ppxscal/embedding_network huggingface dataset:
Analysis of the Tip-Timing Precision of Double-Shielded Capacitive Pulse Sensor
Authors: Fajie Duan, Menglin Li, Ouyang Tao, Xianghong Kong
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 01 (2009)

A Double-Shielded Capacitive Pulse Sensor designed for the measurement of blade tip clearance and blade time of arrival is introduced combined with its post-circuit. On the basis of research, the accuracy of measurement concerns with the tip-timing precision of the sensor which is determined by the zero-crossing point of the signal. As the influence factors of the precision, the discussion about the mathematical model of bipolar pulse signal and cybernetics model of circuit are with application to design the post-circuit, furthermore, the analysis of the signal’s spectrum and impulse response of circuit system are used for the optimization of the bandwidth. With the comparison of the simulation results in different bandwidth, the evidences to the system design are present in the paper. A dynamical testing experiment prepared for the verification of accuracy shows the output of Double-Shielded Capacitive Pulse Sensor featured with appropriate bandwidth and rapid response.
POLIPO: Policies & OntoLogies for Interoperability, Portability, and autOnomy
Authors: Daniel Trivellato, Fred Spiessens, Nicola Zannone, Sandro Etalle
Venue: Proceedings of the 2009 IEEE International Symposium on Policies for Distributed Systems and Networks (2009)

In this paper we identify the requirements for the definition of a security framework for distributed access control in dynamic coalitions of heterogeneous systems. Based on the elicited requirements, we introduce the POLIPO framework that combines distributed access control with ontologies to give a globally understandable semantics to policies, enabling interoperability among heterogeneous systems.
Self-movement Feeling Generation in Sports Watching with Screen Movement via Pan-Tilt Steerable Projector
Authors: Hiroshi Noguchi, Kei Yoshinaka, Taketoshi Mori, Tomomasa Sato
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part IV: Interacting in Various Application Domains (2009)

This paper describes system displays video frame of sports broadcasting with screen movement by an active projector. Since the screen moves as the camera operator controls their camera in the stadium by automatic detection of background movement from video frames, the watchers are force to move their heads in home environment. The head movement helps the watchers to feel self-movement as if they ware located in the stadium. The experiments demonstrate that the head movement when the watchers track the moving screen with their eyes and heads generates sense of self-movement and active feeling about players.
Handbook of Remote Biometrics: for Surveillance and Security, 1st edition
Authors: Massimo Tistarelli, Stan Z. Li, Rama Chellappa
Venue: Advances In Pattern Recognition (2009)

This comprehensive and innovative handbook covers aspects of biometrics from the perspective of recognizing individuals at a distance, in motion, and under a surveillance scenario. Features: Starts with a thorough introductory chapter; Provides topics from a range of different perspectives offered by an international collection of leading researchers in the field; Contains selected expanded contributions from the 5th IAPR International Summer School for Advanced Studies on Biometrics for Secure Authentication; Investigates issues of iris recognition, gait recognition, and touchless fingerprint recognition, as well as various aspects of face recognition; Discusses multibiometric systems, and machine learning techniques; Examines biometrics ethics and policy; Presents international standards in biometrics, including those under preparation. This state-of-the-art volume is designed to help form and inform professionals, young researchers, and graduate students in advanced biometric technologies.
New Integrated Framework for Video Based Moving Object Tracking
Authors: Md. Zahidul Islam, Chi-Min Oh, Chil-Woo Lee
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part III: Ubiquitous and Intelligent Interaction (2009)

In this paper, we depict a novel approach to improve the moving object tracking system with particle filter using shape similarity and color histogram matching by a new integrated framework. The shape similarity between a template and estimated regions in the video sequences can be measured by their normalized cross-correlation of distance transformation image map. Observation model of the particle filter is based on shape from distance transformed edge features with concurrent effect of color information. The target object to be tracked forms the reference color window and its histogram are calculated, which is used to compute the histogram distance while performing a deterministic search for matching window. For both shape and color matching reference template window is created instantly by selecting any object in a video scene and updated in every frame. Experimental results have been offered to show the effectiveness of the proposed method.
AHSCAN: Agglomerative Hierarchical Structural Clustering Algorithm for Networks
Authors: Nurcan Yuruk, Mutlu Mete, Xiaowei Xu, Thomas A. J. Schweiger
Venue: Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining (2009)

Many systems in sciences, engineering and nature can be modeled as networks. Examples include the internet, WWW and social networks. Finding hidden structures is important for making sense of complex networked data. In this paper we present a new network clustering method that can find clusters in an agglomerative fashion using structural similarity of vertices in the given network. Experiments conducted on real datasets demonstrate promising performance of the new method.
Multiple indexing in an electronic Kanji dictionary
Authors: James Breen
Venue: Proceedings of the Workshop on Enhancing and Using Electronic Dictionaries (2004)

