ppxscal/embedding_network huggingface dataset:
Discontinuous Galerkin Spectral/hp Element Modelling of Dispersive Shallow Water Systems
Authors: C. Eskilsson, S. J. Sherwin
Venue: Journal of Scientific Computing (2005)

Two-dimensional shallow water systems are frequently used in engineering practice to model environmental flows. The benefit of these systems are that, by integration over the water depth, a two-dimensional system is obtained which approximates the full three-dimensional problem. Nevertheless, for most applications the need to propagate waves over many wavelengths means that the numerical solution of these equations remains particularly challenging. The requirement for an accurate discretization in geometrically complex domains makes the use of spectral/hp elements attractive. However, to allow for the possibility of discontinuous solutions the most natural formulation of the system is within a discontinuous Galerkin (DG) framework. In this paper we consider the unstructured spectral/hp DG formulation of (i) weakly nonlinear dispersive Boussinesq equations and (ii) nonlinear shallow water equations (a subset of the Boussinesq equations). Discretization of the Boussinesq equations involves resolving third order mixed derivatives. To efficiently handle these high order terms a new scalar formulation based on the divergence of the momentum equations is presented. Numerical computations illustrate the exponential convergence with regard to expansion order and finally, we simulate solitary wave solutions.
An implementation method of a location-based active map transformation system
Authors: Yoshihide Hosokawa, Naoki Kimura, Naohisa Takahashi
Venue: Proceedings of the 6th international conference on Mobile data management (2005)

A map is one of the most useful media in disseminating urgent location-based information (e.g., information on urgent events like congestion, accidents, fire, or sales within a limited time). However, it is generally difficult to recognize the geographical features of urgent information by utilizing maps in mobile computing environments, because there is no technology that automatically focuses on areas within the small display frame of the mobile tool being used.In this paper, we present an implementation method of a location-based active map transformation system that automatically focuses on areas in the display frame according to urgent location-based information being transmitted. Its main feature is that it pulls urgent information into the frame while maintaining the quality of the geographical information being represented. The new strategy reduces the number of new objects in the display frame and the number of objects deleted from it. As a result, it provides a map mobile users can understand.We clarify the feasibility and effectiveness of this method through several experiments.
A Bayesian Hierarchical Model for Learning Natural Scene Categories
Authors: Fei-Fei Li, Pietro Perona
Venue: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02 (2005)

We propose a novel approach to learn and recognize natural scene categories. Unlike previous work [9, 17], it does not require experts to annotate the training set. We represent the image of a scene by a collection of local regions, denoted as codewords obtained by unsupervised learning. Each region is represented as part of a "theme". In previous work, such themes were learnt from hand-annotations of experts, while our method learns the theme distributions as well as the codewords distribution over the themes without supervision. We report satisfactory categorization performances on a large set of 13 categories of complex scenes.
Probabilistic Classification Based Image Regions Labeling
Authors: Min Zhang, Yunde Jia
Venue: Proceedings of the Third International Conference on Image and Graphics (2004)

Image regions labeling is a crucial step of the scene understanding. In this paper we propose an approach that can solve the image regions labeling problem under Bayesian probabilistic framework. In our approach, we first extract the efficient low-level visual features from segmented image regions. Then we represent the knowledge of each label class as a Gaussian mixture model of image region features, and describe the relationship between different region label classes using likelihood function. Finally, the label of each image region is determined by probabilistic classification. The proposed approach is evaluated on the outdoor scene images and the overall recognition accuracy is over 86%.
Context-aware collaborative filtering system: predicting the user's preferences in ubiquitous computing
Authors: Annie Chen
Venue: CHI '05 extended abstracts on Human factors in computing systems (2005)

In this paper I propose a context-aware collaborative filtering system that can predict a user's preference in different context situations based on past user-experiences. The system uses what other like-minded users have done in similar context to predict a user's preference towards an item in the current context.
Parametric polymorphism for Java: is there any hope in sight?
Authors: Brian Cabana, Suad Alagić, Jeff Faulkner
Venue: ACM SIGPLAN Notices (2004)

In spite of years of research toward a solution for the problem of extending Java with parametric polymorphism (genericity) the officially accepted solution already in its beta release allows violation of the Java type system and turns a type safe language into an unsafe one. The run-time type information in this release is incorrect which leads to major problems for the programmers relying on the Java reflective capabilities. We show that there are two basic reasons for these problems. The first one is that the idiom underlying this solution is provably incorrect. The second one is that the problem of extending Java with parametric polymorphism does not have a correct solution unless the Java Virtual Machine is extended to handle it properly. This paper elaborates the subtleties required by a correct implementation technique that includes representation of parametric classes in the standard Java class file format, representation of the instantiated parametric class objects, extensions of the Java Core Reflection to report type information about (instantiated) parametric classes, and the loading techniques required by this solution for extending Java with generics. Previous solutions for this problem are analyzed as well.
A Cost-Effective Main Memory Organization for Future Servers
Authors: Magnus Ekman, Per Stenstrom
Venue: Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Papers - Volume 01 (2005)

