ppxscal/embedding_network huggingface dataset:
Dictionary-based decomposition of linear mixtures of Gaussian processes
Authors: C. Couvreur
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 05 (1996)

We consider the problem of detecting and classifying an unknown number of multiple simultaneous Gaussian processes with unknown variances given a finite length observation of their sum and a dictionary of candidate models for the signals. The optimal minimum description length (MDL) detector is presented. Asymptotic and quadratic approximations of the MDL criterion are derived, and regularization algorithms for their efficient implementation are described. The performance of the algorithms is illustrated by numerical simulations. Interpretations in terms of vector quantization and in model-based spectral analysis are discussed together with applications and possible extensions.
A New k-means Based Clustering Algorithm in Aspect Mining
Authors: Gabriela Serban, Grigoreta Sofia Moldovan
Venue: Proceedings of the Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (2006)

Clustering is a division of data into groups of similar objects. Aspect mining is a process that tries to identify cross-cutting concerns in existing software systems. The goal is to refactor the existing systems to use aspect oriented programming, in order to make them easier to maintain and to evolve. This paper aims at presenting a new k-means based clustering algorithm used in Aspect Mining. Clustering is used in order to identify crosscutting concerns. We propose some quality measures in order to evaluate the results both from the clustering point of view and the aspect mining point of view, and we also report two case studies.
Management of probabilistic data: foundations and challenges
Authors: Nilesh Dalvi, Dan Suciu
Venue: Proceedings of the twenty-sixth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems (2007)

Many applications today need to manage large data sets with uncertainties. In this paper we describe the foundations of managing data where the uncertainties are quantified as probabilities. We review the basic definitions of the probabilistic data model, present some fundamental theoretical result for query evaluation on probabilistic databases, and discuss several challenges, open problems, and research directions.
Pilot-based estimation of time-varying multipath channels
Authors: M.-A. R. Baissas
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 05 (2000)

Reliable coherent communication over multipath wireless channels requires accurate estimation of time-varying channel parameters. For coherent estimation, a key channel characteristic is the coherence time that approximately corresponds to the interval over which the channel parameters remain strongly correlated. We address linear MMSE estimation of code division multiple access (CDMA) multipath channels based on a pilot transmission. We derive a simple characterization of the estimator in terms of a bank of filters. We show that the estimator performance is primarily governed by an effective SNR that is proportional to the coherence time. We also propose two suboptimal estimators that are easy to implement and demonstrate that they deliver near-optimal performance if properly designed.
On stochastic methods for surface reconstruction
Authors: Waqar Saleem, Oliver Schall, Giuseppe Patan&#x00e8;, Alexander Belyaev, Hans-Peter Seidel
Venue: The Visual Computer: International Journal of Computer Graphics (2007)

In this article, we present and discuss three statistical methods for surface reconstruction. A typical input to a surface reconstruction technique consists of a large set of points that has been sampled from a smooth surface and contains uncertain data in the form of noise and outliers. We first present a method that filters out uncertain and redundant information yielding a more accurate and economical surface representation. Then we present two methods, each of which converts the input point data to a standard shape representation; the first produces an implicit representation while the second yields a triangle mesh.
Spectral estimation under nature missing data
Authors: Jui-Chung Hung
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 05 (2001)

This paper considers the problem of estimating the autoregressive moving average (ARMA) power spectral density when measurements are corrupted by noises and with missing data. The missing data model is based on an unknown probabilistic structure. In this situation, the spectral estimation becomes a highly nonlinear optimization problem with many local minima. In this paper, we use the global search method of genetic algorithm (GA) to achieve a global optimal solution of this spectral estimation problem. From the simulation results, we have found that the performance is improved significantly if the probability of data missing is considered in the spectral estimation problem.
A Flexible Platform Framework for Rapid Transactional Memory Systems Prototyping and Evaluation
Authors: Fernando Kronbauer, Alexandro Baldassin, Bruno Albertini, Paulo Centoducatte, Sandro Rigo, Guido Araujo, Rodolfo Azevedo
Venue: Proceedings of the 18th IEEE/IFIP International Workshop on Rapid System Prototyping (2007)

