ppxscal/embedding_network huggingface dataset:
INEX 2007 Evaluation Measures
Authors: Jaap Kamps, Jovan Pehcevski, Gabriella Kazai, Mounia Lalmas, Stephen Robertson
Venue: Focused Access to XML Documents: 6th International Workshop of the Initiative for the Evaluation of XML Retrieval, INEX 2007 Dagstuhl Castle, Germany, December 17-19, 2007. Selected Papers (2008)

This paper describes the official measures of retrieval effectiveness that are employed for the Ad Hoc Track at INEX 2007. Whereas in earlier years all, but only, XML elements could be retrieved, the result format has been liberalized to arbitrary passages. In response, the INEX 2007 measures are based on the amount of highlighted text retrieved, leading to natural extensions of the well-established measures of precision and recall. The following measures are defined: The Focused Task is evaluated by interpolated precision at 1% recall (iP[0.01]) in terms of the highlighted text retrieved. The Relevant in Context Task is evaluated by mean average generalized precision (MAgP) where the generalized score per article is based on the retrieved highlighted text. The Best in Context Task is also evaluated by mean average generalized precision (MAgP) but here the generalized score per article is based on the distance to the assessor's best-entry point.
A Case-Based Song Scheduler for Group Customised Radio
Authors: Claudio Baccigalupo, Enric Plaza
Venue: Proceedings of the 7th international conference on Case-Based Reasoning: Case-Based Reasoning Research and Development (2007)

This paper presents a knowledge-intensive Case-Based Reasoning system to generate a sequence of songs customised for a community of listeners. To select each song in the sequence, first a subset of songs musically associated with the last song of the sequence is retrieved from a music pool; then the preferences of the audience expressed as cases are reused to customise the selection for the group of listeners; finally listeners can revise their satisfaction (or lack thereof) for the songs they have heard. We have integrated this CBR system with Poolcasting, a social group-based Web radio architecture in which listeners can actively contribute to the music played and influence the channels programming process. The paper introduces the Poolcasting architecture, presents the CBR technique that tailors in real-time the music of each channel for the current audience, and discusses how this approach may radically improve the group-satisfaction of the audience for a Web radio.
Adaptive Output-Feedback Stochastic Nonlinear Stabilization Using Neural Network
Authors: Jun Yang, Junchao Ni, Weisheng Chen
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

This letter extends adaptive neural network control method to a class of stochastic nonlinear output-feedback systems . Differently from the existing results, the nonlinear terms are assumed to be completely unknown and only a neural network is employed to compensate all unknown nonlinear functions. Based on stochastic LaSalle theorem, the resulting closed-loop system is proved to be globally asymptotically stable in probability.
Dynamic and Neuro-Dynamic Optimization of a Fed-Batch Fermentation Process
Authors: Tatiana Ilkova, Mitko Petrov
Venue: Proceedings of the 13th international conference on Artificial Intelligence: Methodology, Systems, and Applications (2008)

A fed-batch fermentation process is examined in this paper for experimental and further dynamic optimization. The optimization of the initial process conditions is developed for to be found out the optimal initial concentrations of the basic biochemical variables --- biomass, substrate and feed substrate concentration. For this aim, the method of dynamic programming is used. After that, these initial values are used for the dynamic optimization carried out by neuro-dynamic programming. The general advantage of this method is that the number of the iterations in the cost approximation part is decreased.
Heuristic Relay Node Selection Algorithm for One-Hop Overlay Routing
Authors: Yin Chen, Li Tang, Jun Li
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems Workshops (2008)

This paper reviews the characteristics of overlay networks and defines effective relay nodes that can improve the performance of interactive real-time applications. A heuristic relay node selection algorithm for overlay routing is proposed. The algorithm can find effective relay nodes for end-to-end links in an overlay network, and is scalable and robust due to its decentralization and randomization. Based on the simulation results, the algorithm is able to maintain a good performance when 40% end nodes in an overlay network encounter failures.
Nonlinear Analysis on Single Pile by Meshfree Local Petrov-Garlerkin Method (MLPG)
Authors: Ming-Hua Zhao, Wei He, You Wang
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

