ppxscal/embedding_network huggingface dataset:
Morphological analysis of the spontaneous speech corpus
Authors: Kiyotaka Uchimoto, Chikashi Nobata, Atsushi Yamada, Hitoshi Isahara, Satoshi Sekine
Venue: Proceedings of the 19th international conference on Computational linguistics - Volume 2 (2002)

This paper describes a project tagging a spontaneous speech corpus with morphological information such as word segmentation and parts-of-speech. We use a morphological analysis system based on a maximum entropy model, which is independent of the domain of corpora. In this paper we show the tagging accuracy achieved by using the model and discuss problems in tagging the spontaneous speech corpus. We also show that a dictionary developed for a corpus on a certain domain is helpful for improving accuracy in analyzing a corpus on another domain.
The AFWL hull code codes for large problems: fluid dynamics (abstract)
Authors: Daniel A. Matuska, Charles E. Needham, Richard E. Durrett
Venue: ACM SIGNUM Newsletter (1975)

The Air Force Weapons Laboratory (AFWL) has maintained a strong interest in large scale fluid dynamics problems since its establishment some ten years ago. Typically, these problems have a spatial extent which changes by several orders of magnitude between the initial conditions and the solution of interest. Time variations of orders of magnitude are also possible. In any case the large scale fluid dynamics problems solved by AFWL may be defined as those in which the smallest lineal resolution desired is less than one percent of the total dimension of interest. A large number of problems fit into this category in two and three dimensions. The AFWL has developed a system of solution for such problems which is easy to use, adaptable to many different problems and computers, and, most importantly, extremely accurate. This system is represented by the HULL code. The basic part of the code is a second order accurate, multi-dimensional Eulerian hydrodynamic code. The differencing method was developed by Capt D. Matuska at AFWL and is itself unique.
Linear vs. nonlinear algorithms for linear problems
Authors: Jakob Creutzig, P. Wojtaszczyk
Venue: Journal of Complexity (2004)

We compare linear and non-linear approximations for linear problems. Let X be a linear space and Y a normed space. Let S : X → Y and N : X → Rn be linear mappings and consider the worst-case setting over some balanced convex set F ⊆ X. We compare the minimal error errlin (S, N) achievable by linear algorithms processing N with the minimal error errlin(S, N) achievable by arbitrary algorithms using N. For bounded linear problems, P. Mathé showed that infN errlin(S, N) ≤ (1 + n1/2) ċ infN err(S, N), where the infimum is taken over all bounded linear mappings N : X → Rn. We generalize this result as follows: If the target space Y is complete, then for any linear N : X → Rn. we have errlin(S, N, F) ≤ (1 +n1/2)err(S, N, F). This and some similar results can easily be derived from a general relation of this problem to extension properties of normed spaces, and the manifold and powerful results available for this problem. This allows a unified treatment of the above estimate together with the results of Smolyak and Packel, who showed that linear algorithms are optimal for some Y. The results are also partially extended to noisy information with uniformly bounded noise.
A Sparse Support Vector Machine Approach to Region-Based Image Categorization
Authors: Jinbo Bi, Yixin Chen, James Z. Wang
Venue: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01 (2005)

Automatic image categorization using low-level features is a challenging research topic in computer vision. In this paper, we formulate the image categorization problem as a multiple-instance learning (MIL) problem by viewing an image as a bag of instances, each corresponding to a region obtained from image segmentation. We propose a new solution to the resulting MIL problem. Unlike many existing MIL approaches that rely on the diverse density framework, our approach performs an effective feature mapping through a chosen metric distance function. Thus the MIL problem becomes solvable by a regular classification algorithm. Sparse SVM is adopted to dramatically reduce the regions that are needed to classify images. The selected regions by a sparse SVM approximate to the target concepts in the traditional diverse density framework. The proposed approach is a lot more efficient in computation and less sensitive to the class label uncertainty. Experimental results are included to demonstrate the effectiveness and robustness of the proposed method.
Four-dimensional variational data assimilation for Doppler radar wind data
Authors: Fathalla A. Rihan, Chris G. Collier, Ian Roulstone
Venue: Journal of Computational and Applied Mathematics (2005)