Transactional memory (TM) is an emerging synchronization mechanism that aims to solve most of the difficulties inherent in lock-based approaches. TM implementations may either rely on special hardware (HTM) or employ a software-only (STM) technique. While STM can be implemented and evaluated in current machines, HTM requires hardware modification and a prototyping infrastructure. We present in this paper a flexible platform framework for rapid prototyping and evaluation of HTM systems. Platform components such as cache, memory and interconnection medium are implemented using SystemC and Transaction-Level Modeling (TLM). Processors are described in an Architecture Description Language (ADL) which makes it practical to change the Instruction Set Architecture (ISA), since simulators and binary utilities are automatically generated by the ADL toolset. The resulting flexibility allows designers to explore the design space in a simple and uniform manner. We illustrate the platform through a case study based on the original HTM proposed by Herlihy and Moss. Simulation results are shown for microbenchmarks supporting up to 256 processors.
Leveraging Social Networks To Motivate Individuals to Reduce their Ecological Footprints
Authors: Jennifer Mankoff, Deanna Matthews, Susan R. Fussell, Michael Johnson
Venue: Proceedings of the 40th Annual Hawaii International Conference on System Sciences (2007)

What role can social networking websites play in supporting large-scale group action and change? We are proposing to explore their use in supporting individual reduction in personal energy consumption. Here we summarize some existing uses of social networking on the web and propose an approach that integrates feedback about ecological footprint data into existing social networking sites and Internet portal sites. Integrating such feedback into popular, commonly used sites allows frequent feedback about performance, while enabling the exploration motivational schemes that leverage group membership. We propose to compare different motivational schemes in three ways: Reduction in CO2 emission; lifestyle changes; and ongoing use by users who join the site (retention).
On-line arbitrarily vertex decomposable trees
Authors: Mirko Horňák, Zsolt Tuza, Mariusz Woniak
Venue: Discrete Applied Mathematics (2007)

A tree T is arbitrarily vertex decomposable if for any sequence @t of positive integers adding up to the order of T there is a sequence of vertex-disjoint subtrees of T whose orders are given by @t. An on-line version of the problem of characterizing arbitrarily vertex decomposable trees is completely solved here.
Work in progress: the adversarial testing system
Authors: D. Gustafson
Venue: Proceedings of the 30th Annual Frontiers in Education - Volume 01 (2000)

The goal of the Adversarial Testing System is to improve student awareness of software testing by rewarding students for developing good software tests. Students are notorious for submitting solutions to programming assignments with little or no testing. Making part of the grade dependent on developing good software tests that find errors in other students programs avoid encourage effort in testing. The basic idea is to let students submit software tests as well as a program solution. The students would be allowed to run their test cases against their own program and against an oracle (problem solution) created by the instructor.
Autonomous Pervasive Systems and the Policy Challenges of a Small World!
Authors: Emil Lupu, Naranker Dulay, Joe Sventek, Morris Sloman
Venue: Proceedings of the Eighth IEEE International Workshop on Policies for Distributed Systems and Networks (2007)

Pervasive systems are the subject of intensifying research efforts and their applications range from health monitoring and intelligent homes, to location aware services, unmanned vehicles and city-wide pervasive infrastructures. Although application-specific solutions have been proposed, their design has often raised additional challenges. This paper discusses the use of Autonomous Pervasive Systems as a fertile testbed for policy-based adaptation and for integrating techniques that span across conventional subject boundaries. Additionally, we present the Self- Managed Cell architectural pattern for realizing policy-driven Autonomous Pervasive Systems and discuss the design of the Ponder2 policy service.
A multilingual approach to technical manuscripts: 16th and 17th-century Portuguese shipbuilding treatises
Authors: Carlos Monroy, Richard Furuta, Filipe Castro
Venue: Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries (2007)

Shipbuilding treatises are technical manuscripts written in a variety of languages and spanning several centuries that describe the construction of ships. Given their technical content, understanding terms, concepts, and construction sequences is a challenging task. In this paper we describe a scalable approach and a multilingual web-based interface for enabling a group of scholars to edit a glossary of nautical terms in multiple languages.
Meshing Non-uniformly Sampled and Incomplete Data Based on Displaced T-spline Level Sets
Authors: Huaiping Yang, Bert Juttler
Venue: Proceedings of the IEEE International Conference on Shape Modeling and Applications 2007 (2007)

We propose a new method for constructing a piecewise smooth mesh from a set of unorganized data points, which may be non-uniformly sampled, noisy, and even containing holes. The method is based on the construction of an implicit representation of the surface, by using smooth (C2 in our case) T-spline scalar functions. We first generate the Tspline control grid, and use an evolution process such that the resulting T-spline level sets capture the topology and outline of the object to be reconstructed. The initial mesh with high quality is obtained from the implicit T-spline function through the marching triangulation method. Then we project each data point to the initial mesh, and get a scalar displacement field. Detailed features will be captured by the displaced mesh. We also propose an additional evolution process, which combines data-driven velocities and featurepreserving bilateral filters, in order to reproduce sharp features.
Time-varying autoregressive system identification using wavelets
Authors: Yuanjin Zheng
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 01 (2000)

