ppxscal/embedding_network huggingface dataset:
Pattern Mining in Discrete Time Series and Application to Music Mining
Authors: Olivier Lartillot
Venue: Proceeding of the 2006 conference on Advances in Intelligent IT: Active Media Technology 2006 (2006)

A new methodology for automated extraction of repeated patterns in discrete time series data is presented, dedicated in particular to the discovery of repeated motives in symbolic music representations, such as MIDI files. The basic principle of the approach consists in a search for closed patterns in a multi-dimensional parametric space. The pattern description is further reduced through a lossless pruning of the sequence description. A notion of cyclic pattern is introduced, enabling an adapted filtering of another form of combinatorial redundancy caused by successive repetitions of patterns. The use of cyclic patterns implies a necessary chronological scanning of the musical sequence. This study shows therefore that automated analysis of music cannot rely on simple mathematical or statistical approaches, but needs rather a complex and detailed modeling of the cognitive system ruling listening processes. The resulting algorithm is able to offer for the first time compact and relevant motivic analyses of simple monodies, and may therefore be applied to automated indexing of symbolic music databases. Numerous additional mechanisms need to be added in order to consider all aspects of music expression, including polyphony and complex musical transformations.
Knowledge Applications for Life Events: How the Dutch Government Informs the Public about Rights and Duties in the Netherlands
Authors: Ronald Heller, Freek Teeseling
Venue: Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications (2009)

The Dutch government has several ontology driven applications on the internet that inform the public about rights and duties that are relevant for certain life events. Life events such as "New to Holland", "The death of a close relative" and "Working and studying" are examples of events in life where you want to be informed about your rights and duties. In the demonstration we show how we make use of an ontology to determine a profile of the user and how we give him or her the information that is tailored to his/her specific situation.
Identifying and proactively managing architecture risk
Authors: William J. Koscho, William Ries
Venue: Proceedings of the 2009 ICSE Workshop on Leadership and Management in Software Architecture (2009)

To help the architect deliver a feasible architecture within given time, cost, and quality constraints, architecture methods such as the ADD, ATAM, QAW, and others have been developed and adopted. The leadership ability of the architect greatly influences the outcome of the application of these methods. We discuss how that leadership ability can be strengthened by leveraging a broad range of risk management techniques, and show how to incorporate a risk-driven architecture management philosophy into mainstream architecture processes. Bringing skills in standardized architecture toolsets, patterns, and methods alone to the table is no longer a significant differentiator for architects. Augmenting these skills with a robust set of risk management practices allows the architect to develop into an organizational leader and add unique and repeatable value in risk- and control-conscious business environments.
Adobe Indesign CS4 Revealed, 1st edition
Authors: Chris Botello
Venue:  (2009)

Graphic design professionals and design students alike are discovering the smart, sophisticated approach of Adobe's page layout software, InDesign; and they're mastering it with Adobe InDesign CS4 Revealed, a thorough overview of the latest release of the software. This highly visual book begins by covering the workspace and other fundamental concepts. Each subsequent chapter delves into new features, offering more in-depth coverage as the book progresses. With new material on the improved interface and features of CS4, this edition retains its step-by-step tutorials and user-friendly design, resulting in a resource that is comprehensive, clear, and effective.
Neural Network Control for a Class of Stochastic Nonlinear Switched System Based on Backstepping
Authors: Sheng Zhang, Fei Long
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

In this paper, we deal with the switched stabilization problem for a class of stochastic switched nonlinear systems based on RBF neural network and backstepping approach. By using the combination design technique of backstepping and neural network, an adaptive neural network switching controller is designed for the switched stabilization of stochastic switched nonlinear system with trigonal structure. It is shown that, under Stochastic Lasalle Theorem, the resulting closed-loop system is proved to be globally asymptotically stable in probability.
Supervised Machine Learning: A Review of Classification Techniques
Authors: S. B. Kotsiantis
Venue: Proceeding of the 2007 conference on Emerging Artificial Intelligence Applications in Computer Engineering: Real Word AI Systems with Applications in eHealth, HCI, Information Retrieval and Pervasive Technologies (2007)

The goal of supervised learning is to build a concise model of the distribution of class labels in terms of predictor features. The resulting classifier is then used to assign class labels to the testing instances where the values of the predictor features are known, but the value of the class label is unknown. This paper describes various supervised machine learning classification techniques. Of course, a single chapter cannot be a complete review of all supervised machine learning classification algorithms (also known induction classification algorithms), yet we hope that the references cited will cover the major theoretical issues, guiding the researcher in interesting research directions and suggesting possible bias combinations that have yet to be explored.
Plenary lecture 6: on Devaney's definition of chaos for discontinuous dynamical systems
Authors: Byungik Kahng
Venue: Proceedings of the 15th american conference on Applied mathematics (2009)

