Computer Sciences Commons^™

Practical Tractability Of Csps By Higher Level Consistency And Tree Decomposition, Shant Karakashian

School of Computing: Dissertations, Theses, and Student Research

Constraint Satisfaction is a flexible paradigm for modeling many decision problems in Engineering, Computer Science, and Management. Constraint Satisfaction Problems (CSPs) are in general NP-complete and are usually solved with search. Research has identified various islands of tractability, which enable solving certain CSPs with backtrack-free search. For example, one sufficient condition for tractability relates the consistency level of a CSP to treewidth of the CSP's constraint network. However, enforcing higher levels of consistency on a CSP may require the addition of constraints, thus altering the topology of the constraint network and increasing its treewidth. This thesis addresses the following question: …

Reliable Peak Selection For Multisample Analysis With Comprehensive Two-Dimensional Chromatography, Stephen E. Reichenbach, Xue Tian, Akwasi A. Boateng, Charles A. Mullen, Chiara Cordero, Qingping Tao

School of Computing: Faculty Publications

Comprehensive two-dimensional chromatography is a powerful technology for analyzing the patterns of constituent compounds in complex samples, but matching chromatographic features for comparative analysis across large sample sets is difficult. Various methods have been described for pairwise peak matching between two chromatograms, but the peaks indicated by these pairwise matches commonly are incomplete or inconsistent across many chromatograms. This paper describes a new, automated method for postprocessing the results of pairwise peak matching to address incomplete and inconsistent peak matches and thereby select chromatographic peaks that reliably correspond across many chromatograms. Reliably corresponding peaks can be used both for directly …

Vsfs: A Versatile Searchable File System For Hpc Analytics, Lei Xu, Ziling Huang, Hong Jiang, Lei Tian, David Swanson

School of Computing: Technical Reports

Big-data/HPC analytics applications have urgent needs for file-search services to drastically reduce the scale of the input data to accelerate analytics. Unfortunately, the existing solutions either are poorly scalable for large-scale systems, or lack well-integrated interface to allow applications to easily use them. We propose a distributed searchable file system, VSFS, which provide a novel and flexible POSIX-compatible searchable file system namespace that can be seamlessly integrate with any legacy code without modification. Additionally, to provide real-time indexing and searching performance, VSFS uses DRAM-based distributed consistent hashing ring to manages all file-index. The results of our evaluation show that VSFS …

Energy-Efficient Failure Recovery In Hadoop Cluster, Weiyue Xu

School of Computing: Dissertations, Theses, and Student Research

Based on U.S. Environmental Protection Agency’s estimation, only in U.S., billions of dollars are spent on the electricity cost of data centers each year, and the cost is continually increasing very quickly. Energy efficiency is now used as an important metric for evaluating a computing system. However, saving energy is a big challenge due to many constraints. For example, in one of the most popular distributed processing frameworks, Hadoop, three replicas of each data block are randomly distributed in order to improve performance and fault tolerance, but such a mechanism limits the largest number of machine that can be turned …

Data Mining The Functional Characterizations Of Proteins To Predict Their Cancer-Relatedness, Peter Revesz, Christopher Assi

School of Computing: Faculty Publications

This paper considers two types of protein data. First, data about protein function described in a number of ways, such as, GO terms and PFAM families. Second, data about whether individual proteins are experimentally associated with cancer by an anomalous elevation or lowering of their expressions within cancerous cells. We combine these two types of protein data and test whether the first type of data, that is, the functional descriptors, can predict the second type of data, that is, cancer-relatedness. By using data mining and machine learning, we derive a classifier algorithm that using only GO term and PFAM family …

Human Performance Regression Testing, Amanda Swearngin, Myra B. Cohen, Bonnie E. John, Rachel K. E. Bellamy

School of Computing: Conference and Workshop Papers

As software systems evolve, new interface features such as keyboard shortcuts and toolbars are introduced. While it is common to regression test the new features for functional correctness, there has been less focus on systematic regression testing for usability, due to the effort and time involved in human studies. Cognitive modeling tools such as CogTool provide some help by computing predictions of user performance, but they still require manual effort to describe the user interface and tasks, limiting regression testing efforts. In recent work, we developed CogTool-Helper to reduce the effort required to generate human performance models of existing systems. …

Fea Estimation And Experimental Validation Of Solid Rotor And Magnet Eddy Current Loss In Single-Sided Axial Flux Permanent Magnet Machines, Xu Yang, Dean Patterson, Jerry Hudgins, Jessica Colton

Department of Electrical and Computer Engineering: Faculty Publications

The rotor and magnet loss in single-sided axial flux permanent magnet machines with non-overlapped windings is studied in this paper. FEA estimations of the loss are carried out using both 2-D and 3-D modeling. The rotor and magnet losses are determined separately for stator slot passing and MMF space harmonics from currents in the stator. The segregation of loss between the solid rotor plate and the magnet is addressed. The eddy current loss reduction by magnet segments is discussed as well. The prototype 24 slot/22 pole single-sided AFPMs, fabricated with both single layer and double layer windings are assembled. Methods …

Biodiversity Heritage Library, Smithsonian Institution Libraries, Deanna Marcum

Copyright, Fair Use, Scholarly Communication, etc.

