ppxscal/embedding_network huggingface dataset:
Computational strategies for meshfree nonrigid registration
Authors: Lawrence Hamilton Staib
Venue:  (2006)

Biological shapes such as the brain are difficult to register due to their complicated geometry. To deal with this, registration methods often rely on a transformation model consisting of a dense regular grid such as a free form deformation or B-spline grid. However, very dense grids or meshes are usually needed to register images with convoluted shapes, and a regular mesh structure is not well suited for the irregular structure of the brain. What is therefore needed is a meshfree approach such as a radial basis function transformation model. Unfortunately, because radial basis functions are typically non-compact, using them with large numbers of points is fraught with numerical difficulties and, as a result, their use in image registration is not prevalent. The goal of this work is to overcome these computational difficulties so that radial basis function transformations can be used efficiently, even with large numbers of points. To achieve this, a new registration framework was developed based on automatic differentiation and the fast multipole method. Automatic differentiation is useful since an important component of registration is computing the gradient of the similarity metric which is to be optimized. Automatic differentiation allows one to efficiently calculate gradients without having to write any gradient code explicitly. Although the technique of automatic differentiation is well established, it does not appear to be used for image registration. The fast multipole method was developed to efficiently evaluate large sums such as radial basis functions but its use in image registration is still minimal. With the integration of these algorithms within a complete registration framework, it should be possible to obtain a truly meshfree registration.
Towards virtual networks for virtual machine grid computing
Authors: Ananth I. Sundararaj, Peter A. Dinda
Venue: Proceedings of the 3rd conference on Virtual Machine Research And Technology Symposium - Volume 3 (2004)

Virtual machines can greatly simplify wide-area distributed computing by lowering the level of abstraction to the benefit of both resource providers and users. Networking, however, can be a challenge because remote sites are loath to provide connectivity to any machine attached to the site network by outsiders. In response, we have developed a simple and efficient layer two virtual network tool that in effect connects the virtual machine to the home network of the user, making the connectivity problem identical to that faced by the user when connecting any new machine to his own network. We describe this tool and evaluate its performance in LAN and WAN environments. Next, we describe our plans to enhance it to become an adaptive virtual network that will dynamically modify its topology and routing rules in response to the offered traffic load of the virtual machines it supports and to the load of the underlying network. We formalize the adaptation problem induced by this scheme and take initial steps to solving it. The virtual network will also be able to use underlying resource reservation mechanisms on behalf of virtual machines. Both adaptation and reservation will work with existing, unmodified applications and operating systems.
Fracture of Kinetic Energy Rods Subject to Oblique Impact
Authors: Robert L. Anderson
Venue: Proceedings of the HPCMP Users Group Conference (2006)

Kinetic energy (KE) penetrators are often used in military anti-armor applications. These penetrators may have a tendency to fracture during oblique penetration, thereby reducing the rod's ability to penetrate subsequent regions of the target. Under this premise, the military is interested in developing penetrator designs to better resist fracture due to the lateral loading applied by oblique impact.
How do high school mathematics texts cover engineering and technology?
Authors: R. J. Quinn
Venue: Proceedings of the Frontiers in Education Conference, 2001. 31st Annual - Volume 02 (2001)

The recently developed National Science Education Standards (NSES) and Principles and Standards for School Mathematics (PSSM) promote scientific and mathematical literacy for all students. Further, NSES recommends that an engineering component is an important part of scientific literacy. In previous papers, obstacles to the fulfillment of these goals were considered. One work reviewed science texts, concluding that while most recent science texts make connections to society and use mathematics and science in technological applications, they fall short with regard to the inclusion of engineering principles in questions, problems, and laboratory activities. In this paper, the authors sample some widely used high school mathematics texts and review their coverage of engineering. They identify problems with their coverage and suggest alternative ways of introducing engineering to students. Throughout the paper, they adopt inquiry as the preferred pedagogy for introducing engineering to high school students.
Incorporation of temporal masking effects into bark spectral distortion measure
Authors: B. Novorita
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 02 (1999)

The objective of this paper is to extend a promising objective speech distortion measurement method, the bark spectral distance (BSD) measure, with the auditory concepts of forward and backward temporal masking to improve its measurement accuracy. The results of this investigation show that automatic BSD-based speech quality ratings may be made to correlate better with existing MOS ratings by removing perceptually irrelevant areas of speech from the distance measure. The correlation between the objective BSD measure to the subjective MOS measure increases from 0.91 to 0.98. The best results were found with a window duration of 128 samples, use of exponential-slope filter characteristics for both forward and backward masking effects, forward masking delays up to 100 msec, and a backward masking time advance of 40 msec.
On the equivalence between FDs in XML and FDs in relations
Authors: Millist W. Vincent, Jixue Liu, Mukesh Mohania
Venue: Acta Informatica (2007)

