Ordered alphabetically by student's last name
Baldwin |
Davis, C | Loughery | Shall |
Barber | Enslen |
Malik | Varnell |
Bose | Habimana-Griffin | Maxey | White |
Cobb | Hopkins | Pedersen |
Investigating Data Models for Automatically Generating Tests for Web Applications Katie Baldwin1, Camille Cobb2, Carrie Hopkins2, Sara Sprenkle2, and Lori Pollock1 1University of Delaware, 2Washington and Lee University Web applications must be
dependable as the number and popularity of web applications increases,
and people become more dependent on them. Web applications are
difficult and expensive to test because of the large input space and
frequent changes. Thus, their characteristics demand an efficient
and effective way of automating the test case generation process.
Current approaches to automatic test case generation for web
applications do not attain all the goals of representing user behavior,
maintaining good code coverage, and reducing the number of test
cases. This research is based on Sant et al.’s user-session-based
test case generation approach, which applies statistical language
learning algorithms to create control and data models, where a control
model represents the possible URL sequences and the data model
represents the possible parameter values. Through analyzing user
sessions, we identify factors that impact values in user sessions, and
use these results to develop a set of data models for automatic test
case generation. This research is sponsored by the CRA-W.
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Hybrid polymer-peptide hydrogels for vocal fold tissue engineering Kathryn I. Barber1, Sarah E. Grieshaber2, and Xinqiao Jia2 1Department of Materials Science and Engineering, Pennsylvania State University and 2Department of Engineering Science and Mechanics, University of Delaware One of the challenges in the
growing field of tissue engineering is the method of successfully
imitating the extracellular matrix (ECM) in which the cells grow and
live. The development of tunable scaffolds is needed to mimic the
morphological, biological, and mechanical properties of the natural ECM
for vocal fold tissue regeneration. The dual nature of hybrid
natural-synthetic polymer hydrogels holds great potential for these
applications because the peptide segments allow control over
structural assembly and biological properties, while the synthetic
polymer domains provide greater tunability and improved mechanical
properties. RGD-containing elastin-mimetic peptides were
synthesized and crosslinked with vinyl sulfone-functionalized Pluronic
F-127 to serve as scaffolds for vocal fold fibroblasts (VFFs).
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Synthesis and Characterization of Block Copolymer Nanoparticles for Controlled Release of Cancer Therapeutics Aditya Bose, Xiaoying Wang, and Xinqiao Jia Department of Materials Science and Engineering The focus of this research is
to synthesize block copolymer nanoparticles that can be utilized as
delivery vehicles for anticancer drugs. Amphiphilic block copolyesters
carrying pendant cyclic ketal or ketone groups were synthesized by ring
opening copolymerization of ε-caprolactone (CL) and 2-Oxepane-1,5-dione
(OPD) using methoxy poly(ethylene glycol) (mPEG) as the initiator and
stannous octoate (Sn(Oct)2) as the catalyst. Ureido-4-pyrimidones (UPY)
was subsequently conjugated to the copolymers through the pendant
ketone groups in the hydrophobic block. The polymer composition and
molecular weight were characterized using proton nuclear magnetic
resonance (1H NMR) and gel permeation chromatography (GPC),
respectively. Dexamethasone was encapsulated in the block
copolymer nanoparticles by a nanoprecipitation procedure. Particle size
and size distribution were analyzed by dynamic light scattering (DLS)
and the drug encapsulation and release were monitored using high
performance liquid chromatography (HPLC). Our preliminary results show
that the custom-designed block copolymers exhibit relatively high drug
encapsulation efficiency and tunable release kinetics. We are
evaluating the potentials of these nanoparticles in the treatment of
childhood leukemia.
