ppxscal/embedding_network huggingface dataset:
Searching and Updating Metric Space Databases Using the Parallel EGNAT
Authors: Mauricio Marin, Roberto Uribe, Ricardo Barrientos
Venue: Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007 (2007)

The Evolutionary Geometric Near-neighbor Access Tree (EGNAT) is a recently proposed data structure that is suitable for indexing large collections of complex objects. It allows searching for similar objects represented in metric spaces. The sequential EGNAT has been shown to achieve good performance in high-dimensional metric spaces with properties (not found in others of the same kind) of allowing update operations and efficient use of secondary memory. Thus, for example, it is suitable for indexing large multimedia databases. However, comparing two objects during a search can be a very expensive operation in terms of running time. This paper shows that parallel computing upon clusters of PCs can be a practical solution for reducing running time costs. We describe alternative distributions for the EGNAT index and their respective parallel search/update algorithms and concurrency control mechanism.
A Domain-Specific Language for Web APIs and Services Mashups
Authors: E. Michael Maximilien, Hernan Wilkinson, Nirmit Desai, Stefan Tai
Venue: Proceedings of the 5th international conference on Service-Oriented Computing (2007)

Distributed programming has shifted from private networks to the public Internet and from using private and controlled services to increasingly using publicly available heterogeneous Web services (e.g., REST, SOAP, RSS, and Atom). This move enables the creation of innovative end-user-oriented composed services with user interfaces. These services mashups are typically point solutions to specific (specialized) problems; however, what is missing is a programming model that facilitates and accelerates creation and deployment of mashups of diverse services. In this paper we describe a domain-specific language that unifies the most common service models and facilitates service composition and integration into end-user-oriented Web applications. We demonstrate our approach with an implementation that leverages the Ruby on Rails framework.
On L(d,1)-labeling of Cartesian product of a cycle and a path
Authors: Shih-Hu Chiang, Jing-Ho Yan
Venue: Discrete Applied Mathematics (2008)

A k-L(d,1)-labeling of a graph G is a function f from the vertex set V(G) to {0,1,...,k} such that |f(u)-f(v)|>=1 if d(u,v)=2 and |f(u)-f(v)|>=d if d(u,v)=1. The L(d,1)-labeling problem is to find the L(d,1)-labeling number @l"d(G) of a graph G, which is the minimum cardinality k such that G has a k-L(d,1)-labeling. In this paper, we determine the L(d,1)-labeling number of the Cartesian product of a cycle and a path.
Least Mean Square vs. Outer Bounding Ellipsoid Algorithm in Confidence Estimation of the GMDH Neural Networks
Authors: Marcin Mrugalski, Józef Korbicz
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II (2007)

The paper deals with the problem of determination of the model uncertainty during the system identification with the application of the Group Method of Data Handling (GMDH) neural network. The main objective is to show how to employ the Least Mean Square (LMS) and the Outer Bounding Ellipsoid (OBE) algorithm to obtain the corresponding model uncertainty.
Effects of virtualization on a scientific application running a hyperspectral radiative transfer code on virtual machines
Authors: Anand Tikotekar, Geoffroy Vallée, Thomas Naughton, Hong Ong, Christian Engelmann, Stephen L. Scott, Anthony M. Filippi
Venue: Proceedings of the 2nd workshop on System-level virtualization for high performance computing (2008)

The topic of system-level virtualization has recently begun to receive interest for high performance computing (HPC). This is in part due to the isolation and encapsulation offered by the virtual machine. These traits enable applications to customize their environments and maintain consistent software configurations in their virtual domains. Additionally, there are mechanisms that can be used for fault tolerance like live virtual machine migration. Given these attractive benefits to virtualization, a fundamental question arises, how does this effect my scientific application? We use this as the premise for our paper and observe a real-world scientific code running on a Xen virtual machine. We studied the effects of running a radiative transfer simulation, Hydrolight, on a virtual machine. We discuss our methodology and report observations regarding the usage of virtualization with this application.
Spatial Memory and Spatial Orientation
Authors: Jonathan W. Kelly, Timothy P. Mcnamara
Venue: Proceedings of the international conference on Spatial Cognition VI: Learning, Reasoning, and Talking about Space (2008)

Navigating through a remembered space depends critically on the ability to stay oriented with respect to the remembered environment and to reorient after becoming lost. This chapter describes the roles of long-term spatial memory, sensorimotor spatial memory, and path integration in determining spatial orientation. Experiments presented here highlight the reference direction structure of long-term spatial memory and suggest that self-position and orientation during locomotion are updated with respect to those reference directions. These results indicate that a complete account of spatial orientation requires a more thorough understanding of the interaction between long-term spatial memory, sensorimotor spatial memory, and path integration.
An Affective Model Applied in Playmate Robot for Children
Authors: Jun Yu, Lun Xie, Zhiliang Wang, Yongxiang Xia
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks, Part II (2008)

