ppxscal/embedding_network huggingface dataset:
A general datalog-based framework for tractable query answering over ontologies
Authors: Andrea Calì, Georg Gottlob, Thomas Lukasiewicz
Venue: Proceedings of the twenty-eighth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems (2009)

In this paper, we introduce a family of expressive extensions of Datalog, called Datalog+/-, as a new paradigm for query answering over ontologies. The Datalog+/- family admits existentially quantified variables in rule heads, and has suitable restrictions to ensure highly efficient ontology querying. We show in particular that Datalog+/- generalizes the DL-Lite family of tractable description logics, which are the most common tractable ontology languages in the context of the Semantic Web and databases. We also show how stratified negation can be added to Datalog+/- while keeping ontology querying tractable. Furthermore, the Datalog+/- family is of interest in its own right and can, moreover, be used in various contexts such as data integration and data exchange.
Processing spatial skyline queries in both vector spaces and spatial network databases
Authors: Mehdi Sharifzadeh, Cyrus Shahabi, Leyla Kazemi
Venue: ACM Transactions on Database Systems (TODS) (2009)

In this article, we first introduce the concept of Spatial Skyline Queries (SSQ). Given a set of data points P and a set of query points Q, each data point has a number of derived spatial attributes each of which is the point's distance to a query point. An SSQ retrieves those points of P which are not dominated by any other point in P considering their derived spatial attributes. The main difference with the regular skyline query is that this spatial domination depends on the location of the query points Q. SSQ has application in several domains such as emergency response and online maps. The main intuition and novelty behind our approaches is that we exploit the geometric properties of the SSQ problem space to avoid the exhaustive examination of all the point pairs in P and Q. Consequently, we reduce the complexity of SSQ search from O(&verbar;P&verbar;2&verbar;Q&verbar;) to O(&verbar;S&verbar;2&verbar;C&verbar; + &sqrt;&verbar;P&verbar;), where &verbar;S&verbar; and &verbar;C&verbar; are the solution size and the number of vertices of the convex hull of Q, respectively. Considering Euclidean distance, we propose two algorithms, B2S2 and VS2, for static query points and one algorithm, VCS2, for streaming Q whose points change location over time (e.g., are mobile). VCS2 exploits the pattern of change in Q to avoid unnecessary recomputation of the skyline and hence efficiently perform updates. We also propose two algorithms, SNS2 and VSNS2, that compute the spatial skyline with respect to the network distance in a spatial network database. Our extensive experiments using real-world datasets verify that both R-tree-based B2S2 and Voronoi-based VS2 outperform the best competitor approach in terms of both processing time and I/O cost. Furthermore, their output computed based on Euclidean distance is a good approximation of the spatial skyline in network space. For accurate computation of spatial skylines in network space, our experiments showed the superiority of VSNS2 over SNS2.
Exploring melodic variance in rhythmic haptic stimulus design
Authors: Bradley A. Swerdfeger, Jennifer Fernquist, Thomas W. Hazelton, Karon E. MacLean
Venue: Proceedings of Graphics Interface 2009 (2009)

Haptic icons are brief, meaningful tactile or force stimuli designed to support the communication of information through the often-underutilized haptic modality. Challenges to producing large, reusable sets of haptic icons include technological constraints and the need for broadly-applicable and validated design heuristics to guide the process. The largest set of haptic stimuli to date was produced through systematic use of heuristics for monotone rhythms. We hypothesized that further extending signal expressivity would continue to enhance icon learnability. Here, we introduce melody into the design of rhythmic stimuli as a means of increasing expressiveness while retaining the principle of systematic design, as guided by music theory. Haptic melodies are evaluated for their perceptual distinctiveness; experimental results from grouping tasks indicate that rhythm dominates user categorization of melodies, with frequency and amplitude potentially left available as new dimensions for the designer to control within-group variation.
Cardiac Fibre Trace Clustering for the Interpretation of the Human Heart Architecture
Authors: Carole Frindel, Marc Robini, Joël Schaerer, Pierre Croisille, Yue-Min Zhu
Venue: Proceedings of the 5th International Conference on Functional Imaging and Modeling of the Heart (2009)