In this paper, the problem of time-varying parametric autoregressive (AR) model identification by wavelets is discussed. Firstly, we derive multiresolution least squares (MLS) algorithm Gaussian time-varying AR model identification employing wavelet operator matrix representation. This method can optimally balance between the over-fitted solution and the poorly represented estimation. Utilizing multiresolution analysis techniques, the smooth trends and the rapidly changing components of time-varying AR model parameters can both be estimated accurately. Then, the proposed MLS algorithm is combined with the total least squares algorithm for noisy time-varying AR model identification. Simulation results verify the effectiveness of our algorithms.
Minimum Redundancy Gene Selection Based on Grey Relational Analysis
Authors: Li-Juan Zhang, Zhou-Jun Li, Huo-Wang Chen, Jian Wen
Venue: Proceedings of the Sixth IEEE International Conference on Data Mining - Workshops (2006)

In this article we describe a method for selecting informative genes from microarray data. The method is based on clustering, namely, it first find similar genes, group them and then select informative genes from these groups to avoid redundancy. A new gene similarity measure based on Grey Relational Analysis (GRA), called Grey Relational Grade (GRG), is used in clustering. Experiments on three public data sets demonstrate the effectiveness of our method.
Serious video game effectiveness
Authors: Wee Ling Wong, Cuihua Shen, Luciano Nocera, Eduardo Carriazo, Fei Tang, Shiyamvar Bugga, Harishkumar Narayanan, Hua Wang, Ute Ritterfeld
Venue: Proceedings of the international conference on Advances in computer entertainment technology (2007)

Given the interactive media characteristics and intrinsically motivating appeal, computer games are often praised for their potential and value in education.allHowever, comprehensive research testing these assumptions is still missing. Preliminary comparative studies on the learning effects of games versus traditional media have shown some promise. In this paper, we describe a comparative study that thoroughly investigates the effects of interactivity and media richness on science learning among college students. We also discuss important results and implications yielded from comparisons among four conditions in our experiment (game, replay, hypertext and text).
System security administration for NT
Authors: Harlan Carvey
Venue: Proceedings of the 3rd conference on Large Installation System Administration of Windows NT - Volume 3 (2000)

System security administration has, for the most part, been largely ignored as network administration has flourished. The result of this is that there are large installations of NT that need to be retrofitted with some form of security administration and management system. There are various third party tools available to assist in this endeavor, but they are somewhat general and not tailored to meet the needs of a particular user or organization. System administrators must therefore learn to mold their infrastructure to the tool, rather than the other way around. Often times, the tools may also be quite expensive, and difficult to learn and maintain.
TTS based very low bit rate speech coder
Authors: Ki-Seung Lee
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 01 (1999)

This paper addresses a speech coder which uses a text-to-speech (TTS) synthesis system to achieve very low bit rates (sub 1 kbps). The main issue of the work is the accurate coding of the pitch (f/sub 0/) and gain contours which are principle components of prosody. This is of paramount interest since the correct prosody will increase naturalness and an efficient coding scheme will provide high coding gain. Together with the phonetic transcription, the f/sub 0/ and gain contour constitute the parameters that are necessary for the TTS system to synthesize the speech signal. Piecewise linear approximation is used to code the f/sub 0/ parameter. A technique which minimizes the bit rate while maintaining f/sub 0/ error below a given threshold are described. To obtain both high compression and smoothly changing gain contours, the variance of the signal is averaged over each half phoneme length is transmitted as gain information. With single speaker stimuli, and a priori text transcription information, we obtained natural sounding speech at an average bit rate of about 300 bps.
Memory bank aware dynamic loop scheduling
Authors: Mahmut Kandemir, Taylan Yemliha, Seung Woo Son, Ozcan Ozturk
Venue: Proceedings of the conference on Design, automation and test in Europe (2007)

