ppxscal/embedding_network huggingface dataset:
How to Make the T-ARGUS Modular Method Applicable to Linked Tables
Authors: Peter-Paul Wolf, Sarah Giessing
Venue: Proceedings of the UNESCO Chair in data privacy international conference on Privacy in Statistical Databases (2008)

The software package T-ARGUS offers a very efficient algorithm for secondary cell suppression known as either HiTaS or the Modular approach. The method is well suited for the protection of up to 3-dimensional hierarchical tables. In practice, statistical agencies release multiple tabulations based on the same dataset. Usually these tables are linked through certain linear constraints. In such a case cell suppressions must obviously be coordinated between tables. In this paper we investigate into the possibilities for an extension of the modular approach to deal with linked tables.
L3S at INEX 2007: Query Expansion for Entity Ranking Using a Highly Accurate Ontology
Authors: Gianluca Demartini, Claudiu S. Firan, Tereza Iofciu
Venue: Focused Access to XML Documents: 6th International Workshop of the Initiative for the Evaluation of XML Retrieval, INEX 2007 Dagstuhl Castle, Germany, December 17-19, 2007. Selected Papers (2008)

Entity ranking on Web scale datasets is still an open challenge. Several resources, as for example Wikipedia-based ontologies, can be used to improve the quality of the entity ranking produced by a system. In this paper we focus on the Wikipedia corpus and propose algorithms for finding entities based on query relaxation using category information. The main contribution is a methodology for expanding the user query by exploiting the semantic structure of the dataset. Our approach focuses on constructing queries using not only keywords from the topic, but also information about relevant categories. This is done leveraging on a highly accurate ontology which is matched to the character strings of the topic. The evaluation is performed using the INEX 2007 Wikipedia collection and entity ranking topics. The results show that our approach performs effectively, especially for early precision metrics.
A simple method for approximating rational Bézier curve using Bézier curves
Authors: Youdu Huang, Huaming Su, Hongwei Lin
Venue: Computer Aided Geometric Design (2008)

This paper presents a simple method for approximating a rational Bezier curve with Bezier curve sequence, whose control points are those of degree-elevated rational Bezier curves. It is proved that the derivatives with any given degree of the Bezier curve sequence constructed this way would uniformly converge to the corresponding derivatives of the original rational Bezier curve.
An application of a fuzzy knowledge system for air cargo overbooking under uncertain capacity
Authors: Yu-Jie Wang, Chao-Shun Kao
Venue: Computers Mathematics with Applications (2008)

Overbooking is a yield management policy of to air cargo to sell more cargo than the available capacity to minimize oversale and spoilage cost. In a yield management system of air cargo, roughly 40% of air carrier profit is obtained from overbooking. Thus overbooking is very important for air cargo yield management. However, the work becomes more complicated to evaluate overbooking capacity under uncertain environment. In this paper, an air cargo overbooking method is presented under uncertain environment to determine overbooking capacity. By the method, we are involved in the development of a fuzzy knowledge system based on fuzzy reasoning to solve the air cargo overbooking problem. Finally, a numerical example is illustrated to describe the fuzzy knowledge system.
Fast k Most Similar Neighbor Classifier for Mixed Data Based on a Tree Structure and Approximating-Eliminating
Authors: Selene Hernández-Rodríguez, J. A. Carrasco-Ochoa, J. Fco. Martínez-Trinidad
Venue: Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications (2008)

The k nearest neighbor (k-NN) classifier has been extensively used as a nonparametric technique in Pattern Recognition. However, in some applications where the training set is large, the exhaustive k-NN classifier becomes impractical. Therefore, many fast k-NN classifiers have been developed to avoid this problem. Most of these classifiers rely on metric properties, usually the triangle inequality, to reduce the number of prototype comparisons. However, in soft sciences, the prototypes are usually described by qualitative and quantitative features (mixed data), and sometimes the comparison function does not satisfy the triangle inequality. Therefore, in this work, a fast k most similar neighbor (k-MSN) classifier, which uses a Tree structure and an Approximating and Eliminating approach for Mixed Data, not based on metric properties (Tree AEMD), is introduced. The proposed classifier is compared against other fast k-NN classifiers.
Method to separate sparse components from signal mixtures
Authors: M. S. Woolfson, C. Bigan, J. A. Crowe, B. R. Hayes-Gill
Venue: Digital Signal Processing (2008)