Today, the amount of main memory in mid-range servers is pushing practical limits with as much as 192 GB memory in a 24 processor system. Further, with the onset of multi-threaded, multi-core processor chips, it is likely that the number of memory chips per processor chip will start to increase, making DRAM cost and size an even larger burden. We investigate in this paper an alternative main memory organization - a two-level noninclusive memory hierarchy - where the second level is substantially slower than the first level, with the aim of reducing total system cost and spatial requirements of servers of today and the future. We quantitatively investigate how big and how slow the second level can be. Surprisingly, we find that only 30% of the entire memory resources typically needed must be accessed at DRAM speed whereas the rest can be accessed at a speed that is an order of magnitude slower with a negligible (1.2% on average) performance impact. We also present a cost-effective implementation of how to manage such a hierarchy and how it can bring down memory cost by leveraging memory compression and sharing of memory resources among servers.
Functionally based augmented sculpting: Research Articles
Authors: Valery Adzhiev, Peter Comninos, Maxim Kazakov, Alexander Pasko
Venue: Computer Animation and Virtual Worlds (2005)

In this paper we describe an approach to computer-aided sculpting concerned with the creation and modification of digital models based on physical abstract sculptures. We begin by presenting a survey of current methods for the creation of computer-aided sculptured artefacts. Then we proceed to present some original methods and tools based on the function representation of geometric models. We introduce a specialized computer language, named HyperFun, which facilitates the modelling of complex objects. As well as presenting computer-generated animated models of pre-existing sculptures by Russian artist Igor Seleznev, we also show how some interesting novel shapes can be generated using the HyperFun system. Finally we outline two advanced projects concerned with creating a sculpture-based augmented reality which allows for the interactive participation of the observer. In this paper, we present experimental results, which hopefully have some artistic appeal. These results were produced by an international team of researchers and students collaborating through the Internet. Copyright &copy; 2005 John Wiley & Sons, Ltd.
Geometric programming for circuit optimization
Authors: Stephen P. Boyd, Seung Jean Kim
Venue: Proceedings of the 2005 international symposium on Physical design (2005)

This tutorial concerns a method for solving a variety of circuit sizing and optimization problems, which is based on formulating the problem as a geometric program (GP), or a generalized geometric program (GGP). These nonlinear, constrained optimization problems can be transformed to convex optimization problems, and then solved (globally) very efficiently.
Interactive Graph Cut Based Segmentation with Shape Priors
Authors: Daniel Freedman, Tao Zhang
Venue: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01 (2005)

Interactive or semi-automatic segmentation is a useful alternative to pure automatic segmentation in many applications. While automatic segmentation can be very challenging, a small amount of user input can often resolve ambiguous decisions on the part of the algorithm. In this work, we devise a graph cut algorithm for interactive segmentation which incorporates shape priors. While traditional graph cut approaches to interactive segmentation are often quite successful, they may fail in cases where there are diffuse edges, or multiple similar objects in close proximity to one another. Incorporation of shape priors within this framework mitigates these problems. Positive results on both medical and natural images are demonstrated.
Book review: Annual Review of Computer Science Volume 1, 1986. Edited by Joseph Traub, Barbara J. Gresz, Butler Lampson, and Nils J. Nilsson (Annual Reviews, Inc.)
Venue: Issue 101 (July 1987) (1987)

Volume 1 of the Annual Review of Computer Science is the first in a series of annual publications by Annual Reviews, Inc. Intended to review the state of the art in computer science through a collection of review articles. This series represents the 27th such series by Annual Reviews (starting with the Annual Review of Biochemistry in 1932.) 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
Adaptive Wavelet Methods for Linear-Quadratic Elliptic Control Problems: Convergence Rates
Authors: Wolfgang Dahmen, Angela Kunoth
Venue: SIAM Journal on Control and Optimization (2005)

