ppxscal/embedding_network huggingface dataset:
Proceedings of the 2005 workshop on Secure web services
Venue: Workshop On Secure Web Services (2005)

It is our great pleasure to welcome you to the 2nd ACM Workshop on Secure Web Services - SWS'05. This year's workshop comes at an interesting stage of development of Web service security research. While the basic building blocks, such as XML Security, the WS-* series of proposals, SAML, and XACML are now firmly in place, a number of challenges are still to be met for Web services and GRID nodes to be fully secured and trusted, providing for secure communications between cross-platform and cross-language Web services. Also, the current trend toward representing Web services orchestration and choreography via advanced business process metadata is fostering a further evolution of security models and languages, whose key issues include setting and managing security policies, inter-organizational (trusted partner) security issues and the implementation of high level business policies in a Web services environment.The mission of the SWS workshop is exploring these challenges, ranging from the advancement and best practices of building block technologies such as XML access control models and Web services security protocols to higher level issues such as advanced metadata, general security policies, trust establishment, risk management, and service assurance. SWS'05 is aimed at identifying new directions for future research and development, giving researchers and practitioners a unique opportunity to share their perspectives with others interested in the various aspects of Web Services security.Our call for papers attracted 22 submissions from Asia, Australia, Europe and the United States. The program committee accepted 10 papers that cover a variety of topics, ranging from theoretical foundations of Web services security models and algorithms to architectural and system-related issues. We are very happy with the quality of the accepted papers and hope that SWS'05 proceedings will serve as a valuable reference for researchers and developers working on Web services.
The asymptotic performance ratio of an on-line algorithm for uniform parallel machine scheduling with release dates
Authors: Mabel C. Chou, Maurice Queyranne, David Simchi-Levi
Venue: Mathematical Programming: Series A and B (2006)

Jobs arriving over time must be non-preemptively processed on one of m parallel machines, each running at its own speed, so as to minimize a weighted sum of the job completion times. In this on-line environment, the processing requirement and weight of a job are not known before the job arrives. The Weighted Shortest Processing Requirement (WSPR) heuristic is a simple extension of the well known WSPT heuristic, which is optimal for the single machine problem without release dates. According to WSPR, whenever a machine completes a job, the next job assigned to it is the one with the least ratio of processing requirement to weight among all jobs available for processing at this point in time. We analyze the performance of this heuristic and prove that its asymptotic competitive ratio is one for all instances with bounded job processing requirements and weights. This implies that the WSPR algorithm generates a solution whose relative error approaches zero as the number of jobs increases. Our proof does not require any probabilistic assumption on the job parameters and relies extensively on properties of optimal solutions to a single machine relaxation of the problem.
Consistency, Feasibility and Multiplicity of Fluxes in Metabolic Pathways
Authors: R. Nigam
Venue: Proceedings of the 18th International Conference on Systems Engineering (2005)

A simple test to check the consistency of large scale stoichiometric matrices in metabolic pathways is presented. Once the flux obtained is consistent, a systematic method is developed to examine the structure of multiple solutions in the metabolic network. Many of these multiple solutions are thermodynamically infeasible, hence a computational method is developed which is computationally intensive when we have to generate feasible multiple solutions. Changing certain fluxes, for example the glucose intake affects the growth of the cell or knocking out a particular gene can affect other fluxes, to explain such features we examine the sensitivity of fluxes to change in controllable fluxes. This technique has been applied to the metabolic network of Escherichia coli.
Motion normalization: the preprocess of motion data
Authors: Yan Gao, Lizhuang Ma, Zhihua Chen, Xiaomao Wu
Venue: Proceedings of the ACM symposium on Virtual reality software and technology (2005)

