ppxscal/embedding_network huggingface dataset:
A Statistical Framework for the Functional Analysis of Metagenomes
Authors: Itai Sharon, Amrita Pati, Victor M. Markowitz, Ron Y. Pinter
Venue: Proceedings of the 13th Annual International Conference on Research in Computational Molecular Biology (2009)

Metagenomicstudies consider the genetic makeup of microbial communities as a whole, rather than their individual member organisms. The functional and metabolic potential of microbial communities can be analyzed by comparing the relative abundance of gene families in their collective genomic sequences (metagenome) under different conditions. Such comparisons require accurate estimation of gene family frequencies. We present a statistical framework for assessing these frequencies based on the Lander-Waterman theory developed originally for Whole Genome Shotgun (WGS) sequencing projects. We also provide a novel method for assessing the reliability of the estimations which can be used for removing seemingly unreliable measurements. We tested our method on a wide range of datasets, including simulated genomes and real WGS data from sequencing projects of whole genomes. Results suggest that our framework corrects inherent biases in accepted methods and provides a good approximation to the true statistics of gene families in WGS projects.
Profiling Java programs for parallelism
Authors: Clemens Hammacher, Kevin Streit, Sebastian Hack, Andreas Zeller
Venue: Proceedings of the 2009 ICSE Workshop on Multicore Software Engineering (2009)

One of the biggest challenges imposed by multi-core architectures is how to exploit their potential for legacy systems not built with multiple cores in mind. By analyzing dynamic data dependences of a program run, one can identify independent computation paths that could have been handled by individual cores. Our prototype computes dynamic dependences for Java programs and recommends locations to the programmer with the highest potential for parallelization. Such measurements can also provide starting points for automatic, speculative parallelization.
A model-driven approach for the visual specification of Role-Based Access Control policies in web systems
Authors: Paloma Diaz, Ignacio Aedo, Daniel Sanz, Alessio Malizia
Venue: Proceedings of the 2008 IEEE Symposium on Visual Languages and Human-Centric Computing (2008)

Specifying the access policy of a web system is a relevant design concern that is often dismissed or postponed until the implementation. ADM-RBAC (Ariadne Development Method with Role-Based Access Control) is a model-driven approach for web systems that supports the specification of access control policies in an integrated way and at two abstraction levels. At the conceptual level a number of visual models specify the access policy in a way that is similar to the users’ point of view. At the detailed level, models are oriented towards providing enough details to generate prototypes in an automatic or semiautomatic way. In this paper we describe the visual models of ADM-RBAC and their empirical evaluation.
Separation of electrocardiographic and encephalographic components based on signal averaging and wavelet shrinkage techniques
Authors: Motoki Sakai, Daming Wei
Venue: Computers in Biology and Medicine (2009)

During ambulatory monitoring, it is often required to record the electroencephalogram (EEG) and the electrocardiogram (ECG) simultaneously. It would be ideal if both EEG and ECG can be obtained with one measurement. We introduce an algorithm combining the wavelet shrinkage and signal averaging techniques to extract the EEG and ECG components from an EEG lead signal to a noncephalic reference (NCR). The evaluation using simulation data and measured data showed that the normalized power spectrum unvaried in all frequency bands for the EEG components, and the sensitivity and specificity of R-wave detection for the ECG component were nearly 100%.
Uniqueness of the Perfect Fusion Grid on Zd
Authors: Jean Cousty, Gilles Bertrand
Venue: Journal of Mathematical Imaging and Vision (2009)

