ppxscal/embedding_network huggingface dataset:
Programming C# 3.0, 5th edition
Authors: Jesse Liberty, Donald Xie
Venue:  (2008)

Written by popular author and .NET expert Jesse Liberty, this thoroughly updated tutorial for beginning to intermediate programmers covers the latest release of Microsoft's popular C# language (C# 3.0) and the newest .NET platform for developing Windows and web applications. Our bestselling Programming C# 3.0, now in its fifth edition, is a world-class tutorial that goes well beyond the documentation otherwise available. Liberty doesn't just teach C#; he tells the complete story of the C# language and how it integrates with all of .NET programming, so that you can get started creating professional quality web and Windows applications. This book: Provides a comprehensive tutorial in C# and .NET programming that also serves as a useful reference you'll want by your side while you're working Covers all of the new features of the language, thoroughly integrated into every chapter, rather than tacked on at the end Provides insight into best practices and insight into real world programming by a professional programmer who worked with C# as an independent contractor for nearly a decade before joining Microsoft as a Senior Program Manager Every chapter in this book has been totally revised, and the entire book has been reorganized to respond to the significant changes in the language Full coverage, from the ground up of LINQ (Language Integrated Query) and other C# 3.0 language innovations to speed up development tasks Explains how to use C# in creating Web Applications as well as Windows Applications, using both the new Windows Presentation Foundation (WPF) and the older WinForms technology This new edition of Programming C# 3.0 is for working programmers who want to develop proficiency inMicrosoft's most important language. No prior .NET experience is required for you to get started. There's no time like the present to work with C# -- and no book like this one to teach you everything you need to know. Special note to VB6 and Java programmers: if you've decided to transition to .NET, this book will take you there.
Importance weighted active learning
Authors: Alina Beygelzimer, Sanjoy Dasgupta, John Langford
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

We present a practical and statistically consistent scheme for actively learning binary classifiers under general loss functions. Our algorithm uses importance weighting to correct sampling bias, and by controlling the variance, we are able to give rigorous label complexity bounds for the learning process.
Combined projection and kernel basis functions for classification in evolutionary neural networks
Authors: P. A. Gutiérrez, C. Hervás, M. Carbonero, J. C. Fernández
Venue: Neurocomputing (2009)

This paper proposes a hybrid neural network model using a possible combination of different transfer projection functions (sigmoidal unit, SU, product unit, PU) and kernel functions (radial basis function, RBF) in the hidden layer of a feed-forward neural network. An evolutionary algorithm is adapted to this model and applied for learning the architecture, weights and node typology. Three different combined basis function models are proposed with all the different pairs that can be obtained with SU, PU and RBF nodes: product-sigmoidal unit (PSU) neural networks, product-radial basis function (PRBF) neural networks, and sigmoidal-radial basis function (SRBF) neural networks; and these are compared to the corresponding pure models: product unit neural network (PUNN), multilayer perceptron (MLP) and the RBF neural network. The proposals are tested using ten benchmark classification problems from well known machine learning problems. Combined functions using projection and kernel functions are found to be better than pure basis functions for the task of classification in several datasets.
Application Scenarios of Ontology-Driven Situation Awareness SystemsExemplified for the Road Traffic Management Domain
Authors: Norbert Baumgartner, Werner Retschitzegger, Wieland Schwinger
Venue: Proceeding of the 2008 conference on Formal Ontologies Meet Industry (2008)

Large-scale control systems, as encountered in the domain of road traffic management, typically deal with highly-dynamic environments providing information about a large number of real-world objects, which stem from multiple heterogeneous sources and are anchored in time and space. Human operators of such systems face information overload which endangers the recognition of critical situations. Situation awareness systems should support operators fulfilling their tasks by leveraging their awareness of the ongoing situations. However, current approaches to SAW miss a common conceptual model necessary for various aspects of SAW. Although the application of ontologies for filling this gap has been proposed in recent years, ontology-driven SAW systems are nevertheless still in their infancy. In this paper, we shape the vision of an ontology-driven SAW system by the analysis of application scenarios facilitating the features of formal ontologies. We illustrate the suggested scenarios with examples from the field of road traffic management and argue that an ontology-driven SAW system does not replace but may actually enhance traditional probabilistic approaches to SAW.
The evaluation of cluster policy by fuzzy MCDM: Empirical evidence from HsinChu Science Park
Authors: Chia-Chi Sun, Grace T. R. Lin, Gwo-Hshiung Tzeng
Venue: Expert Systems with Applications: An International Journal (2009)

