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Dynamic agent safety logic : theory and applications
(University of Missouri--Columbia, 2019)
Modal logic is a family of logics for reasoning about relational structures, broadly construed. It sits at the nexus of philosophy, mathematics, software engineering, and economics. By modeling a target domain as a relational ...
Adversarial robustness of deep learning enabled industry 4.0 prognostics
(University of Missouri--Columbia, 2020)
The advent of Industry 4.0 in automation and data exchange leads us toward a constant evolution in smart manufacturing environments, including extensive utilization of Internet-of-Things (IoT) and Deep Learning (DL). Specifically, the state...
Decoder-learning based distributed source coding for high-efficiency, low-cost and secure multimedia communications
(University of Missouri--Columbia, 2008)
Conventional multimedia compression leverages the source statistics at the encoder side. This is not suitable for some emerging applications such as wireless sensor networks, where the encoders usually have limited ...
PRIMEGENSv2 : a service based platform using object oriented model view controller design pattern
(University of Missouri--Columbia, 2009)
architecture using object oriented methodologies of abstraction and encapsulation. Application release notes and its related manuals can be found on the webpage of Digital Biology Laboratory (http://digbio.missouri.edu/primegens/)....
Knowledge-driven multidimensional indexing for content-based information retrieval
(University of Missouri--Columbia, 2008)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] Media data are being generated at rates unimaginable only years ago. We face challenges in providing efficient and accurate access to media content, using minimal manual human...
Applications of deep neural networks to protein structure prediction
(University of Missouri--Columbia, 2018)
. In extensive experiments on multiple datasets, the proposed deep neural architectures outperformed the best existing methods and other deep neural networks significantly: The proposed DeepNRN achieved highest Q8 75.33, 72.9, 70.8 on CASP 10, 11, 12 higher than...
Optimization of a software-only H.264 encoder
(University of Missouri--Columbia, 2008)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] With the booming of semiconductor and information technology, digital video have become more popular than ever. The large volume nature of video data has made the capturing...
MUPrimer : a tool for finding allele specific PCR-primers for homologous gene sequences
(University of Missouri--Columbia, 2009)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] Polymerase chain reaction (PCR) amplification of specific regions of DNA has proven to be a powerful tool in molecular biology research. Synthetic short oligonucleotide DNA...
Real-time visualization of massive imagery and volumetric datasets
(University of Missouri--Columbia, 2006)
on top of an existing out-of-core image tile caching and paging system known as Kolam, developed at the University of Missouri, Columbia. Discussions of Kolam's architecture are provided, which include image representations, tile request methods, cache...
Deep learning methods for 360 monocular depth estimation and point cloud semantic segmentation
(University of Missouri--Columbia, 2022)
Monocular depth estimation and point cloud segmentation are essential tasks for 3D scene understanding in computer vision. Depth estimation for omnidirectional images is challenging due to the spherical distortion issue ...
Algorithm design and error analysis of quantized RSSI based localization in wireless sensor networks
(University of Missouri--Columbia, 2007)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] Wireless Sensor Network localization is an important aspect in sensor network applications such as tracking and monitoring. The general goal of localization is to obtain...
Improvement of decoding engine & phonetic decision tree in acoustic modeling for online large vocabulary conversational speech recognition
(University of Missouri--Columbia, 2007)
In this work, new approaches are proposed for online large vocabulary conversational speech recognition, including a fast confusion network algorithm, novel features and a Random Forests based classifier for word confidence ...
Fast and adaptive H.264/AVC video coding for network based applications
(University of Missouri--Columbia, 2009)
As the state of the art video coding standard, H.264/AVC achieves significant coding performance gain comparing to its predecessors. Nevertheless, the advance comes at huge complexity increase of the encoder, which may ...
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 ...
Adaptive bilateral extensor for image interpolation
(University of Missouri--Columbia, 2006)
A novel algorithm for image interpolation, referred to as adaptive bilateral extensor interpolation, is proposed in this thesis. It combines useful features of an extensor based algorithm, utilizing a non-linear mapping ...
An interpretable protein localization prediction framework
(University of Missouri--Columbia, 2021)
Protein localization is related to many human diseases. Therefore, the prediction of protein localization is an essential task that has been extensively studied. Additionally, the study of the localization mechanism can provide more biological...
Ensemble methods in large vocabulary continuous speech recognition
(University of Missouri--Columbia, 2008)
in the telemedicine automatic captioning system developed by the SLIPL group of the University of Missouri--Columbia....
Genome scale meta analysis of microarrays for biological inferences
(University of Missouri--Columbia, 2009)
In this present era of high-throughput technologies, meta-analysis is being widely used to integrate multiple similar high throughput studies. Here we propose a novel framework for applying meta-analysis techniques on ...
Machine learning methods for 3D object classification and segmentation
(University of Missouri--Columbia, 2018)
Object understanding is a fundamental problem in computer vision and it has been extensively researched in recent years thanks to the availability of powerful GPUs and labelled data, especially in the context of images. However, 3D object...
Local and deep texture features for classification of natural and biomedical images
(University of Missouri--Columbia, 2019)
Developing efficient feature descriptors is very important in many computer vision applications including biomedical image analysis. In the past two decades and before the popularity of deep learning approaches in image ...