ppxscal/embedding_network huggingface dataset:
Marking the Close analysis in Thai Bond Market Surveillance using association rules
Authors: Janjao Mongkolnavin, Sunti Tirapat
Venue: Expert Systems with Applications: An International Journal (2009)

This study investigates the opportunity of employing data mining techniques as a supplement to traditional techniques, such as economic modeling, to detect misconduct in the Thai Bond Market. In the study, association rules are used to detect ''Mark the Close'' conduct in the Thai Bond Market Association (ThaiBMA) surveillance system. The experiment was conducted on 54,334 trading transactions reported to the ThaiBMA in the year 2005. The result shows that association rules can be effectively used to provide a short list of traders who are likely to behave in such a way.
Evolutionary multiobjective fuzzy system design
Authors: Hisao Ishibuchi, Yusuke Nojima
Venue: Proceedings of the 3rd International Conference on Bio-Inspired Models of Network, Information and Computing Sytems (2008)

This paper briefly reviews genetic algorithm-based approaches to the design of fuzzy systems. In the 1990s, genetic algorithms were mainly used for the accuracy maximization of fuzzy systems. Various aspects of fuzzy systems were optimized by genetic algorithms such as the fuzzy partition of each input variable, the number of fuzzy rules, and the consequent part of each fuzzy rule. The accuracy maximization of fuzzy systems for training data, however, tends to increase their complexity. That is, the accuracy maximization often degrades the interpretability of fuzzy systems through the increase in their complexity. Some studies in the late 1990s tried to find a good tradeoff (i.e., compromise) between the accuracy and the complexity of fuzzy systems. The latest trend in the design of fuzzy systems is their evolutionary multiobjective design. A number of non-dominated fuzzy systems with different accuracy-complexity tradeoffs can be obtained by a single run of multiobjective approaches. In this paper, we briefly review the above-mentioned main stream of research on fuzzy system design.
Eddy current system for material inspection and flaw visualization
Authors: R. Bachnak, S. King, W. Maeger, T. Nguyen
Venue: Proceedings of the 6th conference on Applications of electrical engineering (2007)

Eddy current methods have been successfully used in a variety of non-destructive evaluation applications including detection of cracks, measurements of material thickness, determining metal thinning due to corrosion, measurements of coating thickness, determining electrical conductivity, identification of materials, and detection of corrosion in heat exchanger tubes. This paper describes the development of an eddy current prototype that combines positional and eddy-current data to produce a C-scan of tested material. The preliminary system consists of an eddy current probe, a position tracking mechanism, and basic data visualization capability. Initial test results of the prototype are presented in this paper.
Comparative analysis of clicks and judgments for IR evaluation
Authors: Jaap Kamps, Marijn Koolen, Andrew Trotman
Venue: Proceedings of the 2009 workshop on Web Search Click Data (2009)

Queries and click-through data taken from search engine transaction logs is an attractive alternative to traditional test collections, due to its volume and the direct relation to end-user querying. The overall aim of this paper is to answer the question: How does click-through data differ from explicit human relevance judgments in information retrieval evaluation? We compare a traditional test collection with manual judgments to transaction log based test collections---by using queries as topics and subsequent clicks as pseudo-relevance judgments for the clicked results. Specifically, we investigate the following two research questions: Firstly, are there significant differences between clicks and relevance judgments. Earlier research suggests that although clicks and explicit judgments show reasonable agreement, clicks are different from static absolute relevance judgments. Secondly, are there significant differences between system ranking based on clicks and based on relevance judgments? This is an open question, but earlier research suggests that comparative evaluation in terms of system ranking is remarkably robust.
Towards an Interpretation of Intestinal Motility Using Capsule Endoscopy Image Sequences
Authors: Hai Vu, Tomio Echigo, Ryusuke Sagawa, Keiko Yagi, Masatsugu Shiba, Kazuhide Higuchi, Tetsuo Arakawa, Yasushi Yagi
Venue: Proceedings of the 3rd Pacific Rim Symposium on Advances in Image and Video Technology (2009)