Cardiac fibre architecture plays a key role in heart function. Recently, the estimation of fibre structure has been simplified with diffusion tensor MRI (DT-MRI). In order to assess the heart architecture and its underlying function, with the goal of dealing with pathological tissues and easing inter-patient comparisons, we propose a methodology for finding cardiac myofibrille trace correspondences across a fibre population obtained from DT-MRI data. It relies on the comparison of geometrical and topological clustering operating on different fibre representation modes (fixed length sequences of 3-D coordinates with or without ordering strategy, and 9-D vectors for trace shape approximation). In geometrical clustering (or k-means) each fibre path is assigned to the cluster with nearest barycenter. In topological (or spectral) clustering the data is represented by a similarity graph and the graph vertices are divided into groups so that intra-cluster connectivity is maximized and inter-cluster connectivity is minimized.Using these different clustering methods and fibre representation modes, we predict different fibre trace classifications for the same cardiac dataset. These classification results are compared to the human heart architecture models proposed in the literature.
AMID: Approximation of MultI-measured Data using SVD
Authors: Jun-Ki Min, Chun-Hee Lee, Chin-Wan Chung
Venue: Information Sciences: an International Journal (2009)

Approximate query answering has recently emerged as an effective method for generating a viable answer. Among various techniques for approximate query answering, wavelets have received a lot of attention. However, wavelet techniques minimizing the root squared error (i.e., the L"2 norm error) have several problems such as the poor quality of reconstructed data when the original data is biased. In this paper, we present AMID (Approximation of MultI-measured Data using SVD) for multi-measured data. In AMID, we adapt the singular value decomposition (SVD) to compress multi-measured data. We show that SVD guarantees the root squared error, and also drive an error bound of SVD for an individual data value, using mathematical analyses. In addition, in order to improve the accuracy of approximated data, we combine SVD and wavelets in AMID. Since SVD is applied to a fixed matrix, we use various properties of matrices to adapt SVD to the incremental update environment. We devise two variants of AMID for the incremental update environment: incremental AMID and local AMID. To the best of our knowledge, our work is the first to extend SVD to incremental update environments.
Linear System Properties: A Quick Reference (Controls), 1st edition
Authors: Venkatarama Krishnan
Venue:  (1998)

This pocket book serves as an immediate reference for the various formulae encountered in linear systems, control systems, probability, communication engineering, signal processing, quantum mechanics, and electromagnetic field theory. It includes novel results on complex convolutions; clearly explains real and complex matrix differentiation methods; provides an unusual amount of orthogonal functions; and presents properties of Fourier series, Fourier transforms, Hilbert transforms, Laplace transforms, and z-transforms. Singular value decomposition techniques for matrix inversion are also clearly presented.This new edition adds material from:oOrthogonal functions oLinear algebraoMatrix analysisoMatrix and vector differentiation oSingular value decompositionoState space techniquesOther discussions include:oDiscrete linear and circular convolutionoGram-Schmidt orthogonalization procedureoGraphical derivation of DFT from CFToTruncation windowsoEigenvalues and eigenvectors of matricesThis succint resource will be particularly useful as a supplement to regular texts, designed for the master's or doctoral student as well as the advanced undergraduate.
Experiences in Improving Flight Software Development Processes
Authors: Ronald Kirk Kandt
Venue: IEEE Software (2009)

The Jet Propulsion Laboratory has undergone a software process improvement effort over the past several years. This article describes the software development processes that one project used to satisfy the goals and practices of a leading software process standard. It also identifies the impact of a higher level of software development maturity on the project's software engineering and assurance activities.
Monotonic Variable Consistency Rough Set Approaches
Authors: Jerzy Błaszczyński, Salvatore Greco, Roman Słowiński, Marcin Szelg
Venue: International Journal of Approximate Reasoning (2009)

