Fifth Annual Sigma Xi Research Day
Monday, April 7, 2003
5:00 - 7:00 p.m.
Susquehanna Room, Hadley Union Building
Sponsored by:
Sigma Xi, Indiana University of Pennsylvania Chapter
Dean, College of Natural Sciences and Mathematics, Indiana University
of Pennsylvania
- Factors of freshman retention
- The effect of polarity on hydrogen bond energies
involving imidazole
- Critical current of low pressure heat-converted
YBCO
- Phosphorylation of insulin and its effect on insulin-sensitive
glucose uptake in 3T3-L1 adipocytes
- Real and ideal: Alcohal use and its perceived effects
on personal traits
- Survey of movie patronage
- New light-emitting polymers
- Television consumption
- Provenance and transport mechanisms of terrigenous
sediment delivered to Atlantic Ocean basins
- Determinants of domestic box office success
- A breath of fresh air; components of GSP and emissions
levels
- School expenditures, student performance, and
the Tiebout hypothesis: Are citizens 'voting with their feet?'
- Determinants of property crime rates: Sociological
and economic variables
- An Improved Tidal Actuator for the LIGO Interferometers
- The relationship of hyperfemininity to problematic
drinking, sexual experiences and attitudes in undergraduate women
- Long-term predictions of global climate using
the ocean conveyor
- Techniques for identifying and eliminating Trojan
horses
- New economic geography: The lessening role of
geographic isolation on economic growth
- Modeling the geometry of AX3E and AX2E2
molecules through non-bonded repulsions
- Snort intrusion detection system
- Estimating labor force participation rates for
each county in Pennsylvania using panel data
- Research on creating webs of trust-for encrypted
email
- Effects of composition on the far infrared reflectivity
and Raman scattering in n-type AlxGa1-xAs layers and GaAs/AlGaAs
superlattices
- Determinants of political participation in the
United States
- Advantages of teaching x-ray powder diffraction
in science education
- Stock Market Data Analysis Using Rescaled Range
(R/S) Analysis Method
- Stock Market Data Analysis with Relative Dispersion
Based Hurst Exponent
- Internet Usage Among Indiana University of Pennsylvania
Students
Alphabetical List of Authors
Justin Aion (1)
Thomas Baker (2, 19)
Jessica Clapper (9)
N. Early (3)
Abid A. Fakhri (4)
D. J. Fleming (6)
Miranda Garay (5, 15)
Kayla Griffith (6)
Jason Gruber (26)
Boonta Hetayothin (8)
TJ Isenberg (9)
Kevin Jones (7)
Pamela Kahler (19)
Jason Kelley (10)
James Kelly (6)
Floyd L. Klavetter (8)
Mileah Kay Kromer (11)
Thomas Kruise (12)
Aaron Krznaric (9)
Charles H. Lake (25)
Robert Leasure (9)
D. Lee (3)
K. Leonard (3)
F. List (3)
Matthew K. Marcus (28)
P.M. Martin (3)
Kenneth McDermott (13)
Heather Partner (14)
Haley J. Pavlikowski (28)
Chris Perry (15)
Tim Rainey (6)
Patrick C Ray (16)
Michael Rhoades (17)
Laurie Roehrich (5, 15)
Micah Savidge (18)
Ronald See (19)
Matthew Selnekovic (27)
Mohan Shan (26)
Daniel Sloppy (23)
Aaron Stanley (6)
Sarah Stroman (20)
Brian Strohecker (21)
Devki N. Talwar (23)
Wendy Trosky (9)
Russell Urban (22)
Maria A. Valero (28)
Robert L. Viégas (24)
Brian M. Wargo (25)
Michelle Wilkins (5, 15)
Stephen Wolfe (28)
J. Yoo (4)
Abstracts
Author: Justin Aion <ntjj@iup.edu>
Economics Department, Indiana University of Pennsylvania
This paper is a study into retention factors of first year students
at various universities. Schools in the sample include both public,
and private universities and colleges from all over the country.
It looks at many characteristics of incoming freshman classes. Ordinary
least squares was used in this analysis. Results indicate that retention
was highly positively correlated with the log of the entering cohort.
