ppxscal/embedding_network huggingface dataset:
Φ-Rough Sets Theory and Its Usage on Mining Approximate Dependencies
Authors: Yiyong Xiao, Ikou Kaku, Wenbing Chang
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence (2008)

In this paper, we present an extension of the rough set theory based on similarity relation, called &Phi;-Rough Set Theory, where the indiscernibility relation of the crisp rough set theory is replaced by the notion of &Phi;-approximate equivalence relation. Many of the related concepts of crisp rough set theory are redefined, e.g., equivalence class, lower and upper approximations, &Phi;-reduction, etc. After that, we give an adequate interpretation of approximate dependencies(ADs) and partial approximate dependencies(PADs) from the point of view of &Phi;-RST, which sheds a new light on the functional dependency(FD) theories. The methodologies of &Phi;-Rough Set Theory are used on mining the ADs and PADs, on relational or fuzzy relational schema database. Finally, a numeric example is given to illustrate the process of mining the ADs and PADs in decision system database with similarity relation.
Baroque Technology
Authors: Jan Borchers
Venue: Proceedings of the 5th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems (2008)

As new interactive systems evolve, they frequently hit a sweet spot: A few new tricks to learn, and users gets tremendous benefits, simplifying their lives. But beyond that lies the dark phase of baroque technology: increasing complexity with little payoff. We will look at examples for both sweet-spot and baroque interactive technologies, from GPS devices to window systems, find out how to identify each kind, and become better interaction designers in the process.
Modelling collaborative workflows using recursive ECATNets
Authors: Awatef Hicheur, Kamel Barkaoui
Venue: Proceedings of the 8th international conference on New technologies in distributed systems (2008)

In this paper, we present our modelling formalism namely the Recursive ECATNets, defined on the basis of a sound combination of the ordinary ECATNets (Extended Concurrent Algebraic Term Nets) and the recursive Petri nets. Then, we show their interest for specification and rapid prototyping of cooperative applications particularly in the field of collaborative workflow processes having a dynamic structure.
Visual Image Filtering at the Level of Cortical Input
Authors: Aleksandr Bulatov, Algis Bertulis
Venue: Informatica (2004)

A computational model of the spatial-frequency filtering processes at the level of 4C&beta; layer of the visual striate cortex is being proposed. The model does not interfere with the filtering performed by the cortical receptive fields itself, and the focus of attention is restricted to the cortical input. The model is based on the literature data concerning the conformal mapping of the visual field representation at the primary visual cortex and uniformity of short-range horizontal connections of cortical neurons. To test the model, the illusory figures were used as input stimuli, responses to which were computed and the output patterns constructed. The psychophysical experiments employing the same illusory figures were performed. A rather good correspondence between the model predictions and the experimental measurements of perceived size distortions was observed. In practice, the neurophysiological model provides a simplified and relatively fast algorithm of evaluation of distortions caused by filtering.
A Question Understanding Model Based on Knowledge Points for Chinese Question Answering Service in E-Learning
Authors: Zheng-Hong Wu, Ming Li, Huamin Feng
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

Question answering service in e-learning environment is an important issue. Chinese semantic analysis is a key bottleneck for question answering service to understand question's content. This paper proposes a question understanding model to understand and process syntactic and semantic structure. In this paper, we analyzed a lot of questions from students, and clustered questions based on knowledge points. The question understanding model is made to get question focus and question type. According to question focus and question type, the question answering service can precisely know the question's answer by locating knowledge point's attribute. This method could more perfectly understand semantic content of questions than using pure Chinese semantic analysis. It is very useful for students to study in a self-learning environment.
Research note: On the assessment of input streams for incremental network computing
Authors: Cho-Chin Lin, Hao-Yun Yin
Venue: Journal of Parallel and Distributed Computing (2008)

