ppxscal/embedding_network huggingface dataset:
Superimposed Code-Based Indexing Method for Extracting MCTs from XML Documents
Authors: Wenxin Liang, Takeshi Miki, Haruo Yokota
Venue: Proceedings of the 19th international conference on Database and Expert Systems Applications (2008)

With the exponential increase in the amount of XML data on the Internet, information retrieval techniques on tree-structured XML documents such as keyword search become important. The search results for this retrieval technique are often represented by minimum connecting trees (MCTs) rooted at the lowest common ancestors (LCAs) of the nodes containing all the search keywords. Recently, effective methods such as the stack-based algorithm for generating the lowest grouped distance MCTs (GDMCTs), which derive a more compact representation of the query results, have been proposed. However, when the XML documents and the number of search keywords become large, these methods are still expensive. To achieve more efficient algorithms for extracting MCTs, especially lowest GDMCTs, we first consider two straightforward LCA detection methods: keyword B + trees with Dewey-order labels and superimposed code-based indexing methods. Then, we propose a method for efficiently detecting the LCAs, which combines the two straightforward indexing methods for LCA detection. We also present an effective solution for the false drop problem caused by the superimposed code. Finally, the proposed LCA detection methods are applied to generate the lowest GDMCTs. We conduct detailed experiments to evaluate the benefits of our proposed algorithms and show that the proposed combined method can completely solve the false drop problem and outperforms the stack-based algorithm in extracting the lowest GDMCTs.
Plenary lecture IV: data mining through data visualisation: computational intelligence approaches
Authors: Colin Fyfe
Venue: Proceedings of the 7th WSEAS International Conference on Software Engineering, Parallel and Distributed Systems (2008)

One of the major tasks today is to create information from data. We do not mean to define information in terms of Shannon or indeed any other mathematical definition but information in terms of the subjective experience of a viewer of the data. People (and probably animals) are very good at pattern recognition; we are far more robust pattern matchers than any current computer programs. Increasingly however, we are dealing with high dimensional (and often high volume) data so to gain intuitions about a data set, we often project data onto low dimensional manifolds. One question which arises then, is what projections to low dimensional manifolds are best in order to present the projected data to a human user. We illustrate several projections which have been found by artificial neural network extensions of Hebbian learning. We then show examples of similar projections found by reinforcement learning; our rationale in this case is that we have agents interacting proactively with a database examining different projections and, without human intervention, getting rewards when the projections reveal some interesting structure. We then give examples of the same projections found by other computational intelligence methods such as the cross entropy method and artificial immune systems. We then examine projections to nonlinear manifolds and show that with a particular model of an underlying latent space, we may identify clusters in data sets when such clusters are not visible in any low dimensional linear projection. Finally we review different data representation techniques: we begin with parallel coordinates and point out some difficulties with this method before reviewing Andrews' Curves, a method from the 1970s which has only become truly practicable with the advent of modern desktop computers. An extension to this method came from Wegman and his colleagues in the 1990s. We also discuss a more recent extension and illustrate three dimensional projections of data samples dancing together.
A Unified Approach to Abstract Interpretation, Formal Verification and Testing of C/C++ Modules
Authors: Jan Peleska
Venue: Proceedings of the 5th international colloquium on Theoretical Aspects of Computing (2008)

In this paper, a unified approach to abstract interpretation, formal verification and testing is described. The approach is applicable for verifying and testing C/C++ functions and methods and complies with the requirements of today's applicable standards for the development of safety-critical systems in the avionics and railway domains. We give an overview over the techniques required and motivate why an integrated approach is not only desirable from the verification specialists' perspective, but also from the tool builders' point of view. Tool support for our approach is available, and it is currently applied in industrial verification projects for railway control systems. All techniques can be adapted to model-based testing in a straightforward way. The objective of this article is to describe the interplay between the methods, techniques and tool components involved; we give references to more comprehensive descriptions of the underlying technical details.
Exposure model for prediction of number of customer reported defects
Authors: Keld Raaschou, Austen W. Rainer
Venue: Proceedings of the Second ACM-IEEE international symposium on Empirical software engineering and measurement (2008)