This paper addresses the blind source separation (BSS) problem where the input data are mixtures of sources that are ''sparse''-that is each source has zero amplitude for some of the time. It is shown that, under certain conditions, it is possible to separate these sources by the analysis of localised segments of the phase space trajectory where one source dominates rather than applying statistical methods to the whole phase space plot. Results are presented for both simulated data, and thoracic and abdominal ECG data taken from an expectant mother. It is shown that when applied to the ECG data, the proposed technique has a comparable performance to the standard Fast ICA method. For the particular simulated data set, the proposed method gives better results for relatively low noise levels but is less robust than the FastICA for higher noise levels. Subsequently, the potential advantage of using the proposed technique for mixtures of correlated sparse sources is demonstrated. However, for more general sources that are not sparse, the proposed technique in its present form has, as expected, an inferior performance compared to the FastICA technique.
Formalizing Ontology Modularization through the Notion of Interfaces
Authors: Faezeh Ensan
Venue: Proceedings of the 16th international conference on Knowledge Engineering: Practice and Patterns (2008)

In this paper, we propose a new formalism for modular ontologies, which exploits the notion of interfaces as well as epistemic queries. In the proposed formalism, each ontology module both employs and realizes two distinct sets of interfaces. The axioms in each interface form the public section of the ontology module, while its ABox and TBoxes are private and can only be accessed through epistemic queries. This formalism permits the separation of configuration and development time manipulation tasks of a modular ontology development process. Hence, ontology modules can be developed independently of each others' signature and description language.
Exploiting Contextual Information for Speech/Non-Speech Detection
Authors: Sree Hari Krishnan Parthasarathi, Petr Motlíček, Hynek Hermansky
Venue: Proceedings of the 11th international conference on Text, Speech and Dialogue (2008)

In this paper, we investigate the effect of temporal context for speech/ non-speech detection (SND). It is shown that even a simple feature such as full-band energy, when employed with a large-enough context, shows promise for further investigation. Experimental evaluations on the test data set, with a state-of-the-art multi-layer perceptron based SND system and a simple energy threshold based SND method, using the F-measure, show an absolute performance gain of 4.4% and 5.4% respectively. The optimal contextual length was found to be 1000 ms. Further numerical optimizations yield an improvement (3.37% absolute), resulting in an absolute gain of 7.77% and 8.77% over the MLP based and energy based methods respectively. ROC based performance evaluation also reveals promising performance for the proposed method, particularly in low SNR conditions.
Privacy Protection for a Secure u-City Life
Authors: Changjin Lee, Bong Gyou Lee, Youngil Kong
Venue: Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007 (2007)

Recently, projects to construct an innovative brand-new city, termed a u-City (ubiquitous City), are being carried out in many countries. The u-City is a future-oriented city which combines ubiquitous information services with city. It has emerged as an alternative for improving the quality of life for human beings and reaching the balanced development among cities. Although a number of privacy problems are anticipated, there are very few researches on the protection of privacy in the u-City. In this study, we describe the privacy guidelines for modern cities as well as the privacy issues in the u-City, and provide suggestions for privacy protection to establish a safe u-City.
Fast Optimization Methods for L1 Regularization: A Comparative Study and Two New Approaches
Authors: Mark Schmidt, Glenn Fung, Rómer Rosales
Venue: Proceedings of the 18th European conference on Machine Learning (2007)

L1 regularization is effective for feature selection, but the resulting optimization is challenging due to the non-differentiability of the 1-norm. In this paper we compare state-of-the-art optimization techniques to solve this problem across several loss functions. Furthermore, we propose two new techniques. The first is based on a smooth (differentiable) convex approximation for the L1 regularizer that does not depend on any assumptions about the loss function used. The other technique is a new strategy that addresses the non-differentiability of the L1-regularizer by casting the problem as a constrained optimization problem that is then solved using a specialized gradient projection method. Extensive comparisons show that our newly proposed approaches consistently rank among the best in terms of convergence speed and efficiency by measuring the number of function evaluations required.
Game Theoretic Packet Scheduling to Combat Non-Cooperativeness in Wireless Mesh Networks
Authors: Zhen Kong, Yu-Kwong Kwok, Jiangzhou Wang
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems Workshops (2008)

In many practical scenarios, wireless mesh clients are autonomous and thus, may exhibit non-cooperative behaviors due to self-interests. For instance, a client may report bogus channel information to a mesh router in order to gain resource allocation advantages. Such non-cooperative behaviors are practicable as the client device's software could be modified by the user. In this paper, we analyze the impact of these rationally selfish and non-cooperative behaviors on the performance of packet scheduling algorithms in wireless mesh networks. Using a mixed strategy game theoretic model, we found that the traditional rate maximizing packet scheduling algorithms can lead non-cooperative clients to an undesirable Nash equilibrium, in which the wireless channel is used inefficiently. Motivated by this observation, we propose a novel repeated game theoretic approach to optimize packet scheduling and achieve efficient equilibria.
A Security Specification Library with a Schemaless Database
Authors: Shoichi Morimoto, Jingde Cheng
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