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Adsorption and Reduction of 2,4-dinitroanisole (DNAN) using Graphitic Black Carbon Craig Warren Davis and Pei C. Chiu Nitro-aromatic compounds (NACs)
such as DNAN (2,4-dinitroanisole) are common explosives and
environmental contaminants, particularly in soil and groundwater
systems. Reduction of NACs in aqueous media is generally slow,
due to the high activation energy involved. However, recent work
has shown that reduction of NACs can be greatly accelerated in the
presence of graphitic black carbon (i.e., carbon left behind from
combustion process that has undergone structural changes due to the
high heat and pressure involved in combustion). This study was
undertaken to investigate the reduction of DNAN catalyzed by graphite
(a model black carbon) in the presence of H2S (a common reductant in
anaerobic environments). We hypothesize that graphite serves a
dual role in this process. First, graphite (surface area ≈ 200 m2/g)
may act as a strong adsorbent and rapidly removes DNAN molecules from
the aqueous phase. Secondly, graphite is conductive and hence may
facilitate electron transfer from H2S to DNAN, effectively acting as a
redox catalyst. To date, we have evaluated the sorptive
capability of graphite in artificial groundwater. Reactors were
set up and aqueous samples were taken at predetermined times.
Samples were analyzed using a high performance liquid chromatograph
(HPLC) and quantified based on DNAN calibration standards. Next, we
plan to evaluate the extent and rates of DNAN adsorption and reduction
with graphite under reducing conditions. The ultimate goals of
this work are to understand the reaction pathway and mechanism and to
develop kinetic and equilibrium models to describe the reduction and
adsorption processes.
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Mining
Source Code to Automatically Split Identifiers for Software Analysis
Eric Enslen, Emily Hill, Lori Pollock, and K. Vijay-Shanker Department of Computer and Information Science Automated software analysis
tools and recommendation systems increasingly rely on natural language
information from comments and identifiers in code. The first step in
analyzing words from identifiers requires splitting identifiers into
their constituent words. Unlike natural languages, where space and
punctuation are used to delineate words, identifiers cannot contain
spaces. One common way to split identifiers is to follow programming
language naming conventions. For example, Java programmers often use
camel case, where words are delineated by uppercase letters or
non-alphabetic characters. However, programmers also create identifiers
by concatenating sequences of words together with no discernible
delineation, which pose challenges to automatic identifier splitting.
/ / In this paper, we present an algorithm to automatically split
identifiers into sequences of words by mining the frequency of potential
substrings from source code. With these word frequencies, our identifier
splitter uses a scoring technique to automatically select the most
appropriate partitioning for an identifier. In an evaluation of over
8000 identifiers from open source Java programs, our Samurai approach
outperforms the existing state of the art techniques.
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Preparation of HA-Pln DIV Conjugates Hydrogel LeMoyne Habimana-Griffin1, Chao Liu2, Xinqiao Jia2 1Rose-Hulman Institute of Technology, 2Department of Materials Science and Engineering, University of Delaware Photo-cross-linkable,
mechano-responsive hydrogels have the potential to serve as a minimally
invasive mean to regenerate vocal fold tissue in vivo. In particular,
glycidyl methacrylate (GMA) functionalized hyaluronic acid(HA) –based
hydrogels have shown great potential as vocal fold tissue
scaffolds. However, without infrastructure within the gel to
support cell adhesion, the cells with merely fall of the gel. But the
incorporation of an immunoglobulin sequence in perlecan domain IV
peptide, which has recently been found to support cell adherence, will
allow the cells to stick to the gel. Nevertheless, highly toxic
catalysts used in the synthesis of the gel, such as
dimethylaminopyridine (DMAP), can interact with the HA-GMA and become
trapped in the polymer during precipitation. We present a novel
method to purify the HA-GMA hydrogel. Using this method we were
able to eliminate most all of the DMAP, as confirmed by nuclear
magnetic resonance spectroscopy. This project was funded by the
National Science Foundation.
