We explore the application of deep learning to the disparate fields of natural language processing and computational biology. Both the sentences uttered by humans as well as the RNA and protein sequences found within the cells of their bodies can be considered formal languages in computer science, as sets of...
Intrinsically disordered proteins (IDP) are a class of proteins that lack a three-dimensional structure and their prevalence and diverse functions in the cell have only been discovered relatively recently. The intermediate chain (IC) subunit of the microtubule motor protein complex dynein contains an N-terminal disordered region, N-IC, which is central...
Designing spectral efficient, high-speed wireless links that offer high quality-
of-service and range capability has been a critical research and engineering challenge. In this thesis, we mainly address the complexity and performance issues of
channel estimation and data detection in multiple-input multiple-output (MIMO)
orthogonal frequency division multiplexing (OFDM) systems over...
Multiple-input multiple-output (MIMO) antenna technology is promising
for high-speed wireless communications without increasing the transmission band-
width. Space time coding (STC) is a scheme that employs multiple antennas to
increase transmission rate or to improve transmission quality. STC is used widely
in mobile cellular networks, wireless local area networks (WLAN)...
RNAs play important roles in the central dogma of molecular biology, and are involved in multiple biology processes such as chromatin modification, transcriptional interference and translation initiation. The functions of RNAs, especially non-coding RNAs, are highly related to its secondary structures, therefore computational methods for RNA structure prediction are of...
Maintaining the sustainability of the earth’s ecosystems has attracted much attention as these ecosystems are facing more and more pressure from human activities. Machine learning can play an important role in promoting sustainability as a large amount of data is being collected from ecosystems. There are at least three important...
The advent of deep learning models leads to a substantial improvement in a wide range of NLP tasks, achieving state-of-art performances without any hand-crafted features. However, training deep models requires a massive amount of labeled data. Labeling new data as a new task or domain emerges consumes time and efforts...
Natural Language Comprehension is a challenging domain of Natural Language Processing. To improve a model’s language comprehension/understanding, one approach would be to enrich the structure of the model to enhance its capability in learning the latent rules of the language.
In this dissertation, we will first introduce several deep models...
We present an experimental investigation of the effect of kinetic energy on the ion doping efficiency of superfluid helium droplets using cesium cations from a thermionic emission source. The kinetic energy of Cs⁺ is controlled by the bias voltage of a collection grid collinearly arranged with the droplet beam. Efficient...
The isotopic composition of water vapour provides integrated perspectives on the hydrological histories of air masses and has been widely used for tracing physical processes in hydrological and climatic studies. Over the last two decades, the infrared laser spectroscopy technique has been used to measure the isotopic composition of water...