ppxscal/embedding_network huggingface dataset:
On the Probability of Facing Fault Patterns: A Performance and Comparison Measure of Network Fault-Tolerance
Authors: Farshad Safaei, Ahmad Khonsari, Reza Moraveji
Venue: Proceedings of the 8th international conference on Computational Science, Part I (2008)

An important issue in the design and deployment of interconnection networks is the issue of network fault-tolerance for various types of failures. In designing parallel processing using torus as the underlying interconnection topology as well as in designing real applications on such processors, the estimates of the network reliability and fault-tolerance are important in choosing the routing algorithms and predicting their performance in the presence of faulty nodes. Under node-failure model, the faulty nodes may coalesce into fault patterns, which classified into two major categories, i.e., convex (|-shaped, $\Box$-shaped) and concave (L-shaped, T-shaped, +-shaped, H-shaped, U-shaped) regions. In this correspondence, we propose the first solution for computing the probability of message facing the fault patterns in tori both for convex and concave regions that is verified using simulation experiments. Our approach works for any number of faults as long as the network remains connected. We use these models to measure the network faulttolerance that can be achieved by adaptive routings, and to assess the impact of various fault patterns on the performance of such networks.
Study of collaborative design system based on HOOPS/NET
Authors: Guolin Duan, Xuan Liu, Jin Cai
Venue: Proceedings of the 8th WSEAS International Conference on Robotics, Control and Manufacturing Technology (2008)

Against current situation that collaborative design system emphasizes rapping off but dissociates from the practical design or modeling process, a HOOPS/NET-based collaborative design system is presented which is closely associated with 3D modeling software. In this paper, the architectural structure of the system is analyzed; the key technologies about how to realize the client terminal, message handling mechanism and the solution for message conflicts are introduced in detail, and the working flow of system operating is also summarized.
The Privacy Advocates: Resisting the Spread of Surveillance
Authors: Colin J. Bennett
Venue:  (2008)

Today, personal information is captured, processed, and disseminated in a bewildering variety of ways, and through increasingly sophisticated, miniaturized, and distributed technologies: identity cards, biometrics, video surveillance, the use of cookies and spyware by Web sites, data mining and profiling, and many others. In The Privacy Advocates, Colin Bennett analyzes the people and groups around the world who have risen to challenge the most intrusive surveillance practices by both government and corporations. Bennett describes a network of self-identified privacy advocates who have emerged from civil societywithout official sanction and with few resources, but surprisingly influential. A number of high-profile conflicts in recent years have brought this international advocacy movement more sharply into focus. Bennett is the first to examine privacy and surveillance not from a legal, political, or technical perspective but from the viewpoint of these independent activists who have found creative ways to affect policy and practice. Drawing on extensive interviews with key informants in the movement, he examines how they frame the issue and how they organize, who they are, and what strategies they use. He also presents a series of case studies that illustrate how effective their efforts have been, including conflicts over key-escrow encryption (which allows the government to read encrypted messages), online advertising through third-party cookies that track users across different Web sites, and online authentication mechanisms such as the short-lived Microsoft Passport. Finally, Bennett considers how the loose coalitions of the privacy network could develop into a more cohesive international social movement.
Computer aided dimensional analysis for knowledge management in chemical engineering processes
Authors: F. A. Batzias, A. S. Kakos, N. P. Nikolaou
Venue: Journal of Computational Methods in Sciences and Engineering (2005)

An algorithmic procedure has been designed/developed for computer aided Dimensional Analysis (DA) of chemical engineering processes. The main purpose of this software is to construct/select the best combination of dimensionless groups describing adequately a process under certain criteria. The creation/operation of an Ontological Knowledge Base (OKB) plays a central role in this procedure as it provides, inter alia, the means for filtering/reducing the dimensionless groups obtained by solving the system of dimensional equations according to the Buckingham &Pi; Theorem. The successful implementation of this software is thoroughly presented step by step in a case of mass transfer (liquid drops moving in immiscible liquids).
Short-range principle in the theory of the charge carrier scattering in CdHgSe solid solution
Authors: O. P. Malyk
Venue: Proceedings of the 10th WSEAS International Conference on Mathematical Methods and Computational Techniques in Electrical Engineering (2008)

Electron scattering on the short-range potential caused by the interaction with polar and nonpolar optical phonons, piezoelectric and acoustic phonons, static strain, ionized impurities in CdxHg1-xSe (0 ≤ x ≤ 0.268) samples annealed in mercury vapour are considered. Within the framework of the precise solution of the stationary Boltzmann equation on the base of short-range principle the temperature dependences of electron mobility in the range 4.2 - 300 K are calculated. A good coordination of the theory to experiment in the investigated temperature range is established.
A Fuzzy Clustering Algorithm to Estimate the Parameters of Radial Basis Functions Neural Networks and Its Application to System Modeling
Authors: Antonios D. Niros, George E. Tsekouras
Venue: Proceedings of the 5th Hellenic conference on Artificial Intelligence: Theories, Models and Applications (2008)

