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"Bring-your-own" plug-in management for next-generation science gateway applications
(University of Missouri--Columbia, 2020)
applications. The OnTimeRecommend Adviser features a variety of recommender modules to help novice/expert users with knowledge discovery through data sources such as e.g., publications, funding records, cloud templates and Jupyter notebooks. Based...
User experience and robustness in social virtual reality applications
(University of Missouri--Columbia, 2020)
Cloud-based applications that rely on emerging technologies such as social virtual reality are increasingly being deployed at high-scale in e.g., remote-learning, public safety, and healthcare. These applications increasingly need mechanisms...
Defeat data poisoning attacks on facial recognition applications
(University of Missouri--Columbia, 2021)
In the modern era, facial photos are used for a wide array of applications, from logging into a smartphone to bragging about a weekend getaway. With the vast amount of use cases for facial images, adversaries will attack ...
Selecting data for multilingual multi-domain neural machine translation on low resource languages
(University of Missouri--Columbia, 2020)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] While machine translation has achieved impressive results on the world's most widely spoken languages, thousands of languages do not have the quantity ...
Enhancing network-edge connectivity and computation security in drone video analytics
(University of Missouri--Columbia, 2020)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI--COLUMBIA AT REQUEST OF AUTHOR.] Unmanned Aerial Vehicle (UAV) systems with high-resolution video cameras are used for many operations such as aerial imaging, search and ...
Explainable contextual data driven fusion
(University of Missouri--Columbia, 2021)
Numerous applications require the intelligent combining of disparate sensor data streams to create a more complete and enhanced observation in support of underlying tasks like classification, regression, or decision making. ...
Knowledge discovery with recommenders for big data management in science and engineering communities
(University of Missouri--Columbia, 2020)
to infer latent patterns within a specific domain in an unsupervised manner. We evaluate our scheme based on large collections of the dataset (i.e., publications, tools, datasets) from bioinformatics and neuroscience domains. Our experiments result using...
Dashboard design and usability study for geospatially enabled information seeking to assist pandemic response and resilience
(University of Missouri--Columbia, 2021)
Counties in Missouri are primarily rural. Rural communities often consist of individuals with poor health, lower economic status, and lack of public health infrastructure. During the COVID- 19 pandemic, most research was centered around urban...
ClaimChain: secure Blockchain platform for handling insurance claims processing
(University of Missouri--Columbia, 2021)
Insurance claims processing involves multi-domain entities and multi-source data, along with a number of human-agent interactions. Consequently, this processing is traditionally manually-intensive and time-consuming. ...
An interpretable protein localization prediction framework
(University of Missouri--Columbia, 2021)
at https://www.mu-loc.org/....
Application of deep reinforcement learning for battery design
(University of Missouri--Columbia, 2020)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] The conventional material research and development are mainly driven by human intuition, labor, and manual decision. It is ineffective and inefficient. ...
Computational protein structure prediction using deep learning
(University of Missouri--Columbia, 2020)
Protein structure prediction is of great importance in bioinformatics and computational biology. Over the past 30 years, many machine learning methods have been developed for this problem in homology-based and ab-initio ...
Privacy-preserving collaboration in an integrated social environment
(University of Missouri--Columbia, 2021)
Privacy and security of data have been a critical concern at the state, organization and individual levels since times immemorial. New and innovative methods for data storage, retrieval and analysis have given rise to ...
Modeling of the acoustic signal of an electric guitar amplifier using recurrent neural networks
(University of Missouri--Columbia, 2021)
Neural networks have topped performance measures across a wide variety of computational tasks. These performances are prevalent within the domain of human perception type tasks such as classification or generation of images, ...
Custom templates based heterogeneous resource allocation for data-intensive applications
(University of Missouri--Columbia, 2020)
resources. However, data-intensive applications' local resources usually present limited capacity and availability due to sizable upfront costs. Moreover, using remote public resources presents constraints at the private edge network domain. Specifically...
Dynamic spatio-temporal graph neural networks for hot topic prediction in scientific literature
(University of Missouri--Columbia, 2020)
With information explosion occurring in past decades, the rapid growth of papers published results in the rapid change of hot topics, especially in the biomedical domain. It turns out very hard for researchers who are ...
Structural modeling of the 3D genome using machine learning
(University of Missouri--Columbia, 2021)
This dissertation, submitted as a partial requirement for completion of the Doctorate of Philosophy, outlines the research performed by Max Highsmith in the BDM Lab. This work includes a functional expansion of a ...
Combining shamir and additive secret sharing to improve efficiency of SMC primitives against malicious adversaries
(University of Missouri--Columbia, 2020)
Secure multi-party computation provides a wide array of protocols for mutually distrustful parties be able to securely evaluate functions of private inputs. Within recent years, many such protocols have been proposed ...
Exploring deep learning techniques to tackle the sparsity problem in recommender systems
(University of Missouri--Columbia, 2020)
With the inception of e-commerce in the early twenty-first century, people's lifestyles have drastically changed. People today tend to do many of their daily routines online, such as shopping, reading the news, and watching ...
Multi-stage cloud framework based on agents for dynamic, scalable, and secure distributed computing
(University of Missouri--Columbia, 2020)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI-COLUMBIA AT REQUEST OF AUTHOR.] We have reached the point of ubiquitous sensing as we continue to witness the explosive growth of the Internet of Things (IoT) and other ...