Digital Commons Network^™

Predicting Power Using Time Series Analysis Of Power Generation And Consumption In Texas, Joshua Eysenbach, Bodie Franklin, Andrew J. Larsen, Joel Lindsey

SMU Data Science Review

Due to the recent power events in Texas, power forecasting has been brought national attention. Accurate demand forecasting is necessary to be sure that there is adequate power supply to meet consumer's needs. While Texas has a forecasting model created by the Electricity Reliability Council of Texas (ERCOT), constant efforts are required to ensure that the model stays at the state-of-the-art and is producing the most reliable forecasts possible. This research seeks to provide improved short- and medium-term forecasting models, bringing in state-of-the-art deep learning models to compare to ERCOT’s forecasts. A model that is more accurate than ERCOT’s own …

Alternative Methods For Deriving Emotion Metrics In The Spotify® Recommendation Algorithm, Ronald M. Sherga Jr., David Wei, Neil Benson, Faizan Javed

SMU Data Science Review

Spotify's® recommendation algorithm tailors music offerings to create a unique listening experience for each user. Though what this recommender does is highly impressive, there is always room for improvement given that these techniques are not fully prescient. This study posits that in addition to creating certain features based on audio analysis, incorporating new features derived from album art color as well as lyrical sentiment analysis may provide additional value to the end user. This team did not find that a significant difference existed between color valence and Spotify® valence; however, all other comparisons resulted in statistically significant difference of means …

Clinical Diagnosis Support With Convolutional Neural Network By Transfer Learning, Spencer Fogleman, Jeremy Otsap, Sangrae Cho

SMU Data Science Review

Breast cancer is prevalent among women in the United States. Breast cancer screening is standard but requires a radiologist to review screening images to make a diagnosis. Diagnosis through the traditional screening method of mammography currently has an accuracy of about 78% for women of all ages and demographics. A more recent and precise technique called Digital Breast Tomosynthesis (DBT) has shown to be more promising but is less well studied. A machine learning model trained on DBT images has the potential to increase the success of identifying breast cancer and reduce the time it takes to diagnose a patient, …

Covid-19 - A Graph Network Approach, Nibhrat Lohia, Rajesh Satluri, Suchismita Moharana, Venkat Kasarla

SMU Data Science Review

The effects of COVID-19 and its spreads are attributed to various factors. This study uses CDC open-source data on COVID-19 effected population with features ranging from location to ethnicity, to create a Knowledge Graph to measure the similarity between COVID-19 cases and estimate the risk for people likely affected by COVID-19. This data could be used to find correlations between distinct factors, like ethnicity and pre-existing health conditions, to find the vulnerability of a given COVID-19 patient. Using the Jaccard similarity coefficient, in the knowledge graph, we are able to identify and explore relationships between COVID-19 cases as well as …

Fashion, Identity And The Muslim-American Narrative, Shireen Soliman

Artizein: Arts and Teaching Journal

In this pivotal time, assumptions, boundaries, power structures and relationships within society are being reconsidered and reimagined. My research project, “Fashion, Identity and the Muslim- American Narrative” builds off of well-established prior models and responds to this moment. Through this multidisciplinary, multimedia design workshop series geared towards Muslim American female adolescents, we are able to leverage the powerful intersection of design, technology, community, social media and social justice. In this affirming, enlightening space, we use fashion, dress and personal narrative as the springboard and means of exploring the intrinsic connection between social and emotional issues surrounding identity development, social justice …

Do Teachers Know This?, David L. Pike

Artizein: Arts and Teaching Journal

A Communication Arts instructor in a Calgary Technical Institute discovers an opportunity to enlarge his vocation when a student asks him a simple four-word question. Methods of thinking and learning are soon integrated into the communications curriculum, and students, together with their instructors, are invited to develop more and better “TLC” capabilities as they study and practice their chosen disciplines. The article closes by suggesting, given the challenges we’re facing in working, learning, and living well together now, that we ask leaders in our communities and beyond the same question; and to encourage them to expand their leadership roles and …

