Data Science Commons^™

Integrated Machine Learning And Optimization Approaches, Dogacan Yilmaz

Dissertations

This dissertation focuses on the integration of machine learning and optimization. Specifically, novel machine learning-based frameworks are proposed to help solve a broad range of well-known operations research problems to reduce the solution times. The first study presents a bidirectional Long Short-Term Memory framework to learn optimal solutions to sequential decision-making problems. Computational results show that the framework significantly reduces the solution time of benchmark capacitated lot-sizing problems without much loss in feasibility and optimality. Also, models trained using shorter planning horizons can successfully predict the optimal solution of the instances with longer planning horizons. For the hardest data set, …

Applying Data Science And Machine Learning To Understand Health Care Transition For Adolescents And Emerging Adults With Special Health Care Needs, Lisamarie Turk

Nursing ETDs

A problem of classification places adolescents and emerging adults with special health care needs among the most at risk for poor or life-threatening health outcomes. This preliminary proof-of-concept study was conducted to determine if phenotypes of health care transition (HCT) for this vulnerable population could be established. Such phenotypes could support development of future studies that require data classifications as input. Mining of electronic health record data and cluster analysis were implemented to identify phenotypes. Subsequently, a machine learning concept model was developed for predicting acute care and medical condition severity. Three clusters were identified and described (Cluster 1, n …

Hybrid Artificial Bee Colony And Improved Simulatedannealing For The Capacitated Vehicle Routing Problem, Farhanna Mar'i, Hafidz Ubaidillah, Wayan Firdaus Mahmudy, Ahmad Afif Supianto

Knowledge Engineering and Data Science

Capacitated Vehicle Routing Problem (CVRP) is a type of NP-Hard combinatorial problem that requires a high computational process. In the case of CVRP, there is an additional constraint in the form of a capacity limit owned by the vehicle, so the complexity of the problem from CVRP is to find the optimum route pattern for minimizing travel costs which are also adjusted to customer demand and vehicle capacity for distribution. One method of solving CVRP can be done by implementing a meta-heuristic algorithm. In this research, two meta-heuristic algorithms have been hybridized: Artificial Bee Colony (ABC) with Improved Simulated Annealing …

An Accurate Real-Time Method For Face Mask Detectionusing Cnn And Svm, Shili Hechmi

Knowledge Engineering and Data Science

Infectious respiratory diseases, including COVID-19, pose a significant challenge to humanity and a potential threat to life due to their severity and rapid spread. Using a surgical mask is among the most significant safety precautions that can help keep this sort of pandemic from spreading, and manual monitoring of large crowds in public places for face masks is problematic. In this research, we suggest a real-time approach for face mask detection. First, we use a multi-scale deep neural network to extract features. As a result, the attributes are better suited for training the detection system. We employ SVM post-processing in …

Indonesian Language Term Extraction Using Multi-Task Neural Network, Joan Santoso, Esther Irawati Setiawan, Fransiskus Xaverius Ferdinandus, Gunawan Gunawan, Leonel Hernandez Collantes

Knowledge Engineering and Data Science

The rapidly expanding size of data makes it difficult to extricate information and store it as computerized knowledge. Relation extraction and term extraction play a crucial role in resolving this issue. Automatically finding a concealed relationship between terms that appear in the text can help people build computer-based knowledge more quickly. Term extraction is required as one of the components because identifying terms that play a significant role in the text is the essential step before determining their relationship. We propose an end-to-end system capable of extracting terms from text to address this Indonesian language issue. Our method combines two …

Adaptive Neuro-Fuzzy Inference System For Waste Prediction, Haviluddin Haviluddin, Herman Santoso Pakpahan, Novianti Puspitasari, Gubtha Mahendra Putra, Rima Yustika Hasnida, Rayner Alfred

