Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 74 for “"learning methodologies"”.
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Machine learning methodologies for high dimensional biomedical & bioinformatics applications
The impact of machine learning has been greatly expanded due to the increase in computational power in recent years, and has made a significant scientific contribution to many fields. This dissertation primarily investigates and expands the usage of certain machine learning methodologies on …
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Robust Deep Learning Methodologies for Weakly Supervised Remote Sensing Image Classification
… studies and environmental monitoring. Deep learning (DL) has proven very effective in addressing the analytical challenges posed by this data, excelling in image analysis and sequential data processing. However, in remote sensing (RS), DL is often hindered by scarce and imperfect labeled …
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Groundwater Interactive: Interdisciplinary Web-Based Software Incorporating New Learning Methodologies and Technologies
… unified approach in instructional materials and learning methodologies for knowledge they do share. The goals of this research are to lessen the impact of variable student backgrounds and to better integrate the courses to improve teaching and learning, through the development of a multi-tiered, …
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Machine Learning Methodologies for Beyond 5G and 6G Heterogeneous Networks: Prediction, Automation, and Performance Analysis
… unlocks the potential of novel machine learning method- ologies in heterogeneous networks, tackling the complex challenges of prediction, automation, and performance analysis. For instance, to address communication network limitations, supervised learning methods are employed, achieving …
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'Scéal to Storia': creating a framework for cultural heritage education, outreach learning methodologies and international exchange in primary schools
… programmes, it became clear just how variable learning can be. The development of this investigation grew over time to consider the ways in which educational barriers could be alleviated, and how learning opportunities could be adapted and delivered within alternative settings. The theme of …
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Physics-Informed Machine Learning Methodologies Using RAPID for Predicting Eigenvalue and 3-D Fission Distribution in JSI TRIGA Mark-II Research Reactor
The most common methodologies for high-fidelity simulations of nuclear reactors are very slow and require significant computer resources. Machine learning (ML) enables computers the ability to learn from data, allowing well-trained models to produce results quickly and accurately. However, the …
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Industry Based Fundamental Analysis: Using Neural Networks and a Dual-Layered Genetic Algorithm Approach
This research tests the ability of artificial learning methodologies to map market returns better than logistic regression. The learning methodologies used are neural networks and dual-layered genetic algorithms. These methodologies are used to develop a trading strategy to generate excess returns. …
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Physics-informed data-driven frameworks for materials discovery
… comprehensive exploration of scientific machine learning methodologies applied to various aspects of material science and additive manufacturing. Chapter 2 introduces a scientific machine learning framework tailored to understand the synthesis process of flash graphene. Leveraging advanced …
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The most effective methodologies to cultivate a global mindset
The aim of this research was to determine which methodologies were found by expatriate managers to be most effective in the development of a global mindset. In support of this aim, the research also investigated whether a global mindset would vary depending on the methodologies experienced by …
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SDEs and MFGs towards Machine Learning applications
… culminates in exploring pertinent Machine Learning methodologies applied to financial and economic decision-making processes.
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Post-Correctional Education Interventions: A Phenomenological Case Study of Empowerment Education Curriculum for Formerly Incarcerated African American Males
… teaching modules and affective teaching and learning methodologies. This research contains experiential data used to assess how a PCEI affected the identity and self-concept of the participants of a reentry program designed to create an atmosphere of empowerment.</p>
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Machine Learning Methods for Decision Making Inference in Healthcare
Machine learning algorithms are widely regarded as disruptive innovations. They have demonstrated superior performance in many complex domains, such as computer visions, signal processing and natural language processing. One area, in particular, in which machine learning has potential widespread …
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Innovations in Deep Learning for Biotechnology
… techniques prove inadequate. Consequently, deep learning methodologies, such as convolutional networks, present a versatile solution, encompassing automated cell quantification. Nevertheless, procuring the essential label information for supervised learning proves to be a resource-intensive and …
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INTEGRATION OF PHYSICS-INFORMED APPROACHES WITH MACHINE LEARNING TECHNIQUES FOR AERODYNAMICS
The thesis utilizes a fusion of machine learning techniques and physics laws to tackle aerodynamic challenges. Specifically, it employs machine learning methodologies to enhance various aspects of aerodynamics, including the optimization of airfoil designs, prediction of 2D flow fields, and …
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Fostering Inclusion; Challenging the Illusion Critically Reflective Educational Stories: Facilitated by students and graduates with different learning abilities on a Fully Inclusive Higher Education Initiative in Ireland.
… the demonstration of inclusive research and learning methodologies. This demonstration in form, which can be readily accessed by all, reflects the diverse learning styles of students, as well as providing a clear space for readers to engage with the study, should they choose to do so. This …
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Exploring Quadratic Expressions through the 5E Model
… has been a transition towards student-centered learning methodologies within mathematics classrooms. Recognizing the evolving landscape of education and the need for personalized learning experiences, a departure from traditional teacher-centered instruction is imperative to prioritize active …
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A Study on Deepsea Fish Detection Using Convolutional Neural Networks
<p>This study investigates automated deep-learning methodologies for two primary tasks, firstly fish and its habitat classification and deep-sea fish detection using the DeepFish dataset. A pretrained ResNet-50 model attained a validation accuracy of 82.8% for multi-class habitat classification, …
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Rapid remaining-useful-life prediction of Li-ion batteries using image-based machine learning
… This thesis proposes the use of novel machine learning methodologies to predict the remaining-useful-life (RUL) of lithium-ion batteries reliably, accurately, and swiftly. Firstly, a method that prides itself on being publicly available, and which can be easily implemented alongside existing …
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Testing the accuracy of machine learning methods to predict deforestation
… aims to explore the predictive power of machine learning techniques to predict spatial patterns of human activities and compare their accuracy of prediction with a traditional statistical method. Using Monte Carlo simulations, land cover data was generated, mimicking human settlement patterns …
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Diné Bizaad Bitsisiléí Bóhoo’aah: A Basis for learning Navajo
… by ideas in Comprehensible Input and Holistic Learning methodologies, this guide intends to encourage learners to situate themselves in Diné Bizaad basics as well as develop a sense of direction upon completion. A simplified look at the structure of Diné Bizaad words and basic sentences …
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