Region merging methods consist of improving an initial segmentation by merging some pairs of neighboring regions. In a graph, merging two regions, separated by a set of vertices, is not straightforward. The perfect fusion graphs defined in J. Cousty et al. (J. Math. Imaging Vis. 30:(1):87---104, 2008) verify all the basic properties required by region merging algorithms as used in image segmentation. Unfortunately, the graphs which are the most frequently used in image analysis (namely, those induced by the direct and the indirect adjacency relations) are not perfect fusion graphs. The perfect fusion grid, introduced in the above mentioned reference, is an adjacency relation on Zd which can be used in image analysis, which indeed induces perfect fusion graphs and which is "between" the graphs induced by the direct and the indirect adjacencies. One of the main results of this paper is that the perfect fusion grid is the only such graph whatever the dimension d.
Collaborative time-based case work
Authors: Morten Bohøj, Niels Olof Bouvin
Venue: Proceedings of the 20th ACM conference on Hypertext and hypermedia (2009)

We explore in this paper using timelines to represent bureaucratic processes in a municipal setting. The system described herein enables citizens and case workers to collaborate over the application for and configuration of parental leave, which is a highly involved process under Danish law.
Formal verification of AADL behavior models: a feasibility investigation
Authors: Hong Liu, David P. Gluch
Venue: Proceedings of the 47th Annual Southeast Regional Conference (2009)

OSATE is an open source platform and toolset built upon Eclipse plug-in technology that supports the modeling and analysis of real-time reactive systems. OSATE implements the Society Automotive Engineers (SAE) standard Architecture Analysis & Design Language (AADL). Because many real-time reactive systems are safety-critical and mission-oriented, the behaviors of these systems are typically subtle and intricate such that even an experienced designer faces significant challenges in their correct design. An AADL Behavior Annex is being developed to help engineers in addressing these challenges. Since several formal model-checking tools have shown the capability of tracing and verifying temporal logic properties of reactive systems, it is desirable to integrate these tools into the OSATE toolset. This will enable the formal verification of the behavior of AADL models. In this paper, we present two case studies that explore the feasibility of extending model-checking tools to the OSATE toolset. The preliminary work and case studies in this paper address several important questions relating to a tool integration project.
Graduate attributes and performance measures: refinements in assessing programs
Authors: John Impagliazzo
Venue: ACM SIGCSE Bulletin (2009)

In this poster, the author provides a pictorial demonstration of the elements associated with assessment and its relationship to the newly developed requirements by accrediting bodies in various countries. Specifically, it illustrates expected attributes of program graduates and it highlights the importance of performance measures when assessing learning outcomes of a program. The poster shows forms of assessment and it provides definitions and examples of program mission, goals, and learning outcomes, performance indicators, performance measures, and the use of rubrics. The poster highlights the interaction of all these assessment characteristics.
Clavius: bi-directional parsing for generic multimodal interaction
Authors: Frank Rudzicz
Venue: Proceedings of the 21st International Conference on computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop (2006)

We introduce a new multi-threaded parsing algorithm on unification grammars designed specifically for multimodal interaction and noisy environments. By lifting some traditional constraints, namely those related to the ordering of constituents, we overcome several difficulties of other systems in this domain. We also present several criteria used in this model to constrain the search process using dynamically loadable scoring functions. Some early analyses of our implementation are discussed.
Resource augmented semi-online bounded space bin packing
Authors: Leah Epstein, Elena Kleiman
Venue: Discrete Applied Mathematics (2009)

We study on-line bounded space bin-packing in the resource augmentation model of competitive analysis. In this model, the on-line bounded space packing algorithm has to pack a list L of items with sizes in (0, 1], into a minimum number of bins of size b, b>=1. A bounded space algorithm has the property that it only has a constant number of active bins available to accept items at any point during processing. The performance of the algorithm is measured by comparing the produced packing with an optimal offline packing of the list L into bins of size 1. The competitive ratio then becomes a function of the on-line bin size b. Csirik and Woeginger studied this problem in [J. Csirik, G.J. Woeginger, Resource augmentation for online bounded space bin packing, Journal of Algorithms 44(2) (2002) 308-320] and proved that no on-line bounded space algorithm can perform better than a certain bound @r(b) in the worst case. We relax the on-line condition by allowing a complete repacking within the active bins, and show that the same lower bound holds for this problem as well, and repacking may only allow one to obtain the exact best possible competitive ratio of @r(b) having a constant number of active bins, instead of achieving this bound in the limit. We design a polynomial time on-line algorithm that uses three active bins and achieves the exact best possible competitive ratio @r(b) for the given problem.
Error Analysis of Stereo Calibration and Reconstruction
Authors: Agnieszka Bier, Leszek Luchowski
Venue: Proceedings of the 4th International Conference on Computer Vision/Computer Graphics CollaborationTechniques (2009)