Retention is also positively correlated with the percentage of freshman
who are 24 years old or older as well as the average SAT score of
the incoming class. The percentage of freshman who received less
that 2.0 for their first term negatively affected the retention
rate. The results also indicate that tuition upon first year of
admissions is also an important factor.
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Author: Thomas Baker <hyfk@iup.edu>
Chemistry Department, Indiana University of Pennsylvania
The effects of a polar medium on the energies of hydrogen bonds
involving imidazole were investigated by molecular orbital calculations
at the B3LYP/6-31G* level. A hydrogen bond from imidazole to Fe-bound
O2 may be an important factor in the stabilization of
)2, relative to CO, in the active site of myoglobin. The gas-phase
hydrogen bond energy on the complex im
Fe(por)(im)(L) was calculated
to be 37 kJ/mol when L = O2, and about 18 kJ/mol when
L = CO or NO; this difference in gas-phase hydrogen bond stabilization
energy (~19 kJ/mol) is too large for the observed effect of the
protein on ligand binding. However, gas-phase calculations may not
be entirely realistic for the active site of a protein. SCI-PCM
is a technique that allows the orbital calculation. Unfortunately,
SCI-PCM did not work for metals, so H2O, (NH2)O
and SO were used in place of the Fe-bound O2. It was
found that, with all three acceptors, the hydrogen bond energy decreased
with increasing polarity of the calculation. The implications of
these results for ligand stabilization in myoglobin will also be
discussed.
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Authors: N. Early1 <xkmh@iup.edu>,
P.M. Martin2, D. Lee2, F. List2, J. Yoo3,
K Leonard3
Physics Department, Indiana University of Pennsylvania1,
ORNL M&C2, ORISE3
Characterizations of critical current density (Jc) dependence on
the thickness of the compound superconductor Yttrium Barium Copper
Oxide are investigated. In 1996, ORNL premiered Rolling Assisted
Biaxially Textured Substrates (RABiTS ), a technique for the growth
of chemically and physically compatible substrate and buffer layers.
YBCO precursor is deposited reel-to-reel by electron beam co-evaporation
and heat converted to form crystal YBa2Cu3O7-x.
Thicker deposition layers are found to be correlated with higher
current Ic but unfortunately lower Jc. Selected
thicknesses (0.3 mm-3.0 mm)
of YBCO were grown and then analyzed with q-2q
XRD for the presence and intensity of randomly oriented grain defects.
77oK transport critical current was measured along the
length of the tape at ½ cm intervals under selected magnetic
field intensities. Critical currents in excess of 100 amps were
reported.
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Author: Abid A. Fakhri <abidfakhri@hotmail.com>
Biology Department, Indiana University of Pennsylvania
Since its discovery by F.G. Banting and C.H. Best in 1929, insulin
has been used worldwide in the treatment of diabetes mellitus. Unfortunately,
a common side effect of this treatment is low levels of blood glucose,
a condition known as hypoglycemia. Previous studies have demonstrated
that the phosphorylation of hydroxyl groups on tyrosine, serine,
and threonine residues in the insulin polypeptide can prevent hypoglycemia.
Exactly how these extra phosphate groups affect glucose uptake has
not yet been demonstrated. This study was intended to investigate
the possibility that phosphorylation inactivates the insulin molecule,
and that a glucose-sensitive phosphatase on the surface of target
cells activates the insulin by cleaving the phosphate group(s).
In order to test for a glucose-sensitive phosphatase, 3T3-L1 adipocytes
were exposed to paranitrophenylphosphate (PNPP) in the presence
of low and high concentrations of D-glucose; absorbance of samples
at 410nm would indicate phosphatase activity. To study its effects
on glucose uptake, phosphorylated insulin was synthesized by the
addition of small quantities of POCl3 under cold, aqueous
conditions. The extent of phosphorylation was assed by electrophoresis.
The ability of phosphorylated insulin to stimulate glucose uptake
in 3T3-L1 adipocytes was compared to normal insulin at both low
and high glucose concentrations; in these experiments, glucose uptake
was monitored using 2-deoxy-[3H]-glucose. Based on the
predicted mechanism, we expected to see insulin stimulation of uptake
at high, but not low glucose concentrations for phosphorylated insulin
but at both low and high glucose concentrations for regular insulin.
