ppxscal/embedding_network huggingface dataset:
VATS: Virtualized-Aware Automated Test Service
Authors: Sebastian Gaisbauer, Johannes Kirschnick, Nigel Edwards, Jerry Rolia
Venue: Proceedings of the 2008 Fifth International Conference on Quantitative Evaluation of Systems (2008)

It is anticipated that by 2015 more than 75% of Information Technology infrastructure will be purchased as a service from service providers. Services will be hosted in virtualized shared resource pools referred to as Clouds. Service providers will need to ensure that customer performance requirements are satisfied while consuming an acceptable quantity of resources. This paper describes a Virtualization-aware Automated Testing Service (VATS). VATS is a framework for automated test execution in Cloud computing environments. It executes tests, manipulates virtualized infrastructure, and collects performance information. VATS uses HP LoadRunner as a load generator and provides the foundation for an automatic performance evaluator for Cloud environments. A case study describes our use of VATS with an SAP R/3 system running in a Xen-based virtualized resource pool. The results from VATS are used to determine the impact of virtual machine configuration parameters on a SAP system.
Cluster Computing in Drug Logistic Monitoring and Management
Authors: Guofeng Qin, Qiyan Li, Xiuying Deng
Venue: Proceedings of the 5th international conference on Cooperative Design, Visualization, and Engineering (2008)

We applied the cluster computing as a key technology for a drug logistic information system that we developed. In order to improve the dependability, scalability, and other QoS features of the server cluster, resource dynamic dispatching, task distribution, and workflow controlling were among the key issues that we focused in our development.
Application of the Particle Filter for Simple Gesture Recognition
Authors: Yang Weon Lee
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence (2008)

This paper describes a gesture recognition algorithm based on the particle filters, namely CONDENSATION. The particle filter is more efficient than any other tracking algorithm because the tracking mechanism follows Bayesian estimation rule of conditional probability propagation. 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
Modeling Phase Transition in Self-organized Mobile Robot Flocks
Authors: Ali Emre Turgut, Cristián Huepe, Hande Çelikkanat, Fatih Gökçe, Erol Şahin
Venue: Proceedings of the 6th international conference on Ant Colony Optimization and Swarm Intelligence (2008)

We implement a self-organized flocking behavior in a group of mobile robots and analyze its transition from an aligned state to an unaligned state. We briefly describe the robot and the simulator platform together with the observed flocking dynamics. By experimenting with robotic and numerical systems, we find that an aligned-to-unaligned phase transition can be observed in both physical and simulated robots as the noise level is increased, and that this transition depends on the characteristics of the heading sensors. We extend the Vectorial Network Model to approximate the robot dynamics and show that it displays an equivalent phase transition. By computing analytically the critical noise value and numerically the steady state solutions of this model, we show that the model matches well the results obtained using detailed physics-based simulations.
Analyzing Perceptual Representations of Complex, Parametrically-Defined Shapes Using MDS
Authors: Nina Gaißert, Christian Wallraven, Heinrich H. Bülthoff
Venue: Proceedings of the 6th international conference on Haptics: Perception, Devices and Scenarios (2008)

In this study we show that humans are able to form a perceptual space from a complex, three-dimensional shape space that is highly congruent to the physical object space no matter if the participants explore the objects visually or haptically. The physical object space consists of complex, shell-shaped objects which were generated by varying three shape parameters. In several psychophysical experiments participants explored the objects either visually or haptically and performed similarity ratings. Multidimensional scaling (MDS) analyses showed high congruency of the visual and haptic perceptual space to the physical object space. Additionally, visual and haptic exploration resulted in very similar MDS maps providing evidence for one shared perceptual space underlying both modalities.
Creating crowd variation with the OCEAN personality model
Authors: Funda Durupinar, Jan Allbeck, Nuria Pelechano, Norman Badler
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3 (2008)

Most current crowd simulators animate homogeneous crowds, but include underlying parameters that can be tuned to create variations within the crowd. These parameters, however, are specific to the crowd models and may be difficult for an animator or na&iuml;ve user to use. We propose mapping these parameters to personality traits. In this paper, we extend the HiDAC (High-Density Autonomous Crowds) system by providing each agent with a personality model in order to examine how the emergent behavior of the crowd is affected. We use the OCEAN personality model as a basis for agent psychology. To each personality trait we associate nominal behaviors; thus, specifying personality for an agent leads to an automation of the low-level parameter tuning process. We describe a plausible mapping from personality traits to existing behavior types and analyze the overall emergent crowd behaviors.
Integral refinable operators exact on polynomials
Authors: L. Gori, E. Pellegrino, E. Santi
Venue: Journal of Computational and Applied Mathematics (2008)

