ppxscal/embedding_network huggingface dataset:
On the Shortest Linear Straight-Line Program for Computing Linear Forms
Authors: Joan Boyar, Philip Matthews, René Peralta
Venue: Proceedings of the 33rd international symposium on Mathematical Foundations of Computer Science (2008)

We study the complexity of the Shortest Linear Program (SLP) problem, which is to minimize the number of linear operations necessary to compute a set of linear forms. SLP is shown to be NP-hard. Furthermore, a special case of the corresponding decision problem is shown to be Max SNP-Complete.Algorithms producing cancellation-free straight-line programs, those in which there is never any cancellation of variables in GF(2), have been proposed for circuit minimization for various cryptographic applications. We show that such algorithms have approximation ratios of at least 3/2 and therefore cannot be expected to yield optimal solutions to non-trivial inputs.
Letters: A new action potential classifier using 3-Gaussian model fitting
Authors: Seong-eun Roh, Joon Hwan Choi, Taejeong Kim
Venue: Neurocomputing (2008)

Spike sorting is a prerequisite for all researches on multi-channel extracellular neural signal recordings. In this paper, we develop a new method for action potential classification. We introduce a mathematical model consisting of three Gaussian waveforms, which appropriately represents the general shapes of action potentials. Then we search for the best-fit waveform for each noise-corrupted spike based on the model, using peak fitting method. These processes result in increased separability among different classes of action potentials. The performance of the proposed method is assessed with synthesized neural recordings composed by spike templates and white Gaussian noise in various SNR environments.
Extension Neural Network Based on Immune Algorithm for Fault Diagnosis
Authors: Changcheng Xiang, Xiyue Huang, Gang Zhao, Zuyuan Yang
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

In this paper, the extension neural network (ENN) is proposed.To tune the weights of the ENN for achieving good clustering performance, the immune algorithm(IA) is applied to learning the ENN's weights, which is replaced the BP algorithm. The affinity degree between the antibody and the antigen is measured by extension distance (ED), which is modified to the conjunction function(CF) in Extensions. The learning speed of the proposed ENN is shown to be faster than the traditional neural networks and other fuzzy classification methods. Moreover, the immune learning algorithm has been proved to have high accuracy and less memory consumption. Experimental results from two different examples verify the effectiveness and applicability of the proposed work.
Optimum Identification of Worm-Infected Hosts
Authors: Noriaki Kamiyama, Tatsuya Mori, Ryoichi Kawahara, Shigeaki Harada
Venue: Proceedings of the 8th IEEE international workshop on IP Operations and Management (2008)

The authors have proposed a method of identifying superspreaders by flow sampling and a method of extracting worm-infected hosts from the identified superspreaders using a white list. However, the problem of how to optimally set parameters, ¿, the measurement period length, m *, the identification threshold of the flow count m within ¿, and H *, the identification probability for hosts with m = m *, remains unsolved. These three parameters seriously affect the worm-spreading property. In this paper, we propose a method of optimally designing these three parameters to satisfy the condition that the ratio of the number of active worm-infected hosts divided by the number of all the vulnerable hosts is bound by a given upper-limit during the time T required to develop a patch or an anti-worm vaccine.
A SOA-Based Vulnerability System Engineering for E-Government Solution
Authors: Namho Yoo
Venue: Proceedings of the 2008 19th International Conference on Systems Engineering (2008)

This paper suggests a Service-Oriented Architecture (SOA)-based Information Assurance (IA) system engineering for system vulnerability in E-Government. Once an information assurance vulnerability notice is given for a system, it is important for reducing massive system engineering efforts for IA vulnerability management. When systems are updated by security patch for mitigating system vulnerability, system engineering efforts based on vulnerability update and request is trivial, in order to increase accuracy, efficiency and effectiveness of software processes. By employing XML technology, it is required to achieve seamless and efficient system engineering between heterogeneous data formats in analysing and exchanging the pertinent information for information assurance vulnerability. Thus, when a system is updated to comply system vulnerability, the proposed SOA-based IA system engineering model and algorithm is proliferating. Then, an executable model for vulnerability system engineering to verify the proposed scheme and testing environment is presented to mitigate vulnerable systems for sustained system.
A Semantic Web Technology Based Approach to Identify Hypertensive Patients for Follow-Up/Recall
Authors: Thusitha De Silva Mabotuwana, Jim Warren
Venue: Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems (2008)

