ppxscal/embedding_network huggingface dataset:
Virtual Distro Dispatcher: A Costless Distributed Virtual Environment from Trashware
Authors: Flavio Bertini, D. Davide Lamanna, Roberto Baldoni
Venue: Proceedings of the 5th international symposium on Parallel and Distributed Processing and Applications (2007)

Obsolete hardware can be effectively reused through intelligent software optimization, which is possible only when source code is available. Virtual Distro Dispatcher (VDD) is a system that produces virtual machines on a central server and projects them on a number of costless physical terminals. VDD is the result of an extreme software optimisation based on virtualization and terminal servers. VDD creates and projects Linux distros that are completely customizable and different from each other. They are virtual desktop machines that can be used for testing or developing and are completely controllable directly from each terminal. Memory consumption has been strongly reduced without sacrificing performances. Test results are encouraging to proceed with the research towards clustering.
Construction of Tree Automata from Regular Expressions
Authors: Dietrich Kuske, Ingmar Meinecke
Venue: Proceedings of the 12th international conference on Developments in Language Theory (2008)

Since recognizable tree languages are closed under the rational operations, every regular tree expression denotes a recognizable tree language. We provide an alternative proof to this fact that results in smaller tree automata. To this aim, we transfer Antimirov's partial derivatives from regular word expressions to regular tree expressions. For an analysis of the size of the resulting automaton as well as for algorithmic improvements, we also transfer the methods of Champarnaud and Ziadi from words to trees.
The Webbridge Framework for Building Web-Based Agent Applications
Authors: Alexander Pokahr, Lars Braubach
Venue: Languages, Methodologies and Development Tools for Multi-Agent Systems: First International Workshop, LADS 2007, Durham, UK, September 4-6, 2007. Revised Selected Papers (2008)

Web applications represent an important category of applications that owe much of their popularity to the ubiquitous accessibility using standard web browsers. The complexity of web applications is steadily increasing since the inception of the Internet and the way it is perceived changes from a pure information source to a platform for applications. Many different web frameworks exist that support recurring and tedious development tasks in order to simplify the process of building web applications. Most of the currently available web frameworks adhere to the widely accepted Model 2 design pattern that targets a clean separation of model, view and controller parts of an application in the sense of MVC. Nevertheless, existing frameworks are conceived to work with standard object-oriented business applications only and do not respect the particularities and possibilities of agent applications. Hence, in this paper a new architecture, in accordance with the Model 2 design pattern, is proposed that is able to combine the strengths of agent-based computing with web interactions. This architecture is the basis for the Jadex Webbridge framework, which enables a seamless integration of the Jadex BDI framework with state-of-the art JSP technology. The usage of web technology in combination with agents is further exemplified by an electronic bookstore case study.
The molecular electric quadrupole moment and electric-field-gradient induced birefringence (Buckingham effect) of Cl$_2$
Authors: Chiara Cappelli, Ulf Ekström, Antonio Rizzo, Sonia Coriani
Venue: Journal of Computational Methods in Sciences and Engineering (2004)

An ab initio investigation of the molecular properties rationalizing the electric-field-gradient induced birefringence (Buckingham effect) for Cl$_2$ is presented. The quadrupole moment is determined using hierarchies of basis sets and wavefunction models. The electric dipole polarizability, the dipole - dipole - quadrupole and dipole - dipole - magnetic dipole hyperpolarizabilities are determined exploiting a Coupled Cluster Singles and Doubles (CCSD) response approach. The properties are zero-point vibrationally averaged, and the contribution of excited ro-vibrational states accounted for. To this end, the interatomic $^1$&Sigma;$_g^+$ ground state potential has been computed at CCSD plus perturbative triples - CCSD(T) - level employing a large augmented correlation consistent basis set. The effect of relativity is estimated at the Dirac-Hartree-Fock level. Our best value for the quadrupole moment of Cl$_2$ is (2.327 &plusmn; 0.010) au and it is in excellent agreement with experiment which, after revision and dependent on the procedure employed for correcting the original estimate of (2.24 &plusmn; 0.04) au of Graham et al., [Mol. Phys., 93, 49, (1998)], ranges from (2.31 &plusmn; 0.04) au to (2.36 &plusmn; 0.04) au.
Privacy-Preserving Publication of User Locations in the Proximity of Sensitive Sites
Authors: Bharath Krishnamachari, Gabriel Ghinita, Panos Kalnis
Venue: Proceedings of the 20th international conference on Scientific and Statistical Database Management (2008)

