ppxscal/embedding_network huggingface dataset:
Clustering Quality and Topology Preservation in Fast Learning SOMs
Authors: Antonino Fiannaca, Giuseppe Fatta, Salvatore Gaglio, Riccardo Rizzo, Alfonso Urso
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part I (2008)

The Self-Organizing Map (SOM) is a popular unsupervised neural network able to provide effective clustering and data visualization for multidimensional input spaces. Fast Learning SOM (FLSOM) adopts a learning algorithm that improves the performance of the standard SOM with respect to the convergence time in the training phase. In this paper we show that FLSOM also improves the quality of the map by providing better clustering quality and topology preservation of multidimensional input data. Several tests have been carried out on different multidimensional datasets, which demonstrate the superiority of the algorithm in comparison with the original SOM.
A web based geoenvironmental data exchange information system
Authors: C. Stergiopoulos, P. Tsiakas, D. Triantis, F. Vallianatos
Venue: Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases (2008)

Different geoenvironmental databases exist in European countries. They are dispersed and have various standards and languages applied. Thus their usefulness and availability are limited, although geophysical information may be very effectively applied, processed and interpreted for a wide variety of purposes. Processing will be enhanced if these databases are integrated in a certain level and accessed via the Internet, offering cross border, European-wide, unified electronic services, making geoenvironmental data much more available. In an effort to increase utilization of geoenvironmental data the MILDMAP-MEDIA consortium has developed an web based data exchange system that provides a convenient storage point for documenting, archiving and exchanging datasets. The users of the system can enter metadata that describe their datasets, upload their dataset files, edit their entries, search for data using specific criteria, browse metadata of datasets in the system and download datasets from the system. The functional design and implementation of this system are presented.
The Problem of Learning the Semantics of Quantifiers
Authors: Nina Gierasimczuk
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)

This paper is concerned with a possible mechanism for learning the meanings of quantifiers in natural language. The meaning of a natural language construction is identified with a procedure for recognizing its extension. Therefore, acquisition of natural language quantifiers is supposed to consist in collecting procedures for computing their denotations. A method for encoding classes of finite models corresponding to given quantifiers is shown. The class of finite models is represented by appropriate languages. Some facts describing dependencies between classes of quantifiers and classes of devices are presented. In the second part of the paper examples of syntax-learning models are shown. According to these models new results in quantifier learning are presented. Finally, the question of the adequacy of syntax-learning tools for describing the process of semantic learning is stated.
Analysis of ID-based restrictive partially blind signatures and applications
Authors: Xiaoming Hu, Shangteng Huang
Venue: Journal of Systems and Software (2008)

Partially blind signatures and restrictive blind signatures are two important techniques in electronic cash systems and voting systems. Restrictive partially blind signatures incorporate the advantages of these two blind signatures. Recently, Chen-Zhang-Liu first proposed an ID-based restrictive partially blind signature from bilinear pairings (Chen, X.F., Zhang, F.G., Liu, S.L., 2007. ID-based restrictive partially blind signatures and applications. The Journal of Systems and Software 80 (2), 164-171). However, in this paper, we show that Chen-Zhang-Liu's scheme has a security weakness. Their scheme does not satisfy the property of restrictiveness as they claimed, and an account-holder cannot be revealed when double-spending happens.
A POD-Based Center Selection for RBF Neural Network in Time Series Prediction Problems
Authors: Wenbo Zhang, Xinchen Guo, Chaoyong Wang, Chunguo Wu
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II (2007)

Center selection based on proper orthogonal decomposition (POD) is presented to select centers for the radial basis function (RBF) neural network in prediction of nonlinear time series. The proposed method takes advantages of the time-sequence feature in time series data and enables the center selection to be implemented in a parallel manner. Simulations on a benchmark problem and on two predictions of stock prices show that the presented method can be applied effectively to the prediction of nonlinear time series. Besides possessing higher precisions in training and testing, the proposed method has stronger generalization and noise resistance abilities, compared to several other popular center selection methods.
Acceleration of High Dynamic Range Imaging Pipeline Based on Multi-threading and SIMD Technologies
Authors: Radosław Mantiuk, Dawid Pająk
Venue: Proceedings of the 8th international conference on Computational Science, Part I (2008)

