ppxscal/embedding_network huggingface dataset:
Resilience Provisioning in Provider-Based Overlay Networks
Authors: Gustav Rosenbaum, Sanjay Jha
Venue: Proceedings of the The IEEE Conference on Local Computer Networks 30th Anniversary (2005)

Guaranteed levels of network resilience are essential for many emerging and future Internet services. Currently, the only network model that can support stringent resilience requirements is a provider-based overlay network. In such an environment, resilience can be implemented either in the overlay networks or in the physical network. In this paper we look at how the network provider revenue is affected by where resilience is implemented. The idea is to measure the revenue in the two implementation scenarios and compare the generated revenues to find out if the network provider has something to gain by implementing resilience in the physical network and if so under what circmstances. The results of our linear programming based experiments show that network providers can potentially double its revenue when resilience is implemented in the physical network. The customers benefit as well since the overlay networks are significantly less complex and can be built at the same or lower cost than when resilience is implemented in the overlay networks.
A New Combinatorial Approach to Surface Reconstruction with Sharp Features
Authors: Chuan-Chu Kuo, Hong-Tzong Yau
Venue: IEEE Transactions on Visualization and Computer Graphics (2006)

This paper presents a new combinatorial approach to surface reconstruction with sharp features. Different from other postprocessing methods, the proposed method provides a systematic way to identify and reconstruct sharp features from unorganized sample points in one integrated reconstruction process. In addition, unlike other approximation methods, the reconstructed triangulated surface is guaranteed to pass through the original sample points. In this paper, the sample points in the sharp regions are defined as characteristic vertices (c-vertices), and their associated poles (c-poles) are used as a "sculptor¿ to extract triangles from a Delaunay structure for the sharp features. But, for smooth surface regions, an efficient region-growing scheme is used for triangle extraction and connection. Since only the c-poles associated with the sharp regions are used to participate in the Delaunay computation with the sample points, the proposed algorithm is adaptive in the sense that, given a sampled object with less sharp features, the triangulation becomes more efficient. To validate the proposed algorithm, some detailed illustrations are given. Experimental results show that it is robust and highly efficient.
Estimating and computing density based distance metrics
Authors: Sajama, Alon Orlitsky
Venue: Proceedings of the 22nd international conference on Machine learning (2005)

Density-based distance metrics have applications in semi-supervised learning, nonlinear interpolation and clustering. We consider density-based metrics induced by Riemannian manifold structures and estimate them using kernel density estimators for the underlying data distribution. We lower bound the rate of convergence of these plug-in path-length estimates and hence of the metric, as the sample size increases. We present an upper bound on the rate of convergence of all estimators of the metric. We also show that the metric can be consistently computed using the shortest path algorithm on a suitably constructed graph on the data samples and lower bound the convergence rate of the computation error. We present experiments illustrating the use of the metrics for semi-supervised classification and non-linear interpolation.
The use of a collegiate cyber defense competition in information security education
Authors: Art Conklin
Venue: Proceedings of the 2nd annual conference on Information security curriculum development (2005)

A Collegiate Cyber Defense Competition was conducted this spring with five universities fielding teams. This event was designed to provide student led teams a simulated operational business environment in which they could test their skills at information security and system operation. This three day event included external hackers attacking the student networks, as well as business users placing operational and administrative demands on the teams. Teams were scored based on their ability to maintain mandated business services, keeping hackers out and answering business scenario injects. The objective was to provide an environment where the teams could exercise their information technology abilities and do so in an operational mode where most information was not freely provided, but must be uncovered and discovered by the students in real time. Issues such as prioritization, resource allocation and technical skill application were tested using real world examples on a known instrumented network. The objective of providing feedback to each team as to its skill level and abilities was achieved and then some over the course of this successful event. Lessons were learned which are being used to move this local event to a national level event.
Evaluating the impact of the simulation environment on experimentation results
Authors: Lambert Schaelicke
Venue: Performance Evaluation (2005)

Simulation has become the tool of choice for advanced computer architecture research. Simulation model abstraction as well as compiler specifics can have significant impact on the observed performance trends and may lead to incorrect conclusions. This study presents a methodology that compares the predicted performance impact of several architectural techniques measured on a variety of simulator and compiler configurations. A significant difference in speedup between experiments indicates that a technique is sensitive to this particular variation. The results demonstrate a strong but non-uniform relationship between modeling abstraction and measurement error, as well as a significant sensitivity to the compiler.
On feature traceability in object oriented programs
Authors: Giuliano Antoniol, Ettore Merlo, Yann-Gaël Guéhéneuc, Houari Sahraoui
Venue: Proceedings of the 3rd international workshop on Traceability in emerging forms of software engineering (2005)

