Physical Sciences and Mathematics Commons^™

Development Of Reduced Order Models Using Reservoir Simulation And Physics Informed Machine Learning Techniques, Mark V. Behl Jr

LSU Master's Theses

Reservoir simulation is the industry standard for prediction and characterization of processes in the subsurface. However, simulation is computationally expensive and time consuming. This study explores reduced order models (ROMs) as an appropriate alternative. ROMs that use neural networks effectively capture nonlinear dependencies, and only require available operational data as inputs. Neural networks are a black box and difficult to interpret, however. Physics informed neural networks (PINNs) provide a potential solution to these shortcomings, but have not yet been applied extensively in petroleum engineering.

A mature black-oil simulation model from Volve public data release was used to generate training data …

Application Of Tda Mapper To Water Data And Bird Data, Wako Bungula

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

A Study Of Sentiment Of Covid-19 Related Tweets In The Usa, Jack Luu, Rosangela Follmann

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Stochastic Modeling Of Ovarian Follicle Growth In Adult Female Rats, Zhaozhi Li

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Making Sense Of Online Public Health Debates With Visual Analytics Systems, Anton Ninkov

Electronic Thesis and Dissertation Repository

Online debates occur frequently and on a wide variety of topics. Particularly, online debates about various public health topics (e.g., vaccines, statins, cannabis, dieting plans) are prevalent in today’s society. These debates are important because of the real-world implications they can have on public health. Therefore, it is important for public health stakeholders (i.e., those with a vested interest in public health) and the general public to have the ability to make sense of these debates quickly and effectively. This dissertation investigates ways of enabling sense-making of these debates with the use of visual analytics systems (VASes). VASes are computational …

Ensemble Labeling Towards Scientific Information Extraction (Elsie), Erin Murphy

College of Computing and Digital Media Dissertations

Extracting scientific facts from unstructured text is difficult due to challenges specific to the ambiguity of the language, the complexity of the scientific named entities and relations to be extracted. This problem is well illustrated through the extraction of polymer names and their properties. Even in the cases where the property is a temperature, identifying the polymer name associated with the temperature may require expertise due to the use of acronyms, synonyms, complicated naming conventions and by the fact that new polymer names are being “introduced” to the vernacular as polymer science advances. While there exist domain-specific machine learning toolkits …

Viral Data, Agnieszka Leszczynski, Matthew Zook

Geography Faculty Publications

We are experiencing a historical moment characterized by unprecedented conditions of virality: a viral pandemic, the viral diffusion of misinformation and conspiracy theories, the viral momentum of ongoing Hong Kong protests, and the viral spread of #BlackLivesMatter demonstrations and related efforts to defund policing. These co-articulations of crises, traumas, and virality both implicate and are implicated by big data practices occurring in a present that is pervasively mediated by data materialities, deeply rooted dataist ideologies that entrench processes of datafication as granting objective access to truth and attendant practices of tracking, data analytics, algorithmic prediction, and data-driven targeting of individuals …

Applying The Data: Predictive Analytics In Sport, Anthony Teeter, Margo Bergman

Access*: Interdisciplinary Journal of Student Research and Scholarship

The history of wagering predictions and their impact on wide reaching disciplines such as statistics and economics dates to at least the 1700’s, if not before. Predicting the outcomes of sports is a multibillion-dollar business that capitalizes on these tools but is in constant development with the addition of big data analytics methods. Sportsline.com, a popular website for fantasy sports leagues, provides odds predictions in multiple sports, produces proprietary computer models of both winning and losing teams, and provides specific point estimates. To test likely candidates for inclusion in these prediction algorithms, the authors developed a computer model, and test …

An Analysis Of Technological Components In Relation To Privacy In A Smart City, Kayla Rutherford, Ben Lands, A. J. Stiles

James Madison Undergraduate Research Journal (JMURJ)

A smart city is an interconnection of technological components that store, process, and wirelessly transmit information to enhance the efficiency of applications and the individuals who use those applications. Over the course of the 21st century, it is expected that an overwhelming majority of the world’s population will live in urban areas and that the number of wireless devices will increase. The resulting increase in wireless data transmission means that the privacy of data will be increasingly at risk. This paper uses a holistic problem-solving approach to evaluate the security challenges posed by the technological components that make up a …