Network latency is an adverse factor for computations performed across the network. Overlapping computation with communication is an important technique for hiding latency. It has been shown that network latency cannot be effectively hidden without considering the order of sending data [C.-C. Lin, Strategies for achieving high performance incremental computing on a network environment, in: Proc.18th Int'l Conf. on Advanced Information Networking and Applications 1, 2004, pp. 113-118]. However, finding a data-sending order for the input to a task which minimizes the remote execution time for any network traffic pattern is NP-hard [C.-C. Lin, D.-W. Wang, T.-S. Hsu, Bounds on the client-server incremental computing, IEICE Trans. Fundamentals E89-A (5) (2006) 1198-1206]. Thus, heuristic algorithms are often employed to search an optimal input stream. The performance of algorithms relies on an effective mechanism for guiding the search toward a promising direction. In this paper, the computation-progress graph is proposed for transforming an input stream of a task to its corresponding pattern of progressive computations. Then, the assessing function is defined for assigning scores to the found input streams based on the computation-progress graph. Based on the scores, the promising search directions can be determined. Finally, the effectiveness of our assessing function is also demonstrated by the search of the optimal orders for computing the product of two polynomials, matrix multiplication and FFT.
Using Time Series 3D AlertGraph and False Alert Classification to Analyse Snort Alerts
Authors: Shahrulniza Musa, David J. Parish
Venue: Proceedings of the 5th international workshop on Visualization for Computer Security (2008)

A top-level overview of Snort alerts using 3D visual and alert classification is discussed. This paper describes the top-level view (time series 3D AlertGraph) with the integration of alert classification to visualise Snort alerts. The advantages of using this view are (1) It summarised the alerts into different colours to indicate the quantity of alerts from (SRCIP, DPORT) pairs; (2) It used alert classification to highlight the true alerts; (3) Through interaction tools, the alerts can be highlighted according to the source IP, destination IP or destination port;. (4) A large numbers of alerts can be viewed in a single display and (5) A temporal characteristic of attacks can be discovered.
Fault Tolerant Control of a Three Tank Benchmark Using Weighted Predictive Control
Authors: L. F. Mendonça, J. M. Sousa, J. M. Sá Da Costa
Venue: Proceedings of the 12th international Fuzzy Systems Association world congress on Foundations of Fuzzy Logic and Soft Computing (2007)

This paper proposes the application of fault-tolerant control (FTC) using weighted fuzzy predictive control. The FTC approach is based on two steps, fault detection and isolation (FDI) and fault accommodation. Fault detection is performed by a model-based approach using fuzzy modeling. Fault isolation uses a fuzzy decision making approach. The model of the isolated fault is used in fault accommodation with a model predictive control (MPC) scheme. This paper uses a weighted fuzzy predictive control scheme, where fuzzy goals and fuzzy constraints are described in a fuzzy objective function. The criteria (goals or constraints) have an associated weight factor, which are chosen by the decision-maker. Two faults were simulated in a three tank benchmark and the respective fuzzy models were identified. The fuzzy FTC scheme proposed in this paper was able to accommodate the simulated faults.
Examining the Role of Scale in the Context of the Non-Local-Means Filter
Authors: Mehran Ebrahimi, Edward R. Vrscay
Venue: Proceedings of the 5th international conference on Image Analysis and Recognition (2008)

We consider the role of scale in the context of the recently-developed non-local-means (NL-means) filter. A new example-based variant of the NL-means is introduced and results based on same-scale and cross-scale counterparts will be compared for a set of images. We consider the cases in which neighborhoods are taken from the observed image itself as well as from other irrelevant images, varying the smoothness parameter as well. Our experiments indicate that using cross-scale (i.e., downsampled) neighborhoods in the NL-means filter yields results that are quite comparable to those obtained by using neighborhoods at the same-scale.
A Twin for Euler's φ Function in $\mathbb{F}_2[X]$
Authors: R. Durán Díaz, J. Muñoz Masqué, A. Peinado Domínguez
Venue: Proceedings of the 1st international workshop on Arithmetic of Finite Fields (2007)

