ppxscal/embedding_network huggingface dataset:
Improving integrated service delivery: a simulation game
Authors: Bram Klievink, Marijn Janssen
Venue: Proceedings of the 10th Annual International Conference on Digital Government Research: Social Networks: Making Connections between Citizens, Data and Government (2009)

Research on digital government finds itself studying a very complex domain. Often, this complexity is -- for research sake -- reduced, for example by applying statistical methods, classifying core concepts, introducing stage models, etc. An emergent and promising method for studying complex phenomena is serious gaming. A serious game refers to a situation in which human participants play a role and follow the rules of play to simulate complex situations. In this research we developed such a serious simulation game for the field of public-private service delivery. The purpose of the game is twofold; it is a teaching instrument for public organizations by enabling them to get to the core of the problem of designing integrated service delivery and to stimulate out-of-the-box solutions. By surveys and analysis instruments, the behavior in-, and outcomes of the game can be evaluated. In this way a serious game is a policy-instrument to stimulate new developments, a way to improve integrated service delivery and is a scientific instrument for theory building and testing in a semi-experimentation setting. Playing the game at a municipality shows that the game is suitable for creating awareness and for the identification and development of alternative solutions.
Expressing OLAP Preferences
Authors: Matteo Golfarelli, Stefano Rizzi
Venue: Proceedings of the 21st International Conference on Scientific and Statistical Database Management (2009)

Multidimensional databases play a relevant role in statistical and scientific applications, as well as in business intelligence systems. Their users express complex OLAP queries, often returning huge volumes of facts, sometimes providing little or no information. Thus, expressing preferences could be highly valuable in this domain. The OLAP domain is representative of an unexplored class of preference queries, characterized by three peculiarities: preferences can be expressed on both numerical and categorical domains; they can also be expressed on the aggregation level of facts; the space on which preferences are expressed includes both elemental and aggregated facts. In this paper we propose a preference algebra for OLAP, that takes into account the three peculiarities above.
An Efficient Large-Scale Volume Data Compression Algorithm
Authors: Degui Xiao, Liping Zhao, Lei Yang, Zhiyong Li, Kenli Li
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

Considering empty region in the volumetric data occupying a certain percentage, an efficient large-scale data compression algorithm based on VQ is presented. Firstly, the entire volume data are divided into many smaller regular blocks, and the blocks are classified into two groups according to their average gradient values: one consists of those blocks with zero average gradient value, and the other consists of those with non-zero average gradient values. Secondly, only those blocks with non-zero average gradient values are decomposed into a three hierarchical representation and vector quantized. Finally, block data in different groups are reconstructed with different ways. When applying this algorithm to the volume data, all experimental results demonstrate the proposed algorithm is more efficient than most existing large-scale volume data compression algorithms.
A New Semantics for the FIPA Agent Communication Language based on Social Attitudes
Authors: Benoit Gaudou, Andreas Herzig, Dominique Longin, Matthias Nickles
Venue: Proceeding of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy (2006)

One of the most important aspects of the research on agent interaction is the definition of agent communication languages (ACLs), and the specification of a proper formal semantics of such languages is a crucial prerequisite for the usefulness and acceptance of artificial agency. Nevertheless, those ACLs which are still mostly used, especially the standard FIPA-ACL, have a communication act semantics in terms of the participating agents' mental attitudes (viz. beliefs and intentions), which are in general undeterminable from an external point of view due to agent autonomy. In contrast, semantics of ACLs based on commitments are fully verifiable, but not sufficiently formalized and understood yet. In order to overcome this situation, we propose a FIPA-ACL semantics which is fully verifiable, fully formalized, lean and easily applicable. It is based on social attitudes represented using a logic of grounding in straightforward extension of the BDI agent model.
Empty monochromatic triangles
Authors: Oswin Aichholzer, Ruy Fabila-Monroy, David Flores-Peòaloza, Thomas Hackl, Clemens Huemer, Jorge Urrutia
Venue: Computational Geometry: Theory and Applications (2009)

We consider a variation of a problem stated by Erdos and Guy in 1973 about the number of convex k-gons determined by any set S of n points in the plane. In our setting the points of S are colored and we say that a spanned polygon is monochromatic if all its points are colored with the same color. As a main result we show that any bi-colored set of n points in R^2 in general position determines a super-linear number of empty monochromatic triangles, namely @W(n^5^/^4).
XML in Easy Steps, 2nd edition
Authors: Mike McGrath
Venue:  (2007)