Human intestinal motility is presented by the propagation of peristaltic waves with their frequencies gradually decreasing along the length of the small bowel. This paper describes a heuristic method, which can be used towards interpreting intestinal motility through recognizing their frequency characteristics from capsule endoscopy image sequences. First, image features that reflect peristaltic activities are extracted to build a functional signal. Then, a Multi-Resolution Analysis technique in the wavelet domain is used to decompose the functional signal taking into account the non-stationary nature of intestinal motility. For peristaltic waveform recognition, the method relies on the principle of peak detections from the decomposed signals. Each waveform is detected when it exceeds a baseline level. The frequency characteristics are interpreted through analysis of the waveform appearance and their velocity propagation. Three healthy sequences were tested in experiments. The estimated trends of the peristaltic wave propagation from the experimental results show a frequency gradient, which follows the well-recognized characteristics of intestinal motility propagation. Therefore, this study is the first demonstration of a detailed interpretation of intestinal motility, and we suggest that further research focuses on intestinal motility dysfunctions.
Path following, real-time, embedded fuzzy control of a mobile platform Pioneer 3-DX
Authors: A. Filipescu, I. Susnea, Al. Stancu, G. Stamatescu
Venue: Proceedings of the 8th conference on Systems theory and scientific computation (2008)

This paper presents a microcontroller implementation of a fuzzy logic control algorithm applied to the mobile platform. As mobile platform, Pioneer 3-DX has been chosen. A robotic manipulator, Pioneer 5- DOF Arm is on the platform. Pioneer 3-DX is a wheeled mobile robot (WMR) with two driving wheels and a caster wheel. The design and implementation of the fuzzy controller is described. Both speed and position are achieved using the same real-time fuzzy controller. The description starts with an example for a circular path following, then presents an implementation of the algorithms for following a generalized curve path.
An Extended Vector Space Model for XML Information Retrieval
Authors: Yongming Guo, Dehua Chen, Jiajin Le
Venue: Proceedings of the 2009 Second International Workshop on Knowledge Discovery and Data Mining (2009)

With the emergence of more and more XML documents, effectively and efficiently retrieving information from XML documents has become an active research area. Since XML documents lie between structured data and unstructured data which describe both content and structure, it is a huge challenge for effectively and efficiently retrieving information from XML documents. This paper develops a novel retrieval model named as Extend Vector Space Model which effectively combines XPath and Vector Space Model for XML information retrieval. A prototype system for XML information retrieval based on this retrieval model has been implemented, and several corresponding algorithms have been introduced. The experiments show that this model has effectively improved recall and precision.
Run-time reconfigurable RTOS for reconfigurable systems-on-chip
Authors: Marcelo Götz, Achim Rettberg, Carlos Eduardo Pereira, Franz J. Rammig
Venue: Journal of Embedded Computing (2009)

High computational performance and flexibility are the requirements of nowadays embedded systems and they are increasing constantly. Moreover, a single architecture must be able to support different applications with dynamically requirements (changing environments). Reconfigurable computing based on hybrid architectures, comprising general purpose processor (CPU) and Field Programmable Gate Array (FPGA), is very attractive because it can provide high computational performance as well as flexibility to support the requirements of today's embedded systems. As an Operating System (OS) is desired to provide support for such systems, it has to use the available resources in an optimal way (competing with the application), since an embedded system architecture usually lack of resources. Therefore, we present here our approach towards a reconfigurable RTOS that is able to distribute itself over a hybrid architecture (comprising FPGA and CPU). In this work we will present the main concepts and methods used to achieve the desired RTOS. Moreover, we present some preliminary evaluation results which show the applicability of our approach.
Learning the Latent Semantic Space for Ranking in Text Retrieval
Authors: Jun Yan, Shuicheng Yan, Ning Liu, Zheng Chen
Venue: Proceedings of the 2008 Eighth IEEE International Conference on Data Mining (2008)