Cash Flow Forecasting Using Probabilistic Neural Networks, Marwan Ashour

Journal of the Arab American University مجلة الجامعة العربية الامريكية للبحوث

This paper aimed to compare the modern methods of cash flow forecasting with the traditional ones. In other words, the researcher compared between the Probabilistic Neural Networks and Transfer Function. It is worth mentioning that cash flow forecasting , nowadays, is very important and helps the upper management plan, control, assess the performance and make decisions. More specifically, in this paper, the Artificial Neural networks were used to diagnose the nature of the cash flow for the next period of time and then forecast the cash flow. The experiment was conducted in The General company for Electricity Distribution in Baghdad. …

Lis Online Graduate Certificate In Data Science, Joanna Burkhardt

Library Impact Statements

No abstract provided.

Using Data Analytics To Predict Students Score, Nang Laik Ma, Gim Hong Chua

Research Collection School Of Computing and Information Systems

Education is very important to Singapore, and the government has continued to invest heavily in our education system to become one of the world-class systems today. A strong foundation of Science, Technology, Engineering, and Mathematics (STEM) was what underpinned Singapore's development over the past 50 years. PISA is a triennial international survey that evaluates education systems worldwide by testing the skills and knowledge of 15-year-old students who are nearing the end of compulsory education. In this paper, the authors used the PISA data from 2012 and 2015 and developed machine learning techniques to predictive the students' scores and understand the …

A New Efficient Method To Detect Genetic Interactions For Lung Cancer Gwas, Jennifer Luyapan, Xuemei Ji, Siting Li, Xiangjun Xiao, Dakai Zhu, Eric J. Duell, David C. Christiani, Matthew B. Schabath, Susanne M. Arnold, Shanbeh Zienolddiny, Hans Brunnström, Olle Melander, Mark D. Thornquist, Todd A. Mackenzie, Christopher I. Amos, Jiang Gui

Markey Cancer Center Faculty Publications

BACKGROUND: Genome-wide association studies (GWAS) have proven successful in predicting genetic risk of disease using single-locus models; however, identifying single nucleotide polymorphism (SNP) interactions at the genome-wide scale is limited due to computational and statistical challenges. We addressed the computational burden encountered when detecting SNP interactions for survival analysis, such as age of disease-onset. To confront this problem, we developed a novel algorithm, called the Efficient Survival Multifactor Dimensionality Reduction (ES-MDR) method, which used Martingale Residuals as the outcome parameter to estimate survival outcomes, and implemented the Quantitative Multifactor Dimensionality Reduction method to identify significant interactions associated with age of …

Comparing Variable Importance In Prediction Of Silence Behaviours Between Random Forest And Conditional Inference Forest Models., Stephen Barrett Dr, Geraldine Gray Dr, Colm Mcguinness Dr, Michael Knoll Dr.

Articles

This paper explores variable importance metrics of Conditional Inference Trees (CIT) and classical Classification And Regression Trees (CART) based Random Forests. The paper compares both algorithms variable importance rankings and highlights why CIT should be used when dealing with data with different levels of aggregation. The models analysed explored the role of cultural factors at individual and societal level when predicting Organisational Silence behaviours.

Towards High Performance Stock Market Prediction Methods, Warren M. Landis, Sangwhan Cha

Other Student Works

Stock markets of today, and will continue to in the future, rely on the metrics of timeliness and efficiency to reach optimal profits. A way stock investors have continued to strive for the best of these two factors of the business is through the use of predictive machine learning systems to help aid in their decision making. However, among the many systems currently in use, it could be said that the myriad of data that they are based on may not be sufficient. In an effort to devise an ensemble learning predictive system that will utilize an array of big …

Tapping Twitter Data For Analyzing And Visualizing Public Sentiments On Censorship, Naveen Kumar Yadav, Akhilesh K.S. Yadav

Library Philosophy and Practice (e-journal)

The main objective of this research study is to analyse and visualize Twitter data with tags “#Censorship”. A connection was established with twitter using Twitter API, and receiving the tweets on Google Spreadsheets. Data visualization was performed using various tools such as Voyant Tools, Tableau, Google Spreadsheet and Orange in order to generate different visualizations based upon, language, geographical areas, retweets etc. The sentiment analysis was performed for the sentiments that were attached to the given set of data by the public in their respective tweets. The 23680 tweets were retrieved during the data collection time and there were 13,771 …