The Meshfree Local Petrov-Garlerkin Method (MLPG) was introduced to study the behavior of extra-long and large-diameter piles. The nonlinear behavior of the soil and pile shaft materials was firstly analyzed, based on these, the solving steps of MLPG was put forward involving the elastic-plastic model of soil and pile shaft reinforcement. Then a testing example was analyzed in contrast to the Finite Element Method (FEM), and the results indicated that the MLPG was of higher accuracy. Lastly, the MLPG was applied to analyze the data of static test on a full scale extra-long pile to study the behavior of pile.
The Cost of Learning Directed Cuts
Authors: Thomas Gärtner, Gemma C. Garriga
Venue: Proceedings of the 18th European conference on Machine Learning (2007)

In this paper we investigate the problem of classifying vertices of a directed graph according to an unknown directed cut. We first consider the usual setting in which the directed cut is fixed. However, even in this setting learning is not possible without in the worst case needing the labels for the whole vertex set. By considering the size of the minimum path cover as a fixed parameter, we derive positive learnability results with tight performance guarantees for active, online, as well as PAC learning. The advantage of this parameter over possible alternatives is that it allows for an a priori estimation of the total cost of labelling all vertices. The main result of this paper is the analysis of learning directed cuts that depend on a hidden and changing context.
Ontology-Based Data Sharing in P2P Databases
Authors: Dimitrios Skoutas, Verena Kantere, Alkis Simitsis, Timos Sellis
Venue: Semantic Web, Ontologies and Databases: VLDB Workshop, SWDB-ODBIS 2007, Vienna, Austria, September 24, 2007, Revised Selected Papers (2008)

We consider peer-to-peer systems in which peers share structured data through the use of schema mappings. Peers express their queries and rewrite incoming queries on their local schema. We assume the existence of one or more ontologies describing the domain of interest of the peers. The ontologies are used to semantically annotate each peer schema, making explicit the type of information provided by it. A major problem in such a system is that peers cannot easily judge the semantic relativeness of their interests to interests of other peers, as these are expressed by the respective local schemas. Moreover, peers cannot evaluate the semantic relativeness of answers that they receive to their queries. In this paper, we propose a semantic similarity measure for evaluating the semantic relativeness between peer schemas, as well as between queries and their rewritten versions on other peers. The similarity measure is first introduced under the assumption of a shared ontology among the community of peers, and then it is extended, employing ontology matching and translation techniques, to support the comparison of class expressions accross multiple ontologies. The proposed similarity measure adopts the notions of recall and precision from the field of Information Retrieval. Our goal is to use this measure for the identification of semantically relevant peers and the evaluation of the quality of the received answers based on the semantic annotations, the mappings, and the queries issued.
The Distributed Wireless Gathering Problem
Authors: Vincenzo Bonifaci, Peter Korteweg, Alberto Marchetti-Spaccamela, Leen Stougie
Venue: Proceedings of the 4th international conference on Algorithmic Aspects in Information and Management (2008)

We address the problem of data gathering in a wireless network using multihop communication; our main goal is the analysis of simple algorithms suitable for implementation in realistic scenarios. We study the performance of distributed algorithms, which do not use any form of local coordination, and we focus on the objective of minimizing average flow times of data packets. We prove a lower bound of ¿(logm) on the competitive ratio of any distributed algorithm minimizing the maximum flow time, where m is the number of packets. Next, we consider a distributed algorithm which sends packets over shortest paths, and we use resource augmentation to analyze its performance when the objective is to minimize the average flow time. If interferences are modeled as in Bar-Yehuda et al. (J. of Computer and Systems Science, 1992) we prove that the algorithm is (1 + ¿)-competitive, when the algorithm sends packets a factor O(log(¿/¿) logΔ) faster than the optimal offline solution; here ¿ is the diameter of the network and Δ the maximum degree. We finally extend this result to a more complex interference model.
Towards a Middleware Approach for a Self-configurable Automotive Embedded System
Authors: Isabell Jahnich, Ina Podolski, Achim Rettberg
Venue: Proceedings of the 6th IFIP WG 10.2 international workshop on Software Technologies for Embedded and Ubiquitous Systems (2008)