Location-based services, such as on-line maps, obtain the exact location of numerous mobile users. This information can be published for research or commercial purposes. However, privacy may be compromised if a user is in the proximity of a sensitive site (e.g., hospital). To preserve privacy, existing methods employ the K-anonymity paradigm to hide each affected user in a group that contains at least K ¿ 1 other users. Nevertheless, current solutions have the following drawbacks: (i) they may fail to achieve anonymity, (ii) they may cause excessive distortion of location data and (iii) they incur high computational cost.In this paper, we define formally the attack model and discuss the conditions that guarantee privacy. Then, we propose two algorithms which employ 2-D to 1-D transformations to anonymize the locations of users in the proximity of sensitive sites. The first algorithm, called MK, creates anonymous groups based on the set of user locations only, and exhibits very low computational cost. The second algorithm, called BK, performs bichromatic clustering of both user locations and sensitive sites; BK is slower but more accurate than MK. We show experimentally that our algorithms outperform the existing methods in terms of computational cost and data distortion.
Visualizing G&ouml;rtler Vortices
Authors: S. H. Winoto, H. Mitsudharmadi, D. A. Shah
Venue: Journal of Visualization (2005)

The development of G&ouml;rtler vortices with pre-set wavelength of 15 mm has been visualized in the boundary-layer on a concave surface of 2.0 m radius of curvature at a free-stream velocity of 3.0 m/s. The wavelength of vortices was pre-set by vertical wires of 0.2 mm diameter located 10 mm upstream of the concave surface leading edge. The velocity contours in the cross-sectional planes at several streamwise locations show the growth and breakdown of the vortices. Three different regions can be identified based on different growth rate of the vortices. The occurrence of a secondary instability mode is indicated by the formation of a small horseshoe eddies generated between the two neighboring vortices traveling streamwise, to form mushroom-like structures as a consequence of the non-linear growth of the G&ouml;rtler vortices.
Joint Routing and Channel Assignment in WMN Using Extended Petri Net
Authors: Hejiao Huang, Yun Peng, Jing Li
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems Workshops (2008)

This paper integrates routing, channel assignment and scheduling expecting for throughput optimization of traffic profile in wireless mesh networks (WMNs). In this paper, Extended Petri Net (EPN) is introduced to describe WMN for the first time. This model integrally describes the backbone structure of WMNs and the routing task of it. By EPN routing, channel assignment and scheduling are seamlessly integrated together and the routing task is translated into a classic problem in Petri net. It opens up a new way for WMNs research. Further more, a genetic algorithm is propose and our evaluation demonstrates that it performs much better than the famous Shortest Path algorithm.
Extending database query models for intuitive data retrieval and analysis
Authors: Divyakant Agrawal
Venue:  (2007)

With the ubiquitous adoption of the World Wide Web, an overwhelming amount of high quality, structured data becomes available on the Web. Unlike in the traditional context, Web databases are directly accessible by end users. To help ordinary users overcome the information overload in structured data, current databases need to improve the usability as well as the querying capability. This thesis makes an effort in this direction by introducing novel, user-friendly query types into existing data management systems and discussing techniques for enabling efficient and scalable implementations of these query operators. We focus on three query types, namely ranking queries, skyline queries and free-text (keyword) queries. Both ranking query and keyword query are the most intuitive query paradigms and have been the most popular way for ordinary users to express their information needs. However, due to the common coexistence of numerical and categorical attributes in the structured data, it is hard for an end user to specify the ranking function themselves. This is where the skyline query comes in. Skyline query and its variants return a set of "interesting" records from a database based on a set of attributes that a user wants to optimize. Any record in the skyline are guaranteed to be of interest assuming a monotonic preference. Our investigation covers two typical application scenarios: data retrieval and data analysis. We first study several distributed top-k algorithms, then we explore how scalable computation of skyline queries can be achieved via parallel processing as well as incrementally maintaining a computed result set. Finally, in the data analysis context, we show how skyline operations and keyword queries can be incorporated into OLAP systems to greatly enhance their query capability and usability.
Robust Kinetic Convex Hulls in 3D
Authors: Umut A. Acar, Guy E. Blelloch, Kanat Tangwongsan, Duru Türkoğlu
Venue: Proceedings of the 16th annual European symposium on Algorithms (2008)