The Biodiversity Heritage Library (BHL), created in 2006, is the result of a collaboration of ten natural history museum and botanical garden libraries seeking to digitize core taxonomic literature and to make it free and openly available throughout the world. Today, the BHL includes fifteen member institutions whose efforts have shaped a collection of over 60,000 titles. It is supported through a combination of membership dues, in-kind support from member institutions, contributions from the user community, and direct support from the Smithsonian Institution Libraries, and it reaches tens of thousands of users each year. While managing the complex partnership has …

The R Journal (December 2012) 4(2): Complete Issue, The R Foundation

The R Journal

Contributing Articles

What's in a Name? Paul Murrell

It's Not What You Draw, It's What You Don't Draw, Paul Murrell

Debugging grid Graphics, Paul Murrell and Velvet Ly

frailtyHL: A Package for Fitting Frailty Models with H-likelihood, Il Do Ha, Maengseok Noh, and Youngjo Lee

influence.ME: Tools for Detecting Influential Data in Mixed Effects Models, Rense Nieuwenhuis, Manfred te Grotenhuis and Ben Pelzer

The crs Package: Nonparametric Regression Splines for Continuous and Categorical Predictors, Zhenghua Nie and Jeffrey S. Racine

Rfit: Rank-based Estimation for Linear Models, John D. Kloke and Joseph W. McKean

Graphical Markov Models with Mixed Graphs in …

The Crs Package: Nonparametric Regression Splines For Continuous And Categorical Predictors, Zhenghua Nie, Jeffery S. Racine

The R Journal

A new package crs is introduced for computing nonparametric regression (and quantile) splines in the presence of both continuous and categorical predictors. B-splines are employed in the regression model for the continuous predictors and kernel weighting is employed for the categorical predictors. We also de velop a simple R interface to NOMAD, which is a mixed integer optimization solver used to compute optimal regression spline solutions.

Influence.Me: Tools For Detecting Influential Data In Mixed Effects Models, Rense Nieuwenhuis, Manfred Te Grotenhuis, Ben Pelzer

The R Journal

influence.ME provides tools for detecting influential data in mixed effects models. The application of these models has become common practice, but the development of diagnostic tools has lagged behind. influence.ME calculates standardized measures of influential data for the point estimates of generalized mixed effects models, such as DFBETAS, Cook’s distance, as well as percentile change and a test for changing levels of significance. influence.ME calculates these measures of influence while ac counting for the nesting structure of the data. The package and measures of influential data are introduced, a practical example is given, and strategies for dealing with influential data …

Graphical Markov Models With Mixed Graphs In R, Kayvan Sadeghi, Giovanni M. Marchetti

The R Journal

In this paper we provide a short tuto rial illustrating the new functions in the package ggm that deal with ancestral, summary and ribbonless graphs. These are mixed graphs (containing three types of edges) that are important because they capture the modified independence structure after marginalisation over, and conditioning on, nodes of directed acyclic graphs. We provide functions to verify whether a mixed graph implies that A is independent of B given C for any disjoint sets of nodes and to generate maximal graphs inducing the same independence structure of non-maximal graphs. Finally, we provide functions to decide on the …

What's In A Name?, Paul Murrell

The R Journal

Any shape that is drawn using the grid graphics package can have a name associated with it. If a name is provided, it is possible to access, query, and modify the shape after it has been drawn. These facilities allow for very detailed customisations of plots and also for very general transformations of plots that are drawn by packages based on grid.

Frailtyhl: A Package For Fitting Frailty Models With H-Likelihood, Il Do Ha, Maengseok Noh, Youngjo Lee

The R Journal

We present the frailtyHL package for fitting semi-parametric frailty models using h likelihood. This package allows lognormal or gamma frailties for random-effect distribution, and it fits shared or multilevel frailty models for correlated survival data. Functions are provided to format and summarize the frailtyHL results. The estimates of fixed effects and frailty parameters and their standard errors are calculated. We illustrate the use of our package with three well known data sets and compare our results with various alternative R-procedures.

