ppxscal/embedding_network huggingface dataset:
Implementing efficient joint beliefs on multi-robot teams
Authors: Ian Douglas Horswill
Venue:  (2003)

In this report, I investigate the problem of coordinating multiple robots in a cooperative team activity. Many different approaches have been suggested for team coordination, ranging from swarm techniques to symbolic methods. I will propose a class of coordination protocols called broadcast-an-aggregate mechanisms and will describe a specific instantiation of this approach on a multi-robot control architecture called HIVEMind (Highly Interconnected Very Efficient Mind) which operates in the following way: (1) Each robot periodically broadcasts all its team-relevant data to its teammates. (2) Team members base control decisions on shared situational awareness formed by aggregating all broadcast data from the team. HIVEMind allows near-instantaneous sharing of data between all team members. This lets the team respond in real-time to contingencies sensed by individual robots. Furthermore, HIVEMind robots can use role-passing inference to support limited real-time symbolic reasoning over synchronized knowledgebases. This allows the use of more structured representations than conventional behavior-based systems, which in turn allows the team to be tasked and monitored in natural ways. All this is accomplished while using surprisingly little bandwidth. I will show that given the assumptions: (1) Relevant aspects of the environment change relatively quickly. (2) All team members must be informed of these changes in bounded time. (3) All team members must be able to detect if they are failing to receiving data in a timely manner from their teammates. The HIVEMind data sharing method is optimal in the sense that any communication scheme would have to transmit at least as many packets as it would. I also will describe an implementation of HIVEMind used to coordinate a team of robots in variety of tasks involving systematic search of physical space.
More accuracy at fixed precision
Authors: Philippe Langlois
Venue: Journal of Computational and Applied Mathematics (2004)

Several different techniques and software intend to improve the accuracy of results computed in a fixed finite precision. Here we focus on the CENA method that processes an automatic correction of the first-order effect of the rounding errors the computation generates. This method provides a corrected result and a bound of the residual error for a class of algorithms we identify. We present the main features of the CENA method and illustrate its interests and limitations with examples.
A BNF-based automatic test program generator for compatible microprocessor verification
Authors: Lieh-Ming Wu, Kuochen Wang, Chuang-Yi Chiu
Venue: ACM Transactions on Design Automation of Electronic Systems (TODAES) (2004)

A novel Backus-Naur-form- (BNF-) based method to automatically generate test programs from simple to complex ones for advanced microprocessors is presented in this paper. We use X86 architecture to illustrate our design method. Our method is equally applicable to other processor architectures by redefining BNF production rules. Design issues for an automatic program generator (APG) are first outlined. We have resolved the design issues and implemented the APG by a top-down recursive descent parsing method which was originated from compiler design. Our APG can produce not only random test programs but also a sequence of instructions for a specific module to be tested by specifying a user menu-driven file. In addition, test programs generated by our APG have the features of no infinite loop, not entering illegal states, controllable data dependency, flexible program size, and data cache testable. Our method has been shown to be efficient and feasible for the development of an APG compared with other approaches. We have also developed a coverage tool to integrate with the APG. Experimental evaluation of the generated test programs indicates that our APG, with the guidance of the coverage tool, only needs to generate a small number of test programs to sustain high coverage.
Integrated querying of XML data in RDBMSs
Authors: Albrecht Schmidt, Stefan Manegold, Martin Kersten
Venue: Proceedings of the 2003 ACM symposium on Applied computing (2003)

This paper proposes a way to integrate cleanly relational databases and XML documents. The main idea is to draw a clear line of demarcation between the two concepts by modelling XML documents as a new atomic SQL type. The standardised XML tools like XPath, XQuery, XSLT are then user-defined functions that operate on this type. Well-defined interoperability is guaranteed by, on the one hand, defining a standard way to markup SQL relations as XML documents and, thus, to make them accessible to the XML tools; on the other hand, XPath and XQuery queries run against the XML portion of the database can use the same predefined schema to make their results accessible to the SQL language for further processing. Additionally, a method for set-oriented evaluation of regular path expressions is presented that integrates into our implementation framework.
TPBDSR: A New DSR-Based Energy Saving Routing in MANET
Authors: Li Xu, Zi-wen Wu, Bao-yu Zheng
Venue: Proceedings of the 2003 International Conference on Computer Networks and Mobile Computing (2003)

