ppxscal/embedding_network huggingface dataset:
Semantic query optimization for processing XML streams with minimized memory footprint
Authors: Ming Li, Murali Mani, Elke A. Rundensteiner
Venue: Proceedings of the 2008 EDBT workshop on Database technologies for handling XML information on the web (2008)

XQuery evaluation over XML streams requires the temporary buffering of XML elements. This paper presents a semantic query optimization solution to minimize memory footprint during XQuery evaluation by exploiting schema knowledge. We focus on one particular class of constraints, namely, the Pattern Non-Occurrence (PNO) constraints for XML streams conforming to pre-defined DTDs. PNO constraints facilitate the early release of buffered data (early buffer release) or possibly avoid to ever store the data (buffer avoidance), thus achieving a minimized memory footprint. We develop an automaton-based technique to detect PNO constraints at runtime. For a given query, optimization opportunities of early buffer release and buffer avoidance which can be triggered by runtime PNO detection are explored and the optimization decision is then encoded into the Raindrop algebraic plan. We implement our optimization technique within the Raindrop XQuery engine. Our experimental studies illustrate that the proposed techniques bring significant performance improvement in both memory and CPU usage with little overhead.
Respecting Users' Individual Privacy Constraints in Web Personalization
Authors: Yang Wang, Alfred Kobsa
Venue: Proceedings of the 11th international conference on User Modeling (2007)

Web personalization has demonstrated to be advantageous for both online customers and vendors. However, its benefits may be severely counter acted by privacy constraints. Personalized systems need to take users' privacy concerns into account, as well as privacy laws and industry self-regulation that may be in effect. In this paper, we first discuss how these constraints may affect web-based personalized systems. We then explain in what way current approaches to this problem fall short of their aims, specifically regarding the need to tailor privacy to the constraints of each individual user. We present a dynamic privacy-enhancing user modeling framework as a superior alternative, which is based on a software product line architecture. Our system dynamically selects personalization methods during runtime that respect users' current privacy concerns as well as the privacy laws and regulations that apply to them.
Efficient profile aggregation and policy evaluation in a middleware for adaptive mobile applications
Authors: Claudio Bettini, Linda Pareschi, Daniele Riboni
Venue: Pervasive and Mobile Computing (2008)

There is a large consensus on the need for a middleware to efficiently support adaptation in pervasive and mobile computing. Advanced forms of adaptation require the aggregation of context data and the evaluation of policy rules that are typically provided by multiple sources. This paper addresses the problem of designing the reasoning core of a middleware that supports these tasks, while guaranteeing very low response times as required by mobile applications. Technically, the paper presents strategies to deal with conflicting rules, algorithms that implement the strategies, and algorithms that detect and solve potential rule cycles. A detailed experimental analysis supports the theoretical results and shows the applicability of the resulting middleware in large-scale applications.
Models for a multi-agent system based on wasp-like behaviour for distributed patients repartition
Authors: Dana Simian, Florin Stoica, Corina Simian
Venue: Proceedings of the 9th WSEAS International Conference on Evolutionary Computing (2008)

In this paper are presented two models for an adaptive multi-agent system for dynamic repartition of the patients within a sanatoria network. The agents use wasp task allocation behaviour, combined with a model of wasp dominance hierarchy formation. An adaptive method allows patients to enter in the system for the first time. The rules for the update of response thresholds assure that an optimal repartition from the point of view of type and gravity of the diseases of a patient is made. Our approach depends on many system's parameters, which define the repartition policies.
Implementing MAC protocols for cooperative relaying: a compiler-assisted approach
Authors: Hermann S. Lichte, Stefan Valentin
Venue: Proceedings of the 1st international conference on Simulation tools and techniques for communications, networks and systems & workshops (2008)

Evaluating the performance of a cooperative relaying protocol requires an implementation for simulators and/or software-defined radios (SDRs) with an appropriate model for error detection, combining, and Medium Access Control (MAC) automaton. Such implementations are essential for meaningful evaluation of practical systems since any protocol introduces overhead that constrains the theoretical performance in non-obvious ways. Unfortunately, protocols for cooperative relaying often yield complex implementations which are tedious to implement and debug. Therefore, we identify basic operations that are inherent to all cooperative relaying protocols, and we propose a new language for their specification. Then, we show how to construct a compiler for the proposed language that generates most of the required implementation (model and MAC automaton) automatically. This approach prevents subtle mistakes during implementation of the protocol, and can significantly increase development time. In addition, this paper discusses code generation exemplarily for OMNeT++/Mobility Framework, but the approach is not restricted to a specific simulator or SDR.
Existence Plots: A Low-Resolution Time Series for Port Behavior Analysis
Authors: Jeff Janies
Venue: Proceedings of the 5th international workshop on Visualization for Computer Security (2008)