We study integral refinable operators of integral type exact on polynomials of even degree constructed by using refinable B-bases of GP type. We prove a general theorem of existence and uniqueness. Then we study the L^p-norm of these operators and we give error bounds in approximating functions and their derivatives belonging to suitable classes. Numerical results and comparisons with other quasi-interpolatory operators having the same order of exactness on polynomial reproduction are presented.
Simulation of Swimming Organisms: Coupling Internal Mechanics with External Fluid Dynamics
Authors: Ricardo Cortez, Lisa Fauci, Nathaniel Cowen, Robert Dillon
Venue: Computing in Science and Engineering (2004)

Problems in biological fluid dynamics typically involve the interaction of an elastic structure with its surrounding fluid. A unified computational approach, based on an immersed boundary framework, couples the internal force-generating mechanisms of organisms and cells with an external, viscous, incompressible fluid.
Marketplace Issues in Software Planning and Design
Authors: David G. Messerschmitt, Clemens Szyperski
Venue: IEEE Software (2004)

For commercial software sold in the general marketplace, many software-planning and design decisions are based not only on meeting user needs but also on various marketplace issues. Many of these issues fall into one of three standard ROI categories: revenue, cost, and risk. For revenue, market share and market size play against one another, but the major considerations are increasing value (and extracting that value through pricing strategies) and minimizing the customer's cost structure. Manipulating the supplier's cost structure depends on the method of software distribution, the management of recurring costs (such as maintenance), and software reuse. Software development always entails a risk that actual revenues and costs might deviate from plan. The most effective way to manage this risk is an integrated approach at the project, organizational, and industry levels through decision techniques, management of intellectual property, investment diversification, and industry cooperation.
A differential OFDM approach to coherence time mitigation in DSRC
Authors: Youwei Zhang, Ian L. Tan, Carl Chun, Ken Laberteaux, Ahmad Bahai
Venue: Proceedings of the fifth ACM international workshop on VehiculAr Inter-NETworking (2008)

As a modification to IEEE 802.11a, the current DSRC standard copes adequately with many of the impairments found in the vehicular wireless channel. However, measurements have shown that these mobile channels exhibit substantially shorter coherence times than those encountered in the indoor environments expected by 802.11a. We propose a modification to the coherent OFDM structure of DSRC, known as time-domain differential OFDM, that preserves the benefits of OFDM while adding robustness to short coherence times. Simulations verify the efficacy of this method over various Doppler spreads and packet lengths.
Cellular automata in financial applications
Authors: Gerardo Beni
Venue:  (2008)

This dissertation is concerned with the application of Cellular Automata (CA) to financial models. Because of ever increasing computational power in storing and processing real-time multi-dimensional data from global financial markets, researchers and professionals discovered many interesting market characteristics, which challenge the basic assumptions of conventional models, including the Efficient Market Theory, the Geometric Brownian Motion, and the Black-Scholes Theory. In particular, these models fail to explain serious market anomalies, including sudden crashes. Thus, new effective methodologies to account for real markets' behavior are actively researched. The methodology described in this dissertation is based on Cellular Automata (CA). CA-based models directly address the market micro-structure. The basic idea is to have a large group of interacted agents, and to specify individual evolution rules for the market participants to mimic various market trading mechanisms. Instead of relying on mathematical descriptions of market macro-behaviors, CA-based models generate market macro-behaviors from the aggregate behaviors of a large population of agents. This bottom-up idea provides a new perspective for explaining some market puzzles that cannot be resolved by conventional models. The contributions lie in the following aspects: (1) A CA-based model is proposed and applied to derivatives pricing, price dynamics modeling and market microstructure. For each application, we obtain plausible explanations for key market characteristics. Theoretical works to connect our model with the conventional ones are provided. (2) In the derivatives pricing application, the CA-based model is proven to generalize the Black-Scholes theory and the Binomial Tree model. (3) In the application to price dynamics, the model provides analytical results and understanding of bubble formation and burst, mean-reverting price mechanism, and volatility anomalies. (4) A Brief discussion about asynchronous CA is given in the end concerning future research directions.
Probabilistic Models Based on the Π-Sigmoid Distribution
Authors: Anastasios Alivanoglou, Aristidis Likas
Venue: Proceedings of the 3rd IAPR workshop on Artificial Neural Networks in Pattern Recognition (2008)

Mixture models constitute a popular type of probabilistic neural networks which model the density of a dataset using a convex combination of statistical distributions, with the Gaussian distribution being the one most commonly used. In this work we propose a new probability density function, called the &Pi;-sigmoid, from its ability to form the shape of the letter "&Pi;" by appropriately combining two sigmoid functions. We demonstrate its modeling properties and the different shapes that can take for particular values of its parameters. We then present the &Pi;-sigmoid mixture model and propose a maximum likelihood estimation method to estimate the parameters of such a mixture model using the Generalized Expectation Maximization algorithm. We assess the performance of the proposed method using synthetic datasets and also on image segmentation and illustrate its superiority over Gaussian mixture models.
Optimization of Tomosynthesis Acquisition Parameters: Angular Range and Number of Projections
Authors: Thomas Mertelmeier, Jasmina Ludwig, Bo Zhao, Wei Zhao
Venue: Proceedings of the 9th international workshop on Digital Mammography (2008)