Knowledge Engineering and Data Science

The volume of landfills that are increasingly piled up and not handled properly will have a negative impact, such as a decrease in public health. Therefore, predicting the volume of landfills with a high degree of accuracy is needed as a reference for government agencies and the community in making future policies. This study aims to analyze the accuracy of the Adaptive Neuro-Fuzzy Inference System (ANFIS) method. The prediction results' accuracy level is measured by the value of the Mean Absolute Percentage Error (MAPE). The final results of this study were obtained from the best MAPE test results. The best …

Associated Patterns In Open-Ended Concept Maps Within E-Learning, Didik Dwi Prasetya, Tsukasa Hirasama

Knowledge Engineering and Data Science

A concept map is a diagram that visualizes the structure of individual cognitive knowledge. An approach to creating a concept map structure that allows users to contribute concepts and linkages that express their understanding freely is known as an "open-ended concept map." It has been demonstrated that an open-ended concept map accurately depicts student knowledge structures and reveals student differences. However, manually analyzing an open-ended map is difficult, time-consuming, and includes many propositions, especially in a big classroom. Educational data mining could be used to further process and analyze a collection of concept maps. However, many works attempted to employ …

Influence Of Waist Circumference Measurement Site On Visceral Fat And Metabolic Risk In Youth, Sojung Lee, Yejin Kim, Minsub Han

Faculty, Staff and Student Publications

Although the rate of childhood obesity seems to have plateaued in recent years, the prevalence of obesity among children and adolescents remains high. Childhood obesity is a major public health concern as overweight and obese youth suffer from many co-morbid conditions once considered exclusive to adults. It is now well demonstrated that abdominal obesity as measured by waist circumference (WC) is an independent risk factor for cardiovascular disease and metabolic dysfunction in youth. Despite the strong associations between WC and cardiometabolic risk factors, there is no consensus regarding the optimal WC measurement sites to assess abdominal obesity and obesity-related health …

Collaborative Interprofessional Health Science Student Led Realistic Mass Casualty Incident Simulation, Deborah L Mccrea, Robert C Coghlan, Tiffany Champagne-Langabeer, Stanley Cron

Faculty, Staff and Student Publications

In collaboration, a health science university and a fire department offered a mass casualty incident (MCI) simulation. The purpose of this study was to evaluate a cross-section of student health care providers to determine their working knowledge of an MCI. Students were given a pretest using the Emergency Preparedness Information Questionnaire (EPIQ) and the Simple Triage and Rapid Transport (START) Quiz. The EPIQ instrument related to knowledge of triage, first aid, bio-agent detection, critical reporting, incident command, isolation/quarantine/decontamination, psychological issues, epidemiology, and communications. The START Quiz gave 10 scenarios. Didactic online content was given followed by the simulation a few …

Digital Technology Enables Construction Of National Governance Modernization, Yue Hao, Kaihua Chen, Jin Kang, Xiaoguang Yang, Chao Zhang, Xiaolong Zheng

Bulletin of Chinese Academy of Sciences (Chinese Version)

As digital technologies continue to be integrated into the whole process of economic and social development, promoting the modernization of digital technology-enabled national governance systems and capabilities has become an important way to seize the strategic initiative in the future world competitive landscape, and has attracted the attention of countries around the world. The rapid development of digital technologies such as big data collection, storage, processing, and analysis is constantly optimizing the organizational system structure of national governance, upgrading and perfecting the quality and methods of national governance personnel, and accelerating the process of making national governance efficient, scientific, intelligent …

Deepening Digital Technologies To Enable Modernization Of China’S Governance Of Health, Tara Qia Sun, Xia Feng, Yuntao Long, Zongben Xu

Bulletin of Chinese Academy of Sciences (Chinese Version)

One significant goal of science and technology innovation is to set our sights on the health and safety of the people. The rapid development of digital technologies provides multiple potentials and path to achieve the modernization of China's health governance. the role of digital technologies on enabling multiple stakeholders (i.e., hospitals, doctors, government, and social groups) to improve the supply capacity, the inclusiveness, fairness, friendliness, and convenience of health service. Second, we explore the four key issues of using digital technologies to enable the governance of health construction of digital health infrastructures, the factors affecting the adoption of digital technologies, …