In the recent years, industrial clusters have received considerable attention from economists and industrial analysts, because they are seen as the main reason for economic growth and success of certain economic region. This study systematically reviews past researches of industrial cluster. The purpose of this paper is to contribute to the understanding of this issue regarding the driving forces for the growth of industrial cluster and find out the priority among these cluster policies. Taiwan HsinChu Science Park is a prime example for this paper, and its connection with the innovative participators. We begin with an examination of the literature on cluster about its driving forces and policies upon which we propose a conceptual framework. In doing so, we explore the cluster-based industrial system. Then this research adopts the Fuzzy Analytic Hierarchy Process as the analytical tool. The Fuzzy Analytic Hierarchy Process method is used to determine the weightings for evaluation dimension among decision makers. From our research results, the Factor Conditions is the most important driving force for advancing the industrial cluster performance. Moreover, the promotion of international linkages policy and broader framework policies rank the first two priorities for cluster policy. Overall, this paper concludes with some simulations of cluster policy alternatives confronting the industry and the Taiwanese government.
Fewer permutations, more accurate P-values
Authors: Theo A. Knijnenburg, Lodewyk F. A. Wessels, Marcel J. T. Reinders, Ilya Shmulevich
Venue: Bioinformatics (2009)

Motivation: Permutation tests have become a standard tool to assess the statistical significance of an event under investigation. The statistical significance, as expressed in a P-value, is calculated as the fraction of permutation values that are at least as extreme as the original statistic, which was derived from non-permuted data. This empirical method directly couples both the minimal obtainable P-value and the resolution of the P-value to the number of permutations. Thereby, it imposes upon itself the need for a very large number of permutations when small P-values are to be accurately estimated. This is computationally expensive and often infeasible. Results: A method of computing P-values based on tail approximation is presented. The tail of the distribution of permutation values is approximated by a generalized Pareto distribution. A good fit and thus accurate P-value estimates can be obtained with a drastically reduced number of permutations when compared with the standard empirical way of computing P-values. Availability: The Matlab code can be obtained from the corresponding author on request. Contact: tknijnenburg@systemsbiology.org Supplementary information: Supplementary data are available at Bioinformatics online.
New Possibilities with Sobolev Active Contours
Authors: Ganesh Sundaramoorthi, Anthony Yezzi, Andrea C. Mennucci, Guillermo Sapiro
Venue: International Journal of Computer Vision (2009)

Recently, the Sobolev metric was introduced to define gradient flows of various geometric active contour energies. It was shown that the Sobolev metric outperforms the traditional metric for the same energy in many cases such as for tracking where the coarse scale changes of the contour are important. Some interesting properties of Sobolev gradient flows include that they stabilize certain unstable traditional flows, and the order of the evolution PDEs are reduced when compared with traditional gradient flows of the same energies. In this paper, we explore new possibilities for active contours made possible by Sobolev metrics. The Sobolev method allows one to implement new energy-based active contour models that were not otherwise considered because the traditional minimizing method render them ill-posed or numerically infeasible. In particular, we exploit the stabilizing and the order reducing properties of Sobolev gradients to implement the gradient descent of these new energies. We give examples of this class of energies, which include some simple geometric priors and new edge-based energies. We also show that these energies can be quite useful for segmentation and tracking. We also show that the gradient flows using the traditional metric are either ill-posed or numerically difficult to implement, and then show that the flows can be implemented in a stable and numerically feasible manner using the Sobolev gradient.
Modelling Search Strategies in Rules2CP
Authors: François Fages, Julien Martin
Venue: Proceedings of the 6th International Conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems (2009)

In this abstract, we present a rule-based modelling language for constraint programming, called Rules2CP [1], and a library PKML for modelling packing problems. Unlike other modelling languages, Rules2CP adopts a single knowledge representation paradigm based on logical rules without recursion, and a restricted set of data structures based on records and enumerated lists given with iterators. We show that this is sufficient to model constraint satisfaction problems together with search strategies, where search trees are expressed by logical formulae, and heuristic choice criteria are defined by preference orderings on variables and formulae. Rules2CP statements are compiled to constraint programs over finite domains (currently SICStus-prolog and soon Choco-Java) by term rewriting and partial evaluation.
Compositional noisy-logical learning
Authors: Alan Yuille, Songfeng Zheng
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

We describe a new method for learning the conditional probability distribution of a binary-valued variable from labelled training examples. Our proposed Compositional Noisy-Logical Learning (CNLL) approach learns a noisy-logical distribution in a compositional manner. CNLL is an alternative to the well-known AdaBoost algorithm which performs coordinate descent on an alternative error measure. We describe two CNLL algorithms and test their performance compared to AdaBoost on two types of problem: (i) noisy-logical data (such as noisy exclusive-or), and (ii) four standard datasets from the UCI repository. Our results show that we outperform AdaBoost while using significantly fewer weak classifiers, thereby giving a more transparent classifier suitable for knowledge extraction.
A Human Activity Aware Learning Mobile Music Player
Authors: Sandor Dornbush, Anupam Joshi, Zary Segall, Tim Oates
Venue: Proceeding of the 2007 conference on Advances in Ambient Intelligence (2007)