Indeed, observation of this predicted activity pattern in certain
cases provided supportive evidence for a glucose-dependant phosphatase
associated with the insulin receptor; however, the lack of a consistent
response to insulin in cell cultures suggests that a further understanding
of the system is necessary before making conclusions.
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Authors: Miranda Garay <vnzh@iup.edu>,
Michelle Wilkins <rtzh@iup.edu>,
and Dr. Laurie Roehrich <roehrich@iup.edu>
Psychology Department, Indiana University of Pennsylvania
Hypotheses that individuals with discrepancies between real and
ideal self-ratings on characteristics of high importance would reflect
what an individual expects to achieve when consuming alcohol, and
that those with high discrepancies would drink more, were studied.
Alcohol expectancies were measured with the Alcohol Expectancy Questionnaire,
and drinking levels by the QFVI and AUDIT. There was a significant
correlation between alcohol expectancies and drinking levels; no
significant correlation was found between drinking levels and trait
discrepancies.
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Authors: Kayla Griffith <mhmj@iup.edu>,
Aaron Stanley <qdmj@iup.edu>,
D. J. Fleming <dkhh@iup.edu>,
Tim Rainey, and James Kelly <mlsh@iup.edu>
Economics Department, Indiana University of Pennsylvania
The purpose of this research is to study student's movie habits.
We surveyed two different Priniciple of Economics classes in order
to gather data with four main research questions in mind. The four
questions that we were seeking to answer were: How does the amount
of a student's free time affect his/her movie viewing habits? How
do students' movie habits change depending on the time of year?
How does a student's income affect his/her movie habits? How are
students' movie viewing patterns related to demographic characteristics?
With these questions asked in various ways through our survey we
hope to enlighten people about movie patronage on the IUP campus.
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Author: Kevin Jones <jqgh@iup.edu>
Advisor: Steve Hovan <hovan@iup.edu>
Geoscience Department, Indiana University of Pennsylvania
We have identified that samples downwind from the Sahara-Sahel
region become better sorted with increased distance west of the
North African shoreline. Despite obvious changes in physical characteristics
of sediment there is no statistically significant change in geochemical
composition. Samples from the South Atlantic display a complex mosaic
of varying physical and geochemical characteristics. Scientists
have assumed the mode of sediment transport by making inferences
about sediment grain size fractions or, based on observations of
the modern world. However, few scientists have succeeded in objectively
identifying mode of transport using data inherent to the sediment.
We examined all, or a subset of 84 samples for grain size distributions,
major/minor element geochemical compositions and radiogenic isotope
ratios in an attempt to elucidate mode of transport. Grain size
data shows a steady decrease in the standard deviation of grain
size with distance from the shoreline of North Africa for samples
located within the core of the modern trade winds. Strontium radiogenic
isotope ratios for these samples remain between the values of 0.721
and 0.726, which are consistent with accepted values for the North
African craton (0.714-0.739). Comparison to Pacific eolian studies
suggests that the increased sorting with distance represents an
enhanced eolian dominance. Invariable geochemical data for samples
downwind from this region suggests that both eolian and hemipelagic
material have geochemically similar sources.
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Authors: Boonta Hetayothin <bhetayo@hotmail.com>,
and Floyd L. Klavetter <flklav@iup.edu>
Chemistry Department, Indiana University of Pennsylvania
By using a mixture various derivatives of the fragrant vanilla
molecule ("vanillin"), electrically-conductive polymers
are synthesized utilizing a Wittig condensation reaction. When these
polymers are exposed to current, they glow brilliantly in a normal
well-lit room. Potential uses for these materials include flat-panel
displays and wrap-around flexible light sources. Synthetic methodology
of these polymers is described, and structural characterization
is also provided.
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Authors: TJ Isenberg <vllj@iup.edu>,
Jessica Clapper <yzyh@iup.edu>,
Wendy Trosky <mbrj@iup.edu>,
Aaron Krznaric <cdfk@iup.edu>,
and Robert Leasure <zybj@iup.edu>
Economics Department, Indiana University of Pennsylvania
The purpose of this research is to study students' perceptions
about the use of television. There are three main research questions
we seek to answer with this project: 1. How television usage among
students relates to demographic characteristics. 2. How television
usage among students relates to usage of other forms of media. 3.How
television usage among students relates to VCR and DVD hardware.