In breast tomosynthesis several projection views of the object are acquired over a limited angular range from which slice images are reconstructed. The image quality of the reconstructed slices, however, depends on the geometric acquisitions parameters and on the reconstruction algorithm. We investigated the impact of the angular range of data acquisition and number of projection views on image quality by performing 3-D cascaded linear system modeling and phantom measurements. The results show that a larger angular range not only increases resolution perpendicular to the slices but also improves the visibility of low-frequency objects since the sampling area in Fourier space is mainly limited at low-frequencies. The effect on contrast resolution is demonstrated also with clinical data sets.
Interorganisational Architectural Framework Leveraging Web Services and AJAX
Authors: Jai Ganesh, Mayank Mathur
Venue: Proceedings of the 2008 IEEE Congress on Services - Part I (2008)

This paper discusses a prototype for managing complex and disparate interorganisational interconnections with internal as well as external partners using Web Services and leveraging AJAX (Asynchronous JavaScript and XML), to conduct engaging and responsive Web Services behavior. The architectural approach focuses on benefits of Web Services at the back-end at the same time bringing in increased end user usability at the front end.
Identifying and expanding titles in web texts
Authors: Clémentine Adam, Estelle Delpech, Patrick Saint-Dizier
Venue: Proceeding of the eighth ACM symposium on Document engineering (2008)

In this paper, we present an analysis based on linguistic and typographic features that allows for the identification of titles in web documents. We focus in particular on procedural texts. Identifying titles is a difficult task because ways of encoding them are very diverse. A number of titles are also incomplete because of context, we propose therefore a way to retrieve the missing elements, in particular predicates, so that titles are fully intelligible.
Factorizing information extraction from text corpora
Authors: Eduard Hovy
Venue:  (2007)

Automatic information extraction (IE) from unstructured text is critical for solving the information overload problem. As text formats become ever more varied and IE requirements become more demanding, target information becomes harder to define and extract. Therefore, IE procedures become more complex and generally require an iterative cycle involving multiple factors, such as the simple traditional IE framework is no longer adequate. However, a new paradigm of IE to address these issues has not been formalized yet. In this thesis, we develop a framework to formalize a more general and powerful procedure of IE. Our formalization provides a method to rapidly define and structure new IE tasks. For this procedure, we analyze the role and impact of each factor. This thesis makes two kinds of contributions: first, a new high-level and expressive framework that shows the relationships between activities such as domain knowledge modeling and representation, annotation, system building, evaluation, and feedback adjustment, etc., and second, several new approaches to performing various level IE tasks. We start with a simple IE task, extracting biographical facts from the web. Here a traditional, straightforward, and one-pass problem-solving procedure, consisting of definition-learning-testing, is sufficient. Our system automatically learns surface text patterns from dynamic flat web corpora for answering biographical queries. In addition, sentence fragments can serve as knowledge indicators to guide the handling of queries. We then demonstrate the new IE framework using two more-complex tasks. First, we investigate the problem of extracting data records (individual experiments) from the biomedical research literature. In conformance with the elaborated IE framework, we have developed approaches to labeling individual sentences, grouping fields into individual meaningful objects, and scaling the results up to large corpora. We design a novel solution to segment semantic objects based on semantic analysis, for cases where traditional word-similarity-based text segmentation approaches do not work. Second, the IE procedures need be adapted and extended for IE problems emerging from new media formats. We address the task of extracting the most informative message(s) from discussion threads. Since the relationship between thread messages characterizes how knowledge is spread, the IE framework has to accommodate the analysis of source structure. We describe a novel way to classify message and thread topics that requires zero annotation for a supervised approach, using ontological knowledge induced from a canonical text. We also invent a novel HITS-style algorithm with link generation functions to extract the conversation focus of discussion threads.
Note: An extended lower bound on the number of (≤k)-edges to generalized configurations of points and the pseudolinear crossing number of Kn
Authors: B. M. Ábrego, J. Balogh, S. Fernández-Merchant, J. Leaòos, G. Salazar
Venue: Journal of Combinatorial Theory Series A (2008)

Recently, Aichholzer, Garcia, Orden, and Ramos derived a remarkably improved lower bound for the number of (=
Some Notes on d-Form Functions with Difference-Balanced Property
Authors: Tongjiang Yan, Xiaoni Du, Enjian Bai, Guozhen Xiao
Venue: Proceedings of the 1st international workshop on Arithmetic of Finite Fields (2007)