Kanji dictionaries, which need to present a large number of complex characters in an order that makes them accessible by users, traditionally use several indexing techniques that are particularly suited to the printed medium. Electronic dictionary technology provides the opportunity of both introducing new indexing techniques that are not feasible with printed dictionaries, and also allowing a wide range of index methods with each dictionary. It also allows dictionaries to be interfaced at the character level with documents and applications, thus removing much of the requirement for complex index methods. This paper surveys the traditional indexing methods, introduces some of the new indexing techniques that have become available with electronic kanji dictionaries, and reports on an analysis of the index usage patterns in a major WWW-based electronic kanji dictionary. This is believed to be the first such analysis conducted and reported.
Enhancing the Social Capital of Learning Communities by Using an Ad Hoc Transient Communities Service
Authors: Sibren Fetter, Adriana J. Berlanga, Peter Sloep
Venue: Proceedings of the 8th International Conference on Advances in Web Based Learning (2009)

In online learning, communities can help to enhance learning. However, because of the dynamic nature of communities, attaining and sustaining these communities can be difficult. One aspect that has an influence on, and is influenced by these dynamics is the social capital of a community. Features of social capital are the social network structure, the sense of belonging and, the support received and provided. It is hypothesized that these features can be improved by using Ad Hoc Transient Communities (AHTCs). Through an AHTC learners are brought together for a specific, learning-related goal (`ad hoc') and for only a limited amount of time (`transience'). To test whether the use of AHTCs has a positive influence on the social capital, a learner support service which enables the use of AHTCs is proposed. Furthermore, requirements, prerequisites, and future research are discussed.
Content ordering in the generation of persuasive discourse
Authors: Chris Reed, Derek Long
Venue: Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2 (1997)

A framework is summarized which supports the planning of natural language argument structure. One key aspect of natural argument is the order in which components are presented. This is in part responsible for both the coherency and persuasive effect of an argument. One means of effecting such ordering is proposed, and an overview is provided of the various classes of ordering heuristics. These heuristics are based upon insights offered by rhetoric texts, psychological research, and a corpus study. Finally, it is demonstrated that such an approach can also contribute to the generation of surface textual features including formatting, punctuation and clue words.
Bootstrapping named entity recognition with automatically generated gazetteer lists
Authors: Zornitsa Kozareva
Venue: Proceedings of the Eleventh Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop (2006)

Current Named Entity Recognition systems suffer from the lack of hand-tagged data as well as degradation when moving to other domain. This paper explores two aspects: the automatic generation of gazetteer lists from unlabeled data; and the building of a Named Entity Recognition system with labeled and unlabeled data.
A New Method of Attribute Reduction Based on Gamma Coefficient
Authors: Jiang Bai, Li-Li Wei
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 02 (2009)

In this paper, nonparametric method in statistics is introduced to analyze the reduction of ordinal attributes. Firstly,Goodman-Kruskal gamma coefficient, which is used to measuring the correlativity between ordinal variables in statistics, is now used as a new measure of correlativity between ordinal attribute sets after modifying it properly. Then, based on this new measure, a new method of attribute reduction for ordered decision tables is presented, and some connections between the method and the rough set theory about attribute reduction can be found. Furthermore, the numerical experiments show that the nonparametric statistical method we proposed is feasible and efficient for both consistent and inconsistent ordered decision tables.
Modeling Unreliable Observations in Bayesian Networks by Credal Networks
Authors: Alessandro Antonucci, Alberto Piatti
Venue: Proceedings of the 3rd International Conference on Scalable Uncertainty Management (2009)

Bayesian networks are probabilistic graphical models widely employed in AI for the implementation of knowledge-based systems. Standard inference algorithms can update the beliefs about a variable of interest in the network after the observation of some other variables. This is usually achieved under the assumption that the observations could reveal the actual states of the variables in a fully reliable way. We propose a procedure for a more general modeling of the observations, which allows for updating beliefs in different situations, including various cases of unreliable, incomplete, uncertain and also missing observations. This is achieved by augmenting the original Bayesian network with a number of auxiliary variables corresponding to the observations. For a flexible modeling of the observational process, the quantification of the relations between these auxiliary variables and those of the original Bayesian network is done by credal sets, i.e., convex sets of probability mass functions. Without any lack of generality, we show how this can be done by simply estimating the bounds of likelihoods of the observations for the different values of the observed variables. Overall, the Bayesian network is transformed into a credal network, for which a standard updating problem has to be solved. Finally, a number of transformations that might simplify the updating of the resulting credal network is provided.
A new Lagrangean approach to the pooling problem
Authors: Hossa Almutairi, Samir Elhedhli
Venue: Journal of Global Optimization (2009)

