ppxscal/embedding_network huggingface dataset:
Scaling parallel I/O performance through I/O delegate and caching system
Authors: Arifa Nisar, Wei-keng Liao, Alok Choudhary
Venue: Proceedings of the 2008 ACM/IEEE conference on Supercomputing (2008)

Increasingly complex scientific applications require massive parallelism to achieve the goals of fidelity and high computational performance. Such applications periodically offload checkpointing data to file system for post-processing and program resumption. As a side effect of high degree of parallelism, I/O contention at servers doesn't allow overall performance to scale with increasing number of processors. To bridge the gap between parallel computational and I/O performance, we propose a portable MPI-IO layer where certain tasks, such as file caching, consistency control, and collective I/O optimization are delegated to a small set of compute nodes, collectively termed as I/O Delegate nodes. A collective cache design is incorporated to resolve cache coherence and hence alleviates the lock contention at I/O servers. By using popular parallel I/O benchmark and application I/O kernels, our experimental evaluation indicates considerable performance improvement with a small percentage of compute resources reserved for I/O.
Semantic Decision Tables: Self-organizing and Reorganizable Decision Tables
Authors: Yan Tang, Robert Meersman, Jan Vanthienen
Venue: Proceedings of the 19th international conference on Database and Expert Systems Applications (2008)

A Semantic Decision Table (SDT) provides a means to capture and examine decision makers' concepts, as well as a tool for refining their decision knowledge and facilitating knowledge sharing in a scalable manner. One challenge SDT faces is to organize decision resources represented in a tabular format based on the user's needs at different levels. It is important to make it self organized and automatically reorganized when the requirements are updated. This paper describes the ongoing research on SDT and its tool that supports the self organizations and automatic reorganization of decision tables. We argue that simplicity, precision, and flexibility are the key issues to respond to the paper challenge. We propose a novel combination of the principles of Decision Support and Database Modeling, together with the modern technologies in Ontology Engineering, in the adaptive self-organization and automatic reorganization procedures (SOAR).
On the Number of Linearly Independent Equations Generated by XL
Authors: Sondre Rønjom, Håvard Raddum
Venue: Proceedings of the 5th international conference on Sequences and Their Applications (2008)

Solving multivariate polynomial equation systems has been the focus of much attention in cryptography in the last years. Since most ciphers can be represented as a system of such equations, the problem of breaking a cipher naturally reduces to the task of solving them. Several papers have appeared on a strategy known as eXtended Linearization (XL) with a view to assessing its complexity. However, its efficiency seems to have been overestimated and its behaviour has yet to be fully understood. Our aim in this paper is to fill in some of these gaps in our knowledge of XL. In particular, by examining how dependencies arise from multiplication by monomials, we give a formula from which the efficiency of XL can be deduced for multivariate polynomial equations over $\mathbb{F}_2.$ This confirms rigorously a result arrived at by Yang and Chen by a completely different approach. The formula was verified empirically by investigating huge amounts of random equation systems with varying degree, number of variables and number of equations.
The Maximum Energy-Constrained Dynamic Flow Problem
Authors: Sándor P. Fekete, Alexander Hall, Ekkehard Köhler, Alexander Kröller
Venue: Proceedings of the 11th Scandinavian workshop on Algorithm Theory (2008)

We study a natural class of flow problems that occur in the context of wireless networks; the objective is to maximize the flow from a set of sources to one sink node within a given time limit, while satisfying a number of constraints. These restrictions include capacities and transit times for edges; in addition, every node has a bound on the amount of transmission it can perform, due to limited battery energy it carries. We show that this Maximum energy-constrained dynamic flow problem (ECDF) is difficult in various ways: it is NP-hard for arbitrary transit times; a solution using flow paths can have exponential-size growth; a solution using edge flow values may not exist; and finding an integral solution is NP-hard. On the positive side, we show that the problem can be solved polynomially for uniform transit times for a limited time limit; we give an FPTAS for finding a fractional flow; and, most notably, there is a distributed FPTAS that can be run directly on the network.
Automated Generation of Knowledge Plane Components for Multimedia Access Networks
Authors: Steven Latré, Pieter Simoens, Wim Meerssche, Bart Vleeschauwer, Filip Turck, Bart Dhoedt, Piet Demeester, Steven Berghe, Edith Gilon-De Lumley
Venue: Proceedings of the 3rd IEEE international workshop on Modelling Autonomic Communications Environments (2008)