The XPod system aims to integrate awareness of human activity and multimedia preferences to produce an adaptive system that plays contextually appropriate media. The XPod project introduces a “smart” music player that learns its user's preferences and activity, and tailors its music selections accordingly. We have experimented with various physiological sensing platforms to measure a user's physiological state. These devices are able to monitor a number of variables to determine the user's levels of activity and motion to predict what music is appropriate at that time. The XPod user trains the player to understand what music is preferred and under what conditions. After training, XPod can predict the desirability of a song given the user's physical state. XPod learns a users listening preferences from the interaction with the user and from collaborative filtering
Temporal Logic Patterns for Querying Qualitative Models of Genetic Regulatory Networks
Authors: Pedro T. Monteiro, Delphine Ropers, Radu Mateescu, Ana T. Freitas, Hidde de Jong
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

Formal verification based on model checking provides a powerful technology to query qualitative models of dynamical systems. The application of model-checking approaches is hampered, however, by the difficulty for non-expert users to formulate appropriate questions in temporal logic. In order to deal with this problem, we propose the use of patterns, that is, high-level query templates capturing recurring questions which can be automatically translated to temporal logic. We develop a set of patterns for the analysis of qualitative models of genetic regulatory networks, which are sufficiently generic though to be useful in other application domains. The applicability of the patterns has been investigated by the analysis of a model of the network of global regulators controlling the carbon starvation response in Escherichia coli.
Adapting service requests to actual service interfaces through semantic annotations
Authors: Luca Cavallaro, Gianluca Ripa, Maurilio Zuccala
Venue: Proceedings of the 2009 ICSE Workshop on Principles of Engineering Service Oriented Systems (2009)

In a previous work we presented an approach to allow invocation of services whose interface and behavior differ from each other. Such approach requires the definition of scripts by some human being able to completely understand the mismatches and properly combine the mapping functions. Furthermore, such approach requires an intensive effort from a system integrator that, in the worst case in which a client can be bound to N different services, could be requested to specify N adapters for each client. In this paper we describe an approach that aims at solving these problems by exploiting semantic annotations of service interfaces and domain ontologies. Our approach extends the previous work and enables the automation of the definition of the adapting scripts.
An experimental investigation of model-based parameter optimisation: SPO and beyond
Authors: Frank Hutter, Holger H. Hoos, Kevin Leyton-Brown, Kevin P. Murphy
Venue: Proceedings of the 11th Annual conference on Genetic and evolutionary computation (2009)

This work experimentally investigates model-based approaches for optimising the performance of parameterised randomised algorithms. We restrict our attention to procedures based on Gaussian process models, the most widely-studied family of models for this problem. We evaluated two approaches from the literature, and found that sequential parameter optimisation (SPO) [4] offered the most robust performance. We then investigated key design decisions within the SPO paradigm, characterising the performance consequences of each. Based on these findings, we propose a new version of SPO, dubbed SPO+, which extends SPO with a novel intensification procedure and log-transformed response values. Finally, in a domain for which performance results for other (model-free) parameter optimisation approaches are available, we demonstrate that SPO+ achieves state-of-the-art performance.
Product Family Design Based on Real Options Valuation
Authors: Jianxin (Roger) Jiao, Ching Moi Lim, Arun Kumar
Venue: Proceeding of the 2006 conference on Leading the Web in Concurrent Engineering: Next Generation Concurrent Engineering (2006)

This paper discusses a real options approach to product family design (PFD), in which PFD is modeled as an investment strategy being crafted by a series of real options that are continuously exercised to achieve expected returns on investment. An application of the real options framework to a vibration motor manufacturer is reported.
PCHM: A bioinformatic resource for high-throughput human mitochondrial proteome searching and comparison
Authors: Taeho Kim, Euiyong Kim, Seok-Ju Park, Hyun Joo
Venue: Computers in Biology and Medicine (2009)