An existence plot is a low-resolution visualization that concurrently represents the activity of all 216 ports on a single host. By doing so, we are able to show patterns of port usage which can indicate server activity and demonstrate scanning. In this work we introduce the existence plot as a visualization and discuss its use in gaining insight into a host's behavior.
Engineering DPLL(T) + Saturation
Authors: Leonardo Moura, Nikolaj Bjørner
Venue: Proceedings of the 4th international joint conference on Automated Reasoning (2008)

Satisfiability Modulo Theories (SMT) solvers have proven highly scalable, efficient and suitable for integrated theory reasoning. The most efficient SMT solvers rely on refutationally incomplete methods for incorporating quantifier reasoning. We describe a calculus and a system that tightly integrates Superposition and DPLL(T). In the calculus, all non-unit ground clauses are delegated to the DPLL(T) core. The integration is tight, dependencies on case splits are tracked as hypotheses in the saturation engine. The hypotheses are discharged during backtracking. The combination is refutationally complete for first-order logic, and its implementation is competitive in performance with E-matching based SMT solvers on problems they are good at.
Model-Based Fault Detection and Isolation Using Locally Recurrent Neural Networks
Authors: Piotr Przystałka
Venue: Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing (2006)

The increasing complexity of technological processes implemented in present industrial installations causes serious problems in the modern control system design and analysis. Chemical refineries, electrical furnaces, water treatments and other industrial plants are complex systems and in some cases cannot be precisely described by classical mathematical models. On the other hand, modern industrial systems are subject to faults in their components. Due to these facts, fault-tolerant control design using soft computing methods is gaining more and more attention in recent years. In this paper, the model-based approach to fault detection and isolation using locally recurrent neural networks is presented. The paper contains a numerical example that illustrates the performance of the proposed locally recurrent neural network with respect to other well-known neural structures. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Mixed Search Number of Permutation Graphs
Authors: Pinar Heggernes, Rodica Mihai
Venue: Proceedings of the 2nd annual international workshop on Frontiers in Algorithmics (2008)

Search games in graphs have attracted significant attention in recent years, and they have applications in securing computer networks against viruses and intruders. Since graph searching is an NP-hard problem, polynomial-time algorithms have been given for solving it on various graph classes. Most of these algorithms concern computing the node search number of a graph, and only few such algorithms are known for computing the mixed search or edge search numbers of specific graph classes. In this paper we show that the mixed search number of permutation graphs can be computed in linear time, and we describe an algorithm for this purpose. In addition, we give a complete characterization of the edge search number of complete bipartite graphs.
Optimal switch location in mobile communication networks using hybrid genetic algorithms
Authors: Sancho Salcedo-Sanz, Jose A. Portilla-Figueras, Emilio G. Ortiz-García, Angel M. Pérez-Bellido, Christopher Thraves, Antonio Fernández-Anta, Xin Yao
Venue: Applied Soft Computing (2008)

The optimal positioning of switches in a mobile communication network is an important task, which can save costs and improve the performance of the network. In this paper we propose a model for establishing which are the best nodes of the network for allocating the available switches, and several hybrid genetic algorithms to solve the problem. The proposed model is based on the so-called capacitated p-median problem, which have been previously tackled in the literature. This problem can be split in two subproblems: the selection of the best set of switches, and a terminal assignment problem to evaluate each selection of switches. The hybrid genetic algorithms for solving the problem are formed by a conventional genetic algorithm, with a restricted search, and several local search heuristics. In this work we also develop novel heuristics for solving the terminal assignment problem in a fast and accurate way. Finally, we show that our novel approaches, hybridized with the genetic algorithm, outperform existing algorithms in the literature for the p-median problem.
Mining Frequent Closed Unordered Trees Through Natural Representations
Authors: José L. Balcázar, Albert Bifet, Antoni Lozano
Venue: Proceedings of the 15th international conference on Conceptual Structures: Knowledge Architectures for Smart Applications (2007)

Many knowledge representation mechanisms consist of link-based structures; they may be studied formally by means of unordered trees. Here we consider the case where labels on the nodes are nonexistent or unreliable, and propose data mining processes focusing on just the link structure. We propose a representation of ordered trees, describe a combinatorial characterization and some properties, and use them to propose an efficient algorithm for mining frequent closed subtrees from a set of input trees. Then we focus on unordered trees, and show that intrinsic characterizations of our representation provide for a way of avoiding the repeated exploration of unordered trees, and then we give an efficient algorithm for mining frequent closed unordered trees.
Unidirectional Lightweight Encapsulation with Header Compression for IP Based Satellite Communication over DVB-S
Authors: Chee-Hong Teh, Tat-Chee Wan, Rahmat Budiarto, Way-Chuang Ang
Venue: Proceedings of the 3rd Asian conference on Internet Engineering: Sustainable Internet (2007)