We consider probabilistic rough set approaches based on different versions of the definition of rough approximation of a set. In these versions, consistency measures are used to control assignment of objects to lower and upper approximations. Inspired by some basic properties of rough sets, we find it reasonable to require from these measures several properties of monotonicity. We consider three types of monotonicity properties: monotonicity with respect to the set of attributes, monotonicity with respect to the set of objects, and monotonicity with respect to the dominance relation. We show that consistency measures used so far in the definition of rough approximation lack some of these monotonicity properties. This observation led us to propose new measures within two kinds of rough set approaches: Variable Consistency Indiscernibility-based Rough Set Approaches (VC-IRSA) and Variable Consistency Dominance-based Rough Set Approaches (VC-DRSA). We investigate properties of these approaches and compare them to previously proposed Variable Precision Rough Set (VPRS) model, Rough Bayesian (RB) model, and previous versions of VC-DRSA.
An Efficient Upper Approximation for Conditional Preference
Authors: Nic Wilson
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)

The fundamental operation of dominance testing, i.e., determining if one alternative is preferred to another, is in general very hard for methods of reasoning with qualitative conditional preferences such as CP-nets and conditional preference theories (CP-theories). It is therefore natural to consider approximations of preference, and upper approximations are of particular interest, since they can be used within a constraint optimisation algorithm to find some of the optimal solutions. Upper approximations for preference in CP-theories have previously been suggested, but they require consistency, as well as strong acyclicity conditions on the variables. We define an upper approximation of conditional preference for which dominance checking is efficient, and which can be applied very generally for CP-theories.
Using fast weights to improve persistent contrastive divergence
Authors: Tijmen Tieleman, Geoffrey Hinton
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

The most commonly used learning algorithm for restricted Boltzmann machines is contrastive divergence which starts a Markov chain at a data point and runs the chain for only a few iterations to get a cheap, low variance estimate of the sufficient statistics under the model. Tieleman (2008) showed that better learning can be achieved by estimating the model's statistics using a small set of persistent "fantasy particles" that are not reinitialized to data points after each weight update. With sufficiently small weight updates, the fantasy particles represent the equilibrium distribution accurately but to explain why the method works with much larger weight updates it is necessary to consider the interaction between the weight updates and the Markov chain. We show that the weight updates force the Markov chain to mix fast, and using this insight we develop an even faster mixing chain that uses an auxiliary set of "fast weights" to implement a temporary overlay on the energy landscape. The fast weights learn rapidly but also decay rapidly and do not contribute to the normal energy landscape that defines the model.
Using relational concept knowledge to improve search in referral networks
Authors: Tony White, Shawn McQuaker, Amirali Salehi Abari
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

The notion of referral networks, as presented in the work of Singh and Yolum, and their application to knowledge management, lacks two fundamental aspects; the relation of concepts within a domain, and the ability of an agent to dynamically change their interests based on suggestions in the form of concept relations. This paper introduces the concept of an oracle agent, which is an agent with relational concept knowledge that can supply suggestions to a querying agent on how to adapt their interests. These new features allow agents to search in new ways so as to achieve superior results and as a consequence outperform agents in a traditional referral network.
Panel on spoken dialog corpus composition and annotation for research
Authors: Giuseppe DiFabbrizio, Dilek Hakkani-Tür, Oliver Lemon, Mazin Gilbert, Alex Rudnicky
Venue: Proceedings of the Workshop on Bridging the Gap: Academic and Industrial Research in Dialog Technologies (2007)