We propose an adaptive algorithm based on wavelets for the fast numerical solution of control problems governed by elliptic boundary value problems with distributed or Neumann boundary control. A quadratic cost functional that may involve fractional Sobolev norms of the state and the control is to be minimized subject to linear constraints in weak form. Placing the problem into the framework of (biorthogonal) wavelets allows us to formulate the functional and the constraints equivalently in terms of $\ell_2$-norms of wavelet expansion coefficients and constraints in the form of an $\ell_2$ automorphism. The resulting first order necessary conditions are then derived as a (still infinite) system in $\ell_2$. Applying the machinery developed in [A. Cohen, W. Dahmen, and R. DeVore, Math. Comp., 70 (2001), pp. 27--75; A. Cohen, W. Dahmen, and R. DeVore, Found. Comput. Math., 2 (2002), pp. 203--245], we propose an adaptive method which can be interpreted as an inexact gradient descent method, where in each iteration step the primal and the adjoint system need to be solved up to a prescribed accuracy. Convergence of the adaptive algorithm is proved. In addition, we show that the adaptive algorithm is asymptotically optimal, that is, the convergence rate achieved for computing the solution up to a desired target tolerance is asymptotically the same as the wavelet-best N-term approximation of the solution, and the total computational work is proportional to the number of computational unknowns.
On the effect of user mobility and density on the performance of protocols for ad-hoc mobile networks: Research Articles
Authors: Ioannis Chatzigiannakis, Elena Kaltsa, Sotiris E. Nikoletseas
Venue: Wireless Communications Mobile Computing (2004)

In this paper, we demonstrate the significant impact of (a) the mobility rate and (b) the user density on the performance of routing protocols in ad-hoc mobile networks. In particular, we study the effect of these parameters on two different approaches for designing routing protocols: (a) the route creation and maintenance approach and (b) the &lsquo;support&rsquo; approach that forces few hosts to move, acting as &lsquo;helpers&rsquo; for message delivery. We study one representative protocol for each approach, i.e. AODV for the first approach and RUNNERS for the second. We have implemented the two protocols and performed a large scale and detailed simulation study of their performance. The main findings are: the AODV protocol behaves well in networks of high user density and low mobility rate, while its performance drops for sparse networks of highly mobile users. On the other hand, the RUNNERS protocol seems to tolerate well (and in fact benefit from) high mobility rates and low densities. Copyright &copy; 2004 John Wiley & Sons, Ltd.
Resource-oriented software quality classification models
Authors: Taghi M. Khoshgoftaar, Naeem Seliya, Angela Herzberg
Venue: Journal of Systems and Software (2005)

Developing high-quality software within the allotted time and budget is a key element for a productive and successful software project. Software quality classification models that provide a risk-based quality estimation, such as fault-prone (fp) and not fault-prone (nfp), have proven their usefulness as software quality assurance techniques. However, their usefulness is largely dependent on the availability of resources for deploying quality improvements to modules predicted as fp. Since every project has its own special needs and specifications, we feel a classification modeling approach based on resource availability is greatly warranted.We propose and demonstrate the use of a resource-based measure, i.e., "Modified Expected Cost of Misclassification" (MECM), for selecting and evaluating classification models. It is an extension of the "Expected Cost of Misclassification" (ECM) measure, which we have previously applied for model-evaluation purposes. The proposed measure facilitates building resource-oriented classification models and overcomes the limitation of ECM, which assumes that enough resources are available to enhance all modules predicted as fp. The primary aspect of MECM is that it penalizes a model, in terms of costs of misclassifications, if the model predicts more number of fp modules than the number that can be enhanced with the available resources. Based on the resources available for improving quality of software modules, a practitioner can use the proposed methodology to select a model that bestsuits the projects goals. Hence, the best possible and practical usage of the available resources can be achieved. The application, analysis, and benefits of MECM is shown by developing models using Logistic Regression. It is concluded that the use of MECM is a promising approach for practical software quality improvement.
A Unified Framework for Monitoring Data Streams in Real Time
Authors: Ahmet Bulut, Ambuj K. Singh
Venue: Proceedings of the 21st International Conference on Data Engineering (2005)

Online monitoring of data streams poses a challenge in many data-centric applications, such as telecommunications networks, traffic management, trend-related analysis, web-click streams, intrusion detection, and sensor networks. Mining techniques employed in these applications have to beefficient in terms of space usage and per-item processing time while providing a high quality of answers to (1) aggregate monitoring queries, such as finding surprising levels of a data stream, detecting bursts, and to (2) similarity queries, such as detecting correlations and finding interesting patterns. The most important aspect of these tasks is their need for flexible query lengths, i.e., it is difficult to set the appropriate lengths a priori. For example, bursts of events can occur at variable temporal modalities from hours to days to weeks. Correlated trends can occur at various temporal scales. The system has to discover "interesting" behavior online and monitor over flexible window sizes. In this paper, we propose a multi-resolution indexing scheme, which handles variable length queries efficiently. We demonstrate the effectiveness of our framework over existing techniques through an extensive set of experiments.
Reducing misspeculation overhead for module-level speculative execution
Authors: Fredrik Warg, Per Stenstrom
Venue: Proceedings of the 2nd conference on Computing frontiers (2005)