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Author: Jason Kelley <skylookspretty@hotmail.com>
Economics Department, Indiana University of Pennsylvania
This paper is a study of the motion picture industry and individual
film gross. Using the top 100 films from the years 1997-2001 as
a sample, final domestic film gross was tested for responsiveness
to numerous independent variables: total budget, various Consumer
Price Index (CPI) levels (gasoline, movie tickets, video/DVD rentals,
television sets, cable television), peak number of screens the film
was shown on during its initial run in theatres, release date, aggregate
critic rating, and various award nominations. The release date dummy
variable showed whether the film release took advantage of any major
vacations, including those found in and around summer, Thanksgiving,
and Christmas. Ordinary Least Squares was used in regression. Results
showed high positive significance in the release date and total
screens variables. The budget variable, hypothesized to be very
significant, was found to be otherwise. The various CPI levels have
thus far proved inconclusive.
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Author: Mileah Kay Kromer <dgdh@iup.edu>
Economics Department, Indiana University of Pennsylvania
In this study the relationship between emissions levels and specific
components of Gross State Product is examined. The independent variables
are components of GSP, namely, total farm production, total transportation
and utility production, total lumber and woods production, and state
population. No evidence is found that emissions levels rise with
the increase of certain pollution-specific areas of economic growth.
Rather, that with the increase in certain areas of GSP, there is
an increase in the number of days that emissions levels were considered
"Good" on the Pollution Standards Index scale. The data
collected is a panel of all 50 states from the years 1997-2000.
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Author: Thomas Kruise <mqvh@iup.edu>
Economics Department, Indiana University of Pennsylvania
This study will use the theory behind the Tiebout Hypothesis to
discuss the quality of schools in the Commonwealth of Pennsylvania.
The data used will be from the 2000-2001 school year gathered by
the Pennsylvania Department of Education, along with other government
organizations. Economic variables used include unemployment rate,
crime rate, and county population figures. The report is to give
support to the hypothesis that schools in suburban area that are
populated with middle and upper class citizens will yield better
outputs because of higher funding.
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Author: Kenneth McDermott <xjkj@iup.edu>
Economics Department, Indiana University of Pennsylvania
This paper estimates the relationship between the rate of property
crime in the United States and various economic and social factors
at that time. Unemployment, percentage change in the CPI, minimum
wage, unemployment, and change in the Gross Domestic Product are
the basis for the economic determinants. Sociological contributors
are college enrollment, divorce rate, high school graduation rate,
teen births, military enlistment, and alcohol consumption. The data
is annual time-series beginning in 1960 and ending in 1998 for the
United States. Initial analysis of the data using the Ordinary Least
Squares model reveals that the state of the economy and society
do have an effect on property crime. Property crime is negatively
related to economic indicators and alternatives to employment and
positively related to the selected social problems.
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Author: Heather Partner <swzh@iup.edu>
Physics Department, Indiana University of Pennsylvania
The Laser Interferometer Gravitational-Wave Observatory (LIGO)
in Hanford, WA attempts to detect theorized gravitational radiation
from space, and has extreme sensitivity requirements. The Earth-tides
due to the moon affect the instrument by changing the lengths of
the 4K-long arms of the interferometer by hundreds of microns. We
correct for this by continually adjusting the frequency of the laser
to cancel the effect. My work involved the assembly and characterization
of an improvement to the apparatus, which changes the laser frequency
by heating and cooling the reference cavity that determines frequency,
and relying on thermal expansion to change its length (and thus
the wavelength).
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Authors: Chris Perry, Michelle Wilkins <rtzh@iup.edu>,
Miranda Garay <vnzh@iup.edu>,
and Dr. Laurie Roehrich <roehrich@iup.edu>
Psychology Department, Indiana University of Pennsylvania
This paper estimates the relationship between the rate of property
crime in the United States and various economic and social factors
at that time. Unemployment, percentage change in the CPI, minimum
wage, unemployment, and change in the Gross Domestic Product are
the basis for the economic determinants. Sociological contributors
are college enrollment, divorce rate, high school graduation rate,
teen births, military enlistment, and alcohol consumption. The data
is annual time-series beginning in 1960 and ending in 1998 for the
United States. Initial analysis of the data using the Ordinary Least
Squares model reveals that the state of the economy and society
do have an effect on property crime. Property crime is negatively
related to economic indicators and alternatives to employment and
positively related to the selected social problems.
