ppxscal/embedding_network huggingface dataset:
Private-to-Private Communications over the Internet
Authors: Atsushi Kara
Venue: Computer (2004)

The meet-in-the-middle network provides a simple way to restore end-to-end connectivity between distant hosts located behind network address translators, and does so without reconfiguring the NAT devices that lie on the path between the hosts.
Verified Software: The Real Grand Challenge
Authors: Ramesh Bharadwaj
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)

This position paper addresses, and attempts to propose solutions for, critical issues in software engineering that need to be resolved before the Verified Software grand challenge as proposed by Professor Tony Hoare can be usefully exploited in industry to increase the assurance of software intensive systems.
New Approaches to Coevolutionary Worst-Case Optimization
Authors: Jürgen Branke, Johanna Rosenbusch
Venue: Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X (2008)

Many real-world optimization problems involve uncertainty. In this paper, we consider the case of worst-case optimization, i.e., the user is interested in a solution's performance in the worst case only. If the number of possible scenarios is large, it is an optimization problem by itself to determine a solution's worst case performance. In this paper, we apply coevolutionary algorithms to co-evolve the worst case test cases along with the solution candidates. We propose a number of new variants of coevolutionary algorithms, and show that these techniques outperform previously proposed coevolutionary worst-case optimizers on some simple test problems.
Evaluating Steiner-tree heuristics and diameter variations for application layer multicast
Authors: Knut-Helge Vik, Pål Halvorsen, Carsten Griwodz
Venue: Computer Networks: The International Journal of Computer and Telecommunications Networking (2008)

Latency reduction in distributed interactive applications has been studied intensively. Such applications may have stringent latency requirements and dynamic user groups. We focus on application-layer multicast with a centralized approach to the group management. The groups are organized in overlay networks that are created using graph algorithms that create a tree structure for the group. A tree has no cycles and uses a small routing table, as opposed to a connected overlay mesh. We investigated a group of spanning tree problems that are referred to as Steiner-tree problems, and we have a particular focus on reducing the diameter of a tree, which is the maximum pairwise latency in a tree. In addition, we focus on reducing the time it takes to execute membership changes. In that context, we use core-selection heuristics to find well-placed client nodes, and edge-pruning algorithms to reduce the number of edges in an otherwise fully meshed overlay. Our edge-pruning algorithms strongly connect well-placed client nodes to the remaining group members, to create new and pruned group graphs. Consequently, when a tree algorithm is applied to a pruned group graph, it is manipulated into creating trees with a smaller diameter. We devised new Steiner-tree heuristics that reduced the diameter, and also proposed new edge-pruning algorithms to make the tree construction faster. These heuristics and algorithms were implemented and analyzed experimentally along with several spanning-tree and core-selection heuristics found in the literature. We found that a full-mesh of shortest paths makes it difficult for Steiner-tree heuristics to find better trees than spanning tree algorithms. The network seen from the application layer is in fact a full mesh of shortest paths. In addition, we found that faster Steiner-tree heuristics that do not explicitly optimize the diameter are able to compete with slower heuristics that do optimize it.
Mobile opportunistic commerce: mechanisms, architecture, and application
Authors: Ece Kamar, Eric Horvitz, Chris Meek
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2 (2008)

We present mechanisms, architectures, and an implementation addressing challenges with mobile opportunistic commerce centering on markets and mechanisms that support the procurement of goods and services in mobile settings. Our efforts seek to extend core concepts from research in electronic commerce to interactions between mobile buyers and brick and mortar businesses that have geographically situated retail offices. We focus on efficient mechanisms, infrastructure, and automation that can enable sellers and buyers to take joint advantage of the relationship of the locations of retail offices to the routes of mobile buyers who may have another primary destination. The methods promote automated vigilance about opportunities to buy and sell, and to support negotiations on the joint value to buyers and sellers including buyers' costs of divergence from their original paths to acquire services and commodities. We extend prior work on auction mechanisms to personal procurement settings by analyzing the dynamics of the cost to buyers based on preexisting plans, location, and overall context. We present mechanisms for auctions in single item, combinatorial, and multiattribute settings that take into consideration personal inconvenience costs within time-sensitive dynamic markets and challenges with privacy and fairness.
Multidimensional line dispensing of unfilled adhesives
Authors: U. Reisgen, S. Scheik
Venue: Microsystem Technologies (2008)