In this paper we present a holistic approach to CPU based acceleration of the high dynamic range imaging (HDRI) pipeline. The high dynamic range representation can encode images regardless of the technology used to create and display them, with the accuracy that is only constrained by the limitations of the human eye and not a particular output medium. Unfortunately, the increase in accuracy causes significant computational overhead and effective hardware acceleration is needed to ensure a utility value of HDRI applications. In this work we propose a novel architecture of the HDRI pipeline based on CPU SIMD and multi-threading technologies. We discuss the impact on processing speed caused by vectorization and parallelization of individual image processing operations. A commercial application of the new HDRI pipeline is described together with evaluation of achieved image processing speed-up.
Intra Routing Protocol with Hierarchical and Distributed Caching in Nested Mobile Networks
Authors: Hyemee Park, Moonseong Kim, Hyunseung Choo
Venue: Proceedings of the 3rd international conference on Embedded Software and Systems (2007)

We propose a novel route optimization protocol for intra-NEMO communication using a hierarchical and distributed caching scheme. The proposed scheme employs the routing cache of each nested MRs to optimize a route to be taken for traffic between MNNs within nested mobile network. For this goal, it supports an efficient cache design and adaptive mechanism for managing cache. By using tree based routing, it has greater data efficiency with less packet overheads, and improves the latency of the data traffic using an optimal route. To support seamless mobility, we propose a solution that reduces the mass signaling for all nested mobile networks when the nested MR handoff frequently occurs. The proposed scheme has approximately 29% of performance improvements in comparison with previous schemes.
Integrating UML and GPSS for business process modeling and simulation
Authors: Yi Xie
Venue: Proceedings of the 8th WSEAS International Conference on Robotics, Control and Manufacturing Technology (2008)

Simulation is a dynamic modeling technology. However there is little integration of business process static modeling and simulation, which prevents simulation from becoming a mainstream modeling method/tool. Firstly, UML activity diagram is extended using UML extensibility mechanism for BPS, which enhances activity diagram's ability of describing business process and adds some information which the simulation needs. Secondly, the principles and methods that can be used to translate extended UML activity diagram into the GPSS model are proposed, which realizes the integration of the static model and the dynamic model. Finally, a supporting software tool system of integrating UML and GPSS for business process modeling and simulation has been developed based on our proposed methods.
Interaction between a Disabled Person and a Scanning Communication Aid: Towards an Automatic Adjustment of the Scanning Rate Adapted to the User
Authors: Souhir Ghedira, Pierre Pino, Guy Bourhis
Venue: Proceedings of the 11th international conference on Computers Helping People with Special Needs (2008)

For many motor disabled persons, using scanning systems remains the only means of communication. The main disadvantage of this system is the slow pace of communication. A way to raise the pace for the selection of messages consists in optimizing the basic scrolling time. The purpose of this pape ris to describe a method making it possible to adjust this time in an automatic and adaptive way.
Let's talk about our &ldquo;being&rdquo;: A linguistic-based ontology framework for coordinating agents
Authors: Maria Teresa Pazienza, Savino Sguera, Armando Stellato
Venue: Applied Ontology (2007)

