Browsing by Subject "Machine Learning"
Now showing items 1-20 of 31
-
A Deep Recurrent Neural Network with Iterative Optimization for Inverse Image Processing Applications
(2021-12-01)Many algorithms and methods have been proposed for inverse image processing applications, such as super-resolution, image de-noising, and image reconstruction, particularly with the recent surge of interest in machine ... -
A DESIGN STRATEGY TO IMPROVE MACHINE LEARNING RESILIENCY OF PHYSICALLY UNCLONABLE FUNCTIONS USING MODULUS PROCESS
(2023-12-01)Physically unclonable functions (PUFs) are hardware security primitives that utilize non-reproducible manufacturing variations to provide device-specific challenge-response pairs (CRPs). Such primitives are desirable for ... -
A Study of Machine Learning Techniques for Dynamical System Prediction
(2022-05-01)Dynamical Systems are ubiquitous in mathematics and science and have been used to model many important application problems such as population dynamics, fluid flow, and control systems. However, some of them are challenging ... -
Advanced Analytics in Smart Manufacturing: Anomaly Detection Using Machine Learning Algorithms and Parallel Machine Scheduling Using a Genetic Algorithm
(2021-12-01)Industry 4.0 offers great opportunities to utilize advanced data processing tools by generating Big Data from a more connected and efficient data collection system. Making good use of data processing technologies, such as ... -
An Application of Clustering and Cluster Update Methods to Boiler Sensor Prediction and Case-Based-Reasoning to Boiler Repair
(2019-12-01)Driven by demand from both consumers and manufacturers alike, Internet of Things (IoT) capabilities are being built into more products. Consumers want more control and access to their devices, while manufacturers can find ... -
Automated Feature Extraction from Large Cardiac Electrophysiological Data Sets, and a Population Dynamics Approach to the Distribution of Space Debris in Low-Earth Orbit
(2022-12-01)We present two applications of mathematics to relevant real-world situations. In the first chapter, we discuss an automated method for the extraction of useful data from large file-size readings of cardiac data. We begin ... -
Bayesian Methods and Machine Learning for Processing Text and Image Data
(2017-08-01)Classification/clustering is an important class of unstructured data processing problems. The classification (supervised, semi-supervised and unsupervised) aims to discover the clusters and group the similar data into ... -
Chasing Transients: Constructing Local Galaxy Catalogs for Electromagnetic Follow-Up of Gravitational Wave Events
(2022-12-01)Gravitational waves (GWs) provide a new window for observing the universe which is not possible using traditional electromagnetic (EM) wave astronomy. The coalescence of compact object binaries, such as black holes (BHs) ... -
Complex Network Analysis for Scientific Collaboration Prediction and Biological Hypothesis Generation
(2014-08-01)With the rapid development of digitalized literature, more and more knowledge has been discovered by computational approaches. This thesis addresses the problem of link prediction in co-authorship networks and protein--protein ... -
Cross Dataset Evaluation for IoT Network Intrusion Detection
(2020-12-01)With the advent of Internet of Things (IOT) technology, the need to ensure the security of an IOT network has become important. There are several intrusion detection systems (IDS) that are available for analyzing and ... -
Development and Evaluation of an Interdisciplinary Periodontal Risk Prediction Tool Using a Machine Learning Approach
(2017-05-01)Periodontitis (PD) is a major public health concern which profoundly affects oral health and concomitantly, general health of the population worldwide. Evidence-based research continues to support association between PD ... -
Dictionary-based Data Generation for Fine-Tuning Bert for Adverbial Paraphrasing Tasks
(2020-08-01)Recent advances in natural language processing technology have led to the emergence of large and deep pre-trained neural networks. The use and focus of these networks are on transfer learning. More specifically, retraining ... -
Emotion Classification and Intensity Prediction on Tweets
(2023-05-01)The task of finding an emotion associated with the text from individuals on a social media platform has become very crucial as it influences the current state of mind of a particular individual in real life. It also helps ... -
Estimating GPU Speedups for Programs Without Writing a Single Line of GPU Code
(2014-08-15)Heterogeneous processing using GPUs is here to stay and today spans mobile devices, laptops, and supercomputers. Although modern software development frameworks like OpenCL and CUDA serve as a high productivity ... -
Evaluating Classifiers During Dataset Shift
(2023-05-01)Deployment of a classifier into a machine learning application likely begins with training different types of algorithms on a subset of the available historical data and then evaluating them on datasets that are drawn from ... -
Fighting Health Misinformation: Building an Interpretable, Criteria-Driven System to Assist the Public in Assessing the Quality of Health News
(2022-12-01)Machine learning techniques have been shown to be efficient at identifying health misinformation. However, interpreting a classification model remains challenging due to the model's intricacy. The absence of a justification ... -
Image-Based Cancer Diagnosis Using Novel Deep Neural Networks
(2022-12-01)Cancer is the major cause of death in many nations. This serious illness can only be effectivelytreated if it is diagnosed early. In contrast, biomedical imaging presents challenges to both clinical institutions and ... -
Internal Fault Diagnosis of MMC-HVDC Based on Classification Algorithms in Machine Learning
(2019-05-01)With the development of the HVDC system, MMC-HVDC is now the most advanced technology that has been put into use. In power systems, faults happen during the operation due to natural reasons or devices physical issues, which ... -
Internal Fault Diagnosis of MMC-HVDC Based on Classification Algorithms in Machine Learning
(2019-05-01)With the development of the HVDC system, MMC-HVDC is now the most advanced technology that has been put into use. In power systems, faults happen during the operation due to natural reasons or devices physical issues, which ... -
Machine-Learning-based Prediction of Sepsis Events from Vertical Clinical Trial Data: a Naïve Approach
(2020-08-01)Sepsis is a potentially life-threatening condition characterized by a dysregulated, disproportionate immune response to infection by which the afflicted body attacks its own tissues, sometimes to the point of organ failure, ...