Integrated Machine Learning And Optimization Approaches,
2022
New Jersey Institute of Technology
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,
2022
University of New Mexico
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 …
An Accurate Real-Time Method For Face Mask Detectionusing Cnn And Svm,
2022
University of Tabuk
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 …
Influence Of Waist Circumference Measurement Site On Visceral Fat And Metabolic Risk In Youth,
2022
The Texas Medical Center Library
Influence Of Waist Circumference Measurement Site On Visceral Fat And Metabolic Risk In Youth
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 …
Hybrid Artificial Bee Colony And Improved Simulatedannealing For The Capacitated Vehicle Routing Problem,
2022
University of Muhammadiyah Gresik, Indonesia
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 …
Adaptive Neuro-Fuzzy Inference System For Waste Prediction,
2022
Universitas Mulawarman, Indonesia
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 …
Indonesian Language Term Extraction Using Multi-Task Neural Network,
2022
Institut Sains dan Teknologi Terpadu Surabaya
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 …
Associated Patterns In Open-Ended Concept Maps Within E-Learning,
2022
Universitas Negeri Malang
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 …
Collaborative Interprofessional Health Science Student Led Realistic Mass Casualty Incident Simulation,
2022
The Texas Medical Center Library
Collaborative Interprofessional Health Science Student Led Realistic Mass Casualty Incident Simulation
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 …
Big Data Technology Enabling Legal Supervision,
2022
Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
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,
2022
School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100049, China
Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China
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 …
Digital Technology Enables Construction Of National Governance Modernization,
2022
Xidian University, Xi'an 710126, China
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,
2022
School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100049, Chin
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, …
Strategic Perspective Of Leveraging New Generation Information Technology To Enable Modernization Of Emergency Management,
2022
School of Government, Nanjing University, Nanjing 210023, China
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 …
Digital Technology Enables Modernization Of National Statistics,
2022
School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an 710049, China
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, …
Application Of Distributed Fiber-Optic Sensing For Pressure Predictions And Multiphase Flow Characterization,
2022
Louisiana State University and Agricultural and Mechanical College
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,
2022
Macalester College
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,
2022
The Texas Medical Center Library
Detection Of Stroke With Retinal Microvascular Density And Self-Supervised Learning Using Oct-A And Fundus Imaging, 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 …
Fairness And Privacy In Machine Learning Algorithms,
2022
Kennesaw State University
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, …
Computer Clinical Decision Support That Automates Personalized Clinical Care: A Challenging But Needed Healthcare Delivery Strategy,
2022
The Texas Medical Center Library
Computer Clinical Decision Support That Automates Personalized Clinical Care: A Challenging But Needed Healthcare Delivery Strategy, 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 …
