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Design of Multi-modality Deep Fusion Architecture for Deep Acoustic Analytics
(2021)
significant challenges to conduct accurately deep learning in the environmental and health audio domain. These challenges may occur due to the various field and categories, e.g., environmental, animal sounds, noises, and human body sounds. Specifically...
A semantic framework for event-driven service composition
(University of Missouri--Kansas City, 2011-09-14)
Service Oriented Architecture (SOA) has become a popular paradigm for designing
distributed systems where loosely coupled services (i.e. computational entities) can be
integrated seamlessly to provide complex composite ...
Dynamic Activity Predictions using Graph-based Neural Networks for Time Series Forecasting
(2023)
Time series forecasting is a vital task in numerous fields, and traditional methods,
machine learning models, and neural graph networks have been employed to improve
prediction accuracy. However, these techniques need ...
AI-based Edge Computing System for Event Based Analytics
(2021)
, desirable availability, and privacy protection. However, cloud-based AI solutions are not readily deployable to the edge in IoT's data-driven world because of the difficulties of dealing with diverse sources, lack of availability, and network traffic...
StoryNet: A 5W1H-based knowledge graph to connect stories
(2021)
embeddings were used and both were compared using an ensemble score (average of CoLA, SST-2, MRPC, QQP, STS-B, MNLI, QNLI, and RTE) along with BLEU and ROUGE scores. A few approaches are studied for training-based analysis - using BERT, Roberta, XLNet, ALBERT...
Software Analytics for Improving Program Comprehension
(2021)
) complex call graphs can become very difficult to understand making call graphs much harder to visualize and interpret by a developer and thus increases the overhead in program comprehension; (2) they are often limited to a single level of granularity...
Deep Open Representative Learning for Image and Text Classification
(2020)
representatives of the discovery process from data to the knowledge that can be used to perform reasoning. In this dissertation, a novel model named Class Representative Learning (CRL) is proposed, a class-based classifier designed with the following unique...
A Graph Analytics Framework for Knowledge Discovery
(2016)
In the current data movement, numerous efforts have been made to convert and normalize
a large number of traditionally structured and unstructured data to semi-structured data
(e.g., RDF, OWL). With the increasing number ...
Second chance competitive autoencoders for understanding textual data
(2021)
three novel autoencoders, SCAT (Second Chance Autoencoder for Text), SSCAT (Similarity-based SCAT), and CSCAT (Coherent-based SCAT). Our autoencoders utilize competitive learning among the k winner neurons in the bottleneck layer, which become...
Topic network: a semantic model for effective learning
(University of Missouri--Kansas City, 2011-06-08)
. This can be achieved by defining a learning model that is based on the automated analysis of the importance of topics and relationships between them. In this thesis, an intelligent and dynamic model called Topic Network is proposed. Given a topic...
Automated End-to-End Management of the Deep Learning Lifecycle
(2020)
to form a stepping-stone to facilitate the \textit{comprehension} of the overall lifecycle implementation (i.e., source code). Specifically, we introduce Code2Graph to facilitate the exploration and tracking of the implementation and its changes over time...
Topic Sentiment Trend Detection and Prediction for Social Media
(2020)
in social media. The proposed framework was designed to cope with the following tasks: topic trend detection, sentiment analysis, and topic prediction. The VADER-based time series sentiment analysis and the KATE-based topic modeling methods were applied...
RUPEE: A Big Data Approach to Indexing and Searching Protein Structures
(2021)
not based on structure alone. In the case of sequence clustering, strong structure similarities are often hidden behind cluster representatives. Existing protein structure searches that focus on better quality results often perform full pairwise protein...
ADInsight: A Multimodal and Explainable Framework for Alzheimer's Disease Progression and Conversion Prediction
(2023)
ADInsight represents the crux of this dissertation, introducing an integrated and explainable framework centered on predicting Alzheimer's disease (AD) conversion, particularly for those at the early stage of mild cognitive ...
Multiple-valued logic: technology and circuit implementation
(2021)
Computing technologies are currently based on the binary logic/number system, which is dependent on the simple on and off switching mechanism of the prevailing transistors. With the exponential increase of data processing and storage needs...
DMLA: A Dynamic Model-Based Lambda Architecture for Learning and Recognition of Features in Big Data
(University of Missouri--Kansas City, 2016)
-time, real-world events (e.g., fire alarm alerts, babies needing immediate attention, etc.) that would require a quick response by the users. Detection of contextual information and utilizing the appropriate model dynamically has been distributed among...
DL-DI: A Deep Learning Framework for Distributed, Incremental Image Classification
(University of Missouri--Kansas City, 2017)
Deep Learning technologies show promise for dramatic advances in fields such as image
classification and speech recognition. Deep Learning (DL) is a class of Machine Learning algorithms
that involves learning of multiple ...
Semantic Frameworks for Document and Ontology Clustering
(University of Missouri--Kansas City, 2011-01-20)
The Internet has made it possible, in principle, for scientists to quickly find research papers of interest. In practice, the overwhelming volume of publications makes this a time consuming task. It is, therefore, important to develop efficient ways...
Context-Aware Adaptive Model for Smart Energy
(2013)
Building energy awareness and providing feedback on energy use is a vital component in transforming the behavior of individuals and communities towards a more efficient use of electric power. An enormous amount of energy ...
A Novel Deep Learning-Based Framework for Context Aware Semantic Segmentation in Medical Imaging
(2023)
automated screening system based on a unified modeling approach of diagnosis. The system can extract multiple ocular features with a novel semantic segmentation network to early detect the symptoms of retinal disease. We proposed a novel technique of dynamic...