As the use of small portable and mobile computing devices increase, the MANET (mobile ad hoc network) is become an increasingly popular topic of research and development activities.MANET is power constrained since nodes operate with limited battery energy. To maximize the lifetime of these networks at the same time of holding the conventional network performance. A new DSR-base energy saving routing is proposed and analyze in this paper.
Representing cultural alterity in hypermedia environments: design practices and prospects
Authors: Lisa A. Larson
Venue:  (2003)

This research project examines how humans are depicted in computer-based representations, with particular attention to the representation of cultural difference. Hypermedia environments from a range of sources are analyzed as sites of meaning making, including two websites built by the researcher, Growing Up in Northern Nigeria and Image Mosaic. This analysis considers the social practices that converge in these hypermedia representations, especially anthropological and museum practices, and how viewers negotiate these multiple social practices in their construction of meaning. These social practices are examined in relation to features of the hypermedia environments, including knowledge representation, interactivity, and agency, as manifested in navigation systems, images, text, and page designs. This project makes use of methods and analytic tools from semiotics, linguistics, and discourse analysis. A semiotic approach is used to investigate signs, connotations, oppositions, intertextuality, and subject positions in text and image, while a linguistic approach examines grammatical subject and referential terms. Discourse analytic methods are employed to consider the hypermedia page as a site of interaction between the designer, the viewer, and those who are represented. This study revealed key issues in the hypermedia representation of cultural alterity, including the constructed subject positions and agency of the viewer and of those depicted; the multiple interpretive layers present in representations, including the institutional; the often contradictory implications of text and image in representations; and the problematical nature of referential terms used for various cultural groups. Further research is called for on viewer interactions with hypermedia environments representing cultural alterity and on the influence of specific design elements on viewer experience. The study has three main pedagogical and policy implications. Given the increased reliance on complex visual representations across disciplines, visual literacy coursework should be considered essential to the curriculum. Because intercultural experience is increasingly computer-mediated, schools should provide students with tools for analyzing and making representations of cultural alterity, including careful attention to social ascription and agency. The designers of hypermedia environments representing cultural alterity, especially those aimed at children, should be increasingly attentive to the sources of their materials and the social practices influencing their representations.
On Some New Approaches to Practical Slepian-Wolf Compression Inspired by Channel Coding
Authors: Todd P. Coleman, Anna H. Lee, Muriel Médard, Michelle Effros
Venue: Proceedings of the Conference on Data Compression (2004)

We introduce three new innovations for compression using LDPCs for the Slepian-Wolfproblem. The first is a general iterative Slepian-Wolf decoding algorithm that incorporatesthe graphical structure of all the encoders and operates in a 'turbo-like' fashion. The secondinnovation introduces source-splitting to enable low-complexity pipelined implementationsof Slepian-Wolf decoding at rates besides corner points of the Slepian-Wolf region. Thisinnovation can also be applied to single-source block coding for reduced decoder complexity.The third approach is a linear programming relaxation to maximum-likelihood sequencedecoding that exhibits the ML-certificate property. This can be used for decoding a singlebinary block-compressed source as well as decoding at vertex points for the binary Slepian-Wolfproblem. All three of these innovations were motivated by recent analogous resultsin the channel coding domain.
Robust content-based image searches for copyright protection
Authors: Sid-Ahmed Berrani, Laurent Amsaleg, Patrick Gros
Venue: Proceedings of the 1st ACM international workshop on Multimedia databases (2003)

This paper proposes a novel content-based image retrieval scheme for image copy identification. Its goal is to detect matches between a set of doubtful images and the ones stored in the database of the legal holders of the photographies. If an image was stolen and used to create a pirated copy, it tries to identify from which original image that copy was created. The image recognition scheme is based on local differential descriptors. Therefore, the matching process takes into account a large set of variations that might have been applied to stolen images in order to create pirated copies. The high cost and the complexity of this image recognition scheme requires a very efficient retrieval process since many individual queries must be executed before being able to construct the final result. This paper therefore proposes to use a novel search method that trades the precision of each individual search for reduced query execution time. This imprecision has only little impact on the overall recognition performance since the final result is a consolidation of many partial results. However, it dramatically accelerates queries. This result has then been corroborated by a theoretically study. Experiments show the efficiency and the robustness of the proposed scheme.
Enhancing Text Classification Using Synopses Extraction
Authors: Liping Ma, John Shepherd, Yanchun Zhang
Venue: Proceedings of the Fourth International Conference on Web Information Systems Engineering (2003)

