ppxscal/embedding_network huggingface dataset:
Universal Booleanization of Constraint Models
Authors: Jinbo Huang
Venue: Proceedings of the 14th international conference on Principles and Practice of Constraint Programming (2008)

While the efficiency and scalability of modern SAT technology offers an intriguing alternative approach to constraint solving via translation to SAT, previous work has mostly focused on the translation of specific types of constraints, such as pseudo Boolean constraints, finite integer linear constraints, and constraints given as explicit listings of allowed tuples. By contrast, we present a translation of constraint models to SAT at language level, using the recently proposed constraint modeling language MiniZinc, such that any satisfaction or optimization problem written in the language (not involving floats) can be automatically Booleanized and solved by one or more calls to a SAT solver. We discuss the strengths and weaknesses of such a universal constraint solver, and report on a large-scale empirical evaluation of it against two existing solvers for MiniZinc: the finite domain solver distributed with MiniZinc and one based on the Gecode constraint programming platform. Our results indicate that Booleanization indeed offers a competitive alternative, exhibiting superior performance on some classes of problems involving large numbers of constraints and complex integer arithmetic, in addition to, naturally, problems that are already largely Boolean. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Attacks on SVD-Based Watermarking Schemes
Authors: Huo-Chong Ling, Raphael C. Phan, Swee-Huay Heng
Venue: Proceedings of the IEEE ISI 2008 PAISI, PACCF, and SOCO international workshops on Intelligence and Security Informatics (2008)

One major application of a watermarking scheme is to protect the copyright of a content owner by embedding the owner's watermark into the content. Recently, two watermarking schemes were proposed by Chang et al. [1, 2], which are based on singular value decomposition (SVD). In this paper, we present attacks on these watermarking schemes and show how the designers' security claims can be invalidated, namely related to robustness and protection of rightful ownership. Our results are the first known attacks on these SVD-based watermarking schemes.
A Method for FLIR Target Tracking Based on Distance Updating
Authors: Lin Qi, Zelin Shi
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

This paper deals with the problem that how to use the distance information of millimeter wave (MMW) radar in the target-tracking of forward looking infrared (FLIR) image sequences. Many conventional image based trackers use timing updating to update template, but how to confirm an appropriate updating period is a difficult problem. However, the presence of noise and image magnification as the camera approaches the target may cause a tracked template to drift. In a MMW/FLIR dual-mode seeking guidance system, MMW radar can provide the precise distance between the missile and the target. The distance information can be used to direct how to update template. Firstly, a distance updating strategy is confirmed after image blowup's influence on pertinence is analyzed. Secondly, magnified template is used to direct template updating after images are magnified by distance information. Lastly, an adaptive template updating algorithm using distance information is presented. Results acquired for real FLIR images obtained from an aircraft are presented. Experiments results show that the higher tracking accuracy and the stronger stability are obtained in the algorithm proposed than those in other methods.
A Novel Approach for Detection of Tubular Objects and Its Application to Medical Image Analysis
Authors: Christian Bauer, Horst Bischof
Venue: Proceedings of the 30th DAGM symposium on Pattern Recognition (2008)

We present a novel approach for detection of tubular objects in medical images. Conventional tube detection / lineness filters make use of local derivatives at multiple scales using a linear scale space; however, using a linear scale space may result in an undesired diffusion of nearby structures into one another and this leads to problems such as detection of two tangenting tubes as one single tube. To avoid this problem, we propose to replace the multi-scale computation of the gradient vectors by the Gradient Vector Flow, because it allows an edge-preserving diffusion of gradient information. Applying Frangi's vesselness measure to the resulting vector field allows detection of centerlines from tubular objects, independent of the tubes size and contrast. Results and comparisons to related methods on synthetic and clinical datasets show a high robustness to image noise and to disturbances outside the tubular objects.
Incorporating Image Quality in Multimodal Biometric Verification
Authors: Hong Huang, Jianwei Li, Zezhong Ma, Hailiang Feng
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

The effect of image quality on the performance of multimodal biometric verification is studied. A biometric system based solely on single modality is often not able to meet the system performance requirements for poor image quality. Prior studies of multimodal biometric authentication have shown that it can improve performance over use of a single unimodal biometric. The well-known multimodal methods do not consider the quality information of the data used when combining the results from different matchers. In the paper, a novel SVM-based multimodal biometric authentication system is presented. It is based on SVM classifiers and quality measures of the input biometric signals. Experimental results on a prototype application based on fingerprint and face are reported. The proposed scheme is shown to outperform significantly multimodal systems without considering quality signals and unimodal systems over a wide range of image quality.
Approximate Periods with Levenshtein Distance
Authors: Martin Šimůnek, Bořivoj Melichar
Venue: Proceedings of the 13th international conference on Implementation and Applications of Automata (2008)

