ppxscal/embedding_network huggingface dataset:
A Hessenberg Markov Chain for Fast Fibre Delay Line Length Optimization
Authors: Joke Lambert, Wouter Rogiest, Benny Houdt, Dieter Fiems, Chris Blondia, Herwig Bruneel
Venue: Proceedings of the 15th international conference on Analytical and Stochastic Modeling Techniques and Applications (2008)

In this paper we present an approach to compute the invariant vector of the N + 1 state Markov chain P presented in (Rogiest et al., Lecture Notes in Computer Science, NET-COOP 2007 Special Issue, pp. 4465:185-194) to determine the loss rate of an FDL buffer consisting of N lines, by solving a related Hessenberg system (i.e., a Markov chain skip-free in one direction). This system is obtained by inserting additional time instants in the sample paths of P and allows us to compute the loss rate for various FDL lengths by solving a single system. This is shown to be especially effective in reducing the computation time of the heuristic LRA algorithm presented in (Lambert et al., Proc. NAEC 2005, pp. 545-555) to optimize the FDL lengths, where improvements of several orders of magnitude can be realized.
Design on Collaborative Virtual Learning Community and Learning Process Visualization
Authors: Wenan Tan, Suxian Lin, Yun Yang, Xianhua Zhao
Venue: Proceedings of the 7th international conference on Advances in Web Based Learning (2008)

Along with the rapid development of network education, virtual learning community emerges its apparent advantages continuously. Collaborative learning has played an important role in educational patterns. Based on the constructivism learning theory, this paper designs a collaborative virtual learning community on the subject of Software Engineering. Moreover, the learner's online action is a force to be reckoned with. In view of collaborative learning processes are very important, the group member's learning characters such as sending or watching the amount of message are extracted to evaluate their usual performances. Then they can be visualized in forms of chart or data report for learners, to the effect that urge learners into adjusting themselves duly.
Multi-Dimensional Image Data Viewer with Flexible Extension Capability and its Application in Computer-Based Medical Systems
Authors: Yoshitaka Masutani
Venue: Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems (2008)

Despite wide use of multi-dimensional image data in clinical environment, current image reading by radiologists is mostly performed based on 2D display of PACS terminal. Various types of commercial-based medical workstations are provided to enhance image reading with 3D visualization and other diagnostic support, but they are not enough for researches of new image analysis techniques. In this short paper, a multi-dimensional image viewer system, VOLUME-ONE, is described and several extension modules such as diffusion MRI analysis are also shown with examples of analysis results in clinical research.
Modified K-Means Clustering Algorithm
Authors: Wei Li
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

Performance of iterative clustering algorithms depends highly on the choice of cluster centers in each step. In this paper we propose an effective algorithm to compute new cluster centers for each iterative step for K-means clustering. This algorithm is based on the optimization formulation of the problem and a novel iterative method. The cluster centers computed using this methodology are found to be very close to the desired cluster centers, for iterative clustering algorithms. The experimental results using the proposed algorithm with a group of randomly constructed data sets are very promising. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Extending Intelligent Tutoring Systems to Mobile Devices
Authors: Vlado Glavinić, Marko Rosić, Marija Zelić
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part I (2008)

Developments in the wireless infrastructure have paved the way to a new e-learning paradigm named mobile learning (m-learning). M-learning systems aim to improve the quality of learning by providing mobile learners with an easy, contextualized and ubiquitous access to knowledge. Our discussion focuses specifically on mobile intelligent tutoring systems. Based on our previous work in the field of intelligent tutoring systems as well as agent technology we have outlined a multi-agent architecture for our intelligent tutoring system xTEx-Sys to be extended to mobile devices. Given the present absence of relevant literature and referent material we think that this paper provides software developers with some valuable guidelines.
Multidimensional Fuzzy Integrals
Authors: Yasuo Narukawa, Vicenç Torra
Venue: Proceedings of the 4th international conference on Modeling Decisions for Artificial Intelligence (2007)

This paper studies multidimensional fuzzy integrals. We consider a multidimensional generalized fuzzy integral that generalizes the multidimensional Choquet and Sugeno integrals. Then, an extension of part of Fubini's theorem is given. Finally, citation analysis is considered as an example of the application of the results presented here.
On Polymorphic Recursion, Type Systems, and Abstract Interpretation
Authors: Marco Comini, Ferruccio Damiani, Samuel Vrech
Venue: Proceedings of the 15th international symposium on Static Analysis (2008)