In this paper, we present an online algorithm to normalize all motion data in database with a common skeleton length. Our algorithm is very simple and efficient. The input motion stream is processed sequentially while the computation for a single frame at each step requires only the results from the previous step over a neighborhood of nearby backward frames. In contrast to previous motion retargeting approaches, we simplify the constraint condition of retargeting problem, which leads to the simpler solutions. Moreover, we improve Shin et al.'s algorithm [10], which is adopted by a widely used Kovar's footskate cleanup algorithm [6] through adding one case missed by it.
Does avatar email improve communication?
Authors: Younghwa Lee, Kenneth A. Kozar, Kai R. Larsen
Venue: Communications of the ACM (2005)

Seeking to enhance communication systems by adding expressive cues.
Efficient Hop ID based Routing for Sparse Ad Hoc Networks
Authors: Yao Zhao, Bo Li, Qian Zhang, Yan Chen, Wenwu Zhu
Venue: Proceedings of the 13TH IEEE International Conference on Network Protocols (2005)

Routing in mobile ad hoc networks remains as a challenging problem given the limited wireless bandwidth, users¿ mobility and potentially large scale. Recently, there has been a thrust of research to address these problems, including on-demand routing [1-2], geographical routing [6- 8], virtual coordinates [15], etc. In this paper, we focus on geographical routing, which was shown to achieve good scalability without flooding, but it usually requires location information and can suffer from the severe dead end problem especially in sparse networks. Specifically, we propose a new Hop ID based routing protocol, which does not require any location information, yet achieves comparable performance with the shortest path routing. In addition, we design efficient algorithms for setting up the system and adapt to the node mobility quickly, and can effectively route out of dead ends. The extensive analysis and simulation show that the Hop ID based routing achieves efficient routing for mobile ad hoc networks with various density, irregular topologies and obstacles.
Object Recognition Using Stereo Vision and Higher Order Spectra
Authors: C. Mc Cool, V. Chandran, A. Nguyen, S. Sridharan
Venue: Proceedings of the Digital Image Computing on Techniques and Applications (2005)

This paper presents a novel technique to conduct correspondence-free stereo processing. Traditional stereo processing estimates structure through computationally expensive correspondence algorithms resulting in the generation of depth maps. If the purpose of estimating structure is to recognise objects, the depth maps (structural information) need to be further processed to produce features which can then be used for recognition. This paper outlines an alternative technique that bypasses the correspondence algorithms to combine the estimation of depth and feature extraction into one step. This is achieved through the application of Higher Order Spectra (HOS) analysis. Results are presented that demonstrate a Top 2 Rank identification rate of 80% for a small database of human faces.
Baseband Digital Predistorter with Quadrature Error Correction
Authors: Ilari Teikari, Jouko Vankka, Kari Halonen
Venue: Analog Integrated Circuits and Signal Processing (2006)

In this article simulation and measurement results of a FPGA implementation of a baseband digital complex gain predistorter with a quadrature modulator and demodulation error correction circuits are presented. Four different methods for finding the quadrature error correction values are compared and the effect of quadrature errors to predistortion is discussed. A 50 dB three stage power amplifier chain with an analog quadrature modulator and demodulator was used in the measurements as the device to be predistorted. The signal used in the measurements and simulations was a 30 dBm 18 kHz 16-QAM signal at 400 MHz carrier frequency. In the measurements 15 dB reduction in 3rd order nonlinearity was achieved. The usage of quadrature error correction reduced the adjacent channel power by 9 dB.
Camera-based Degraded Character Segmentation into Individual Components
Authors: Celine Mancas-Thillou, Matei Mancas, Bernard Gosselin
Venue: Proceedings of the Eighth International Conference on Document Analysis and Recognition (2005)

In this article we present a novel fully automatic character segmentation for camera-based images. This is a top-down approach inspired by the human visual system: the high level step is based on color clustering while the low level one on the phase of Log-Gabor filters. First, this latter step deals with remaining touching characters after the color clustering approach and then takes into account the neighborhood information to address the problem of broken characters. Results are very encouraging and the method should be fast enough to be used on embedded platforms like personal digital assistants.
Video Sketches: Exploring Pervasive Computing Interaction Designs
Authors: John Zimmerman
Venue: IEEE Pervasive Computing (2005)