In comparison with competitive joining methods, the joining technology &#x201c;adhesive bonding&#x201d;, provides advantages in the low-stress joining of similar and dissimilar material combinations. As far as the micro-range is concerned, this technology is particularly suitable for the joining of hybrid micro-systems made of different materials and featuring complex geometries. The variety of available adhesives allows the adaptation of the process to the specific joining task. If the technology is transferred from the macro-range to the micro-range, the dispensing and application of the requested minimal adhesive volumes is one of the fundamental challenges. The process limits of nowadays-used micro-dispensing systems are characterised by the minimally dispensable adhesive volume and also by the flexibility with regard to the applicable adhesives and dispensable layout. The objective of the research work, which is specified in this paper is the expansion of the process limits up to smaller volumes and also the guarantee of flexible handling and a high-process stability. This has been the motivation for the Welding and Joining Institute of the RWTH Aachen to develop a micro-dispensing unit for spot and linear adhesive application. The unit comprises a positive-displacement dispensing system with integrated adhesive tempering, process gas supply and process optics. A reproducible dispensing process requires the adhesive reservoir to be absolutely free from gas. For this reason, a one-way system has been developed which allows degasification before the actual dispensing process takes place. Different degasification principles have, in this connection, been tested with regard to their achievement potential. The one-way system further reduces expenditure for cleaning, maintaining and setting-up of the unit. The unit allows the determination of the important parameters influencing the line dispensing of unfilled adhesives with a line width of <50&#x00a0;&#x03bc;m.
Data Clustering with Semi-binary Nonnegative Matrix Factorization
Authors: Rafal Zdunek
Venue: Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing (2006)

Recently, a considerable growth of interest in using Nonnegative Matrix Factorization (NMF) for pattern classification and data clustering has been observed. For nonnegative data (observations, data items, feature vectors) many problems of partitional clustering can be modeled in terms of a matrix factorization into two groups of vectors: the nonnegative centroid vectors and the binary vectors of cluster indicators. Hence our data partitional clustering problem boils down to a semi-binary NMF problem. Usually, NMF problems are solved with an alternating minimization of a given cost function with multiplicative algorithms. Since our NMF problem has a particular characteristics, we apply a different algorithm for updating the estimated factors than commonly-used, i.e. a binary update with simulated annealing steering. As a result, our algorithm outperforms some well-known algorithms for partitional clustering.
VISOLE: An Example of Hybrid Learning
Authors: Jun Jie Shang, Morris Siu Jong, Fong Lok Lee, Jimmy Ho Lee
Venue: Proceedings of the 1st international conference on Hybrid Learning and Education (2008)

In this paper, we discussed the VISOLE learning mode, which is a hybrid learning that combined the game-based learning and the traditional learning. Briefly speaking, the VISOLE approach is composed of 3 phases in which students have to (Phase 1) preliminarily acquire some high-level knowledge in specific subject domains through teachers' scaffolding; (Phase 2) actively participate as game characters in a game-based virtual interactive environment to construct knowledge and skills through their near real-life gameplay experiences; (Phase 3) reflect and generalize their game-based learning experiences through teachers' debriefing. During the design and develop process of the VISOLE, we paid close attention to the guiding function of teachers, and emphasized the subject position of students. Under the present research, we empirically found that most students were much more motivated during this learning process, and enhanced their knowledge, intellectual and nonintellectual skills. Therefore, VISOLE is a valuable learning mode worthy of promotion.
Speech Signal Enhancement Based on Adaptive Multi-resolution Form of SVD
Authors: Lu Yanhong, Qin Xiaohong
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 2 - Volume 02 (2008)

A speech signal enhancement method based on adaptive multi-resolution form of singular value decomposition (MSVD) is proposed in this paper. The residual noise after spectral subtraction, which results in audible musical noise, is reduced further by MSVD filter. In comparison with the original singular value decomposition filter (SVD), MSVD filter reduces the computational burden, which is very important for real time speech processing situations.
First-Order Probabilistic Languages: Into the Unknown
Authors: Brian Milch, Stuart Russell
Venue: Inductive Logic Programming: 16th International Conference, ILP 2006, Santiago de Compostela, Spain, August 24-27, 2006, Revised Selected Papers (2007)

This paper surveys first-order probabilistic languages (FOPLs), which combine the expressive power of first-order logic with a probabilistic treatment of uncertainty. We provide a taxonomy that helps make sense of the profusion of FOPLs that have been proposed over the past fifteen years. We also emphasize the importance of representing uncertainty not just about the attributes and relations of a fixed set of objects, but also about what objects exist. This leads us to Bayesian logic, or BLOG, a language for defining probabilistic models with unknown objects. We give a brief overview of BLOG syntax and semantics, and emphasize some of the design decisions that distinguish it from other languages. Finally, we consider the challenge of constructing FOPL models automatically from data.
IdentityRank: Named Entity Disambiguation in the Context of the NEWS Project
Authors: Norberto Fernández, José M. Blázquez, Luis Sánchez, Ansgar Bernardi
Venue: Proceedings of the 4th European conference on The Semantic Web: Research and Applications (2007)