Digital Technology Enables Modernization Of National Statistics, Zongben Xu, Yanyun Zhao, Liping Zhu, Guang Chen, Hongyun Zhang

Bulletin of Chinese Academy of Sciences (Chinese Version)

The modernization of national statistics is part of the modernization of national governance. Digital technology has provided power for the transformation of statistical production mode, the improvement of statistical productivity, and the reconstruction of statistical production relations. Digital technology has become an important prerequisite for the promotion of statistical modernization reform. This study summarizes the international experience of digital technology enabling government statistics, the top-level design of national statistical legal system, and the importance of digital technology in promoting the modernization of statistics. This study also analyzes the main challenges existing in the current national statistics and data work. Finally, …

Big Data Technology Enabling Legal Supervision, Qingjie Liu, Shuo Liu, Yirong Wu, Yueqiang Weng, Yihao Wen, Ming Li

Bulletin of Chinese Academy of Sciences (Chinese Version)

Legal supervision plays an important role in the national governance system and capacity. In the era of digital revolution, the rapid development of digital procuratorial work with big data legal supervision as the core promotes to reshape the legal supervision and governance system. In this study, the inherent need of legal supervision for active prosecution in the new era, and the innovative role of new public interest litigation in comprehensive social governance, are firstly analyzed. Then, the core meaning and reshaping role of big-data-enabling-legalsupervision and supervision-promoting-national-governance of digital prosecution are discussed. After summarizing the practical experiences and challenges of big …

Strengthen Fundamental Role Of Data Element Governance In National Governance Modernization, Kaihua Chen, Zhuo Feng, Rui Guo, Yue Hao, Jin Kang, Xiaoguang Yang, Chao Zhang, Binbin Zhao

Bulletin of Chinese Academy of Sciences (Chinese Version)

Data element governance is a key factor to promote the modernization of national governance in the digital era. By strengthening the deep integration of data factors and national governance, a new model of data-driven national governance can be formed, and the national governance can be made more scientific, refined, intelligent, and efficient. The US and European countries have continuously strengthened the top-level system design, technological innovation application, collaborative governance mechanism, and global governance cooperation of data element governance, which has effectively improved the level of data element governance and provided experience for China. Nevertheless, due to the virtuality of data …

Strategic Perspective Of Leveraging New Generation Information Technology To Enable Modernization Of Emergency Management, Haibo Zhang, Xinyu Dai, Depei Qian, Jian Lyu

Bulletin of Chinese Academy of Sciences (Chinese Version)

The application and development of the new generation information technology is a vital support to realize the modernization of emergency management. At present, the new generation information technology such as big data and artificial intelligence has been widely used in natural disasters, safe production, and other fields. It has improved the monitoring and early warning, regulation and law enforcement, command and decision support, rescue, and social mobilization capabilities of governments, promoted the level of intrinsic safety of enterprises, provided important support for the precise prevention and control of the COVID-19, and increased the efficiency of China’s emergency management and sense …

Application Of Distributed Fiber-Optic Sensing For Pressure Predictions And Multiphase Flow Characterization, Gerald Kelechi Ekechukwu

LSU Doctoral Dissertations

In the oil and gas industry, distributed fiber optics sensing (DFOS) has the potential to revolutionize well and reservoir surveillance applications. Using fiber optic sensors is becoming increasingly common because of its chemically passive and non-magnetic interference properties, the possibility of flexible installations that could be behind the casing, on the tubing, or run on wireline, as well as the potential for densely distributed measurements along the entire length of the fiber. The main objectives of my research are to develop and demonstrate novel signal processing and machine learning computational techniques and workflows on DFOS data for a variety of …

Utilizing Remote Sensing Technology To Relocate Lubra Village And Visualize Flood Damages, Ronan Wallace