The paper describes a mathematical model, the Exposure Model, for the prediction of customer reported defects in a large software system. In the model, exposure is defined as the likely fraction of the original defects in the software system that is reported by any customer, in any month and against any version of the system. The basic idea is to try to model exposure as the product of the isolated effects of a few customer- and system-characteristics. The model has been used for several purposes: to better understand defect detection mechanisms, and to better predict the resources required for defect correction. Also, the model has enabled us to make an early estimate of product quality, and thereby give valuable input for other important purposes.
The hB-pi* Tree: An Optimized Comprehensive Access Method for Frequent-Update Multi-dimensional Point Data
Authors: Panfeng Zhou, Betty Salzberg
Venue: Proceedings of the 20th international conference on Scientific and Statistical Database Management (2008)

The R-tree [7] family is the most popular multi-dimensional index method. The R-tree, however, has overlaps among index entries and its index page fanout decreases rapidly as data dimension increases. Furthermore, the R-tree has poor concurrency performance. For frequent-update multi-dimensional point data sets, the hB-pi [5] tree is a better choice than the R*-tree. But the hB-pi tree (and all other kd-tree based access methods) indexes the whole space no matter whether or not there is any data in some sub-spaces. Indexing empty space (i.e., space without data inside) leads to unnecessary data page accesses which increase with growing dimension. This paper addresses this problem by proposing the hB-pi* tree, which efficiently indicates empty spaces and improves range query performances while preserving the hB-pi's high fan-out and good concurrency. Our methods can be applied to any kd-tree based access methods, and our claims are supported by extensive experimental evaluation.
iCat, the chess player: the influence of embodiment in the enjoyment of a game
Authors: André Pereira, Carlos Martinho, Iolanda Leite, Ana Paiva
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3 (2008)

This paper presents an experiment that evaluates and compares the user enjoyment when playing a game of chess in two situations: against a physically embodied robotic agent and against a virtually embodied agent, displayed on screen. The results of the study suggest that embodiment has implications on user enjoyment, as the experience against a robotic agent was classified as more enjoyable than against a virtually embodied agent.
Intelligent Assistance in German Software Development: A Survey
Authors: Jörg Rech, Eric Ras, Björn Decker
Venue: IEEE Software (2007)

Researchers have studied and created a wide range of techniques to support software engineers during development. This article reports on the results of a survey of 135 participants that was conducted in Germany to shed light on the usage of and demand for intelligent assistance in software engineering activities. The survey showed that there's a high demand and acceptance for unobtrusive, quickly executable, and reactive assistance in core software engineering phases to help solve the problems at hand. In addition, several challenges for the future in software engineering work environments are pointed out.
A Prototype Implementation of MPI for SMARTMAP
Authors: Ron Brightwell
Venue: Proceedings of the 15th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface (2008)

Recently the Catamount lightweight kernel was extended to support direct access shared memory between processes running on the same compute node. This extension, called SMARTMAP, allows each process read/write access to another process' memory by extending the virtual address mapping. Simple virtual address bit manipulation can be used to access the same virtual address in a different process' address space. This paper describes a prototype implementation of MPI that uses SMARTMAP for intra-node message passing. SMARTMAP has several advantages over POSIX shared memory techniques for implementing MPI. We present performance results comparing MPI using SMARTMAP to the existing MPI transport layer on a quad-core Cray XT platform.
Utility of multilayer perceptron neural network classifiers in the diagnosis of the obstructive sleep apnoea syndrome from nocturnal oximetry
Authors: J. Víctor Marcos, Roberto Hornero, Daniel Álvarez, Félix del Campo, Carlos Zamarrón, Miguel López
Venue: Computer Methods and Programs in Biomedicine (2008)