In a parallel system with multiple CPUs, one of the key problems is to assign loop iterations to processors. This problem, known as the loop scheduling problem, has been studied in the past, and several schemes, both static and dynamic, have been proposed. One of the attractive features of dynamic schemes, as compared to their static counterparts, is their ability of exploiting the latency variations across the execution times of the different loop iterations. In all the dynamic loop scheduling techniques proposed in literature so far, performance has been the primary metric of interest. In a battery-operated embedded execution environment, however, power consumption is another metric to consider during iteration-to-processor assignment. In particular, in a banked memory system, this assignment can have an important impact on memory power consumption, which can be a significant portion of the overall energy consumption, especially for data-intensive embedded applications such as those from the domain of image data processing. This paper presents a bank aware dynamic loop scheduling scheme for array-intensive embedded media applications. The goal behind this new scheduling scheme is to minimize the number of memory banks that need to be used for executing the current working set (group of loop iterations) when all processors are considered together. That is, during the loop iteration-to-processor assignment, our approach considers the bank access patterns of loop iterations and carefully selects the set of iterations to assign to an idle processor so that, if possible, the number of memory banks that are used at the current state is not increased. Our experimental results show that the proposed scheduling scheme leads to much better energy results when compared to prior loop scheduling techniques and it is also competitive with the scheduler that generates the best performance. To our knowledge, this is the first dynamic loop scheduling scheme that is memory bank aware.
Effect of learning style diversity on engineering student teams
Authors: S. G. Adams
Venue: Proceedings of the Frontiers in Education Conference, 2001. on 31st Annual - Volume 01 (2001)

Modern demands of industry and ABET Engineering Criteria 2000 have resulted in a dramatically increased emphasis on team based learning in the engineering curriculum. Nevertheless, very little attention has been given to the development of practical guidelines for the implementation of teams in the engineering classroom environment. The authors have proposed a comprehensive curriculum to implement a student training for engineering team effectiveness. The curriculum includes training to develop personal effectiveness in teams, as well as training on interpersonal effectiveness and project management.
Supporting large-scale science with workflows
Authors: Deana D. Pennington
Venue: Proceedings of the 2nd workshop on Workflows in support of large-scale science (2007)

Current workflow systems support data flow through complex analyses in a distributed environment. The scope of scientific workflow systems could expand to support the entire scientific research cycle, which includes data flow, design flow, and knowledge flow tasks. Example tasks and requirements within each of these are explored, illustrated by a use case in environmental science. Nexus points between scientific tasks and potential workflow support mechanisms are identified and described. Several new ideas, or modifications of existing ideas are introduced: science dashboards, meta-provenance, event-driven workflows, extreme workflow development, and collective thinking workflows.
Sequential Bayesian computation of logistic regression models
Authors: M. Niranjan
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 02 (1999)

The extended Kalman filter (EKF) algorithm for identification of a state space model is shown to be a sensible tool in estimating a logistic regression model sequentially. A Gaussian probability density over the parameters of the logistic model is propagated on a sample by sample basis. Two other approaches, the Laplace approximation and the variational approximation are compared with the state space formulation. Features of the latter approach, such as the possibility of inferring noise levels by maximising the "innovation probability" are indicated. Experimental illustrations of these ideas on a synthetic problem and two real world problems are discussed.
Automated clock inference for stream function-based system level specifications
Authors: J.-P. Talpin, S. K. Shukla
Venue: Proceedings of the High-Level Design Validation and Test Workshop, 2005. on Tenth IEEE International (2005)

Among system-level design frameworks and languages, system modeling approaches based on functional programming aim at rapid specification and prototyping of processing of data streams. Models constructed with functional programs provide highly modular and computationally correct models for prototyping and simulation purposes. For design space exploration, the functional programming frameworks provide semantically sound methodologies for establishing formal refinement relations and secure a trustable design automation flow. However, the stream computations expressed by functions embody an implicitly single clocked model of computation (untimed or fully synchronous) which does not take advantage of possible polychronous (multiclock) computation inherent to the system's dataflow. To this end, we propose a type inference system for representing a synchronous and multiclocked model of computation in the typed and functional programming language ML. Along the way, we address the issue of performing the automated refinement of implicitly timed stream functions in a model of computation that supports reasoning on partially ordered signal clocks, allowing for formal design transformation and verification to be performed in the context of a functional programming environment.
On The Design of High Throughput Adaptive Multicast Communication
Authors: Ahmed Yassin Al-Dubai, Imed Romdhani
Venue: Proceedings of the Sixth International Symposium on Parallel and Distributed Computing (2007)

The efficient and high throughput multicast communication in interconnection networks is known as a fundamental but hard problem. In the literature, most of the related works handle multicast communication within limited operating conditions and low throughput. Recently, a new multicast scheme, known as Qualified Groups QG, was proposed in [2] and has shown promising performance characteristics. However, this scheme has been examined only, so far, under deterministic routing and symmetric networks. In order to examine the QG in more realistic and different scenarios, this paper makes two major contributions. Firstly, the QG is generalised here to handling multicast communication in symmetric, asymmetric and different network sizes. Secondly, unlike most existing multicast algorithms the present study proposes a new adaptive multicast algorithm that maintains good performance levels for various system sizes. Our experiments show that the QG exhibits significant improvement in both throughput and multicast latency.