In open scenarios, agents willing to cooperate must impact the communication barrier between them and their unknown partners. If agents are not relying on any agreement about the meaning they ascribe to the symbols used in the conversation, semantic misalignments will arise on the discourse domain as well, thus making the communication impossible. In wide and heterogeneous scenarios offered by the Web (and its newborn semantic incarnation), traditional and meaning-safe methodologies for communication need to keep abreast of new dynamic communicative interaction modalities. The uncertainties arising from communication between actors which base their behavior on different and heterogeneous knowledge models have to be taken into account, wisely balancing the extent of &ldquo;reachable knowledge&rdquo; with the trustworthiness of its information. Main objective of this work is to augment the FIPA Ontology Service Specification with linguistically-aware methodologies for communication, describing a wide-scope framework for multi-agent systems design, semantic integration and coordination.
A game-engine based virtual museum authoring and presentation system
Authors: Victor Mateevitsi, Michael Sfakianos, George Lepouras, Costas Vassilakis
Venue: Proceedings of the 3rd international conference on Digital Interactive Media in Entertainment and Arts (2008)

In this paper we present a system that facilitates virtual museum development and usage. The system is based on a game engine, ensuring thus minimal cost and good performance, and includes provisions that enable museum curators design the virtual museum without any specialized knowledge. Besides visual and auditory information, museum curators may also provide metadata which provide additional information to the visitor, while they can be also exploited for searching for exhibits with certain properties. A guide is also included in the museum, to present additional information to the visitors and aid them throughout their tour.
Expansion and Lack Thereof in Randomly Perturbed Graphs
Authors: Abraham D. Flaxman
Venue: Algorithms and Models for the Web-Graph: Fourth International Workshop, WAW 2006, Banff, Canada, November 30 - December 1, 2006. Revised Papers (2007)

This paper studies the expansion properties of randomly perturbed graphs. These graphs are formed by, for example, adding a random $1{\text{-out}}$ or very sparse Erdős-Rényi graph to an arbitrary connected graph.The central results show that there exists a constant ¿ such that when any connected n-vertex base graph $\bar{G}$ is perturbed by adding a random 1-out then, with high probability, the resulting graph has $e(S,\bar S) \geq \delta |S|$ for all S ¿ V with $|S| \leq \frac34 n$. When $\bar{G}$ is perturbed by adding a random Erdős-Rényi graph, $\mathbb{G}_{n,\epsilon/n}$, the expansion of the perturbed graph depends on the structure of the base graph. A necessary condition for the base graph is given under which the resulting graph is an expander with high probability.The proof techniques are also applied to study rapid mixing in the small worlds graphs described by Watts and Strogatz in [Nature 292 (1998), 440---442] and by Kleinberg in [Proc. of 32nd ACM Symposium on Theory of Computing (2000), 163---170]. Analysis of Kleinberg's model shows that the graph stops being an expander exactly at the point where a decentralized algorithm is effective in constructing a short path.The proofs of expansion rely on a way of summing over subsets of vertices which allows an argument based on the First Moment Method to succeed.
Algorithm for Selecting either an Overlay or Flat Route Based on the Amount of the Delay Measurement Load on the Home Agent in a Hierarchical Mobile IPv6 Network
Authors: Hidetoshi Kobayashi, Kazumasa Takami
Venue: Proceedings of the 8th international conference, NEW2AN and 1st Russian Conference on Smart Spaces, ruSMART on Next Generation Teletraffic and Wired/Wireless Advanced Networking (2008)

In a Hierarchical Mobile IPv6 (HMIPv6), two alternative routes are available: a Home Agent (HA) route (overlay route), and a direct communication route (flat route), which does not pass through the HA and is determined using the Return Routability procedure. The flat route is not always optimal when handover frequencies are taken into consideration. Therefore, it is necessary to select either the overlay or flat rate based on the particular communication situation. This paper proposes a communication route selection algorithm that is suitable of an HMIPv6 configuration, in which the route to be used is selected based on the packet delay measurement of each route. The algorithm's effectiveness has been verified through a simulation of its operation, and the evaluation of the reduction in the number of delay measurement packets arriving at the HA.
An Empirical Approach to Identify Information Misuse by Insiders (Extended Abstract)
Authors: Deanna D. Caputo, Greg Stephens, Brad Stephenson, Megan Cormier, Minna Kim
Venue: Proceedings of the 11th international symposium on Recent Advances in Intrusion Detection (2008)