The goal of this forum is to provide researchers from various institutes with the opportunity to comment on a proposed NSF-sponsored data collection plan for a spoken dialog corpus. The corpus is to be used for research in speech recognition, spoken language understanding, dialog management, machine learning, and language generation. Currently, there exists a corpus with over 600 dialog interactions, collected from users using the Discoh system (from the IEEE SLT 2006 workshop) and the Conquest system (from ICSLP 2006) to obtain general information about conference services. These systems were created as part of a joint collaboration between CMU, ATT, Edinburgh and ICSI.
EXEHDA: adaptive middleware for building a pervasive grid environment
Authors: Adenauer Yamin, Iara Augustin, Luciano Cavalheiro da Silva, Rodrigo Araujo Real, Alberto E. Schaeffer Filho, Claudio F. Resin Geyer
Venue: Proceeding of the 2005 conference on Self-Organization and Autonomic Informatics (I) (2005)

We consider that the concept derived of the integration of pervasive, context-aware and grid computing is suitable for building the next generation of the grid applications which assist to nomadic and mobile users. To demonstrate our ideas we have implemented a pilot application, called GeneAl, using the API provided by EXEHDA middleware. EXEHDA is adaptive, service oriented and was conceived to support the execution of pervasive grid applications. The main concept embedded in middleware and application design is the context-awareness expressed by their adaptive behavior. This is also a key to provide functionality adapted to the constraints and unpredictability of the large-scale mobile environment. To achieve this objective, EXEHDA employs a lot of strategies in its services to allow the adaptation to the current state of the execution context, such as on-demand adaptive service loading and dynamic discovery and configuration. The middleware manages and implements the follow-me semantics for pervasive grid applications. In that sense, it provides services for distributed adaptive execution, context recognition, pervasive storage and access, anonymous and asynchronous communications.
Sequential organization of speech in computational auditory scene analysis
Authors: Yang Shao, DeLiang Wang
Venue: Speech Communication (2009)

A human listener has the ability to follow a speaker's voice over time in the presence of other talkers and non-speech interference. This paper proposes a general system for sequential organization of speech based on speaker models. By training a general background model, the proposed system is shown to function well with both interfering talkers and non-speech intrusions. To deal with situations where prior information about specific speakers is not available, a speaker quantization method is employed to extract representative models from a large speaker space and obtained generic models are used to perform sequential grouping. Our systematic evaluations show that grouping performance using generic models is only moderately lower than the performance level achieved with known speaker models.
Smart Business Intelligence Solutions with Microsoft SQL Server 2008
Authors: Lynn Langit, Kevin S. Goff, Davide Mauri, Sahil Malik, John Welch
Venue: Pro-Developer (2009)

Get expert guidance on SQL Server 2008 technologies, processes, and procedures and accelerate your proficiency developing smart, business intelligence solutions. This book provides practical, end-to-end coverage on how to envision, plan, develop, test, and deploy a complete SQL Server 2008-based business intelligence solution. First, you ll build a foundational knowledge of business intelligence systems and components, including case studies of the most common scenarios. Next, you ll work through the physical and logical design of a business intelligence solution, examining SQL Server tools including SQL Server Analysis Services, SQL Server Integration Services, and SQL Server Reporting Services and the problems they solve. Finally, you ll master core reporting and data-mining techniques. Throughout the book, real-world scenarios and examples illustrate essential concepts and demonstrate the most effective ways to implement the platform. The author brings pragmatic perspectives valuable to the range of business intelligence implementers from business decision makers and administrators, to beginning and advanced level developers and architects.
A Robust Video-Based Algorithm for Detecting Snow Movement in Traffic Scenes
Authors: Jun Cai, Mohamed Shehata, Wael Badawy
Venue: Journal of Signal Processing Systems (2009)

Video-based Automatic Incident Detection (AID) systems are widely deployed in many cities for detecting traffic incidents to provide smoother, safer and congestion free traffic flow. However, the accuracy of an AID system operating in an outdoor environment suffers from high false alarm rates due to environmental factors. These factors include snow movement, static shadow and static glare on the roads. In this paper, a robust real-time algorithm is proposed to detect snow movement in video streams to improve the rate of detection. This is done by having the AID system reducing its sensitivity in the areas that have snow movements. The feasibility of the proposed algorithm has been evaluated using traffic videos captured from several cameras at the City of Calgary.
Opinion mining and relationship discovery using CopeOpi opinion analysis system
Authors: Lun-Wei Ku, Hsiu-Wei Ho, Hsin-Hsi Chen
Venue: Journal of the American Society for Information Science and Technology (2009)