This paper describes a novel approach to document classification that uses decision-tree machine learning based on a succinct vector of important terms in each document. The succinct vector itself is generated by a machine-learning approach which builds parsers that can identify significant features in a document by partitioning it into regions based on low-level document characteristics. The fact that the feature vector is succinct overcomes the problem of very large term vectors, which have hindered the application of conventional machine learning to document classification. The fact that the parser can be trained to extract only important terms from documents means that small training sets can be used to achieve the same classification accuracy as with conventional approaches.
A Comparative Study of Feature Selection Methods for Probabilistic Neural Networks in Cancer Classification
Authors: Chenn-Jung Huang, Wei-Chen Liao
Venue: Proceedings of the 15th IEEE International Conference on Tools with Artificial Intelligence (2003)

Accurate diagnosis and classification is the key issue for the optimal treatment of cancer patients. Several studies demonstrate that cancer classification can be estimated with high accuracy, sensitivity and specificity from microarray-based gene expression profiling usingartificial neural networks. In this paper, a comprehensive study was undertaken to investigate the capability of the probabilistic neural networks (PNN) associated with a feature selection method, a so-called signal-to-noise statistic, in the application of cancer classification. The signal-to-noise statistic, which represents the correlation with the class distinction, is used to select the marker genes and trim the dimension of data samples for the PNN. The experimental results show that the association of the probabilistic neural network with the signal-to-noise statistic can achieve superior classification results for two types of acute leukemias and five categories of embryonal tumors of central nervous system with satisfactory computation speed. Furthermore, the signal-to-noise statistic analysis provides candidate genes for future study in understanding the disease process and the identification of potential targets for therapeutic intervention.
Computational intelligence in rate-based control for data networking
Authors: Robert Mcleod
Venue:  (2003)

The work presented in this thesis developed a negative acknowledgment based transport layer protocol called the versatile transport protocol (VTP). In addition to this a fuzzy neural network based fuzzy controller for the VTP was evaluated. The controller was developed by extending the Brain Construction Kit neural network simulation software to support fuzzy neural networks. The VTP controller was then used together with a client/server bulk transfer software called Phat (developed at the University of Manitoba), which acted as the emulation environment for VTP. To implement a generic multi-layered feed-forward fuzzy neural network, the generalized delta rule for back-propagation was extended to include both logic-based as well as arithmetic neural descriptions. To implement training of the network it was also necessary to develop a fuzzy back-propagation algorithm to guarantee the correctness of the connection strength parameters for logic-based neurons. In doing this a different view of the learning rate was required, one that incorporates both a network independent as well as a network sensitive part. This thesis represents one of the first attempts to use a fuzzy neural network to control or broker bandwidth within a rate-based transport protocol running over IP. As opposed to models based on simulation, a fuzzy neural controller was demonstrated on top of the Phat protocol which was used to emulate a rate-based transport layer protocol. In addition to contributions made to fuzzy neural network control theory, this work illustrates the viability of fuzzy control as applied to telecommunication applications such as bandwidth brokering within the confines of an IP network. In addition, the study illustrates the role that fuzzy control can play in improving end-to-end performance by adaptation to host and/or network bottlenecks.
Time-Energy Design Space Exploration for Multi-Layer Memory Architectures
Authors: Radoslaw Szymanek, Francky Catthoor, Krzysztof Kuchcinski
Venue: Proceedings of the conference on Design, automation and test in Europe - Volume 1 (2004)

This paper presents an exploration algorithm which examines execution time and energy consumption of a given application, while considering a parameterized memory architecture. The input to our algorithm is an application given as an annotated task graph and a specification of a multi-layer memory architecture. The algorithm produces Pareto trade-off points representing different multi-objective execution options for the whole application. Different metrics are used to estimate parameters for application-level Pareto points obtainedby merging all Pareto diagrams of the tasks composing the application. We estimate application execution time although the final scheduling is not yet known. The algorithm makes it possible to trade off the quality of the results and its runtime depending on the usedmetrics and the number of levels in the hierarchical composition of the tasks' Pareto points. We have evaluated our algorithm on a medical image processing application and randomly generated task graphs. We have shown that our algorithm can explore huge design space and obtain (near) optimal results in terms of Pareto diagram quality.
Convergence Analysis of an Infeasible Interior Point Algorithm Based on a Regularized Central Path for Linear Complementarity Problems
Authors: Guanglu Zhou, Kim-Chuan Toh, Gongyun Zhao
Venue: Computational Optimization and Applications (2004)