Rogue employees with access to sensitive information can easily abuse their access to engage in information theft. To help differentiate malicious from benign behavior, this study measures how participants, given a common search topic, seek information. This study uses double-blind procedures, a stratified sample, and carefully designed control and experimental conditions. We seek to validate previously identified network indicators (ELICIT), find new host-based behaviors, and consider other human attributes that affect the information-use of malicious insiders by comparing their behavior to equivalent non-malicious users.
Support for Fine Grained Dependent Tasks in OpenMP
Authors: Oliver Sinnen, Jsun Pe, Alexei Vladimirovich Kozlov
Venue: Proceedings of the 3rd international workshop on OpenMP: A Practical Programming Model for the Multi-Core Era (2007)

OpenMP is widely used for shared memory parallel programming and is especially useful for the parallelisation of loops. When it comes to task parallelism, however, OpenMP is less powerful and the sections construct lacks support for dependences and fine grained tasks. This paper proposes a new work-sharing construct, tasks, which is a generalisation of sections. It goes beyond sections by allowing unbalanced and finer grained tasks with arbitrary dependence structure. A proof-of-concept compiler has been implemented for the new directives, which includes a state-of-the-art scheduling algorithm for task graphs. Experiments with a large set of programs were conducted using the new directives. The results demonstrate that the new approach can efficiently exploit the task parallelism inherent in the code, without introducing any additional overhead.
Duplication in DNA Sequences
Authors: Masami Ito, Lila Kari, Zachary Kincaid, Shinnosuke Seki
Venue: Proceedings of the 12th international conference on Developments in Language Theory (2008)

Duplication and repeat-deletion are the basic models of errors occurring during DNA replication from the viewpoint of formal languages. During DNA replication, subsequences of a strand of DNA may be copied several times (duplication) or skipped (repeat-deletion). Iterated duplication and repeat-deletion have been well-studied, but little is known about single-step duplication and repeat-deletion. In this paper, we investigate properties of these operations, such as closure properties of language families in the Chomsky hierarchy, language equations involving these operations. We also make progress towards a characterization of regular languages that are generated by duplicating a regular language.
Possibilistic Clustering in Feature Space
Authors: Maurizio Filippone, Francesco Masulli, Stefano Rovetta
Venue: Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory (2007)

In this paper we propose the Possibilistic C-Means in Feature Space and the One-Cluster Possibilistic C-Means in Feature Space algorithms which are kernel methods for clustering in feature space based on the ossibilistic approach to clustering. The proposed algorithms retain the properties of the possibilistic clustering, working as density estimators in feature space and showing high robustness to outliers, and in addition are able to model densities in the data space in a non-parametric way. One-Cluster Possibilistic C-Means in Feature Space can be seen also as a generalization of One-Class SVM.
Finding Additive Biclusters with Random Background
Authors: Jing Xiao, Lusheng Wang, Xiaowen Liu, Tao Jiang
Venue: Proceedings of the 19th annual symposium on Combinatorial Pattern Matching (2008)

