ppxscal/embedding_network huggingface dataset:
Extending Attribute Dependencies for Lattice-Based Querying and Navigation
Authors: Nizar Messai, Marie-Dominique Devignes, Amedeo Napoli, Malika Smaïl-Tabbone
Venue: Proceedings of the 16th international conference on Conceptual Structures: Knowledge Visualization and Reasoning (2008)

In this paper we study dependencies of attributes in the context of Formal Concept Analysis. These dependencies allow to define a hierarchy of attributes reflecting the importance or interest in attributes. A hierarchy of attributes is a set of attributes partially ordered with respect to their importance. It represents domain knowledge used to improve lattice-based querying and navigation. Actually, in lattice-based querying, hierarchies of attributes are used to define complex queries containing attributes with different levels of importance: more important attributes define the focus of the retrieval while less important ones define secondary information whose presence is desirable in the answers. Furthermore, the relation between attributes in a complex query represents implicit or explicit knowledge units that must be considered while computing answers. Similarly, in lattice-based navigation, the choice of moving to a particular concept rather than to another is influenced by the higher importance of the attributes in the concept intent. Hence, the design and use of a hierarchy of attributes leads to a navigation guided by domain knowledge.
CREAM: A Generic Build-Time Component Framework for Distributed Embedded Systems
Authors: Chetan Raj, Jiyong Park, Jungkeun Park, Seongsoo Hong
Venue: Proceedings of the 2008 14th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (2008)

A component framework plays an important role in CBSD as it determines how software components are developed, packaged, assembled and deployed. A desirable component framework for developing diverse cross-domain embedded applications should meet such requirements as (1) lightweight on memory use, (2) integrated task execution model, (3) fast inter-component communication, (4) support for distributed processing, and (5) transparency from underlying communication middleware. Although current embedded system component frameworks address some of the above requirements, they fail to meet all of them taken together. We thus propose a new embedded system component framework called CREAM (Component-based Remote-communicating Embedded Application Model). It achieves these goals by using build-time code generation, explicit control of task creation and execution in the component framework, static analysis of component composition to generate efficient component binding, and abstraction of the component’s application logic from the communication middleware. We have implemented the CREAM component framework and conducted a series of experiments to compare its performance characteristics to a raw socket-based communication implementation and the Lightweight-CCM implementation by MicoCCM.
Attracting communities and students to IT with a community service web contest
Authors: Gary B. Randolph, Dennis O. Owen
Venue: Proceedings of the 9th ACM SIGITE conference on Information technology education (2008)

This paper describes a high school web design contest held by a computer and information technology program. The goals were to serve the community with community engagement websites and also to provide experiential learning in an IT field and hopefully to encourage students to pursue careers in IT. Five high schools competed, with forty-eight students in thirteen different teams.
Advanced modelling of retail pricing by fuzzy networks
Authors: Alexander Gegov, Emil Gegov, Philip Treleaven
Venue: Proceedings of the 9th WSEAS International Conference on Fuzzy Systems (2008)

This paper presents the application of three fuzzy network models to the procurement phase of the retail pricing process. Each model uses a specific type of node composition method such as functional composition (FC), inferential composition (IC) and linguistic composition (LC). The purpose of this composition is to convert the fuzzy network into a fuzzy system by taking into account the connections among network nodes. The methods are compared in terms of accuracy, efficiency, transparency and feasibility.
Stochastic Online Scheduling Revisited
Authors: Andreas S. Schulz
Venue: Proceedings of the 2nd international conference on Combinatorial Optimization and Applications (2008)

We consider the problem of minimizing the total weighted completion time on identical parallel machines when jobs have stochastic processing times and may arrive over time. We give randomized as well as deterministic online and off-line algorithms that have the best known performance guarantees in either setting, deterministic and off-line or randomized and online. Our analysis is based on a novel linear programming relaxation for stochastic scheduling problems, which can be solved online.
A Korean Part-of-Speech Tagging System Using Resolution Rules for Individual Ambiguous Word
Authors: Young-Min Ahn, Seung-Eun Shin, Hee-Geun Park, Hyungsuk Ji, Young-Hoon Seo
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

In this paper we present a Korean part-of-speech tagging system using resolution rules for individual ambiguous word. Our system resolves lexical ambiguities by common rules, rules for individual ambiguous word, and statistical approach. We built resolution rules for each word which has several distinct morphological analysis results with a view to enhancing tagging accuracy. Statistical approach based on Hidden Markov Model (HMM) is applied for ambiguous words that are not resolved by the rules. The experiment on the test set shows that the part-of-speech tagging system has high accuracy and broad coverage.
Anonymity Architecture for Mobile Agent Systems
Authors: Rafał Leszczyna
Venue: Proceedings of the 3rd international conference on Industrial Applications of Holonic and Multi-Agent Systems: Holonic and Multi-Agent Systems for Manufacturing (2007)