We present a new algorithm deciding for strings t and w whether w is an approximate generator of t with Levenshtein distance at most k. The algorithm is based on finite state transducers.
Searching for Points-To Analysis
Authors: Glenn Bruns Satish Chandra
Venue: IEEE Transactions on Software Engineering (2003)

The points-to analysis problem is to find the pointer relationships that could arise during program execution. Many points-to analysis algorithms exist, each making a particular trade off between cost of the analysis and precision of the results. In this paper, we show how points-to analysis algorithms can be defined as transformed versions of an exact algorithm. We present a set of program transformations over a general program model and use them to define some existing points-to analysis algorithms. Doing so makes explicit the approximations involved in these algorithms. We also show how the transformations can be used to define new points-to analysis algorithms. Our transformations are generic and may be useful in the design of other program analysis algorithms.
A unified elementary approach to the Dyson, Morris, Aomoto, and Forrester constant term identities
Authors: Ira M. Gessel, Lun Lv, Guoce Xin, Yue Zhou
Venue: Journal of Combinatorial Theory Series A (2008)

We introduce an elementary method to give unified proofs of the Dyson, Morris, and Aomoto identities for constant terms of Laurent polynomials. These identities can be expressed as equalities of polynomials and thus can be proved by verifying them for sufficiently many values, usually at negative integers where they vanish. Our method also proves some special cases of the Forrester conjecture.
Impact of Learning on the Structural Properties of Neural Networks
Authors: Branko Šter, Ivan Gabrijel, Andrej Dobnikar
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II (2007)

We research the impact of the learning process of neural networks (NN) on the structural properties of the derived graphs. A type of recurrent neural network is used (GARNN). A graph is derived from a NN by defining a connection between any pair od nodes having weights in both directions above a certain threshold. We measured structural properties of graphs such as characteristic path lengths (L), clustering coefficients (C) and degree distributions (P). We found that well trained networks differ from badly trained ones in both L and C.
An Introduction to Conceptual Graphs
Authors: Simon Polovina
Venue: Proceedings of the 15th international conference on Conceptual Structures: Knowledge Architectures for Smart Applications (2007)

This paper provides a lucid introduction to Conceptual Graphs (CG), a powerful knowledge representation and inference environment that exhibits the familiar object-oriented features of contemporary enterprise and web applications. An illustrative business case study is used to convey how CG adds value to data, including inference for new knowledge. It enables newcomers to conceptual structures to engage with this exciting field and to realise "Conceptual Structures: Knowledge Architectures for Smart Applications", the theme of the 15 th Annual International Conference on Conceptual Structures (ICCS 2007, www.iccs2007.info).
Unsupervised Bayesian Network Learning for Object Recognition in Image Sequences
Authors: Daniel Oberhoff, Marina Kolesnik
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part I (2008)

We present work on the learning of hierarchical Bayesian networks for image recognition tasks. We employ Bayesian priors to the parameters to avoid over-fitting and variational learning. We further explore the effect of embedding Hidden Markov Models with adjusted priors to perform sequence based grouping, and two different learning strategies, one of which can be seen as a first step towards online-learning. Results on a simple data-set show, that the simplest network and learning strategy work best, but that the penalty for the more complex models is reasonable, encouraging work on more complex problems.
Active learning and feedback patterns: version 4
Authors: Joseph Bergin
Venue: Proceedings of the 2006 conference on Pattern languages of programs (2006)

These four Pedagogical Patterns are intended to extend the Feedback [5] and Active Learning [2] collections within the Pedagogical Patterns Project. The ideas here have been gathered from observing expert teachers and the descriptions of what they do.
A Quantitative Evaluation of Dissemination-Time Preservation Metadata
Authors: Joan A. Smith, Michael L. Nelson
Venue: Proceedings of the 12th European conference on Research and Advanced Technology for Digital Libraries (2008)

One of many challenges facing web preservation efforts is the lack of metadata available for web resources. In prior work, we proposed a model that takes advantage of a site's own web server to prepare its resources for preservation. When responding to a request from an archiving repository, the server applies a series of metadata utilities, such as Jhove and Exif, to the requested resource. The output from each utility is included in the HTTP response along with the resource itself. This paper addresses the question of feasibility: Is it in fact practical to use the site's web server as a just-in-time metadata generator, or does the extra processing create an unacceptable deterioration in server responsiveness to quotidian events? Our tests indicate that (a) this approach can work effectively for both the crawler and the server; and that (b) utility selection is an important factor in overall performance.
Some remarks on logical design and programming checks
Authors: Herman H. Goldstine
Venue: Papers and discussions presented at the Dec. 8-10, 1953, eastern joint AIEE-IRE computer conference: information processing systems---reliability and requirements (1953)