Mitochondrial proteins associated with a wide spectrum of human diseases and currently large amounts of tissue or organ specific human mitochondrial proteome datasets are generated. However, high-throughput comparative proteomic methods have yet to be applied to extract subtle differences among mitochondria from different tissues or muscle types. The aim of this work was to provide an integrated way to identify and compare huge mitochondrial protein or peptide mass spectral data sets acquired from expert mitochondrial proteome or biomarker discovery community. Proteome comparison of human mitochondria (PCHM) is a web-based analysis environment for manual or automatic analysis of individual peptide mass fingerprints alongside a database of proteins and peptides identified in various organs for human mitochondrial proteins. PCHM provides a suite of graphical tools that allow the virtual plot of peptide mass fingerprinting (PMF) spectra and a fully automatic protein function classification based on gene ontology (GO) annotation system. The new virtual PMF plot is very useful to validate fragmented ion loses of any identical proteins and to remove unwanted foreign ion peaks. Fully automatic protein function classifier provides an easier way to compare the subtle differences of compositionally biased mitochondrial protein functions. PCHM also provides a variety of query algorithms aid in browsing, searching, and accessing complete annotations of data relevant to each mitochondrial protein of interest, which link external databases and users. PCHM will be a useful tool for the systematic and functional characterization of the mitochondrial proteins in relation to human diseases or biological research applications. PCHM can be accessed freely via a web interface http://pchm.inje.ac.kr.
MASQ: towards an integral approach to interaction
Authors: Tiberiu Stratulat, Jacques Ferber, John Tranier
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

In this paper we describe MASQ (Multi-Agent Systems based on Quadrants), a model that defines four perspectives over an agent-based interaction according to two axes: internal/external and individual/collective. With MASQ, we mainly show how to integrate the essential elements that intervene in the description of the interaction process such as agents, environments, organizations and institutions. We also discuss some methodological aspects of such an approach and show that it is possible to apply it to build practical models.
Analyzing Receiver Operating Characteristic Curves With SAS, 1st edition
Authors: Mithat Gonen
Venue:  (2007)

As a diagnostic decision-making tool, receiver operating characteristic (ROC) curves provide a comprehensive and visually attractive way to summarize the accuracy of predictions. They are extensively used in medical diagnosis and increasingly in fields such as data mining, credit scoring, weather forecasting, and psychometry. In this example-driven book, author Mithat Gnen illustrates the many existing SAS procedures that can be tailored to produce ROC curves and expands upon further analyses using other SAS procedures and macros. Both parametric and nonparametric methods for analyzing ROC curves are covered in detail. Topics addressed include: Appropriate methods for binary, ordinal, and continuous measures Computations using PROC FREQ, PROC LOGISTIC, PROC NLMIXED, and macros Comparing the ROC curves of several markers and adjusting them for covariates ROC curves with censored data Using the ROC curve for evaluating multivariable prediction models via bootstrap and cross-validation ROC curves in SAS Enterprise Miner And more! Written for any statistician interested in learning more about ROC curve methodology, the book assumes readers have a basic understanding of regression procedures and moderate familiarity with Base SAS and SAS/STAT. Some familiarity with SAS/GRAPH is helpful but not essential.
WiMap: Fast handover for 802.11 mobile devices
Authors: A. Kulkarni, S. Menezes, H. Vu, C. Liyana Arachchige
Venue: Proceedings of the 2008 International Symposium on a World of Wireless, Mobile and Multimedia Networks (2008)

Low latency handover is desired to support real time applications, such as VoIP. We introduce WiMap, a new handover scheme that uses past information of handovers. Through our analysis and simulation, we show that WiMap performs 50% faster than traditional handover solutions. WiMap does not require modifications to the Access Points or WLAN infrastructure and thus can be efficiently implemented.
Tool support for automating architectural knowledge extraction
Authors: Aman-ul-haq, Muhammad Ali Babar
Venue: Proceedings of the 2009 ICSE Workshop on Sharing and Reusing Architectural Knowledge (2009)

Development of large projects is a knowledge intensive task. Applying knowledge management techniques to project activities can enhance productivity and reduce risks of failures. However, it has been observed that knowledge management activities suffer from problems such as unavailability of structured information and lack of incentives to put extra efforts for these activities. In this paper, we present a tool that captures architectural knowledge from documents and emails and stores it in more structured manner in knowledge repositories with minimum user intervention, thus minimizing the required amount of effort.
A 3D Vector-Additive Iterative Solver for the Anisotropic Inhomogeneous Poisson Equation in the Forward EEG problem
Authors: Vasily Volkov, Aleksei Zherdetsky, Sergei Turovets, Allen Malony
Venue: Proceedings of the 9th International Conference on Computational Science: Part I (2009)

We describe a novel 3D finite difference method for solving the anisotropic inhomogeneous Poisson equation based on a multi-component additive implicit method with a 13-point stencil. The serial performance is found to be comparable to the most efficient solvers from the family of preconditioned conjugate gradient (PCG) algorithms. The proposed multi-component additive algorithm is unconditionally stable in 3D and amenable for transparent domain decomposition parallelization up to one eighth of the total grid points in the initial computational domain. Some validation and numerical examples are given. 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