The aim of this study is to assess the ability of multilayer perceptron (MLP) neural networks as an assistant tool in the diagnosis of the obstructive sleep apnoea syndrome (OSAS). Non-linear features from nocturnal oxygen saturation (SaO"2) recordings were used to discriminate between OSAS positive and negative patients. A total of 187 subjects suspected of suffering from OSAS (111 with a positive diagnosis of OSAS and 76 with a negative diagnosis of OSAS) took part in the study. The initial population was divided into training, validation and test sets for deriving and testing our neural network classifier. Three methods were applied to extract non-linear features from SaO"2 signals: approximate entropy (ApEn), central tendency measure (CTM) and Lempel-Ziv complexity (LZC). The selected MLP-based classifier provided a diagnostic accuracy of 85.5% (89.8% sensitivity and 79.4% specificity). Our neural network algorithm could represent a useful technique for OSAS detection. It could contribute to reduce the demand for polysomnographic studies in OSAS screening.
Division of Spanish Words into Morphemes with a Genetic Algorithm
Authors: Alexander Gelbukh, Grigori Sidorov, Diego Lara-Reyes, Liliana Chanona-Hernandez
Venue: Proceedings of the 13th international conference on Natural Language and Information Systems: Applications of Natural Language to Information Systems (2008)

We discuss an unsupervised technique for determining morpheme structure of words in an inflective language, with Spanish as a case study. For this, we use a global optimization (implemented with a genetic algorithm), while most of the previous works are based on heuristics calculated using conditional probabilities of word parts. Thus, we deal with complete space of solutions and do not reduce it with the risk to eliminate some correct solutions beforehand. Also, we are working at the derivative level as contrasted with the more traditional grammatical level interested only in flexions. The algorithm works as follows. The input data is a wordlist built on the base of a large dictionary or corpus in the given language and the output data is the same wordlist with each word divided into morphemes. First, we build a redundant list of all strings that might possibly be prefixes, suffixes, and stems of the words in the wordlist. Then, we detect possible paradigms in this set and filter out all items from the lists of possible prefixes and suffixes (though not stems) that do not participate in such paradigms. Finally, a subset of those lists of possible prefixes, stems, and suffixes is chosen using the genetic algorithm. The fitness function is based on the ideas of minimum length description, i.e. we choose the minimum number of elements that are necessary for covering all the words. The obtained subset is used for dividing the words from the wordlist. Algorithm parameters are presented. Preliminary evaluation of the experimental results for a dictionary of Spanish is given.
Diagrammatic Reasoning in Separation Logic
Authors: M. Ridsdale, M. Jamnik, N. Benton, J. Berdine
Venue: Proceedings of the 5th international conference on Diagrammatic Representation and Inference (2008)

A new method of reasoning about simple imperative programs in separation logic is proposed. Rather than proving program specifications symbolically, the hope is to model more closely human diagrammatic reasoning, and to perform automated diagrammatic reasoning in separation logic.
Building Blocks for Computer Vision with Stochastic Partial Differential Equations
Authors: Tobias Preusser, Hanno Scharr, Kai Krajsek, Robert M. Kirby
Venue: International Journal of Computer Vision (2008)