This paper addresses the problem of the propagation of input data errors in the stereovision process and its influence on the quality of reconstructed 3D points. We consider only those particular camera calibration and 3D reconstruction algorithms which employ singular value decomposition (SVD) methods. Using the SVD Jacobian estimation method developed by Papadopoulo and Lourakis, we determine all the partial derivatives of outputs with respect to the inputs and present a set of tests applying them in various stereovision conditions in order to evaluate their impact on the quality of 3D reconstruction.
A memetic algorithm for gene selection and molecular classification of cancer
Authors: Béatrice Duval, Jin-Kao Hao, Jose Crispin Hernandez Hernandez
Venue: Proceedings of the 11th Annual conference on Genetic and evolutionary computation (2009)

Choosing a small subset of genes that enables a good classification of diseases on the basis of microarray data is a difficult optimization problem. This paper presents a memetic algorithm, called MAGS, to deal with gene selection for supervised classification of microarray data. MAGS is based on an embedded approach for attribute selection where a classifier tightly interacts with the selection process. The strength of MAGS relies on the synergy created by combining a problem specific crossover operator and a dedicated local search procedure, both being guided by relevant information from a SVM classifier. Computational experiments on 8 well-known microarray datasets show that our memetic algorithm is very competitive compared with some recently published studies.
An outdoor time scenes simulation scheme based on support vector regression with radial basis function on DCT domain
Authors: Chen-Chung Liu, Kai-Wen Chuang
Venue: Image and Vision Computing (2009)

In this paper, a novel strategy for forecasting outdoor scenes is introduced. This new approach combines the support vector regression in neural network computation and the discrete cosine transform (DCT). In 1995, Vapnik introduced a neural-network algorithm called support vector machine (SVM). During the recent years, due to SVM's high generalization performance and attractive modeling features, it has received increasing attention in the application of regression estimation - which is called support vector regression (SVR). In SVR, a set of color-block images were transformed by the discrete cosine transformation to be the training data. We also used the radial basis function (RBF) of the training data as SVR's kernel to establish the RBF neural network. Finally, the time scenes simulation algorithm (TSSA) is able to synthesize the corresponding scene of any assigned time of the original outdoor scene image. To explore the utility and demonstrate the efficiency of the proposed algorithm, simulations under various input images were conducted. The experiment results showed that our proposed algorithm can precisely simulate the desired scenes at an assigned time and has two advantages: (a) Using the color-block images instead of using the scene images of a place to create the reference database, the database can be used for any outdoor scene image taken at anywhere at anytime. (b) Taking the support vector regression on the DCT coefficients of scene images instead of taking the SVR on the spatial pixels of scene images, it simplifies the regression procedure and saves the processing time.
High Acceleration for Video Processing Applications Using Specialized Instruction Set Based on Parallelism and Data Reuse
Authors: Nicolas Beucher, Normand Bélanger, Yvon Savaria, Guy Bois
Venue: Journal of Signal Processing Systems (2009)