This issue's column focuses on integrating research and teaching. John Zimmerman (Carnegie Mellon University) used a group project in introductory interaction design courses to develop and refine video sketches as a prototyping method for pervasive computing.
A Comprehensive Image Processing Suite for Book Re-mastering
Authors: Jian Fan, Xiaofan Lin, Steven Simske
Venue: Proceedings of the Eighth International Conference on Document Analysis and Recognition (2005)

Converting paper books into electronic form provides benefits for archiving, distribution and content reuse. However, directly scanned images are usually undesirable for electronic books, and automated content re-mastering is required. In this paper, we describe a comprehensive image processing suite consisting of three major components: 1) image enhancement with deskew, cropping, color correction, contrast enhancement and text sharpening, 2) compound document image compression, and 3) extraction of TOC (table of content) and linking. We built a processing pipeline that automatically converts a set of scanned page images into a high quality and highly compressed e-book in the popular PDF format.
Self Port Scanning Tool: Providing a More Secure Computing Environment Through the Use of Proactive Port Scanning
Authors: Joshua E. Kocher, David P. Gilliam
Venue: Proceedings of the 14th IEEE International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprise (2005)

Secure computing is a necessity in the hostile environment that the Internet has become. Protection from nefarious individuals and organizations requires a solution that is more a methodology than a one time fix. One aspect of this methodology is having the knowledge of which network ports a computer has open to the world. These network ports are essentially the doorways from the Internet into the computer. An assessment method which uses the nmap software to scan ports has been developed to aid System Administrators (SAs) with analysis of open ports on their system(s). Additionally, baselines for several operating systems have been developed so that SAs can compare their open ports to a baseline for a given operating system. Further, the tool is deployed on a website where SAs and Users can request a port scan of their computer. The results are then emailed to the requester. This tool aids Users, SAs, and security professionals by providing an overall picture of what services are running, what ports are open, potential trojan programs or back doors, and what ports can be closed.
New techniques for efficiently discovering frequent patterns
Authors: Gagan Agrawal
Venue:  (2005)

Because of its theoretical and practical importance, the field of frequent pattern mining has been and remain to be one of the most active research area in KDD. In this dissertation, we study three different problems in frequent pattern mining, mining multiple datasets, mining streaming data, and mining large-scale structures from graph datasets. Our study has not only extended the breadth of frequent pattern mining, but also brought new techniques and algorithms into this field. Specifically, our contributions are as follows. (1) Mining multiple datasets. We develop a systematic approach to generate efficient query plans for a single mining query across multiple datasets. We also propose methods to simultaneously optimize multiple such queries and utilize the past mining results in a query-intensive KDD environment. Our experimental results have shown a speedup up to two-order of magnitude comparing with the naive methods without these optimizations. (2) Mining frequent itemsets over streaming data. We propose a new algorithm StreamMining to discover the frequent itemsets over streaming data. In a single pass, StreamMining will guarantee to find a superset of frequent itemsets, but false positive may occur. If the second pass is allowed, StreamMining will be able to remove the false positive and find the exact frequent itemsets. Our detailed evaluation using both synthetic and real datasets has shown our one-pass algorithm is very accurate in practice, and is also very memory efficient. (3) Mining frequent large-scale structures from graph datasets. We develop a new framework to discover the frequent large-scale structures from graph datasets. This framework is derived from a mathematical concept, topological minor. In this framework, we propose a new algorithm TSMiner, which efficiently enumerates all the frequent large-scale structures in a graph dataset, and a new approach called relabeling function to perform constraint mining. We apply our framework to protein structure data and discover meaningful topological structures. Finally, we demonstrate the viability and scalability of the proposed algorithms on both real and synthetic datasets.
Methods and techniques for the evaluation of user-adaptive systems
Authors: Cristina Gena
Venue: The Knowledge Engineering Review (2005)