With the growing use of the eXtensible Markup Language (XML) in database technology as a format for the permanent storage of data, the topic functional dependencies in XML (XFDs) has assumed increased importance because of its central role in database design. Recently, two different approaches have been proposed for defining an XFD. The first uses the concept of a &#x2018;tree tuple&#x2019;, whereas the second uses the concept of a &#x2018;closest node&#x2019;. In general, the two approaches are not comparable, but are comparable when a Document Type Definition is present and there is no missing information in the XML document. The first contribution of this article shows that when the two XFD definitions are comparable, the definitions are equivalent, and so there is essentially a common definition of an XFD in complete XML documents. The second contribution is to provide justification for the definition of a &#x2018;closest node&#x2019; XFD. We show that if a complete flat relation is mapped to an XML document by an arbitrary sequence of nest operations, the XML document satisfies a &#x2018;closest node&#x2019; XFD if and only if the relation satisfies the corresponding functional dependency. The class of XML documents generated in this fashion is a subset of the class of XML documents for which the two definitions of XFDs coincide. Hence &#x2018;tree tuple&#x2019; and &#x2018;closest node&#x2019; XFDs both capture the semantics of FDs when a complete relation is mapped to an XML document via arbitrary nesting.
Modified Line Search Method for Global Optimization
Authors: Crina Grosan, Ajith Abraham
Venue: Proceedings of the First Asia International Conference on Modelling & Simulation (2007)

This paper introduces a modified version of the well known global optimization technique named line search method. The modifications refer to the way in which the direction and the steps are determined. The modified line search technique (MLS) is applied for some global optimization problems. Functions having a high number of dimensions are considered (50 in this case). Results obtained by the proposed method on a set of well known benchmarks are compared to the results obtained by the standard line search method, genetic algorithms and differential evolution. Numerical results show the effectiveness of the proposed approach while compared to the other techniques.
Voice activity detection based on a family of parametric distributions
Authors: Jong Won Shin, Joon-Hyuk Chang, Nam Soo Kim
Venue: Pattern Recognition Letters (2007)

In this letter, generalized gamma distribution (G@CD) is introduced as a new statistical model of spectral distribution to be applied to the likelihood ratio test performed in voice activity detection (VAD). A gradient-based on-line algorithm is proposed to estimate the parameters of G@CD according to the maximum likelihood criterion. Experimental results show that the VAD algorithm implemented based on G@CD outperformed those adopting other parametric distributions.
Perceptual and objective detection of discontinuities in concatenative speech synthesis
Authors: Y. Stylianou
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 200. on IEEE International Conference - Volume 02 (2001)

Concatenative speech synthesis systems attempt to minimize audible signal discontinuities between two successive concatenated units. An objective distance measure which is able to predict audible discontinuities is therefore very important, particularly in unit selection synthesis, for which units are selected from among a large inventory at run time. In this paper, we describe a perceptual test to measure the detection rate of concatenation discontinuity by humans, and then we evaluate 13 different objective distance measures based on their ability to predict the human results. Criteria used to classify these distances include the detection rate, the Bhattacharyya measure of separability of two distributions, and receiver operating characteristic (ROC) curves. Results show that the Kullback-Leibler distance on power spectra has the higher detection rate followed by the Euclidean distance on Mel-frequency cepstral coefficients (MFCC).
Beowulf cluster design for scientific PDE models
Authors: B. McGarvey, R. Cicconetti, N. Bushyager, E. Dalton, M. Tentzeris
Venue: Proceedings of the 5th annual Linux Showcase & Conference - Volume 5 (2001)

This paper details some of the basic issues that arise when designing a Beowulf cluster for particular types of scientific simulations. The general problems of interest are partial differential equations (PDEs). These equations describe natural phenomenon and can be numerically solved. Finite differencing is used to solve the system of equations. This method naturally delineates the problem into four distinct categories based on the span of the data stencil used to update the next point: Independent, Nearest Neighbor, Quasi-Global, and Global. This delineation also relates the communication requirements between the independent processes. Other important factors include computation and memory requirements of the algorithm and particular problem. Design tradeoffs are presented with regards to algorithm development, communication architecture, and node configuration.
COTS Software Selection Process
Authors: Han Lin, Anh Lai, Rebecca Ullrich, Michal Kuca, Kelly McClelland, Jessica Shaffer-Gant, Sandra Pacheco, Karen Dalton, William Watkins
Venue: Proceedings of the Sixth International IEEE Conference on Commercial-off-the-Shelf (COTS)-Based Software Systems (2007)

