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Digital Library Education in Computer Science Programs
Get PDFIn an effort to identify the “state of the art†in digital library
education in computer science (CS) programs, we analyzed CS
courses on digital libraries and digital library-related topics.
Fifteen courses that mention digital libraries in the title or short
description were identified; of these, five are concerned with
digital libraries as the primary topic of the course. The readings
from these five courses were analyzed further, in terms of their
authors and the journals in which they were published
Compositional Mining of Multi-Relational Biological Datasets
Get PDFHigh-throughput biological screens are yielding ever-growing streams of
information about multiple aspects of cellular activity. As more and more
categories of datasets come online, there is a corresponding multitude of ways
in which inferences can be chained across them, motivating the need for
compositional data mining algorithms. In this paper, we argue that such
compositional data mining can be effectively realized by functionally cascading
redescription mining and biclustering algorithms as primitives. Both these
primitives mirror shifts of vocabulary that can be composed in arbitrary ways
to create rich chains of inferences. Given a relational database and its
schema, we show how the schema can be automatically compiled into a
compositional data mining program, and how different domains in the schema can
be related through logical sequences of biclustering and redescription
invocations. This feature allows us to rapidly prototype new data mining
applications, yielding greater understanding of scientific datasets. We
describe two applications of compositional data mining: (i) matching terms
across categories of the Gene Ontology and (ii) understanding the molecular
mechanisms underlying stress response in human cells
Assessing the Utility of a Personal Desktop Cluster
Get PDFThe computer workstation, introduced by Sun Microsystems in 1982, was the tool of
choice for scientists and engineers as an interactive computing environment for the development
of scientific codes. However, by the mid-1990s, the performance of workstations
began to lag behind high-end commodity PCs. This, coupled with the disappearance of
BSD-based operating systems in workstations and the emergence of Linux as an opensource
operating system for PCs, arguably led to the demise of the workstation as we
knew it.
Around the same time, computational scientists started to leverage PCs running
Linux to create a commodity-based (Beowulf) cluster that provided dedicated compute
cycles, i.e., supercomputing for the rest of us, as a cost-effective alternative to large
supercomputers, i.e., supercomputing for the few. However, as the cluster movement
has matured, with respect to cluster hardware and open-source software, these clusters
have become much more like their large-scale supercomputing brethren — a shared
datacenter resource that resides in a machine room.
Consequently, the above observations, when coupled with the ever-increasing performance
gap between the PC and cluster supercomputer, provide the motivation for a
personal desktop cluster workstation — a turnkey solution that provides an interactive and parallel computing environment with the approximate form factor of a Sun SPARCstation
1 “pizza box†workstation. In this paper, we present the hardware and software
architecture of such a solution as well as its prowess as a developmental platform for parallel codes. In short, imagine a 12-node personal desktop cluster that achieves 14 Gflops on Linpack but sips only 150-180 watts of power, resulting in a performance-power ratio that is over 300% better than our test SMP platform
Remote Usability Testing Methods a la Carte
Get PDFAlthough existing lab-based formative usability testing is frequently and effectively applied to improving usability of software user interfaces, it has limitations that have led developers to turn to remote usability evaluation methods (RUEMs) to collect formative usability data from daily usage by real users in their own real-world task environments.
The enormous increase in Web usage, where users can be isolated and the network and remote work settingbecome intrinsic parts of usage patterns, is strong motivation for supplementing lab-based testing with remote usability evaluation methods. Another significant impetus for remote evaluation is the fact that the iterative development cycle for any software, Web application or not, does not end with initial deployment. We review and informally compare several approaches to remote usability evaluation with respect to quantity and quality of data collected and the effort to collect the data
ReSHAPE: A Framework for Dynamic Resizing and Scheduling of Homogeneous Applications in a Parallel Environment
Get PDFApplications in science and engineering often require huge computational resources for solving problems
within a reasonable time frame. Parallel supercomputers provide the computational infrastructure
for solving such problems. A traditional application scheduler running on a parallel cluster only supports
static scheduling where the number of processors allocated to an application remains fixed throughout
the lifetime of execution of the job. Due to the unpredictability in job arrival times and varying resource
requirements, static scheduling can result in idle system resources thereby decreasing the overall
system throughput. In this paper we present a prototype framework called ReSHAPE, which supports
dynamic resizing of parallel MPI applications executed on distributed memory platforms. The framework
includes a scheduler that supports resizing of applications, an API to enable applications to interact
with the scheduler, and a library that makes resizing viable. Applications executed using the ReSHAPE
scheduler framework can expand to take advantage of additional free processors or can shrink to accommodate
a high priority application, without getting suspended. In our research, we have mainly focused
on structured applications that have two-dimensional data arrays distributed across a two-dimensional
processor grid. The resize library includes algorithms for processor selection and processor mapping.