Probably the most widely accepted definition of chaos is the one by Devaney, which we will call Devaney-chaos. It consists of three conditions, (1) the sensitive dependence upon the initial condition, (2) the topological transitivity, and (3) the dense distribution of the periodic orbits. The third condition is often omitted for being too stringent. The purpose of our research is to investigate how the first two characteristic properties of Devaney-chaos are affected by the presence of the discontinuity. Devaney-chaos is more inclusive than most of the competing notions of chaos, especially when the dynamics includes singularity. Recent discoveries by Goetz and Buzzi on the discontinuous dynamical systems include that the piecewise isometric dynamical systems, which are partly inspired by the digital signal processing and Hamiltonian dynamics, can generate complicated orbit structure, even though their Lyapunov-exponents and topological entropies are 0. Consequently, neither Lyapunov-chaos nor topological chaos can be applied to explain the complex behavior of the piecewise isometric dynamics. Goetz also proved that Smale-chaos fails to apply as well. Devaney-chaos, on the other hand, proved to be a useful tool, at least for some special cases, as exemplified by some of the author's earlier contributions. We prove that Devaney-chaos can be used to successfully characterize the chaos that are generated by the discontinuity in general, if appropriate adjustments are made. Also, we show that the straightforward application of Devaney's conditions is too inclusive, when the system is discontinuous, consequently necessitating the aforementioned adjustments.
Technological Innovation and Acquisitions
Authors: Xinlei Zhao
Venue: Management Science (2009)

I examine whether technological innovation is a motivating factor in firms' acquisition decisions and how an acquisition (or an acquisition withdrawal) affects technological innovation in subsequent years. I find that firms engaging in acquisition activities are less innovative and have often experienced declines in technological innovation during the years prior to the bid. Among the bidders, the relatively more innovative ones are less likely to complete a deal. During the three years after the bid, successful bidders do not underperform matching firms, whereas failed bidders significantly underperform their nonbidding peers. I further find that formerly less innovative bidders benefit more from acquisitions. These findings suggest that technological innovation affects firms' acquisition decisions, and in turn, acquisitions help firms' innovation efforts.
Microsoft Visual C# 2008 Comprehensive: An Introduction to Object-Oriented Programming, 1st edition
Authors: Joyce Farrell
Venue:  (2009)

Microsoft Visual C# Comprehensive is an expanded version of Microsoft Visual C# 2008: An Introduction to Object-Oriented Programming with five NEW chapters, for a more complete C# course! The Comprehensive text builds on the established pedagogy of Microsoft Visual C# 2008: An Introduction to Object-Oriented Programming, adding topics to provide a thorough foundation in C# suitable for a two-semester or three-quarter course sequence. After presenting thorough coverage of object-oriented programming fundamentals in general, and C# programming fundamentals in particular, this book delves into topics such as multithreading, XAML, The Windows Presentation Foundation, and dynamic data structures.
Optimization-Based Peptide Mass Fingerprinting for Protein Mixture Identification
Authors: Zengyou He, Chao Yang, Can Yang, Robert Z. Qi, Jason Po-Ming Tam, Weichuan Yu
Venue: Proceedings of the 13th Annual International Conference on Research in Computational Molecular Biology (2009)

In current proteome research, the most widely used method for protein mixture identification is probably peptide sequencing. Peptide sequencing is based on tandem Mass Spectrometry (MS/MS) data. The disadvantage is that MS/MS data only sequences a limited number of peptides and leaves many more peptides uncovered.Peptide Mass Fingerprinting (PMF) has been widely used to identify single purified proteins from single-stage MS data. Unfortunately, this technique is less accurate than the peptide sequencing method and can not handle protein mixtures, which hampers the widespread use of PMF.In this paper, we tackle the problem of protein mixture identification from an optimization point of view. We show that some simple heuristics can find good solutions to the optimization problem. As a result, we obtain much better identification results than previous methods. Through a comprehensive simulation study, we identify a set of limiting factors that hinder the performance of PMF-based protein mixture identification. We argue that it is feasible to remove these limitations and PMF can be a powerful tool in the analysis of protein mixtures, especially in the identification of low-abundance proteins which are less likely to be sequenced by MS/MS scanning.Availability: The source codes, data and supplementary documents are available at http://bioinformatics.ust.hk/PMFMixture.rar
A Topic-Independent Method for Automatically Scoring Essay Content Rivaling Topic-Dependent Methods
Authors: Ryo Nagata, Junichi Kakegawa, Yukiko Yabuta
Venue: Proceedings of the 2009 Ninth IEEE International Conference on Advanced Learning Technologies (2009)