Today's need for rapid software development has generated a great interest in employing Commercial- Off-The-Shelf (COTS) software products as a way of managing cost, developing time, and effort. With an abundance of COTS software packages to choose from, the problem now is how to systematically evaluate, rank, and select a COTS product that best meets the software project requirements and at the same time can leverage off the current corporate information technology architectural environment. This paper describes a systematic process for decision support in evaluating and ranking COTS software. Performed right after the requirement analysis phase, this process provides the evaluators with more concise, structural, and step-by-step activities for determining the best COTS software product with manageable risk. In addition, the process is presented in phases that are flexible to allow for customization or tailoring to meet various projects' requirements.
X-ray images enhancement using human visual system model properties and adaptive filters
Authors: M. M. Hadhoud
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 03 (2001)

This paper proposes the use of an adaptive image enhancement system that implements the human visual system (HVS) properties for contrast enhancement of X-ray images. X-ray images are of poor quality and are usually interpreted visually. The HVS properties considered are its adaptive nature, multichannel mechanism and high nonlinearity. The proposed method is adaptive, nonlinear and multichannel, and combines adaptive filters and homomorphic processing. Results presented illustrate the effectiveness of the proposed method.
Pruning Bio-Ontologies
Authors: Jong Woo Kim, Jordi Conesa Caralt, Julia K. Hilliard
Venue: Proceedings of the 40th Annual Hawaii International Conference on System Sciences (2007)

The explosive growth of biomedical data makes researchers and professionals recognize the need of developing large ontologies. However as the size of data increases and knowledge evolves, ontologies tend to grow big and large, and hence, retrieving manageable amount of information from large ontologies becomes a difficult and costly task. The purpose of this paper is to find and apply pruning methods from ontology engineering field to bio-ontologies as well as evaluate the results. These methods support systematic identification of relevant concepts and deletion of irrelevant part of an ontology. The paper shows how different pruning methods can be applied in bio-ontologies. To show the usefulness of pruning methods, a large bio-ontology called gene ontology is pruned to obtain a sub-ontology that contains only the relevant information a user is interested in.
The ARPA/NAVY Mountaintop Program: adaptive signal processing for airborne early warning radar
Authors: G. W. Titi
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 02 (1996)

The Mountaintop Program is an ARPA/NAVY sponsored initiative started in 1990 to study advanced processing techniques and technologies required to support the mission requirements of next generation airborne early warning (AEW) platforms. Central to the effort is a surveillance radar measurements program executed from various mountaintop locations including field sites at the White Sands Missile Range (WMSR), New Mexico and the Pacific Missile Range Facility (PMRF), Hawaii. The program is collecting data to support the evaluation of space-time adaptive processing (STAP) algorithms and the characterization and modeling of monostatic and bistatic scattering. Some of the data collected is hosted in CREST, the Common Research Environment for STAP, at the Maui High Performance Computing Center (MHPCC) and is accessible to the digital signal processing community via the World Wide Web. A subset of that data has been provided for inclusion in the IEEE Signal Processing Information Base at Rice University. This paper includes a discussion of program objectives and test segments and a description of the program's assets, field sites, and data product. A companion off-line demonstration of AEW signal processing concepts, using Mountaintop data available at the MHPCC, is planned.
WISDOM-II: a large in silico docking effort for finding novel hits against malaria using computational grid infrastructure
Authors: Vinod Kumar Kasam, Jean Salzemann, Vincent Breton, Nicolas Jacq
Venue: Proceedings of the 5th IEEE workshop on Challenges of large applications in distributed environments (2007)

After having deployed a first data challenge on malaria and a second one on avian flu, respectively in summer 2005 and spring 2006, we are demonstrating here again how efficiently the computational grids can be used to produce massive docking data at a high-throughput. During more than 2 months and a half, we have achieved at least 140 million dockings, representing an average throughput of almost 80,000 dockings per hour. This was made possible by the availability of thousands of CPUs through different infrastructures worldwide. Through the acquired experience, the WISDOM production environment is evolving to enable an easy and fault-tolerant deployment of biological tools; in this case it is the FlexX commercial docking software which is used to dock the whole ZINC database against 4 different targets.
Numerical approximation of Lévy-Feller diffusion equation and its probability interpretation
Authors: H. Zhang, F. Liu, V. Anh
Venue: Journal of Computational and Applied Mathematics (2007)