We discuss the basic concepts of computer vision with stochastic partial differential equations (SPDEs). In typical approaches based on partial differential equations (PDEs), the end result in the best case is usually one value per pixel, the "expected" value. Error estimates or even full probability density functions PDFs are usually not available. This paper provides a framework allowing one to derive such PDFs, rendering computer vision approaches into measurements fulfilling scientific standards due to full error propagation. We identify the image data with random fields in order to model images and image sequences which carry uncertainty in their gray values, e.g. due to noise in the acquisition process.The noisy behaviors of gray values is modeled as stochastic processes which are approximated with the method of generalized polynomial chaos (Wiener-Askey-Chaos). The Wiener-Askey polynomial chaos is combined with a standard spatial approximation based upon piecewise multi-linear finite elements. We present the basic building blocks needed for computer vision and image processing in this stochastic setting, i.e. we discuss the computation of stochastic moments, projections, gradient magnitudes, edge indicators, structure tensors, etc. Finally we show applications of our framework to derive stochastic analogs of well known PDEs for de-noising and optical flow extraction. These models are discretized with the stochastic Galerkin method. Our selection of SPDE models allows us to draw connections to the classical deterministic models as well as to stochastic image processing not based on PDEs. Several examples guide the reader through the presentation and show the usefulness of the framework.
Rule Selection for Collaborative Ubiquitous Smart Device Development: Rough Set Based Approach
Authors: Kyoung-Yun Kim, Keunho Choi, Ohbyung Kwon
Venue: Proceedings of the 5th international conference on Ubiquitous Intelligence and Computing (2008)

Comparing with general mobile devices, Ubiquitous Smart Device (USD) is characterized by its capability to generate or use context data for autonomous services, and it provides users with personalized and situation-aware interfaces. While the USD development requires more knowledge-intensive and collaborative environment, the capture, retrieval, accessibility, and reusability of that design knowledge are increasingly critical. In the design collaboration, the cumulative, evolutionary design information and design rules behind the USD design are infrequently captured and often difficult to hurdle due to its complexity. Rough set theory synthesizes approximation of concepts, analyzes data by discovering patterns, and classifies into certain decision classes. Such patterns can be extracted from data by means of methods based on Boolean reasoning and discernibility. In this paper, a rough set theory generates demanded rules and selects the appropriate minimal rules among the demanded rules associated to USD physical component design. The presented method shows the feasibility of rough-set based rule selection considering complex design data objects of USD physical components.
Linking Business Goals to Process Models in Semantic Business Process Modeling
Authors: Ivan Markovic, Marek Kowalkiewicz
Venue: Proceedings of the 2008 12th International IEEE Enterprise Distributed Object Computing Conference (2008)

Broad knowledge is required when a business process is modeled by a business analyst. We argue that existing Business Process Management methodologies do not consider business goals at the appropriate level. In this paper we present an approach to integrate business goals and business process models. We design a Business Goal Ontology for modeling business goals. Furthermore, we devise a modeling pattern for linking the goals to process models and show how the ontology can be used in query answering. In this way, we integrate the intentional perspective into our business process ontology framework, enriching the process description and enabling new types of business process analysis.
Computational models for computing fuzzy cardinal directional relations between regions
Authors: Haibin Sun
Venue: Knowledge-Based Systems (2008)

In this paper, we investigate the deficiency of Goyal and Egenhofer's method for modeling cardinal directional relations between simple regions and provide the computational model based on the concept of mathematical morphology, which can be a complement and refinement of Goyal and Egenhofer's model for crisp regions. To the best of our knowledge, the cardinal directional relations between fuzzy regions have not been modeled. Based on fuzzy set theory, we extend Goyal and Egenhofer's model to handle fuzziness and provide a computational model based on alpha-morphology, which combines fuzzy set theory and mathematical morphology, to refine the fuzzy cardinal directional relations. Then the computational problems are investigated. The definitions for the cardinal directions are not important and we aim to present the methodology and power of using fuzzy morphology to model directional relations. We also give an example of spatial configuration in 2-dimensional discrete space. The experiment results confirm the cognitive plausibility of our computational models.
Modeling Agent-Environment Interactions in Adaptive MAS
Authors: R. Zalila Mili, Renee Steiner
Venue: Engineering Environment-Mediated Multi-Agent Systems: International Workshop, EEMMAS 2007, Dresden, Germany, October 5, 2007. Selected Revised and Invited Papers (2008)