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Author: Patrick C Ray <mzkh@iup.edu>
Physics Department, Indiana University of Pennsylvania
Many have attributed the Great Ocean Conveyor as a major driver
of global climate change over millennia as well as a possible explanation
for shorter (multidecadal) oscillations. The conveyor is thought
to have a cycle time on the order of 1000 years, however recent
research has suggested that it is much faster than previously believed
(about 100 years). A faster conveyor leads to the possibility of
the conveyor's role in even shorter oscillations such as the El
Nino/Southern Oscillation (ENSO) and the North Atlantic Oscillation
(NAO). The conveyor is primarily density driven. In this study the
salty outflow of the Red Sea is used to predict its behavior ten
years into the future. A successful model could lead to a long-term
prediction (ten years) of El Ninos, Atlantic hurricane season intensity,
as well as global temperature and precipitation patterns.
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Author: Michael Rhoades <yvqj@iup.edu>
Advisor: Mary Micco <micco@iup.edu>
Computer Science Department, Indiana University of Pennsylvania
Trojan horses can be installed on a computer through an email attachment
intended to be opened by the victim. They are typically disguised
as an appealing message or piece of software. As the user enjoys
the attachment, infection occurs simultaneously and silently. If
a remote control Trojan is installed and initialized on a system,
that computer is now completely open to anyone who knows to connect
to it using the Trojan horse as a server. Because the Trojan is
under the control of the hacker, he can change the port it uses,
the Key it hides under and many other characteristics, making them
extremely hard to eliminate once they have implanted themselves.
Our research has focused on first locating then disassembling the
code used to run these programs. As part of this process, we have
learned a great deal about how they work and the next step of our
research will focus on developing software that can effectively
protect users from these rogue programs.
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Author: Micah Savidge <bqwh@iup.edu>
Economics Department, Indiana University of Pennsylvania
The focus of this paper is the impact of being land-locked on a
nation's GDP, and how through the 1990's the impact has decreased
by the emergence of a larger service sector. Independent variables
such as economic aid as percentage of GDP, the percentage of the
labor force in the service economy, the fertility rate, the percentage
of the population in urban areas, and a dummy variable for being
a coastal nation. The coastal dummy variable will help to determine
how much, if any, a nation's GDP is affected by the lack of access
to international waters and almost negligible transportation costs.
Data was collected through the World Bank's "World Development
Report".
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Authors: Dr. Ronald See <rfsee@iup.edu>,
Thomas Baker <hyfk@iup.edu>,
and Pamela Kahler
Chemistry Department, Indiana University of Pennsylvania
The geometries of the AX3E and AX2E2
molecules vary spectacularly, with the bond (X-A-X) angle ranging
from 91º to 180º. This variation has been explained using
many models (directed valence, VSEPR, perturbation theory, second-order
Jahn-Teller effect, and more), but never satisfactorily or without
exceptions. The ligand close-packing (LCP) model suggests that molecular
geometries are primarily a result of repulsive interactions between
the terminal atoms or groups. In the case of the AX3E
and AX2E2 molecules, there are two sets of
repulsive interactions: the repulsion between two terminal X atoms
or groups; and the repulsion between an X atom (or group) and the
stereochemical nonbonding electrons (lone pairs) on the central
atom A. We have quantified these repulsions using a simple, linear
distance-interaction relationship for both sets of forces. For molecules
with A = N, P, As, O, S or Se and X = H, F, Cl, Br, I, CH3,
CF3, SiH3 or t-butyl, a single linear regression
describes all computational and empirically-observed structures
to a high degree (R2 = 0.99) of accuracy. This strong
correlation, with no significant exceptions, is convincing evidence
that the LCP model correctly models the physical forces that primarily
determine molecular geometry.