The management of Quality of Experience (QoE) in the access network is largely complicated by the wide range of offered services, the myriad of possible QoE restoring actions and the increasing heterogeneity of home network configurations. The Knowledge Plane is an autonomic framework for QoE management in the access network, aiming to provide QoE management on a per user and per service basis. The Knowledge Plane contains multiple problem solving components that determine the appropriate restoring actions. Due to the wide range of possible problems and the requirement of being adaptive to new services or restoring actions, it must be possible to easily add or adapt problem solving components. Currently, generating such a problem solving component takes a lot of time and needs manual tweaking. To enable an automated generation, we present the Knowledge Plane Compiler which takes a service management objective as input, stating available monitor inputs and relevant output actions and determines a suitable neural network based Knowledge Plane incorporating this objective. The architecture of the compiler is detailed and performance results are presented.
Load balancing routing in multi-hop wireless networks
Authors: Yu Wang
Venue:  (2008)

Multi-hop wireless networks have attracted significant interests in recent years because of the improved flexibility, mobility and low-cost compared to wired networks. Routing in multi-hop wireless networks has been heavily studied in the last decade and numerous routing protocols were proposed in literature. Most current wireless routing protocols are based on Shortest Path Routing (SPR) where packets are delivered along the shortest route from a source to a destination. Even for geographical localized routing protocols, such as the greedy routing, the packets usually follow the shortest paths between sources and destinations when the network is dense and uniformly distributed. Taking the shortest path can achieve smaller delay or traveled distance. However, under uniform communication shortest path routing suffers from uneven load distribution in the network, such as crowded center effect where the center nodes have much heavier load than the nodes in the periphery. We propose a novel routing method, called Circular Sailing Routing (CSR) seeking to distribute the traffic more evenly in the network. The proposed method first maps the network onto a sphere via a simple stereographic projection. Then the route decision is made by the spherical distance on the sphere instead of the Euclidean distance in the plane. By spreading the traffic across a virtual sphere, CSR can diminish the crowded center effect and increase the energy lifetime of the network. CSR can be easily implemented by using current position-based routing protocol without any major changes or additional overhead. The only modification is a simple mapping calculation of the position information. We theoretically prove that for a network the distance traveled by the packets using CSR is no more than a small constant factor of the minimum (the distance of the shortest path). We call this factor as Competitiveness Factor. We then extend CSR to a localized version, Localized CSR, by modifying the greedy routing without any additional communication overhead. Although most existing wireless systems and protocols are based on two-dimensional (2D) design, in reality, a variety of networks operate in three-dimensional space. In this dissertation, we also investigate how to design CSR load balancing routing for 3D networks. We describe two mapping methods for 3D CSR, i.e., wireless nodes in a 3D network are projected on a 3D or 4D sphere. We provide theoretical proofs of their competitiveness compared to SPR. For all proposed methods, we conduct extensive simulations to study their performance and compare them with global shortest path routing or greedy routing in 2D and 3D wireless networks. The simulation results demonstrate our routing protocols have much smaller maximum traffic load and the standard deviation of traffic load and the simulation results also confirm our theoretical bounds about the competitiveness factor.
LoSS Detection Approach Based on ESOSS and ASOSS Models
Authors: Mohd Fo'ad Rohani, Mohd Aizaini Maarof, Ali Selamat, Houssain Kettani
Venue: Proceedings of the 2008 The Fourth International Conference on Information Assurance and Security (2008)

This paper investigates Loss of Self-similarity (LoSS) detection performance using Exact and Asymptotic Second Order Self-Similarity (ESOSS and ASOSS) models. Previous works on LoSS detection have used ESOSS model with fixed sampling that we believe is insufficient to reveal LoSS detection efficiently. In this work, we study two variables known as sampling level and correlation lag in order to improve LoSS detection accuracy. This is important when ESOSS and ASOSS models are considered concurrently in the self-similarity parameter estimation method. We used the Optimization Method (OM) to estimate the self-similarity parameter value since it was proven faster and more accurate compared to known methods in the literature. Our simulation results show that normal traffic behavior is not influenced by the sampling parameter. For abnormal traffic, however, LoSS detection accuracy is very much affected by the value of sampling level and correlation lag used in the estimation.
Geographical information systems and public accountability
Authors: A. Meijer
Venue: Information Polity (2002)

This paper explores the question which consequences the use of geographical information systems (GISs) may have for public accountability. Empirical data from a Delphi-survey were used for this exploration. Respondents were asked to reflect on the consequences of GISs for the availability of data for accountability. Based on their answers four hypotheses were formulated. The use of a GIS leads to an increased focus on up-to-date data at the expense of historical data. Important data for accountability will sometimes not be retained. The use of a GIS leads to an increased need to maintain about data how, when and by whom data have been generated. This need may not be sufficiently met. In a process of accountability, data from a GIS may then be difficult to interpret or cannot be trusted. A GIS increases the possibility to look at the data in different ways. In processes of accountability for a may ask governmental organizations to substantiate the choice fora certain perspective. The use of a GIS leads to better access to the data. Therefore, data from a GIS may play a more important role in a process of accountability. These hypotheses require further attention to gain a better understanding of long-term public accountability in an information age.
A Cognitive Model of Concept Learning with a Flexible Internal Representation System
Authors: Toshihiko Matsuka, Yasuaki Sakamoto
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