Subspace learning techniques for text analysis, such as Latent Semantic Indexing (LSI), have been widely studied in the past decade. However, to our best knowledge, no previous study has leveraged the rank information for subspace learning in ranking tasks. In this paper, we propose a novel algorithm, called Learning Latent Semantics for Ranking (LLSR), to seek the optimal Latent Semantic Space tailored to the ranking tasks. We first present a dual explanation for the classical Latent Semantic Indexing (LSI) algorithm, namely learning the so-called Latent Semantic Space (LSS) to encode the data information. Then, to handle the increasing amount of training data for the practical ranking tasks, we propose a novel objective function to derive the optimal LSS for ranking. Experimental results on two SMART sub-collections and a TREC dataset show that LLSR effectively improves the ranking performance compared with the classical LSI algorithm and ranking without subspace learning.
Automated generation and parameterization of throughput models for semiconductor tools
Authors: Jan Lange, Kilian Schmidt, Roy Börner, Oliver Rose
Venue: Proceedings of the 40th Conference on Winter Simulation (2008)

Cluster tools play an important role in modern semiconductor fabs. Due to their complexity in configuration and their varying material flow, the creation of accurate throughput models for cluster tools is a demanding task. Proposed analytical approaches are either quite intricate and require manual maintenance process, or are inexact due to reliance on lot-level events. This paper presents an approach for the automated generation and parameterization of detailed cluster tool models based on bottleneck analysis. Equipment configuration as well as all throughput model base data is extracted from recent equipment reporting data.
Defining the notion of &#x2018;Information Content&#x2019; and reasoning about it in a database
Authors: Kaibo Xu, Junkang Feng, Malcolm Crowe
Venue: Knowledge and Information Systems (2009)

The problem of &#x2018;information content&#x2019; of an information system appears elusive. In the field of databases, the information content of a database has been taken as the instance of a database. We argue that this view misses two fundamental points. One is a convincing conception of the phenomenon concerning information in databases, especially a properly defined notion of &#x2018;information content&#x2019;. The other is a framework for reasoning about information content. In this paper, we suggest a modification of the well known definition of &#x2018;information content&#x2019; given by Dretske(Knowledge and the flow of information,1981). We then define what we call the &#x2018;information content inclusion&#x2019; relation (IIR for short) between two random events. We present a set of inference rules for reasoning about information content, which we call the IIR Rules. Then we explore how these ideas and the rules may be used in a database setting to look at databases and to derive otherwise hidden information by deriving new relations from a given set of IIR. A prototype is presented, which shows how the idea of IIR-Reasoning might be exploited in a database setting including the relationship between real world events and database values.
Vertex and edge covers with clustering properties: Complexity and algorithms
Authors: Henning Fernau, David F. Manlove
Venue: Journal of Discrete Algorithms (2009)

We consider the concepts of a t-total vertex cover and a t-total edge cover(t>=1), which generalise the notions of a vertex cover and an edge cover, respectively. A t-total vertex (respectively edge) cover of a connected graph G is a vertex (edge) cover S of G such that each connected component of the subgraph of G induced by S has at least t vertices (edges). These definitions are motivated by combining the concepts of clustering and covering in graphs. Moreover they yield a spectrum of parameters that essentially range from a vertex cover to a connected vertex cover (in the vertex case) and from an edge cover to a spanning tree (in the edge case). For various values of t, we present NP-completeness and approximability results (both upper and lower bounds) and FPT algorithms for problems concerned with finding the minimum size of a t-total vertex cover, t-total edge cover and connected vertex cover, in particular improving on a previous FPT algorithm for the latter problem.
Towards Information Flow Properties for Distributed Systems
Authors: Roberto Gorrieri, Fabio Martinelli, Ilaria Matteucci
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2009)