The Multi-Protocol Encapsulation (MPE) is a standard method for encapsulating IP packets into MPEG-2 TS frames. However MPE has some disadvantages in simplicity and efficiency to support next generation network. The Unidirectional Lightweight Encapsulation (ULE) is a new solution to overcome limitations of MPE. In ULE, packets are layered directly into the payload field of MPEG-2 TS frames. This is a new encapsulation method for the transport of IPv4 and other network protocol packets directly over MPEG-2 TS. In this paper, we describe the principles and the benefits of ULE and we also proposed Robust Header Compression Scheme to work with ULE in order to enhance the performance of existing ULE. This paper also provides a simulation analysis to show that the new proposed method can offer a better performance in delay, throughput and overhead especially when the packet size is small.
A Practical Approach to Word Level Model Checking of Industrial Netlists
Authors: Per Bjesse
Venue: Proceedings of the 20th international conference on Computer Aided Verification (2008)

In this paper we present a word-level model checking method that attempts to speed up safety property checking of industrial netlists. Our aim is to construct an algorithm that allows us to check both bounded and unbounded properties using standard bit-level model checking methods as back-end decision procedures, while incurring minimum runtime penalties for designs that are unsuited to our analysis. We do this by combining modifications of several previously known techniques into a static abstraction algorithm which is guaranteed to produce bit-level netlists that are as small or smaller than the original bitblasted designs. We evaluate our algorithm on several challenging hardware components.
Mutual Development of Behavior Acquisition and Recognition Based on Value System
Authors: Yasutake Takahashi, Yoshihiro Tamura, Minoru Asada
Venue: Proceedings of the 10th international conference on Simulation of Adaptive Behavior: From Animals to Animats (2008)

Both self-learning architecture (embedded structure) and explicit/implicit teaching from other agents (environmental design issue) are necessary not only for one behavior learning but more seriously for life-time behavior learning. This paper presents a method for a robot to understand unfamiliar behavior shown by others through the collaboration between behavior acquisition and recognition of observed behavior, where the state value has an important role not simply for behavior acquisition (reinforcement learning) but also for behavior recognition (observation). That is, the state value updates can be accelerated by observation without real trials and errors while the learned values enrich the recognition system since it is based on estimation of the state value of the observed behavior. The validity of the proposed method is shown by applying it to a dynamic environment where two robots play soccer.
Text mining biomedical literature for improving medline retrieval
Authors: Ying Liu
Venue:  (2008)

A major problem faced in biomedical informatics involves how best to present information retrieval results. This dissertation developed an approach that present users with reduced sets of relevant citations together with topic label. A text mining system is designed to group the retrieved citations, rank the citations in each cluster, and generate a set of keywords and MeSH terms to describe the common theme of each cluster. A series of follow-up researches were conducted for better performance of the system. A spectral analysis clustering method was proposed based on the content similarity network techniques for information retrieval systems. The new approach organizes all these search results into categories intelligently. Our experimental results demonstrated that the presented method performs well in real world applications. Automated concept recognition for each cluster is one of the important tasks in our text mining system. The system can perform keyword, key MeSH term and key noun-phrase extraction. Within each cluster, the extraction of keyword and key MeSH term is based on modeling the document-term-matrix as a weighted bipartite graph. A mutual reinforcement principle is used to rank the terms. Our new key noun-phrase extraction method is based on the context-free grammatical rules extracted from the input documents. An existing algorithm called Sequitur is used for constructing the context-free grammar rules that re-represent a sequence as a hierarchical structure. Noun-phrases are extracted from the grammatical rules. The key noun-phrases were identified from top frequency rules without extracting all the grammatical rules. The experimental results showed that our key noun-phrase extraction method is effective in identifying key concepts from documents, and outperforms current widely-used methods. We also explored to rank MEDLINE citations using an existing web ranking algorithm, HITS (Hyperlink-Induced Topic Search) algorithm. We further extended HITS to supervised HITS to rank citations. Our results showed that supervised HITS algorithm significantly outperforms HITS algorithm (p<0.01). Compared with HITS, supervised HITS can improve citation ranking from 15% to more than 59% in almost all the cases we tested. Furthermore, MeSH terms outperforms text words in ranking citations, especially when HITS was applied (p<0.01).
Workshops at MODELS 2008
Authors: Michel R. Chaudron
Venue: Proceedings of the 11th international conference on Model Driven Engineering Languages and Systems (2008)

