Computer Sciences Commons^™

A First Practical Algorithm For High Levels Of Relational Consistency, Shant Karakashian, Robert J. Woodward, Christopher Reeson, Berthe Y. Choueiry, Christian Bessiere

School of Computing: Conference and Workshop Papers

Consistency properties and algorithms for achieving them are at the heart of the success of Constraint Programming. In this paper, we study the relational consistency property R(*,m)C, which is equivalent to m-wise consistency proposed in relational databases. We also define wR(*,m)C, a weaker variant of this property. We propose an algorithm for enforcing these properties on a Constraint Satisfaction Problem by tightening the existing relations and without introducing new ones. We empirically show that wR(*,m)C solves in a backtrackfree manner all the instances of some CSP benchmark classes, thus hinting at the tractability …

A Partial Taxonomy Of Substitutability And Interchangeability, Shant Karakashian, Robert J. Woodward, Berthe Y. Choueiry, Steven D. Prestwich, Eugene C. Freuder

School of Computing: Conference and Workshop Papers

Substitutability, interchangeability and related concepts in Constraint Programming were introduced approximately twenty years ago and have given rise to considerable subsequent research. We survey this work, classify, and relate the different concepts, and indicate directions for future work, in particular with respect to making connections with research into symmetry breaking. This paper is a condensed version of a larger work in progress.

Mechanical Sensorless Maximum Power Tracking Control For Direct-Drive Pmsg Wind Turbines, Xu Yang, Xiang Gong, Wei Qiao

Department of Electrical and Computer Engineering: Faculty Publications

Wind turbine generators (WTGs) are usually equipped with mechanical sensors to measure wind speed and rotor position for system control, monitoring, and protection. The use of mechanical sensors increases the cost and hardware complexity and reduces the reliability of the WTG systems. This paper proposes a mechanical sensorless maximum power tracking control for wind turbines directly driving permanent magnetic synchronous generators (PMSGs). In the proposed algorithm, the PMSG rotor position is estimated from the measured stator voltages and currents by using a sliding mode observer (SMO). The wind turbine shaft speed is estimated from the PMSG back electromotive force (EMF) …

Vowel Recognition From Continuous Articulatory Movements For Speaker-Dependent Applications, Jun Wang, Jordan R. Green, Ashok Samal, Tom D. Carrell

Department of Special Education and Communication Disorders: Faculty Publications

A novel approach was developed to recognize vowels from continuous tongue and lip movements. Vowels were classified based on movement patterns (rather than on derived articulatory features, e.g., lip opening) using a machine learning approach. Recognition accuracy on a single-speaker dataset was 94.02% with a very short latency. Recognition accuracy was better for high vowels than for low vowels. This finding parallels previous empirical findings on tongue movements during vowels. The recognition algorithm was then used to drive an articulation-to-acoustics synthesizer. The synthesizer recognizes vowels from continuous input stream of tongue and lip movements and plays the corresponding sound samples …

Biological Sequence Simulation For Testing Complex Evolutionary Hypotheses: Indel-Seq-Gen Version 2.0, Cory L. Strope

School of Computing: Dissertations, Theses, and Student Research

Reconstructing the evolutionary history of biological sequences will provide a better understanding of mechanisms of sequence divergence and functional evolution. Long-term sequence evolution includes not only substitutions of residues but also more dynamic changes such as insertion, deletion, and long-range rearrangements. Such dynamic changes make reconstructing sequence evolution history difficult and affect the accuracy of molecular evolutionary methods, such as multiple sequence alignments (MSAs) and phylogenetic methods. In order to test the accuracy of these methods, benchmark datasets are required. However, currently available benchmark datasets have limitations in their sizes and evolutionary histories of the included sequences are unknown. These …

Sos: Searching Help Pages Of R Packages, Spencer Graves, Sundar Dorai-Raj, Romain François

The R Journal

The sos package provides a means to quickly and flexibly search the help pages of contributed packages, finding functions and datasets in seconds or minutes that could not be found in hours or days by any other means we know. Its findFn function accesses Jonathan Baron’s R Site Search database and returns the matches in a data frame of class "findFn", which can be further manipulated by other sos functions to produce, for example, an Excel file that starts with a summary sheet that makes it relatively easy to prioritize alternative packages for further study. As such, it provides a …

Rattle: A Data Mining Gui For R, Graham J. Williams

The R Journal

Data mining delivers insights, pat terns, and descriptive and predictive models from the large amounts of data available today in many organisations. The data miner draws heavily on methodologies, techniques and algorithms from statistics, machine learning, and computer science. R increasingly provides a powerful platform for data mining. However, scripting and programming is sometimes a challenge for data analysts moving into data mining. The Rattle package provides a graphical user interface specifically for data mining using R. It also provides a stepping stone toward using R as a programming language for data analysis.

