ppxscal/embedding_network huggingface dataset:
The Influence of Cognitive and Personality Characteristics on User Navigation: An Empirical Study
Authors: Nikola Marangunić, Andrina Granić
Venue: Proceedings of the 5th International Conference on Universal Access in Human-Computer Interaction. Part III: Applications and Services (2009)

An empirical study aiming to investigate the influence of cognitive and personality characteristics on user web navigation is presented in this paper. Individual cognitive abilities and personality dimensions were identified and validated, and expected correlations with results of objective variables were postulated. Effectiveness, efficiency and orientation within a web site were the measured objective variables. Measures of spatial ability and extraversion were correlated with objective accomplishment measures and orientation. A high statistically significant correlation was found between spatial ability measure and orientation measure. Conversely, no other correlations were supported. Future work will be significantly improved by employing new variables, measures and instruments, especially for user personality dimensions.
Optimizing Compilation and Computational Complexity of Constraint Handling Rules
Authors: Jon Sneyers
Venue: Proceedings of the 25th International Conference on Logic Programming (2009)

Constraint Handling Rules [1,2] is a high-level programming language extension based on multi-headed committed-choice multiset rewrite rules. It can be used as a stand-alone language or as an extension to an existing host language. CHR systems have been implemented for nearly every Prolog system, and there are also CHR systems for Haskell, Java and C.
Sensor Health Monitoring in Wireless Sensor Networks
Authors: Chongming Zhang, Xi Zhou, Chuanshan Gao, Chunmei Wang, Huafeng Wu
Venue: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 01 (2009)

Wireless Sensor Network (WSN) has been widely used in information collection and monitoring applications. At the center of attention in these applications are data, which come from the sensor part of each WSN node. Sensor faults are common due to the sensor device itself and the harsh deployment environment. These faults may degrade the data quality from the very beginning and thus have a possible large influence on the final success of specific WSN application. Our work presented in this paper is to monitor the health status of sensors in WSN. Inspired by the latest development of time series data mining technology, a flexible approach is proposed for unspecific fault monitoring. Each deployed WSN node learns the frequent patterns periodically. Any sensor fault follows a pattern that is different from the node’s learned frequent patterns. The proposed method can find fault patterns efficiently. We show how this method works well in Castalia simulation environment.
Proceedings of the 10th MEDEA workshop on MEmory performance: DEaling with Applications, systems and architecture
Venue: ACM International Conference Proceeding Series (2009)

MEDEA is a half day workshop that wants to be a forum for academic and industrial people to exchange ideas and experience on memory architectures for general-purpose, commercial and embedded systems. Main topics are memory architecture and memory-related performance/power issues, as well as memory management and optimization themes, considering system architecture and application domain in a joint manner. The program presents works on memory organization, performance and power in various kinds of systems (e.g. vector and heterogeneous CMP), and works on memory management on CMP architectures. We hope you enjoy the workshop.
Unsupervised induction of natural language morphology inflection classes
Authors: Christian Monson, Alon Lavie, Jaime Carbonell, Lori Levin
Venue: Proceedings of the 7th Meeting of the ACL Special Interest Group in Computational Phonology: Current Themes in Computational Phonology and Morphology (2004)

We propose a novel language-independent framework for inducing a collection of morphological inflection classes from a monolingual corpus of full form words. Our approach involves two main stages. In the first stage, we generate a large data structure of candidate inflection classes and their interrelationships. In the second stage, search and filtering techniques are applied to this data structure, to identify a select collection of "true" inflection classes of the language. We describe the basic methodology involved in both stages of our approach and present an evaluation of our baseline techniques applied to induction of major inflection classes of Spanish. The preliminary results on an initial training corpus already surpass an F1 of 0.5 against ideal Spanish inflectional morphology classes.
Estimation in the Semiparametric Frailty Model with Covariate Measurement Errors
Authors: Liu Huanbin, Sun Liuquan
Venue: Proceedings of the 2009 IITA International Conference on Control, Automation and Systems Engineering (case 2009) (2009)

Marginal partial likelihood approach is used for estimating the parameters in general frailty measurement error models when covariates are measured with error. An efficient algorithm based on Markov chain Monte Carlo stochastic approximation is proposed to solve the resulting estimating equations. Simulation studies show that the proposed estimation procedure work well and gives accurate estimates and their variance estimates. We also illustrate the method with a data set from the western Kenya parasitaemia data.
IEEE President-Elect Candidates Address Computer Society Concerns
Venue: Computer (2009)

The president-elect candidates in this year's IEEE election provide responses to key questions posed by the IEEE Computer Society's volunteer leaders addressing topics of concern to Society members.
P3FSM: Portable Predictive Pattern Matching Finite State Machine
Authors: Lucas Vespa, Mini Mathew, Ning Weng
Venue: Proceedings of the 2009 20th IEEE International Conference on Application-specific Systems, Architectures and Processors (2009)