XML in Easy Steps is designed for new users who want to quickly get up to speed, from job seekers to programmers to hobbyists. In clear, step-by-step instructions, and with screenshots illustrating every example, it demonstrates the parts of XML that have become popular in today's real-world applications. The book begins with a description of eXtensible Markup Language (XML) along with the associated technologies of Document Type Definition (DTD), XmlSchema Documents (XSD), and the eXtensible Stylesheet Language (XSL). It then illustrates how XML can be used to create Scalable Vector Graphics (SVG), how to access XML data with JavaScript, and how to deploy XML in modern AJAX web applications. At the books end, even the newcomer has a solid understanding of XML and can create well-formed documents and validating schemas.
Impact of weather inputs on heating plant: agglomeration modeling
Authors: Pavel Varacha
Venue: Proceedings of the 10th WSEAS international conference on Neural networks (2009)

This article describes performance of artificial neural network (ANN) on modeling interface between a heating plant and an agglomeration. ANN perform one step ahead prediction of water temperature returned from agglomeration based on input water temperature, flow and atmospheric temperature in past 24 hours. Usage of ANN in two factual heating plant in Komorany and Detmarovice, Czech Republic. Main concern of the article is to explore possibility of tuning ANN accuracy by additional inputs for humidity and wind speed.
A domain decomposition method for two-phase transport model in the cathode of a polymer electrolyte fuel cell
Authors: Pengtao Sun, Guangri Xue, Chao-yang Wang, Jinchao Xu
Venue: Journal of Computational Physics (2009)

Using Kirchhoff transformation, we develop a Dirichlet-Neumann alternating iterative domain decomposition method for a 2D steady-state two-phase model for the cathode of a polymer electrolyte fuel cell (PEFC) which contains a channel and a gas diffusion layer (GDL). This two-phase PEFC model is represented by a nonlinear coupled system which typically includes a modified Navier-Stokes equation with Darcy's drag as an additional source term of the momentum equation, and a convection-diffusion equation for the water concentration with discontinuous and degenerate diffusivity. For both cases of dry and wet gas channel, we employ Kirchhoff transformation and Dirichlet-Neumann alternating iteration with appropriate interfacial conditions on the GDL/channel interface to treat the jump nonlinearities in the water equation. Numerical experiments demonstrate that fast convergence as well as accurate numerical solutions are obtained simultaneously owing to the implementation of the above-described numerical techniques along with a combined finite element-upwind finite volume discretization to automatically control the dominant convection terms arising in the gas channel.
Machine translation system combination using ITG-based alignments
Authors: Damianos Karakos, Jason Eisner, Sanjeev Khudanpur, Markus Dreyer
Venue: Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers (2008)

Given several systems' automatic translations of the same sentence, we show how to combine them into a confusion network, whose various paths represent composite translations that could be considered in a subsequent rescoring step. We build our confusion networks using the method of Rosti et al. (2007), but, instead of forming alignments using the tercom script (Snover et al., 2006), we create alignments that minimize invWER (Leusch et al., 2003), a form of edit distance that permits properly nested block movements of substrings. Oracle experiments with Chinese newswire and weblog translations show that our confusion networks contain paths which are significantly better (in terms of BLEU and TER) than those in tercom-based confusion networks.
On reduced neighborhood mutation analysis using a single mutagenic operator
Authors: Roland H. Untch
Venue: Proceedings of the 47th Annual Southeast Regional Conference (2009)

Mutation analysis evaluates the quality of a test suite based on its ability to reveal simple faults, termed mutations, injected in the program under test. Unfortunately, the need to execute many slightly different versions, or mutants, of a program makes mutation analysis a computationally expensive technique. This paper reports on a promising approach that reduces the cost of mutation analysis by reducing the number of mutants that need to be executed.
Data Mining and Knowledge Discovery Technologies
Authors: David Taniar
Venue:  (2007)

As information technology continues to advance in massive increments, the bank of information available from personal, financial, and business electronic transactions and all other electronic documentation and data storage is growing at an exponential rate. With this wealth of information comes the opportunity and necessity to utilize this information to maintain competitive advantage and process information effectively in real-world situations. Data Mining and Knowledge Discovery Technologies presents researchers and practitioners in fields such as knowledge management, information science, Web engineering, and medical informatics, with comprehensive, innovative research on data mining methods, structures, tools, and methods, the knowledge discovery process, and data marts, among many other cutting-edge topics. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Designing autonomous layered video coders
Authors: Nicholas Mastronarde, Mihaela van der Schaar
Venue: Image Communication (2009)