We propose a two-staged fuzzy clustering algorithm to train radial basis function neural networks. The novelty of the contribution lies in the way we handle the input training data information between the two stages of the algorithm. The back-propagation method is employed to optimize the network parameters. The number of hidden nodes is determined by the iterative implementation of the fuzzy clustering and the back-propagation. Simulation results show that the methodology produces accurate models compared to the standard and more sophisticated techniques reported in the literature.
Detecting and Disposing Abnormal Signal Outliers with Masking Effect by Using Data Accumulated Generating Operation
Authors: Jian-zhou Wang, Jian-ning Wen, Dong-huai Sun, Hai-yan Lu
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 5 - Volume 05 (2008)

In this paper, we study a signal processing problem which concentrates on outlier detection and data mining in order to rediscover some useful information. Moreover, the great difficulty of the subject is caused by both the external environment and the internal mechanism. In the external, owing to limit of impersonal condition, such as, realistic disturbance from noise signal can not avoid. In the internal, the masking effect appears in outlying observation so as to produce some unreasonable results by data analysis. Therefore, based not only on the requirement of external quality assurance schemes, but also on internal quality control where screening for outliers should probably be part of the procedure for our main goal. As a consequence, we have applied data accumulated generating operation and sample median test for solving the conundrum.
Visualization of a Wall Shear Flow: Development of a New Particle Image Interrogation Method
Authors: P. Debaene, U. Kertzscher, L. Goubergrits, K. Affeld
Venue: Journal of Visualization (2005)

In this paper we propose a new method which might be useful to investigate the flow fields close to vaulted walls with spatial and temporal resolution. This kind of flow visualization is important in the field of biofluid mechanics, since a close relationship is assumed between flow and biological phenomena. This new method is non-invasive, and is also applicable for unsteady flows. It has been used to investigate the steady and the unsteady laminar flow in a rectangular duct, as well as the steady, laminar flow in two different U-shaped ducts, both with a backward facing step, one having a rectangular cross-section, the other a nearly elliptical cross-section. The results concurred well with analytical or numerical solutions.
Computer Science in the Information Age
Authors: John Hopcroft
Venue: Proceedings of the 2nd annual international workshop on Frontiers in Algorithmics (2008)

The last forty years have seen computer science evolve as a major academic discipline. Today the field is undergoing a major change. Some of the drivers of this change are the internet, the world wide web, large sensor networks, large quantities of information in digital form and the wide spread use of computers for accessing information. This change is requiring universities to revise the content of computer science programs. This talk will cover the changes in the theoretical foundations needed to support information access in the coming years.
Internal Density Theorems for Hierarchies of Continuous Functionals
Authors: Dag Normann
Venue: Proceedings of the 4th conference on Computability in Europe: Logic and Theory of Algorithms (2008)

One standard way of constructing a hierarchy of total, continuous functionals over a fixed set of base types is to use a suitable cartesian closed category of domains where we may construct the corresponding hierarchy of partial continuous functionals, and then extract the hereditarily total ones. One important theorem, when available, is the Density Theorem: Each finitary domain object can be extended to a total one.We will see how we in the context of limit spaces, may formulate and prove versions of the density theorems and avoid domain theory.
A Simulation Environment for Middle-Size Robots with Multi-level Abstraction
Authors: Daniel Beck, Alexander Ferrein, Gerhard Lakemeyer
Venue: RoboCup 2007: Robot Soccer World Cup XI (2008)

Larger fields in the Middle-size league as well as the effort to build mixed teams from different universities require a simulation environment which is capable to physically correctly simulate the robots and the environment. A standardized simulation environment has not yet been proposed for this league. In this paper we present our simulation environment, which is based on the Gazebo system. We show how typical Middle-size robots with features like omni-drives and omni-directional cameras can be modeled with relative ease. In particular, the control software for the real robots can be used with few changes, thus facilitating the transfer of results obtained in simulation back to the robots. We address some technical issues such as adapting time-triggered events in the robot control software to the simulation, and we introduce the concept of multi-level abstractions. The latter allows switching between faithful but computionally expensive sensor models and abstract but cheap approximations. These abstractions are needed especially when simulating whole teams of robots.
Fusing Edge Cues to Handle Colour Problems in Image Segmentation
Authors: I. Huerta, A. Amato, J. Gonzàlez, J. J. Villanueva
Venue: Proceedings of the 5th international conference on Articulated Motion and Deformable Objects (2008)