In the human mind, high-order knowledge is categorically organized, yet the nature of its internal representation system is not well understood. While it has been traditionally considered that there is a single innate representation system in our mind, recent studies suggest that the representational system is a dynamic, capable of adjusting a representation scheme to meet situational characteristics. In the present paper, we introduce a new cognitive modeling framework accounting for the flexibility in representing high-order category knowledge. Our modeling framework flexibly learns to adjust its internal knowledge representation scheme using a meta-heuristic optimization method. It also accounts for the multi-objective and the multi-notion natures of human learning, both of which are indicated as very important but often overlooked characteristics of human cognition.
Supporting Practices of Positive Redundancy for Seamless Care
Authors: Federico Cabitza, Carla Simone
Venue: Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems (2008)

The paper shows how redundancy can be put at work to play a positive role in facilitating the cognitive and coordinative tasks of clinicians in a ward setting. The main requirement to accomplish this positive function is to allow and support clinicians in annotating the clinical record and making correlations between redundant data explicit. We report an observational study we undertook in the design of coordination mechanisms based on a minimal set of meaningful correlations.
An Efficient Montgomery Exponentiation Algorithm for Cryptographic Applications
Authors: Chia-Long Wu, Der-Chyuan Lou, Te-Jen Chang
Venue: Informatica (2005)

Efficient computation of the modular exponentiations is very important and useful for public-key cryptosystems. In this paper, an efficient parallel binary exponentiation algorithm is proposed which based on the Montgomery multiplication algorithm, the signed-digit-folding (SDF) and common-multiplicand-multiplicand (CMM) techniques. By using the CMM technique of computing the common part from two modular multiplications, the same common part in two modular multiplications can be computed once rather twice, we can thus improve the efficiency of the binary exponentiation algorithm by decreasing the number of modular multiplications. By dividing the bit pattern of the minimal-signed-digit recoding exponent into three equal length parts and using the technique of recording the common parts in the folded substrings, the proposed SDF-CMM algorithm can improve the efficiency of the binary algorithm, thus can further decrease the computational complexity of modular exponentiation. Furthermore, by using the proposed parallel SDF-CMM Montgomery binary exponentiation algorithm, on average the total number of single-precision multiplications can be reduced by about 61.3% and 74.1% as compared with Chang-Kuo-Lin's CMM modular exponentiation algorithm and Ha-Moon's CMM Montgomery modular exponentiation algorithm, respectively.
Indirect Online Evolution --- A Conceptual Framework for Adaptation in Industrial Robotic Systems
Authors: Marcus Furuholmen, Kyrre Glette, Jim Torresen, Mats Hovin
Venue: Proceedings of the 8th international conference on Evolvable Systems: From Biology to Hardware (2008)

A conceptual framework for online evolution in robotic systems called Indirect Online Evolution (IDOE) is presented. A model specie automatically infers models of a physical system and a parameter specie simultaneously optimizes the parameters of the inferred models according to a specified target behavior. Training vectors required for modelling are automatically provided online by the interplay between the two coevolving species and the physical system. At every generation, only the estimated fittest individual of the parameter specie is executed on the physical system, hence limiting both the evaluation time, the wear out and the potential hazards normally associated with direct online evolution (DOE), where every candidate solution has to be evaluated on the physical system. Features of IDOE are demonstrated by inferring models of a simple hidden system containing geometric shapes that are further optimized according to a target value. Simulated experiments indicate that the fitness of the IDOE approach is generally higher than the average fitness of DOE.
Monitoring assisted robust routing in wireless mesh networks
Authors: Zainab R. Zaidi, Bjorn Landfeldt
Venue: Mobile Networks and Applications (2008)

In this paper, we present a monitoring assisted robust routing scheme for wireless mesh networks which exploits the broadcast nature of wireless transmissions at special routers with added monitoring functionalities. These routers passively listen to the transmissions in their neighborhood and compare the routing behavior against the routing state collectively maintained by them. If any inconsistency is found, as a result of software/hardware malfunction, these routers try to determine the node causing it and recover from it in a timely fashion. The scheme is developed for wireless mesh networks where the communication overhead is a critical issue. The performance evaluation of our scheme shows considerable improvement in reliability (i.e., delivery ratio achieved by standard routing protocols) with minimal overhead under situations of malfunctions.
An Insect-Inspired Active Vision Approach for Orientation Estimation with Panoramic Images
Authors: Wolfgang Stürzl, Ralf Möller
Venue: Proceedings of the 2nd international work-conference on The Interplay Between Natural and Artificial Computation, Part I: Bio-inspired Modeling of Cognitive Tasks (2007)