Signature-based network intrusion detection requires fast and reconfigurable pattern matching for deep packet inspection. In our previous work we address this problem with a hardware based pattern matching engine that utilizes a novel state encoding scheme to allow memory efficient use of Deterministic Finite Automata. In this work we expand on these concepts to create a completely software based system, P3FSM, which combines the properties of hardware based systems with the portability and programmability of software. Specifically we introduce two methods, Character Aware and SDFA, for encoding predictive state codes which can forecast the next states of our FSM. The result is software based pattern matching which is fast, reconfigurable, memory-efficient and portable.
Propagation Modeling and Analysis of Incidental Topics in Blogosphere
Authors: Li Zhao, Ruixi Yuan, Xiaohong Guan, Mingyang Li
Venue: Proceedings of the 3d International Conference on Online Communities and Social Computing: Held as Part of HCI International 2009 (2009)

Blog has become one of the most important media among the general public, and the propagation modeling of incidental topics in blogosphere is of great interest in social network studies. Most existing analysis methods are based on the infection models in epidemiology. However, many of these models are inconsistent with the widely observed power-law decay of the propagation velocity. In this paper, the propagation of incidental topics is described by a susceptible infection (SI) model based on the individual fitness. It is proved that the propagation velocity will asymptotically drop with power-law if the fitness density function satisfies certain conditions. Moreover, if the individual fitness is of uniform distribution, analytical solution of propagation velocity can be obtained based on our model. Model verifications are performed on the data from several widely discussed popular topics in Sina Blog and the results show that our model is consistent with the actual propagations.
Real-Time Robust Adaptive Modeling and Scheduling for an Electronic Commerce Server
Authors: Bing Du, Chun Ruan
Venue: Proceedings of the 10th International Conference on E-Commerce and Web Technologies (2009)

With the increasing importance and pervasiveness of Internet services, it is becoming a challenge for the proliferation of electronic commerce services to provide performance guarantees under extreme overload. This paper describes a real-time optimization modeling and scheduling approach for performance guarantee of electronic commerce servers. We show that an electronic commerce server may be simulated as a multi-tank system. A robust adaptive server model is subject to unknown additive load disturbances and uncertain model matching. Overload control techniques are based on adaptive admission control to achieve timing guarantees. We evaluate the performance of the model using a complex simulation that is subjected to varying model parameters and massive overload.
A high-order low-dispersion symmetry-preserving finite-volume method for compressible flow on curvilinear grids
Authors: J. C. Kok
Venue: Journal of Computational Physics (2009)

A new high-order finite-volume method is presented that preserves the skew symmetry of convection for the compressible flow equations. The method is intended for Large-Eddy Simulations (LES) of compressible turbulent flows, in particular in the context of hybrid RANS-LES computations. The method is fourth-order accurate and has low numerical dissipation and dispersion. Due to the finite-volume approach, mass, momentum, and total energy are locally conserved. Furthermore, the skew-symmetry preservation implies that kinetic energy, sound-velocity, and internal energy are all locally conserved by convection as well. The method is unique in that all these properties hold on non-uniform, curvilinear, structured grids. Due to the conservation of kinetic energy, there is no spurious production or dissipation of kinetic energy stemming from the discretization of convection. This enhances the numerical stability and reduces the possible interference of numerical errors with the subgrid-scale model. By minimizing the numerical dispersion, the numerical errors are reduced by an order of magnitude compared to a standard fourth-order finite-volume method.
Spatial scaffolding for sociable robot learning
Authors: Cynthia Breazeal, Matt Berlin
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 3 (2008)

Spatial scaffolding is a naturally occurring human teaching behavior, in which teachers use their bodies to spatially structure the learning environment to direct the attention of the learner. Robotic systems can take advantage of simple, highly reliable spatial scaffolding cues to learn from human teachers. We present an integrated robotic architecture that combines social attention and machine learning components to learn tasks effectively from natural spatial scaffolding interactions with human teachers. We evaluate the performance of this architecture in comparison to human learning data drawn from a novel study of the use of embodied cues in human task learning and teaching behavior. This evaluation provides quantitative evidence for the utility of spatial scaffolding to learning systems. In addition, this evaluation supported the construction of a novel, interactive demonstration of a humanoid robot taking advantage of spatial scaffolding cues to learn from natural human teaching behavior.
From rhetorical structures to document structure: shallow pragmatic analysis for document engineering
Authors: Gersende Georg, Hugo Hernault, Marc Cavazza, Helmut Prendinger, Mitsuru Ishizuka
Venue: Proceedings of the 9th ACM symposium on Document engineering (2009)