The biclustering problem has been extensively studied in many areas including e-commerce, data mining, machine learning, pattern recognition, statistics, and more recently in computational biology. Given an n ×m matrix A (n ¿ m), the main goal of biclustering is to identify a subset of rows (called objects) and a subset of columns (called properties) such that some objective function that specifies the quality of the found bicluster (formed by the subsets of rows and of columns of A) is optimized. The problem has been proved or conjectured to be NP-hard under various mathematical models. In this paper, we study a probabilistic model of the implanted additive bicluster problem, where each element in the n×m background matrix is a random number from [0, L ¿ 1], and a k×k implanted additive bicluster is obtained from an error-free additive bicluster by randomly changing each element to a number in [0, L ¿ 1] with probability ¿. We propose an O(n 2 m) time voting algorithm to solve the problem. We show that for any constant ¿ such that $(1-\delta)(1-\theta)^2 -\frac 1 L >0$, when $k \ge \max \left\{\frac 8 \alpha \sqrt{n\log n},~ \frac {8 \log n} c + \log (2L)\right\}$, where c is a constant number, the voting algorithm can correctly find the implanted bicluster with probability at least $1 - \frac{9}{n^{2}}$. We also implement our algorithm as a software tool for finding novel biclusters in microarray gene expression data, called VOTE. The implementation incorporates several nontrivial ideas for estimating the size of an implanted bicluster, adjusting the threshold in voting, dealing with small biclusters, and dealing with multiple (and overlapping) implanted biclusters. Our experimental results on both simulated and real datasets show that VOTE can find biclusters with a high accuracy and speed.
A gas-kinetic BGK scheme for semiclassical Boltzmann hydrodynamic transport
Authors: Yu-Hsin Shi, J. Y. Yang
Venue: Journal of Computational Physics (2008)

A class of gas-kinetic BGK schemes for solving quantum hydrodynamic transport based on the semiclassical Boltzmann equation with the relaxation time approximation is presented. The derivation is a generalization to the development of Xu [K. Xu, A gas-kinetic BGK scheme for the Navier-Stokes equations and its connection with artificial dissipation and Godunov method, from gas-kinetic theory, J. Comput. Phys. 171 (2001) 289-335] for the classical gas. Both Bose-Einstein and Fermi-Dirac gases are considered. Some new features due to the quantum equilibrium distributions are delineated. The first-order Chapman-Enskog expansion of the quantum BGK-Boltzmann equation is derived. The coefficients of shear viscosity and thermal conductivity of a quantum gas are given. The van Leer's limiter is used to interpolate and construct the distribution on interface to achieve second-order accuracy. The present quantum gas-kinetic BGK scheme recovers the Xu's scheme when the classical limit is taken. Several one-dimensional quantum gas flows in a shock tube are computed to illustrate the present method.
Predicting the activity phase of a follower neuron with A-current in an inhibitory network
Authors: Yu Zhang, Amitabha Bose, Farzan Nadim
Venue: Biological Cybernetics (2008)

The transient potassium A-current is present in most neurons and plays an important role in determining the timing of action potentials. We examine the role of the A-current in the activity phase of a follower neuron in a rhythmic feed-forward inhibitory network with a reduced three-variable model and conduct experiments to verify the usefulness of our model. Using geometric analysis of dynamical systems, we explore the factors that determine the onset of activity in a follower neuron following release from inhibition. We first analyze the behavior of the follower neuron in a single cycle and find that the phase plane structure of the model can be used to predict the potential behaviors of the follower neuron following release from inhibition. We show that, depending on the relative scales of the inactivation time constant of the A-current and the time constant of the recovery variable, the follower neuron may or may not reach its active state following inhibition. Our simple model is used to derive a recursive set of equations to predict the contribution of the A-current parameters in determining the activity phase of a follower neuron as a function of the duration and frequency of the inhibitory input it receives. These equations can be used to demonstrate the dependence of activity phase on the period and duty cycle of the periodic inhibition, as seen by comparing the predictions of the model with the activity of the pyloric constrictor (PY) neurons in the crustacean pyloric network.
Appendix: Workshop and Tutorial Abstracts
Authors: Jianjun Zhao, Jeff Poulin
Venue: Proceedings of the 10th international conference on Software Reuse: High Confidence Software Reuse in Large Systems (2008)

Software reuse is a promising and attractive concept for improving software productivity, quality and time to market. However, a series of problems will often be encountered when considering reuse in a completely general context, including incompatible variability assumption, architecture mismatch, inability for more specific problem, etc. So a more promising way is to practice reuse based product development within specific domain in a prescribed way, as in the area of domain engineering and software product line.