ppxscal/embedding_network huggingface dataset:
Another look at search-based drama management
Authors: Mark J. Nelson, Michael Mateas
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3 (2008)

A drama manager (DM) is a system that monitors an interactive experience, such as a computer game, and intervenes to keep the global experience in line with the author's goals without decreasing a player's interactive agency. In declarative optimization-based drama management (DODM), an author declaratively specifies desired properties of the experience; the DM intervenes in a way that optimizes the specified metric. The initial DODM approach used online search to optimize an experience-quality function. Later work questioned both online search as a technical approach and the experience-quality optimization framework. Recent work on targeted trajectory distribution Markov decision processes (TTD-MDPs) replaced the experience-quality metric with a metric and associated algorithm based on targeting experience distributions. We show that, though apparently quite different on the surface, the original optimization formulation and TTD-MDPs are actually variants of the same underlying search algorithm, and that offline cached search, as is done by the TTD-MDP algorithm, allows the original search-based systems to achieve similar results to TTD-MDPs. Furthermore, we argue that the original idea of optimizing an experience-quality function does not destroy interactive agency, as had previously been argued, and that in fact it can capture that goal directly.
Sampling theorems on bounded domains
Authors: Massimo Fornasier, Laura Gori
Venue: Journal of Computational and Applied Mathematics (2008)

This paper concerns with iterative schemes for the perfect reconstruction from nonuniform sampling of functions belonging to multiresolution spaces on bounded manifolds. Since the iterations converge uniformly, we can produce the corresponding iterative integration schemes that allow to recover the integral of functions belonging to multiresolution spaces from nonuniform sampling. We present also an error analysis and, in particular, we estimate the L^2-error we produce in recovering smooth functions in H^s, but not necessarily in any multiresolution space. The error analysis extends to integrals. Our results hold regardless of the dimension of the domain and for a variety of multiresolution spaces constructed from certain refinable bases formed by the so-called GP-functions.
The IT Organization Modeling and Assessment Tool for IT Governance Decision Support
Authors: Mårten Simonsson, Pontus Johnson, Mathias Ekstedt
Venue: Proceedings of the 20th international conference on Advanced Information Systems Engineering (2008)

This short paper describes the IT Organization Modeling and Assessment Tool (ITOMAT) and how it can be used for IT governance decision making support. ITOMAT consists of an enterprise architecture metamodel that describes IT organizations. ITOMAT further contains a Bayesian network for making predictions on how changes to IT organization models will affect the IT governance performance as perceived by business stakeholders. In order to make such predictions accurately, the network learns from data on previous experience. Case studies at 35 companies have been utilized for calibration of the network.
Challenges and opportunities for improving code-based testing of graphical user interfaces
Authors: Marcel R. Karam, Sergiu M. Dascalu, Rami H. Hazimé
Venue: Journal of Computational Methods in Sciences and Engineering (2006)

The research presented in this paper introduces an execution model for graphical user interfaces (GUIs) that we have developed and formalized as a sequence of actions and finite output states. This model has allowed us to investigate the possibility of applying code-based testing methodologies to testing graphical user interfaces. Our findings highlighted challenges and revealed opportunities to adapt code-based testing methodology to verify the correctness of such interfaces. In particular, the "All-OP-DUs" technique provides important error detection capability and can be applied effectively to test GUIs. This paper also introduces Xtester, the GUI testing tool we are currently building to empirically evaluate our proposed testing criteria.
Novel log management for sender-based message logging
Authors: Jinho Ahn
Venue: Proceedings of the 9th WSEAS International Conference on International Conference on Automation and Information (2008)