Thread-level speculative execution is a technique that makes it possible for a wider range of single-threaded applications to make use of the processing resources in a chip multiprocessor.We consider module-level speculation, i.e., speculative threads executing the code after a module (i.e., a procedure, function, or method) call. Unfortunately, previous studies have shown that indiscriminate module-level speculation results in significant overheads, mainly due to frequent misspeculations. In addition to hurting performance, excessive overhead is harmful from a resource usage and energy efficiency standpoint. We show that the overhead when spawning speculative threads for all module continuations is on average three times as big as the time spent on useful execution on our baseline 8-way chip multiprocessorIn this paper, we present and make a detailed evaluation of a technique that aims at reducing the overhead associated with misspeculations. History-based prediction is used in an attempt to prevent speculative threads from being spawned when they are expected to cause misspeculations. We find that the overhead can be reduced with a factor of six on average compared to indiscriminate speculation. The impact on speedup is small for most applications, but in several cases speedup is slightly improved.
Local Discriminant Embedding and Its Variants
Authors: Hwann-Tzong Chen, Huang-Wei Chang, Tyng-Luh Liu
Venue: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02 (2005)

We present a new approach, called local discriminant embedding (LDE), to manifold learning and pattern classification. In our framework, the neighbor and class relations of data are used to construct the embedding for classification problems. The proposed algorithm learns the embedding for the submanifold of each class by solving an optimization problem. After being embedded into a low-dimensional subspace, data points of the same class maintain their intrinsic neighbor relations, whereas neighboring points of different classes no longer stick to one another. Via embedding, new test data are thus more reliably classified by the nearest neighbor rule, owing to the locally discriminating nature. We also describe two useful variants: two-dimensional LDE and kernel LDE. Comprehensive comparisons and extensive experiments on face recognition are included to demonstrate the effectiveness of our method.
Book Reviews
Authors: Benjamin Lev
Venue: Interfaces (2005)

The range of books reviewed is wide, covering theory and applications in operations research, statistics, management science, econometrics, mathematics, computers, and information systems (no software is reviewed). In addition, we include books in other fields that emphasize technical applications. Publishers who wish to have their books reviewed should send them to Professor Benjamin Lev. We list the books received; not all books received can be reviewed because space is limited. Those who would like to review books are urged to send me their names, addresses, and specific areas of expertise. We commission all reviews and do not accept unsolicited book reviews. Readers are encouraged to suggest books that might be reviewed or to ask publishers to send me copies of such books.The authors or editors of the books reviewed in this issue are Emile Aarts and Jan Karel Lenstra; Rommert Dekker, Moritz Fleischmann, Karl Inderfurth, and Luk N. Van Wassenhove; Gianpaolo Ghiani, Gilbert Laporte, and Roberto Musmanno; Nikitas-Spiros Koutsoukis and Gautam Mitra; and Panos M. Pardalos and Victor Korotkikh.
Cyclic knowledge management system in e-governance: a case study of evaluating polls on referendum-independence of quebec using ANN
Authors: Manzur Ashraf, Humayra Binte Ali, Md. Mahfuz Ashraf
Venue: Proceedings of the 2005 ACM SIGMIS CPR conference on Computer personnel research (2005)

E-Governance brings urban and rural together and breaks the barrier of distance to lead an efficient administration. Surprisingly, E-Governance have not made enough impact on the people as e-Commerce and e-Learning have done. From the software engineering point of view, E-Governance has a lot of characteristics, which are different from e-Commerce and e-Learning. It is enough for e-Commerce and e-Learning to be reactive whereas E-Governance needs to be proactive. While e-Commerce and e-Learning involve Information Management, E-Governance involves Knowledge Management (KM). Knowledge management is the management of information, skill, experience, innovation, and intelligence. Our model of E-Governance based on Knowledge Management System (KMS) is built on KM cycle of Knowledge capturing, Knowledge sharing, Knowledge enhancing, and Knowledge preserving. A few popular models of E-Governance use a concept of "knowledge centers" to share knowledge. Our model shares knowledge that supports the law of knowledge dynamics. The development model of E-Governance based on Information Management System (IMS) applies a cycle-based process such as spiral or iterative process. This paper studies a development model of KMS-based E-Governance, which is path-based. This model provides an environment where the system grows with the people. To simulate the proposed KMS model, we analyzed a scenario based on the poll on Referendum question of Quebec, CA regarding independence (unilateral action or negotiation) using Artificial Neural Network.
Applications of **-Matrix Techniques in Micromagnetics
Authors: N. Popovi&#x0107;, D. Praetorius
Venue: Computing (2005)

The variational model by Landau and Lifshitz is frequently used in the simulation of stationary micromagnetic phenomena. We consider the limit case of large and soft magnetic bodies, treating the associated Maxwell equation exactly via an integral operator **. In numerical simulations of the resulting minimization problem, difficulties arise due to the imposed side-constraint and the unboundedness of the domain. We introduce a possible discretization by a penalization strategy. Here the computation of ** is numerically the most challenging issue, as it leads to densely populated matrices. We show how an efficient treatment of both ** and the corresponding bilinear form can be achieved by application of **-matrix techniques.