In this paper we present a framework for the specification of information flow properties for distributed systems. We consider partially specified distributed systems in which there are several unspecified components located in different places. As a case study, in this paper we consider the notion of Non Deducibility on Composition, NDC for short, originally proposed for nondeterministic systems and based on trace semantics. We study how this information flow property can be extended in order to deal also with distributed partially specified systems. In particular, we adapt the NDC property to distributed systems by distinguishing between two different approaches. The first one we call centralized NDC, according to which there is just one unspecified global component that has complete control of the n distributed locations where interaction occurs between the system and the unspecified component. The second one is called distributed NDC, according to which there is one unspecified component for each distributed location, and the n unspecified components are completely independent, i.e., they cannot coordinate or cooperate each other. Surprisingly enough, we prove that centralized NDC is as discriminating as decentralized NDC. However, when we move to Bisimulation-based Non-Deducibility on Composition, BNDC for short, the situation is completely different. Indeed, we prove that centralized BNDC is strictly finer than decentralized BNDC, hence proving the quite expected fact that a system that can resist to coordinated attacks is also able to resist to simpler attacks performed by independent entities.
A generalized linear integrate-and-fire neural model produces diverse spiking behaviors
Authors: Ştefan Mihalaş, Ernst Niebur
Venue: Neural Computation (2009)

For simulations of neural networks, there is a trade-off between the size of the network that can be simulated and the complexity of the model used for individual neurons. In this study, we describe a generalization of the leaky integrate-and-fire model that produces a wide variety of spiking behaviors while still being analytically solvable between firings. For different parameter values, the model produces spiking or bursting, tonic, phasic or adapting responses, depolarizing or hyperpolarizing after potentials and so forth. The model consists of a diagonalizable set of linear differential equations describing the time evolution of membrane potential, a variable threshold, and an arbitrary number of firing-induced currents. Each of these variables is modified by an update rule when the potential reaches threshold. The variables used are intuitive and have biological significance. The model's rich behavior does not come from the differential equations, which are linear, but rather from complex update rules. This single-neuron model can be implemented using algorithms similar to the standard integrate-and-fire model. It is a natural match with event-driven algorithms for which the firing times are obtained as a solution of a polynomial equation.
Human or Automatic Answers? A User's Based Study
Authors: Cristina González-Caro, Mari-Carmen Marcos, Liliana Calderón-Benavides, Ricardo Baeza-Yates
Venue: Proceedings of the 2008 Latin American Web Conference (2008)

Understanding the different ways of the information seeking behavior of users, and their implications is an important challenge of Web Information Services. In this paper we examine the suitability of Web Search Engines (SE)and Community Question-Answering (community QA) to satisfy the different expectations of users: queries expecting knowledge-based answers, and queries expecting subjective opinion-based answers. From this categorization, we conducted a user study of the results obtained from three Web SE, and three Communities QA. In this way, we found that SE result in a better alternative when the query is designed to get a uni-objective answer, while communities QA provide better results if the question gets multi-objective answers. On the other hand, when the query expects a subjective answer, none of these systems provides a very effective answer that can fulfill the expectations from the user. Knowing more about the type of queries that require human support would be useful to improve the user search experience in SE.
NS2 Extension for Multi-channel MAC Simulation Model
Authors: Wei Geng-Yu, Wang Hua, Li Xiao-Xiao, Xu Liu-Tong
Venue: International Journal of Distributed Sensor Networks (2009)