In order to develop highly secure information systems, it is important to make a security specification of the systems, although it requires heavy labor. Thus database technologies have been applied to software engineering and information security engineering for practical reuse of security specifications. However, because the specifications do not have fixed layout, it is difficult to develop a flexible and useful library for the documents with conventional database technologies. Therefore, this paper proposes a security specification library with a schemaless native XML database. Users of the library can directly store and manage security specifications with any layout. Consequently, the library mitigates the labor for making security specifications.
Query Propagation in a P2P Data Integration System in the Presence of Schema Constraints
Authors: Tadeusz Pankowski
Venue: Proceedings of the 1st international conference on Data Management in Grid and Peer-to-Peer Systems (2008)

This paper addresses the problem of data integration in a P2P environment, where each peer stores schema of its local data, mappings between the schemas, and some schema constraints. The goal of the integration is to answer queries formulated against a chosen peer. The answer consists of data stored in the queried peer as well as data of its direct and indirect partners. We focus on defining and using mappings, schema constraints, query propagation across the P2P system, and query reformulation in such scenario. The main focus is the exploitation of constraints for merging results from different peers to derive more complex information, and utilizing constraint knowledge to query propagation and the merging strategy. We show how the discussed method has been implemented in SixP2P system.
Pointer analysis and separation logic
Authors: Elodie-Jane Sims
Venue:  (2007)

We are interested in modular static analysis to analyse softwares automatically. We focus on programs with data structures, and in particular, programs with pointers. The final goal is to find errors in a program (problems of dereferencing, aliasing, etc) or to prove that a program is correct (regarding those problems) in an automatic way. Isthiaq, Pym, O'Hearn and Reynolds have recently developed separation logics, which are Hoare logics with assertions and predicates language that allow to prove the correctness of programs that manipulate pointers. The semantics of the logic's triples ({P}C{ P'}) is defined by predicate transformers in the style of weakest preconditions. We expressed and proved the correctness of those weakest preconditions (wlp) and strongest postconditions (sp), in particular in the case of while-loops. The advance from the existing work is that wlp and sp are defined for any formula, while previously existing rules had syntactic restrictions. We added fixpoints to the logic as well as a postponed substitution which then allow to express recursive formulae. We expressed wlp and sp in the extended logic and proved their correctness. The postponed substitution is directly useful to express recursive formulae. For example, nclist(x) = &mu;X &upsi;. (x = nil) &sext; &exist; x1, x2.(isval( x1) &and; (x x1, x2 * X&upsi;[x2/x])) describes the set of memory where x points to a list of integers. Next, the goal was to use separation logic with fixpoints as an interface language for pointer analysis. That is, translating the domains of those analyses into formulae of the logic (and conversely) and to prove their correctness. One might also use the translations to prove the correctness of the pointer analysis itself. We illustrate this approach with a simple pointers-partitioning analysis. We translate the logic formulae into an abstract language we designed which allows us to describe the type of values registered in the memory (nil, integer, booleans, pointers to pairs of some types, etc.) as well as the aliasing and non-aliasing relations between variables and locations in the memory. The main contribution is the definition of the abstract language and its semantics in a concrete domain which is the same as the one for the semantics of formulae. In particular, the semantics of the auxiliary variables, which is usually a question of implementation, is explicit in our language and its semantics. The abstract language is a partially reduced product of several subdomains and can be parametrised with existing numerical domains. We created a subdomain which is a tabular data structure to cope with the imprecision from not having sets of graphs. We expressed and proved the translations of formulae into this abstract language.
Development of an Efficient Conversion System for GML Documents
Authors: Dong-Suk Hong, Hong-Koo Kang, Dong-Oh Kim, Ki-Joon Han
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

In this paper, we designed and implemented a Conversion System for GML documents, and evaluated the performance of the system. The conversion system that uses the BXML-based binary encoding specification can directly display geographic information from BXML documents and can convert GML documents to BXML documents without loss of information, and vice versa. BXML is generally more effective in scanning cost and space requirement than GML and coordinate values in the form of BXML can be used directly without conversion.
No Guru, No Method, No Teacher: Self-classification and Self-modelling of E-Learning Communities
Authors: Zinayida Petrushyna, Ralf Klamma
Venue: Proceedings of the 3rd European conference on Technology Enhanced Learning: Times of Convergence: Technologies Across Learning Contexts (2008)