Copas: An R Package For Fitting The Copas Selection Model, J. Carpenter, G. Rücker, G. Schhwarzer

The R Journal

This article describes the R package copas which is an add-on package to the R pack age meta. The R package copas can be used to f it the Copas selection model to adjust for bias in meta-analysis. A clinical example is used to illustrate fitting and interpreting the Copas selection model.

Party On!, Carolin Strobl, Torsten Hothorn, Achim Zeileis

The R Journal

Random forests are one of the most popular statistical learning algorithms, and a variety of methods for fitting random forests and related recursive partitioning approaches is available in R. This paper points out two important features of the random forest implementation cforest available in the party package: The resulting forests are unbiased and thus prefer able to the randomForest implementation avail able in randomForest if predictor variables are of different types. Moreover, a conditional per mutation importance measure has recently been added to the party package, which can help evaluate the importance of correlated predictor variables. The rationale of this …

Aspects Of The Social Organization And Trajectory Of The R Project, John Fox

The R Journal

Based partly on interviews with members of the R Core team, this paper considers the development of the R Project in the context of open-source software development and, more generally, voluntary activities. The paper de scribes aspects of the social organization of the R Project, including the organization of the R Core team; describes the trajectory of the R Project; seeks to identify factors crucial to the success of R; and speculates about the prospects for R.

Asymptest: A Simple R Package For Classical Parametric Statistical Tests And Confidence Intervals In Large Samples, J.-F. Coeurjolly, R. Drouilhet, P. Lafaye De Micheaux, J.-F. Robineau

The R Journal

asympTest is an R package implementing large sample tests and confidence intervals. One and two sample mean and variance tests (differences and ratios) are considered. The test statistics are all expressed in the same form as the Student t-test, which facilitates their presentation in the classroom. This contribution also fills the gap of a robust (to non-normality) alternative to the chi-square single variance test for large samples, since no such procedure is implemented in standard statistical software.

Convergenceconcepts: An R Package To Investigate Various Modes Of Convergence, Pierre Lafaye De Micheaux, Benoit Liquet

The R Journal

ConvergenceConcepts is an R pack age, built upon the tkrplot, tcltk and lattice packages, designed to investigate the convergence of simulated sequences of random variables. Four classical modes of convergence may be studied, namely: almost sure convergence (a.s.), convergence in probability (P), convergence in law (L) and convergence in r-th mean (r). This investigation is performed through ac curate graphical representations. This package may be used as a pedagogical tool. It may give students a better understanding of these notions and help them to visualize these difficult theoretical concepts. Moreover, …

The R Journal (December 2009) 1(2): Complete Issue, The R Foundation

The R Journal

Contributed Research Articles

Aspects of the Social Organization and Trajectory of the R Project, John Fox

Party on! Carolin Strobl, Torsten Hothorn and Achim Zeileis

ConvergenceConcepts: An R Package to Investigate Various Modes of Convergence, Pierre Lafaye de Micheaux and Benoit Liquet

asympTest: A Simple R Package for Classical Parametric Statistical Tests and Confidence Intervals in Large Samples, J.-F. Coeurjolly, R. Drouilhet, P. Lafaye de Micheaux and J.-F. Robineau

copas: An R package for Fitting the Copas Selection Model, J. Carpenter, G. Rücker and G. Schwarzer

Transitioning to R: Replicating SAS, Stata, and SUDAAN Analysis Techniques in Health Policy Data, …

Classification, Clustering And Data-Mining Of Biological Data, Thomas Triplet

School of Computing: Dissertations, Theses, and Student Research

The proliferation of biological databases and the easy access enabled by the Internet is having a beneficial impact on biological sciences and transforming the way research is conducted. There are currently over 1,100 molecular biology databases dispersed throughout the Internet. However, very few of them integrate data from multiple sources. To assist in the functional and evolutionary analysis of the abundant number of novel proteins, we introduce the PROFESS (PROtein Function, Evolution, Structure and Sequence) database that integrates data from various biological sources. PROFESS is freely available at http://cse.unl.edu/~profess/. Our database is designed to be versatile and expandable and …

Dynamic Load Balancing For I/O-Intensive Applications On Clusters, Xiao Qin, Hong Jiang, Adam Manzanares, Xiaojun Ruan, Shu Yin

School of Computing: Faculty Publications

Load balancing for clusters has been investigated extensively, mainly focusing on the effective usage of global CPU and memory resources. However, previous CPU- or memory-centric load balancing schemes suffer significant performance drop under I/O-intensive workloads due to the imbalance of I/O load. To solve this problem, we propose two simple yet effective I/O-aware load-balancing schemes for two types of clusters: (1) homogeneous clusters where nodes are identical and (2) heterogeneous clusters, which are comprised of a variety of nodes with different performance characteristics in computing power, memory capacity, and disk speed. In addition to assigning I/O-intensive sequential and parallel jobs …