We present an ontology based approach to identify hypertensive patients who show non-adherence to prescribed medication. Using the Web Ontology Language (OWL), we have developed an ontology that includes patient prescription details, medication possession ratios (MPRs) and blood pressure measurements (together with other patient related information) that has been populated with production electronic medical record (EMR) data from a General Medical Practice in New Zealand. We have written queries using the Semantic Query-enhanced Web Rule Language (SQWRL) to query this ontology to determine patients who have lapsed medication while having a low MPR. We also discuss some practical issues related to patient recall based on EMR data, as well as the suitability of the proposed scheme.
A Reduction Attack on Algebraic Surface Public-Key Cryptosystems
Authors: Maki Iwami
Venue: Computer Mathematics: 8th Asian Symposium, ASCM 2007, Singapore, December 15-17, 2007. Revised and Invited Papers (2008)

An algebraic surface public-key cryptosystem was developed by Akiyama and Goto. Its security is based on a decision randomizing polynomial problem which is related to a problem of finding sections on fibered algebraic surfaces which can be reduced to solving a multivariate equation system known to be NP-complete. In the case that the defining equation of a surface used for public-key is in a certain form, Uchiyama and Tokunaga succeeded in attacking in the sense of getting plain texts from corresponding ciphertexts using reductions efficiently without solving section finding problem. In this paper, two algorithms applicable to all cases are suggested. One is the generalization of Uchiyama-Tokunaga's attack from polynomial ring over to polynomial ring over rational function field, and the other takes advantages of Gröbner base techniques so as to deal with in the polynomial ring over . 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 Teleo-Reactive Architecture for Fast, Reactive and Robust Control of Mobile Robots
Authors: Gerhard Gubisch, Gerald Steinbauer, Martin Weiglhofer, Franz Wotawa
Venue: Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence (2008)

One of the elementary tasks of an autonomous mobile robot is the execution of different behavior patterns in order to fulfill a given task. The complexity of this problem is especially high if the robot operates in a dynamic, unpredictable environment and requires the parallel control of multiple actuators. In this paper we present a novel architecture for robust and fast mobile robot control. The architecture is based on Teleo-Reactive Programs. We discuss the benefits and drawbacks of such programs, extend the basic definition for the parallel control of multiple actuators, and propose a new language and a compiler for extended Teleo-Reactive Programs. These tools simplify the creation of new behavior patterns and increase the runtime performance. Finally, we discuss implementation issues of the architecture when applying it to RoboCup Middle-Size soccer robots.
On Fuzzy Projection-Based Utility Decomposition in Compound Multi-agent Negotiations
Authors: Jakub Brzostowski, Ryszard Kowalczyk
Venue: Proceedings of the 12th international Fuzzy Systems Association world congress on Foundations of Fuzzy Logic and Soft Computing (2007)

In the process of compound multi-agent negotiation a number of agents concurrently negotiate with one or more counterparts in order to satisfy the individual preferences that lead to the collective maximization of the overall utility function imposed on the compound service. In order to perform this task the overall utility function has to be decomposed into individual single-service utility functions. This problem is not trivial, especially in compound multi-agent negotiations involving more complex aggregation patters of negotiated issues. In this paper we propose an approach for derivation of the individual utility functions based of the principles of fuzzy set projection. We also propose a way of modifying the initially generated utility functions in the case where the agreement was not reached with those functions, what allows for reaching an agreement in repeated negotiation.
Learning as Data Compression
Authors: Pieter Adriaans
Venue: Proceedings of the 3rd conference on Computability in Europe: Computation and Logic in the Real World (2007)

In this paper I describe the general principles of learning as data compression. I introduce two-part code optimization and analyze the theoretical background in terms of Kolmogorov complexity. The good news is that the optimal compression theoretically represents the optimal interpretation of the data, the bad news is that such an optimal compression cannot be computed and that an increase in compression not necessarily implies a better theory. I discuss the application of these insights to DFA induction.
Self-similarity of Images in the Fourier Domain, with Applications to MRI
Authors: G. S. Mayer, Edward R. Vrscay, M. L. Lauzon, B. G. Goodyear, J. R. Mitchell
Venue: Proceedings of the 5th international conference on Image Analysis and Recognition (2008)

Results presented in this paper represent part of an ongoing research programme dedicated to the resolution enhancement of Fourier domain magnetic resonance (MR) data. Here we explore the use of self-similarity methods that may aid in frequency extrapolation of such data. To this end, we present analytical and empirical results demonstrating the self similarity of complex, Fourier domain MR data.
Predicting the Presence of Oil Slicks After an Oil Spill
Authors: Juan Manuel Corchado, Aitor Mata
Venue: Proceedings of the 9th European conference on Advances in Case-Based Reasoning (2008)