Among message logging approaches, volatile logging by sender processes considerably alleviates the normal operation overhead of synchronous logging on stable storage. But, this approach forces each process to maintain log information of its sent messages in its limited volatile memory. This paper presents a novel log management algorithm to effectively eliminate the volatile log information at sender processes on demand without the violation of the system consistency. First, the algorithm gets rid of needless logged messages from the corresponding senders' volatile memories only by piggybacking a vector on their sent messages. This advantageous feature results in no additional message and forced checkpoint. If the more empty buffer space for the volatile logging is needed after the first procedure executed, the next procedure of this proposed algorithm is performed to address this limitation. This procedure uses a vector for saving the size of the log information required to recover every other process and enables the information to be efficiently removed while satisfying the consistency condition.
Improving the Border Detection and Image Enhancement Algorithms in Tableau
Authors: Daniel Marques Oliveira, Rafael Dueire Lins
Venue: Proceedings of the 5th international conference on Image Analysis and Recognition (2008)

Tableau is a software environment for processing images from teaching-boards acquired using portable digital cameras and cell-phones. This paper presents two new algorithms to improve the performance of Tableau. The first one enhances border detection while the second algorithm targets at image enhancement. Tableau has its performance compared to similar commercial softwares.
Multifilters and prefilters: Uniqueness and algorithmic aspects
Authors: Mariantonia Cotronei, Maria Laura Lo Cascio, Tomas Sauer
Venue: Journal of Computational and Applied Mathematics (2008)

In this paper we study the structure of prefilters which ensure a certain approximation order of a given multifilter system. We show how all prefilters can be obtained from the generic one and that in general these prefilters are necessarily rational filters, but point out how a judicious choice of parameters can be used to obtain FIR filters for the approximation orders 1,2,3. Moreover, we illustrate the results by giving prefilters for the standard examples of multiwavelets.
Brief paper: A design methodology for switched discrete time linear systems with applications to automotive roll dynamics control
Authors: Selim Solmaz, Robert Shorten, Kai Wulff, Fiacre í Cairbre
Venue: Automatica (Journal of IFAC) (2008)

In this paper we consider the asymptotic stability of a class of discrete-time switching linear systems, where each of the constituent subsystems is Schur stable. We first present an example to motivate our study, which illustrates that the bilinear transform does not preserve the stability of a class of switched linear systems. Consequently, continuous time stability results cannot be transformed to discrete time analogs using this transformation. We then present a subclass of discrete-time switching systems that arise frequently in practical applications. We prove that global attractivity for this subclass can be obtained without requiring the existence of a common quadratic Lyapunov function (CQLF). Using this result, we present a synthesis procedure to construct switching stabilizing controllers for an automotive control problem, which is related to the stabilization of a vehicle's roll dynamics subject to switches in the center of gravitys (CG) height.
A new method for computer aided detection of pulmonary nodules in X-ray CT images
Authors: Noriyasu Homma, Kazunori Takei, Tadashi Ishibashi
Venue: Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases (2008)

In this paper, we propose a new method for computer aided detection of pulmonary nodules in X-ray CT images to reduce false positive (FP) rate under high true positive (TP) rate conditions. An essential core of the method is to extract and combine two novel and effective features from the raw CT images: One is orientation features of nodules in a region of interest (ROI) extracted by a Gabor filter, while the other is variation of CT values of the ROI in the direction along body axis. By using the extracted features, pattern recognition technics can then used to discriminate between nodule and non-nodule images. Simulation results show that discrimination performance using the proposed features is extremely improved compared to that of the conventional method.
Combining One Class Fuzzy KNN's
Authors: Vito Di Gesù, Giosuè Lo Bosco
Venue: Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory (2007)

This paper introduces a parallel combination of N > 2 one class fuzzy KNN (FKNN) classifiers. The classifier combination consists of a new optimization procedure based on a genetic algorithm applied to FKNN's, that differ in the kind of similarity used. We tested the integration techniques in the case of N = 5 similarities that have been recently introduced to face with categorical data sets. The assessment of the method has been carried out on two public data set, the Masquerading User Data (www.schonlau.net) and the badges database on the UCI Machine Learning Repository (http://www.ics.uci.edu/~mlearn/). Preliminary results show the better performance obtained by the fuzzy integration respect to the crisp one.
Systematic Analysis of Control Panel Interfaces Using Formal Tools
Authors: J. Creissac Campos, M. D. Harrison
Venue: Interactive Systems. Design, Specification, and Verification: 15th International Workshop, DSV-IS 2008 Kingston, Canada, July 16-18, 2008 Revised Papers (2008)