Espade: An Efficient And Semantically Secure Shortest Path Discovery For Outsourced Location-Based Services, Bharath K. Samanthula, Divyadharshini Karthikeyan, Boxiang Dong, K. Anitha Kumari

Department of Computer Science Faculty Scholarship and Creative Works

With the rapid growth of smart devices and technological advancements in tracking geospatial data, the demand for Location-Based Services (LBS) is facing a constant rise in several domains, including military, healthcare and transportation. It is a natural step to migrate LBS to a cloud environment to achieve on-demand scalability and increased resiliency. Nonetheless, outsourcing sensitive location data to a third-party cloud provider raises a host of privacy concerns as the data owners have reduced visibility and control over the outsourced data. In this paper, we consider outsourced LBS where users want to retrieve map directions without disclosing their location information. …

Fall 2020

In The Loop

Studio CDM Documents Remote Initiatives; "Tom of Your Life" Film Release; Animation Jam Goes Virtual; DePaul Experimental Film Showcase 2020; Trackmania Soundtrack; Alumni Games at Pixel Pop; Alumnus Commemorates St. Vincent de Paul; Cybersecurity Champion Alina Kuzmenkova; Walking the Walk: Youth programs at CDM express DePaul’s Vincentian values; Fair Treatment: Three initiatives address racial inequity in health care; They've Got You Covered: A School of Design instructor leads a cottage industry of makers protecting essential workers from the novel coronavirus; Meet Would-Be Hot Topic Influencer Vera Drew; Data Detectives: CDM helps Chicago track the racial proportions of its COVID-19 cases

Using Spatial Analysis And Machine Learning Techniques To Develop A Comprehensive Highway-Rail Grade Crossing Consolidation Model, Samira Soleimani

LSU Doctoral Dissertations

The safety of highway-railroad grade crossings (HRGC) is still an issue in the United States of America (USA). The grade crossing is where a railroad crosses a road at the same level without any over or underpass. To improve the safety of crossings, the crossings’ condition should be explored from several aspects such as engineering design (speed limit, warning signs, etc.), road condition (number of lanes, surface markings, etc.), rail design (the type of track, ballast, etc.), temporal variables (weather, visibility, time of day, lightning, etc.), social variables (population, race, etc.), and last but not least, spatial variables (the type …

Project In Data Science Dsp 499, Joanna Burkhardt

Library Impact Statements

No abstract provided.

Research In Data Science Dsp 599, Harrison Dekker

Library Impact Statements

No abstract provided.

Data Science Internship Dsp 477, Harrison Dekker

Library Impact Statements

No abstract provided.

Extraction D’Information À Partir Des Sites Web En Arabe Basée Sur Une Méthode À Base Des Règles, Moustafa Alhajj, Amani Sabra

Al Jinan الجنان

Cet article décrit un outil qui se sert de l’ingénierie de la langue pour l’extraction d’information à partir des sites web en arabe, Ces informations serviront aux documentalistes du Web poue créer des fches d’archivage pour les sites. Une fche d’archivage est proposée, l’objectif étant de remplir cette fche automatiquement. Pour la reconnaissance et la classifcation des segments textuels, la méthode d’exploration contextuelle proposée par Descles est utilisée, les marqueurs et règles linguistiques sont défnis en se basant sur une étude synthétique des spécifcités de la langue arabe. Un corpus de plus de 1300 sites Web en langue arabe a …

Data Analytics Beyond Traditional Probabilistic Approach To Uncertainty, Vladik Kreinovich

Departmental Technical Reports (CS)

Data for processing mostly comes from measurements, and measurements are never absolutely accurate: there is always the "measurement error" -- the difference between the measurement result and the actual (unknown) value of the measured quantity. In many applications, it is important to find out how these measurement errors affect the accuracy of the result of data processing. Traditional data processing techniques implicitly assume that we know the probability distributions. In many practical situations, however, we only have partial information about these distributions. In some cases, all we know is the upper bound on the absolute value of the measurement error. …

Imaging Data On Characterization Of Retinal Autofluorescent Lesions In A Mouse Model Of Juvenile Neuronal Ceroid Lipofuscinosis (Cln3 Disease), Qing Jun Wang, Kyung Sik Jung, Kabhilan Mohan, Mark E. Kleinman