Kinetic data structures provide a framework for computing combinatorial properties of continuously moving objects. Although kinetic data structures for many problems have been proposed, some difficulties remain in devising and implementing them, especially robustly. One set of difficulties stems from the required update mechanisms used for processing certificate failures--devising efficient update mechanisms can be difficult, especially for sophisticated problems such as those in 3D. Another set of difficulties arises due to the strong assumption in the framework that the update mechanism is invoked with a single event. This assumption requires ordering the events precisely, which is generally expensive. This assumption also makes it difficult to deal with simultaneous events that arise due to degeneracies or due to intrinsic properties of the kinetized algorithms. In this paper, we apply advances on self-adjusting computation to provide a robust motion simulation technique that combines kinetic event-based scheduling and the classic idea of fixed-time sampling. The idea is to divide time into a lattice of fixed-size intervals, and process events at the resolution of an interval. We apply the approach to the problem of kinetic maintenance of convex hulls in 3D, a problem that has been open since 90s. We evaluate the effectiveness of the proposal experimentally. Using the approach, we are able to run simulations consisting of tens of thousands of points robustly and efficiently.
Modular structures in the open architecture systems
Authors: Luige Vladareanu, Lucian M. Velea, Alexandru Vasile, Adrian Curaj, Aurelian Vasile
Venue: Proceedings of the 9th WSEAS International Conference on Acoustics & Music: Theory & Applications (2008)

The paper presents mainly the possibility of introducing on process distributed and decentralized modular structures which use programmable logical automates, thereby offering all the facilities for real time control and additionally the possibility of interactive interfacing with a PC by developing an open architecture system. To this end, a modular structure in open architecture system is developed, based on the SCADA concept of control in complex automations, dedicated to the modular control system for grain mills. Economic analyses reveal that in comparison with a centralized structure the presented system with modularized and decentralized structure significantly reduces efforts with conceiving, designing and controlling the technological flux. A modern solution is thus offered for conceiving and developing of new complex automation installations and updating existing ones.
Trilateration Analysis for Movement Planning in a Group of Mobile Robots
Authors: Svetoslav Genchev, Pencho Venkov, Boris Vidolov
Venue: Proceedings of the 13th international conference on Artificial Intelligence: Methodology, Systems, and Applications (2008)

This paper presents a real-time, low-computation trilateration model, designed for teams of cooperating mobile robots, working in unknown in-door environments without GPS signal accessibility. It allows to analytically build precision maps of the working area, giving information for the potential localization errors in each point of the space around the robots and thus simplifying movement planning and tracking. The technique relies on Time-Of-Flight measurements between several members of the team, used as static beacons, and the rest of the robots currently in motion. Simple parameter analysis is proposed for choosing the best suited robots to act as beacons for a given task. The performances of the mathematical and the statistical models have been validated numerically by computer simulations.
A semantic web service environment for B2B and B2C auction applications within extended and virtual enterprises
Authors: Harinder Jagdev, Laurentiu Vasiliu, Jim Browne, Michal Zaremba
Venue: Computers in Industry (2008)

Existing web services specifications lack an appropriate semantic framework for the creation and operation of emerging manufacturing systems such as the supply chains and extended/virtual enterprises (EE/VE) in order to execute business processes over internet. Semantic web services (SWS) technology aims to add sufficient semantics to the specifications and implementations of web services to make possible the (automatic) integration of distributed autonomous systems, with independently designed data and behaviour models. Defining data, behaviour and system components in a machine understandable way using ontologies provides the basis for reducing the need for humans to be in the loop for routine system integration processes. In this paper we present the design and implementation of a unique bid auction application for procurement automation within supply chains embedded in extended and virtual enterprises. We show how emerging semantic web services technologies such as the web services execution environment (WSMX) facilitate the creation of such applications, and we discuss the advantages of such applications.
A Generative Model for Motion Synthesis and Blending Using Probability Density Estimation
Authors: Dumebi Okwechime, Richard Bowden
Venue: Proceedings of the 5th international conference on Articulated Motion and Deformable Objects (2008)

The main focus of this paper is to present a method of reusing motion captured data by learning a generative model of motion. The model allows synthesis and blending of cyclic motion, whilst providing it with the style and realism present in the original data. This is achieved by projecting the data into a lower dimensional space and learning a multivariate probability distribution of the motion sequences. Functioning as a generative model, the probability density estimation is used to produce novel motions from the model and gradient based optimisation used to generate the final animation. Results show plausible motion generation and lifelike blends between different actions.
Nonlinear Function Learning Using Radial Basis Function Networks: Convergence and Rates
Authors: Adam Krzyżak, Dominik Schäfer
Venue: Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing (2006)

We apply normalized RBF networks to the problem of learning nonlinear regression functions. The parameters of the networks are learned by empirical risk minimization and complexity regularization. We study convergence of the RBF networks for various radial kernels as the number of training samples increases. The rates of convergence are also examined.
Up and Down: Mining Multidimensional Sequential Patterns Using Hierarchies
Authors: Marc Plantevit, Anne Laurent, Maguelonne Teisseire
Venue: Proceedings of the 10th international conference on Data Warehousing and Knowledge Discovery (2008)

