Computer Sciences Commons^™

Learning About Modeling In Teacher Preparation Programs, Hyunyi Jung, Eryn Stehr, Jia He, Sharon L. Senk

Hyunyi Jung

This study explores opportunities that secondary mathematics teacher preparation programs provide to learn about modeling in algebra. Forty-eight course instructors and ten focus groups at five universities were interviewed to answer questions related to modeling. With the analysis of the interview transcripts and related course materials, we found few opportunities for PSTs to engage with the full modeling cycle. Examples of opportunities to learn about algebraic modeling and the participants’ perspectives on the opportunities can contribute to the study of modeling and algebra in teacher education.

Statistical Analysis Of Momentum In Basketball, Mackenzi Stump

Honors Projects

The “hot hand” in sports has been debated for as long as sports have been around. The debate involves whether streaks and slumps in sports are true phenomena or just simply perceptions in the mind of the human viewer. This statistical analysis of momentum in basketball analyzes the distribution of time between scoring events for the BGSU Women’s Basketball team from 2011-2017. We discuss how the distribution of time between scoring events changes with normal game factors such as location of the game, game outcome, and several other factors. If scoring events during a game were always randomly distributed, or …

Transient Solution Of M[X1],M[X2]/G1,G2/1 With Priority Services, Modified Bernoulli Vacation, Bernoulli Feedback, Breakdown, Delaying Repair And Reneging, G. Ayyappan, J. Udayageetha

Applications and Applied Mathematics: An International Journal (AAM)

This paper considers a queuing system which facilitates a single server that serves two classes of units: high priority and low priority units. These two classes of units arrive at the system in two independent compound Poisson processes. It aims to decipher average queue size and average waiting time of the units. Under the pre-emptive priority rule, the server provides a general service to these arriving units. It is further assumed the server may take a vacation after serving the last high priority unit present in the system or at the service completion of each low priority unit present in …

Developing Leading And Lagging Indicators To Enhance Equipment Reliability In A Lean System, Dhanush Agara Mallesh

Masters Theses

With increasing complexity in equipment, the failure rates are becoming a critical metric due to the unplanned maintenance in a production environment. Unplanned maintenance in manufacturing process is created issues with downtimes and decreasing the reliability of equipment. Failures in equipment have resulted in the loss of revenue to organizations encouraging maintenance practitioners to analyze ways to change unplanned to planned maintenance. Efficient failure prediction models are being developed to learn about the failures in advance. With this information, failures predicted can reduce the downtimes in the system and improve the throughput.

The goal of this thesis is to predict …

Using Data Analytics For Discovering Library Resource Insights: Case From Singapore Management University, Ning Lu, Rui Song, Dina Li Gwek Heng, Swapna Gottipati, Aaron Tay

Research Collection School Of Computing and Information Systems

Library resources are critical in supporting teaching, research and learning processes. Several universities have employed online platforms and infrastructure for enabling the online services to students, faculty and staff. To provide efficient services by understanding and predicting user needs libraries are looking into the area of data analytics. Library analytics in Singapore Management University is the project committed to provide an interface for data-intensive project collaboration, while supporting one of the library’s key pillars on its commitment to collaborate on initiatives with SMU Communities and external groups. In this paper, we study the transaction logs for user behavior analysis that …

Using Data To Improve Services For Infants With Hearing Loss: Linking Newborn Hearing Screening Records With Early Intervention Records, Maria Gonzalez, Lori Iarossi, Yan Wu, Ying Huang, Kirsten Siegenthaler

Journal of Early Hearing Detection and Intervention

The purpose of this study was to match records of infants with permanent hearing loss from the New York Early Hearing Detection and Intervention Information System (NYEHDI-IS) to records of infants with permanent hearing loss receiving early intervention services from the New York State Early Intervention Program (NYSEIP) to identify areas in the state where hearing screening, diagnostic evaluations and referrals to the NYSEIP were not being made or documented in a timely manner. Data from 2014-2016 NYEHDI-IS and NYEIS information systems were matched using The Link King. There were 274 infants documented in NYEIS Information System as receiving early …

Perfect Ratings With Negative Comments: Learning From Contradictory Patient Survey Responses, Andrew S. Gallan, Marina Girju, Roxana Girju