It is always the focus of researchers' attention to endow the robot with the emotion similar to human in human robot interaction. This paper present an artificial affective model based on Hidden Markov Model (HMM). It can achieve the transfer of several affective states under some basic hypothesis and restriction. The paper also shows some simulation results of affective states change. It is the basis for architecture in support of interactive robot. Then the paper explains the technical route of playmate robot for children in detail. The robot can behave like a human child and attempt daily communication with human supported by the affective model and these technologies.
Decision-Level Fusion for Audio-Visual Laughter Detection
Authors: Boris Reuderink, Mannes Poel, Khiet Truong, Ronald Poppe, Maja Pantic
Venue: Proceedings of the 5th international workshop on Machine Learning for Multimodal Interaction (2008)

Laughter is a highly variable signal, which can be caused by a spectrum of emotions. This makes the automatic detection of laughter a challenging, but interesting task. We perform automatic laughter detection using audio-visual data from the AMI Meeting Corpus. Audio-visual laughter detection is performed by fusing the results of separate audio and video classifiers on the decision level. This results in laughter detection with a significantly higher AUC-ROC than single-modality classification.
Unified signal processing and machine learning for modeling nonlinear complex systems
Authors: Kayvan Najarian
Venue:  (2007)

Modeling Complex systems usually needs to be done with using different techniques from different fields. Signal processing and machine learning can play a significant role in developing models to analyze complex systems. In this proposal, the application of signal processing and machine learning in developing models for two types of complex systems is studied. The first set of complex systems include inferring gene regulatory networks and the second set includes money service business.
Total Domination in Graphs with Given Girth
Authors: Michael A. Henning, Anders Yeo
Venue: Graphs and Combinatorics (2008)

A set S of vertices in a graph G without isolated vertices is a total dominating set of G if every vertex of G is adjacent to some vertex in S. The minimum cardinality of a total dominating set of G is the total domination number &#x03b3;t (G) of G. In this paper, we establish an upper bound on the total domination number of a graph with minimum degree at least two in terms of its order and girth. We prove that if G is a graph of order n with minimum degree at least two and girth g, then &#x03b3;t (G) &#x2264;&#x00a0;n/2 +&#x00a0;n/g, and this bound is sharp. Our proof is an interplay between graph theory and transversals in hypergraphs.
A Further Discussion on Convergence Rate of Immune Genetic Algorithm to Absorbed-State
Authors: Xiaoping Luo, Wenyao Pang, Ji Huang
Venue: Computational Intelligence and Security: International Conference, CIS 2006, Guangzhou, China, November 3-6, 2006, Revised Selected Papers (2007)

A new Immune Genetic Algorithm (IGA) modeling was completed using Markov chain. The convergence rate of IGA to absorbed-state was deduced using norm and the analysis of transition probability matrix. According to the design and the performance of IGA, the detailed quantitative expressions of convergence rate to absorbed-state which include immune parameters in IGA was presented. Then the discussion was carried out about the effect of the parameters on the convergence rate. It was found that several parameters such as the population size, the population distribution, the string length etc. would all affect the optimization. The conclusions demonstrate that why IGA can maintain the diversity very well so that the optimization is very quick. This paper can also be helpful for the further study on the convergence rate of Immune Genetic Algorithm.
Prediction of total AC power output from a grid-photovoltaic system using multi-model ANN
Authors: Shahril Irwan Sulaiman, Ismail Musirin, Titik Khawa Abdul Rahman
Venue: Proceedings of the 7th WSEAS International Conference on Application of Electrical Engineering (2008)

This paper presents the prediction of total AC power output from a grid-photovoltaic system using multimodel artificial neural network (ANN). In this study, three-layer feedforward Artificial Neural Network (ANN) model for the prediction of total AC power output from a grid-photovoltaic system has been considered. The multi-model was configured from three ANN models considering different sets of ANN inputs. The first model utilizes solar radiation and ambient temperature as its inputs while the second model uses solar radiation and wind speed as its inputs. The third model uses solar radiation, ambient temperature and wind speed as its inputs. Nevertheless, all the three models employ similar type of output which is the total AC power produced from the grid-PV system. Data filtering process has been introduced to select the quality data patterns to be used in training process, making only the informative features are available. Thus, the regression analysis and root mean square error (RMSE) performance of each model could be enhanced. After the training process is completed, the testing process is performed to decide whether the training process should be repeated or stopped. Besides selecting the best prediction model, this study also exhibits some of the experimental results which illustrate the effectiveness of the data filtering in predicting the total AC power output from a grid-PV system. Fully trained ANN model should be later able to predict the AC power output from a set of un-seen data patterns.
Watermarking Based on the Density Coefficients of Faber-Schauder Wavelets
Authors: Mohamed Hajji, Hassin Douzi, Rachid Harba
Venue: Proceedings of the 3rd international conference on Image and Signal Processing (2008)