The paper explores the role that formal modeling may play in aiding the visualization and implementation of usability requirements of a control panel. We propose that this form of analysis should become a systematic and routine aspect of the development of such interfaces. We use a notation for describing the interface that is convenient to use by software engineers, and describe a set of tools designed to make the process systematic and exhaustive.
Co-evolutionary Multi-agent System with Predator-Prey Mechanism for Multi-objective Optimization
Authors: Rafał Dreżewski, Leszek Siwik
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I (2007)

Co-evolutionary techniques for evolutionary algorithms allow for the application of such algorithms to problems for which it is difficult or even impossible to formulate explicit fitness function. These techniques also maintain population diversity, allows for speciation and help overcoming limited adaptive capabilities of evolutionary algorithms. In this paper the idea of co-evolutionary multi-agent system with predator-prey mechanism for multi-objective optimization is introduced. In presented system the Pareto frontier is located by the population of agents as a result of co-evolutionary interactions between two species: predators and prey. Results from runs of presented system against test problem and comparison to classical multi-objective evolutionary algorithms conclude the paper.
Feasible Depth
Authors: David Doty, Philippe Moser
Venue: Proceedings of the 3rd conference on Computability in Europe: Computation and Logic in the Real World (2007)

This paper introduces two complexity-theoretic formulations of Bennett's logical depth: finite-state depth and polynomial-time depth. It is shown that for both formulations, trivial and random infinite sequences are shallow, and a slow growth law holds, implying that deep sequences cannot be created easily from shallow sequences. Furthermore, the E analogue of the halting language is shown to be polynomial-time deep, by proving a more general result: every language to which a nonnegligible subset of E can be reduced in uniform exponential time is polynomial-time deep.
Unit Knowledge Management
Authors: Jonathan Stratford, James H. Davenport
Venue: Proceedings of the 9th AISC international conference, the 15th Calculemas symposium, and the 7th international MKM conference on Intelligent Computer Mathematics (2008)

In [9], various observations on the handling of (physical) units in OpenMath were made. In this paper, we update those observations, and make some comments based on a working unit converter [21] that, because of its OpenMath-based design, is modular, extensible and reflective. We also note that some of the issues in an effective converter, such as the rules governing abbreviations, being more linguistic than mathematical, do not lend themselves to easy expression in OpenMath.
Architecture for a Hardware-Based, TCP/IP Content-Processing System
Authors: David V. Schuehler, James Moscola, John W. Lockwood
Venue: IEEE Micro (2004)

A new architecture performs content scanning of TCP flows in highspeed networks. Combining a TCP processing engine, a per-flow state store, and a content-scanning engine, this architecture permits complete payload inspections on 8 million TCP flows at 2.5 Gbps.
Practical Object-Oriented Back-in-Time Debugging
Authors: Adrian Lienhard, Tudor Gîrba, Oscar Nierstrasz
Venue: Proceedings of the 22nd European conference on Object-Oriented Programming (2008)

Back-in-time debuggers are extremely useful tools for identifying the causes of bugs. Unfortunately the "omniscient" approaches that try to remember all previous states are impractical because they consume too much space or they are far too slow. Several approaches rely on heuristics to limit these penalties, but they ultimately end up throwing out too much relevant information. In this paper we propose a practical approach that attempts to keep track of only the relevant data. In contrast to other approaches, we keep object history information together with the regular objects in the application memory. Although seemingly counter-intuitive, this approach has the effect that data not reachable from current application objects (and hence, no longer relevant) is garbage collected. We describe the technical details of our approach, and we present benchmarks that demonstrate that memory consumption stays within practical bounds. Furthermore, the performance penalty is significantly less than with other approaches.
Binary Phase-Coded Sequence Recognition Based on EMD
Authors: Zhibin Yu, Weidong Jin, Chunxia Chen, Taowei Chen
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