Amelia's Gift, Daniel J. Mydlack

Artizein: Arts and Teaching Journal

Professor Danny Mydlack recounts the mysterious arc of his student’s creative unfolding. Amelia, a middle-aged single mom, drops out of the personal videography production class before the end and yet her final assignment is delivered, posthumously, by her adult daughters. For the author, Amelia returned him to the core principles from his student days: the vast, wide terrain that is the true realm of art-making and an embrace of the fullness rather than merely the fineness of art practice. Mydlack proposes that with teaching there is more unseen than seen, more beyond our manipulation than within it, and that pedagogical …

Full Issue Artizein_December 2021, Peter London

Artizein: Arts and Teaching Journal

A full PDF of the themed Artizein: Arts & Teaching Journal issue entitled 'Stories that Mattered' edited by Peter London.

Real-Time Voice Biometric Speaker Verification, Inderbir Dhillon, Jason Rupp, Aniketh Vankina, Robert Slater

SMU Data Science Review

Abstract. Automated speaker verification has been an area of increased research in the last few years, with a special interest in metric learning approaches that compute distances between speaker voiceprints. In this paper, three metric learning systems are built and compared in a one-shot speaker verification task using contrastive max-margin loss, triplet loss, and quadruplet loss. For all the models, spectrograms are created from speaker audio. Convolutional Neural Network embedding layers are trained to produce compact voiceprints that allow users to be distinguished using distance calculations. Performances of the three models were similar, but the model with the best EER …

Machine Learning Approach To Distinguish Ulcerative Colitis And Crohn’S Disease Using Smote (Synthetic Minority Oversampling Technique) Methods, Kris Ghimire, Walter Lai, Yasser Omar, Thad Schwebke, Jamie Vo

SMU Data Science Review

Irritable Bowel Disease (IBD) affects a sizable portion of the US population, causing symptoms such as vomiting, abdominal pain, and diarrhea. Despite the disease’s prevalence, the precise cause is not fully understood. This study consists of endoscopic and histological data from patients diagnosed with IBD and a control population for reference. The machine learning models' focus is to classify patients into IBD types. Several models were analyzed, including decision trees, logistic regression, and k-nearest neighbors. In addition, various methods of SMOTE were applied to determine the most effective transformation and ensuring that the dataset is balanced. The best model with …

Urban Traffic Simulation: Network And Demand Representation Impacts On Congestion Metrics, Aaron Faltesek, Balasubramaniam Dakshinamoorthi, Sreeni Prabhala, Akbar Thobani, Anu Kuncheria, Jane Macfarlane

SMU Data Science Review

Traffic simulations are often used by city planners as a basis for predicting the impact of policies, plans, and operations. The complexities underpinning traffic simulations are often not described in detail yet can significantly impact the simulation outcome. Conflating underlying data for simulations is complex and hinders the interest in this type of exploration. This paper aims to elucidate critical features of traffic simulations that drive the generated metrics of the modeled urban environment. Specifically, this paper examines differences in two road graph networks for the metropolitan region of Houston, TX: a reduced network composed of 45,675 road links and …

Intelligent Investment Portfolio Management Using Time-Series Analytics And Deep Reinforcement Learning, Sachin Chavan, Pradeep Kumar, Tom Gianelle

SMU Data Science Review

Abstract. – With globalization, the capital markets have exploded in size and value, making them exceedingly difficult to predict. These days the public has access to real-time data of the market-leading to more participation. As a positive step, this might lead to better wealth distribution in the society, and it also adds to the random nature of the market, making it more unpredictable. The portfolio accounts consisting of stocks and bonds are considered serious investment assets. They can make or break a person’s future. It is also a way of shielding one against market risk or rising inflation. These accounts, …

Identification And Characterization Of Forest Fire Risk Zones Leveraging Machine Learning Methods, Joshua Balson, Matt Chinchilla, Cam Lu, Jeff Washburn, Nibhrat Lohia

SMU Data Science Review

Across the United States, record numbers of wildfires are observed costing billions of dollars in property damage, polluting the environment, and putting lives at risk. The ability of emergency management professionals, city planners, and private entities such as insurance companies to determine if an area is at higher risk of a fire breaking out has never been greater. This paper proposes a novel methodology for identifying and characterizing zones with increased risks of forest fires. Methods involving machine learning techniques use the widely available and recorded data, thus making it possible to implement the tool quickly.