In this paper a middleware architecture for distributed automotive systems that supports self-configuration by dynamic load balancing of tasks is presented. The inclusion of self-configurability is able to offer reliability within the multimedia network of the vehicle (Infotainment). Load balancing of tasks could be applied if an error occurred within the network. The error detection in the network and the load balancing should run automatically. Therefore, the middleware architecture has to deal on one hand with the error detection and on the other hand with the migration of tasks. Additionally, to enable the migration it is important to identify the requirements of all electronic control units (ECU) and tasks within the network.
Cooperative Design Workflows for Multiphysics Applications
Authors: Toàn Nguyên, Jean-Antoine Désidéri
Venue: Proceedings of the 5th international conference on Cooperative Design, Visualization, and Engineering (2008)

This paper is devoted to the distributed workflows as a means to support large simulation applications, such as aircraft in flight dynamics. We are interested in the descripton of physics, their modeling in adequate tools, implementation and their deployment and execution on wide-area networks. This requires a layer where application codes are deployed and must be run cooperatively in distributed and parallel environments. We advocate the use of distrbuted and composite workflows in order to achieve effective and seamless large-scale simulation.
Dynamic workload balancing of parallel applications with user-level scheduling on the Grid
Authors: Vladimir V. Korkhov, Jakub T. Moscicki, Valeria V. Krzhizhanovskaya
Venue: Future Generation Computer Systems (2009)

This paper suggests a hybrid resource management approach for efficient parallel distributed computing on the Grid. It operates on both application and system levels, combining user-level job scheduling with dynamic workload balancing algorithm that automatically adapts a parallel application to the heterogeneous resources, based on the actual resource parameters and estimated requirements of the application. The hybrid environment and the algorithm for automated load balancing are described, the influence of resource heterogeneity level is measured, and the speedup achieved with this technique is demonstrated for different types of applications and resources.
ASIC Hardware Performance
Authors: Tim Good, Mohammed Benaissa
Venue: New Stream Cipher Designs: The eSTREAM Finalists (2008)

This chapter presents detailed hardware implementation results and performance metrics for the eSTREAM candidate stream ciphers remaining in the Phase 3 hardware profile. Performance assessment has been made in accordance with the eSTREAM hardware testing framework in terms of power, area and speed. An attempt has been made to quantify the flexibility and scalability dimensions of performance. The results are presented in tabular and graphical format together with summarising the utility of the candidates against two notional applications: one for 10Mbps wireless network and a second for 100kHz RFID. Where applicable to a particular cipher, guidance on any limitations on the choice of key or IV is given. The chapter concludes with a summary of the performance of each of the candidates and some general guidance for future low resource hardware stream cipher development.
On the Number of Facets of Three-Dimensional Dirichlet Stereohedra III: Full Cubic Groups
Authors: Pilar Sabariego, Francisco Santos
Venue: Discrete Computational Geometry (2008)

We are interested in the maximum possible number of facets that Dirichlet stereohedra for three-dimensional crystallographic groups can have. In two previous papers, D.&#x00a0;Bochi&#x015f; and the second author studied the problem for noncubic groups. This paper deals with &#x201c;full&#x201d; cubic groups, while &#x201c;quarter&#x201d; cubic groups are left for a subsequent paper. Here, &#x201c;full&#x201d; and &#x201c;quarter&#x201d; refers to the recent classification of three-dimensional crystallographic groups by Conway, Delgado-Friedrichs, Huson and Thurston. This paper&#x2019;s main result is that Dirichlet stereohedra for any of the 27 full groups cannot have more than 25 facets. We also find stereohedra with 17 facets for one of these groups.
Combinatorial and computational properties of a diameter constrained network reliability model
Authors: Louis Petingi
Venue: Proceedings of the WSEAS International Conference on Applied Computing Conference (2008)