We present a new Lagrangean approach for the pooling problem. The relaxation targets all nonlinear constraints, and results in a Lagrangean subproblem with a nonlinear objective function and linear constraints, that is reformulated as a linear mixed integer program. Besides being used to generate lower bounds, the subproblem solutions are exploited within Lagrangean heuristics to find feasible solutions. Valid cuts, derived from bilinear terms, are added to the subproblem to strengthen the Lagrangean bound and improve the quality of feasible solutions. The procedure is tested on a benchmark set of fifteen problems from the literature. The proposed bounds are found to outperform or equal earlier bounds from the literature on 14 out of 15 tested problems. Similarly, the Lagrangean heuristics outperform the VNS and MALT heuristics on 4 instances. Furthermore, the Lagrangean lower bound is equal to the global optimum for nine problems, and on average is 2.1% from the optimum. The Lagrangean heuristics, on the other hand, find the global solution for ten problems and on average are 0.043% from the optimum.
Towards unsupervised recognition of dialogue acts
Authors: Nicole Novielli, Carlo Strapparava
Venue: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Student Research Workshop and Doctoral Consortium (2009)

When engaged in dialogues, people perform communicative actions to pursue specific communicative goals. Speech acts recognition attracted computational linguistics since long time and could impact considerably a huge variety of application domains. We study the task of automatic labeling dialogues with the proper dialogue acts, relying on empirical methods and simply exploiting lexical semantics of the utterances. In particular, we present some experiments in supervised and unsupervised framework on both an English and an Italian corpus of dialogue transcriptions. The evaluation displays encouraging results in both languages, especially in the unsupervised version of the methodology.
An economic framework for dynamic spectrum access and service pricing
Authors: Shamik Sengupta, Mainak Chatterjee
Venue: IEEE/ACM Transactions on Networking (TON) (2009)

The concept of dynamic spectrum access will allow the radio spectrum to be traded in a market like scenario allowing wireless service providers (WSPs) to lease chunks of spectrum on a short-term basis. Such market mechanisms will lead to competition among WSPs where they not only compete to acquire spectrum but also attract and retain users. Currently, there is little understanding on how such a dynamic trading system will operate so as to make the system feasible under economic terms. In this paper, we propose an economic framework that can be used to guide i) the dynamic spectrum allocation process and ii) the service pricing mechanisms that the providers can use. We propose a knapsack based auction model that dynamically allocates spectrum to the WSPs such that revenue and spectrum usage are maximized. We borrow techniques from game theory to capture the conflict of interest between WSPs and end users. A dynamic pricing strategy for the providers is also proposed. We show that even in a greedy and non-cooperative behavioral game model, it is in the best interest of the WSPs to adhere to a price and channel threshold which is a direct consequence of price equilibrium. Through simulation results, we show that the proposed auction model entices WSPs to participate in the auction, makes optimal use of the spectrum, and avoids collusion among WSPs. We demonstrate how pricing can be used as an effective tool for providing incentives to the WSPs to upgrade their network resources and offer better services.
Resolving Loads with Positive Interior Stresses
Authors: Günter Rote, André Schulz
Venue: Proceedings of the 11th International Symposium on Algorithms and Data Structures (2009)

We consider the pair (p i ,f i ) as a force with two-dimensional direction vector f i applied at the point p i in the plane. For a given set of forces we ask for a non-crossing geometric graph on the points p i that has the following property: There exists a weight assignment to the edges of the graph, such that for every p i the sum of the weighted edges (seen as vectors) around p i yields ¿ f i . As additional constraint we restrict ourselves to weights that are non-negative on every edge that is not on the convex hull of the point set. We show that (under a generic assumption) for any reasonable set of forces there is exactly one pointed pseudo-triangulation that fulfils the desired properties. Our results will be obtained by linear programming duality over the PPT-polytope. For the case where the forces appear only at convex hull vertices we show that the pseudo-triangulation that resolves the load can be computed as weighted Delaunay triangulation. Our observations lead to a new characterization of pointed pseudo-triangulations, structures that have been proven to be extremely useful in the design and analysis of efficient geometric algorithms.As an application, we discuss how to compute the maximal locally convex function for a polygon whose corners lie on its convex hull.
Imputation of Missing Data Using PCA, Neuro-Fuzzy and Genetic Algorithms
Authors: Nthabiseng Hlalele, Fulufhelo Nelwamondo, Tshilidzi Marwala
Venue: Advances in Neuro-Information Processing: 15th International Conference, ICONIP 2008, Auckland, New Zealand, November 25-28, 2008, Revised Selected Papers, Part II (2009)