This paper presents a new background subtraction algorithm for mobile objects segmentation from a static background scene. Firstly, a case analysis of colour-motion segmentation problems is presented. Secondly, an architecture which fuses colour, intensity and edge cues is developed to cope the motion segmentation problems presented in the case analysis. Our approach first combines both colour and intensity cues in order to solve problems, such as saturation or the lack of the colour when the background model is built. Nonetheless, some colours problems presented in the case analysis are not solved yet, such as the camouflage in chroma. Then, in order to solve this problems a new cue based on edges is proposed. Finally, our approach which fuses colour, intensity and edge cues is presented, thereby obtaining accurate motion segmentation in both indoor and outdoor scenes.
Pre-processing Large Spatial Data Sets with Bayesian Methods
Authors: Saara Hyvönen, Esa Junttila, Marko Salmenkivi
Venue: Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases (2007)

Binary data appears in many spatial applications such as dialectology and ecology. We demonstrate that a simple Bayesian modeling approach can be used in pre-processing large spatial data sets with missing or uncertain data. Our experiments on real and synthetic data show that conducting the pre-processing phase before applying conventional data mining methods, such as PCA, clustering or NMF, improves the results significantly.
A space--time discontinuous Galerkin method for the time-dependent Oseen equations
Authors: J. J. W. van der Vegt, J. J. Sudirham
Venue: Applied Numerical Mathematics (2008)

A space-time discontinuous Galerkin finite element method for the Oseen equations on time-dependent flow domains is presented. The algorithm results in a higher order accurate conservative discretization on moving and deforming meshes and is well suited for hp-adaptation. A detailed analysis of the stability of the numerical discretization is given which shows that the algorithm is unconditionally stable, also when equal order polynomial basis functions for the pressure and velocity are used. The accuracy of the space-time discretization is investigated using a detailed hp-error analysis and computations on a model problem.
Automatic Transactions Identification in Use Cases
Authors: Mirosław Ochodek, Jerzy Nawrocki
Venue: Balancing Agility and Formalism in Software Engineering: Second IFIP TC 2 Central and East European Conference on Software Engineering Techniques, CEE-SET 2007, Poznan, Poland, October 10-12, 2007, Revised Selected Papers (2008)

Since the early 90's of the previous century, use cases have became informal industry standard for presenting functional requirements. The rapid popularity growth stimulated many different approaches for their presentation and writing styles. Unfortunately, this variability makes automatic processing of use cases very difficult. This problem might be mitigated by the use of transaction concept, which is defined as an atomic part of the use case scenario. In this paper we present approach to the automatic transaction discovery in the textual use cases, through the NLP analysis. The proposed solution was implemented as a prototype tool UCTD and preliminarily verified in a case study.
Dynamic sub-ontology evolution for traditional Chinese medicine web ontology
Authors: Yuxin Mao, Zhaohui Wu, Wenya Tian, Xiaohong Jiang, William K. Cheung
Venue: Journal of Biomedical Informatics (2008)

As a form of important domain knowledge, large-scale ontologies play a critical role in building a large variety of knowledge-based systems. To overcome the problem of semantic heterogeneity and encode domain knowledge in reusable format, a large-scale and well-defined ontology is also required in the traditional Chinese medicine discipline. We argue that to meet the on-demand and scalability requirement ontology-based systems should go beyond the use of static ontology and be able to self-evolve and specialize for the domain knowledge they possess. In particular, we refer to the context-specific portions from large-scale ontologies like the traditional Chinese medicine ontology as sub-ontologies. Ontology-based systems are able to reuse sub-ontologies in local repository called ontology cache. In order to improve the overall performance of ontology cache, we propose to evolve sub-ontologies in ontology cache to optimize the knowledge structure of sub-ontologies. Moreover, we present the sub-ontology evolution approach based on a genetic algorithm for reusing large-scale ontologies. We evaluate the proposed evolution approach with the traditional Chinese medicine ontology and obtain promising results.
An Ideal Observer for a Model of X-Ray Imaging in Breast Parenchymal Tissue
Authors: Craig K. Abbey, John M. Boone
Venue: Proceedings of the 9th international workshop on Digital Mammography (2008)

We develop and evaluate an ideal observer for model of the 3D spatial distribution of x-ray attenuation coefficients in the breast. This model relies on thresholding of an underlying Gaussian random field to generate binary objects representing the distribution of adipose and glandular tissue in the breast parenchyma. Our motivation is to evaluate an emerging breast CT device for breast cancer screening. We show how the thresholded Gaussian model fits into the Markov-Chain Monte-Carlo (MCMC) approach for evaluating ideal-observer performance devised by Kupinski et al. [JOSA-A, 2003], and we show some preliminary results indicating that the procedure can be made to generate qualitatively realistic simulations. We demonstrate improved performance of the MCMC ideal observer over a Hotelling linear filter in a small-scale simulation.
Hotness-Aware Sensor Networks
Authors: Dong Li, Yanmin Zhu, Li Cui, Lionel M. Ni
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems (2008)