I should like to discuss two topics which are of some interest. One, is it possible to construct out of elements which are known to be imperfect a logical automaton which will have a given degree of reliability? Two, given a machine, what can one do by way of programming checks to insure accuracy of the final results?
A Novel Approach to Efficient Monte-Carlo Localization in RoboCup
Authors: Patrick Heinemann, Jürgen Haase, Andreas Zell
Venue: RoboCup 2006: Robot Soccer World Cup X (2006)

Recently, efficient self-localization methods have been developed, among which probabilistic Monte-Carlo localization (MCL) is one of the most popular. However, standard MCL algorithms need at least 100 samples to compute an acceptable position estimation. This paper presents a novel approach to MCL that uses an adaptive number of samples that drops down to a single sample if the pose estimation is sufficiently accurate. Experiments show that the method remains in this efficient single sample tracking mode for more than 90% of the cycles.
Precise Semantics of EMF Model Transformations by Graph Transformation
Authors: Enrico Biermann, Claudia Ermel, Gabriele Taentzer
Venue: Proceedings of the 11th international conference on Model Driven Engineering Languages and Systems (2008)

Model transformation is one of the key activities in model-driven software development. An increasingly popular technology to define modeling languages is provided by the Eclipse Modeling Framework (EMF). Several EMF model transformation approaches have been developed, focusing on different transformation aspects. To validate model transformations wrt. functional behavior and correctness, a formal foundation is needed. In this paper, we define EMF model transformations as a special kind of typed graph transformations using node type inheritance. Containment constraints of EMF model transformations are translated to a special kind of EMF model transformation rules such that their application leads to consistent transformation results only. Thus, we identify a kind of EMF model transformations which behave like algebraic graph transformations. As a consequence, the rich theory of algebraic graph transformation can be applied to these EMF model transformations to show functional behavior and correctness. We illustrate our approach by selected refactorings of simplified statechart models.
Composable Security in the Bounded-Quantum-Storage Model
Authors: Stephanie Wehner, Jürg Wullschleger
Venue: Proceedings of the 35th international colloquium on Automata, Languages and Programming, Part II (2008)

We give a new, simulation-based, definition for security in the bounded-quantum-storage model, and show that this definition allows for sequential composition of protocols. Damgård et al. (FOCS '05, CRYPTO '07) showed how to securely implement bit commitment and oblivious transfer in the bounded-quantum-storage model, where the adversary is only allowed to store a limited number of qubits. However, their security definitions did only apply to the standalone setting, and it was not clear if their protocols could be composed. Indeed, we show that these protocols are not composable in our framework without a small refinement. We then prove the security of their randomized oblivious transfer protocol with our refinement. Secure implementations of oblivious transfer and bit commitment follow easily by a (classical) reduction to randomized oblivious transfer.
Computational discovery of gene modules, regulatory networks and expression programs
Authors: David K. Gifford
Venue:  (2007)

High-throughput molecular data are revolutionizing biology by providing massive amounts of information about gene expression and regulation. Such information is applicable both to furthering our understanding of fundamental biology and to developing new diagnostic and treatment approaches for diseases. However, novel mathematical methods are needed for extracting biological knowledge from high-dimensional, complex and noisy data sources. In this thesis, I develop and apply three novel computational approaches for this task. The common theme of these approaches is that they seek to discover meaningful groups of genes, which confer robustness to noise and compress complex information into interpretable models. I first present the GRAM algorithm, which fuses information from genome-wide expression and in vivo transcription factor-DNA binding data to discover regulatory networks of gene modules. I use the GRAM algorithm to discover regulatory networks in Saccharomyces cerevisiae, including rich media, rapamycin, and cell-cycle module networks. I use functional annotation databases, independent biological experiments and DNA-motif information to validate the discovered networks, and to show that they yield new biological insights. Second, I present GeneProgram, a framework based on Hierarchical Dirichlet Processes, which uses large compendia of mammalian expression data to simultaneously organize genes into overlapping programs and tissues into groups to produce maps of expression programs. I demonstrate that GeneProgram outperforms several popular analysis methods, and using mouse and human expression data, show that it automatically constructs a comprehensive, body-wide map of inter-species expression programs. Finally, I present an extension of GeneProgram that models temporal dynamics. I apply the algorithm to a compendium of short time-series gene expression experiments in which human cells were exposed to various infectious agents. I show that discovered expression programs exhibit temporal pattern usage differences corresponding to classes of host cells and infectious agents, and describe several programs that implicate surprising signaling pathways and receptor types in human responses to infection. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)
Black box methods for inferring parallel applications' properties in virtual environments
Authors: Peter Dinda
Venue:  (2008)