A new predicting system is presented in which the aim is to forecast the presence or not of oil slicks in a certain area of the open sea after an oil spill. In this case, the CBR methodology has been chosen to solve the problem. The system designed to predict the presence of oil slicks wraps other artificial intelligence techniques such as a Growing Radial Basis Function Networks, Growing Cell Structures and Fast Iterative Kernel Principal Components Analysis in order to develop the different phases of the CBR cycle. The proposed system uses information such as sea salinity, sea temperature, wind, currents, pressure, number and area of the slicks.... obtained from various satellites. The system has been trained using data obtained after the Prestige accident. Oil Spill CBR system (OSCBR) has been able to accurately predict the presence of oil slicks in the north west of the Galician coast, using historical data.
A comparative test of web accessibility evaluation methods
Authors: Giorgio Brajnik
Venue: Proceedings of the 10th international ACM SIGACCESS conference on Computers and accessibility (2008)

Accessibility auditors have to choose a method when evaluating accessibility: expert review (a.k.a. conformance testing), user testing, subjective evaluations, barrier walkthrough are some possibilities. However, little is known to date about their relative strengths and weaknesses. Furthermore, what happened for usability evaluation methods is likely to repeat for accessibility: that there is uncertainty about not only pros and cons of methods, but also about criteria to be used to compare them and metrics to measure these criteria. After a quick review and description of methods, the paper illustrates a comparative test of two web accessibility evaluation methods: conformance testing and barrier walkthrough. The comparison aims at determining merits of barrier walkthrough, using conformance testing as a control condition. A comparison framework is outlined, followed by the description of a laboratory experiment with 12 subjects (novice accessibility evaluators), and its results. Significant differences were found in terms of correctness, one of the several metrics used to compare the methods. Reliability also appears to be different.
Fault Tolerance for PetaScale Systems: Current Knowledge, Challenges and Opportunities
Authors: Franck Cappello
Venue: Proceedings of the 15th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface (2008)

The emergence of PetaScale systems reinvigorates the community interest about how to manage failures in such systems and ensure that large applications successfully complete. Existing results for several key mechanisms associated with fault tolerance in HPC platforms will be presented during this talk. Most of these key mechanisms come from the distributed system theory. Over the last decade, they have received a lot of attention from the community and there is probably little to gain by trying to optimize them again. We will describe some of the latest findings in this domain. Unfortunately, despite their high degree of optimization, existing approaches do not fit well with the challenging evolutions of large scale systems. There is room and even a need for new approaches. Opportunities may come from different origins like adding hardware dedicated to fault tolerance or relaxing some of the constraints inherited from the pure distributed system theory. We will sketch some of these opportunities and their associated limitations.
Analysis of the Publication Sharing Behaviour in BibSonomy
Authors: Robert Jäschke, Andreas Hotho, Christoph Schmitz, Gerd Stumme
Venue: Proceedings of the 15th international conference on Conceptual Structures: Knowledge Architectures for Smart Applications (2007)

BibSonomy is a web-based social resource sharing system which allows users to organise and share bookmarks and publications in a collaborative manner. In this paper we present the system, followed by a description of the insights in the structure of its bibliographic data that we gained by applying techniques we developed in the area of Formal Concept Analysis.
Hardness and Approximability of the Inverse Scope Problem
Authors: Zoran Nikoloski, Sergio Grimbs, Joachim Selbig, Oliver Ebenhöh
Venue: Proceedings of the 8th international workshop on Algorithms in Bioinformatics (2008)

For a given metabolic network, we address the problem of determining the minimum cardinality set of substrate compounds necessary for synthesizing a set of target metabolites, called the inverse scope problem. We define three variants of the inverse scope problem whose solutions may indicate minimal nutritional requirements that must be met to ensure sustenance of an organism, with or without some side products. Here, we show that the inverse scope problems are NP-hard on general graphs and directed acyclic graphs (DAGs). Moreover, we show that the general inverse scope problem cannot be approximated within n 1/2 ¿ ¿ for any constant ¿> 0 unless P = NP. Our results have direct implications for identifying the biosynthetic capabilities of a given organism and for designing biochemical experiments.
A Process Meta Model to Support Policy Based Management in Workflow System
Authors: Song Ouyang, Hao Xu
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

Policy-based management and process-based management are two main management paradigms that are widely used in information management systems. The foundation of traditional WfMS is process-based management. In this paper we present a process meta model to support policy based management in WfMS. With the new meta model the system has better flexibility in workflow design time and higher adaptability at run-time. It can also keep the business rules consistent across the whole enterprise and provide a uniform method to deal with business rules, resources and security in workflow system.
Short Note: On preconditioning for a parallel solution of the Richards equation
Authors: Michael Herbst, Swen Gottschalk, Martin Reiíel, Horst Hardelauf, Roy Kasteel, Matthieu Javaux, Jan Vanderborght, Harry Vereecken
Venue: Computers Geosciences (2008)