In order to improve network performance of delay and throughput, an increasing number of networks begin to support multi-channel communications. Although Network Simulator 2 (NS2) has been the dominant network simulation tool, it does not provide native support for multi-channel simulation. Existing works on extending NS2, such as Hyacinth's and Ramon's contributions, show apparent limitations for usage. This paper proposes a novel extension of NS2, named Multi-channel MAC Simulation Model (MMSM), which defines the facilities for multi-channel MAC protocol simulation. This paper describes the initiative, simulation model architecture of MMSM. Based on extensions of NS2 MobileNode architecture, MMSM has features of flexibility of configuration and transparency to the upper layer. MMSM defines one MAC entity associated with a number of NetIF (Network Interface) entities and each NetIF adhered to one channel. So the mobile node has the ability to send and receive packets simultaneously through multiple channels to or from different adjoining nodes. Thus MMSM provides strong support for simulating newly designed multi-channel MAC protocols such as MAC over Multiple Input Multiple Output (MIMO) or MIMO-like mechanisms. MMSM not only makes the specific simulation available, but also keeps the upper layer facilities unchanged as usual when implementing multi-channel simulation. The paper also describes the implementation of MMSM in NS2 (version 2.29). Modifications are carried out both on TCL and on C++ codes. In TCL level ns-mobilenode.tcl and ns-lib.tcl are modified to assemble the multi-channel components and to make TCL scripts to support multi-channel configuration. In C++ level mac.{h,cc}, mobilenode.{h,cc} and channel.{h,cc} are modified to add the channel selection algorithm and to manage the multi-channel node lists. Based on modifications of NS2 described above, researchers can implement their multi-channel MAC protocols conveniently. To validate the implementation of MMSM, two existing MAC protocols in NS-2.29, the Mac802_11 and Tdma, are extended to have the capability of multi-channel processing. Two typical scenarios are chosen to run the simulation on both the multi-channel and the single channel. Simulation results show that the network throughput of multi-channel MAC is enhanced over the single channel MAC, and therefore it proves the multi-channel capability of MMSM.
Wavelet-based dynamic time warping
Authors: Sylvio Barbon,  Jr., Rodrigo Capobianco Guido, Lucimar Sasso Vieira, Everthon Silva Fonseca, Fabrício Lopes Sanchez, Paulo Rogério Scalassara, Carlos Dias Maciel, José Carlos Pereira, Shi-Huang Chen
Venue: Journal of Computational and Applied Mathematics (2009)

Dynamic Time Warping (DTW), a pattern matching technique traditionally used for restricted vocabulary speech recognition, is based on a temporal alignment of the input signal with the template models. The principal drawback of DTW is its high computational cost as the lengths of the signals increase. This paper shows extended results over our previously published conference paper, which introduces an optimized version of the DTW that is based on the Discrete Wavelet Transform (DWT).
SCADA-based Automatic Control System for Radon Chamber
Authors: Shumin Zhou, Bin Tang, Rui Chen
Venue: Proceedings of the 2009 International Conference on Electronic Computer Technology (2009)

This paper discusses the application of the process monitoring and control for Radon Chamber with WinCC, configuration software with a human-machine interface (HMI) and Supervisory Control and Data Acquisition (SCADA), which is used to monitor the dynamical industrial process. Both software and hardware-based implementations of this system are described in detail, including the dynamic replenishment model. The paper also presents the every component of radon chamber structure exhaustively.
n-Gram characterization of genomic islands in bacterial genomes
Authors: Gordana M. Pavlović-Laetić, Nenad S. Mitić, Miloš V. Beljanski
Venue: Computer Methods and Programs in Biomedicine (2009)

The paper presents a novel, n-gram-based method for analysis of bacterial genome segments known as genomic islands (GIs). Identification of GIs in bacterial genomes is an important task since many of them represent inserts that may contribute to bacterial evolution and pathogenesis. In order to characterize and distinguish GIs from rest of the genome, binary classification of islands based on n-gram frequency distribution have been performed. It consists of testing the agreement of islands n-gram frequency distributions with the complete genome and backbone sequence. In addition, a statistic based on the maximal order Markov model is used to identify significantly overrepresented and underrepresented n-grams in islands. The results may be used as a basis for Zipf-like analysis suggesting that some of the n-grams are overrepresented in a subset of islands and underrepresented in the backbone, or vice versa, thus complementing the binary classification. The method is applied to strain-specific regions in the Escherichia coli O157:H7 EDL933 genome (O-islands), resulting in two groups of O-islands with different n-gram characteristics. It refines a characterization based on other compositional features such as G+C content and codon usage, and may help in identification of GIs, and also in research and development of adequate drugs targeting virulence genes in them.