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Design of learning objects to support constructivist learning environments
(University of Missouri--Columbia, 2005)
Using Constructivism to guide the design of learning objects, we develop a generic structure that classifies knowledge into different types on different levels. With a simple generic structure of learning object, learners can easily share knowledge...
Increase students learning effectiveness and promote active learning in sexual health and body image through VR technology
(University of Missouri--Columbia, 2023)
proven that VR is helpful to improve student's learning effectiveness and engagement. The purpose of this thesis is to explore if sexual health and body image education through VR is an optimal option over traditional instruction materials, such as Power...
"Bring-your-own" plug-in management for next-generation science gateway applications
(University of Missouri--Columbia, 2020)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI-COLUMBIA AT REQUEST OF AUTHOR.] Science gateways are web-portals that hide background complexities of underlying resources and expose easy-to-use capabilities of scientific applications to users...
Next-generation DevOps for network and compute-intensive applications
(University of Missouri--Columbia, 2023)
and system resilience through network microsegmentation; and 3) a highly usable training module for improving knowledge and skills in deploying machine learning based applications using KubeFlow on a public cloud platform. We evaluate these contributions both...
An application of machine learning techniques to interactive, constraint-based search
(University of Missouri--Columbia, 2005)
Search engine users frequently place additional constraints on search results that are not included in the user's original query. To respond to these additional constraints, search engine designers frequently add an "advanced ...
Application of deep reinforcement learning for battery design
(University of Missouri--Columbia, 2020)
machine-learning framework called Material Artificial Intelligence Robotics-driven System (MARS), aiming to reduce the costs with the help of machine learning techniques. We applied advanced deep-learning networks to better predict conductivity. We...
Fuzzy-based conversational recommender for data-intensive science gateway applications
(University of Missouri--Columbia, 2018)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Neuro-scientists are increasingly relying on parallel and distributed computing resources for analysis and visualization of their neuron simulations. Although science gateways...
Fuzzy-based conversational recommender for data-intensive science gateway applications
(University of Missouri--Columbia, 2018)
Neuro-scientists are increasingly relying on parallel and distributed computing resources for analysis and visualization of their neuron simulations. Although science gateways (SG) have democratized relevant high performance/throughput resources...
Advance : adversarial collaborative learning for detection and verification of artificially created examples
(University of Missouri--Columbia, 2023)
regarding the authenticity of information consumed by the general public, exemplified by the prevalence of deepfakes. Consequently, various approaches have been proposed to detect adversarial generated data, aiming to address this challenge. However, a...
Feasibility of the nintendo Ds for teaching problem-based learning in kindergarten through twelfth grade students
(University of Missouri--Columbia, 2008)
Problem-based learning (PBL) is an instructional approach that has been employed successfully since the 1960s and continues to gain mainstream acceptance in many areas of study. PBL is an instructional, and curricular, learner-centered approach...
Enhancing network-edge connectivity and computation security in drone video analytics
(University of Missouri--Columbia, 2020)
) an intelligent and dynamic decision algorithm based on machine learning to detect anomaly events without decreasing the performance in a real-time FANET deployment, and (iii) a web-based experiment control module that features a graphical user interface to assist...
Dynamic spatio-temporal graph neural networks for hot topic prediction in scientific literature
(University of Missouri--Columbia, 2020)
to be an efficient method to extract information from texts and use the information to predict the future trends. Under the thriving background of Deep Learning, Graph Neural Network (GNN) is able to capture the information from graph structures. There are various...
Capturing and managing daily symptoms data in the treatment of autism spectrum disorder using mobile technology
(University of Missouri--Columbia, 2020)
. Sensitive individual health information becomes widely available and accessible through smartphones and wearable devices. It is critical for developers to use and store personal health information securely, and comply with government regulations of the user...
Conversation understanding and realistic artificial crash data generation with deep learning
(University of Missouri--Columbia, 2023)
[EMBARGOED UNTIL 5/1/2024] This dissertation focuses on conversation understanding and realistic crash data generation with deep learning. Conversation understanding includes conversational outcome, formality, and politeness prediction...
Explainable parts-based concept modeling and reasoning
(University of Missouri--Columbia, 2023)
State-of-the-art artificial intelligence (AI) learning algorithms heavily rely on deep learning methods that exploit correlation between inputs and outputs. While effective, these methods typically provide little insight to the reasoning process...
Augmenting biological pathway extraction with synthetic data and active learning
(University of Missouri--Columbia, 2022)
iteratively generates each pathway relationship uniquely and is demonstrated to improve the generalization of our object detection model significantly across a variety of settings. Additionally, with the capability to generate unique and informative samples...
Improving object recognition in aerial image and ambulatory assessment analysis by deep learning
(University of Missouri--Columbia, 2019)
information. This dissertation focuses on two types of data: aerial images and physiological sensor data. Several new methods have been proposed based on deep learning techniques to advance the state-of-the-art in analyzing these data. For aerial images, a new...
A comprehensive web-based platform for multi-omics data-driven phenotype prediction and marker discovery
(University of Missouri--Columbia, 2023)
and other biological phenomena. Moreover, the server integrates The Cancer Genome Atlas (TCGA) datasets with long-term and non-long-term survival phenotypes. The server and the Python-based deep-learning model are available at https://g2pdeep.org and https://github.com/shuaizengMU...
Intelligence-driven edge computing for visual cloud computing systems
(University of Missouri--Columbia, 2018)
offloading costs in order to better inform scheduling decisions for multi-edge scales. We investigate several aspects of the learning problem such as feature engineering, model selection, offline data generation using networking testbeds, and the benefits...
Fine-grained authorization in the Great Plains network virtual organization
(University of Missouri--Columbia, 2007)
The last few years have experienced a steady growth in research institutions showing interest in developing research projects that involve more than one institution's computing resources forming so called virtual organizations. ...