This article presents a comprehensive overview of methods and techniques used for the evaluation of user-adaptive systems. It describes the methodologies derived both from the evaluation of human&ndash;computer interaction systems and from information retrieval and information filtering systems by giving examples of the application of these methodologies in the user-adaptive systems. The state of the art and the main results in the evaluation of these systems are reported. In particular, empirical evaluation and layered approaches are discussed in detail. Finally, focus on less explored methodologies, such as qualitative approaches (e.g. Grounded Theory), is proposed.
PRISAD: A Partitioned Rendering Infrastructure for Scalable Accordion Drawing
Authors: James Slack, Kristian Hildebrand, Tamara Munzner
Venue: Proceedings of the Proceedings of the 2005 IEEE Symposium on Information Visualization (2005)

We present PRISAD, the first generic rendering infrastructure for information visualization applications that use the accordion drawing technique: rubber-sheet navigation with guaranteed visibility for marked areas of interest. Our new rendering algorithms are based on the partitioning of screen-space, which allows us to handle dense dataset regions correctly. The algorithms in previous work led to incorrect visual representations because of overculling, and to inefficiencies due to overdrawing multiple items in the same region. Our pixel-based drawing infrastructure guarantees correctness by eliminating overculling, and improves rendering performance with tight bounds on overdrawing. PRITree and PRISeq are applications built on PRISAD, with the feature sets of TreeJuxtaposer and SequenceJuxtaposer, respectively. We describe our PRITree and PRISeq dataset traversal algorithms, which are used for efficient rendering, culling, and layout of datasets within the PRISAD framework. We also discuss PRITree node marking techniques, which offer order-of-magnitude improvements to both memory and time performance versus previous range storage and retrieval techniques. Our PRITree implementation features a five-fold increase in rendering speed for non-trivial tree structures, and also reduces memory requirements in some realworld datasets by up to eight times, so we are able to handle trees of several million nodes. PRISeq renders fifteen times faster and handles datasets twenty times larger than previous work.
Text Locating from Natural Scene Images Using Image Intensitie
Authors: JiSoo Kim, SangCheol Park, SooHyung Kim
Venue: Proceedings of the Eighth International Conference on Document Analysis and Recognition (2005)

In this paper, we propose three text extraction methods based on intensity information for natural scene images. The first method is composed of gray value stretching and binarization by an average intensity of the image. This method is appropriate to extract texts from complex backgrounds. The second method is a Split and Merge approach which is one of well-known algorithms for image segmentation. The third one is a combination of the two. Experimental results show that the proposed approaches are superior to conventional methods both in simple and complex images.
Early Warning in On-line Stock Trading Systems
Authors: Piotr Lipinski, Jerzy Korczak
Venue: Proceedings of the 5th International Conference on Intelligent Systems Design and Applications (2005)

In this paper, a new functionality of early warning for an online stock trading system is presented. The warning functionality helps to focus traders' attention on specific situations on the stock market. The specific situations relate to the rare circumstances where a trader should be alerted by exceptional raises or drops of share prices, volatilities and market index changes. Usually, these alerts force a trader to make a decision either to buy or sell a share. To discover the warning rules and events, an evolution-based model is proposed. This model also introduces a new function that stores the experimental knowledge by keeping track of all historical alert events - solutions and actions taken by a trader. This model is composed of the three following components, which are integrated with each other: Alert Rules, Pattern Clustering and Genetic Engine. This approach has been tested on real data extracted from the internet Bourse Expert System and Paris Stock Exchange.
Global optimization of rational functions: a semidefinite programming approach
Authors: D. Jibetean, E. de Klerk
Venue: Mathematical Programming: Series A and B (2006)