Ophthalmology and Visual Science Faculty Publications

Juvenile neuronal ceroid lipofuscinosis (JNCL, aka. juvenile Batten disease or CLN3 disease), a lethal pediatric neurodegenerative disease without cure, often presents with vision impairment and characteristic ophthalmoscopic features including focal areas of hyper-autofluorescence. In the associated research article “Loss of CLN3, the gene mutated in juvenile neuronal ceroid lipofuscinosis, leads to metabolic impairment and autophagy induction in retinal pigment epithelium” (Zhong et al., 2020) [1], we reported ophthalmoscopic observations of focal autofluorescent lesions or puncta in the Cln3^Δex7/8 mouse retina at as young as 8 month old. In this data article, we performed differential interference contrast and …

A Tree Frog (Boana Pugnax) Dataset Of Skin Transcriptome For The Identification Of Biomolecules With Potential Antimicrobial Activities, Yamil Liscano Martinez, Claudia Marcela Arenas Gómez, Jeramiah J. Smith, Jean Paul Delgado

Biology Faculty Publications

Increases in the prevalence of multiply resistant microbes have necessitated the search for new molecules with antimicrobial properties. One noteworthy avenue in this search is inspired by the presence of native antimicrobial peptides in the skin of amphibians. Having the second highest diversity of frogs worldwide, Colombian anurans represent an extensive natural reservoir that could be tapped in this search. Among this diversity, species such as Boana pugnax (the Chirique-Flusse Treefrog) are particularly notable, in that they thrive in a diversity of marginal habitats, utilize both aquatic and arboreal habitats, and are members of one of few genera that are …

European Floating Strike Lookback Options: Alpha Prediction And Generation Using Unsupervised Learning, Tristan Lim, Aldy Gunawan, Chin Sin Ong

Research Collection School Of Computing and Information Systems

This research utilized the intrinsic quality of European floating strike lookback call options, alongside selected return and volatility parameters, in a K-means clustering environment, to recommend an alpha generative trading strategy. The result is an elegant easy-to-use alpha strategy based on the option mechanisms which identifies investment assets with high degree of significance. In an upward trending market, the research had identified European floating strike lookback call option as an evaluative criterion and investable asset, which would both allow investors to predict and profit from alpha opportunities. The findings will be useful for (i) buy-side investors seeking alpha generation and/or …

Automated Discussion Analysis - Framework For Knowledge Analysis From Class Discussions, Swapna Gottipati, Venky Shankararaman, Mallikan Gokarn Nitin

Research Collection School Of Computing and Information Systems

This research full paper, describes knowledge management of class discussions using an analytics based framework. Discussions, either live classroom or through online forums, when used as a teaching method can help stimulate critical thinking. It allows the teacher to explore in-depth the key concepts covered in the course, motivates students to articulate their ideas clearly and challenge the students to think more deeply. Analysing the discussions helps instructors gain better insights on the personal and collaborative learning behaviour of students. However, knowledge from in-class discussions and online forums is not effectively captured and mined due to lack of appropriate automated …

Visual Sentiment Analysis For Review Images With Item-Oriented And User-Oriented Cnn: Reproducibility Companion Paper, Quoc Tuan Truong, Hady W. Lauw, Martin Aumuller, Naoko Nitta

Research Collection School Of Computing and Information Systems

We revisit our contributions on visual sentiment analysis for online review images published at ACM Multimedia 2017, where we develop item-oriented and user-oriented convolutional neural networks that better capture the interaction of image features with specific expressions of users or items. In this work, we outline the experimental claims as well as describe the procedures to reproduce the results therein. In addition, we provide artifacts including data sets and code to replicate the experiments.

Data Is Personal: We Should Treat It As Such, Kaleb Dunn

Student Papers in Public Policy

The rise of the internet as a fact of daily life is the defining element of the modern age. Widespread use of the internet has fundamentally altered entire industries, and much of American life has migrated online. Dating is augmented by online dating; shopping by online shopping; television by internet streaming.

The digitization of American life has brought with it considerable benefits, including great convenience and innumerable efficiencies, but it has not come without a cost. Although there are many business models used by internet companies, many of the now-largest companies in the world have converged on one entity upon …