This paper proposes a topic-independent method for automatically scoring essay content. Unlike conventional topic-dependent methods, it predicts the human score of a given essay without training essays written to the same topic as the target essay. To achieve this, this paper introduces a new measure called MIDF that measures how important and relevant a word is in a given essay. The proposed method predicts the score relying on the distribution of MIDF. Surprisingly, experiments show that the proposed method achieves an accuracy of 0.848 and performs as well as or even better than conventional topic-dependent methods.
An exactly conservative particle method for one dimensional scalar conservation laws
Authors: Yossi Farjoun, Benjamin Seibold
Venue: Journal of Computational Physics (2009)

A particle scheme for scalar conservation laws in one space dimension is presented. Particles representing the solution are moved according to their characteristic velocities. Particle interaction is resolved locally, satisfying exact conservation of area. Shocks stay sharp and propagate at correct speeds, while rarefaction waves are created where appropriate. The method is variation diminishing, entropy decreasing, exactly conservative, and has no numerical dissipation away from shocks. Solutions, including the location of shocks, are approximated with second order accuracy. Source terms can be included. The method is compared to CLAWPACK in various examples, and found to yield a comparable or better accuracy for similar resolutions.
An Analysis of Bayesian Network Model-Approximation Techniques
Authors: Adamo Santana, Gregory Provan
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

Two approaches have been used to perform approximate inference in Bayesian networks for which exact inference is infeasible: employing an approximation algorithm, or approximating the structure. In this article we compare two structure-approximation techniques, edge-deletion and approximate structure learning based on sub-sampling, in terms of relative accuracy and computational efficiency. Our empirical results indicate that edge-deletion techniques dominate the subsampling/induction strategy, in both accuracy and performance of generating the approximate network. We show, for several large Bayesian networks, how edge-deletion can create approximate networks with order-of-magnitude inference speedups and relatively little loss of accuracy.
Comparisons between an exact and a metaheuristic algorithm for the molecular distance geometry problem
Authors: Antonio Mucherino, Leo Liberti, Carlile Lavor, Nelson Maculan
Venue: Proceedings of the 11th Annual conference on Genetic and evolutionary computation (2009)

We consider the Discretizable Molecular Distance Geometry Problem (DMDGP), which consists in a subclass of instances of the distance geometry problem related to molecular conformations for which a combinatorial reformulation can be supplied. We investigate the performances of two different algorithms for solving the DMDGP. The first one is the Branch and Prune (BP) algorithm, an exact algorithm that is strongly based on the structure of the combinatorial problem. The second one is the Monkey Search (MS) algorithm, a meta-heuristic algorithm that is inspired by the behavior of a monkey climbing trees in search for food supplies, and that exploits ideas and strategies from other meta-heuristic searches, such Genetic Algorithms, Differential Evolution, and so on. The comparison between the two algorithms is performed on a set of instances related to protein conformations. The used instances simulate data obtained from the Nuclear Magnetic Resonance (NMR), because the typical distances provided by NMR are considered and a predetermined number of wrong distances are included.
Keynote lecture 2: cardiovascular informatics: how to stop a heart attack before it happens
Authors: Ioannis A. Kakadiaris
Venue: Proceedings of the international conference on Computational and information science 2009 (2009)

In this talk, first I will offer a short overview of the research activities of the Computational Biomedicine Laboratory, University of Houston. Then, I will present our research in the area of biomedical image computing for the mining of information from cardiovascular imaging data for the detection of persons with a high likelihood of developing a heart attack in the near future (vulnerable patients). Specifically, I'll present methods for detection and segmentation of anatomical structures, and shape and motion estimation of dynamic organs. The left ventricle in non-invasive cardiac MRI data is extracted using a novel multi-class, multi-feature fuzzy connectedness method and deformable models for shape and volume estimation. In non-invasive cardiac CT data, the thoracic fat is detected using a relaxed version of multi-class, multi-feature fuzzy connectedness method. Additionally, the calcified lesions in the coronary arteries are also identified and quantified using a novel hierarchical supervised learning framework from the CT data. In non-invasive contrast-enhanced CT, the coronary arteries are detected using our novel tubular shape detection method for motion estimation and possibly, for non-calcified lesion detection. In invasive IVUS imaging, our team has developed a unique IVUS acquisition protocol and novel signal/image analysis methods) for the detection (for the first time in vivo) of 'vasa vasorum' (VV). The VV are micro-vessels that are commonly present to feed the walls of larger vessels; however, recent clinical evidence has uncovered their tendency to proliferate around areas of inflammation, including the inflammation associated with vulnerable plaques. In summary, our work is focused on developing novel computational tools to mine quantitative parameters from the imaging data for early detection of asymptomatic cardiovascular patient. The expected impact of our work stems from the fact that sudden heart attack remains the number one cause of death in the US, and unpredicted heart attacks account for the majority of the $280 billion burden of cardiovascular diseases.
Newton-Cotes cubature rules over (d+1)-pencil lattices
Authors: Jernej Kozak, Vito Vitrih
Venue: Journal of Computational and Applied Mathematics (2009)