Open-source and industrial software systems often lack up-to-date documents on the implementation of user-observable functionalities. This lack of documents is particularly hindering for large systems. Moreover, as with any other software artifacts, user-observable functionalities evolve through software evolution activities. Evolution activities sometimes have undesired and unexpected side-effects on other functionalities, causing these to fail or to malfunction. In this position paper, we promote the idea that a traceability link between user-observable functionalities and constituents of a software architecture (classes, methods. . . implementing the functionalities) is essential to reduce the software evolution effort. We outline an approach to recover and to study the evolution of features---subsets of the constituents of a software architecture---responsible for a functionality.
Automatical Definition of Measures from the Combination of Shape Descriptors
Authors: J.-P. Salmon, L. Wendling, S. Tabbone
Venue: Proceedings of the Eighth International Conference on Document Analysis and Recognition (2005)

This paper presents a novel approach to combine shape descriptors. Each approach is applied on several clusters of objects. For each cluster and for any descriptor a map is associated directly from the confusion matrix. Such a method allows to determine automatically the better weight associated to the descriptor for the object under consideration. At last, we show that the additive combination of such measures allows to improve the classification.
A Novel Method of Two-Stage Decomposition Dedicated for PAL-based CPLDs
Authors: Dariusz Kania, Jozef Kulisz, Adam Milik
Venue: Proceedings of the 8th Euromicro Conference on Digital System Design (2005)

A PAL-based logic block is the core of great majority of contemporary CPLD devices. The purpose of the paper is to present a novel method of two-stage PAL decomposition. The idea of the method consist in sequential search for a decomposition providing feasibility of implementation of the free block in a PAL-based logic block containing a limited number of product terms. The proposed approach is an alternative to the classical method based on two-level minimization of separate single-output functions. Results of experiments, which are also presented, prove that the proposed algorithm leads to significant reduction of chip area in relation to the classical method, especially for CPLD structures consisting of PAL-based logic blocks containing 2i (a power of 2) product terms.
ARDE: A Novel Framework to Define Workflow Participants
Authors: Qijun Deng, Jiangtao Liu, Qing Zhang
Venue: Proceedings of the IEEE International Conference on e-Business Engineering (2005)

The organizational structures-based workflow participant definition, which appoints activity executors according to user's role, department or ID, is widely used in commercial workflow management systems presently. This approach lacks of flexible mechanisms for complex participants assignment. This paper described a novel approach (ARDE) to define workflow participants. ARDE defines participant from four facets, namely Assignment, Rule, Duration and Exception. Assignment uses an SQL-like language to define the qualification that activity participants must meet. Rule expresses a regulation to choose user(s) from all of qualified participants to undertake the task at runtime. The regulation considers the use's context, including workload, online and vacancy, etc. Duration is the interval during which the task starts and completes. Exception represents the handling strategy when a task cannot be finished in the planned duration. In order to enforce the expression capacity, an organizational meta-model, several built-in functions and an entity outdata are introduced in this article.
Geometric containers for efficient shortest-path computation
Authors: Dorothea Wagner, Thomas Willhalm, Christos Zaroliagis
Venue: Journal of Experimental Algorithmics (JEA) (2005)

A fundamental approach in finding efficiently best routes or optimal itineraries in traffic information systems is to reduce the search space (part of graph visited) of the most commonly used shortest path routine (Dijkstra's algorithm) on a suitably defined graph. We investigate reduction of the search space while simultaneously retaining data structures, created during a preprocessing phase, of size linear (i.e., optimal) to the size of the graph. We show that the search space of Dijkstra's algorithm can be significantly reduced by extracting geometric information from a given layout of the graph and by encapsulating precomputed shortest-path information in resulted geometric objects (containers). We present an extensive experimental study comparing the impact of different types of geometric containers using test data from real-world traffic networks. We also present new algorithms as well as an empirical study for the dynamic case of this problem, where edge weights are subject to change and the geometric containers have to be updated and show that our new methods are two to three times faster than recomputing everything from scratch. Finally, in an appendix, we discuss the software framework that we developed to realize the implementations of all of our variants of Dijkstra's algorithm. Such a framework is not trivial to achieve as our goal was to maintain a common code base that is, at the same time, small, efficient, and flexible, as we wanted to enhance and combine several variants in any possible way.
Highlight ranking for sports video browsing
Authors: Xiaofeng Tong, Qingshan Liu, Yifan Zhang, Hanqing Lu
Venue: Proceedings of the 13th annual ACM international conference on Multimedia (2005)