Layered compression paradigms such as scalable, multiple description, and multi-view video coding, require coupled encoding decisions among layers to achieve optimal distortion performance under buffer constraints. Moreover, due to the dynamic and time-varying source characteristics, and temporal coupling of encoding decisions through the buffer constraints, it is not only necessary to consider the immediate rate-distortion impact of encoding decisions, but also their long-term rate-distortion impact. In other words, optimal encoding decisions must consider the coupling between layers and the coupling across time. In many scenarios, however, it may be impractical to make joint coding decisions for all of the layers. For instance, a two layer bitstream may be coded using different encoders for the base layer and enhancement layer, each with its own autonomous control plane; or, if the same encoder is used for multiple layers, then a joint decision process, which considers the aforementioned dependencies, may be too complex. In this paper, we propose a framework for autonomous decision making in layered video coders, which decouples the decision making processes at the various layers using a novel layered Markov decision process. We illustrate how this framework can be applied to decompose the decision processes for several typical layered video coders with different dependency structures and we observe that the performance of the proposed decomposition highly depends on the ability of the layers to model each other.
Mismatched models, wrong results, and dreadful decisions: on choosing appropriate data mining tools
Authors: David J. Hand
Venue: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining (2009)

Data mining techniques use 'score functions' to quantify how well a model fits a given data set. Parameters are estimated by optimising the fit, as measured by the chosen score function, and model choice is guided by the size of the scores for the different models. Since different score functions summarise the fit in different ways, it is important to choose a function which matches the objectives of the data mining exercise. For predictive classification problems, a wide variety of score functions exist, including measures such as precision and recall, the F measure, misclassification rate, the area under the ROC curve (the AUC), and others. The first four of these require a 'classification threshold' to be chosen, a choice which may not be easy, or may even be impossible, especially when the classification rule is to be applied in the future. In contrast, the AUC does not require the specification of a classification threshold, but summarises performance over the range of possible threshold choices. However, unfortunately, and despite the widespread use of the AUC, it has a previously unrecognised fundamental incoherence lying at the core of its definition. This means that using the AUC can lead to poor model choice and unecessary misclassifications. The AUC is set in context, its deficiency explained and the implications illustrated - with the bottom line being that the AUC should not be used. A family of coherent alternative scores is described. The ideas are illustrated with examples from bank loans, fraud, face recognition, and health screening.
Generalized Cramér-von Mises goodness-of-fit tests for multivariate distributions
Authors: Sung Nok Chiu, Kwong Ip Liu
Venue: Computational Statistics Data Analysis (2009)

A class of statistics for testing the goodness-of-fit for any multivariate continuous distribution is proposed. These statistics consider not only the goodness-of-fit of the joint distribution but also the goodness-of-fit of all marginal distributions, and can be regarded as generalizations of the multivariate Cramer-von Mises statistic. Simulation shows that these generalizations, using the Monte Carlo test procedure to approximate their finite-sample p-values, are more powerful than the multivariate Kolmogorov-Smirnov statistic.
Performance Trade-Offs in Using NVRAM Write Buffer for Flash Memory-Based Storage Devices
Authors: Sooyong Kang, Sungmin Park, Hoyoung Jung, Hyoki Shim, Jaehyuk Cha
Venue: IEEE Transactions on Computers (2009)

While NAND flash memory is used in a variety of end-user devices, it has a few disadvantages, such as asymmetric speed of read and write operations, inability to in-place updates, among others. To overcome these problems, various flash-aware strategies have been suggested in terms of buffer cache, file system, FTL, and others. Also, the recent development of next-generation nonvolatile memory types such as MRAM, FeRAM, and PRAM provide higher commercial value to Non-Volatile RAM (NVRAM). At today's prices, however, they are not yet cost-effective. In this paper, we suggest the utilization of small-sized, next-generation NVRAM as a write buffer to improve the overall performance of NAND flash memory-based storage systems. We propose various block-based NVRAM write buffer management policies and evaluate the performance improvement of NAND flash memory-based storage systems under each policy. Also, we propose a novel write buffer-aware flash translation layer algorithm, optimistic FTL, which is designed to harmonize well with NVRAM write buffers. Simulation results show that the proposed buffer management policies outperform the traditional page-based LRU algorithm and the proposed optimistic FTL outperforms previous log block-based FTL algorithms, such as BAST and FAST.
Introducing an innovative mathematical method to predict the bankruptcy risk: measures for the financial markets stability
Authors: Raileanu Szeles Monica
Venue: Proceedings of the 10th WSEAS international conference on Mathematical and computational methods in science and engineering (2008)