The paper presents a new security architecture for MAS, which supports anonymity of agent owners. The architecture is composed of two main elements: Module I: Untraceability Protocol Infrastructure and Module II: Additional Untraceability Support. Module I is based on the recently proposed untraceability protocol for MAS and it forms the core of the anonymity architecture, which can be supported by the elements of the second module. This part of architecture was implemented and provided to MAS users. Module II instead, is defined in abstract way, through high-level description of its components.
Reduction Under Substitution
Authors: Jörg Endrullis, Roel Vrijer
Venue: Proceedings of the 19th international conference on Rewriting Techniques and Applications (2008)

The Reduction-under-Substitution Lemma (RuS) , due to van Daalen [Daa80] , provides an answer to the following question concerning the lambda calculus: given a reduction $M[{x}:={L}] \twoheadrightarrow N$, what can we say about the contribution of the substitution to the result N. It is related to a not very well-known lemma that was conjectured by Barendregt in the early 70's, addressing the similar question as to the contribution of the argument M in a reduction $FM \twoheadrightarrow N$. The origin of Barendregt's Lemma lies in undefinablity proofs, whereas van Daalen's interest came from its application to the so-called Square Brackets Lemma, which is used in proofs of strong normalization.In this paper we compare various forms of RuS. We strengthen RuS to multiple substitution and context filling and show how it can be used to give short and perspicuous proofs of undefinability results. Most of these are known as consequences of Berry's Sequentiality Theorem, but some fall outside its scope. We show that RuS can also be used to prove the sequentiality theorem itself. To that purpose we give a further adaptation of RuS, now also involving "bottom" reduction rules, sending unsolvable terms to a bottom element and in the limit producing Böhm trees.
Deterministic Defuzzification Based on Spectral Projected Gradient Optimization
Authors: Tibor Lukić, Nataša Sladoje, Joakim Lindblad
Venue: Proceedings of the 30th DAGM symposium on Pattern Recognition (2008)

We apply deterministic optimization based on Spectral Projected Gradient method in combination with concave regularization to solve the minimization problem imposed by defuzzification by feature distance minimization. We compare the performance of the proposed algorithm with the methods previously recommended for the same task, (non-deterministic) simulated annealing and (deterministic) DC based algorithm. The evaluation, including numerical tests performed on synthetic and real images, shows advantages of the new method in terms of speed and flexibility regarding inclusion of additional features in defuzzification. Its relatively low memory requirements allow the application of the suggested method for defuzzification of 3D objects.
State of the art: Linux audio 2008
Authors: Dave Phillips
Venue: Linux Journal (2008)

How does Linux sound these days? Dave Phillips gets his groove on in Part I of his survey of Linux audio capabilities.
Proceedings of the 1st Workshop on Social Network Systems
Venue: European Conference on Computer Systems (2008)

In the past couple of years, websites such as Facebook, MySpace, and YouTube have rocketed to the top of web popularity. These sites are instances of what is known as "Web 2.0". Notably, and in contrast to the more traditional popular sites such as portals, search engines, or news aggregators, these sites are organized around user identities and a social network (or graph) of links between identities. The social network gives users a new basis for forming and maintaining relationships and locating, consuming, filtering, and publishing content. Since the social network is expressed in a formal way, it can also be used by non-user system components to improve performance, security, or other objectives based on assumptions about trust or shared interests. A social network system is a software system organized around a dynamic social network core. The study and understanding of these systems is highly relevant to the systems community. Surprisingly, despite both their exciting possibilities and their amazing popularity growth, social network systems have been largely neglected by researchers. To begin to remedy this, we have organized this workshop; the First Workshop on Social Network Systems (SocialNets'08). As a first-year workshop, we were pleasantly surprised to receive sixteen high-quality submissions. We accepted eight into the workshop, for an acceptance rate of exactly 50 percent. A tight reviewing schedule gave the program committee just over one week to complete and submit reviews. However, we are happy to report that all papers received at least three reviews from program committee members. The workshop papers cover a range of topics on social network systems. The presentations are organized into three broad sessions; the measurement and analysis of existing social networks, issues of security and privacy in social network systems, and new applications that leverage social networks. Many of the papers are likely to spark lively discussion at the workshop.
Toward a Theory of Embodied Statistical Learning
Authors: Daniel Burfoot, Max Lungarella, Yasuo Kuniyoshi
Venue: Proceedings of the 10th international conference on Simulation of Adaptive Behavior: From Animals to Animats (2008)