Patient Experience Journal

This research explores why patients give perfect domain scores yet provide negative comments on surveys. In order to explore this phenomenon, vendor-supplied in-patient survey data from eleven different hospitals of a major U.S. health care system were utilized. The dataset included survey scores and comments from 56,900 patients, collected from January 2015 through October 2016. Of the total number of responses, 30,485 (54%) contained at least one comment. For our analysis, we use a two-step approach: a quantitative analysis on the domain scores augmented by a qualitative text analysis of patients’ comments. To focus the research, we start by building …

Deep Energy-Based Models For Structured Prediction, David Belanger

Doctoral Dissertations

We introduce structured prediction energy networks (SPENs), a flexible frame- work for structured prediction. A deep architecture is used to define an energy func- tion over candidate outputs and predictions are produced by gradient-based energy minimization. This deep energy captures dependencies between labels that would lead to intractable graphical models, and allows us to automatically discover discrim- inative features of the structured output. Furthermore, practitioners can explore a wide variety of energy function architectures without having to hand-design predic- tion and learning methods for each model. This is because all of our prediction and learning methods interact with the energy …

Propagation Of Probabilistic Uncertainty: The Simplest Case (A Brief Pedagogical Introduction), Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

The main objective of this text is to provide a brief introduction to formulas describing the simplest case of propagation of probabilistic uncertainty -- for students who have not yet taken a probability course.

Interproximal Distance Analysis Of Stereolithographic Casts Made By Cad-Cam Technology: An In Vitro Study, Melanie Hoffman, Seok-Hwan Cho, Naveen K. Bansal

Mathematics, Statistics and Computer Science Faculty Research and Publications

Statement of problem

The accuracy of interproximal distances of the definitive casts made by computer-aided design and computer-aided manufacturing (CAD-CAM) technology is not yet known.

Purpose

The purpose of this in vitro study was to compare the interproximal distances of stereolithographic casts made by CAD-CAM technology with those of stone casts made by the conventional method.

Material and methods

Dentoform teeth were prepared for a single ceramic crown on the maxillary left central incisor, a 3-unit fixed dental prosthesis (FDP) on the second premolar for a metal-ceramic crown, and a maxillary right first molar for a metal crown. Twenty digital …

Dodrant-Homomorphic Encryption For Cloud Databases Using Table Lookup, Thomas Schwarz

Mathematics, Statistics and Computer Science Faculty Research and Publications

Users of large commercial databases increasingly want to outsource their database operations to a cloud service providers, but guaranteeing the privacy of data in an outsourced database has become the major obstacle to this move. Encrypting all data solves the privacy issue, but makes many operations on the data impossible in the cloud, unless the service provider has the capacity to decrypt data temporarily. Homomorphic encryption would solve this issue, but despite great and on-going progress, it is still far from being operationally feasible. In 2015, we presented what we now call dodrant-homomorphic encryption, a method that encrypts numeric values …

Correct Model Selection In Multiple Regression Analyses Of Big Data, Katherine L. Thompson

Commonwealth Computational Summit

Goals:

• Improve statistical modeling in a variety of application areas
• Correctly identify the relationships present in data sets
• Understand the difficulty in choosing the correct statistical model in big data

Open Source Artificial Intelligence In A Biological/Ecological Context, Trevor Grant

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Deep Learning In R, Troy Hernandez

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Spatiotemporal Subspace Feature Tracking By Mining Discriminatory Characteristics, Richard D. Appiah

Doctoral Dissertations

Recent advancements in data collection technologies have made it possible to collect heterogeneous data at complex levels of abstraction, and at an alarming pace and volume. Data mining, and most recently data science seek to discover hidden patterns and insights from these data by employing a variety of knowledge discovery techniques. At the core of these techniques is the selection and use of features, variables or properties upon which the data were acquired to facilitate effective data modeling. Selecting relevant features in data modeling is critical to ensure an overall model accuracy and optimal predictive performance of future effects. The …

On Congruence Lattices Of Nilsemigroups, Alexander L. Popovich, Peter Jones

Mathematics, Statistics and Computer Science Faculty Research and Publications

We prove that the congruence lattice of a nilsemigroup is modular if and only if the width of the semigroup, as a poset, is at most two, and distributive if and only if its width is one. In the latter case, such semigroups therefore coincide with the nil Δ">Δ Δ -semigroups. It is further shown that if a finitely generated nilsemigroup has modular congruence lattice, then the semigroup is finite.