Mathematics, Statistics, and Computer Science Honors Projects

As weather patterns change worldwide, isolated communities impacted by climate change go unnoticed and we need community and habitat-conscious solutions. In Himalayan Mustang, Nepal, indigenous Lubra village faces threats of increasing flash flooding. After every flood, residual concrete-like sediment hardens across the riverbed, causing the riverbed elevation to rise. As elevation increases, sediment encroaches on Lubra’s agricultural fields and homes, magnifying flood vulnerability. In the last monsoon season alone, the village witnessed floods swallowing several fields and damaging two homes. One solution considers relocating the village to a new location entirely. However, relocation poses a challenging task, as eight centuries …

Detection Of Stroke With Retinal Microvascular Density And Self-Supervised Learning Using Oct-A And Fundus Imaging, Samiksha Pachade, Ivan Coronado, Rania Abdelkhaleq, Juntao Yan, Sergio Salazar-Marioni, Amanda Jagolino, Charles Green, Mozhdeh Bahrainian, Roomasa Channa, Sunil A Sheth, Luca Giancardo

Faculty, Staff and Student Publications

Acute cerebral stroke is a leading cause of disability and death, which could be reduced with a prompt diagnosis during patient transportation to the hospital. A portable retina imaging system could enable this by measuring vascular information and blood perfusion in the retina and, due to the homology between retinal and cerebral vessels, infer if a cerebral stroke is underway. However, the feasibility of this strategy, the imaging features, and retina imaging modalities to do this are not clear. In this work, we show initial evidence of the feasibility of this approach by training machine learning models using feature engineering …

Computer Clinical Decision Support That Automates Personalized Clinical Care: A Challenging But Needed Healthcare Delivery Strategy, Alan H Morris, Christopher Horvat, Brian Stagg, David W Grainger, Michael Lanspa, James Orme, Terry P Clemmer, Lindell K Weaver, Frank O Thomas, Colin K Grissom, Ellie Hirshberg, Thomas D East, Carrie Jane Wallace, Michael P Young, Dean F Sittig, Mary Suchyta, James E Pearl, Antinio Pesenti, Michela Bombino, Eduardo Beck, Katherine A Sward, Charlene Weir, Shobha Phansalkar, Gordon R Bernard, B Taylor Thompson, Roy Brower, Jonathon Truwit, Jay Steingrub, R Duncan Hiten, Douglas F Willson, Jerry J Zimmerman, Vinay Nadkarni, Adrienne G Randolph, Martha A Q Curley, Christopher J L Newth, Jacques Lacroix, Michael S D Agus, Kang Hoe Lee, Bennett P Deboisblanc, Frederick Alan Moore, R Scott Evans, Dean K Sorenson, Anthony Wong, Michael V Boland, Willard H Dere, Alan Crandall, Julio Facelli, Stanley M Huff, Peter J Haug, Ulrike Pielmeier, Stephen E Rees, Dan S Karbing, Steen Andreassen, Eddy Fan, Roberta M Goldring, Kenneth I Berger, Beno W Oppenheimer, E Wesley Ely, Brian W Pickering, David A Schoenfeld, Irena Tocino, Russell S Gonnering, Peter J Pronovost, Lucy A Savitz, Didier Dreyfuss, Arthur S Slutsky, James D Crapo, Michael R Pinsky, Brent James, Donald M Berwick

Faculty, Staff and Student Publications

How to deliver best care in various clinical settings remains a vexing problem. All pertinent healthcare-related questions have not, cannot, and will not be addressable with costly time- and resource-consuming controlled clinical trials. At present, evidence-based guidelines can address only a small fraction of the types of care that clinicians deliver. Furthermore, underserved areas rarely can access state-of-the-art evidence-based guidelines in real-time, and often lack the wherewithal to implement advanced guidelines. Care providers in such settings frequently do not have sufficient training to undertake advanced guideline implementation. Nevertheless, in advanced modern healthcare delivery environments, use of eActions (validated clinical decision …