This paper advances innovative measurement models for bankruptcy risk and develops a framework for further research in the use of latent multilevel static and dynamic models in modeling bankruptcy decision making. A brief presentation of literature is given, with an emphasis on the most recent developments in this field. The econometric model underlying the fuzzy sets theory applied to the measurement of bankruptcy risk is particularly examined here. The innovative part of the paper is the application of a new methodology to the analysis of bankruptcy. This model, called Item Response Theory (IRT), is a traditional technique in psychometrics and brings a set of advantages when being applied to the analysis of latent measures by a set of observable binary indicators, as is the bankruptcy risk. At the end, the paper concludes on the need for more collaboration among researchers in business, computer science and low, in order to develop new interdisciplinary measurement tools in finance.
Improved approximation of interactive dynamic influence diagrams using discriminative model updates
Authors: Prashant Doshi, Yifeng Zeng
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

Interactive dynamic influence diagrams (I-DIDs) are graphical models for sequential decision making in uncertain settings shared by other agents. Algorithms for solving I-DIDs face the challenge of an exponentially growing space of candidate models ascribed to other agents, over time. We formalize the concept of a minimal model set, which facilitates qualitative comparisons between different approximation techniques. We then present a new approximation technique that minimizes the space of candidate models by discriminating between model updates. We empirically demonstrate that our approach improves significantly in performance on the previous clustering based approximation technique.
Mining rich session context to improve web search
Authors: Guangyu Zhu, Gilad Mishne
Venue: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining (2009)

User browsing information, particularly their non-search related activity, reveals important contextual information on the preferences and the intent of web users. In this paper, we expand the use of browsing information for web search ranking and other applications, with an emphasis on analyzing individual user sessions for creating aggregate models. In this context, we introduce ClickRank, an efficient, scalable algorithm for estimating web page and web site importance from browsing information. We lay out the theoretical foundation of ClickRank based on an intentional surfer model and analyze its properties. We evaluate its effectiveness for the problem of web search ranking, showing that it contributes significantly to retrieval performance as a novel web search feature. We demonstrate that the results produced by ClickRank for web search ranking are highly competitive with those produced by other approaches, yet achieved at better scalability and substantially lower computational costs. Finally, we discuss novel applications of ClickRank in providing enriched user web search experience, highlighting the usefulness of our approach for non-ranking tasks.
Data reduction for signals observed in colored noise
Authors: Marius-Constantin Popescu, Onisifor Olaru, Nikos E. Mastorakis
Venue: Proceedings of the 10th WSEAS international conference on Automation & information (2009)

This article treats data reduction in array processing for the spatially colored noise case. The purpose is to reduce the computational complexity of the applied signal processing algorithms by mapping the data into a space of lower dimension by means of a linear transformation. We discuss ways to implement the transformation and show that it suffices to estimate the array covariance matrix instead of the noise covariance matrix in the design process of the optimal transformation. Computer simulations are given that illustrate the problem of interference from out-of-band-sources that result when a beamspace transformation is designed to focus on a particular sector.
Functional Fractional Calculus for System Identification and Controls, 1st edition
Authors: Shantanu Das
Venue:  (2007)

When a new extraordinary and outstanding theory is stated, it has to face criticism and skepticism, because it is beyond the usual concept. The fractional calculus though not new, was not discussed or developed for a long time, particularly for lack of its applications to real life problems. It is extraordinary because it does not deal with ordinary differential calculus. It is outstanding because it can now be applied to situations where existing theories fail to give satisfactory results. In this book not only mathematical abstractions are discussed in a lucid manner, but also several practical applications are given particularly for system identification, description and then efficient controls. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Vectorizing Cartoon Animations
Authors: Song-Hai Zhang, Tao Chen, Yi-Fei Zhang, Shi-Min Hu, Ralph R. Martin
Venue: IEEE Transactions on Visualization and Computer Graphics (2009)

We present a system for vectorizing 2D raster format cartoon animations. The output animations are visually flicker free, smaller in file size, and easy to edit. We identify decorative lines separately from colored regions. We use an accurate and semantically meaningful image decomposition algorithm, supporting an arbitrary color model for each region. To ensure temporal coherence in the output, we reconstruct a universal background for all frames and separately extract foreground regions. Simple user-assistance is required to complete the background. Each region and decorative line is vectorized and stored together with their motions from frame to frame. The contributions of this paper are: 1) the new trapped-ball segmentation method, which is fast, supports nonuniformly colored regions, and allows robust region segmentation even in the presence of imperfectly linked region edges, 2) the separate handling of decorative lines as special objects during image decomposition, avoiding results containing multiple short, thin oversegmented regions, and 3) extraction of a single patch-based background for all frames, which provides a basis for consistent, flicker-free animations.