In this paper, we present a class of preconditioning methods for a parallel solution of the three-dimensional Richards equation. The preconditioning methods Jacobi scaling, block-Jacobi, incomplete lower-upper, incomplete Cholesky and algebraic multigrid were applied in combination with a parallel conjugate gradient solver and tested for robustness and convergence using two model scenarios. The first scenario was an infiltration into initially dry, sandy soil discretised in 500,000 nodes. The second scenario comprised spatially distributed soil properties using 275,706 numerical nodes and atmospheric boundary conditions. Computational results showed a high efficiency of the nonlinear parallel solution procedure for both scenarios using up to 64 processors. Using 32 processors for the first scenario reduced the wall clock time to slightly more than 1% of the single processor run. For scenario 2 the use of 64 processors reduces the wall clock time to slightly more than 20% of the 8 processors wall clock time. The difference in the efficiency of the various preconditioning methods is moderate but not negligible. The use of the multigrid preconditioning algorithm is recommended, since on average it performed best for both scenarios.
Human Actors and Virtual Agents Playing Together to Transform Stage Direction Practices
Authors: Alain Bonardi, Christine Zeppenfeld
Venue: Proceedings of the 7th international conference on Intelligent Virtual Agents (2007)

In this article, we show how approaches based on interactive data-mining may inspire new conceptions of theatre staging. They may be applied thanks to virtual agent systems interacting with comedians. We then give an example of such a theatre production, La Traversée de la nuit.
A Manifolded AdaBoost for Face Recognition
Authors: C. Lu, J. Jiang, G. Feng, C. Qing
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part I (2008)

Manifold learning is an effective dimension reduction method to extract nonlinear structures from high dimensional data. Recently, manifold learning started to attract attention within the research communities of image analysis, computer vision, and document data analysis. In this paper, we propose a Manifolded AdaBoost algorithm towards automatic 2D face recognition by using AdaBoost to fold the manifold space dimension and exploit the strength of both techniques. Experimental results support that the proposed algorithm improve over existing benchmarks in terms of stability and recognition precision rates.
Active-Vision System Reconfiguration for Form Recognition in the Presence of Dynamic Obstacles
Authors: Matthew Mackay, Beno Benhabib
Venue: Proceedings of the 5th international conference on Articulated Motion and Deformable Objects (2008)

This paper presents a novel, agent-based sensing-system reconfigura tion methodology for the recognition of time-varying geometry objects or subjects (targets). A multi-camera active-vision system is used to improve form-recognition performance by selecting near-optimal viewpoints along a prediction horizon. The proposed method seeks to maximize the visibility of such a time-varying geometry in a cluttered, dynamic environment. Simulated experiments clearly show a tangible potential performance gain.
An Actor-Oriented Group Mobility Model for Wireless Ad Hoc Sensor Networks
Authors: Enkhbold Ochirsuren, Leandro Soares Indrusiak, Manfred Glesner
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems Workshops (2008)

High level system modeling has significant impact on the early analysis and evaluation of the embedded electronic systems. Being a class of distributed embedded systems, wireless ad hoc sensor networks can benefit from such system-level modeling, but require a suitable mobility model in order to analyze and design reliable and energy-efficient communication protocols. In this paper we propose an actor-oriented group mobility model for wireless ad hoc sensor networks dedicated to wildlife tracking and monitoring. The model can present individual and group motion according to the specified movement patterns, which in turn are characterized by the average moved distance and the average turning angle.
Approaches for Model Transformation Reuse: Factorization and Composition
Authors: Jesús Sánchez Cuadrado, Jesús García Molina
Venue: Proceedings of the 1st international conference on Theory and Practice of Model Transformations (2008)

Reusability is one of the principal software quality factors. In the context of model driven development (MDD), reuse of model transformations is also considered a key activity to achieve productivity and quality. It is necessary to devote important research efforts to find out appropriate reusability mechanisms for transformation tools and languages. In this paper we present two approaches for reusing model transformation definitions. Firstly, we tackle the creation of related model transformations, showing how the factorization of common parts can be achieved. Secondly, we describe a proposal on the composition of existing, separated transformation definitions so that they can be used to solve a concrete transformation problem. We illustrate both proposals with examples taken from the development of a software product line for adventure games, which has been implemented using the modularization mechanisms of the RubyTL transformation language.