Browsing by Subject "Machine learning"
Now showing items 1-20 of 37
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A hierarchical, fuzzy inference approach to data filtration and feature prioritization in the connected manufacturing enterprise
(2018-11-19)In manufacturing, the technology to capture and store large volumes of data developed earlier and faster than corresponding capabilities to analyze, interpret, and apply it. The result for many manufacturers is a collection ... -
A Reinforcement Learning Approach to Sequential Acceptance Sampling as a Critical Success Factor for Lean Six Sigma
(2020-05-01)In the 21st century, globalization coupled with technological advancement and free trade has created competition among various businesses enterprises. This competition has led many businesses to adopt various management ... -
Analysis of Gait Motion Sensor Authentication with Machine Learning
(2024-04)In recent decades, mobile devices have evolved in potential and prevalence significantly while advancements in security have stagnated. As smartphones now hold unprecedented amounts of sensitive data, there is an increasing ... -
Analysis of privacy threats in internet of medical things (IoMT) using machine learning
(University of Wisconsin - Whitewater, 2022-12)The growing market for Internet of Medical Things (IoMT) promises new conveniences for consumers while presenting new challenges for preserving consumers’ privacy. Most of the IoMT devices have sensors that keep capturing ... -
Application of machine learning methods to imager cloud property estimation and the feasibility of their use in operations and climate data records
(University of Wisconsin-Madison, 2022) -
Audio generation from a single sample using deep convolutional generative adversarial networks
(University of Wisconsin - Whitewater, 2021-12)Training neural networks require sizeable datasets for meaningful output. It is difficult to acquire large datasets for many types of data. This is especially challenging for individuals and small organizations. We have ... -
Behavioral Biometrics Based User Authentication Schemes Using Machine Learning
(2022-04)In recent years, the amount of secure information being stored on mobile devices has grown exponentially. However, current security schemas for mobile devices such as physiological biometrics and passwords are not secure ... -
A Bibliographic Overview of Colorectal Cancer Detection and Prevention Using Machine Learning Techniques
(2022-04)The idea of using machine learning techniques to identify colorectal cancer is a relatively new one, with most of the research being done in the last ten years. To determine the current state of research in this field, an ... -
Classification of Independent Medical Examination Reports Using Supervised Learning Methods
(2022-04)An independent medical examination (IME) is requested by an insurance provider or self-insured employer to determine the extent of an injured worker’s disability, including if the injury or ailment is permanent or ... -
Continuous, Dynamic User Authentication Using Mobile Touch Dynamics Based on Machine Learning
(2022-04)Modern user authentication measures on mobile devices often include biometric authentication (facial and fingerprint), multi-factor authentication, and password entry as ways of authenticating users. These authentication ... -
Data-Driven Approaches for Cyber-Physical Attack and Defense in Modern Power Grids
(2022-08-01)With the tighter integration of advanced communication and computing technologies, electrical power system is being transformed to more complex, efficient and sustainable smart grid. Today, almost every sector of physical ... -
A Deep Learning Model for Pancreatic Ductal Adenocarcinoma Chemotherapy Outcome Prediction
(2022-04)Pancreatic Ductal Adenocarcinoma (PDAC) is an aggressive abdominal malignancy, with an overall 8.5% 5-year survival rate. PDAC is often detected too late for surgical resection and associated with resistance to chemotherapy ... -
Deep Learning Segmentation of Kidney Tissue Microarrays Using Infrared Spectral Imaging
(2022-04)Renal function is an essential marker in the classification of renal disease and clinical symptoms of renal failure develop when there is 15% renal function. In this study, we used infrared spectroscopic (IR) imaging to ... -
Detecting Stuttering Types Using Deep Learning
(2024-04)Stuttering, recognized as a prevalent speech disfluency, presents considerable challenges in achieving accurate identification. Notably, technological advancements, such as Apple’s Siri, highlight the complexities encountered ... -
Emergent behavior in neuroevolved agents
(University of Wisconsin--Whitewater, 2018-11)Neural networks have been widely used for their ability to create generalized rulesets for a given set of training data. In applications where no such training data exists such as new video games, they are often overlooked ... -
Emotion Sentiment Analysis in Turkish Music
(2024-04)Music has become an indispensable element of human life. Its rhythms, melodies, and harmonies resonate deeply within us, touching our emotions and echoing sentiments in us. In recent years, many music emotion sentiment ... -
Essays on organizational ambidexterity, financial reporting quality, and investment efficiency
(University of Wisconsin - Whitewater, 2021-08)Organizational ambidexterity is a corporate strategy where a firm simultaneously seeks to pursue exploration and exploitation (March, 1991). Despite being described as one of the most interesting subjects in strategy ... -
Estimating Soil Variability using GIS and Deep Learning
(2024-04)This study explores the creative integration of Feature Selection, Geographic Information Systems (GIS), Variable Rate Technology (VRT), and Soil Sensors to improve precision fertilization strategies within arid agricultural ... -
Exploration of Machine Learning Classification Models Used for Behavioral Biometrics Authentication
(2022)Today’s research finds that behavioral biometrics, a method that makes a decision based on the user’s behaviors, can provide a secure authentication method for mobile devices. This presentation will provide a review on the ... -
Human Activity Recognition : Models Using Limited Consumer Device Sensors and Machine Learning Aims Research
(2022-04)Human activity recognition has grown in popularity significantly with daily lifestyle or medical related applications. Data collection is limited to easily accessible devices: smartphones and smartwatches. Eliminate the ...