This paper is intended as a summary of combinatorial and computational properties of a Diameter-constrained network reliability model. Classical network reliability models are based on the existence of end-to-end paths between network nodes, not taking into account the length of these paths; for many applications this is inadequate because the connection will only be established or attain the required quality if the distance between the connecting nodes does not exceed a given value. An alternative topological reliability model is the Diameter-constrained reliability of a network (DCR); this measure considers not only the underlying topology, but also imposes a bound on the diameter, which is the maximum distance between the nodes of the network. As communication networks can be modeled by undirected as well as directed graphs, we present a synopsis of the results known up until now pertaining the DCR for both topological representations. Moreover we show some important combinatorial properties of this model, and as a consequence we also prove well-known properties of the classical network reliability measure (i.e., where no distance constraints are imposed on the paths connecting the nodes of a network) as the DCR subsumes the classical network reliability measure.
Simulation of a Peer to Peer Market for Grid Computing
Authors: Uli Harder, Fernando Martínez Ortuño
Venue: Proceedings of the 15th international conference on Analytical and Stochastic Modeling Techniques and Applications (2008)

In this paper we investigate the market economy of a Peer-to-Peer network for Grid Computing. We present a simulation of P2P network where nodes either require or offer resources, which can be thought as CPU time for example. We examine the market behaviour of the P2P network for Erdős-Rényi and Barabási-Albert networks types of different sizes ranging from 4,096 nodes to 1,048,576 nodes. We find that utilisation and market behaviour depend on the network type but not the size. Similarly, different price update algorithms have little effect on the price development, which is more determined by the network type. We also measure the average buffer size and number of messages in the system. For the Barabási-Albert network, we find that the buffer size of each node has an effect on the price development in the system. The results are useful to guide designers of P2P Grid computing systems, like the Global Open Grid.
Selecting Genotyping Oligo Probes Via Logical Analysis of Data
Authors: Kwangsoo Kim, Hong Seo Ryoo
Venue: Proceedings of the 20th conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence (2007)

Based on the general framework of logical analysis of data, we develop a probe design method for selecting short oligo probes for genotyping applications in this paper. When extensively tested on genomic sequences downloaded from the Lost Alamos National Laboratory and the National Center of Biotechnology Information websites in various monospecific and polyspecific in silico experimental settings, the proposed probe design method selected a small number of oligo probes of length 7 or 8 nucleotides that perfectly classified all unseen testing sequences. These results well illustrate the utility of the proposed method in genotyping applications.
Encoding the Pure Lambda Calculus into Hierarchical Graph Rewriting
Authors: Kazunori Ueda
Venue: Proceedings of the 19th international conference on Rewriting Techniques and Applications (2008)

Fine-grained reformulation of the lambda calculus is expected to solve several difficulties with the notion of substitutions--definition, implementation and cost properties. However, previous attempts including those using explicit substitutions and those using Interaction Nets were not ideally simple when it came to the encoding of the pure (as opposed to weak) lambda calculus. This paper presents a novel, fine-grained, and highly asynchronous encoding of the pure lambda calculus using LMNtal, a hierarchical graph rewriting language, and discusses its properties. The major strength of the encoding is that it is significantly simpler than previous encodings, making it promising as an alternative formulation, rather than just the encoding, of the pure lambda calculus. The membrane construct of LMNtal plays an essential role in encoding colored tokens and operations on them. The encoding has been tested using the publicly available LMNtal implementation.
How to Build a Persuasive Web Application
Authors: Evan Rosenfeld
Venue: Proceedings of the 3rd international conference on Persuasive Technology (2008)