Sports video has been extensively studied for its wide viewer-ship and tremendous commercial potentials. Many studies focused on highlight extraction for summarizing a lengthy video. In this paper, we present an advanced highlight analysis system for sports video browsing, in which highlight evaluation and ranking are concerned besides highlight detection. First, we use replay detection to efficiently localize the highlights. Then incorporating with domain-specific knowledge, we adopt several significant cues to evaluate the importance degree of the highlights with support vector regression. Finally, the highlights are ranked with descending sort according to their importance value. The ranking results can provide a hierarchical video browsing and customized content delivery scheme. Initial experimental results on soccer videos show an encouraging performance comparing with human subjective evaluation.
Interactive Visualization of Genealogical Graphs
Authors: Michael J. McGuffin, Ravin Balakrishnan
Venue: Proceedings of the Proceedings of the 2005 IEEE Symposium on Information Visualization (2005)

The general problem of visualizing "family trees", or genealogical graphs, in 2D, is considered. A graph theoretic analysis is given, which identifies why genealogical graphs can be difficult to draw. This motivates some novel graphical representations, including one based on a dual-tree, a subgraph formed by the union of two trees. Dual-trees can be drawn in various styles, including an indented outline style, and allow users to browse general multitrees in addition to genealogical graphs, by transitioning between different dual-tree views. A software prototype for such browsing is described, that supports smoothly animated transitions, automatic camera framing, rotation of subtrees, and a novel interaction technique for expanding or collapsing subtrees to any depth with a single mouse drag.
Research on Modeling Resources Based on Web Service Technologies in Manufacturing Grid
Authors: Shi Shengyou, Mo Rong, Chang Zhiyong, Chen Zefeng
Venue: Proceedings of the IEEE International Conference on e-Business Engineering (2005)

Manufacturing grid will provides an integrated sustention environment for cooperative problem-solving and manufacturing resource sharing. It is a typical application of grid technologies in manufacturing field. Modeling manufacturing resource, one key issue of realizing a manufacturing grid system, is investigated intensively in this article. To modeling various manufacturing resources in a uniform manner, we propose a high level abstract model called Manufacturing Resource Hierarchy Model (MRHM), which is composed of resource layer, resource expressing layer and resource interface layer. In the model, various resources are sorted and aggregated in resource layer; all resource information and data are encapsulated in information expressing layer based on XML Schema; accessing operations to resource are defined in resource interface layer employing WSDL. Being validation, a standard part library system is developed as a grid resource node using the model, which can provide online services for users.
Performance-constrained Distributed DVS Scheduling for Scientific Applications on Power-aware Clusters
Authors: Rong Ge, Xizhou Feng, Kirk W. Cameron
Venue: Proceedings of the 2005 ACM/IEEE conference on Supercomputing (2005)

Left unchecked, the fundamental drive to increase peak performance using tens of thousands of power hungry components will lead to intolerable operating costs and failure rates. High-performance, power-aware distributed computing reduces power and energy consumption of distributed applications and systems without sacrificing performance. Generally, we use DVS (Dynamic Voltage Scaling) technology now available in high-performance microprocessors to reduce power consumption during parallel application runs when peak CPU performance is not necessary due to load imbalance, communication delays, etc. We propose distributed performance-directed DVS scheduling strategies for use in scalable power-aware HPC clusters. By varying scheduling granularity we can obtain significant energy savings without increasing execution time (36% for FT from NAS PB). We created a software framework to implement and evaluate our various techniques and show performance-directed scheduling consistently saves more energy (nearly 25% for several codes) than comparable approaches with less impact on execution time (
On the Impact of Structural Circuit Partitioning on SAT-Based Combinational Circuit Verification
Authors: Marc Herbstritt, Thomas Kmieciak, Bernd Becker
Venue: Proceedings of the Fifth International Workshop on Microprocessor Test and Verification (2004)

In this work we present an approach for SAT-based combinational circuit verification using partitionings of the set of primary outputs. We formally analyze the applied partitioning heuristics for the first time and present a closed verification framework incorporating traditional techniques. We report on experiments using our partitioning-based verification procedure that result in speedups of 276% on the average compared to traditional techniques.
Temporal data mining methodologies in a geo-spatial decision support system
Authors: Dan Li
Venue:  (2005)