Smartstore: A New Metadata Organization Paradigm With Semantic-Awareness For Next-Generation File Systems, Yu Hua, Hong Jiang, Yifeng Zhu, Dan Feng, Lei Tian

School of Computing: Conference and Workshop Papers

Existing storage systems using hierarchical directory tree do not meet scalability and functionality requirements for exponentially growing datasets and increasingly complex queries in Exabyte-level systems with billions of files. This paper proposes semantic-aware organization, called SmartStore, which exploits metadata semantics of files to judiciously aggregate correlated files into semantic-aware groups by using information retrieval tools. Decentralized design improves system scalability and reduces query latency for complex queries (range and top-k queries), which is conducive to constructing semantic-aware caching, and conventional filename-based query. SmartStore limits search scope of complex query to a single or a minimal number of semantically related groups …

Digital Logic Based Encoding Strategies For Steganography On Voice-Over-Ip, Hui Tian, Ke Zhou, Hong Jiang, Dan Feng

School of Computing: Conference and Workshop Papers

This paper presents three encoding strategies based on digital logic for steganography on Voice over IP (VoIP), which aim to enhance the embedding transparency. Differing from previous approaches, our strategies reduce the embedding distortion by improving the similarity between the cover and the covert message using digital logical transformations, instead of reducing the amount of the substitution bits. Therefore, by contrast, our strategies will improve the embedding transparency without sacrificing the embedding capacity. Of these three strategies, the first one adopts logical operations, the second one employs circular shifting operations, and the third one combines the operations of the first …

Refactoring Pipe-Like Mashups For End-User Programmers, Kathryn T. Stolee, Sebastian Elbaum

School of Computing: Technical Reports

Mashups are becoming increasingly popular as end users are able to easily access, manipulate, and compose data from many web sources. We have observed, however, that mashups tend to suffer from deficiencies that propagate as mashups are reused. To address these deficiencies, we would like to bring some of the benefits of software engineering techniques to the end users creating these programs. In this work, we focus on identifying code smells indicative of the deficiencies we observed in web mashups programmed in the popular Yahoo! Pipes environment. Through an empirical study, we explore the impact of those smells on end-user …

Temporal Data Classification Using Linear Classifiers, Peter Revesz, Thomas Triplet

School of Computing: Conference and Workshop Papers

Data classification is usually based on measurements recorded at the same time. This paper considers temporal data classification where the input is a temporal database that describes measurements over a period of time in history while the predicted class is expected to occur in the future. We describe a new temporal classification method that improves the accuracy of standard classification methods. The benefits of the method are tested on weather forecasting using the meteorological database from the Texas Commission on Environmental Quality.

Vowel Recognition From Articulatory Position Time-Series Data, Jun Wang, Ashok Samal, Jordan R. Green, Tom D. Carrell

School of Computing: Conference and Workshop Papers

A new approach of recognizing vowels from articulatory position time-series data was proposed and tested in this paper. This approach directly mapped articulatory position time-series data to vowels without extracting articulatory features such as mouth opening. The input time-series data were time-normalized and sampled to fixed-width vectors of articulatory positions. Three commonly used classifiers, Neural Network, Support Vector Machine and Decision Tree were used and their performances were compared on the vectors. A single speaker dataset of eight major English vowels acquired using Electromagnetic Articulograph (EMA) AG500 was used. Recognition rate using cross validation ranged from 76.07% to 91.32% for …

Exploiting Set-Level Non-Uniformity Of Capacity Demand To Enhance Cmp Cooperative Caching, Dongyuan Zhan, Hong Jiang, Sharad C. Seth

School of Computing: Technical Reports

As the Memory Wall remains a bottleneck for Chip Multiprocessors (CMP), the effective management of CMP last level caches becomes of paramount importance in minimizing expensive off-chip memory accesses. For the CMPs with private last level caches, Cooperative Caching (CC) has been proposed to enable capacity sharing among private caches by spilling an evicted block from one cache to another. But this eviction-driven CC does not necessarily promote cache performance since it implicitly favors the applications full of block evictions regardless of their real capacity demand. The recent Dynamic Spill-Receive (DSR) paradigm improves cooperative caching by prioritizing applications with higher …

Selection Of Switching Sites In All-Optical Nework Topology Design, Shivashis Saha, Eric D. Manley, Jitender S. Deogun

School of Computing: Technical Reports

In this paper, we consider the problem of topology design for optical networks. We investigate the problem of selecting switching sites to minimize total cost of the optical network. The cost of an optical network can be expressed as a sum of three main factors: the site cost, the link cost, and the switch cost. To the best of our knowledge, this problem has not been studied in its general form as investigated in this paper. We present a mixed integer quadratic programming (MIQP) formulation of the problem to find the optimal value of the total network cost. We also …

Design Of An All-Optical Wdm Lightpath Concentrator, Shivashis Saha, Jitender S. Deogun

School of Computing: Technical Reports

A design of a nonblocking, all-optical lightpath concentrator using WOC and WDM crossbar switches is presented. The proposed concentrator is highly scalable, cost-efficient, and can switch signals in both space and wavelength domains without requiring a separate wavelength conversion stage.