The purpose of this paper is to outline a new formulation of statistical learning that will be more useful and relevant to the field of robotics. The primary motivation for this new perspective is the mismatch between the form of data assumed by current statistical learning algorithms, and the form of data that is actually generated by robotic systems. Specifically, robotic systems generate a vast unlabeled data stream, while most current algorithms are designed to handle limited numbers of discrete, labeled, independent and identically distributed samples. We argue that there is only one meaningful unsupervised learning process that can be applied to a vast data stream: adaptive compression. The compression rate can be used to compare different techniques, and statistical models obtained through adaptive compression should also be useful for other tasks.
Brief paper: An efficient algorithm for discrete-time H∞ preview control
Authors: Andrew Hazell, David J. N. Limebeer
Venue: Automatica (Journal of IFAC) (2008)

An efficient numerical solution to the output feedback, discrete-time, H"~ preview control problem is presented. The first step of the solution comes from embedding the preview control problem in a two-degree-of-freedom generalised regulator framework, in which the augmented system state includes a segment of the (frequency weighted) previewed signal. An efficient method for solving the resulting inflated Discrete Algebraic Riccati Equations (DAREs) is then found. It is demonstrated that one need only solve an (estimation) Riccati equation with dimension that of the plant, and a control Riccati equation with dimension that of the plant and reference weighting taken together. The reduced control Riccati equation is the product of a recursive reduction, enabled by the zero eigenvalues in the associated closed-loop matrix. An added feature of the presented algorithm is that no 'large' matrix computations are required and no large matrices need be stored; only the edges of the full information Riccati equation solution are required when synthesising the controller.
Beyond Accuracy. Reputation for Partner Selection with Lies and Retaliation
Authors: Isaac Pinyol, Mario Paolucci, Jordi Sabater-Mir, Rosaria Conte
Venue: Multi-Agent-Based Simulation VIII: International Workshop, MABS 2007, Honolulu, HI, USA, May 15, 2007, Revised and Invited Papers (2008)

In an unpredictable, heterogeneous world, intelligent agents depend on accurate social information; reputation, among the preeminent artifacts to transmit social evaluations, has been receiving growing attention by social scientists. A realistic description of reputation must include inaccurate information; in this paper, based on the distinction between image (agents' believed evaluation of a target) and reputation (circulating evaluation, without reference to the evaluation source), we model the spreading of information in a simple market with the presence of liars and the possibility of retaliation. While fear of retaliation inhibits the spreading of image, the detached character of reputation can be a cause of inaccuracy; The two forces could balance in different settings. In a set of simulations, with agents using the Repage platform for management of image and reputation, we compare the usage of image alone with the usage of both image and reputation. Reputation is shown to be preferable over image to allow for faster discover of scarce good sellers.
Data aggregation and roadside unit placement for a vanet traffic information system
Authors: Christian Lochert, Björn Scheuermann, Christian Wewetzer, Andreas Luebke, Martin Mauve
Venue: Proceedings of the fifth ACM international workshop on VehiculAr Inter-NETworking (2008)

In this paper we investigate how a VANET-based traffic information system can overcome the two key problems of strictly limited bandwidth and minimal initial deployment. First, we present a domain specific aggregation scheme in order to minimize the required overall bandwidth. Then we propose a genetic algorithm which is able to identify good positions for static roadside units in order to cope with the highly partitioned nature of a VANET in an early deployment stage. A tailored toolchain allows to optimize the placement with respect to an application-centric objective function, based on travel time savings. By means of simulation we assess the performance of the resulting traffic information system and the optimization strategy.
XML Document Classification Using Extended VSM
Authors: Jianwu Yang, Fudong Zhang
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)

Structured link vector model (SLVM) is a representation recently proposed for modeling XML documents, which was extended from the conventional vector space model (VSM) by incorporating document structures. In this paper, we describe the classification approach for XML documents based on SLVM and Support Vector Machine (SVM) in INEX 2007 Document Mining Challenge. The experimental results on the challenge's data set show that it outperforms any other approach on XML document classification task at the challenge.
Tree-based methods to model dependent data
Authors: Guillermo Mendez
Venue:  (2008)