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Author: Sarah Stroman <bqpj@iup.edu>
Advisor: Mary Micco <micco@iup.edu>
Computer Science Department, Indiana University of Pennsylvania
This is an expert system developed as an engine that can look for
the signatures of known viruses, worms and other wild life on the
internet. The engine is designed in such a way that you can pass
it the signature of a known virus and it can immediately update
the rules to detect this signature as well. One weakness of this
system is that it depends on the virus or worm using a consistent
signature that consists of certain phrases, the use of specific
ports and a consistent pattern of behavior, such as the order of
the steps it goes through to install itself on the victim's system.
Since attackers are well aware of this, they have taken pains to
randomize the ports used, the phrases, the names of the executables
and the steps they goes through. Our hypothesis is that regardless
of randomization, all viruses exhibit certain abnormal patterns
that are identifiable. We are currently disassembling the Snort
engine and hope shortly to begin testing to see if the exploits
we have obtained do in fact demonstrate repetitive behaviors.
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Author: Brian Strohecker <bds3399@hotmail.com>
Economics Department, Indiana University of Pennsylvania
This paper takes into consideration a few variables related to
the Labor Force Participation Rate, the dependent variable, including
the unemployment rate, average yearly wages, yearly income, yearly
population, work injuries including fatal and nonfatal, the fertility
rate, political party, and the number of children in elementary
school. The panel data included is annual data collected from 1990-2000
for each of the 67 counties in Pennsylvania. Expected results of
the unemployment rate, work injuries, and the fertility rate are
to be negatively related to the dependent variable, while income,
population, and averages wages are expected to show positive relationships
to the dependent variable.
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Author: Russell Urban <ykwk@iup.edu>
Advisor: Mary Micco <micco@iup.edu>
Computer Science Department, Indiana University of Pennsylvania
The problem being worked on is developing effective techniques
for encouraging people to develop webs of trust with whom they can
share encrypted email. This is seen as a major problem in our field.
We know how to protect the privacy of email, but people are just
resisting moving towards using encryption. Our hypothesis is that
we can promote more frequent and more effective use of encryption
through holding key exchange parties, where individuals in the group
get together for a social time and exchange keys and fingerprints
at that time. In our research design we plan to have three classes
of similar students enrolled in beginning programming classes. One
class, the control group will just be asked to use encrypted email
by the professor with a very brief introduction. The second group
will be provided a lecture and hands on lab in the use of encryption,
The third group will be invited to a key party with a hands on component
under the direction of the professor. Food and fun will be involved.
Students will be surveyed before the treatment and again when the
semester is over. During the semester we will track the frequency
and use of encryption among the students and the professor. Our
goal is not only to see if the key parties encourage a more positive
attitude toward the use of encryption but if that behavior persists
once it is initiated with a web of trust.
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Authors: Devki Talwar <talwar@iup.edu>
and Daniel Sloppy <pxfk@iup.edu>
Physics Department, Indiana University of Pennsylvania
Many optoelectronic devices, such as semiconductor laser diodes,
detectors, modulators and non-linear optical devices are based on
multilayered structure composed of various thin homo- or hetero-layers
of different thicknesses and doping levels. The characterization
of electrical and structural parameters, such as layer thickness,
alloy composition of these complex structures has been and still
is a challenge for both experimentalists and theorists. Optical
techniques including Raman scattering and far-infrared spectroscopy
are versatile for examining the semiconductor alloys, multiple-quantum
wells and superlattices (SLs). In this work, we present a comprehensive
study to understand the effects of composition observed in the far-infrared
reflectivity (FIR) and Raman scattering of the coupled plasmon-phonon
modes in n-type AlxGa1-xAs layers and
GaAs/AlGaAs SLs as a function of carrier concentration. The far
infrared reflectance spectra reported from 100 - 450 cm-1
in GaAs/AlxGa1-xAs SLs with different period,
thickness and composition have demonstrated the confinement of optical
phonons in both GaAs and AlGaAs layers. A significant influence
on the FIR spectra of the buffer layer has been observed in the
transparency region between the two 'restrahlen' bands of GaAs and
AlGaAs. The superlattice modes caused by the coupling between LO
phonons and the collective intersubband excitations are also seen
in doped SLs. In the Raman spectra of n-doped AlxGa1-xAs
layers and GaAs/AlGaAs SLs, three branches of the coupled modes
are found whose frequencies and damping depended upon the carrier
concentration and the alloy composition. The coupling of LO phonons
with plasmons caused blue shift in the Raman lines and dramatically
changed its line shapes - the asymmetry of Raman lines was found
opposite to that of the LO phonons. A simple analysis of the IR
reflectivity and Raman data with an iterative method, performed
in the effective medium approximation modified to include the effects
of composition and the anisotropic plasma response in the wells,
has allowed us a very accurate determination of the structural parameters
not only of the superlattice (viz.,carrier concentration,
individual layer thickness, disorder activated polar phonons, total
SL thickness) but also of the buffer layer.