This paper describes an application-specific instruction set for a configurable processor to accelerate motion-compensated frame rate conversion (MC-FRC) algorithms based on block motion estimation (BME). The paper shows that the key to achieve very high performance when creating new instructions is to leverage, at the same time, parallel computations, data reuse, and efficient cache use. This is supported by concrete examples that demonstrate how it can be done in the case of the two algorithms considered. The new instructions are used to implement two BME algorithms: one implements the full search (FS) block matching algorithm (BMA), while the other implements the One-Dimensional Full Search (ODFS) BMA. The obtained acceleration factors exceed one hundred for the MC-FRC algorithm embedding the FS algorithm and twenty for the ODFS algorithm. The results show that getting such global acceleration is the consequence of combining parallel computations, data reuse, and efficient cache use, not of only one of them.
A stochastic memoizer for sequence data
Authors: Frank Wood, Cédric Archambeau, Jan Gasthaus, Lancelot James, Yee Whye Teh
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

We propose an unbounded-depth, hierarchical, Bayesian nonparametric model for discrete sequence data. This model can be estimated from a single training sequence, yet shares statistical strength between subsequent symbol predictive distributions in such a way that predictive performance generalizes well. The model builds on a specific parameterization of an unbounded-depth hierarchical Pitman-Yor process. We introduce analytic marginalization steps (using coagulation operators) to reduce this model to one that can be represented in time and space linear in the length of the training sequence. We show how to perform inference in such a model without truncation approximation and introduce fragmentation operators necessary to do predictive inference. We demonstrate the sequence memoizer by using it as a language model, achieving state-of-the-art results.
Efficient Deniable Authentication for Signatures
Authors: Jean Monnerat, Sylvain Pasini, Serge Vaudenay
Venue: Proceedings of the 7th International Conference on Applied Cryptography and Network Security (2009)

Releasing a classical digital signature faces to privacy issues. Indeed, there are cases where the prover needs to authenticate some data without making it possible for any malicious verifier to transfer the proof to anyone else. It is for instance the case for e-passports where the signature from the national authority authenticates personal data. To solve this problem, we can prove knowledge of a valid signature without revealing it. This proof should be non-transferable.We first study deniability for signature verification. Deniability is essentially a weaker form of non-transferability. It holds as soon as the protocol is finished (it is often called offline non-transferability).We introduce Offline Non-Transferable Authentication Protocol (ONTAP) and we show that it can be built by using a classical signature scheme and a deniable zero-knowledge proof of knowledge. For that reason, we use a generic transform for Σ-protocols.Finally, we give examples to upgrade signature standards based on RSA or ElGamal into an ONTAP. Our examples are well-suited for implementation in e-passports.
Mastering Microsoft Exchange Server 2007 SP1, 2nd edition
Authors: Jim McBee
Venue:  (2009)

Microsoft Exchange Server provides a reliable messaging system that protects against spam and viruses and allows for access to e-mail, voicemail, and calendars from a variety devices and any location. Fully updated for the latest release of Microsoft Exchange Server 2007 Service Pack 1 (SP1), this book offers a look at the significant improvements and exciting features of SP1 and explains how they will increase productivity. Youll walk through planning and design, installation, administration and management, maintenance, and more and also take a look at SP1s interoperability with Windows Server 2008, unified messaging, and enhancements in mobile e-mail security and management.
Spectral Method in Multiaxial Random Fatigue, 1st edition
Authors: Adam Nieslony, Ewald Macha
Venue: Lecture Notes In Applied And Computational Mechanics (2007)

This monograph contains theoretical foundations of the spectral method for fatigue life determination where the authors discuss a rule of description of random loading states with the matrix of power spectral density functions of the stress/strain tensor components. Some chosen criteria of multiaxial fatigue failure being linear combinations of stress or strain components on the critical plane are analyzed. The formula proposed in this book enables to determine power spectral density of the equivalent history directly from the components of the power spectral density matrix of the multidimensional stochastic process. It presents the assumptions and the procedure of determination of basic relationships of the spectral method. The authors work out equations determining the fatigue life according to the spectral method using various linear hypotheses of fatigue damage accumulation. The algorithm of fatigue life contains five blocks: 1 determination of loading, 2 determination of the critical plane position for the assumed multiaxial fatigue failure criterion, 3 determination of power spectral density of the equivalent stress or strain, 4 determination of statistical parameters of the equivalent parameter responsible for fatigue damage, and 5 fatigue life calculation according to a suitable hypothesis of damage accumulation.
A finite element variational multiscale method for incompressible flows based on two local gauss integrations
Authors: Haibiao Zheng, Yanren Hou, Feng Shi, Lina Song
Venue: Journal of Computational Physics (2009)