All forecast models, whether they represent the state of the weather, the spread of a disease, or levels of economic activity, contain unknown parameters. These parameters may be the model's initial conditions, its boundary conditions, or other tunable parameters which have to be determined. Four dimensional variational data assimilation (4D-Var) is a method of estimating this set of parameters by optimizing the fit between the solution of the model and a set of observations which the model is meant to predict.Although the method of 4D-Var described in this paper is not restricted to any particular system, the application described here has a numerical weather prediction (NWP) model at its core, and the parameters to be determined are the initial conditions of the model.The purpose of this paper is to give a review covering assimilation of Doppler radar wind data into a NWP model. Some associated problems, such as sensitivity to small variations in the initial conditions or due to small changes in the background variables, and biases due to nonlinearity are also studied.
A class of high performance Maekawa-type algorithms for distributed systems under heavy demand
Authors: Roberto Baldoni, Bruno Ciciani
Venue: Distributed Computing (1995)

Distributed Mutual Exclusion algorithms have been mainly compared using the number of messages exchanged per critical section execution. In such algorithms, no attention has been paid to the serialization order of the requests. Indeed, they adopt FCFS discipline. Conversely, the insertion of priority serialization disciplines, such as Short-Job-First, Head-Of-Line, Shortest-Remaining-Job-First etc., can be useful in many applications to optimize some performance indices. However, such priority disciplines are prone to starvation. The goal of this paper is to investigate and evaluate the impact of the insertion of a priority discipline in Maekawa-type algorithms. Priority serialization disciplines will be inserted by means of a gated batch mechanism which avoids starvation. In a distributed algorithm, such a mechanism needs synchronizations among the processes. In order to highlight the usefulness of the priority based serialization discipline, we show how it can be used to improve the average response time compared to the FCFS discipline. The gated batch approach exhibits other advantages: algorithms are inherently deadlock-free and messages do not need to piggyback timestamps. We also show that, under heavy demand, algorithms using gated batch exchange less messages than Maekawa-type algorithms per critical section execution.
Three novel pigmentation mutants generated by genome-wide random ENU mutagenesis in the mouse: Short Communications
Authors: Vicky Tsipouri, John A. Curtin, Pat M. Nolan, Lucie Vizor, Claire A. Parsons, Colin M. Clapham, Ian D. Latham, Lesley J. Rooke, Jo E. Martin, Jo Peters, A. Jackie Hunter, Derek Rogers, Sohaila Rastan, Steve D. M. Brown, Elizabeth M. C. Fisher, Nigel K. Spurr, Ian C. Gray
Venue: Comparative and Functional Genomics (2004)

Three mutant mice with pigmentation phenotypes were recovered from a genome-wide random mouse chemical mutagenesis study. White toes (Whto; MGI:1861986), Belly spot and white toes (Bswt; MGI:2152776) and Dark footpads 2 (Dfp2; MGI:1861991) were identified following visual inspection of progeny from a male exposed to the point mutagen ethylnitrosourea (ENU). In order to rapidly localize the causative mutations, genome-wide linkage scans were performed on pooled DNA samples from backcross animals for each mutant line. Whto was mapped to proximal mouse chromosome (Mmu) 7 between Cen (the centromere) and D7Mit112 (8.0 cM from the centromere), Bswt was mapped to centric Mmul between D1Mit214 (32.1 cM) and D1Mit480 (32.8 cM) and Dfp2 was mapped to proximal Mmu4 between Cen and D4Mit18 (5.2 cM). Whto, Bswt and Dfp2 may provide novel starting points in furthering the elucidation of genetic and biochemical pathways relevant to pigmentation and associated biological processes. Copyright &copy; 2004 John Wiley & Sons, Ltd.
Gabor Wavelets Transform and Extended Nearest Feature Space Classifier for Face Recognition
Authors: Jianke Zhu, Mang I. Vai, Peng Un Mak
Venue: Proceedings of the Third International Conference on Image and Graphics (2004)