The field of watermarking is of great development in recent years. There is still relevance to find high-performance methods that link robustness and discretion. In this paper, we will present a method of watermarking based on a mixed scale wavelet transformations of Faber-Schauder and the selection of high-density regions of the dominant coefficients. Simulation results demonstrate the robustness of our image watermarking procedure under various attacks and could serve for the image watermarking of identity and access cards.
A New Document Clustering Algorithm for Topic Discovering and Labeling
Authors: Henry Anaya-Sánchez, Aurora Pons-Porrata, Rafael Berlanga-Llavori
Venue: Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications (2008)

In this paper, we introduce a new clustering algorithm for obtaining labeled document clusters that accurately identify the topics of a text collection. In order to determine the topics, our approach relies on both probable term pairs generated from the collection and the estimation of the topic homogeneity associated to term pair clusters. Experimental results obtained over two benchmark text collections demonstrate the utility of this new approach.
Multi-agent Cooperation Method Based on Intention Recognition
Authors: Lin Liu, Yuehuan Wang
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

The paper discusses the cooperation method among multiple agents in 3D space based on intention recognition. It is assumed that an observer observes multiple moving objects that are its company and the enemy. The purpose of our work is to help the observer to make cooperation decision efficiently. Due to the distortions the perspective brings, cooperating in 3D space is difficult. To contact agents with each other, we list two kinds of tracking model to analyse the problem, for the observer's teammates can estimate the enemy's trace to adjust their flight paths, and also can just move towards the directions of the enemy. The relationship among the agents and the moving intentions of them are to be estimated by sequence images. Aimed at each tracking model, estimation algorithms are proposed respectively by which the probabilities of intention are gained. First, we analyse the characteristic of the two models in detail. Then an estimation function is listed to predict the possibility of tracking trends and it is proved that there is also a normal distribution relationship between agents with the Kalman filter. The proposed approaches are applied to process several groups of simulated images at the end. The result of the experiments proves the availability and the robustness of the proposed method.
Context-Aware Middleware for Reliable Multi-hop Multi-path Connectivity
Authors: Paolo Bellavista, Antonio Corradi, Carlo Giannelli
Venue: Proceedings of the 6th IFIP WG 10.2 international workshop on Software Technologies for Embedded and Ubiquitous Systems (2008)

The widespread diffusion of portable devices with multiple wireless interfaces, e.g., UMTS/GPRS, IEEE 802.11, and/or Bluetooth, is enabling multi-homing and multi-channel scenarios, possibly made up by multi-hop cooperative paths towards the traditional Internet infrastructure. There is the need for novel middleware supports, aware of innovative context information, to select and dynamically re-configure the most suitable interfaces and connectivity providers for each client application. In particular, novel middlewares should effectively exploit concise and lightweight context indicators about expected node mobility, path throughput, and energy availability to take proper connectivity management decisions at session startup and to promptly re-configure them with limited overhead at runtime. Here, we present how our MMHC middleware originally uses mobility/throughput/energy context to manage connectivity opportunities effectively, i) by filtering out connectivity opportunities that are considered insufficiently reliable, and ii) by carefully evaluating the residual candidates in two distinguished local/global management phases to achieve the most suitable tradeoff between promptness and management costs.
Topic 8 Distributed Systems and Algorithms
Authors: Luís Rodrigues, Achour Mostefaoui, Christof Fetzer, Philippas Tsigas
Venue: Proceedings of the 13th European international conference on Parallel Processing (2007)

Parallel computing is increasingly exposed to the development and challenges of distributed systems, such as the lack of load balancing, asynchrony, long latencies, network partitions, failures, disconnected operations, heterogeneity and protocol standardization. Furthermore, distributed systems are becoming larger, more diverse and more dynamic. This Euro-Par topic provides a forum for research and practice, of interest to both academia and industry, about distributed systems, distributed computing, distributed algorithms, and parallel processing on distributed systems. Submission was encouraged across the whole area, with emphasis on the following: design and practice of distributed algorithms and data structures, analysis of the behaviour of distributed systems and algorithms, distributed operating systems, parallel processing on distributed systems, resource and service discovery, resource sharing and in distributed systems, distributed fault tolerance, security in distributed systems, scalability, concurrency and performance in distributed systems, middleware for parallel computations, web services, interoperability and standards, self-organised and self-adjusting distributed systems.
Improving presence theory through experiential design
Authors: Dustin B. Chertoff, Sae Lynne Schatz Rudy McDaniel Clint A. Bowers
Venue: Presence: Teleoperators and Virtual Environments (2008)