Successful web applications are able to influence the behaviors of their users. The top 40 facebook applications were analyzed to determine the most persuasive ways of achieving such influence. This paper presents a framework of feedback loops for this purpose and then applies it within the context of facebook.
Unsupervised Documents Categorization Using New Threshold-Sensitive Weighting Technique
Authors: Frederic Ehrler, Patrick Ruch
Venue: Proceedings of the 11th conference on Artificial Intelligence in Medicine (2007)

As the number of published documents increase quickly, there is a crucial need for fast and sensitive categorization methods to manage the produced information. In this paper, we focused on the categorization of biomedical documents with concepts of the Gene Ontology, an ontology dedicated to gene description. Our approach discovers associations between the predefined concepts and the documents using string matching techniques. The assignations are ranked according to a score computed given several strategies. The effects of these different scoring strategies on the categorization effectiveness are evaluated. More especially a new weighting technique based on term frequency is presented. This new weighting technique improves the categorization effectiveness on most of the experiment performed. This paper shows that a cleaver use of the frequency can bring substantial benefits when performing automatic categorization on large collection of documents.
An Ontology-Centric Approach to Sensor-Mission Assignment
Authors: Mario Gomez, Alun Preece, Matthew P. Johnson, Geeth Mel, Wamberto Vasconcelos, Christopher Gibson, Amotz Bar-Noy, Konrad Borowiecki, Thomas Porta, Diego Pizzocaro, Hosam Rowaihy, Gavin Pearson, Tien Pham
Venue: Proceedings of the 16th international conference on Knowledge Engineering: Practice and Patterns (2008)

Sensor-mission assignment involves the allocation of sensor and other information-providing resources to missions in order to cover the information needs of the individual tasks in each mission. This is an important problem in the intelligence, surveillance, and reconnaissance (ISR) domain, where sensors are typically over-subscribed, and task requirements change dynamically. This paper approaches the sensor-mission assignment problem from a Semantic Web perspective: the core of the approach is a set of ontologies describing mission tasks, sensors, and deployment platforms. Semantic reasoning is used to recommend collections of types of sensors and platforms that are known to be "fit-for-purpose" for a particular task, during the mission planning process. These recommended solutions are used to constrain a search for available instances of sensors and platforms that can be allocated at mission execution-time to the relevant tasks. An interface to the physical sensor environment allows the instances to be configured to operate as a coherent whole and deliver the necessary data to users. Feedback loops exist throughout, allowing re-planning of the sensor-task fitness, reallocation of instances, and reconfiguration of the sensor network.
EAI as a Service - Combining the Power of Executable EAI Patterns and SaaS
Authors: Thorsten Scheibler, Ralph Mietzner, Frank Leymann
Venue: Proceedings of the 2008 12th International IEEE Enterprise Distributed Object Computing Conference (2008)

Enterprise Application Integration (EAI) problems are one of the major challenges IT departments are facing today. As enterprises merge, split up, or grow, existing legacy systems from different vendors implemented in different programming languages and running in different environments as well as roll-your-own applications have to be integrated. Furthermore, companies are starting to shift more and more on-premise software to software run in aSoftware as a Service (SaaS) business model. Outsourcing software to external and internal SaaS providers introduces new integration challenges, namely those of the integration of standard SaaS software with on-premise systems or other systems run at different SaaS providers which is a problem not addressed by SaaS platforms today. Recurring integration problems can be described by means of Enterprise Application Integration patterns. Those are used as nuggets of advice to solve complex integration problems. In this paper, we introduce executable EAI patterns offered in a SaaS business model to allow companies to focus on the integration without the need for the setup of complex integration infrastructures. Users will be guided by workflows customizing configurable EAI patterns to easily create integration solutions. We therefore propose EAI as a Service as a flexible, customizable, inexpensive way to tackle EAI problems both of on-premise systems but also of systems run in a SaaS business model.