In this paper, we present a function in $\mathbb{F}_2[X]$ and prove that several of its properties closely resemble those of Euler's ¿ function. Additionally, we conjecture another property for this function that can be used as a simple primality test in $\mathbb{F}_2[X]$, and we provide numerical evidence to support this conjecture. Finally, we further apply the previous results to design a simple primality test for trinomials.Mathematics Subject Classification 2000: Primary 13P05; Secondary 11T06, 12E05, 15A04.
A Musical Framework with Swarming Robots
Authors: Yuta Uozumi, Masato Takahashi, Ryoho Kobayashi
Venue: Computer Music Modeling and Retrieval. Sense of Sounds: 4th International Symposium, CMMR 2007, Copenhagen, Denmark, August 27-31, 2007. Revised Papers (2008)

In this paper, we describe an approach to a musical framework with interactions among numerous physical autonomous devices. The devices behave as metaphors of life and self-organize sounds and rhythm. Users can manipulate the system by affecting the interactions of the devices. We implemented the system as two different installations.
A Lagrangian particle method for the simulation of linear and nonlinear elastic models of soft tissue
Authors: Simone E. Hieber, Petros Koumoutsakos
Venue: Journal of Computational Physics (2008)

We present a novel Lagrangian particle method for the simulation of linear and nonlinear elastic models of soft tissue. Linear solids are represented by the Lagrangian formulation of the stress-strain relationship that is extended to nonlinear solids by using the Lagrangian evolution of the deformation gradient described in a moving framework. The present method introduces a level set description, along with the particles, to capture the body deformations and to enforce the boundary conditions. Furthermore, the accuracy of the method in cases of large deformations is ensured by implementing a particle remeshing procedure. The method is validated in several benchmark problems, in two and three dimensions and the results compare well with the results of respective finite elements simulations. In simulations of large solid deformation under plane strain compression, the finite element solver exhibits spurious structures that are not present in the Lagrangian particle simulations. The particle simulations are compared with experimental results in an aspiration test of liver tissue.
Architectural Risk Analysis of Software Systems Based on Security Patterns
Authors: Spyros T. Halkidis, Nikolaos Tsantalis, Alexander Chatzigeorgiou, George Stephanides
Venue: IEEE Transactions on Dependable and Secure Computing (2008)

The importance of software security has been profound, since most attacks to software systems are based on vulnerabilities caused by poorly designed and developed software. Furthermore, the enforcement of security in software systems at the design phase can reduce the high cost and effort associated with the introduction of security during implementation. For this purpose, security patterns that offer security at the architectural level have been proposed in analogy to the well known design patterns. The main goal of this paper is to perform risk analysis of software systems based on the security patterns they contain. The first step is to determine to what extent specific security patterns shield from known attacks. This information is fed to a mathematical model based on fuzzy set theory and fuzzy fault trees in order to compute the risk for each category of attacks. The whole process has been automated using a methodology that extracts the risk of a software system by reading the class diagram of the system under study.
On Fault Tolerance in Law-Governed Multi-agent Systems
Authors: Maíra A. C. Gatti, Gustavo R. Carvalho, Rodrigo B. Paes, Carlos J. Lucena, Jean-Pierre Briot
Venue: Software Engineering for Multi-Agent Systems V: Research Issues and Practical Applications (2007)

The dependability of open multi-agent systems is a particular concern, notably because of their main characteristics as decentralization and no single point of control. This paper describes an approach to increase the availability of such systems through a technique of fault tolerance known as agent replication, and to increase their reliability through a mechanism of agent interaction regulation called law enforcement mechanism. Therefore, we combine two frameworks: one for law enforcement, named XMLaw, and another for agent adaptive replication, named DimaX, in which the decision of replicating an agent is based on a dynamic estimation of its criticality. Moreover, we will describe how we can reuse some of the information expressed by laws in order to help at the estimation of agent criticality, thus providing a better integration of the two frameworks. At the end of the paper, we recommend a means to specify criticality monitoring variation through a structured argumentation approach that documents the rationale around the decisions of the law elements derivation.
Turning Software into a Service
Authors: Mark Turner, David Budgen, Pearl Brereton
Venue: Computer (2003)

