Augmented Reality (AR) is a method of mixing computer-generated graphics with real-world environments. In AR, observers retain the ability to see their physical surroundings while additional (augmented) information is depicted as simulated graphical objects matched to the real-world view. In the following experiments, optical see-through head-mounted displays (HMDs) were used to present observers with both Augmented and Virtual Reality environments. Observers were presented with varied real, virtual, and combined stimuli with and without the addition of motion parallax. The apparent locations of the stimuli were then measured using quantitative methods of egocentric depth judgment. The data collected from these experiments were then used to determine how observers perceived egocentric depth with respect to both real-world and virtual objects.

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Photodynamic therapy (PDT) currently utilizes drug and light doses which are primarily based on clinical experience. This can lead to a dose which is not sufficient to destroy the entire tumor, or alternatively, it can lead to the undesirable destruction of healthy tissue around the treatment area. PDT of topically applied photosensitizers is one focus of this research. This concerns the diffusion of an externally applied drug into the tissue, as well as its subsequent destruction during the irradiation procedure. This work involves the non-invasive measurement of the inherent fluorescence of the photosensitizer, allowing the determination of the concentration and distribution of drug within the tissue, and thus optimizing this treatment. To do this, one must be able to describe the propagation of light within the tissue. Consequently, a photon diffusion model has been developed to calculate the steady-state spatially resolved fluorescence from a pencil beam excitation in a depth dependent medium. The validity of this model was then verified by comparison with Monte Carlo simulations and measurements made on phantoms with optical properties similar to those of human tissue. Theoretical conditions were then explored, and potential uses of the model were demonstrated. / Thesis / Master of Science (MS)

Yes / Local scour around submarine pipelines can affect the stability of the pipeline. The accurate estimation of the scour around submarine pipelines has been a hot topic of research among marine engineers. This paper presents results from a numerical study of clear-water scour depth below a submarine pipeline for a range of the steady flow conditions. The flow field around the pipeline under scour equilibrium condition is numerically simulated by solving the Reynolds-Averaged Navier-Stokes (RANS) equations with the standard k-ε turbulence closure. The flow discharge through the scour hole for various flow conditions is investigated. The results are used to establish the relationship between the flow discharge and the maximum scour depth. Incorporated with the Colebrook-White equation, the bed shear stress is obtained and an iterative method is proposed to predict the scour depth around the submarine pipeline. The calculated scour depths using the present method agree well with the laboratory measurements, with the average absolute relative error being smaller than that using previous methods, indicating that the proposed method can be used to predict the clear-water scour around the submarine pipeline with satisfactory accuracy. / National Nature Science Fund of China (Grant No.50879084, 51279189), the Open Fund from the State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University (SKHL1302),China Scholarship Council, Public Projects of Zhejiang Province (2016C33095) and the Natural Science Fund of Zhejiang Province (LQ16E090004).

As the world moves towards more green technology and energy-resources, the need for rare earth elements (REE) has increased rapidly. A potential secondary resource for REE’s are mine tailings, and a technique to estimate the thickness of a tailing is the horizontal-to-vertical spectral ratio (HVSR) method. In this project, the depth of a mine-tailing along a profile in Blötberget was estimated using this method. The HVSR method is a non-invasive environmentally friendly seismic method which utilizes ambient noise of the Earth. The method uses seismic sensors consisting of 3 components, which measures ground motion in three directions. The acquired data was processed in the Geopsy software, where certain parameters, such as filtering and window selection, are set to make the most satisfactory results. The Geopsy software provides the user HVSRs for the selected windows. This ratio makes up a curve in the frequency domain, where a fundamental resonant frequency can be derived. The fundamental frequency is determined as the sharp, lowest-frequency peak in the data in case of a strong velocity contrast. This fundamental frequency must fulfil certain criteria to be considered reliable. When the fundamental resonant frequencies could be determined reliable, they were mathematically calculated into the thickness of the tailing by a simple mathematical formula in Excel, using the shear-wave velocity of the overlying layer and the fundamental frequency. The elevation at the location of each sensor and the thickness of the contrasting interface is used to provide a 2-D depth of the mine-tailing. This profile was compared to radiomagnetotelluric measurements. Although the measurement locations were not coinciding reasonable results were obtained.

There is a great need in real world applications for estimating depth through electronic means without human intervention. There are many methods in the field which help in autonomously finding depth measurements. Some of which are using LiDAR, Radar, etc. One of the most researched topic in the field of depth measurements is Computer Vision which uses techniques on 2D images to achieve the desired result. Out of the many 3D vision techniques used, stereovision is a field where a lot of research is being done to solve this kind of problem. Human vision plays an important part behind the inspiration and research performed in this field. Stereovision gives a very high spatial resolution of depth estimates which is used for obstacle avoidance, path planning, object recognition, etc. Stereovision makes use of two images in the image pair. These images are taken with two cameras from different views and those two images are processed to get depth information. Processing stereo images has been one of the most intensively sought-after research topics in computer vision. Many factors affect the performance of this approach like computational efficiency, depth discontinuities, lighting changes, correspondence and correlation, electronic noise, etc. An algorithm is proposed which uses texture features obtained using Laws Energy Masks and multi-block approach to perform correspondence matching between stereo pair of images with high baseline. This is followed by forming disparity maps to get the relative depth of pixels in the image. An analysis is also made between this approach to the current state-of-the-art algorithms. A robust method to score and rank the stereo algorithms is also proposed. This approach provides a simple way for researchers to rank the algorithms according to their application needs. / Master of Science

This thesis compared macrotexture measurements obtained using the volumetric method (Sand Patch) and three laser-based devices: MGPS system, ICC laser profiler, and Circular Texture Meter (CTMeter). The study used data from three sources: two controlled experiments conducted at the Virginia Smart Road, field data collected on eight newly constructed hot-mix-asphalt (HMA) roadway surfaces, and data collected on airport surfaces at the Wallops flight facility, Virginia. The data collected at the Virginia Smart Road, a controlled-access two-lane road that includes various HMA and concrete surfaces, was used for the main analysis. The other two sets of data were used for verification and validation of the model developed. The analysis of the data collected at the Virginia Smart Road showed that the CTMeter mean profile depth (MPD) has the highest correlation with the volumetric (Sand Patch) mean texture depth (MTD). Furthermore, texture convexity had a significant effect on the correlation between the measurements obtained with different devices. Two sets of models for converting the laser-based texture measurements to an estimated MTD (ETD) were developed. One set of equations considered all the data collected at the Virginia Smart Road, and the other excluded the measurements on the Open-Graded Friction Course (OGFC). The developed models were tested using measurements collected at eight roadway sections throughout Virginia and the Wallops flight facility. The model, excluding the OGFC section, was successfully applied to other sites. / Master of Science