This paper proposes new hybrid approaches for face recognition. Gabor wavelets representation of face images is an effective approach for both facial action recognition and face identification. Perform dimensionality reduction and linear discriminant analysis on the down-sampled Gabor waveletfaces can increase the discriminant ability. Nearest feature space is extended to various similarity measures. In our experiments, proposed Gabor wavelet-faces combined with extended nearest feature space classifier shows very good performance, which can achieve 99 % maximum correct recognition rate on ORL data set without any preprocessing step.
Adversarial models for priority-based networks
Authors: C. Àlvarez, M. Blesa, J. Díaz, M. Serna, A. Fernández
Venue: Networks (2005)

In this article, we propose several variations of the adversarial queueing model and address stability issues of networks and protocols in those proposed models. The first such variation is the priority model, which is directed at static network topologies and takes into account the case in which packets can have different priorities. Those priorities are assigned by an adversary at injection time. A second variation, the variable priority model, is an extension of the priority model in which the adversary may dynamically change the priority of packets at each time step. Two more variations, namely the failure model and the reliable model, are proposed to cope with dynamic networks. In the failure and reliable models the adversary controls, under different constraints, the failures that the links of the topology might suffer. Concerning stability of networks in the proposed adversarial models, we show that the set of universally stable networks in the adversarial model remains the same in the priority, variable priority, failure, and reliable models. From the point of view of protocols &lpar;or queueing policies&rpar;, we show that several protocols that are universally stable in the adversarial queueing model remain so in the priority, failure, and reliable models. However, we show that the longest-in-system &lpar;LIS&rpar; protocol, which is universally stable in the adversarial queueing model, is not universally stable in any of the other models we propose. Moreover, we show that no queueing policy is universally stable in the variable priority model. Finally, we analyze the problem of deciding stability of a given network under a fixed protocol. We provide a characterization of the networks that are stable under first-in-first-out &lpar;FIFO&rpar; and LIS in the failure model &lpar;and therefore in the reliable and priority models&rpar;. This characterization allows us to show that the stability problem under FIFO and LIS in the failure model can be solved in polynomial time. &copy; 2004 Wiley Periodicals, Inc. NETWORKS, Vol. 45&lpar;1&rpar;, 23&ndash;35 2005Part of this work was presented in 28th International Symposium on Mathematical Foundations of Computer Science, Bratislava, Slovakia, 2003. LNCS 2747:142&ndash;151, Springer.
System Support to Balance the Resource Supply and Demand in High-end Computing
Authors: Xiaodong Zhang
Venue: Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 10 - Volume 11 (2005)

Modern and large scale high-end systems built by commercial processors can easily provide unbalanced computing resources with over-supplied CPU cycles and increasingly long latency of data accesses at different levels of the memory hierarchy for high demands of data-intensive applications. The imbalance is mainly caused by two technology changes. First, the speed gap between the CPU and the memory and the I/O storage continues to grow. Second, the latency improvement significantly lags behind the bandwidth improvement in any pair connection of the computer systems. We are working on three research projects to cope with the imbalance problem. (1) We develop models to characterize the increasingly complex and deep memory hierarchy, providing critical insights and guidance for high-end systems design. (2) We develop several memory-centric load-sharing schemes and their implementations for high end-systems management. (3) We develop efficient locality-aware caching algorithms and their system implementations for virtual memory and buffer cache management. This paper briefly report the background, motivation, and working progress of our research funded by the NSF NGS program.
Parallel File System Testing for the Lunatic Fringe: The Care and Feeding of Restless I/O Power Users
Authors: Richard Hedges, Bill Loewe, Tyce McLarty, Chris Morrone
Venue: Proceedings of the 22nd IEEE / 13th NASA Goddard Conference on Mass Storage Systems and Technologies (2005)