Rfit: Rank-Based Estimation For Linear Models, John D. Kloke, Joseph W. Mckeen

The R Journal

In the nineteen seventies, Jureĉková and Jaeckel proposed rank estimation for linear models. Since that time, several authors have developed inference and diagnostic methods for these estimators. These rank-based estimators and their associated inference are highly efficient and are robust to outliers in response space. The methods include estimation of standard errors, tests of general linear hypotheses, confidence intervals, diagnostic procedures including studentized residuals, and measures of influential cases. We have developed an R package, Rfit, for computing of these robust procedures. In this paper we highlight the main features of the pack age. The package uses standard linear …

It's Not What You Draw, It's What You Don't Draw, Paul Murrell

The R Journal

The R graphics engine has new support for drawing complex paths via the functions polypath() and grid.path(). This article explains what is meant by a complex path and demonstrates the usefulness of complex paths in drawing non-trivial shapes, logos, customised data symbols, and maps.

Debugging Grid Graphics, Paul Murrell, Velvet Ly

The R Journal

A graphical scene that has been produced using the grid graphics package consists of grobs (graphical objects) and viewports. This article describes functions that allow the exploration and inspection of the grobs and viewports in a grid scene, including several functions that are available in a new package called gridDe bug. The ability to explore the grobs and view ports in a grid scene is useful for adding more drawing to a scene that was produced using grid and for understanding and debugging the grid code that produced a scene.

The State Of Naming Conventions In R, Rasmus Bååth

The R Journal

Most programming language communities have naming conventions that are generally agreed upon, that is, a set of rules that governs how functions and variables are named. This is not the case with R, and a review of unofficial style guides and naming convention us age on CRAN shows that a number of different naming conventions are currently in use. Some naming conventions are, however, more popular than others and as a newcomer to the R community or as a developer of a new package this could be useful to consider when choosing what naming convention to adopt.

Identification Of Tcp Protocols, Juan Shao

School of Computing: Dissertations, Theses, and Student Research

Recently, many new TCP algorithms, such as BIC, CUBIC, and CTCP, have been deployed in the Internet. Investigating the deployment statistics of these TCP algorithms is meaningful to study the performance and stability of the Internet. Currently, there is a tool named Congestion Avoidance Algorithm Identification (CAAI) for identifying the TCP algorithm of a web server and then for investigating the TCP deployment statistics. However, CAAI using a simple k-NN algorithm can not achieve a high identification accuracy. In this thesis, we comprehensively study the identification accuracy of five popular machine learning models. We find that the random forest model …

Dynamic Data Race Detection And Healing, Du Li

School of Computing: Dissertations, Theses, and Student Research

Perpetual availability is an important operational goal in today's computer systems. However, achieving this goal is challenging because modern software systems contain faults that can cause them to fail. For example, multi-threading is widely used in modern software to fully utilize the computing capability of multicore processors. However, employing multi-threading can lead to concurrency faults such as deadlock and data race that are notoriously difficult to to isolate, detect, and repair.Data races, which involves two concurrent accesses to the same data where at least one is a write, are the most common concurrency faults.

As our first step, we investigate …

Data Mining Of Pancreatic Cancer Protein Databases, Peter Revesz, Christopher Assi

School of Computing: Conference and Workshop Papers

Data mining of protein databases poses special challenges because many protein databases are non- relational whereas most data mining and machine learning algorithms assume the input data to be a type of rela- tional database that is also representable as an ARFF file. We developed a method to restructure protein databases so that they become amenable for various data mining and machine learning tools. Our restructuring method en- abled us to apply both decision tree and support vector machine classifiers to a pancreatic protein database. The SVM classifier that used both GO term and PFAM families to characterize proteins gave …

Hog: Distributed Hadoop Mapreduce On The Grid, Chen He, Derek J. Weitzel, David Swanson, Ying Lu

School of Computing: Conference and Workshop Papers

MapReduce is a powerful data processing platform for commercial and academic applications. In this paper, we build a novel Hadoop MapReduce framework executed on the Open Science Grid which spans multiple institutions across the United States – Hadoop On the Grid (HOG). It is different from previous MapReduce platforms that run on dedicated environments like clusters or clouds. HOG provides a free, elastic, and dynamic MapReduce environment on the opportunistic resources of the grid. In HOG, we improve Hadoop’s fault tolerance for wide area data analysis by mapping data centers across the U.S. to virtual racks and creating multi-institution failure …

Temporal Data Mining Of Uncertain Water Reservoir Data, Abhinaya Mohan, Peter Revesz

School of Computing: Conference and Workshop Papers

This paper describes the challenges of data mining uncertain water reservoir data based on past human operations in order to learn from them reservoir policies that can be automated for the future operation of the water reservoirs. Records of human operations of water reservoirs often contain uncertain data. For example, the recorded amounts of water released and retained in the water reservoirs are typically uncertain, i.e., they are bounded by some minimum and maximum values. Moreover, the time of release is also uncertain, i.e., typically only monthly or weekly amounts are recorded. To increase the effectiveness of data mining of …

Improving Performance Of Solid State Drives In Enterprise Environment, Jian Hu

School of Computing: Dissertations, Theses, and Student Research

Flash memory, in the form of Solid State Drive (SSD), is being increasingly employed in mobile and enterprise-level storage systems due to its superior features such as high energy efficiency, high random read performance and small form factor. However, SSD suffers from the erase-before-write and endurance problems, which limit the direct deployment of SSD in enterprise environment. Existing studies either develop SSD-friendly on-board buffer management algorithms, or design sophisticated Flash Translation Layers (FTL) to ease the erase-before-write problem. This dissertation addresses the two issues and consists of two parts.