In this paper, we extend previous work on the automatic structuring of medical documents using content analysis. Our long-term objective is to take advantage of specific rhetoric markers encountered in specialized medical documents (clinical guidelines) to automatically structure free text according to its role in the document. This should enable to generate multiple views of the same document depending on the target audience, generate document summaries, as well as facilitating knowledge extraction from text. We have established in previous work that the structure of clinical guidelines could be refined through the identification of a limited set of deontic operators. We now propose to extend this approach by analyzing the text delimited by these operators using Rhetorical Structure Theory. The emphasis on causality and time in RST proves a powerful complement to the recognition of deontic structures while retaining the same philosophy of high-level recognition of sentence structure, which can be converted into application-specific mark-ups. Throughout the paper, we illustrate our findings through results produced by the automatic processing of English guidelines for the management of hypertension and Alzheimer disease.
Research on Representation of Geographic Spatio-temporal Information and Spatio-temporal Reasoning Rules Based on Geo-ontology and SWRL
Authors: Yongqi Huang, Gaoyan Deng
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 03 (2009)

Recently spatial reasoning has gradually become a research hotspot in some domains such as GIS and spatio-temporal database. At present many spatio-temporal methods put forward by scholars are methods based on logic or algebra by and large, and researches on formalization representation and reasoning of geographic spatio-temporal knowledge are few. Geo-ontology researches detailed connotations and hierarchy relationships of concepts of geographic spatial information in the geoinformatics domain and offers semantic annotations of concepts. Semantic and spatio-temporal relationships can fuse into geo-ontology and form knowledge base of geo-ontology. But OWL, an ontology representation language, can’t describe determining and reasoning rules of spatio-temporal relationships owing on account of its limitation. At the same time SWRL can make up the deficiency of OWL, which implements the combination of Horn-like rules and OWL knowledge base by adopting highly abstract syntax to express knowledge represented by OWL ontology. This paper does a research on adopting geo-ontology to represent semantic and spatio-temporal relationships and applying SWRL to express spatio-temporal rules, which lays the solid foundation of spatio-temporal reasoning.
Error Resilient Speech Coding Using Sub-band Hilbert Envelopes
Authors: Sriram Ganapathy, Petr Motlicek, Hynek Hermansky
Venue: Proceedings of the 12th International Conference on Text, Speech and Dialogue (2009)

Frequency Domain Linear Prediction (FDLP) represents a technique for auto-regressive modelling of Hilbert envelopes of a signal. In this paper, we propose a speech coding technique that uses FDLP in Quadrature Mirror Filter (QMF) sub-bands of short segments of the speech signal (25 ms). Line Spectral Frequency parameters related to autoregressive models and the spectral components of the residual signals are transmitted. For simulating the effects of lossy transmission channels, bit-packets are dropped randomly. In the objective and subjective quality evaluations, the proposed FDLP speech codec is judged to be more resilient to bit-packet losses compared to the state-of-the-art Adaptive Multi-Rate Wide-Band (AMR-WB) codec at 12 kbps.
A Novel Approach Based on PCNNs Template for Fingerprint Image Thinning
Authors: Dacheng Xu, Bailiang Li, Anton Nijholt
Venue: Proceedings of the 2009 Eigth IEEE/ACIS International Conference on Computer and Information Science (2009)

A PCNNs-based square-and-triangle-template method for binary fingerprint image thinning is proposed. The algorithm is iterative: combined sequential and parallel processing is employed to accelerate execution. When a neuron satisfies the square template, the pixel corresponding to this neuron will be noted during the process and be deleted until the end of the iteration; on the other hand, if a neuron meets a triangle template, it will be removed directly. In addition, this proposed algorithm can be effective for fingerprint thinning without considering the direction. The results showed that, with combined sequential and parallel conditions for border pixels removal, the algorithm could not only speed up the fingerprint thinning process, but also be applied to other common images. Furthermore, this algorithm might be applied to fingerprint identification systems to save time for identifying and eliminating spurious minutiae.
Screen-Camera Calibration Using Gray Codes
Authors: Yannick Francken, Chris Hermans, Philippe Bekaert
Venue: Proceedings of the 2009 Canadian Conference on Computer and Robot Vision (2009)

In this paper we present a method for efficient calibration of a screen-camera setup, in which the camera is not directly facing the screen. A spherical mirror is used to make the screen visible to the camera. Using Gray code illumination patterns, we can uniquely identify the reflection of each screen pixel on the imaged spherical mirror. This allows us to compute a large set of 2D-3D correspondences, using only two sphere locations. Compared to previous work, this means we require less manual interventions, combined with a more robust screen pixel detection scheme. This results in a consistent improvement in accuracy, which we illustrate with experiments on both synthetic and real data.
An Improved SAT Algorithm in Terms of Formula Length
Authors: Jianer Chen, Yang Liu
Venue: Proceedings of the 11th International Symposium on Algorithms and Data Structures (2009)

