Deep learning has greatly improved visual recognition in recent years. However, recent research has shown that there exist many adversarial examples that can negatively impact the performance of such an architecture. Different from previous perspectives that focus on improving the classifiers to detect the adversarial examples, this work focuses on...
This dissertation is separated into two parts according to the two major distinct research projects. In Part I, the full account of synthetic studies toward C10-functionalized lycopodium alkaloids is described. In Part II, the detailed discussion on the exploration of the Pummerer cyclization methodology and its application to the total...
The first total syntheses of triptobenzene T, vitexifolin C, 4-epi-triptobenzene L, triptobenzene L, and nepetaefolin F have been accomplished through an enantioselective, common intermediate approach and have enabled the confirmation and/or establishment of the absolute stereochemistry of each natural product synthesized. Application of three new and/or underutilized Pummerer reaction pathways...
Two viable pathways (vinyl sulfide and acyl oxonium ion) for the Pummerer cyclization have been unraveled that expand the reaction scope and capabilities. Use of Bronsted-enhanced Lewis acidity was key to realization of the vinyl sulfide pathway, whereas selective complexation of the sulfur lone pair facilitated the unprecedented acyl oxonium...
Mismatch repair (MMR) system performs mainly three roles to maintain
genomic stability, correct DNA biosynthetic errors, ensure the fidelity of
genetic recombination, and in mammalian cells participate in the cellular
response to some DNA damages. Deficiencies in mismatch repair increase
mutation rates and cancer risks. In eukaryotes, the MMR system...
Low-distortion architecture is widely used in wideband discrete-time switched-capacitor delta-sigma ADC design. However, it suffers from the power-hungry active adder and critical timing for quantization and dynamic element matching (DEM). To solve this problem, this dissertation presents a delta-sigma modulator architecture with shifted loop delays. In this project, shifted loop...
This thesis investigates an implementation of speech recognition front-end. It is an application specific integrated circuit (ASIC) solution. A Mel Cepstrum algorithm is implemented for the feature extraction. We present a new mixed split-radix and radix-2 Fast Fourier Transform (FFT) algorithm, which can effectively minimize the number of complex multiplications...
Heatmap regression has became one of the mainstream approaches to localize facial landmarks. As Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) are becoming popular in solving computer vision tasks, extensive research has been done on these architectures. However, the loss function for heatmap regression is rarely studied. In...
In this thesis, we introduce a novel Explanation Neural Network (XNN) to explain the predictions made by a deep network. The XNN works by embedding a high-dimensional activation vector of a deep network layer non-linearly into a low-dimensional explanation space while retaining faithfulness i.e., the original deep learning predictions can...
Deep neural networks currently comprise the backbone of many applications where safety is a critical concern, for example: autonomous driving and medical diagnostics. Unfortunately these systems currently fail to detect out-of-distribution (OOD) inputs and can be prone to making dangerous errors when exposed to them. In addition, these same systems...