Most existing interior-point methods for a linear complementarity problem (LCP) require the existence of a strictly feasible point to guarantee that the iterates are bounded. Based on a regularized central path, we present an infeasible interior-point algorithm for LCPs without requiring the strict feasibility condition. The iterates generated by the algorithm are bounded when the problem is a P* LCP and has a solution. Moreover, when the problem is a monotone LCP and has a solution, we prove that the convergence rate is globally linear and it achieves &epsi;-feasibility and &epsi;-complementarity in at most O(n2 ln(1/&epsi;)) iterations with a properly chosen starting point.
Some results on maximum stable sets in certain P5-free graphs
Authors: Raffaele Mosca
Venue: Discrete Applied Mathematics (2003)

We introduce some large classes of P5-free graphs for which the maximum stable set problem can be efficiently solved. The solution algorithms are based on the search of augmenting vertices. Then a method for extending some of them to the weighted case is provided.
Some Spectral Characterizations of Strongly Distance-Regular Graphs
Authors: M. A. Fiol
Venue: Combinatorics, Probability and Computing (2001)

A graph &Gamma; with diameter d is strongly distance-regular if &Gamma; is distance-regular and its distance-d graph &Gamma;d is strongly regular. Some known examples of such graphs are the connected strongly regular graphs, with distance-d graph &Gamma;d = &Gamma; (the complement of &Gamma;), and the antipodal distance-regular graphs. Here we study some spectral conditions for a (regular or distance-regular) graph to be strongly distance-regular. In particular, for the case d = 3 the following characterization is proved. A regular (connected) graph &Gamma;, with distinct eigenvalues &lambda;0 > &lambda;1 > &lambda;2 > &lambda;3, is strongly distance-regular if and only if &lambda;2 = &minus;1, and &Gamma;3 is k-regular with degree k satisfying an expression which depends only on the order and the different eigenvalues of &Gamma;.
Non-Uniform Information Dissemination for Sensor Networks
Authors: Sameer Tilak, Amy Murphy, Wendi Heinzelman
Venue: Proceedings of the 11th IEEE International Conference on Network Protocols (2003)

Future smart environments will be characterized by multiple nodes that sense, collect, and disseminate information about environmental phenomena through a wireless network. In this paper, we define a set of applications that require a new form of distributed knowledge about the environment, referred to as non-uniform information granularity. By non-uniform information granularity we mean that the required accuracy or precision of information is proportional to the distance between a source node (information producer) and current sink node (information consumer). That is, as the distance between the source node and sink node increases, loss in information precision is acceptable. Applications that can benefit from this type of knowledge range from battle field scenarios to rescue operations. The main objectives of this paper are two-fold: first, we will precisely define non-uniform information granularity, and second we will describe different protocols that achieve non-uniform information dissemination and analyze these protocols based on complexity, energy consumption, and accuracy of information.
Proceedings of the 11th ACM international symposium on Advances in geographic information systems
Venue: Geographic Information Systems (2003)

On behalf of the Program Committee, it is our pleasure to welcome the participants to the 11th International Symposium of ACM GIS, held in New Orleans, Louisiana on November 7th and 8th, 2003. This year's ACM-GIS is the eleventh of a series of symposia/workshops that began in 1993 with the aim of bringing together researchers, developers, users, and practitioners carrying out research and development in novel systems based on geo-spatial data and knowledge, and fostering interdisciplinary discussions and research in all aspects of geographic information systems.Following an international call for papers, 82 papers were submitted and reviewed by an international panel of experts in the field of GIS. Of the 82 submitted papers, 22 were accepted (yielding an acceptance rate of 27%). The size of the submission indicates the continued health of the field and interest in it. All final papers, modified according to comments from the reviewers, appear in this volume.The invited keynote talk was from Dr. David Maguire, who presented a lecture entitled "Beyond the GIS Desktop".We would like to thank the Program Committee for giving so freely of their time and insightful opinions. Their reviews were based upon paper originality, significance, relevance, presentation and technical quality. Many of the submitted papers required further review and discussion. We appreciate the efforts of the reviewers in arriving at consensus on the papers involved. This process requires much time and effort.