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Author: Robert L. Viégas <qcbj@iup.edu>
Economics Department, Indiana University of Pennsylvania
This paper examines political participation using demographic,
social, and economic indicators. The sample consists of cross-sectional
data from the 2000 national elections across the 50 States and the
District of Columbia. The dependent variable is voter turnout as
a percentage of the voting age population. Semilog Ordinary Least
Squares analysis of the sample suggests that the dependent variable
is positively affected by social indicators, such as education and
race, while demographic and economic variables show little bearing
on political participation.
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Authors: Brian M. Wargo1 and Charles H. Lake2
Physics Department, Freedom Area High School1, Chemistry
Department, Indiana University of Pennsylvania2
Crystallography is relevant to all disciplines of the natural sciences.
Unfortunately the relationship is lost in most undergraduate programs.
Even though textbooks often devote a section to x-ray diffraction,
it is usually skipped by most instructors because they perceive
it as overwhelmingly difficult, time consuming, and mathematically
challenging. We feel that this perception is erroneous.
This ongoing project is designed to allow non-crystallographers
to appreciate the power of XRD and convince them to incorporate
XRD into existing laboratory courses (if the equipment is available).
These exercises primarily target physics, geology, chemistry and
material science undergraduate programs. Students seeking jobs in
the solid state and pharmaceutical industries have a high probability
of encountering powder XRD instrumentation and therefore will benefit
from the experiences gained in these laboratory exercises.
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Authors: Jason Gruber and Mohan Shan
I: Soundararajan Ezekiel
Computer ScienceDepartment, Indiana University of Pennsylvania2
Methods for accessing the fractal characteristics are useful for
non-stationary signals such as stock market data. These signals
which vary apparently irregularly have been considered to be driven
by external parameters. Standard Methods such as Fourier analysis
assume that the signals are stationary in temporal windows. Such
an assumption is inappropriate for stock market data because it
changes constantly. Fractal based methods such as relative dispersional
methods and rescaled range analysis methods do not impose this assumption
and therefore are better suited for this analysis. In this paper,
we use rescaled range analysis to analyze stock market data which
gives statistical insight.
In 1951, Hurst defined a method to study natural phenomena such
as the flow of the Nile River. This method was based on the statistical
assessment of many observations of the natural phenomena. After
studying 800 years of records, Hurst observed that the flow of the
Nile River was not random it was patterned. He defined a constant,
K, which measures the bias of the fractional Brownian motion. In
1968 Mandelbrot defined this pattern as fractal. There are many
algorithms to calculate fractal characteristics such as fractal
dimensions, which is a number that quantitatively describes how
an object fills its space. He renamed the constant K to H in honor
of Hurst. The fractal dimension, D, can be derived from the Hurst
exponent, H, by the relation D = 2 - H. The Hurst exponent gives
a measure of the smoothness of a fractal object where H varies between
0 and 1. A low H value indicates a high level of roughness. This
means the signal almost fills the next higher dimension. A high
value of H indicates a high level of smoothness. This means the
signal fills very little of the next higher dimension. We use H
and D to analyze our stock market data because it has a broad applicability
to signal processing because of its robustness. These parameters
can be calculated by the rescaled range analysis method and it is
useful to distinguish between random and nonrandom data points.
If H equals 0.5, then the data is determined to be random. If the
H value varies between 0 and 0.5, it represents anti-persistence.
This means, if the signal is up/down in the last period then more
likely it will go down/up in the next period. If the H value varies
between 0.5 and 1, this represents persistence; in this case, if
the signal is up/down in the last period, then it is more likely
that in the next period the signal will continue going up/down.