The authors explore the concept of software as a service, which envisages a demand-led software market in which businesses assemble and provide services when needed to address a particular requirement. The SaaS vision focuses on separating the possession and ownership of software from its use. Delivering software's functionality as a set of distributed services that can be configured and bound at delivery time can overcome many current limitations constraining software use, deployment, and evolution.
"Off-line": The 2004 European parliamentary elections on television news in the enlarged Europe
Authors: Claes H. de Vreese, Susan Banducci, Holli A. Semetko, Hajo G. Boomgaarden
Venue: Information Polity (2005)

We outline the competitive television news market in the enlarged European Union (EU) and demonstrate the continued importance of traditional media, in particular television, in the context of proliferation in choice of news sources, including on-line news services. Drawing upon a content analysis of the most widely watched evening television news programs in each of the EU countries, we find that on average, EU news in 2004 was more visible in the new member states than in the old member states. The level of coverage in the old member states was slightly higher in 2004 compared to 1999. Looking at individual countries there was considerable variation with some countries (e.g., Greece, Denmark, Slovakia, and Austria) devoting about 20% of the news to the elections and others (e.g., Germany, Belgium, and the Czech Republic) devoting about 5% or less to the elections.
Nonlinear Principal Manifolds --- Adaptive Hybrid Learning Approaches
Authors: Hujun Yin
Venue: Proceedings of the 3rd international workshop on Hybrid Artificial Intelligence Systems (2008)

Dimension reduction has long been associated with retinotopic mapping for understanding cortical maps. Multisensory information is processed, fused, fed and mapped to a 2-D cortex in a near-optimal information preserving manner. Data projection and visualization, inspired by this mechanism, are playing an increasingly important role in many computational applications such as cluster analysis, classification, data mining, knowledge management and retrieval, decision support, marketing, image processing and analysis. Such tasks involving either visual and spatial analysis or reduction of features or volume of the data are essential in many fields from biology, neuroscience, decision support, to management science. The topic has recently attracted a great deal of attention. There have been considerable advances in methodology and techniques for extracting nonlinear manifold as to reduce data dimensionality and a number of novel methods have been proposed from statistics, geometry theory and adaptive neural networks. Typical approaches include multidimensional scaling, nonlinear PCA and principal curve/surface. This paper provides an overview on this challenging and emerging topic. It discusses various recent methods such as self-organizing maps, kernel PCA, principal manifold, isomap, local linear embedding, Laplacian eigenmap and spectral clustering, and many of them can be seen as a combined, adaptive learning framework. Their usefulness and potentials will be presented and illustrated in various applications.
A neural model for stereo transparency with the population of the disparity energy models
Authors: Osamu Watanabe
Venue: Neurocomputing (2008)

The disparity energy model can interpret a variety of physiological properties of binocular neurons in the early visual cortex quantitatively. Therefore, many physiologically plausible models for binocular stereopsis employed the disparity energy model as a model neuron. These models can explain a variety of psychological findings concerning stereo perception. However, most of the models cannot handle with stereo transparency. Here, we develop a simple stereo model for transparency perception with the hybrid-type disparity energy model, and examine the ability to detect overlapping disparities. Computer simulations showed that the model properties of transparency detection are consistent with many psychophysical findings concerning stereo transparency.
Using MPI-2: A Problem-Based Approach
Authors: William D. Gropp, Ewing Lusk
Venue: Proceedings of the 14th European PVM/MPI User's Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface (2007)