We consider the problem of global minimization of rational functions on ** (unconstrained case), and on an open, connected, semi-algebraic subset of **, or the (partial) closure of such a set (constrained case). We show that in the univariate case (n = 1), these problems have exact reformulations as semidefinite programming (SDP) problems, by using reformulations introduced in the PhD thesis of Jibetean [16]. This extends the analogous results by Nesterov [13] for global minimization of univariate polynomials.For the bivariate case (n = 2), we obtain a fully polynomial time approximation scheme (FPTAS) for the unconstrained problem, if an a priori lower bound on the infimum is known, by using results by De Klerk and Pasechnik [1].For the NP-hard multivariate case, we discuss semidefinite programming-based relaxations for obtaining lower bounds on the infimum, by using results by Parrilo [15], and Lasserre [12].
One-round zero-knowledge proofs and their applications in cryptographic systems
Authors: Clifford Neuman
Venue:  (2005)

A zero-knowledge proof (ZKP) is an interactive proof between two parties: prover and verifier, where the prover proves the knowledge of a secret without revealing any information about the secret itself. ZKPs were first introduced in 1985 for identity verification systems and became powerful tools for many cryptographic applications. There has been a growing concern about the risk of identity theft in critical situations, like homeland security and e-commerce. ZKPs are the ideal solution to challenges in identification since they allow costumers to prove identities without exchanging sensitive information that may lead to identity theft. Other applications of ZKPs include smart cards, digital cash, anonymous communication, electronic wallets, electronic voting, multimedia security and digital watermarks. Existing ZKPs are iterative in nature; their protocols require multiple communication rounds between parties. Due to the cost of iteration, practitioners see ZKPs as unsuitable in practice and therefore develop other tools to avoid using ZKPs. The proposed approach creates new protocols that allow the prover to prove knowledge of a secret without revealing it. The new approach, called a one-round zero-knowledge-proof, meets all the requirements of ZKPs, yet runs in a single round. The new approach substantially reduces the running-time complexity and communications cost. It eliminates the iteration cost and makes such proofs suitable for practical cryptographic systems for both governmental and commercial applications. The focus of this dissertation is the theory of one-round ZKPs. It presents efficient and secure one-round ZKPs for several classical problems that are used in real life applications. It studies the performance of the proposed one-round ZKPs compared to the existing iterative ZKPs in terms of computation and communication costs. It presents a case study on an identity verification scheme that uses both the iterative ZKP and the new one-round ZKP to compare the results and show the advantages of the new approach.
What Should the User Do? Inference Structures and Line Drawing Interpretation
Authors: S. Ablameyko, V. Bucha, T. P. Pridmore
Venue: Proceedings of the Eighth International Conference on Document Analysis and Recognition (2005)

It is widely accepted that automatic interpretation of drawings and documents will not be achieved in the short to medium term and that manual digitisation is not an acceptable alternative. Despite this there has been little systematic discussion of the role of the user in line drawing interpretation. We consider desirable properties of human interaction with line drawing interpretation systems, argue that descriptions are required of the inference structure of line drawing interpretation tasks and systems if appropriate and effective user involvement is to be achieved, and develop and compare the inference structures of two well-developed line drawing interpretation systems; one automatic, one interactive. Analysis of these representations highlights two areas in which interactivity could be improved. An interactive system addressing one of those areas is outlined and directions for future research are identified.
The pynchon gate: a secure method of pseudonymous mail retrieval
Authors: Len Sassaman, Bram Cohen, Nick Mathewson
Venue: Proceedings of the 2005 ACM workshop on Privacy in the electronic society (2005)

We describe the Pynchon Gate, a practical pseudonymous message retrieval system. Our design uses a simple distributed-trust private information retrieval protocol to prevent adversaries from linking recipients to their pseudonyms, even when some of the infrastructure has been compromised. This approach resists global traffic analysis significantly better than existing deployed pseudonymous email solutions, at the cost of additional bandwidth. We examine security concerns raised by our model, and propose solutions.