To illustrate our proposed method we applied it to 48 sets of daily
closing prices of various stocks listed from the New York Stock
Exchange and the NASDAQ from January 25, 1988 to January 24, 2003.
We then calculated the H value for each data set and found that
the maximum H value is 0.5928 and the minimum value is 0.4257. Further
we observed that all these values are differing from 0.5, which
shows that the stock market is clearly fractal. We can also measure
how jagged the signal is by using the parameter H. Low H values
represent higher noise, and more random-like, or volatile data,
thus representing a higher risk. A higher H value, on the other
hand, indicates lower noise levels and less randomness, representing
a lower risk. In our observation, GD had the highest H value, while
XOM had the lowest H value. Therefore we would conclude GD less
risky than XOM. However, further experimental analysis needs to
be carried out with different data sources, including international
markets, bonds and mutual funds, commodities, and currency exchanges.
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27. Stock Market Data Analysis with Relative Dispersion Based
Hurst Exponent
Author: Matthew Selnekovic
Advisor: Soundararajan Ezekiel
Computer Science Department, Indiana University of Pennsylvania
Fractal based methods is a new and promising approach for the analysis
of non-stationary signals, such as stock market data. Traditional
Fourier analysis methods assume that the signals are stationary
in temporal windows. Such an assumption is inappropriate for stock
market data because it changes constantly. Fractal based methods
do not impose this assumption and therefore are better suited for
this analysis. In this paper, we present a fractal dimension based
method to analyze stock market data. We use the Hurst exponent to
calculate fractal dimensions and to present experimental results
demonstrating their effectiveness. The results suggest that fractal
based techniques can provide useful information that is not available
from traditional methods. The basic idea is to calculate the Hurst
exponent for a stock market data by using relative dispersional
analysis. The Hurst exponent, H, has a broad applicability to signal
processing because of its robustness. It has a few underlying assumptions
about the signal and it can distinguish between random and nonrandom
signals. If H equals 0.5, then the signal is random. Further, we
can measure the level of noise from H; that is, how much lower H
is from 0.5. There are three different cases of H: i) 0<H<0.5
ii) H=0.5 iii) 0.5<H<1. Case one represents anti-persistence.
This means, if a signal is up in the last period then more likely
it will go down in the next period. Case two represents randomness
that implies the values are uncorrelated. Case three represents
persistence; in this case, if the signal is up in the last period,
then it is more likely that in the next period the signal will continue
going up. The fractal dimension is then derived from the relation
2 - H. To illustrate our proposed method we applied it to 49 sets
of daily closing prices of various stocks listed from the New York
Stock Exchange and the NASDAQ from January 25, 1988 to January 24,
2003. We then calculated the H value for each data set. Since the
H values are differing from 0.5, it shows that the stock market
is clearly fractal. Further, H also measures how jagged the signal
is. Low H values represent higher noise, and more random-like, or
volatile data, thus representing a higher risk. A higher H value,
on the other hand, indicates lower noise levels and less randomness,
representing a lower risk. In our observation, AMD had an H value
of 0.5413, while 3M had an H value of 0.3817. We there for would
conclude AMD less risky than 3M. However, further experimental analysis
needs to be carried out with different data sources, including international
markets, bonds and mutual funds, commodities, and currency exchanges.
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Authors: Matthew K. Marcus, Haley J. Pavlikowski, Maria
A. Valero, Stephen Wolfe
Economics Department, Indiana University of Pennsylvania
In today's society, the Internet has become a key component to
daily life. Its uses are widely varied from communication to entertainment.
Due to its multiple facets, it has become a reliable tool in business,
industry, home usage and education. The realms of higher education
have especially sought to utilize this device's fullest potential.
In order to do this, however, the patterns of a college student's
typical Internet usage must be charted. This research, in accordance
with the Economics Department, seeks to achieve this goal by identifying
common trends in Internet usage among college students at Indiana
University of Pennsylvania (IUP). As a narrower focus, this investigation
looks to determine the most common computer access for available
for IUP students, how much time they spend on the internet per week,
their main purpose for Internet usage and how these ideas correlate
across the demographics of IUP.
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