The first part focuses on the white-box approaches that optimize the …

Whole-Word Recognition From Articulatory Movements For Silent Speech Interfaces, Jun Wang, Ashok Samal, Jordan R. Green, Frank Rudzicz

Department of Special Education and Communication Disorders: Faculty Publications

Articulation-based silent speech interfaces convert silently produced speech movements into audible words. These systems are still in their experimental stages, but have significant potential for facilitating oral communication in persons with laryngectomy or speech impairments. In this paper, we report the result of a novel, real-time algorithm that recognizes whole-words based on articulatory movements. This approach differs from prior work that has focused primarily on phoneme-level recognition based on articulatory features. On average, our algorithm missed 1.93 words in a sequence of twenty-five words with an average latency of 0.79 seconds for each word prediction using a data set of …

Retrieval Of Sub-Pixel-Based Fire Intensity And Its Application For Characterizing Smoke Injection Heights And Fire Weather In North America, David Peterson

Department of Earth and Atmospheric Sciences: Dissertations, Theses, and Student Research

For over two decades, satellite sensors have provided the locations of global fire activity with ever-increasing accuracy. However, the ability to measure fire intensity, know as fire radiative power (FRP), and its potential relationships to meteorology and smoke plume injection heights, are currently limited by the pixel resolution. This dissertation describes the development of a new, sub-pixel-based FRP calculation (FRP_f) for fire pixels detected by the MODerate Resolution Imaging Spectroradiometer (MODIS) fire detection algorithm (Collection 5), which is subsequently applied to several large wildfire events in North America. The methodology inherits an earlier bi-spectral algorithm for retrieving sub-pixel …

Automation Of Landmark Selection For Rodent Brain Mri-Histology Registration Using Thin-Plate Splines, Ayan Sengupta

School of Computing: Dissertations, Theses, and Student Research

Image registration is the process of aligning two different images of the same object taken at different times, at different orientations or using different instruments. This is common in medical applications since multiple modalities are used to image different parts of the body. This is an important early step in many diagnostic procedures such as change detection, monitoring tumor or quantifying spread of a disease. The widely used landmark based registration approach is tedious, time consuming, inconsistent and error prone. Furthermore, the standard schemes based on rigid and affine transformation can only describe global geometric differences between the objects of …

Simulation, Development And Deployment Of Mobile Wireless Sensor Networks For Migratory Bird Tracking, William P. Bennett Jr.

School of Computing: Dissertations, Theses, and Student Research

This thesis presents CraneTracker, a multi-modal sensing and communication system for monitoring migratory species at the continental level. By exploiting the robust and extensive cellular infrastructure across the continent, traditional mobile wireless sensor networks can be extended to enable reliable, low-cost monitoring of migratory species. The developed multi-tier architecture yields ecologists with unconventional behavior information not furnished by alternative tracking systems at such a large scale and for a low-cost. The simulation, development and implementation of the CraneTracker software system is presented. The system is shown effective through multiple proxy deployments on wildlife and has been operational for 10 months …

Palantir: Early Detection Of Development Conflicts Arising From Parallel Code Changes, Anita Sarma, D F. Redmiles, Andre Van Der Hoek

School of Computing: Faculty Publications

The earlier a conflict is detected, the easier it is to resolve—this is the main precept of workspace awareness. Workspace awareness seeks to provide users with information of relevant ongoing parallel changes occurring in private workspaces, thereby enabling the early detection and resolution of potential conflicts. The key approach is to unobtrusively inform developers of potential conflicts arising because of concurrent changes to the same file and dependency violations in ongoing parallel work. This paper describes our research goals, approach, and implementation of workspace awareness through Palantır and includes a comprehensive evaluation involving two laboratory experiments. We present both quantitative …

Routing Over The Interplanetary Internet, Joyeeta Mukherjee

School of Computing: Dissertations, Theses, and Student Research

Future space exploration demands a Space Network that will be able to connect spacecrafts with one another and in turn with Earth's terrestrial Internet and hence efficiently transfer data back and forth. The feasibility of this technology would enable common people to directly access telemetric data from distant planets and satellites. The concept of an Interplanetary Internet (IPN) is only in its incubation stage and considerable amount of common standards and research is required before widespread deployment can occur to make IPN feasible.

We provide a comprehensive survey that presents a picture of the current space networking technologies and architectures. …