Over the last several years there has been a major thrust at the Lawrence Livermore National Laboratory toward building extremely large scale computing clusters based on open source software and commodity hardware. On the storage front, our efforts have focused upon the development of the Lustre file system and bringing it into production in our computer center. Given our customers' requirements, it is assured that we will be living on the bleeding edge with this file system software as we press it into production. A further reality is that our partners are not able to duplicate the scale of systems as required for these testing purposes. For these practical reasons, the onus for file system testing at scale has fallen largely upon us. As an integral part of our testing efforts, we have developed programs for stress and performance testing of parallel file systems. This paper focuses on these unique test programs and upon how we apply them to understand the usage and failure modes of such large-scale parallel file systems.
A method of estimation of magnetic resonance spectroscopy using complex-valued neural networks
Authors: Naoyuki Morita, Osamu Konishi
Venue: Systems and Computers in Japan (2004)

MRS (magnetic resonance spectroscopy) consists of collecting the nuclear magnetic resonance (NMR) spectrum of the metabolites in the living body and estimating it. In the field of MRS, we usually get an NMR spectrum by applying the Fourier transform to the real part of the NMR signal [free induction decay (FID) signal], which is a complex-valued signal. We must then measure the area of the spectral peak to estimate metabolites in the living body from the spectrum. A curve fitting technique is used for that measurement. However, this technique is not suitable for large quantities of data processing, because human intervention is necessary and is laborious. For this reason, an automatic method of estimating an NMR spectrum is required in the field of MRS. In this paper, we propose a method of estimation of an NMR spectrum by using a Hopfield complex-valued neural network and try to estimate the spectrum automatically. In addition, we consider damping state of the NMR signal and devise a method called sequential extension of section (SES). It is shown that the estimation precision of the spectrum improves when SES is used. Furthermore, SES is found to reduce the local minimum problem in Hopfield neural networks. &copy; 2004 Wiley Periodicals, Inc. Syst Comp Jpn, 35(10): 14&ndash;22, 2004; Published online in Wiley InterScience (). DOI 10.1002&sol;scj.10705
Head Pose Estimation of Partially Occluded Faces
Authors: Markus T. Wenzel, Wolfram H. Schiffmann
Venue: Proceedings of the 2nd Canadian conference on Computer and Robot Vision (2005)

This paper describes an algorithm which calculates the approximate head pose of partially occluded faces without training or manual initialization. The presented approach works on low-resolution webcam images. The algorithm is based on the observation that for small depth rotations of a head the rotation angles can be approximated linearly. It uses the CamShift (Continuous adaptive Mean Shift) algorithm to track the users head. With a pyramidal implementation of an iterative Lucas-Kanade optical flow algorithm, a certain feature point in the face is tracked. Pan and tilt of the head are estimated from the shift of the feature point relative to the center of the head. 3D Position and roll are estimated from the CamShift results.
Virtual laboratory as a tool to increace student's research work
Authors: Ivan Pankov, Evelina Karaminkova
Venue: Proceedings of the 5th international conference on Computer systems and technologies (2004)

The use of virtual educational research laboratories is necessitated for the following reasons:&bull; The classical laboratories are equipped with expensive apparatuses and require highly skilled research teams, and that leads to their restricted use in technical colleges and high schools.&bull; The substantial financial investment, which is not readily available to professional education, reflects also on the tutorial documentation (plans and programs), corresponding to the technique and the technologies of the obsolete material equipment.
Modeling Internet Traffic Using Nongaussian Time Series Models
Authors: Z. Liu, J. Almhana, V. Choulakian, R. McGorman
Venue: Proceedings of the 3rd Annual Communication Networks and Services Research Conference (2005)

Internet traffic is usually represented by a time series of number of packets or number of bits received in each time slot. There exists a class of Internet traffic traces that have slowly decreasing autocorrelation, their marginal distributions of the number of packets are fit by negative binomial distributions and the time series of number of bits are fit by Gamma distributions. To model this class of traffic, this paper divides the traffic input stream into several sub-streams by decomposing thier autocorrelation functions, and models each substream as a negative binomial time series or a Gamma time series. The proposed models can simultaneously capture the autocorrelation and the marginal distribution. A queue performance criterion is used to validate the models.
The Poisson equation in axisymmetric domains with conical points
Authors: Boniface Nkemzi
Venue: Journal of Computational and Applied Mathematics (2005)