Identifying the phase-coded sequence of the binary phase-coded radar signal is a difficultly issue in the radar countermeasures. In this paper, a new approach of abstracting waveform features of the radar signal and identifying the phase-coded sequences is proposed, based on experimental model decomposition. The proposed approach can successfully identify complex phase-coded signal. Moreover, the presented approach can be applied as an integral part of radar signal recognition algorithm to prevent the electronic support measure (ESM) system from taking actions against false radar signal recognition and consequently avoid the waste of the available resources. Computer simulation results have shown that the proposed approach can successfully identify phase-coded sequences, and the recognition accuracy is greater than or equal to 89% when the signal-to-noise ratio is as low as 8 dB.
Map-Based Spatial Navigation: A Cortical Column Model for Action Planning
Authors: Louis-Emmanuel Martinet, Jean-Baptiste Passot, Benjamin Fouque, Jean-Arcady Meyer, Angelo Arleo
Venue: Proceedings of the international conference on Spatial Cognition VI: Learning, Reasoning, and Talking about Space (2008)

We modelled the cortical columnar organisation to design a neuromimetic architecture for topological spatial learning and action planning. Here, we first introduce the biological constraints and the hypotheses upon which our model was based. Then, we describe the learning architecture, and we provide a series of numerical simulation results. The system was validated on a classical spatial learning task, the Tolman Honzik's detour protocol, which enabled us to assess the ability of the model to build topological representations suitable for spatial planning, and to use them to perform flexible goal-directed behaviour (e.g., to predict the outcome of alternative trajectories avoiding dynamically blocked pathways). We show that the model reproduced the navigation performance of rodents in terms of goal-directed path selection. In addition, we present a series of statistical and information theoretic analyses to study the neural coding properties of the learnt space representations.
Quo Vadis computer science: From Turing to personal computer, personal content and collective intelligence
Authors: Epaminondas Kapetanios
Venue: Data Knowledge Engineering (2008)

Since the first formal specifications of modern computing machinery as laid out by Alan Turing and his contemporary fellows, we have been witnessing, during the last three decades, an evolutionary path in computing towards more personalized and contextualized data and knowledge artifacts. Information sharing, co-ordination, co-operation and, to some extent, collaboration among machines has been envisioned for complex problem solving. A prominent example of this problem solving approach has been the Fifth Generation Computer Systems (FGCS) project as launched in Japan in the 1980s and based on the concept of calculation using massive parallelism in logic and hardware. Grid and Distributed Computing, also known as Future Generation Computer Systems, is another similar attempt to exploit massive parallelism in order to solve complex problems. In this article, we explore the notion of Collective Intelligence (CI) in the realm of the Social Web and its potential to become a new computing paradigm for creating solutions or strategies to tackle wicked problems where the synergistic interactions of a group of people with diverse cultural and professional backgrounds are requested.
Productivity improvement of manufacturing SMEs via technology innovation in Korea
Authors: Min Kyun Doo, So Young Sohn
Venue: Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases (2008)

The competitive strength of small and medium enterprises (SMEs) based on technological innovation is one of the most important managerial strategies for holding a dominant position under the fierce global competition. In this study, a decision tree is used to grasp SMEs' innovation activities hierarchically for technological innovation, where the increase of annual productivity rate is used as a proxy target variable for innovation while SMEs' various innovative activities are used as explanatory variables in the form of information acquisition, technological cooperation, technology acquisition, government support, patenting, and compensation. Based on the results of our decision tree analysis, we suggest some insightful strategies for successful innovation of SMEs. It is expected that our study can provide a means for improvement of productivity based on technological innovation.
Evolving strategy for a probabilistic game of imperfect information using genetic programming
Authors: Wojciech Jaśkowski, Krzysztof Krawiec, Bartosz Wieloch
Venue: Genetic Programming and Evolvable Machines (2008)