The relation between a cyclic relative difference set and a cyclic difference set is considered. Both the sets are with Singer parameters and can be constructed from a difference-balanced d-form function. Although neither of the inversions of Klapper A.¿s and No J. S.¿s main theorems is true, we prove that a difference-balanced d-form function can be obtained by the cyclic relative difference set and the cyclic difference set introduced by these two main theorems respectively.
Machining of micro-systems
Authors: Berend Denkena, Hans-Werner Hoffmeister, Dennis Hahmann, Marcus Hlavac
Venue: Microsystem Technologies (2008)

An increasing trend towards miniaturization of mechanical components necessitates the further development of micro-machining techniques in order to produce components within given tolerances. For the dressing of multilayered, metallically bonded, fine-grained grinding wheels that are used for micro-grinding the technique of electro contact discharge dressing was developed. In the following, the determined interrelations between the variables dressing voltage, limitation of dressing current, infeed and feed of electrode, and the volume flow rate in conditioning as well as the quality factor in conditioning are presented and illustrated. Thanks to the development of new geometries of CVD-diamond micro-grinding-pencils, a reduction of edge disruptions as well as a reduction of tool diameters to a minimum of 250&#x00a0;&#x03bc;m for the machining of brittle materials could be achieved. For the micro-drilling of ductile materials the maximal drilling depth could be increased by means of an adjusted process control. The smallest examined drill diameter was 50&#x00a0;&#x03bc;m. The utilizability of the developed processes and tools was proven in the production of aerostatic micro-bearings in the scope of the collaborative research center (SFB) 516.
An Efficient Lagrangian Relaxation for the Contact Map Overlap Problem
Authors: Rumen Andonov, Nicola Yanev, Noël Malod-Dognin
Venue: Proceedings of the 8th international workshop on Algorithms in Bioinformatics (2008)

Among the measures for quantifying the similarity between protein 3-D structures, contact map overlap (CMO) maximization deserved sustained attention during past decade. Despite this large involvement, the known algorithms possess a modest performance and are not applicable for large scale comparison.This paper offers a clear advance in this respect. We present a new integer programming model for CMO and propose an exact B B algorithm with bounds obtained by a novel Lagrangian relaxation. The efficiency of the approach is demonstrated on a popular small benchmark (Skolnick set, 40 domains). On this set our algorithm significantly outperforms the best existing exact algorithms. Many hard CMO instances have been solved for the first time. To assess furthermore our approach, we constructed a large scale set of 300 protein domains. Computing the similarity measure for any of the 44850 couples, we obtained a classification in excellent agreement with SCOP.
Accessing grid resources from portals and applications
Authors: Felicia Ionescu, Silviu Popescu
Venue: Proceedings of the 9th WSEAS International Conference on International Conference on Automation and Information (2008)

The users of Grid-based applications and portals must be able to access Grid resources from different contexts, using high-level abstraction and full control of access parameters. Globus Toolkit, which is the most important solution for building Grid infrastructures, offers command line clients for access different resources such as data transfer using Grid FTP protocol and job submission using Gram services. But these clients are difficult to be used from different application and portals. This paper presents a complete and concise solution for the problem of access Grid resources from portals and applications through development of context-independent Java clients for accessing data transfer and execution management, and these clients can be used from applications and portals more efficiently and simpler than using command line clients offered by Globus Toolkit.
For Wireless USB, the Future Starts Now
Authors: Neal Leavitt
Venue: Computer (2007)

To overcome the limitations imposed by using cables, vendors are beginning to release USB products based on wireless technology.
Guest Editors' Introduction: 3D Documents
Authors: Dieter W. Fellner, Dietmar Saupe, Harald Krottmaier
Venue: IEEE Computer Graphics and Applications (2007)

The guest editors of this special issue describe the research problems in the field and the four articles they've chosen for the issue.
Informative Gene Set Selection Via Distance Sensitive Rival Penalized Competitive Learning and Redundancy Analysis
Authors: Liangliang Wang, Jinwen Ma
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

This paper presents an informative gene set selection approach to tumor diagnosis based on the Distance Sensitive Rival Penalized Competitive Learning (DSRPCL) algorithm and redundancy analysis. Since the DSRPCL algorithm can allocate an appropriate number of clusters for an input dataset automatically, we can utilize it to classify the genes (expressed by the gene expression levels of all the samples) into certain basic clusters. Then, we apply the post-filtering algorithm to each basic gene cluster to get the typical and independent informative genes. In this way we can obtain a compact set of informative genes. To test the effectiveness of the selected informative gene set, we utilize the support vector machine (SVM) to construct a tumor diagnosis system based on the express profiles of its genes. It is shown by the experiments that the proposed method can achieve a higher diagnosis accuracy with a smaller number of informative genes and less computational complexity in comparison with the previous ones.