The Double-Edged Sword: A Mixed Methods Study Of The Interplay Between Bipolar Disorder And Technology Use, Mark Matthews, Elizabeth Murnane, Jaime Snyder, Shion Guha, Pamara Chang, Gavin Doherty, Geri K. Gay

Mathematics, Statistics and Computer Science Faculty Research and Publications

Human behavior is increasingly reflected or acted out through technology. This is of particular salience when it comes to changes in behavior associated with serious mental illnesses including schizophrenia and bipolar disorder. Early detection is crucial for these conditions but presently very challenging to achieve. Potentially, characteristics of these conditions' traits and symptoms, at both idiosyncratic and collective levels, may be detectable through technology use patterns. In bipolar disorder specifically, initial evidence associates changes in mood with changes in technology-mediated communication patterns. However much less is known about how people with bipolar disorder use technology more generally in their lives, …

Using Hydroacoustics To Investigate Biological Responses In Fish Abundance To Restoration Efforts In The Penobscot River, Maine, Constantin C. Scherelis

Electronic Theses and Dissertations

Spatiotemporal advantages linked to hydroacoustic sampling techniques have caused a surge in the use of these techniques for fisheries monitoring studies applied over long periods of time in marine systems. Dynamic physical conditions such as tidal height, boat traffic, floating debris, and suspended particle concentrations result in unwanted noise signatures that vary in intensity and location within a hydroacoustic beam over time and can be mixed with the acoustic returns from intended targets (e.g., fish). Typical processing filters applied over long term datasets to minimize noise and maximize signals do not address spatiotemporal fluctuations of noise in dynamic systems. We …

Anomalydetection: Implementation Of Augmented Network Log Anomaly Detection Procedures, Robert J. Gutierrez, Bradley C. Boehmke, Kenneth W. Bauer, Cade M. Saie, Trevor J. Bihl

Faculty Publications

As the number of cyber-attacks continues to grow on a daily basis, so does the delay in threat detection. For instance, in 2015, the Office of Personnel Management discovered that approximately 21.5 million individual records of Federal employees and contractors had been stolen. On average, the time between an attack and its discovery is more than 200 days. In the case of the OPM breach, the attack had been going on for almost a year. Currently, cyber analysts inspect numerous potential incidents on a daily basis, but have neither the time nor the resources available to perform such a task. …

Improving The Accuracy For The Long-Term Hydrologic Impact Assessment (L-Thia) Model, Anqi Zhang, Lawrence Theller, Bernard A. Engel

The Summer Undergraduate Research Fellowship (SURF) Symposium

Urbanization increases runoff by changing land use types from less impervious to impervious covers. Improving the accuracy of a runoff assessment model, the Long-Term Hydrologic Impact Assessment (L-THIA) Model, can help us to better evaluate the potential uses of Low Impact Development (LID) practices aimed at reducing runoff, as well as to identify appropriate runoff and water quality mitigation methods. Several versions of the model have been built over time, and inconsistencies have been introduced between the models. To improve the accuracy and consistency of the model, the equations and parameters (primarily curve numbers in the case of this model) …

Implant Treatment In The Predoctoral Clinic: A Retrospective Database Study Of 1091 Patients, Soni Prasad, Christopher Hambrook, Eric Reigle, Katherine Sherman, Naveen K. Bansal, Arthur F. Hefti

Mathematics, Statistics and Computer Science Faculty Research and Publications

Purpose: This retrospective study was conducted at the Marquette University School of Dentistry to (1) characterize the implant patient population in a predoctoral clinic, (2) describe the implants inserted, and (3) provide information on implant failures.

Materials and Methods: The study cohort included 1091 patients who received 1918 dental implants between 2004 and 2012, and had their implants restored by a crown or a fixed dental prosthesis. Data were collected from patient records, entered in a database, and summarized in tables and figures. Contingency tables were prepared and analyzed by a chi-squared test. The cumulative survival probability of implants was …

Integrating Apache Spark And R For Big Data Analytics On Solving Geographic Problems, Mengqi Zhang, Tin Seong Kam

Research Collection School Of Computing and Information Systems

With the advent ofdigital technology and smart devices, a flood of digital data is beinggenerated every day. This huge amount of data not only records the historyactivities but also provides future valuable information for organizations andbusinesses. However, the true values of these data will not be fullyappreciated until they have been processed, analyzed and the analysis resultsbeen communicated to decision makers in a business friendly manner.In view of thisneed, big data has been one of the major research focus in the academicresearch community especially in the field of computer science and the softwarevendor as well as the big data service …

Classification With Large Sparse Datasets: Convergence Analysis And Scalable Algorithms, Xiang Li

Electronic Thesis and Dissertation Repository

Large and sparse datasets, such as user ratings over a large collection of items, are common in the big data era. Many applications need to classify the users or items based on the high-dimensional and sparse data vectors, e.g., to predict the profitability of a product or the age group of a user, etc. Linear classifiers are popular choices for classifying such datasets because of their efficiency. In order to classify the large sparse data more effectively, the following important questions need to be answered.