It is well known that observations gathered in the real world are not perfectly independent as is assumed in many data analyses. Typically a linear mixed model (LMM) is used when the clustering structure is known and it provides a powerful tool. Small area estimation, that is, predicting population means of a variable of interest, when only a few observations from each population are sampled, is one application of LMMs. In contrast to LMMs, most supervised learning methods do not take into account whether the data have some clustered structure. Random forests, one such method which uses many randomized decision trees, is a popular algorithm used to model large complex data sets because it tends to produce accurate predictions. In this dissertation, two estimators of residual variance are proposed using random forest and they are studied through simulations. A robust modeling technique for mixed-effects data is then proposed, called Mixed Random Forest (MRF), that uses regression trees and accounts for the data's clustered structure. The performance of the MRF algorithm is compared to that of LMMs for different underlying functions and different values of the variance components. The MRF method is shown to perform better in terms of mean squared prediction error (MSPE) when the underlying function is complex, such as conditionally linear. The theoretical MSPE of the predicted group mean is also derived and an estimator of the MSPE is proposed. The performance of the MSPE estimator is investigated via simulations and the results back up the theoretical result. The MRF method is applied to data from the American Community Survey in the small area estimation context. 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
The explosive ordnance disposal robot: CEO mission EOD
Authors: Amon Tunwannarux, Supanunt Tunwannarux
Venue: Proceedings of the 10th WSEAS International Conference on Automatic Control, Modelling & Simulation (2008)

This paper presents the design and development of the explosive ordnance disposal robot named CEO Mission EOD. It is the enhanced project from the rescue robot called CEO Mission IV. The mechanical arm with the X-ray equipment set attached for improvised explosive device inspection (IED inspection) is installed on the track wheel type universal robot platform of the CEO Mission IV robot. The X-ray set which is composed of X-ray source and screen is installed and plugged into the versatile controlling and monitoring system so the X-ray image can be sent to the teleoperator control suitcase wirelessly and easily. Software and hardware interface box is developed in order to control and get image from the X-ray set without its hardware modification. The X-ray source is installed on the top of robot body and the X-ray screen is attached on the tip of four bar linkage mechanical arm. The position of the X-ray screen is controlled by two servo motors which have 2 degrees of freedom. The first degree is the forward angle of four bar linkage and the second degree is the downward linear range of X-ray screen. The maximum height of suspicious object that the robot can inspect is 85 cm. because the design target is for the inspection of the objects which are hidden under the cushion of motorcycle. The user friendly GUI software on the teleoperator control suitcase is developed further from the rescue version. The X-ray control function, the disrupter ignition control function and the X-ray image manipulating function are implemented. The number of exposed X-ray pulses is used as the control factor of the inspection image depth. In addition, the high pressure water jet gun (disrupter) is attached in order to destroy the IED objects. The 100 Volts high voltage is pumped up step by step for the ignition preparation in order to achieve high security. This project is researched and developed for giving to the Royal Thai Air Force. The results are excellent and good enough for using it in the practical applications of the EOD mission in Thailand.
Modeling filled pauses for spontaneous speech recognition applications
Authors: Andrej Žgank, Tomaž Rotovnik, Mirjam Sepesy Maučec
Venue: Proceedings of the 7th WSEAS International Conference on Application of Electrical Engineering (2008)

This paper is focused on acoustic modeling for spontaneous speech recognition applications. This topic is still a very challenging task for speech technology research community. The attributes of spontaneous speech can heavily degrade speech recognizer's accuracy. Filled pauses and onomatopoeias present one of such important attributes. A novel acoustic modeling approach is proposed in this paper, where the filled pauses are modeled using the phonetic broad classes, which corresponds with their acoustic-phonetic properties. The new modeling approach is compared with three other filled pauses modeling methods. All experiments were carried out using a context-dependent Hidden Markov Models based speech recognition system. For training and evaluation, the Slovenian BNSI Broadcast News speech and text database was applied. The database contains manually transcribed recording of TV news shows. The evaluation of the proposed acoustic modeling approach was done with a set of spontaneous speech. The overall best acoustic modeling of filled pauses improved the speech recognizer's word accuracy for 5.70% relatively in comparison to the baseline system.
Meta-programming Applied to Automatic SMP Parallelization of Linear Algebra Code
Authors: Joel Falcou, Jocelyn Sérot, Lucien Pech, Jean-Thierry Lapresté
Venue: Proceedings of the 14th international Euro-Par conference on Parallel Processing (2008)

We describe a software solution to the problem of automatic parallelization of linear algebra code on multi-processor and multi-core architectures. This solution relies on the definition of a domain specific language for matrix computations, a performance model for multi-processor architectures and its implementation using C++ template meta-programming. Experimental results asses this model and its implementation on sample computation kernels.