Experimental results show that the ReSHAPE framework can improve individual job turn-around time
and overall system throughput
Multirate explicit Adams methods for time integration of conservation laws
Get PDFThis paper constructs multirate linear multistep time discretizations based on Adams-Bashforth methods. These methods are aimed at solving conservation laws and allow different timesteps to be used in different parts of the spatial domain. The proposed family of discretizations is second order accurate in time and has conservation and linear and nonlinear stability properties under local CFL conditions. Multirate timestepping avoids the necessity to take small global timesteps - restricted by the largest value of the Courant number on the grid - and therefore results in more efficient computations. Numerical results obtained for the advection and Burgers' equations confirm the theoretical findings
A Modiï¬ed Uniformization Method for the Solution of the Chemical Master Equation
Get PDFThe chemical master equation is considered an accurate description of general chemical systems, and especially so for modeling cell cycle and gene regulatory networks. This paper proposes an efficient way of solving the chemical master equation for some prototypical problems in systems biology. A comparison between this new approach and some traditional approaches is also given
Uncertainty Quantification and Apportionment in Air Quality Models using the Polynomial Chaos Method
Get PDFSimulations of large-scale physical systems are often affected by the uncertainties in data, in model parameters, and by incomplete knowledge of the underlying physics. The traditional deterministic simulations do not account for such uncertainties. It is of interest to extend simulation results with ``error bars'' that quantify the degree of uncertainty. This added information provides a confidence level for the simulation result. For example, the air quality forecast with an associated uncertainty information is very useful for making policy decisions regarding environmental protection. Techniques such as Monte Carlo (MC) and response surface are popular for uncertainty quantification, but accurate results require a large number of runs. This incurs a high computational cost, which maybe prohibitive for large-scale models. The polynomial chaos (PC) method was proposed as a practical and efficient approach for uncertainty quantification, and has been successfully applied in many engineering fields. Polynomial chaos uses a spectral representation of uncertainty. It has the ability to handle both linear and nonlinear problems with either Gaussian or non-Gaussian uncertainties.
This work extends the functionality of the polynomial chaos method to Source Uncertainty Apportionment (SUA), i.e., we use the polynomial chaos approach to attribute the uncertainty in model results to different sources of uncertainty. The uncertainty quantification and source apportionment are implemented in the Sulfur Transport Eulerian Model (STEM-III). It allows us to assess the combined effects of different sources of uncertainty to the ozone forecast. It also enables to quantify the contribution of each source to the total uncertainty in the predicted ozone levels
Multirate timestepping methods for hyperbolic conservation laws
Get PDFThis paper constructs multirate time discretizations for hyperbolic conservation laws that allow different time-steps to be used in different parts of the spatial domain. The discretization is second order accurate in time and preserves the conservation and stability properties under local CFL conditions. Multirate timestepping avoids the necessity to take small global time-steps (restricted by the largest value of the Courant number on the grid) and therefore results in more efficient algorithms
Education and Design: Using Human-Computer Interaction Case Studies to Learn
Get PDFComputers are essentially an ever-present tool that can be used in almost any discipline to make work faster and easier. Creating these programs, however, such that they fulfill the needs of the customer is a challenging process given the uniqueness of the discipline and circumstance. Thus, the use of a programming design methodology can enable the computer program designer to create a better system that meets the needs of the customer. Teaching this process, or in essence how to design, is the focus of this work. In this paper we present how using case studies in Human-Computer Interaction, and more specifically displaying the evolution of a case study, increases a designer’s ability to learn and then apply this knowledge. We investigate how to use this design evolution within case studies and the effects it had on application, while also exploring how case studies can be used in educating computer scientists