1. Sparse data and convergence behavior. How different properties of a dataset, such as …

Merging Peg Solitaire In Graphs, John Engbers, Ryan Weber

Mathematics, Statistics and Computer Science Faculty Research and Publications

Peg solitaire has recently been generalized to graphs. Here, pegs start on all but one of the vertices in a graph. A move takes pegs on adjacent vertices x and y, with y also adjacent to a hole on vertex z, and jumps the peg on x over the peg ony to z, removing the peg on y. The goal of the game is to reduce the number of pegs to one.

We introduce the game merging peg solitaire on graphs, where a move takes pegs on vertices x and z (with a hole on y) and merges them to …

Testing The Independence Hypothesis Of Accepted Mutations For Pairs Of Adjacent Amino Acids In Protein Sequences, Jyotsna Ramanan, Peter Revesz

School of Computing: Faculty Publications

Evolutionary studies usually assume that the genetic mutations are independent of each other. However, that does not imply that the observed mutations are independent of each other because it is possible that when a nucleotide is mutated, then it may be biologically beneficial if an adjacent nucleotide mutates too. With a number of decoded genes currently available in various genome libraries and online databases, it is now possible to have a large-scale computer-based study to test whether the independence assumption holds for pairs of adjacent amino acids. Hence the independence question also arises for pairs of adjacent amino acids within …

A Perspective On The Challenges And Issues In Developing Biomarkers For Human Allergic Risk Assessments, Ying Mu, Dianne E. Godar, Stephen Merrill

Mathematics, Statistics and Computer Science Faculty Research and Publications

No abstract provided.

A Privacy Preserving Framework For Rfid Based Healthcare Systems, Farzana Rahman, Anwarul A. Bhuiyan, Sheikh Iqbal Ahamed

Mathematics, Statistics and Computer Science Faculty Research and Publications

RFID (Radio Frequency IDentification) is anticipated to be a core technology that will be used in many practical applications of our life in near future. It has received considerable attention within the healthcare for almost a decade now. The technology’s promise to efficiently track hospital supplies, medical equipment, medications and patients is an attractive proposition to the healthcare industry. However, the prospect of wide spread use of RFID tags in the healthcare area has also triggered discussions regarding privacy, particularly because RFID data in transit may easily be intercepted and can be send to track its user (owner). In a …

Mining Diverse Consumer Preferences For Bundling And Recommendation, Ha Loc Do

Dissertations and Theses Collection

That consumers share similar tastes on some products does not guarantee their agreement on other products. Therefore, both similarity and dierence should be taken into account for a more rounded view on consumer preferences. This manuscript focuses on mining this diversity of consumer preferences from two perspectives, namely 1) between consumers and 2) between products. Diversity of preferences between consumers is studied in the context of recommendation systems. In some preference models, measuring similarities in preferences between two consumers plays the key role. These approaches assume two consumers would share certain degree of similarity on any products, ignoring the fact …

Motion-Capture-Based Hand Gesture Recognition For Computing And Control, Andrew Gardner

Doctoral Dissertations

This dissertation focuses on the study and development of algorithms that enable the analysis and recognition of hand gestures in a motion capture environment. Central to this work is the study of unlabeled point sets in a more abstract sense. Evaluations of proposed methods focus on examining their generalization to users not encountered during system training.

In an initial exploratory study, we compare various classification algorithms based upon multiple interpretations and feature transformations of point sets, including those based upon aggregate features (e.g. mean) and a pseudo-rasterization of the capture space. We find aggregate feature classifiers to be balanced across …

Educational Magic Tricks Based On Error-Detection Schemes, Ronald I. Greenberg

Computer Science: Faculty Publications and Other Works

Magic tricks based on computer science concepts help grab student attention and can motivate them to delve more deeply. Error detection ideas long used by computer scientists provide a rich basis for working magic; probably the most well known trick of this type is one included in the CS Unplugged activities. This paper shows that much more powerful variations of the trick can be performed, some in an unplugged environment and some with computer assistance. Some of the tricks also show off additional concepts in computer science and discrete mathematics.