This paper presents a method of imputing missing data that combines principal component analysis and neuro-fuzzy (PCA-NF) modeling in conjunction with genetic algorithms (GA). The ability of the model to impute missing data is tested using the South African HIV sero-prevalence dataset. The results indicate an average increase in accuracy from 60 % when using the neuro-fuzzy model independently to 99 % when the proposed model is used.
Refinement Sensitive Formal Semantics of State Machines With Persistent Choice
Authors: Harald Fecher, Michael Huth, Heiko Schmidt, Jens Schönborn
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2009)

Modeling languages usually support two kinds of nondeterminism, an external one for interactions of a system with its environment, and one that stems from under-specification as familiar in models of behavioral requirements. Both forms of nondeterminism are resolvable by composing a system with an environment model and by refining under-specified behavior (respectively). Modeling languages usually don't support nondeterminism that is persistent in that neither the composition with an environment nor refinements of under-specification will resolve it. Persistent nondeterminism is used, e.g., for modeling faulty systems. We present a formal semantics for UML state machines enriched with an operator ''persistent choice'' that models persistent nondeterminism. This semantics is based on abstract models -@m-automata with a novel refinement relation - and a sound three-valued satisfaction relation for properties expressed in the @m-calculus.
Blurred Shape Model for binary and grey-level symbol recognition
Authors: Sergio Escalera, Alicia Fornés, Oriol Pujol, Petia Radeva, Gemma Sánchez, Josep Lladós
Venue: Pattern Recognition Letters (2009)

Many symbol recognition problems require the use of robust descriptors in order to obtain rich information of the data. However, the research of a good descriptor is still an open issue due to the high variability of symbols appearance. Rotation, partial occlusions, elastic deformations, intra-class and inter-class variations, or high variability among symbols due to different writing styles, are just a few problems. In this paper, we introduce a symbol shape description to deal with the changes in appearance that these types of symbols suffer. The shape of the symbol is aligned based on principal components to make the recognition invariant to rotation and reflection. Then, we present the Blurred Shape Model descriptor (BSM), where new features encode the probability of appearance of each pixel that outlines the symbols shape. Moreover, we include the new descriptor in a system to deal with multi-class symbol categorization problems. Adaboost is used to train the binary classifiers, learning the BSM features that better split symbol classes. Then, the binary problems are embedded in an Error-Correcting Output Codes framework (ECOC) to deal with the multi-class case. The methodology is evaluated on different synthetic and real data sets. State-of-the-art descriptors and classifiers are compared, showing the robustness and better performance of the present scheme to classify symbols with high variability of appearance.
Semi-supervised Prediction of Protein Interaction Sentences Exploiting Semantically Encoded Metrics
Authors: Tamara Polajnar, Mark Girolami
Venue: Proceedings of the 4th IAPR International Conference on Pattern Recognition in Bioinformatics (2009)

Protein-protein interaction (PPI) identification is an integral component of many biomedical research and database curation tools. Automation of this task through classification is one of the key goals of text mining (TM). However, labelled PPI corpora required to train classifiers are generally small. In order to overcome this sparsity in the training data, we propose a novel method of integrating corpora that do not contain relevance judgements. Our approach uses a semantic language model to gather word similarity from a large unlabelled corpus. This additional information is integrated into the sentence classification process using kernel transformations and has a re-weighting effect on the training features that leads to an 8% improvement in F-score over the baseline results. Furthermore, we discover that some words which are generally considered indicative of interactions are actually neutralised by this process.
An Encoding of XQuery in Prolog
Authors: Jesús M. Almendros-Jiménez
Venue: Proceedings of the 6th International XML Database Symposium on Database and XML Technologies (2009)

In this paper we describe the implementation of (a subset of) the XQuery language using logic programming (in particular, by means of Prolog). Such implementation has been developed using the Prolog interpreter SWI-Prolog. XML files are handled by means of the XML Library of SWI-Prolog. XPath/XQuery are encoded by means of Prolog rules. Such Prolog rules are executed in order to obtain the answer of the query.
Monitoring BPEL-Based Web Service Composition Using AOP
Authors: Mingjie Sun, Bixin Li, Pengcheng Zhang
Venue: Proceedings of the 2009 Eigth IEEE/ACIS International Conference on Computer and Information Science (2009)

With the loose coupling and dynamic attributes of Web Service, the implementation behavior may be different from original requirement, so it’s essential to implement the run-time monitoring. Monitoring analyzes the conformance of a Web Service to the requirements.This paper gives a novel monitoring prototype framework. It introduces WS-Policy to express the user’s monitoring requirement on the Services. Then, AOP (Aspect Oriented Programming) technology is used to extend the BPEL execution engine in order to capture run-time information of the service. Finally, monitoring information is analyzed against the EMSC (Extended Message Sequence Charts) and METG property specification of that service, reaching the predefined goal of monitoring. To evaluate our approach, we have executed a travel reservation service sample under the monitoring framework. Case study demonstrates the feasibility.