The main problem this internship project explores is the selection, conversion, and encoding of mathematical models that pertain to the finance industry for processing on available types of analog optimization processors. This research investigation aims to develop new algorithms and code that take advantage of an analog optimization process which acts as an "oracle" for a classical Turing Machine computer. This will be done by developing methods to translate a range of problems into the ideal form for currently available adiabatic annealing hardware.
Carbonate hosted hydrothermal ore deposits commonly develop narrow mineral alteration (i.e. visible) haloes, complicating exploration targeting. In contrast, hydrothermal modification of the country rock’s stable isotope composition usually extends far beyond visible alteration. Hence, stable isotope “mapping” is an effective tool to aid exploration for carbonate?hosted deposits. However, widespread utilization of stable isotope data has been hampered by its high cost and long turn-around times.
Features identification and extraction from remotely sensed (RS) image is an ongoing research endeavor and has wider applications. Traditionally it has been based on pixel-based image analysis which has proved to be inefficient and ineffective especially for very high resolution (VHR) data. More recently object-based image analysis (OBIA) has gained a wider recognition because of its potential for accurately extracting objects from RS data corresponding to real-world features.
Features identification and extraction from remotely sensed (RS) image is an ongoing research endeavor and has wider applications. Traditionally it has been based on pixel-based image analysis which has proved to be inefficient and ineffective especially for very high resolution (VHR) data. More recently object-based image analysis (OBIA) has gained a wider recognition because of its potential for accurately extracting objects from RS data corresponding to real-world features.
Changes in sea-level are attributable mainly to crustal deformation, changes in global ocean volumes (eustasy) and the response of the Earth's crust to glaciation (isostasy). On the British Columbia coast, sea-level history is complex owing to regional differences in these factors. A geographic data gap exists in our understanding of Holocene (past 10,000 years) sea-level change and landscape evolution along the central coast. The proposed research will help close this gap, by studying post-glacial sea-level and landscape response on Calvert Island.
Changes in sea-level are attributable mainly to crustal deformation, changes in global ocean volumes (eustasy) and the response of the Earth's crust to glaciation (isostasy). On the British Columbia coast, sea-level history is complex owing to regional differences in these factors. A geographic data gap exists in our understanding of Holocene (past 10,000 years) sea-level change and landscape evolution along the central coast. The proposed research will help close this gap, by studying post-glacial sea-level and landscape response on Calvert Island.
Recent advancements in TEM sample preparation techniques using the latest generation of dual focused ion and electron beam (FIB-SEM) instrumentation allows for high-resolution examination of textures, elemental composition and structures of minerals at unprecedented resolution. These instruments enable the extraction of FIB-prepared TEM foils at any desired location of the sample (Wirth, 2004, 2009).
When using geophysical methods to gain insight into the structure of earth, large geophysical data sets are collected. Since the earth is a 3D structure, the data must be interpreted and processed in 3D to be of the most value in the exploration process. This research will develop the capability to invert large gravity, magnetics, and airborne EM datasets accurately and in a reasonable timeframe. This requires the research and development of inversion software, data visualization and QC software, and inversion setup scripts.
Features identification and extraction from remotely sensed (RS) image is an ongoing research endeavor and has wider applications. Traditionally it has been based on pixel-based image analysis which has proved to be inefficient and ineffective especially for very high resolution (VHR) data. More recently object-based image analysis (OBIA) has gained a wider recognition because of its potential for accurately extracting objects from RS data corresponding to real-world features.