MPI-2 introduced many new capabilities, including dynamic process management, one-sided communication, and parallel I/O. Implementations of these features are becoming widespread. This tutorial shows how to use these features by showing all of the steps involved in designing, coding, and tuning solutions to specific problems. The problems are chosen for their practical use in applications as well as for their ability to illustrate specific MPI-2 topics. Complete examples that illustrate the use of MPI one-sided communication and MPI parallel I/O will be discussed and full source code will be made available to the attendees. Each example will include a hands-on lab session; these sessions will also introduce the use of performance and correctness debugging tools that are available for the MPI environment. Guidance on tuning MPI programs will be included, with examples and data from MPI implementations on a variety of parallel systems, including Sun, IBM, SGI, and clusters. Examples in C, Fortran, and C++ will be included. Familiarity with basic MPI usage will be assumed.
Classification of Benign and Malignant Masses in Ultrasound Breast Image Based on Geometric and Echo Features
Authors: Gobert N. Lee, Daisuke Fukuoka, Yuji Ikedo, Takeshi Hara, Hiroshi Fujita, Etsuo Takada, Tokiko Endo, Takako Morita
Venue: Proceedings of the 9th international workshop on Digital Mammography (2008)

The aim of this paper is to study the use of geometric and echo features in classifying masses in ultrasound images as benign or malignant. While mammography is very effective in detecting masses and other lesions, breast ultrasound is a valuable adjunct in distinguishing solid and fluid-filled masses where the former is mostly malignant and the latter benign. Six features including two geometric features and four echo features derived from the segmented mass and its neighboring regions are employed in this study. They are the compactness and orientation of the mass, two intensity ratios of the mass and its neighboring regions, homogeneity, and depth-to-width ratio of the mass. Linear discriminant analysis and receiver operating characteristic (ROC) analysis are employed for classification and performance evaluation. The area under the ROC curve (AUC) has a value of 0.940 using all breast masses for training and testing and 0.923 using the leave-one-mass-out cross-validation method. Clinically significance of the results will be evaluated using a larger dataset.
Weighted Nearest Neighbor Algorithms for the Graph Exploration Problem on Cycles
Authors: Yuichi Asahiro, Eiji Miyano, Shuichi Miyazaki, Takuro Yoshimuta
Venue: Proceedings of the 33rd conference on Current Trends in Theory and Practice of Computer Science (2007)

In the graph exploration problem, a searcher explores the whole set of nodes of an unknown graph. The searcher is not aware of the existence of an edge until he/she visits one of its endpoints. The searcher's task is to visit all the nodes and go back to the starting node by traveling as a short tour as possible. One of the simplest strategies is the nearest neighbor algorithm (NN), which always chooses the unvisited node nearest to the searcher's current position. The weighted NN (WNN) is an extension of NN, which chooses the next node to visit by using the weighted distance. It is known that WNN with weight 3 is 16-competitive for planar graphs. In this paper we prove that NN achieves the competitive ratio of 1.5 for cycles. In addition, we show that the analysis for the competitive ratio of NN is tight by providing an instance for which the bound of 1.5 is attained, and NN is the best for cycles among WNN with all possible weights. Furthermore, we prove that no online algorithm is better than 1.25-competitive.
Modelling an Environmental Knowledge-Representation System
Authors: Nicolas Padilla, Luis Iribarne, Jose A. Asensio, Francisco J. Muñoz, Rosa Ayala
Venue: Proceedings of the 1st world summit on The Knowledge Society: Emerging Technologies and Information Systems for the Knowledge Society (2008)

Environmental Management Systems (EMS) are social-technical systems with a variety of final users and actors that cooperate with each other and interact with the system for decision-making, problems resolution, etc. The modelling of these systems using formal methods provides mechanisms and tools that guarantee the users a correct deployment and use of it. In this paper we showing environmental knowledge modelling accomplished in the SOLERES project, a spatio-temporal information system for environmental management, a cooperative system based on multi-agent architectures and intelligent agents. The system modelling uses UML for knowledge representation, and Model-Driven Engineering (MDE) perspective --based on the OMG classical Model-driven Architecture (MDA)-- to create OWL/XML ontology automatically.