In this paper we introduce the IdentityRank algorithm, developed as part of the EU-funded project NEWS to address the problem of named entity disambiguation in the context of semantic annotation of news items. The algorithm provides a ranking of the candidate instances within an ontology which can be associated to a certain entity. In order to do so, it uses as context the metadata available in a certain news item. The algorithm has been evaluated with promising results.
Characterizing the Basic Synchronization and Communication Operations in Dual Cell-Based Blades
Authors: José L. Abellán, Juan Fernández, Manuel E. Acacio
Venue: Proceedings of the 8th international conference on Computational Science, Part I (2008)

The Cell Broadband Engine (Cell BE) is a heterogeneous chip-multiprocessor (CMP) architecture to offer very high performance, especially on game and multimedia applications. The singularity of its architecture, nine cores of two different types, along with the variety of synchronization and communication primitives offered to programmers, make the task of developing efficient applications very challenging. This situation gets even worse when we consider Dual Cell-Based Blade architectures where two separate Cells can be linked together through a dedicated high-speed interface. In this work, we present a characterization of the main synchronization and communication primitives provided by dual Cell-based blades under varying workloads. In particular, we focus on the DMA transfer mechanism, the mailboxes, the signals, the read-modify-write atomic operations, and the time taken by thread creation. Our performance results expose the bottlenecks and asymmetries of these platforms which must be taken into account by programmers for improving the efficiency of their applications.
Extraction of Binary Features by Probabilistic Neural Networks
Authors: Jiří Grim
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part II (2008)

In order to design probabilistic neural networks in the framework of pattern recognition we estimate class-conditional probability distributions in the form of finite mixtures of product components. As the mixture components correspond to neurons we specify the properties of neurons in terms of component parameters. The probabilistic features defined by neuron outputs can be used to transform the classification problem without information loss and, simultaneously, the Shannon entropy of the feature space is minimized. We show that, instead of dimensionality reduction, the decision problem can be simplified by using binary approximation of the probabilistic features. In experiments the resulting binary features improve recognition accuracy but also they are nearly independent - in accordance with the minimum entropy property.
New Upper Bounds on Continuous Tree Edge-Partition Problem
Authors: Robert Benkoczi, Binay Bhattacharya, Qiaosheng Shi
Venue: Proceedings of the 4th international conference on Algorithmic Aspects in Information and Management (2008)

We consider continuous tree edge-partition problem on a edge-weighted tree network. A continuous p-edge-partition of a tree is to divide it into p subtrees by selecting p ¿ 1 cut points along the edges of the underlying tree. The objective is to maximize (minimize) the minimum (maximum) length of the subtrees. We present an O(nlog2 n)-time algorithm for the max-min problem which is based on parametric search technique [7] and an efficient solution to the ratio search problem. Similar algorithmic technique, when applied to the min-max problem, results in an O(nh T logn)-time algorithm where h T is the height of the underlying tree network. The previous results for both max-min and min-max problems are O(n 2) [5].
Improved IPv6 mobility architecture in IPv4 networks
Authors: J. Gnana Jayanthi, S. Albert Rabara, N. Rajendran
Venue: Proceedings of the 7th WSEAS International Conference on Electronics, Hardware, Wireless and Optical Communications (2008)

The lack of IP address space and the features in IPv6 force the mobile environment march towards Mobile IPv6. However, the current Mobile IP protocol is supported only when the Mobile Node (MN) moves within networks of the same IP version because the Mobile IPv4 protocol is not compatible with Mobile IPv6 protocol. In this paper, mobility architecture is proposed for providing Inter operability and co-existence of Mobile IPv6 networks with Mobile IPv4 networks. It provides an easy mobility of IPv6 client in the IPv4 environment. This proposal has been implemented using the test bed and results were analyzed. So here we do not need any tunnelling to transfer IPv6 traffic to other IPv6 nodes.
Pragmatic Methods for Commercial Software Product Line Engineering Practice
Authors: Charles W. Krueger
Venue: Proceedings of the 2008 12th International Software Product Line Conference (2008)

The current generation of software product line (SPL) engineering success stories is being driven by a new generation of methods, tools and techniques. In this tutorial, we explore the latest in the ongoing evolution of SPL best practices that make it easier to adopt an SPL engineering approach and that make it more efficient to achieve optimal benefits over the long term.
Context-aware prediction of clinician information needs using "infobuttons."
Authors: Guilherme Del Fiol
Venue:  (2008)