We provide the complete record of methodology that let us evolve BrilliAnt, the winner of the Ant Wars contest. Ant Wars contestants are virtual ants collecting food on a grid board in the presence of a competing ant. BrilliAnt has been evolved through a competitive one-population coevolution using genetic programming and fitnessless selection. In this paper, we detail the evolutionary setup that lead to BrilliAnt's emergence, assess its direct and indirect human-competitiveness, and describe the behavioral patterns observed in its strategy.
Registration of 3D FMT and CT Images of Mouse Via Affine Transformation with Bayesian Iterative Closest Points
Authors: Xia Zheng, Xiaobo Zhou, Youxian Sun, Stephen T. Wong
Venue: Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks (2007)

It is difficult to directly co-register the 3D FMT (Fluorescence Molecular Tomography) image of a small tumor in a mouse whose maximal diameter is only a few mm with a larger CT image of the entire animal that spans about ten cm. This paper proposes a new method to register 2D flat and projected CT image first to facilitate the registration between small 3D FMT images and large CT images. And a novel algorithm Bayesian Iterative Closest Point (BICP) is introduced and validated in 2D affine registration. The visualization of the alignment of the 3D FMT and CT image through 2D registration shows promising results that would lead to automated 3D registration.
People Side of IT Globalization
Authors: Carol Dekkers
Venue: Proceedings of the 8th international conference on Product-Focused Software Process Improvement (2007)

IT today consists of myriad combinations of outsourcing, insourcing, offshoring, global development teams, and project teams scattered across multiple time zones. Technology abounds, integration and on-time delivery become mission critical, and process improvement demands increase. But... what's the impact of all this advancement on the people involved? As the technical demands for faster, better, and cheaper software increase, so, too, do the needs for effective communication and cultural intelligence. This presentation examines the people side of IT globalization and provides insights and recommendations for succeeding with project teams in a truly global world.
A selective Bayes Classifier for classifying incomplete data based on gain ratio
Authors: Jingnian Chen, Houkuan Huang, Fengzhan Tian, Shengfeng Tian
Venue: Knowledge-Based Systems (2008)

Actual data sets are often incomplete because of various kinds of reasons. Although numerous algorithms about classification have been proposed, most of them deal with complete data. So methods of constructing classifiers for incomplete data deserve more attention. By analyzing main methods of processing incomplete data for classification, this paper presents a selective Bayes Classifier for classifying incomplete data with a simpler formula for computing gain ratio. The proposed algorithm needs no assumption about data sets that are necessary for previous methods of processing incomplete data in classification. Experiments on 12 benchmark incomplete data sets show that this method can greatly improve the accuracy of classification. Furthermore, it can sharply reduce the number of attributes and so can greatly simplify the data sets and classifiers.
Comparing Mixed Interactive Systems for Navigating 3D Environments in Museums
Authors: Emmanuel Dubois, Cédric Bach, Philippe Truillet
Venue: Interactive Systems. Design, Specification, and Verification: 15th International Workshop, DSV-IS 2008 Kingston, Canada, July 16-18, 2008 Revised Papers (2008)

This work aims at developing appropriate Mixed Interaction Systems (MIS) for navigating 3D environments in a science centre context. Due to the wide range and multi-disciplinary design aspects to consider in this context and the lack of expertise in terms of MIS and public context evaluation, designing and evaluating MIS is a complex task. Based on an integrated development process, which combines a design model and a user-testing, this paper presents the outcomes of the comparison of two MIS in terms of performance and satisfaction.