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Extraction of Lipids from Wastewater Microorganisms for Biodiesel Fuel Production Scott R. Loughery, Nathan S. Kiracofe, and Daniel K. Cha Department of Civil and Environmental Engineering Natural fatty acids from
wastewater activated sludge and Nocardia Amarae foam were extracted and
analyzed for the purpose of converting these lipids into biodiesel
fuel. Special attention was paid to the Nocardia bacterial
foam. Because the Nocardia species has a filamentous cell
structure, a higher oil yield was expected. Lipids from
microorganisms can be converted into fuel sources by a process known as
transesterification. This process involves converting
triglyceride molecules found in cellular lipids into fatty acid methyl
esters (FAME). The FAME can be burned as a diesel fuel
source. The conversion of a triglyceride molecule into FAME is
triggered by the addition of an organic carbon source at a moderately
high temperature. A hexane/methanol solvent was used as the
organic carbon source. Activated sludge and Nocardia foam were
retrieved from several different aeration basins from the Wilmington
Wastewater Treatment Plant, where they were then oven-dried to remove
moisture and stored in preparation for extraction. The FAME
process involved transesterifying the samples with methanol/sulfuric
acid, extracting the samples with hexane, separation of the biomass and
organic solvent layers by centrifuge, and removal and evaporation of
the organic solvent. The composition of the samples after
undergoing this process was a dark oil. The specific oil yield of
our samples were typically between 10 and 20 percent by mass.
These yields compare favorably to other common biodiesel sources such
as soybean oil, peanut oil, and algae and help to show that wastewater
bacteria can be a viable source of diesel fuel. Research funded
by the Science and Engineering Scholars Program and the University of
Delaware Undergraduate Research Program.
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Applying a Software Word Usage Model (SWUM) to Other Languages Sana Malik, Emily Hill, Lori Pollock, and K. Vijay-Shanker Computer and Information Sciences With program code growing
larger and larger, software developers need more support, especially
for software maintenance. Currently, there are many automatic and
semi-automatic tools meant to expedite software maintenance; however,
most of these tools rely solely on the structural model of the program,
while disregarding any semantic information from the natural language
used by programmer. Our previous work towards solving this problem
involves a general Software Word Usage Model (SWUM). Unlike other
software maintenance tools that use lexical concepts (the function or
meaning of a word), SWUM looks for and applies linguistic relations
between these lexical concepts to form a more complete interpretation
of the program. Although SWUM is capable of representing
all programming languages, its current implementation is limited to
Java. The potential structural, semantic, and syntactic differences
with other languages must be examined to generalize SWUM beyond a
single language. In this paper we analyze the differences between Java
and C++, modify the SWUM construction algorithm to work for C++, and
evaluate the accuracy of the phrases it generates for C++.
This project is sponsored by the CRA-W DREU program.
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Detection of Structural Damage using Thermal Imaging Joseph Maxey, Mary Marchegiano, Robert Hunsperger, Michael Chajes, and Erik G. Kunz Departments of Electrical & Computer Engineering and Civil & Environmental Engineering Major problems in bridge
collapses are due to flaws in its structure. NASA’s space exploration
and aeronautics also can have difficulties due to material flaws. This
paper presents a method for detecting hidden flaws in structures and
materials by thermal imaging. The idea is to use a thermal imaging
camera to detect flaws in some samples of materials, including steel
strands, and a composite piece made of e-glass with epoxy resin. A
crack was put into the steel strand and a cut was put into the
composite piece. Natural corrosion was present on another steel strand.
The flawed regions should heat faster because their resistance is more
than that of the non-flawed region, which follows from a Law of Heat
Transfer. Electrical current was used in the steel strands to heat them
and to detect the cut on one strand, and the corrosion on the other
strand, while thermal induction was used to heat the composite piece.
Results from the thermal camera did indeed show the flaws having a
higher temperature than their surroundings. This may means that
structure damage can be detected by thermal imaging early enough to
prevent catastrophes. The NASA Space Program sponsored this work.