This paper analyzes the effects of conical points on the rotation axis of axisymmetric domains Ω ⊂ R3 on the regularity of the Fourier coefficients un (n ∈ Z) of the solution u of the Dirichlet problem for the Poisson equation -Δu = f in Ω. The asymptotic behavior of the coefficients un, near the conical points is carefully described and for f ∈ L2(Ω), it is proved that if the interior opening angle θc at the conical point is greater than a certain critical angle θ*, then the regularity of the coefficient u0 will be lower than expected. Moreover, it is shown that conical points on the rotation axis of the axisymmetric domain do not affect the regularity of the coefficients un, n ≠ 0. An approximation of the critical angle θ* is established numerically and a priori error estimate for the Fourier-finite-element solutions in the norm of W21 (Ω) is given.
Sound methods and effective tools for model-based security engineering with UML
Authors: Jan Jürjens
Venue: Proceedings of the 27th international conference on Software engineering (2005)

Developing security-critical systems is difficult and there are many well-known examples of security weaknesses exploited in practice. Thus a sound methodology supporting secure systems development is urgently needed.We present an extensible verification framework for verifying UML models for security requirements. In particular, it includes various plugins performing different security analyses on models of the security extension UMLsec of UML. Here, we concentrate on an automated theorem prover binding to verify security properties of UMLsec models which make use of cryptography (such as cryptographic protocols). The work aims to contribute towards usage of UML for secure systems development in practice by offering automated analysis routines connected to popular CASE tools. We present an example of such an application where our approach found and corrected several serious design flaws in an industrial biometric authentication system.
Splinoid interpolation on finite posets
Authors: Tomislav Došlić, Douglas J. Klein
Venue: Journal of Computational and Applied Mathematics (2005)

The problem of interpolating data on the discrete nodes of a partially ordered set is considered. A solution in terms of a sort of cubic spline is described, as well as an application to test "robustness" on a chemically relevant substitution-reaction poset.
Digital Modulator with Bandpass Delta-Sigma Modulator
Authors: Johan Sommarek, Jouko Vankka, Jaakko Ketola, Jonne Lindeberg, Kari Halonen
Venue: Analog Integrated Circuits and Signal Processing (2005)

A digital quadrature modulator with a bandpass ¿¿-modulator is presented that interpolates orthogonal input carriers by 16 and performs a digital quadrature modulation at carrier frequencies fs/4, ¿fs/4 (fs is the sampling frequency). After quadrature modulation, the signal is converted into an analogue IF signal using a bandpass ¿¿ modulator and a 1-bit D/A converter. The die area of the chip is 5.2 mm2 (0.13 ¿m CMOS technology). The total power consumption is 139 mW at 1.5 V with a clock frequency of 700 MHz (D/A converter full-scale output current 11.5 mA).
Object Class Recognition by Boosting a Part-Based Model
Authors: Aharon Bar-Hillel, Tomer Hertz, Daphna Weinshall
Venue: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01 (2005)

We propose a new technique for object class recognition, which learns a generative appearance model in a discriminative manner. The technique is based on the intermediate representation of an image as a set of patches, which are extracted using an interest point detector. The learning problem becomes an instance of supervised learning from sets of unordered features. In order to solve this problem, we designed a classifier based on a simple, part based, generative object model. Only the appearance of each part is modeled. When learning the model parameters, we use a discriminative boosting algorithm which minimizes the loss of the training error directly. The models thus learnt have clear probabilistic semantics, and also maintain good classification performance. The performance of the algorithm has been tested using publicly available benchmark data, and shown to be comparable to other state of the art algorithms for this task; our main advantage in these comparisons is speed (order of magnitudes faster) and scalability.