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Detecting targeted data poisoning attacks on deep neural networks
(University of Missouri--Columbia, 2022)
Deep neural networks (DNNs) are widely used for various facial image-recognition purposes, including facial recognition and subsequent authentication, and the detection of altered facial images. Unfortunately, due to their ...
"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...
Conversation understanding and realistic artificial crash data generation with deep learning
(University of Missouri--Columbia, 2023)
. Formality-BERT is trained on a public dataset that contains four genres of text and outperforms existing models by 14 points on the Spearman correlation between predicted formality and human-labeled formality for four genres. We propose Politeness...
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 ...
Building environmentally-aware classifiers on streaming data
(University of Missouri--Columbia, 2022)
) for solving the same task. SPC maintains a fixed number of structures to model the data stream. These structures can be updated and merged based only on their "footprints", that is, summary statistics that contain all of the information from the stream needed...
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. ...
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...
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...
Explainable cohort discoveries driven by exploratory data mining and efficient risk pattern detection
(University of Missouri--Columbia, 2022)
Finding small homogeneous subgroup cohorts in a large heterogeneous population is a critical process for hypothesis development within a broad range of applications, such as fraud detection, ad targeting, and geospatial ...
An interpretable protein localization prediction framework
(University of Missouri--Columbia, 2021)
at https://www.mu-loc.org/....
IICON : identifying informative comments in online news
(University of Missouri--Columbia, 2023)
[EMBARGOED UNTIL 12/1/2024] Many news outlets are discontinuing their comment sections due to moderation challenges as manual moderation for identifying irrelevant and informative comments is inadequate, costly, and ...
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. ...
Pathway curator: an online webserver extracting genes and interactions from figures
(University of Missouri--Columbia, 2022)
increase of the literature requires laborious extraction of information from a publication at a time. A gene pathway map recognition system is devised and implemented in this study. Based on the pathway map and relevant information supplied by users...
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 ...