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Implementation of a Correlation Algorithm on the Cyclops-64 Architecture Jeremy Pedersen, Juergen Ributzka, Guang R. Gao Computer Architecture and Parallel Systems Laboratory (CAPSL) There has been a shift in radio
astronomy away from the use of large dishes and towards the use
of arrays of smaller antennas. This requires that large amounts
of sample data be cross correlated to generate useful signals.
Cross correlation is an I/O intensive operation at 1 FLOP per byte
loaded from memory. Since large antenna arrays like SKA and LOFAR will
generate massive amounts of data (in the case of LOFAR it is 100 TB per
day), an efficient means of processing this data in real-time is
required. Computer architectures with large amounts of on-chip memory
and enough parallelism to truly take advantage of the embarrassingly
parallel nature of the correlation algorithm are needed. Cyclops-64,
with its 5 MB of on chip SRAM and 160 Thread Units (TU) is a great
candidate for this task. Because Cyclops-64's on-chip SRAM is not a
cache, but is user managed, clever use of this space can overlap memory
loads and stores with computation, and increase the number of
arithmetic operations performed per byte loaded from memory. We look
first at a naíve implementation of the correlation algorithm,
and then at a more sophisticated implementation in which a ring buffer
is set up in SRAM for storing sample data to be correlated, allowing
correlations to be performed by some threads while others do fetches
from main memory into on-chip memory.
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Towards Generating Useful Comments for Program Code Jonathan Schall, Giriprasad Sridhara, Emily Gibson Hill, Lori Pollock, K. Vijay Shanker Department of Computer and Information Science With the use of 60-90% of software cycle resources being used on program maintenance, there is a call for automated software tools that help software engineers explore and comprehend today’s large and complex computer programs. Modern software tools often ignore the lexical information contained in comments, identifiers, and program structure. My work involves identifying the useful information in computer programs (both structure and naming conventions) that can be used to automatically generate useful English-like comments. To this end, I analyzed program code information for appropriateness for generating comments. I compared this code information with real programmer-written comments and identified the program structure information that helps to correct discrepancies between the programmer-written comment and the automatically extracted phrases. I documented the relevant program code information, natural language comment, along with the parts of the program structure I found useful. My research suggests that the assignment operator, looping structures, and the naming of classes and methods are useful in automatically generating useful natural language comments for software maintainers. |
Fiber optic cables are used to
create simple sensors that can detect problems in hidden places like
inside bridge supports or landfills. There are several reasons
why fiber optic sensors are different than other sensors. They
are less expensive than other systems because the materials they are
made from (glass or plastic) are readily available. Also, fiber
optics are not effected by electronic interference (like lightning). To
make the sensor that we have investigated, the fiber optic cable is
shaped into several tight loops. If the loops are tight enough, some of
the light traveling through the fiber will escape. The loops must
be tight enough to let light out so that it can sense the surroundings,
but not too tight or almost all of the light will escape. The
amount of light that escapes from the loops depends on what is
around the fiber, which allows the sensor to detect the amount of water
or chloride present. This information would be used to determine
if the correct amount of water is in a landfill or how much water and
chloride are present inside a bridge support. The presence of
water or chloride would indicate that there is a danger of
corrosion. Funded by the Undergraduate Research Program at
University of Delaware
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In recent years, cost-effective
and environmentally friendly sources of energy have become increasingly
important for research and development. Solid oxide fuel cells
(SOFCs), which release energy from a fuel using oxygen as the oxidant,
have great potential for efficiency and minimal carbon emissions.
Current SOFCs utilize ceramic electrolytes, such as yttria-stabilized
zirconia (YSZ) and gadolinium-doped ceria (GDC), that conduct oxygen at
high temperatures (over 600°C) through vacancies in their crystal
structures. Solid-state electrolytes that conduct oxygen as
crystalline interstitials instead of vacancies were synthesized and
characterized in an effort to produce improved ceramics for use in
SOFCs. The K2NiF4 structure, known for its high concentration of
interstitial defects, is the target configuration for the new
ceramics. X-ray powder diffractometry has revealed moderate
success in obtaining the structure for several of the different
ceramics.
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