Sample Size Estimation While Controlling False Discovery Rate For Microarray Experiments Using The Ssize.Fdr Package, Megan Orr, Peng Liu

The R Journal

Microarray experiments are becoming more and more popular and critical in many biological disciplines. As in any statistical experiment, appropriate experimental design is essential for reliable statistical inference, and sample size has a crucial role in experimental design. Because microarray experiments are rather costly, it is important to have an adequate sample size that will achieve a desired power with out wasting resources.

For a given microarray data set, thousands of hypotheses, one for each gene, are simultaneously tested. Storey and Tibshirani (2003) argue that con trolling false discovery rate (FDR) is more reasonable and more powerful than controlling family-wise …

Emd: A Package For Empirical Mode Decomposition And Hilbert Spectrum, Donghoh Kim, Hee-Seok Oh

The R Journal

The concept of empirical mode decomposition (EMD)and the Hilber tspectrum (HS) has been developed rapidly in many disciplines of science and engineering since Huang et al. (1998) invented EMD. The key feature of EMD is to decompose a signal into so-called intrinsic mode function (IMF). Further more, the Hilbert spectral analysis of intrinsic mode functions provides frequency information evolving with time and quantifies the amount of variation due to oscillation at different time scales and time locations. In this article,we introduce an R package called EMD (KimandOh, 2008) that performs one and two-dimensional EMD and HS.

Modeling Without Data Using Expert Opinion, Vincent Goulet, Michel Jacques, Mathieu Pigeon

The R Journal

The expert package provides tools to create and manipulate empirical statistical models using expert opinion (or judgment). Here, the latter expression refers to a specific body of techniques to elicit the distribution of a random variable when data is scarce or unavailable. Opinions on the quantiles of the distribution are sought from experts in the field and aggregated into a final estimate. The package supports aggregation by means of the Cooke, Mendel–Sheridan and predefined weights models.

We do not mean to give a complete introduction to the theory and practice of expert opinion elicitation in this paper. However, for the …

Admit, David Ardia, Lennart F. Hoogerheide, Herman K. Van Dijk

The R Journal

This note presents the package AdMit (Ardia et al., 2008, 2009), an R implementation of the adaptive mixture of Student-t distributions (AdMit) procedure developed by Hoogerheide (2006); see also Hoogerheide et al. (2007); Hoogerheide and van Dijk (2008). The AdMit strategy consists of the construction of a mixture of Student-t distributions which approximates a target distribution of interest. The fitting procedure relies only on a kernel of the tar get density, so that the normalizing constant is not required. In a second step, this approximation is used as an importance function in importance sampling or as a candidate density in …

The Hwriter Package: Composing Html Documents With R Objects, Gregoire Pau, Wolfgang Huber

The R Journal

HTML documents are structured documents made of diverse elements such as paragraphs, sections, columns, figures and tables organized in a hierarchical layout. Combination of HTML documents and hyperlinking is useful to report analysis results; for example, in the package array Quality Metrics (Kauffmannetal., 2009), estimating the quality of mi croarray data sets and cellHTS2(Boutrosetal.,2006), performing the analysis of cell-based screens.

There are several tools for exporting data from R into HTML documents. The package R2HTML is able to render a large diversity of R objects in HTML but does not easily support combining them in a structured layout and …

Collaborative Software Development Using R-Forge, Stefan Theußl, Achim Zeileis

The R Journal

Open source software (OSS) is typically created in a decentralized self-organizing process by a community of developers having the same or similar interests (see the famous essay by Raymond, 1999). A key factor for the success of OSS over the last two decades is the Internet: Developers who rarely meet face-to-face can employ new means of communication, both for rapidly writing and deploying software (in the spirit of Linus Torvald’s “release early, release often paradigm”). Therefore, many tools emerged that assist a collaborative software development process, including in particular tools for source code management (SCM) and version control.

In the …

Facets Of R, John M. Chambers

The R Journal

We are seeing today a widespread, and welcome, tendency for non-computer-specialists among statisticians and others to write collections of R functions that organize and communicate their work. Along with the flood of software sometimes comes an attitude that one need-only-learn, or teach, a sort of basic how-to-write-the-function level of R programming, beyond which most of the detail is unimportant or can be absorbed without much discussion. As delusions go, this one is not very objectionable if it encourages participation. Nevertheless, a delusion it is. In fact, functions are only one of a variety of important facets that R has acquired …