In this dissertation, temporal data mining methodologies are developed to facilitate knowledge discovery in the framework of a distributed Geo-spatial Decision Support System (GDSS), with a focus on drought risk management. In this process, climatic data are collected from a variety of sources at weather stations. However, there are two kinds of missing (or incomplete) data. First, data are partially missing because of temporary malfunction or unavailability of equipment. Imputation methods based on clustering and soft computing techniques are developed to solve this missing data problem. Second, some locations do not have local observed data due to cost, physical, or technical considerations. To generate association rules for these un-sampled locations, three spatial interpolation models are developed and integrated into the temporal data mining process. After data preparation and preprocessing, we look more closely at the temporal property of time series data. Because a periodic pattern indicates something persistent and predictable, it is important to identify and characterize the periodicity. In this dissertation, an approach for mining partial periodic association rules in temporal databases is discussed. This approach allows the discovery of periodic episodes such that the events in an episode are not constrained by a fixed order. Moreover, this approach treats the antecedent and consequent of a rule separately and allows time lag between them. Thus, rules discovered are useful for prediction. Additionally, droughts occur infrequently by nature. To facilitate drought risk management, it is important to discover infrequent episodes from multiple data sequences. In this dissertation, an algorithm is developed for the discovery of infrequent episodes with a combination of bottom-up and top-down scanning schema. The information sharing between bottom-up and top-down scanning helps prune candidate episodes, and thus, efficiently find infrequent episodes that are interesting to users. Overall, the objective of this research is to enhance the body of work in the area of temporal data mining to enable knowledge discovery in the context of a GDSS.
Expected Convergence Properties of BGP
Authors: Ramesh Viswanathan, Krishan K. Sabnani, Robert J. Holt, Arun N. Netravali
Venue: Proceedings of the 13TH IEEE International Conference on Network Protocols (2005)

Border Gateway Protocol (BGP) is the de facto standard used for interdomain routing. Since packet forwarding may not be possible until stable routes are learned, it is not only critical for BGP to converge but it is important that the convergence be rapid. The distributed and asynchronous nature of BGP in conjunction with local policies makes it difficult to analyze with respect to convergence behavior. We present a novel model which, to our knowledge, is the first one to permit analysis of convergence in the aggregate (i.e., over all message exchange orders between routers regarding route advertisements), rather than worst case behavior. We introduce the notion of probabilistic safety as requiring the probability of convergence to be 1. We provide a necessary and sufficient condition characterizing probabilistic safety that shows that probabilistic safety accommodates BGP configurations whose potential divergence stems solely from pathological message sequences. More generally, we show how to compute for any BGP configuration its probability of convergence. For probabilistically safe configurations, we present procedures for computing their expected time to converge as well as the probability distribution on their convergence times. The ability to compute these quantitative characteristics makes our work "constructive" and provides the basis for further understanding and deriving procedures for optimizing network characteristics. Finally, we simulate several network examples and verify the consistency between our analysis and the simulations.
High-Speed and Low-Power Network Search Engine Using Adaptive Block-Selection Scheme
Authors: Mohammad J. Akhbarizadeh, Mehrdad Nourani, Rina Panigrahy, Samar Sharma
Venue: Proceedings of the 13th Symposium on High Performance Interconnects (2005)

A new approach for using block-selection scheme to increase the search throughput of multi-block TCAM-based network search engines is proposed. While the existing methods try to counter and forcibly balance the inherent bias of the Internet traffic, our method takes advantage of it. Our method improves flexibility of table management and gains scalability towards high rates of change in traffic bias. It offers higher throughput than the current art and a very low average power consumption. One of the embodiments of the proposed model, using four TCAM chips, can deliver over six times the throughput of a conventional configuration of the same TCAM chips.
Co-active intelligence for image retrieval
Authors: Mark Truran, James Goulding, Helen Ashman
Venue: Proceedings of the 13th annual ACM international conference on Multimedia (2005)

Lexical ambiguity in query-based image retrieval is an immemorial problem which has seemingly resisted all countermeasures. In this paper we introduce a methodology that expresses the users of a system and their navigational behaviour as the paramount resource for resolving query term ambiguity. Mass user consensus is modelled within a multi-dimensional feature space and evaluated through cluster analysis. This technique resolves query term ambiguity in a wholly democratic and dynamic fashion, in contrast to the brittle centralised models of contemporary word sense classification systems. The simple approach contained herein leads to several interesting emergent properties.
Using rough sets to edit training set in k-NN method
Authors: Yaile Caballero, Simone Joseph, Yuniesky Lezcano, Rafael Bello, Maria M. Garcia, Yaimara Pizano
Venue: Proceedings of the 5th International Conference on Intelligent Systems Design and Applications (2005)

Rough Set Theory (RST) is a technique for data analysis. In this paper, we use RST to improve the performance of the k-NN method. The RST is used to edit the training set. We propose two methods to edit training sets, which are based on the lower and upper approximations. Experimental results show a satisfactory performance of the k-NN using these techniques.