Learning processes are an infinite chain of knowledge transformation initiated by human collaboration. Our intention is to analyze E-Learning commu-nities. The current drawback of communities is a lack of common vocabularies that can be used for an E-Learning community description, design, evolution, and comparison. We examine structural and semantic parameters of E-Learning communities gathered in MediaBase of the PROLEARN Network of Excellence for professional learning. Using the parameters and the community-of-practice theory we define more standard description for a particular community or a set of communities and to identify factors that are essential for identifying overlappings between communities.
Perception based navigation for underactuated robots
Authors: Daniel E. Koditschek, Jessy W. Grizzle
Venue:  (2008)

Robot autonomous navigation is a very active field of robotics. In this thesis we propose a hierarchical approach to a class of underactuated robots by composing a collection of local controllers with well understood domains of attraction. We start by addressing the problem of robot navigation with nonholonomic motion constraints and perceptual cues arising from onboard visual servoing in partially engineered environments. We propose a general hybrid procedure that adapts to the constrained motion setting the standard feedback controller arising from a navigation function in the fully actuated case. This is accomplished by switching back and forth between moving "down" and "across" the associated gradient field toward the stable manifold it induces in the constrained dynamics. Guaranteed to avoid obstacles in all cases, we provide conditions under which the new procedure brings initial configurations to within an arbitrarily small neighborhood of the goal. We summarize with simulation results on a sample of visual servoing problems with a few different perceptual models. We document the empirical effectiveness of the proposed algorithm by reporting the results of its application to outdoor autonomous visual registration experiments with the robot RHex guided by engineered beacons. Next we explore the possibility of adapting the resulting first order hybrid feedback controller to its dynamical counterpart by introducing tunable damping terms in the control law. Just as gradient controllers for standard quasi-static mechanical systems give rise to generalized "PD-style" controllers for dynamical versions of those standard systems, we show that it is possible to construct similar "lifts" in the presence of non-holonomic constraints notwithstanding the necessary absence of point attractors. Simulation results corroborate the proposed lift. Finally we present an implementation of a fully autonomous navigation application for a legged robot. The robot adapts its leg trajectory parameters by recourse to a discrete gradient descent algorithm, while managing its experiments and outcome measurements autonomously via the navigation visual servoing algorithms proposed in this thesis.
Frequent Events and Epochs in Data Stream
Authors: Krzysztof Cabaj
Venue: Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms (2007)

Currently used data-mining algorithms treat data globally. Nevertheless, with such methods, potentially useful knowledge that relates to local phenomena may be undetected. In this paper, we introduce new patterns in a form of local frequent events and epochs, boundaries of which correspond to discovered changes in a data stream. A local frequent event is an event which occurs in some period of time frequently, but not necessarily in the whole data stream. Such an event will be called a frequent event in a data stream. An epoch is understood as a sufficiently large group of frequent events that occur in a similar part of the data stream. The epochs are defined in such a way that they do not overlap are separated by so called change periods. In the paper, we discuss some potential applications of the proposed knowledge. Preliminary experiments are described as well.
Impact Analysis of Faults and Attacks in Large-Scale Networks
Authors: Salim Hariri, Guangzhi Qu, Tushneem Dharmagadda, Modukuri Ramkishore, Cauligi S. Raghavendra
Venue: IEEE Security and Privacy (2003)

Monitoring and quantifying component behavior is key to making networks reliable and robust. The agent-based architecture presented here continuously monitors network vulnerability metrics, providing new ways to measure the impact of faults and attacks.
Dynamic Delayed Duplicate Detection for External Memory Model Checking
Authors: Sami Evangelista
Venue: Proceedings of the 15th international workshop on Model Checking Software (2008)

Duplicate detection is an expensive operation of disk-based model checkers. It consists of comparing some potentially new states, the candidate states, to previous visited states. We propose a new approach to this technique called dynamic delayed duplicate detection. This one exploits some typical properties of states spaces, and adapts itself to the structure of the state space to dynamically decide when duplicate detection must be conducted. We implemented this method in a new algorithm and found out that it greatly cuts down the cost of duplicate detection. On some classes of models, it performs significantly better than some previously published algorithms.
Constrained Interpolation with Implicit Plane Cubic A-Splines
Authors: S. Behar-Jequín, J. Estrada-Sarlabous, V. Hernández-Mederos
Venue: Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications (2008)

In this work we focus on the following problem: given an ordered set of points in the plane lying on one side of a given boundary polygon, construct a smooth curve interpolating these points, such that the curve lies on the same side of the polygon as the data.We have developed a G 2-continuous cubic A-spline scheme smoothing the polygon defined by the line segments joining consecutive data points, such that the spline curve lies completely on the same side of the boundary polygon as the data. The proposed A-spline scheme provides an efficient method for generating a smooth robot's path that avoids corners or polygonal objects for a given planned path, for designing a smooth curve on a polygonal piece of material, etc.