The problem of typing polymorphic recursion (i.e. recursive function definitions rec {x=e} where different occurrences of x in e are used with different types) has been investigated both by people working on type systems and by people working on abstract interpretation.Recently, Gori and Levi have developed a family of abstract interpreters that are able to type all the ML typable recursive definitions and interesting examples of polymorphic recursion. The problem of finding type systems corresponding to their abstract interpreters was open (such systems would lie between the let-free-free fragments of the ML and of the Milner-Mycroft systems).In this paper we exploit the notion of principal typing to: (i) provide a complete stratification of (let-free) Milner-Mycroft typability, and (ii) solve the problem of finding type systems corresponding to the type abstract interpreters proposed by Gori and Levi.
Mining Top-K Multidimensional Gradients
Authors: Ronnie Alves, Orlando Belo, Joel Ribeiro
Venue: Proceedings of the 9th international conference on Data Warehousing and Knowledge Discovery (2007)

Several business applications such as marketing basket analysis, clickstream analysis, fraud detection and churning migration analysis demand gradient data analysis. By employing gradient data analysis one is able to identify trends, outliers and answering "what-if" questions over large databases. Gradient queries were first introduced by Imielinski et al [1] as the cubegrade problem. The main idea is to detect interesting changes in a multidimensional space (MDS). Thus, changes in a set of measures (aggregates) are associated with changes in sector characteristics (dimensions). MDS contains a huge number of cells which poses great challenge for mining gradient cells on a useful time. Dong et al [2] have proposed gradient constraints to smooth the computational costs involved in such queries. Even by using such constraints on large databases, the number of interesting cases to evaluate is still large. In this work, we are interested to explore best cases (Top-K cells) of interesting multidimensional gradients. There several studies on Top-K queries, but preference queries with multidimensional selection were introduced quite recently by Dong et al [9]. Furthermore, traditional Top-K methods work well in presence of convex functions (gradients are non-convex ones). We have revisited iceberg cubing for complex measures, since it is the basis for mining gradient cells. We also propose a gradient-based cubing strategy to evaluate interesting gradient regions in MDS. Thus, the main challenge is to find maximum gradient regions (MGRs) that maximize the task of mining Top-K gradient cells. Our performance study indicates that our strategy is effective on finding the most interesting gradients in multidimensional space.
Best hybrid classifiers for intrusion detection
Authors: Sanaa Kholfi, Muhammad Habib, Sultan Aljahdali
Venue: Journal of Computational Methods in Sciences and Engineering (2006)

We present in this paper an intrusion detection software-system that we have built based on combined statistical and computational models to detect intrusions and classify them as attack or non-attack. More specifically, we build a computational machine to derive optimal parsimonious hybrid model of classifiers in intrusion detection. The classifiers are based on the following classification methods, Na&iuml;ve Bayes-NB, K-nearest neighbor-K-nn, and Neural networks-NN.
Focus and `Only' in Hungarian
Authors: Kata Balogh
Venue: Logic, Language, and Computation: 6th International Tbilisi Symposium on Logic, Language, and Computation,TbiLLC 2005 Batumi, Georgia, September 12-16, 2005. Revised Selected Papers (2007)

The main of this paper to investigate Hungarian focus interpretations. Hungarian has a special pre-verbal position for focussed constituents, which receive an exhaustive interpretation. Since the focus sensitive particle, `only' goes together with this exhaustive focus, `only' seems to be redundant or superfluous. For this reasons, we will investigate focus and `only' in answers and multiple focus constructions and propose an analysis where exhaustivity-operator and only-operator are distinct. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Adaptation through Planning in Knowledge Intensive CBR
Authors: Antonio Sánchez-Ruiz, Pedro P. Gómez-Martín, Belén Díaz-Agudo, Pedro A. González-Calero
Venue: Proceedings of the 9th European conference on Advances in Case-Based Reasoning (2008)

Adaptation is probably the most difficult task in Case-Based Reasoning (CBR) systems. Most techniques for adaptation propose ad-hoc solutions that require an effort on knowledge acquisition beyond typical CBR standards.In this paper we demonstrate the applicability of domain-independent planning techniques that exploit the knowledge already acquired in many knowledge-rich approaches to CBR. Those techniques are exemplified in a case-based training system that generates a 3D scenario from a declarative description of the training case.
Scale-Space Based Weak Regressors for Boosting
Authors: Jin-Hyeong Park, Chandan K. Reddy
Venue: Proceedings of the 18th European conference on Machine Learning (2007)

Boosting is a simple yet powerful modeling technique that is used in many machine learning and data mining related applications. In this paper, we propose a novel scale-space based boosting framework which applies scale-space theory for choosing the optimal regressors during the various iterations of the boosting algorithm. In other words, the data is considered at different resolutions for each iteration in the boosting algorithm. Our framework chooses the weak regressors for the boosting algorithm that can best fit the current resolution and as the iterations progress, the resolution of the data is increased. The amount of increase in the resolution follows from the wavelet decomposition methods. For regression modeling, we use logitboost update equations based on first derivative of the loss function. We clearly manifest the advantages of using this scale-space based framework for regression problems and show results on different real-world regression datasets.
Standards for Talking Computers
Authors: Fernando Berzal
Venue: IEEE Distributed Systems Online (2004)