In a realistic sensor network, in particular with a non-uniform deployment, sensor nodes inevitably have varying workloads. This causes a natural problem that some sensor nodes are subject to excessive power consumption and thus become hot. These hot nodes deplete much earlier resulting in system performance degradation. This paper proposes a systematic approach to design a hotness-aware sensor network where each node is able to obtain its own hotness information. Based on these vital information, the system is able to provide various technologies to protect the critical set of hot nodes. More specifically, we design a centralized optimal algorithm to derive the precise hotness of each node. In addition, we develop a completely distributed algorithm to estimate hotness with high accuracy. An effective hotness-aware MAC is developed to offer medium access priority to the nodes with higher hotness to protect and prolong their lifetimes. It is demonstrated, through both theoretical analysis and comprehensive simulations, that our approach is valuable to improving system performance of practical sensor networks.
Behavior-Based Access Control for Distributed Healthcare Environment
Authors: Mohammad H. Yarmand, Kamran Sartipi, Douglas G. Down
Venue: Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems (2008)

Privacy and security are critical requirements for using patient profiles in distributed healthcare environments. The amalgamation of new information technology with traditional healthcare workflows for sharing patient profiles has made the entire system vulnerable to security and privacy breaches. In this paper we present a novel access control model based on a framework designed for data and service interoperability in the healthcare domain. The proposed model for customizable access control captures the dynamic behavior of the user and determines access rights accordingly. The model is generic and flexible in the sense that an access control engine dynamically receives security effective factors from the subject user, and identifies the privilege level in accessing clinical data using different specialized components within the engine. Standard data representation formats are used to make the model compatible with different healthcare environments. The access control engine uses a flow-based approach to follow the user's behavior. The proposed model is supported by a real world case study.
OptIPuter: Enabling advanced applications with novel optical control planes and backplanes
Authors: Joe Mambretti
Venue: Future Generation Computer Systems (2009)

Many emerging and anticipated advanced applications have demanding requirements that cannot be supported using traditional communication services, architecture, and technologies. Such requirements include those related to high performance, large scale data volume transport, dynamic provisioning, path flexibility, and stringent determinism for all service parameters. The OptIPuter research initiative was established to investigate the potential for meeting these and other exceptional challenges by creating new types of communication services that could be implemented as complements to traditional approaches and, in some special cases, as alternatives. In particular, the OptIPuter initiative has been exploring advanced communication services based on individually addressable, dynamically allocated lightpaths. These approaches require novel control plane and backplane architecture and technology. As part of its core research agenda, the OptIPuter initiative designed and deployed such architecture and technology, which is described here along with a large scale testbed implementation, including national and international extensions. This testbed was used for a series of experiments, and the results are summarized.
CG-M-FOCUSS and Its Application to Distributed Compressed Sensing
Authors: Zhaoshui He, Andrzej Cichocki, Rafal Zdunek, Jianting Cao
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks (2008)

M-FOCUSS is one of the most successful and efficient methods for sparse representation. To reduce the computational cost of M-FOCUSS and to extend its availability for large scale problems, M-FOCUSS is extended to CG-M-FOCUSS by incorporating conjugate gradient (CG) iterations in this paper. Furthermore, the CG-M-FOCUSS is applied to distributed compressed sensing. We illustrate the performance of CG-M-FOCUSS by an MRI image reconstruction example, in which CG-M- FOCUSS can not only reconstruct the MRI image with high precision, but also considerably reduce the computational time.
Decision Tree for Tracking Learner's Emotional State Predicted from His Electrical Brain Activity
Authors: Alicia Heraz, Tariq Daouda, Claude Frasson
Venue: Proceedings of the 9th international conference on Intelligent Tutoring Systems (2008)

This paper proposes the use of machine learning techniques to build an efficient learner's emotional transition diagram transition. For information Extraction tasks, we led an experimentation in which we exposed a group of 17 learners to a series of pictures from the International Affective Picture System (IAPS). Decision tree classifier has demonstrated the best ability to learn model structure from data collected. Among the emotions involved in learning and according to the picture from IAPS and the current emotional state, we drew up the transition diagram. Our model aims to improve the task of predicting the emotional state in an Intelligent Tutoring System and achieve a prediction accuracy of 63.11%. These results suggest that the implementation of the decision tree algorithm in the intelligent tutoring system we are developing improves the ability for an ITS to track the learners emotional states.
FITTING: A Portal to Fit Potential Energy Functionals to ab initio Points
Authors: Leonardo Pacifici, Leonardo Arteconi, Antonio Laganà
Venue: Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007 (2007)

The design and the implementation in a Grid environment of an Internet portal devoted to best fitting potential energy functionals to ab initio data for few body systems is discussed. The case study of a generalized LEPS functional suited to fit reactive three body systems is discussed with an application to the NO2 system.