The knowledge that clinicians face numerous information needs during the course of patient care is common place in the medical literature. Although on-line health information resources are now widely available, clinicians list a series of barriers for the effective use of these resources at the point of care. Infobuttons are decision support tools that integrate electronic medical record systems into information resources as an attempt to lower these barriers. In this dissertation, alternative methods to enhance infobuttons are designed and evaluated in three separate studies. The first study addresses the question whether infobutton links that lead clinicians to specific content topics (topic links) are more effective than those links that point to more general content ( nonspecific links). The study concluded that clinicians with access to topic links were able to find answers to their questions more quickly than clinicians who were offered nonspecific links. In addition, the overall results confirm previous evidence that infobuttons are able to provide clinicians with answers to most of their medication-related questions. The second and third studies assess the feasibility of machine learning methods over infobutton usage data as a method to predict the information needs that a clinician is most likely to have in a given context as well as the information resources that clinicians are likely to visit. Classification models developed in both studies demonstrated a good prediction performance, suggesting that these models may further enhance the effectiveness of infobuttons if implemented in a production environment. In summary, this dissertation adds to the knowledge about infobuttons: First, it confirms the effectiveness of infobuttons in answering questions at the point of care. Second, it suggests a novel approach to the implementation of infobuttons, based on machine learning methods, that may lead to further enhancement. Last, this dissertation also suggests that machine learning methods over usage data may also be of use to enhance other clinical decision support systems, in particular when used from a knowledge management perspective.
Improved Global Exponential Stability Criterion for BAM Neural Networks with Time-Varying Delays
Authors: Yonggang Chen, Tiheng Qin
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks (2008)

In this paper, the global exponential stability analysis is investigated for a class of bidirectional associative memory (BAM) neural networks with time-varying delays. By using Lyapunov functional method, and by reserving the useful terms when estimating the upper bound of the derivative of Lyapunov functional, the less conservative exponential stability criterion is derived in terms of linear matrix inequality (LMI). Numerical example is presented to show the effectiveness and the less conservativeness of the proposed method.
A Discriminative Model-Constrained Graph Cuts Approach to Fully Automated Pediatric Brain Tumor Segmentation in 3-D MRI
Authors: Michael Wels, Gustavo Carneiro, Alexander Aplas, Martin Huber, Joachim Hornegger, Dorin Comaniciu
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

In this paper we present a fully automated approach to the segmentation of pediatric brain tumors in multi-spectral 3-D magnetic resonance images. It is a top-down segmentation approach based on a Markov random field (MRF) model that combines probabilistic boosting trees (PBT) and lower-level segmentation via graph cuts. The PBT algorithm provides a strong discriminative observation model that classifies tumor appearance while a spatial prior takes into account the pair-wise homogeneity in terms of classification labels and multi-spectral voxel intensities. The discriminative model relies not only on observed local intensities but also on surrounding context for detecting candidate regions for pathology. A mathematically sound formulation for integrating the two approaches into a unified statistical framework is given. The proposed method is applied to the challenging task of detection and delineation of pediatric brain tumors. This segmentation task is characterized by a high non-uniformity of both the pathology and the surrounding non-pathologic brain tissue. A quantitative evaluation illustrates the robustness of the proposed method. Despite dealing with more complicated cases of pediatric brain tumors the results obtained are mostly better than those reported for current state-of-the-art approaches to 3-D MR brain tumor segmentation in adult patients. The entire processing of one multi-spectral data set does not require any user interaction, and takes less time than previously proposed methods.
Complexity of Decoding Positive-Rate Reed-Solomon Codes
Authors: Qi Cheng, Daqing Wan
Venue: Proceedings of the 35th international colloquium on Automata, Languages and Programming, Part I (2008)

The complexity of maximum likelihood decoding of the Reed-Solomon codes [q - 1, k]q is a well known open problem. The only known result [4] in this direction states that it is at least as hard as the discrete logarithm in some cases where the information rate unfortunately goes to zero. In this paper, we remove the rate restriction and prove that the same complexity result holds for any positive information rate. In particular, this resolves an open problem left in [4], and rules out the possibility of a polynomial time algorithm for maximum likelihood decoding problem of Reed-Solomon codes of any rate under a well known cryptographical hardness assumption. As a side result, we give an explicit construction of Hamming balls of radius bounded away from the minimum distance, which contain exponentially many codewords for Reed-Solomon code of any positive rate less than one. The previous constructions in [2][7] only apply to Reed-Solomon codes of diminishing rates. We also give an explicit construction of Hamming balls of relative radius less than 1 which contain subexponentially many codewords for Reed-Solomon code of rate approaching one.