Data warehouses contain large volumes of time-variant data stored to help analysis. Despite the evolution of OLAP analysis tools and methods, it is still impossible for decision makers to find data mining tools taking the specificity of the data (e.g. multidimensionality, hierarchies, time-variant) into account. In this paper, we propose an original method to automatically extract sequential patterns with respect to hierarchies. This method extracts patterns that describe the inner trends by displaying patterns that either go from precise knowledge to general knowledge or go from general knowledge to precise knowledge. For instance, one rule exhibited could be data contain first many sales of coke in Paris and lemonade in London for the same date, followed by a large number of sales of soft drinks in Europe, which is said to be divergent (as precise results like coke precede general ones like soft drinks). On the opposite, rules like data contain first many sales of soft drinks in Europe and chips in London for the same date, followed by a large number of sales of coke in Paris are said to be convergent. In this paper, we define the concepts related to this original method as well as the associated algorithms. The experiments which we carried out show the interest of our proposal.
Intel's Technology Vision and Products for HPC
Authors: Paweł Gepner
Venue: Proceedings of the 8th international conference on Computational Science, Part I (2008)

Traditionally most hardware and software architectural innovations have come through High End Computing. Today, innovation moves up from the bottom (low-power) and down from the top (parallelization) but the High-End is still a main foundation of new ideas. What is in today's supercomputer will be in tomorrow's desktop. What Intel does for HPC and what is the Intel vision and product portfolio for HPC segment will be covered during the lecture.
Neurofuzzy Power Plant Predictive Control
Authors: Xiang-Jie Liu, Ji-Zhen Liu
Venue: Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks (2007)

In unit steam-boiler generation, a coordinated control strategy is required to ensure a higher rate of load change without violating thermal constraints. The process is characterized by nonlinearity and uncertainty. Using of neuro-fuzzy networks (NFNs) to represent a nonlinear dynamical process is one choice. Two alternative methods of exploiting the NFNs within a generalised predictive control (GPC) framework are described. Coordinated control of steam-boiler generation using the two nonlinear GPC methods show excellent tracking and disturbance rejection results.
Introductory steps for an indexing based HDMR algorithm: lumping HDMR
Authors: M. Alper Tunga, Metin Demiralp
Venue: Proceedings of the 1st WSEAS International Conference on Multivariate Analysis and its Application in Science and Engineering (2008)

Generalized HDMR can be used to partition the given multivariate data set into less variate data sets to avoid the standard numerical methods' restrictions coming from the multivariance and to minimize the memory insufficiencies occured in the computer based applications when all nodes of the whole domain defined for an multivariate interpolation problem are not given, that is, randomly selected nodes are given. Hovewer, this method has some disadvantages to obtain acceptable approximations in engineering problems. For this purpose, High Dimensional Model Representation (HDMR) method can be used in these types of problems. In fact, this method needs an orthogonal geometry. The main purpose of this work is to reconstruct the given multivariate data set by imposing an indexing scheme and to obtain an orthogonal geometry for the given problem. The introductory steps of this new method called Lumping HDMR are given in this work. The remaining details and the maturization of this new method is still under intense study.
Evaluating the Quality of a Network Topology through Random Walks
Authors: Anne-Marie Kermarrec, Erwan Merrer, Bruno Sericola, Gilles Trédan
Venue: Proceedings of the 22nd international symposium on Distributed Computing (2008)

In this brief announcement we propose a distributed algorithm to assess the connectivity quality of a network, be it physical or logical. In large complex networks, some nodes may play a vital role due to their position (e.g. for routing or network reliability). Assessing global properties of a graph, as importance of nodes, usually involves lots of communications; doing so while keeping the overhead low is an open challenge. To that end, centrality notions have been introduced by researchers (see e.g. [Fre77]) to rank the nodes as a function of their importance in the topology. Some of these techniques are based on computing the ratio of shortest-paths that pass through any graph node. This approach has a limitation as nodes "close" from the shortest-paths do not get a better score than any other arbitrary ones. To avoid this drawback, physician Newman proposed a centralized measure of betweenness centrality [New03] based on random walks: counting for each node the number of visits of a random walk travelling from a node i to a target node j, and then averaging this value by all graph source/target pairs. Yet this approach relies on the full knowledge of the graph for each system node, as the random walk target node should be known by advance; this is not an option in large-scale networks. We propose a distributed solution that relies on a single random walk travelling in the graph; each node only needs to be aware of its topological neighbors to forward the walk.