We present an improved algorithm for the general satisfiability problem. We introduce a new measure, the l-value, for a Boolean formula $\cal F$, which is defined based on weighted variable frequencies in the formula $\cal F$. We then develop a branch-and-search algorithm for the satisfiability problem that tries to maximize the decreasing rates in terms of the l-value during the branch-and-search process. The complexity of the algorithm in terms of the l-value is finally converted into the complexity in terms of the total length L of the input formula, resulting in an algorithm of running time O(20.0911L ) = O(1.0652 L ) for the satisfiability problem, improving the previous best upper bound O(20.0926L ) = O(1.0663 L ) for the problem.
Assessment of Structural Vulnerability for Power Grids by Network Performance Based on Complex Networks
Authors: Ettore Bompard, Marcelo Masera, Roberto Napoli, Fei Xue
Venue: Critical Information Infrastructure Security: Third International Workshop, CRITIS 2008, Rome, Italy, October13-15, 2008. Revised Papers (2009)

Power grids have been widely acknowledged as complex networks (CN) since this theory emerged and received considerable attention recently. Many works have been performed to investigate the structural vulnerability of power grids from the topological point of view based on CN. However, most of them applied conceptions and measurements of CN directly to the analysis of power grids which have more specific features that can not be reflected in generic perspective. This paper proposes several most serious obstacles for applying CN to analysis of vulnerability for power grids. Based on the proposed solutions for these obstacles, specific concept of network performance to indicate power supply ability of the network will be defined. Furthermore, the proposed method will be investigated by a 34-bus test system in comparison with the result from general concept of efficiency in CN to indicate its effectiveness.
Feature Ranking Algorithms for Improving Classification of Vector Space Embedded Graphs
Authors: Kaspar Riesen, Horst Bunke
Venue: Proceedings of the 13th International Conference on Computer Analysis of Images and Patterns (2009)

Graphs provide us with a powerful and flexible representation formalism for pattern recognition. Yet, the vast majority of pattern recognition algorithms rely on vectorial data descriptions and cannot directly be applied to graphs. In order to overcome this severe limitation, an embedding of the underlying graphs in a vector space ¿ n is employed. The basic idea is to regard the dissimilarities of a graph g to a number of prototype graphs as numerical features of g. In previous works, the prototypes are selected beforehand with selection strategies based on some heuristics. In the present paper we take a more fundamental approach and regard the problem of prototype selection as a feature selection problem, for which many methods are available. With several experimental results we show the feasibility of graph embedding based on prototypes obtained from feature selection algorithms. 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
A Vision and Agenda for Theory Provenance in Scientific Publishing
Authors: Ian Wood, J. Walter Larson, Henry Gardner
Venue: Database Systems for Advanced Applications: DASFAA 2009 International Workshops: BenchmarX, MCIS, WDPP, PPDA, MBC, PhD, Brisbane, Australia, April 20 - 23, 2009 (2009)

Primary motivations for effective data and process provenance in science are to facilitate validation and reproduction of experiments and to assist in the interpretation of data-analysis outcomes. Central to both these aims is an understanding of the ideas and hypotheses that the data supports, and how those ideas fit into the wider scientific context. Such knowledge consists of the collection of relevant previous ideas and experiments from the body of scientific knowledge, or, more specifically, how those ideas and hypotheses evolved, the steps in that evolution, and the experiments and results used to support those steps. This information we term the provenance of ideas or theory provenance. We propose an integrated approach to scientific knowledge management, combining data, process and theory provenance, providing full transparency for effective verification and review.
A QoS Framework with Traffic Request in Wireless Mesh Network
Authors: Bo Fu, Hejiao Huang
Venue: Proceedings of the 4th International Conference on Wireless Algorithms, Systems, and Applications (2009)

In this paper, we consider major issues in ensuring greater Quality-of-Service (QoS) in Wireless Mesh Networks (WMNs), specifically with regard to reliability and delay. To this end, we use traffic request to record QoS requirements of data flows. In order to achieve required QoS for all data flows efficiently and with high portability, we develop Network State Update Algorithm. All assumptions, definitions, and algorithms are made exclusively with WMNs in mind, guaranteeing the portability of our framework to various environments in WMNs. The simulation results in proof that our framework is correct.
One Solution on Multi Data Source Open Access in Telecom Network
Authors: Yu Hualong, Tang Shoulian
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 01 (2009)

To meet the continuing growing needs of service development and improve customer experiences, it is very important of customer and service data mining in future telecom service provision. The difficulty to get data from different sources at present is analyzed and a method of using unified database gateway function to solve this problem is proposed. Multi data source of telecom network is connected by unified database gateway which provides the interface of unified data access to service developers. The architecture and implementation methods of the unified database gateway are studied in details.