Despite ongoing research over the last 15 years, the presence construct remains somewhat limited in its ability to be applied beyond the sensory domain. In order to increase its usefulness for applied challenges (e.g., using presence theory to enhance simulators' effectiveness), a discussion about a new conceptualization of presence is introduced. This novel perspective on presence is rooted in the notion of “experiential design,” an approach businesses use to create strategically compelling and memorable experiences. The paper begins with a brief review of presence and then a description of the concepts of experimental design. Following this, a theoretical model of presence, based upon experimental design, is offered. Using this model, an exploration on the mitigation of breaks in presence is offered (a break in presence occurs when presence fails to be maintained). These ideas are presented in order to improve the likelihood of presence emerging for simulation participants and to enhance interdisciplinary researchers' shared conceptualizations of presence.
Transferring Instances for Model-Based Reinforcement Learning
Authors: Matthew E. Taylor, Nicholas K. Jong, Peter Stone
Venue: Proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases - Part II (2008)

Reinforcement learning agents typically require a significant amount of data before performing well on complex tasks. Transfer learning methods have made progress reducing sample complexity, but they have primarily been applied to model-free learning methods, not more data-efficient model-based learning methods. This paper introduces timbrel, a novel method capable of transferring information effectively into a model-based reinforcement learning algorithm. We demonstrate that timbrel can significantly improve the sample efficiency and asymptotic performance of a model-based algorithm when learning in a continuous state space. Additionally, we conduct experiments to test the limits of timbrel's effectiveness.
Collision Search for Elliptic Curve Discrete Logarithm over GF(2m) with FPGA
Authors: Guerric Meurice De Dormale, Philippe Bulens, Jean-Jacques Quisquater
Venue: Proceedings of the 9th international workshop on Cryptographic Hardware and Embedded Systems (2007)

In this last decade, Elliptic Curve Cryptography (ECC) has gained increasing acceptance in the industry and the academic community and has been the subject of several standards. This interest is mainly due to the high level of security with relatively small keys provided by ECC. Indeed, no sub-exponential algorithms are known to solve the underlying hard problem: the Elliptic Curve Discrete Logarithm.The aim of this work is to explore the possibilities of dedicated hardware implementing the best known algorithm for generic curves: the parallelized Pollard's ρ method. This problem has specific constraints and requires therefore new architectures. Four different strategies were investigated with different FPGA families in order to provide the best area-time product, according to the capabilities of the chosen platforms. The approach yielding the best throughput over hardware cost ratio is then fully described and was implemented in order to estimate the cost of an attack. Such results should help to improve the accuracy of the security level offered by a given key size, especially for the shorter parameters proposed for resource constrained devices.
An Analysis of Improvements for Voter Interfaces in Polling Station and Remote Electronic Voting Systems
Authors: Maider Huarte, Maria Madarieta, Iñaki Goirizelaia, Juan José Unzilla
Venue: Proceedings of the 10th international conference on Visual Information Systems: Web-Based Visual Information Search and Management (2008)

Due to the rapid growth of computer networks and advances in cryptography, Electronic Voting Systems are becoming a real option for voters. These systems must fulfil requirements such as accuracy, invulnerability, privacy, verifiability, convenience, flexibility and mobility, protected by the required security schemes. Those requirements guarantee that elections run on such systems are universal, equal, secret and free. Voter interfaces for those systems should be designed so that no eligible voter feels discriminated. Thus, they should be adapted even for disabled and illiterate voters. In this paper, we analyse different interfaces used in already developed and tested electronic voting systems, organizing them into polling station and remote system types. Then, we describe the interface of electronic voting systems and propose improvements to adapt them to all eligible voters. Afterwards, we perform the same analysis and corresponding proposals for remote electronic voting systems.
Improving software projects course work by enhanced management
Authors: Jyhjong Lin
Venue: Proceedings of the 7th WSEAS International Conference on Software Engineering, Parallel and Distributed Systems (2008)

Software projects are an important course in software engineering curricula. They provide students with an opportunity to gain valuable experiences in applying the theoretical materials learned at software engineering courses. However, many drawbacks in our current projects course work make these benefits difficult to realize. In this paper, we discuss these drawbacks and how they affect the effectiveness of this course. To address these difficulties, we advocate a model of enhancing the management approach to provide an effective administration for each project. Our experiments from the model have shown significant improvements in the quality of projects and the experiencing effects of students.