We present CopeOpi, an opinion-analysis system, which extracts from the Web opinions about specific targets, summarizes the polarity and strength of these opinions, and tracks opinion variations over time. Objects that yield similar opinion tendencies over a certain time period may be correlated due to the latent causal events. CopeOpi discovers relationships among objects based on their opinion-tracking plots and collocations. Event bursts are detected from the tracking plots, and the strength of opinion relationships is determined by the coverage of these plots. To evaluate opinion mining, we use the NTCIR corpus annotated with opinion information at sentence and document levels. CopeOpi achieves sentence- and document-level f-measures of 62&percnt; and 74&percnt;. For relationship discovery, we collected 1.3M economics-related documents from 93 Web sources over 22 months, and analyzed collocation-based, opinion-based, and hybrid models. We consider as correlated company pairs that demonstrate similar stock-price variations, and selected these as the gold standard for evaluation. Results show that opinion-based and collocation-based models complement each other, and that integrated models perform the best. The top 25, 50, and 100 pairs discovered achieve precision rates of 1, 0.92, and 0.79, respectively. &copy; 2009 Wiley Periodicals, Inc.
Ultrafast Optics
Authors: Andrew Weiner
Venue:  (2009)

A comprehensive treatment of ultrafast optics This book fills the need for a thorough and detailed account of ultrafast optics. Written by one of the most preeminent researchers in the field, it sheds new light on technology that has already had a revolutionary impact on precision frequency metrology, high-speed electrical testing, biomedical imaging, and in revealing the initial steps in chemical reactions. Ultrafast Optics begins with a summary of ultrashort laser pulses and their practical applications in a range of real-world settings. Next, it reviews important background material, including an introduction to Fourier series and Fourier transforms, and goes on to cover: Principles of mode-locking Ultrafast pulse measurement methods Dispersion and dispersion compensation Ultrafast nonlinear optics: second order Ultrafast nonlinear optics: third order Mode-locking: selected advanced topics Manipulation of ultrashort pulses Ultrafast time-resolved spectroscopy Terahertz time-domain electromagnetics Professor Weiner's expertise and cutting-edge research result in a book that is destined to become a seminal text for engineers, researchers, and graduate students alike.
A body-conforming tactile jacket to enrich movie viewing
Authors: Paul Lemmens, Floris Crompvoets, Dirk Brokken, Jack van den Eerenbeemd, Gert-Jan de Vries
Venue: Proceedings of the World Haptics 2009 - Third Joint EuroHaptics conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems (2009)

Adding haptic stimulation to movies is a promising step in creating more emotionally immersive experiences. To explore the potential of this concept, we have created a wearable tactile jacket that is used to deliver movie-specific tactile stimuli to the viewer's body that are specifically targeted to influence the viewer's emotions. Immersion was evaluated in a user test using questionnaires and physiological measurements. The findings show promising effects of the haptic stimuli that need to be substantiated in further more refined user tests.
Adolescents' Use of SRL Behaviors and Their Relation to Qualitative Mental Model Shifts While Using Hypermedia
Authors: Jeffrey A. Greene, Roger Azevedo
Venue: Proceeding of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology (2005)

This study examined 214 adolescents' use of self-regulated learning (SRL) behaviors when learning about the circulatory system using hypermedia for 40 minutes. We examined students' verbal protocols to determine the relationship between SRL behaviors and qualitative shifts in students' mental models from pretest to posttest. Results indicated that students who exhibited a qualitative shift in their mental models pre to posttest displayed differential use of six SRL behaviors. These SRL behaviors included metacognitive monitoring activities and learning strategies. Implications for the design of hypermedia learning environments are presented.