In this paper, we consider the Levy-Feller fractional diffusion equation, which is obtained from the standard diffusion equation by replacing the second-order space derivative with a Riesz-Feller derivative of order @a@?(0,2](@a
The cost of security in skeletal systems
Authors: M. Aldinucci, M. Danelutto
Venue: Proceedings of the 15th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (2007)

Skeletal systems exploit algorithmical skeletons technology to provide the user very high level, efficient parallel programming environments. They have been recently demonstrated to be suitable for highly distributed architectures, such as workstation clusters, networks and grids. However, when using skeletal system for grid programming care must be taken to secure data and code transfers across nondedicated, non-secure network links. In this work we take into account the cost of security introduction in muskel, a Java based skeletal system exploiting macro data flow implementation technology. We consider the adoption of mechanisms that allow securing all the communications taking place between remote, unreliable nodes and we evaluate the cost of such mechanisms. In particular, we consider the implications on the computational grains needed to scale secure and insecure skeletal computations.
Towards an Engineering Discipline of Computational Society
Authors: Ali Mili, Alex Vinokurov, Lamia Labed Jilani, Frederick T. Sheldon, Rahma Ben Ayed
Venue: Proceedings of the 40th Annual Hawaii International Conference on System Sciences (2007)

George Boole ushered the era of modern logic by arguing that logical reasoning does not fall in the realm of philosophy, as it was considered up to his time, but in the realm of mathematics. As such, logical propositions and logical arguments are modeled using algebraic structures. Likewise, we submit that security attributes must be modeled as formal mathematical propositions that are subject to mathematical analysis. In this paper, we approach this problem by attempting to model security attributes in a refinement-like framework that has traditionally been used to represent reliability and safety claims.
Generation of super-resolution images from blurred observations using Markov random fields
Authors: D. Rajan
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 03 (2001)

This paper presents a new technique for generating a high resolution image from a blurred image sequence; this is also referred to as super-resolution restoration of images. The image sequence consists of decimated, blurred and noisy versions of the high resolution image. The high resolution image is modeled as a Markov random field (MRF) and a maximum a posteriori (MAP) estimation technique is used. A simple gradient descent method is used to optimize the functional. Further, line fields are introduced in the cost function and optimization using Graduated Non-Convexity (GNC) is shown to yield improved results. Lastly, we present results of optimization using Simulated Annealing (SA).
The Emergence of Standards: A Meta-Analysis
Authors: Geerten van de Kaa, Henk Jan de Vries, Eric van Heck, Jan van den Ende
Venue: Proceedings of the 40th Annual Hawaii International Conference on System Sciences (2007)

This paper provides a list of factors that influence the outcome of standard battles. We have developed this list by performing a meta-analysis of 103 papers. An extensive literature study has revealed 31 factors which we have grouped under five categories: superior design, mechanisms, stakeholders, dominant agent, and strategy. We discuss the relations between the factors and we have applied the set of factors to an example of a standardization battle: the video case.
Bayesian estimation for multiscale image segmentation
Authors: S. Sista
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 06 (1999)

We present a solution to the problem of intensity image segmentation using Bayesian estimation in a multiscale set up. Our approach regards the number of regions, the data partition and the parameter vectors that describe the probability densities of the regions as unknowns. We compute their MAP estimates jointly by maximizing their joint posterior probability density given the data. Since the estimation of the number of regions is also included into the Bayesian formulation we have a fully automatic or unsupervised method of segmenting images. An important aspect of our formulation is to consider the data partition as a variable to be estimated. We provide a descent algorithm that starts with an arbitrary initial segmentation of the image when the number of regions is known and iteratively computes the MAP estimates of the data partition and the associated parameter vectors of the probability densities. Our method can incorporate any additional information about a region while assigning its probability density. It can also utilize any available training samples that arise from different regions.
Estimation of delay and Doppler by wavelet transform
Authors: K. C. Ho
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 06 (1996)

This paper studies the use of wavelet transform for delay and Doppler estimation between a sensor pair with relative motion between source and/or receivers. In passive sonar or radar estimation, the optimum wavelet is one of the receiver outputs and a method which scales the wavelet in discrete form is proposed. In active estimation, the maximum-likelihood (ML) estimator is shown to be equivalent to performing a wavelet transform of one of the receiving signals followed by a cross-correlation. The optimum wavelet in this case is equal to the weighting in the ML cost function. The wavelet approach combines noise filtering and scaling together, yielding a reduction in complexity. The proposed estimators were shown to approach the Cramer-Rao lower bound for delay and Doppler estimation.