A review of .NET Web Services: Architecture and Implementation, by Keith Ballinger
myMCL: A Web Portal for Protein Complexes Prediction
Authors: Mario Cannataro, Pietro Hiram Guzzi, Pierangelo Veltri
Venue: Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems (2008)

Interactomics is the study of the Interactome, i.e. the whole set of macromolecular interactions within a cell. Proteins interact among them and different interactions are represented as graphs named Protein to Protein Interaction (PPI) networks. The interest in analyzing PPI networks is related to the possibility of predicting PPI properties on the basis of global properties of the graph (e.g. verify if homology among species involves PPI similarity), or to find set of protein interactions that has a biological meaning. The prediction of protein complexes has been faced in the last years by using different clustering algorithms. The Markov Clustering algorithm (MCL) is a method that presents one of the best performance but is currently available only as a stand alone application with a simple command-line interface available only on Linux platforms. Following a trend in bioinformatics, we provide a web portal (myMCL) allowing remote users to access MCL functions through the Internet. myMCL enables user to submit a job and stores results in a local database for further processing.
Speccast: toward a more general network layer
Authors: Kenneth L. Calvert, James N. Griffioen
Venue:  (2007)

The current Internet architecture has several characteristics that are widely believed to limit its flexibility. Addressing, routing, and forwarding are tightly intertwined, making it difficult to change or improve any one of them in isolation. This dissertation presents a study of a new service called speccast, which offers insights that could be useful for redesigning and improving the current Internet architecture. Speccast offers a generalized addressing and routing abstraction on which a rich variety of semantic services can be built, and, as such, provides a vehicle for studying the relationships among routing, addressing, and topology. Unlike overlay-based systems, the studied problem is more basic, in which the topology of the network is given, and there is not necessarily a pre-existing, underlying network service. In the speccast model, each packet carries a destination predicate, and the network's job is to deliver the packet to all nodes satisfying that predicate. First, the dissertation presents a layered solution for a specific class of simple predicates. The trade-offs in the various forms of the proposed approach are examined, and the speccast solution is compared to existing solutions for unicast and multicast. Studies using transit-stub graphs show that our generic service performs comparably to existing solutions for traditional services, while also effectively supporting new and emerging services. Second, the dissertation describes a new network-layer architecture that provides a much greater degree of separation between routing and forwarding decisions than the current Internet architecture. This new architecture allows for a broader class of predicates than the previous solution. The forwarding infrastructure is independent of the addressing architecture, so multiple addressing architectures can be used simultaneously with the same forwarding architecture. An extensive simulation study shows that overhead costs (delay, state, and network load) are comparable to those of the existing Internet across a range of parameter values. The dissertation also presents a novel algorithm for the formation of a clustering hierarchy based on both predicates and a topology. Keywords: Networks, Routing, Internet, Clustering, Locality
Cache-based Statistical Language Models of English and Highly Inflected Lithuanian
Authors: Airenas Vaičiūnas, Gailius Raškinis
Venue: Informatica (2006)

This paper investigates a variety of statistical cache-based language models built upon three corpora: English, Lithuanian, and Lithuanian base forms. The impact of the cache size, type of the decay function, including custom corpus derived functions, and interpolation technique (static vs. dynamic) on the perplexity of a language model is studied. The best results are achieved by models consisting of 3 components: standard 3-gram, decaying cache 1-gram and decaying cache 2-gram that are joined together by means of linear interpolation using the technique of dynamic weight update. Such a model led up to 36% and 43% perplexity improvement with respect to the 3-gram baseline for Lithuanian words and Lithuanian word base forms respectively. The best language model of English led up to a 16% perplexity improvement. This suggests that cache-based modeling is of greater utility for the free word order highly inflected languages.
Constructions of optimal GDRP(n,λ;v)'s of type λ1µm-1
Authors: Jie Yan, Jianxing Yin
Venue: Discrete Applied Mathematics (2008)

Generalized doubly resolvable packings (GDRPs) represent a combinatorial characterization of constant composition codes (CCCs). In this paper, we develop a number of general constructions of GDRPs of type @l^1@m^m^-^1. As a consequence, a new series of optimal CCCs is obtained.
Formal Model and Scheduling Heuristics for the Replica Migration Problem
Authors: Nikos Tziritas, Thanasis Loukopoulos, Petros Lampsas, Spyros Lalis
Venue: Proceedings of the 14th international Euro-Par conference on Parallel Processing (2008)