Fairness And Privacy In Machine Learning Algorithms, Neha Bhargava

Master of Science in Computer Science Theses

Roughly 2.5 quintillion bytes of data is generated daily in this digital era. Manual processing of such huge amounts of data to extract useful information is nearly impossible but with the widespread use of machine learning algorithms and their ability to process enormous data in a fast, cost-effective, and scalable way has proven to be a preferred choice to glean useful insights and solve business problems in many domains. With this widespread use of machine learning algorithms there has always been concerns about the ethical issues that may arise from the use of this modern technology. While achieving high accuracies, …

Spatial Validation Of Agent-Based Models, Kristoffer Wikstrom, Hal T. Nelson

Public Administration Faculty Publications and Presentations

This paper adapts an existing techno–social agent-based model (ABM) in order to develop a new framework for spatially validating ABMs. The ABM simulates citizen opposition to locally unwanted land uses, using historical data from an energy infrastructure siting process in Southern California. Spatial theory, as well as the model’s design, suggest that adequate validation requires multiple tests rather than relying solely on a single test-statistic. A pattern-oriented modeling approach was employed that first mapped real and simulated citizen comments across the US Census tract. The suite of spatial tests included Global Moran’s I, complemented with bivariate correlations, as well as …

Issues In Melanoma Detection: Semisupervised Deep Learning Algorithm Development Via A Combination Of Human And Artificial Intelligence, Xinyuan Zhang, Ziqian Xie, Yang Xiang, Imran Baig, Mena Kozman, Carly Stender, Luca Giancardo, Cui Tao

Faculty, Staff and Student Publications

BACKGROUND: Automatic skin lesion recognition has shown to be effective in increasing access to reliable dermatology evaluation; however, most existing algorithms rely solely on images. Many diagnostic rules, including the 3-point checklist, are not considered by artificial intelligence algorithms, which comprise human knowledge and reflect the diagnosis process of human experts.

OBJECTIVE: In this paper, we aimed to develop a semisupervised model that can not only integrate the dermoscopic features and scoring rule from the 3-point checklist but also automate the feature-annotation process.

METHODS: We first trained the semisupervised model on a small, annotated data set with disease and dermoscopic …

Experiences Of Parents With Opioid Use Disorder During Their Attempts To Seek Treatment: A Qualitative Analysis, Christine Bakos-Block, Angela J Nash, A Sarah Cohen, Tiffany Champagne-Langabeer

Faculty, Staff and Student Publications

In the U.S., 12.3% of children live with at least one parent who has a substance use disorder. Prior research has shown that men are more likely to seek treatment than women and that the barriers are different; however, there is limited research focusing specifically on opioid use disorder (OUD). We sought to understand the barriers and motivators for parents with OUD. We conducted a qualitative study by interviewing parents with OUD who were part of an outpatient treatment program. Interviews followed a semi-structured format with questions on access to and motivation for treatment. The interviews were recorded and transcribed …

Advancing Access To Healthcare Through Telehealth: A Brownsville Community Assessment, Edna Ely-Ledesma, Tiffany Champagne-Langabeer

Faculty, Staff and Student Publications

(1) Background: This paper focuses on the development of a community assessment for telehealth using an interprofessional lens, which sits at the intersection of public health and urban planning using multistakeholder input. The paper analyzes the process of designing and implementing a telemedicine plan for the City of Brownsville and its surrounding metros. (2) Methods: We employed an interprofessional approach to CBPR which assumed all stakeholders as equal partners alongside the researchers to uncover the most relevant and useful knowledge to inform the development of telehealth community assessment. (3) Results: Key findings include that: physicians do not have the technology, …

Investigating Applications Of Deep Learning For Diagnosis Of Post Traumatic Elbow Disease, Hugh James

McKelvey School of Engineering Graduate Student Theses & Dissertations

Traumatic events such as dislocation, breaks, and arthritis of musculoskeletal joints can cause the development of post-traumatic joint contracture (PTJC). Clinically, noninvasive techniques such as Magnetic Resonance Imaging (MRI) scans are used to analyze the disease. Such procedures require a patient to sit sedentary for long periods of time and can be expensive as well. Additionally, years of practice and experience are required for clinicians to accurately recognize the diseased anterior capsule region and make an accurate diagnosis. Manual tracing of the anterior capsule is done to help with diagnosis but is subjective and timely. As a result, there is …