In this paper, Newton-Cotes cubature rules are extended to (d+1)-pencil lattices over simplices and simplicial partitions. The closed form of the cubature rules as well as the error term are determined. Further, the basic cubature rules can be combined with an adaptive algorithm over simplicial partitions. The key point of the algorithm is a subdivision step that refines a (d+1)-pencil lattice over a simplex to its subsimplices. If the number of function evaluations is crucial, the additional freedom provided by (d+1)-pencil lattices may be used to decrease it significantly.
Designing wiimprovisation for mediation in group music therapy with children suffering from behavioral disorders
Authors: Samuel Benveniste, Pierre Jouvelot, Edith Lecourt, Renaud Michel
Venue: Proceedings of the 8th International Conference on Interaction Design and Children (2009)

We present qualitative experimental evidence that the "Wiimprovisation" process of using Nintendo Wiimotes as virtual instruments linked to a musical sound system within the framework of Group Music Therapy sessions can provide effective psychodynamic mediation for patients. We designed and implemented specific modalities for movement-based sound control and tested our tool in two clinical settings with children (age 7 to 12) suffering from behavioral disorders. Our preliminary results show immediate acceptance of, long term motivation for and meaningful expression through our system by patients. Future work will focus on assessing the therapeutic potential of our platform's personalization features in a controlled experiment.
Maintaining and evolving GUI-directed test scripts
Authors: Mark Grechanik, Qing Xie, Chen Fu
Venue: Proceedings of the 2009 IEEE 31st International Conference on Software Engineering (2009)

Since manual black-box testing of GUI-based APplications (GAPs) is tedious and laborious, test engineers create test scripts to automate the testing process. These test scripts interact with GAPs by performing actions on their GUI objects. An extra effort that test engineers put in writing test scripts is paid off when these scripts are run repeatedly. Unfortunately, releasing new versions of GAPs with modified GUIs breaks their corresponding test scripts thereby obliterating benefits of test automation. We offer a novel approach for maintaining and evolving test scripts so that they can test new versions of their respective GAPs. We built a tool to implement our approach, and we conducted a case study with forty five professional programmers and test engineers to evaluate this tool. The results show with strong statistical significance that users find more failures and report fewer false positives (p ≪ 0.02) in test scripts with our tool than with a flagship industry product and a baseline manual approach. Our tool is lightweight and it takes less than eight seconds to analyze approximately 1KLOC of test scripts.
Understanding community: the implications of information flow and social interactions in online discussion groups
Authors: Karen E. Fisher
Venue:  (2008)

An increasingly difficult challenge that users of online communities face is how to assess the quality and trustworthiness of content generated by strangers. This is especially true in help and support question-answer newsgroups where little information is displayed in the interface to show an authors' status or reputation within a group or their past behavior in online discussion environments in general. Moreover, different users of online discussion groups behave and interact with information in differing ways. This dissertation investigates the behaviors that are manifested through various social types when they interact with others in online discussion groups. Mixed methods were employed to ensure the rigor of the research, including (1) segmentation of newsgroup posting behavior by aggregate newsgroups and authors; (2) focus groups with key informants to explore how social norms and the collective worldviews of newsgroup participants shape the ways different social types behave; and (3) a survey addressed to a general population of newsgroup users to gain an understanding of how various social types view their own information behavior and that of others.This dissertation uses the theory of normative behavior (Chatman 2000) to address the concepts of worldviews (shared understanding of the small world), social norms (what is perceived to be right or wrong in the group), social types (generalized classification of a person or persons) and information behaviors (how a person acts upon given information) exhibited by members of Usenet newsgroups. Implications are suggested for academics seeking a framework for studying online discussion groups, system designers needing advice on how to set up a user community, end users looking for clues on how to decipher and judge information that is being shared, content creators wanting ways to synthesize and preserve important content, and community managers desiring to know how various social types interact with information in order to maximize the experience for the users and the understanding for an organization.