In this paper, we discuss a way to model Agent-Environment interactions in adaptive multi-agent systems. We describe the interactions at various levels of abstraction starting with the highest. For each level, we specify the interactions from four viewpoints functional, behavioral, data and structural. This results into a set of models that capture the main properties of agent-environment interactions.
Describing the Wadge Hierarchy for the Alternation Free Fragment of μ-Calculus (I)
Authors: Jacques Duparc, Alessandro Facchini
Venue: Proceedings of the 4th conference on Computability in Europe: Logic and Theory of Algorithms (2008)

The height of the Wadge Hierarchy for the Alternation Free Fragment of μ-calculus is known to be at least ¿ 0. It was conjectured that the height is exactly ¿ 0. We make a first step towards the proof of this conjecture by showing that there is no $\Delta^\mu_{2}$ definable set in between the levels ¿ ¿ and ¿ 1 of the Wadge Hierarchy of Borel Sets.
Measuring Learning Object Reuse
Authors: Xavier Ochoa, Erik Duval
Venue: Proceedings of the 3rd European conference on Technology Enhanced Learning: Times of Convergence: Technologies Across Learning Contexts (2008)

This paper presents a quantitative analysis of the reuse of learning objects in real world settings. The data for this analysis was obtained from three sources: Connexions' modules, University courses and Presentation components. They represent the reuse of learning objects at different granularity levels. Data from other types of reusable components, such as software libraries, Wikipedia images and Web APIs, were used for comparison purposes. Finally, the paper discusses the implications of the findings in the field of Learning Object research.
Pulsating and Synthetic Impinging Jets
Authors: V. Tesař, Z. Trávníček
Venue: Journal of Visualization (2005)

This is the second part of a survey summarizing authors' research over a period of two decades on enhancing impinging jet heat and/or mass transfer by periodic unsteadiness of nozzle flow rate. The first part, Tesa&rcaron; and Tr&aacute;vn&iacute;&ccaron;ek (2004 b), identified the reasons why pulsation does not always improve the transfer rate: the pulses do not reach up to the wall. The authors nevertheless demonstrate a transfer rate improvement, but in flows with inherent instability found in annular impinging jet. The excitation there causes a topological metamorphosis (reversal of flow character). Also in the extreme case of the synthetic (zero time-mean flow) jets the authors demonstrated a substantial improvement with the annular nozzle. The new approaches presented in the paper offer increased performance of drying and heating/cooling systems, in particular in microdevices with otherwise low or absent levels of natural jet turbulence.
EasyControl --- Universal Control System
Authors: Marcela Fejtová, Petr Novák, Olga Štěpánková
Venue: Proceedings of the 11th international conference on Computers Helping People with Special Needs (2008)

Usually, people access and control technical devices through various peripheries, e.g. PC mouse, computer keyboard or other remote control devices with buttons. Construction of these peripheries assumes that the user can hold them in his/her hand and handle them. Our team has designed and developed several peripheries and helpful software programs, which are ready to provide assistance for people with some disabilities. Our peripheries are named e.g. I4Control®, BlinkSwitch, FingerSwitch and others. Universal control system named EasyControl was developed by our team to enable primary to control PC through several input devices. Using these input devices and system EasyControl user cannot control only our PC but olsou other devices in surounding environment. Some applications and toys were developed to unable users to master some input devices.
Developments in Telecommunications: With a Focus on SS7 Network Reliability, 1 edition
Authors: Gerhard Rufa
Venue:  (2008)

This book summarizes important developments in telecommunications, including SS7 over IP, with a focus on SS7 network reliability. But why is SS7 network security and reliability so important? An SS7network outage results in a breakdown of the signalling between the individual nodes of the network, so that the services of the telecommunication network are no longer available for customers. Apart from the tremendous financial damage to the network operator, the social consequences of such a network breakdown cannot be underestimated. It is shown that the problems can be avoided by suitable network planning, i.e., by assuring bidirectionality, loop-freeness, and sufficient node disjoint routes, or the introduction of new transmission and switching technologies based on ATM and IP networks. The book is written for non-SS7 experts and tries to provide more detailed background knowledge about the SS7 network protocols, the problems, and their solution during the specification work.