IEEE International Symposim on High Assurance Systems Engineering

作者： Wenke Zhang Favyen Bastani I-Ling Yen Kevin Hulin Farokh Bastani Latifur Khan University of Texas at Dallas USA Massachusetts Institute of Technology USA University of Texas Dallas USA

For deployed systems, software fault detection can be challenging. Generally, faulty behaviors are detected based on execution logs, which may contain a large volume of execution traces, making analysis extremely difficult. this paper investigates and compares the effectiveness and efficiency of various data mining techniques for software fault detection based on execution logs, including clustering based, density based, and probabilistic automata based methods. However, some existing algorithms suffer from high complexity and do not scale well to large datasets. To address this problem, we present a suite of prefix tree based anomaly detection techniques. the prefix tree model serves as a compact loss less data representation of execution traces. Also, the prefix tree distance metric provides an effective heuristic to guide the search for execution traces having close proximity to each other. In the density based algorithm, the prefix tree distance is used to confine the K-nearest neighbor search to a small subset of the nodes, which greatly reduces the computing time without sacrificing accuracy. Experimental studies show a significant speedup in our prefix tree based and prefix tree distance guided approaches, from days to minutes in the best cases, in automated identification of software failures.

关键词： Software Clustering algorithms Algorithm design and analysis Automata Probabilistic logic Software algorithms data models

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Advancing Critical Care in the ICU: A Human-Centered Biomedical data visualization Systems

Advancing Critical Care in the ICU: A Human-Centered Biomedi...

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International Conference on Ergonomics and Health Aspects of Work with Computers (EHAWC)/14th International Conference on Human-Computer Interaction (HCI)

作者： Faiola, Anthony Newlon, Chris Indiana Univ Sch Informat Indianapolis IN 46202 USA

ISBN: (纸本)9783642217166;9783642217159

the purpose of this research is to provide medical clinicians with a new technology for interpreting large and diverse datasets to expedite critical care decision-making in the ICU. We refer to this technology as the medical information visualization assistant (MIVA). MIVA delivers multivariate biometric (bedside) data via a visualization display by transforming and organizing it into temporal resolutions that can provide contextual knowledge to clinicians. the result is a spatial organization of multiple datasets that allows rapid analysis and interpretation of trends. Findings from the usability study of the MIVA static prototype and heuristic inspection of the dynamic prototype suggest that using MIVA can yield faster and more accurate results. Furthermore, comments from the majority of the experimental group and the heuristic inspectors indicate that MIVA can facilitate clinical task flow in context-dependent health care settings.

关键词： Biomedical data visualization human-computer interaction health care health information technology interface design

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Efficient graph comparison and visualization using GPU

Efficient graph comparison and visualization using GPU

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14th IEEE Int. Conf. on Computational Science and Engineering, CSE 2011, the 11th International symposium on Pervasive Systems, Algorithms, and Networks, I-SPAN 2011, and the 10th IEEE Int. Conf. on Ubiquitous Computing and Communications, IUCC 2011

作者： Czech, Wojciech Yuen, David A. Institute of Computer Science AGH University of Science and Technology Krakow Poland Minnesota Supercomputing Institute University of Minnesota Minneapolis MN United States

ISBN: (纸本)9780769544779

this paper presents application of several graph algorithms for comparison and visualization of real-world networks. In order to obtain interactive and robust framework for analysis of large graphs we use CUDA implementations of all-shortest-paths (APSP) and breadth-first-search (BFS) algorithms along with CULA matrix decomposition routines. Such an approach allows for efficient computation of graph feature vectors, visualization with graph B-matrices and accelerating dimensionality reduction methods used to embed graphs into low-dimensional metric spaces. Graph analysis algorithms implemented in CUDA were integrated with Graph Investigator Java application via Java Native Interface (JNI) what makes them more convenient to use. We further present two real-world usage scenarios i.e. analysis and visualization of vascular networks in presence of tumor and clusterization based on graph representations of satelite photos. © 2011 IEEE.

关键词： visualization

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