The MODELS conference organizes a number of workshops as co-located events. Workshops provide the opportunity for a small group of people to exchange recent or preliminary results and to conductintensive discussions on a particular topic. They complement the main conference and are generally very well appreciated by attendees.
Swarms of Self-assembling Robots
Authors: Marco Dorigo
Venue: Engineering Environment-Mediated Multi-Agent Systems: International Workshop, EEMMAS 2007, Dresden, Germany, October 5, 2007. Selected Revised and Invited Papers (2008)

In this talk I present recent research in swarm robotics, the discipline that studies robotic systems composed of swarms of robots tightly interacting and cooperating to reach their goals. In particular, I will present a new type of robot, called swarm-bot, and the results of a number of experiments run with it. A swarm-bot [4,7] is an artifact composed of a swarm of assembled s-bots. The s-bots are mobile robots capable of connecting to, and disconnecting from, other s-bots. In the swarm-bot form, the s-bots are attached to each other and, when needed, become a single robotic system that can move and change its shape. S-bots have relatively simple sensors and motors and limited computational capabilities. A swarm-bot can solve problems that cannot be solved by s-bots alone. In the talk, I first describe the s-bots hardware and the methodology we followed to develop algorithms for their control. Then I illustrate the capabilities of the swarm-bot robotic system by showing video recordings of some of the many experiments we performed to study coordinated movement [1], path formation [8], collective transport [5], shape formation [2,3], and other collective behaviors [6,9,10].
Approximating PageRank from In-Degree
Authors: Santo Fortunato, Marián Boguñá, Alessandro Flammini, Filippo Menczer
Venue: Algorithms and Models for the Web-Graph: Fourth International Workshop, WAW 2006, Banff, Canada, November 30 - December 1, 2006. Revised Papers (2007)

PageRank is a key element in the success of search engines, allowing to rank the most important hits in the top screen of results. One key aspect that distinguishes PageRank from other prestige measures such as in-degree is its global nature. From the information provider perspective, this makes it difficult or impossible to predict how their pages will be ranked. Consequently a market has emerged for the optimization of search engine results. Here we study the accuracy with which PageRank can be approximated by in-degree, a local measure made freely available by search engines. Theoretical and empirical analyses lead to conclude that given the weak degree correlations in the Web link graph, the approximation can be relatively accurate, giving service and information providers an effective new marketing tool.
A Hoare Logic for Call-by-Value Functional Programs
Authors: Yann Régis-Gianas, François Pottier
Venue: Proceedings of the 9th international conference on Mathematics of Program Construction (2008)

We present a Hoare logic for a call-by-value programming language equipped with recursive, higher-order functions, algebraic data types, and a polymorphic type system in the style of Hindley and Milner. It is the theoretical basis for a tool that extracts proof obligations out of programs annotated with logical assertions. These proof obligations, expressed in a typed, higher-order logic, are discharged using off-the-shelf automated or interactive theorem provers. Although the technical apparatus that we exploit is by now standard, its application to call-by-value functional programming languages appears to be new, and (we claim) deserves attention. As a sample application, we check the partial correctness of a balanced binary search tree implementation.
Decision Making Logic of Visual Brain
Authors: Andrzej W. Przybyszewski
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part II (2008)

A popular view is that the brain is making fast decisions in temporal and frontal cortices predominantly on the bases of the feedforward pathways (FF). In later stages iterations (reverberations) with delayed feedback connections (FB) may be helpful. We propose, an opposite concept, that decisions are made in single neurons from the retina to the cortex, and that FB is fast as FF, and from the beginning participates in making decisions. The main differences between FF and FB are their different logics: FF follows driver logical rules, but FB follows modulator logical rules. Driver logical rules are gathering all possible information together therefore and they are context dependent, FB pathways, however, using selective modulator logical rules extract only hypothetically important information. We say that FF FB interaction is prediction hypothesis testing system. Our psychophysical system is different than Turing Machine because we are often insensible to changes of some symbols but same symbols in different configuration may lead to different classification of the same object. In present work we are looking for the anatomical and neurophysiological basis of these perceptual effects. We describe interactions between parts and their configurations on the basis of a single cell electrophysiological activity in cortical area V4. This area is related to simple shape classification. We have divided area V4 cell responses into three categories and found equivalent classes of object attributes for each cell response category. On this basis, we found decision rules for different area V4 cells (rough set theory - Pawlak, 1992 [1]). Some of these rules are not consistent, which may suggest that the brain may use different, non-consistent strategies in parallel in order to classify significant attributes of the unknown object.