In this article, we present a finite element variational multiscale (VMS) method for incompressible flows based on two local Gauss integrations, and compare it with common VMS method which is defined by a low order finite element space L"h on the same grid as X"h for the velocity deformation tensor and a stabilization parameter @a. The best algorithmic feature of our method is using two local Gauss integrations to replace projection operator. We theoretically discuss the relationship between our method and common VMS method for the Taylor-Hood elements, and show that the nonlinear system derived from our method by finite element discretization is much smaller than that of common VMS method computationally. Additionally we present numerical simulations to demonstrate the effectiveness, storage, computational complexity of our method. Finally, we give some numerical simulations of the nonlinear flow problems to show good stability and accuracy properties of the method.
Feature level fusion of range and intensity images of an object
Authors: Umesh C. Pati, Pranab K. Dutta, Alok Barua
Venue: International Journal of Computational Vision and Robotics (2009)

This paper presents feature level fusion of images of an object obtained from two different imaging techniques. A draft 3-D view of the object is generated by registering range images obtained from scanning the object by a laser beam. For that purpose, the method of optical triangulation is employed for data acquisition and feature matching technique for the registration of the images. Triangle-based linear interpolation is used to obtain a 3-D mesh representing the object surface. Structural features are extracted from the draft 3-D model of the object and subsequently mapped to 2-D plane by perspective transformation. Hough transform technique has been implemented for the extraction of structural features from the intensity image of the object obtained under illumination light. Fusion of both the extracted edge maps is accomplished by affine transformation after identifying a set of control points. This provides a high-level description of the object.
Sparse Linear Combination of SOMs for Data Imputation: Application to Financial Database
Authors: Antti Sorjamaa, Francesco Corona, Yoan Miche, Paul Merlin, Bertrand Maillet, Eric Séverin, Amaury Lendasse
Venue: Proceedings of the 7th International Workshop on Advances in Self-Organizing Maps (2009)

This paper presents a new methodology for missing value imputation in a database. The methodology combines the outputs of several Self-Organizing Maps in order to obtain an accurate filling for the missing values. The maps are combined using MultiResponse Sparse Regression and the Hannan-Quinn Information Criterion. The new combination methodology removes the need for any lengthy cross-validation procedure, thus speeding up the computation significantly. Furthermore, the accuracy of the filling is improved, as demonstrated in the experiments.
A New Image Fusion Method for Estimating 3D Surface Depth
Authors: Marcin Denkowski, Michał Chlebiej, Paweł Mikołajczak
Venue: Proceedings of the International Conference on Computer Vision and Graphics: Revised Papers (2008)

Creation of virtual reality models from photographs is very complex and time-consuming process, that requires special equipment like laser scanners, a large number of photographs and manual interaction. In this work we present a method for generating of surface geometry of photographed scene. Our approach is based on the phenomenon of shallow depth-of-field in close-up photography. Representing such surface details is useful to increase the visual realism in a range of application areas, especially biological structures or microorganisms.For testing purposes a set of images of the same scene is taken from a typical digital camera with macro lenses with a different depth-of-field. Our new image fusion method employs discrete Fourier transform to designate sharp regions in this set of images, combine them together into a fully focused image and finally produce a height field map. Further image processing algorithms approximate three dimensional surface using this height field map and a fused image. Experimental results show that our method works for wide range of cases and gives a good tool for acquiring surfaces from a few photographs.