Design Methodology For Input Shapers Using Genetic Algorithms In Flexible Nonlinear Systems, Mohab Adel Hakim Meshreki

Archived Theses and Dissertations

No abstract provided.

End Milling Process Modeling Using Artificial Neural Networks, Khaled Abdel-Hamid Elsayed

Archived Theses and Dissertations

No abstract provided.

Assessment Of Residential Drinking Water Quality In Maadi, Egypt, Sally Fadel Naguib El Komos

Archived Theses and Dissertations

No abstract provided.

The Fierce Green Fire: Vol. 12 Issue 9, Wofford College. Department Of Environmental Studies

The Fierce Green Fire

No abstract provided.

Utilization Of Non-Verbal Language In Engine Room Training, Emi Yutaka, Muramatsu Nagisa

International Maritime Lecturers' Association (IMLA) 2021 Joint Conference With IMEC32, ICERS15 and INSLC21

The Engine control room in a vessel is covered with a soundproof wall. Therefore, crews can not communicate with each other with normal voices. Therefore, crews in the engine room communicated with colleagues by hand signals instead of loud voices in the noisy space when there was no control room yet in a vessel. An example of a hand signal that Japanese crews used to use in the past was putting your right hand into your left armpit, which means “measure”. One of the advantages of hand signals is that they are a useful communication tool in such a noisy …

Alumna Returns As New Director Of Dietetics Program, Reese Colaluca

University of Mississippi News

Ellen Ossorio brings energy, experience to help guide students to their career paths

Pittsburg State University Commencement, December 2021, Pittsburg State University

Commencement, 1903-Present

Program of undergraduate and graduate commencement exercises at Pittsburg State University on December 10, 2021.

The Application Of Design Thinking On Evaluating A User Self-Service Data Analytics/Science Platform, Aheeka Pattnaik

Dissertations and Theses

This thesis is aimed at utilising design thinking and the first half of the double diamond framework to i) set-up a research and select the appropriate participants, ii) gather requirements and define user personas from those eligible participants, and then iii) define the framework for evaluating a user self-service data analytics/science platform. Derived from the author’s own experiences, both as a Business Analyst (BA) and Citizen Data Scientist, with no-, low-, and code-based data analytics and science platforms are being implemented for enabling user self-service analytics – for users who are completely new to the space of data analysis and …

Navigating The Impact Of Covid-19 On Small Commercial Businesses And Insurance Companies, And A Call To Action For Future Communicable Disease Outbreaks, Natalie Peña

Honors Program Theses and Research Projects

The short-term and long-term effects of Covid-19 have caused many small commercial businesses to face financial hardships, loss of employees, and even closures for entities that were already experiencing low profit margins. Distraught with their businesses suffering, owners turned to their primary insurance companies to receive compensation through their business interruption policies. However, most insureds were upset when they discovered that their insurance plans did not include communicable diseases and pandemics as a covered peril. This led to many small businesses battling these issues in the courts and fighting for insurance companies to provide financial assistance to them during this …

Aa Ms 19 Eugene Jackson Papers, Emily Margaret Newell

Search the Manuscript Collection (Finding Aids)

This collection is comprised of family photographs, photo albums, bibles, hymnals, and newspaper from the early 20th century onward. The collection is organized into three series:

Series 1: Photographs

This series includes the personal photographs of Eugene Jackson’s friends and family as far back as the early 1900s. The most common themes and activities found in these photographs are leisure activities such as trips to the beach or the mountains, family get-togethers, professional portraits, and Christmas greeting cards.

Subseries 1.1: Loose Photographs

Loose photographs are organized into topical folders.