Virtual machine based distributed computing greatly simplifies and enhances adaptive/autonomic computing by lowering the level of abstraction, benefiting both resource providers and users. We are developing Virtuoso, a middleware system for virtual machine shared-resource computing (e.g. grids) that provides numerous advantages and overcomes many obstacles a user faces in using shared resources for deploying distributed applications. A major hurdle for distributed applications to function in such an environment is locating, reserving/scheduling and dynamically adapting to the appropriate communication and computational resources so as to meet the applications' demands, limited by cost constraints. Resources can be very heterogeneous, especially in wide area or shared infrastructures, and their availability is also highly dynamic.To achieve such automated adaptation, one must first learn about the various demands and properties of the distributed application running inside the VMs. My thesis is that it is feasible to infer the applications' demands and behavior, to a significant degree, without actually knowing much about the application or its operating system; I have investigated and demonstrated numerous novel techniques to infer many useful properties of parallel applications, in an automated fashion. Throughout my work I have used a black box approach to inference. Thus the results are applicable to existing, unmodified applications and operating systems and are widely applicable.I show how to infer the communication behavior and the runtime topology of a parallel application. I also show how to infer very useful runtime properties of a parallel application such as its runtime performance. I have developed the algorithms to understand quantitatively the slowdown of an application under external load to find global bottlenecks at the resource and process level using time decomposition of the application's execution.In addition, my dissertation also gives limited evidence and points to other work that shows that this inferred information can actually be used to benefit the application, without having any knowledge of the application/OS itself.
Heuristic Hill-Climbing as a Markov Process
Authors: Carlos Linares López
Venue: Proceedings of the 13th international conference on Artificial Intelligence: Methodology, Systems, and Applications (2008)

The purpose of this paper is twofold: on one hand, modelling the hill-climbing heuristic search algorithm as a stochastic process serves for deriving interesting properties about its expected performance; on the other hand, the probability that a hill-climbing search algorithm ever fails when approaching the target node (i.e., it does not find a descendant with a heuristic value strictly lower than the current one) can be considered as a pesimistic measure of the accuracy of the heuristic function guiding it. Thus, in this work, it is suggested to model heuristic hill-climbing search algorithms with Markov chains in order to fulfill these goals. Empirical results obtained in various sizes of the (n,m)-Puzzle domain prove that this model leads to very accurate predictions. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
The MM-Tree: A Memory-Based Metric Tree Without Overlap Between Nodes
Authors: Ives Rene Pola, Caetano Traina,  Jr., Agma Juci Traina
Venue: Proceedings of the 11th East European conference on Advances in Databases and Information Systems (2007)

Advanced database systems offer similarity queries on complex data. Searching by similarity on complex data is accelerated through the use of metric access methods (MAM). These access methods organize data in order to reduce the number of comparison between elements when answering queries. MAM can be categorized in two types: disk-based and memory-based. The disk-based structures limit the partitioning of space forcing nodes to have multiple elements according to disk page sizes. However, memory-based trees allows more flexibility, producing trees faster to build and to perform queries. Although recent developments target disk-based methods on tree structures, several applications benefits from a faster way to build indexes on main memory. This paper presents a memory-based metric tree, the MM-tree, which successively partitions the space into non-overlapping regions. We present experiments comparing MM-tree with existing high performance MAM, including the disk-based Slim-tree. The experiments reveal that MM-tree requires up to one fifth of the number of distance calculations to be constructed when compared with Slim-tree, performs range queries requiring 64% less distance calculations and KNN queries requiring 74% less distance calculations.
ERDRM: A Digital Rights Management System Model for Educational Resources
Authors: Shujuan Wang, Qingtang Liu
Venue: Proceedings of the 7th international conference on Advances in Web Based Learning (2008)

The intellectual property protection problem has been an obstacle to restrict the development of distance education. Enhancing the intellectual property protection of educational resources will make great realistic significance in improving quality of distance education. DRM provides technological support to the intellectual property protection in distance education. In the first part of this paper, we introduce the current situation of DRM technology and its fundamental features. And then, through analysis of the special demands of the educational field and contrastive study of security technology available currently, we bring forth the ERDRM, a digital rights management system model for educational resources.