Effect Of Temperature Cycling Pretreatment On The Thermal Stability Of Sm2(Co, Fe, Zr, Cu)17 Magnets In The Mild Temperature Range, Hulin Wu, Zhimei Long, Zhongsheng Li, Kaiqiang Song, Chaoqun Li, Dalong Cong, Bin Shao, Xiaowei Liu, Jianchun Sun, Yilong Ma

Faculty, Staff and Student Publications

The irredeemable magnetic losses of Sm(Co, Fe, Zr, Cu)7.8 permanent magnets caused by oxidation are very important for their practical application. In this work, the simulated results with R2 ≥ 98% based on the data of the temperature cycling test and the long-term isothermal test for the original samples confirmed that the magnetic flux losses reached 9.38% after the 5000th cycle in range R.T.–300 °C, and 7.15% after oxidated at 180 °C for 10 years, respectively. Demagnetization curves showed that the low-temperature oxidation mainly led to the remanence attenuation, while the coercivity remained relatively stable. SEM observation and EDS …

High-Frequency Ultrasound In Patients With Seronegative Rheumatoid Arthritis, Junkui Wang, Miao Wang, Qinghua Qi, Zhibin Wu, Jianguo Wen

Faculty, Staff and Student Publications

This study aimed to investigate the value of high-frequency ultrasound (HFUS) in differentiation of the seronegative rheumatoid arthritis (SNRA) and osteoarthritis (OA) and in the diagnosis of SNRA. 83 patients diagnosed with SNRA (SNRA group) and 40 diagnosed with OA (OA group) who received HFUS were retrospectively analyzed. The grayscale (GS) scores, power Doppler (PD) scores, and bone erosion (BE)scores were recorded, and added up to calculate the total scores of US variables. The correlations of the total scores of US variables with the 28-joint disease activity score (DAS28), erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) were analyzed. The …

Examining The Relationship Between Stomiiform Fish Morphology And Their Ecological Traits, Mikayla L. Twiss

All HCAS Student Capstones, Theses, and Dissertations

Trait-based ecology characterizes individuals’ functional attributes to better understand and predict their interactions with other species and their environments. Utilizing morphological traits to describe functional groups has helped group species with similar ecological niches that are not necessarily taxonomically related. Within the deep-pelagic fishes, the Order Stomiiformes exhibits high morphological and species diversity, and many species undertake diel vertical migration (DVM). While the morphology and behavior of stomiiform fishes have been extensively studied and described through taxonomic assessments, the connection between their form and function regarding their DVM types, morphotypes, and daytime depth distributions is not well known. Here, three …

Transfer Of Personality Through Text Style, Michael O'Mahony, Robert Ross

Other resources

The style of generated text is how something is said rather than what is said. We hypothesize that changing the style of generated text can change the perceived personality of the text generation agent. Dialogue systems that aim to imitate a human agent can appear to have a consistent personality through a consistent, controllable style of conversation. Some recent work on the style of generated text [1] performs impressively in the small number of domains selected for their experiments using transformer and LSTM-based models. Lin et al. [1] used weak supervised learning as their data set lacks parallel data. The …

A Maturity Model Of Data Modeling In Self-Service Business Intelligence Software, Anna Kurenkov

Master of Science in Information Technology Theses

Although Self-Service Business Intelligence (SSBI) is continually being adopted in various industries, there is a lack of research focused on data modeling in SSBI. This research aims to fill that research gap and propose a maturity model for SSBI data modeling which is generalizeable between different software and applicable for users of all technical backgrounds. Through extensive literature review, a five-tier maturity model was proposed, explained, and instantiated in PowerBI and Tableau. The testing of the model was found to be simple and intuitive, and the research concludes that the model is applicable to enterprise SSBI environments. This research is …