Subseries 1.2: Ruby Family Photograph Album

The photograph album includes black-and-white …

Hydrogen Peroxide Vapor Decontamination Of Polylactic Acid Fibers, Alexandra Craig

Mechanical Engineering Theses

Electrospun fibers have attracted attentions in topical drug delivery due to the ability to modulate drug release at high drug loading. While the pharmaceutical properties of these drug-eluting fibers were reported elsewhere, the compatibility of these fibers with hydrogen peroxide vapor, an effective decontaminant, is not fully established. In this work, polylactic acid (PLA) microfibers loaded with acetylsalicylic acid (ASA) were electrospun to examine their compatibility with hydrogen peroxide vapor. Results suggested a strengthening effect of the PLA/ASA fibers due to intermolecular interactions of ASA with PLA, which modulated the in vitro drug release rates. After exposing PLA/ASA fibers to …

Healthcare Access Barriers And Proposed Solutions For Limited English-Proficient (Lep) Latinx Patients In Southwest Michigan, Carmen Vinkemulder

Honors Theses

This research study explores the circumstances and experiences of LatinX patients with limited English proficiency (LEP) when seeking treatment in the healthcare system of Southwest Michigan, in addition to proposing solutions to better facilitate this population’s access. The terminology used in this research, LatinX, is an American English neologism used as a genderinclusive term used interchangeably with Latino/a and/or Hispanic. This research provides an overview of the current socio-political legislature and climate of the American healthcare system as it pertains to the LatinX population to spread awareness and identify the barriers existing in our current healthcare model. This study will …

Eating Detection With A Head-Mounted Video Camera, Shengjie Bi, David Kotz

Computer Science Technical Reports

In this paper, we present a computer-vision based approach to detect eating. Specifically, our goal is to develop a wearable system that is effective and robust enough to automatically detect when people eat, and for how long. We collected video from a cap-mounted camera on 10 participants for about 55 hours in free-living conditions. We evaluated performance of eating detection with four different Convolutional Neural Network (CNN) models. The best model achieved accuracy 90.9% and F1 score 78.7% for eating detection with a 1-minute resolution. We also discuss the resources needed to deploy a 3D CNN model in wearable or …

First Record Of Fungal Diversity In The Tropical And Warm-Temperate Middle Miocene Climate Optimum Forests Of Eurasia, Jennifer M.K. O'Keefe

Faculty Research at Morehead State University

The middle Miocene Climate Optimum (MMCO) was the warmest interval of the last 23 million years and is one of the best analogs for proposed future climate change scenarios. Fungi play a key role in the terrestrial carbon cycle as dominant decomposers of plant debris, and through their interactions with plants and other organisms as symbionts, parasites, and endobionts. Thus, their study in the fossil record, especially during the MMCO, is essential to better understand biodiversity changes and terrestrial carbon cycle dynamics in past analogous environments, as well as to model future ecological and climatic scenarios. The fossil record also …

First Record Of Fungal Diversity In The Tropical And Warm-Temperate Middle Miocene Climate Optimum Forests Of Eurasia, Ingrid C. Romero, Noelia B. Nuñez Otaño, Martha E. Gibson, Tyler M. Spears, C. Jolene Fairchild, Laikin Tarlton, Savannah Jones, Harvey E. Belkin, Sophie Warny, Matthew J. Pound, Jennifer M.K. O’Keefe

Faculty Publications

The middle Miocene Climate Optimum (MMCO) was the warmest interval of the last 23 million years and is one of the best analogs for proposed future climate change scenarios. Fungi play a key role in the terrestrial carbon cycle as dominant decomposers of plant debris, and through their interactions with plants and other organisms as symbionts, parasites, and endobionts. Thus, their study in the fossil record, especially during the MMCO, is essential to better understand biodiversity changes and terrestrial carbon cycle dynamics in past analogous environments, as well as to model future ecological and climatic scenarios. The fossil record also …

2021 Fall Commencement Program: Winona State University, Winona State University

WSU Commencement Programs

This is the Winona State University Fall 2021 commencement program. Commencement was on Friday, December 10, 2021.

Ud In The News Dec. 3-10, University Of Dayton

News Releases

Commonweal, Newsweek, National Geographic; The Attitude on the Pacifica Network, which has 220 affiliates; and Catholic News Service are among the national news outlets sharing UD faculty expertise. Local media featured the Greater West Dayton Incubator's grand opening.