Replication of the most popular objects is often used in distributed data provision systems to reduce access time and improve availability. In fact, a given replica placement scheme may have to be redefined as object popularity changes. Given two replica placement schemes X old and X new , the Replica Migration Problem (RMP) is to compute a schedule of replica transfers and deletions that lead from X old to X new in the shortest time possible. In this paper, we provide a rigorous problem formulation and prove that even for trivial cases RMP is intractable. We also propose a set of heuristics and evaluate them for different scenarios using simulations.
A Novel Secure Interoperation System
Authors: Li Jin, Zhengding Lu
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

Secure interoperation for a distributed system, such as a multi-domain system, is a complex and challenging task. The reason for this is that more and more abnormal requests and hidden intrusions make the static access control policies to be fragile. The access control model presented in this paper approaches this problem by proposing a concept of "trust-level", which involves a statistical learning algorithm, an adaptive calculating algorithm and a self-protecting mechanism to evaluate a dynamic trust degree and realize secure interoperations.
Comparison of Packages for Interval Arithmetic
Authors: Julius Žilinskas
Venue: Informatica (2005)

In this paper public available C and C++ packages for interval arithmetic are investigated and experimentally compared. The results of comparison give suggestions which packages and when are preferable.
Text Retrieval and Blind Feedback for the ImageCLEFphoto Task
Authors: Ray R. Larson
Venue: Evaluation of Multilingual and Multi-modal Information Retrieval: 7th Workshop of the Cross-Language Evaluation Forum, CLEF 2006, Alicante, Spain, September 20-22, 2006, Revised Selected Papers (2007)

In this paper we will describe Berkeley's approach to the ImageCLEFphoto task for CLEF 2006. This year is the first time that we have participated in ImageCLEF, and we chose to primarily establish a baseline for the Cheshire II system for this task, while we had originally hoped to use GeoCLEF methods for this task, in the end time constraints led us to restrict our submissions to the basic required runs for the task.
Probabilistic Methods for Structured Document Classification at INEX'07
Authors: Luis M. Campos, Juan M. Fernández-Luna, Juan F. Huete, Alfonso E. Romero
Venue: Focused Access to XML Documents: 6th International Workshop of the Initiative for the Evaluation of XML Retrieval, INEX 2007 Dagstuhl Castle, Germany, December 17-19, 2007. Selected Papers (2008)

This paper exposes the results of our participation in the Document Mining track at INEX'07. We have focused on the task of classification of XML documents. Our approach to deal with structured document representations uses classification methods for plain text, applied to flattened versions of the documents, where some of their structural properties have been translated to plain text. We have explored several options to convert structured documents into flat documents, in combination with two probabilistic methods for text categorization. The main conclusion of our experiments is that taking advantage of document structure to improve classification results is a difficult task.
An uncertainty principle for quaternion Fourier transform
Authors: Mawardi Bahri, Eckhard S. M. Hitzer, Akihisa Hayashi, Ryuichi Ashino
Venue: Computers Mathematics with Applications (2008)

We review the quaternionic Fourier transform (QFT). Using the properties of the QFT we establish an uncertainty principle for the right-sided QFT. This uncertainty principle prescribes a lower bound on the product of the effective widths of quaternion-valued signals in the spatial and frequency domains. It is shown that only a Gaussian quaternion signal minimizes the uncertainty.
Relational Transparency Model for Interactive Technical Illustration
Authors: Ladislav Čmolík
Venue: Proceedings of the 9th international symposium on Smart Graphics (2008)

Ghosted views are technical illustrations that communicate not only shape, but also inner structure and spatial relations of the depicted objects. Modulation of opacity is utilized to communicate the inner structure, therefore the spatial relations remains undistorted. In this paper an approach that enables real-time rendering of 3D ghosted views is presented. The advantage over classical handcrafted ghosted views is that the user is able to interact (e.g. pan, zoom and rotate) with the 3D model.
An Indexing Technique for Fuzzy Numerical Data
Authors: Carlos D. Barranco, Jesús R. Campaña, Juan M. Medina
Venue: Proceedings of the 1st international conference on Scalable Uncertainty Management (2007)

This paper introduces an indexing technique for fuzzy numerical data which relies on the classical, well-known and well-spread B+tree index data structure. The proposed indexing technique is specifically devised to increase the performance of query processing when a possibility measured flexible condition is involved. The proposal relies on the use of an indexing data structure implemented in virtually every database management system. This feature makes the proposal a good candidate to be used, with very low implementation effort, in a fuzzy database management system created as an extension of a classical one. The paper includes a performance analysis of the proposed indexing technique in contrast with other purpose equivalent techniques in order to evaluate the suitability of the proposal.