We present an insect-inspired approach to orientation estimation for panoramic images. It has been shown by Zeil et al. (2003) that relative rotation can be estimated from global image differences, which could be used by insects and robots as a visual compass [1]. However the performance decreases gradually with the distance of the recording positions of the images. We show that an active vision approach based on local translational movements can significantly improve the orientation estimation. Tests were performed with a mobile robot equipped with a panoramic imaging system in a large entrance hall. Our approach is minimalistic insofar as it is solely based on image differences.
Guarding Art Galleries: The Extra Cost for Sculptures Is Linear
Authors: Louigi Addario-Berry, Omid Amini, Jean-Sébastien Sereni, Stéphan Thomassé
Venue: Proceedings of the 11th Scandinavian workshop on Algorithm Theory (2008)

Art gallery problems have been extensively studied over the last decade and have found different type of applications. Normally the number of sides of a polygon or the general shape of the polygon is used as a measure of the complexity of the problem. In this paper we explore another measure of complexity, namely, the number of guards required to guard the boundary, or the walls, of the gallery. We prove that if n guards are necessary to guard the walls of an art gallery, then an additional team of at most 4n ¿ 6 will guard the whole gallery. This result improves a previously known quadratic bound, and is a step towards a possibly optimal value of n ¿ 2 additional guards. The proof is algorithmic, uses ideas from graph theory, and is mainly based on the definition of a new reduction operator which recursively eliminates the simple parts of the polygon. We also prove that every gallery with c convex vertices can be guarded by at most 2c ¿ 4 guards, which is optimal.
Usages of Generalization in Case-Based Reasoning
Authors: Eva Armengol
Venue: Proceedings of the 7th international conference on Case-Based Reasoning: Case-Based Reasoning Research and Development (2007)

The aim of this paper is to analyze how the generalizations built by a CBR method can be used as local approximations of a concept. From this point of view, these local approximations can take a role similar to the global approximations built by eager learning methods. Thus, we propose that local approximations can be interpreted either as: 1) a symbolic similitude among a set of cases, 2) a partial domain model, or 3) an explanation of the system classification. We illustrate these usages by solving the Predictive Toxicology task.
Probability and Information: An Integrated Approach, 2 edition
Authors: David Applebaum
Venue:  (2008)

This new and updated textbook is an excellent way to introduce probability and information theory to students new to mathematics, computer science, engineering, statistics, economics, or business studies. Only requiring knowledge of basic calculus, it begins by building a clear and systematic foundation to probability and information. Classic topics covered include discrete and continuous random variables, entropy and mutual information, maximum entropy methods, the central limit theorem and the coding and transmission of information. Newly covered for this edition is modern material on Markov chains and their entropy. Examples and exercises are included to illustrate how to use the theory in a wide range of applications, with detailed solutions to most exercises available online for instructors.
PSO for Selecting Cutting Tools Geometry
Authors: Orlando Duran, Nibaldo Rodriguez, Luiz Airton Consalter
Venue: Proceedings of the 3rd international workshop on Hybrid Artificial Intelligence Systems (2008)

Today an extensive variety of cutting tool is available to suit different cutting situations and needs. Cutting tool selection is a very important subtask involved in process planning activities. This paper proposes the application of the particle swarm optimization (PSO) process for the definition of the optimal cutting tool geometry. This optimization model was developed considering an approach to the macro-level optimization of tool geometry in machining model satisfying technological constraints. To determine the most appropriate configuration of the algorithm and its parameters a set of tests were carried out. The different parameters settings were tested against data obtained from the literature. A variety of simulations were carried out to validate the performance of the system and to show the usefulness of the applied approach. The definition of proposed system also has presented the following main conclusion: through the utilization of the PSO approach, the selection of the appropriate cutting tool geometry is possible in real world environments.
Visualizing Web Search Results in 3D
Authors: Wojciech Cellary, Wojciech Wiza, Krzysztof Walczak
Venue: Computer (2004)

Periscope presents a holistic view of data related to a search query.
An Overview of Separation Logic
Authors: John C. Reynolds
Venue: Verified Software: Theories, Tools, Experiments: First IFIP TC 2/WG 2.3 Conference, VSTTE 2005, Zurich, Switzerland, October 10-13, 2005, Revised Selected Papers and Discussions (2005)

After some general remarks about program verification, we introduce separation logic, a novel extension of Hoare logic that can strengthen the applicability and scalability of program verification for imperative programs that use shared mutable data structures or shared-memory concurrency.