3D Navigation with Six Degrees-of-Freedom using a Multi-Touch Display

With the introduction of new input devices, such as multi-touch surface displays, the Nintendo WiiMote, the Microsoft Kinect, and the Leap Motion sensor, among others, the field of Human-Computer Interaction (HCI) finds itself at an important crossroads that requires solving new challenges. Given the amount of three-dimensional (3D) data available today, 3D navigation plays an important role in 3D User Interfaces (3DUI). This dissertation deals with multi-touch, 3D navigation, and how users can explore 3D virtual worlds using a multi-touch, non-stereo, desktop display. The contributions of this dissertation include a feature-extraction algorithm for multi-touch displays (FETOUCH), a multi-touch and gyroscope interaction technique (GyroTouch), a theoretical model for multi-touch interaction using high-level Petri Nets (PeNTa), an algorithm to resolve ambiguities in the multi-touch gesture classification process (Yield), a proposed technique for navigational experiments (FaNS), a proposed gesture (Hold-and-Roll), and an experiment prototype for 3D navigation (3DNav). The verification experiment for 3DNav was conducted with 30 human-subjects of both genders. The experiment used the 3DNav prototype to present a pseudo-universe, where each user was required to find five objects using the multi-touch display and five objects using a game controller (GamePad). For the multi-touch display, 3DNav used a commercial library called GestureWorks in conjunction with Yield to resolve the ambiguity posed by the multiplicity of gestures reported by the initial classification. The experiment compared both devices. The task completion time with multi-touch was slightly shorter, but the difference was not statistically significant. The design of experiment also included an equation that determined the level of video game console expertise of the subjects, which was used to break down users into two groups: casual users and experienced users. The study found that experienced gamers performed significantly faster with the GamePad than casual users. When looking at the groups separately, casual gamers performed significantly better using the multi-touch display, compared to the GamePad. Additional results are found in this dissertation.

Rare earth element concentrations and geochemistry of carbonate minerals from the Logatchev Hydrothermal Field and the Gakkel Ridge

The ultramafic-hosted Logatchev Hydrothermal Field (LHF) at 15°N on the Mid-Atlantic Ridge and the Arctic Gakkel Ridge (GR) feature carbonate precipitates (aragonite, calcite, and dolomite) in voids and fractures within different types of host rocks. We present chemical and Sr isotopic compositions of these different carbonates to examine the conditions that led to their formation. Our data reveal that different processes have led to the precipitation of carbonates in the various settings. Seawater-like 87Sr/86Sr ratios for aragonite in serpentinites (0.70909 to 0.70917) from the LHF are similar to those of aragonite from the GR (0.70912 to 0.70917) and indicate aragonite precipitation from seawater at ambient conditions at both sites. Aragonite veins in sulfide breccias from LHF also have seawater-like Sr isotope compositions (0.70909 to 0.70915), however, their rare earth element (REE) patterns show a clear positive europium (Eu) anomaly indicative of a small (< 1%) hydrothermal contribution. In contrast to aragonite, dolomite from the LHF has precipitated at much higher temperatures (~100 °C), and yet its 87Sr/86Sr ratios (0.70896 to 0.70907) are only slightly lower than those of aragonite. Even higher temperatures are calculated for the precipitation of deformed calcite veins in serpentine-talc fault schists form north of the LHF. These calcites show unradiogenic 87Sr/86Sr ratios (0.70460 to 0.70499) indicative of precipitation from evolved hydrothermal fluids. A simple mixing model based on Sr mass balance and enthalpy conservation indicates strongly variable conditions of fluid mixing and heat transfers involved in carbonate formation. Dolomite precipitated from a mixture of 97% seawater and 3% hydrothermal fluid that should have had a temperature of approximately 14 °C assuming that no heat was transferred. The much higher apparent precipitation temperatures based on oxygen isotopes (~ 100 °C) may be indicative of conductive heating, probably of seawater prior to mixing. The hydrothermal calcite in the fault schist has precipitated from a mixture of 67% hydrothermal fluid and 33% seawater, which should have had an isenthalpic mixing temperature of ~ 250 °C. The significantly lower temperatures calculated from oxygen isotopes are likely due to conductive cooling of hydrothermal fluid discharging along faults. Rare earth element patterns corroborate the results of the mixing model, since the hydrothermal calcite, which formed from waters with the greatest hydrothermal contribution, has REE patterns that closely resemble those of vent fluids from the LHF. Our results demonstrate, for the first time, that (1) precipitation from pure seawater, (2) conductive heating of seawater, and (3) conductive cooling of hydrothermal fluids in the sub-seafloor all can lead to carbonate precipitation within a single ultramafic-hosted hydrothermal system.

3D considerations for motion perception and visuomotor transformations

Moving through a stable, three-dimensional world is a hallmark of our motor and perceptual experience. This stability is constantly being challenged by movements of the eyes and head, inducing retinal blur and retino-spatial misalignments for which the brain must compensate. To do so, the brain must account for eye and head kinematics to transform two-dimensional retinal input into the reference frame necessary for movement or perception. The four studies in this thesis used both computational and psychophysical approaches to investigate several aspects of this reference frame transformation. In the first study, we examined the neural mechanism underlying the visuomotor transformation for smooth pursuit using a feedforward neural network model. After training, the model performed the general, three-dimensional transformation using gain modulation. This gave mechanistic significance to gain modulation observed in cortical pursuit areas while also providing several testable hypotheses for future electrophysiological work. In the second study, we asked how anticipatory pursuit, which is driven by memorized signals, accounts for eye and head geometry using a novel head-roll updating paradigm. We showed that the velocity memory driving anticipatory smooth pursuit relies on retinal signals, but is updated for the current head orientation. In the third study, we asked how forcing retinal motion to undergo a reference frame transformation influences perceptual decision making. We found that simply rolling one's head impairs perceptual decision making in a way captured by stochastic reference frame transformations. In the final study, we asked how torsional shifts of the retinal projection occurring with almost every eye movement influence orientation perception across saccades. We found a pre-saccadic, predictive remapping consistent with maintaining a purely retinal (but spatially inaccurate) orientation perception throughout the movement. Together these studies suggest that, despite their spatial inaccuracy, retinal signals play a surprisingly large role in our seamless visual experience. This work therefore represents a significant advance in our understanding of how the brain performs one of its most fundamental functions.

Fast 2D/3D object representation with growing neural gas

This work presents the design of a real-time system to model visual objects with the use of self-organising networks. The architecture of the system addresses multiple computer vision tasks such as image segmentation, optimal parameter estimation and object representation. We first develop a framework for building non-rigid shapes using the growth mechanism of the self-organising maps, and then we define an optimal number of nodes without overfitting or underfitting the network based on the knowledge obtained from information-theoretic considerations. We present experimental results for hands and faces, and we quantitatively evaluate the matching capabilities of the proposed method with the topographic product. The proposed method is easily extensible to 3D objects, as it offers similar features for efficient mesh reconstruction.

Co-production of bio-oil and propylene through the hydrothermal liquefaction of polyhydroxybutyrate producing cyanobacteria

A polyhydroxybutyrate (PHB) producing cyanobacteria was converted through hydrothermal liquefaction (HTL) into propylene and a bio-oil suitable for advanced biofuel production. HTL of model compounds demonstrated that in contrast to proteins and carbohydrates, no synergistic effects were detected when converting PHB in the presence of algae. Subsequently, Synechocystis cf. salina, which had accumulated 7.5wt% PHB was converted via HTL (15% dry weight loading, 340°C). The reaction gave an overall propylene yield of 2.6%, higher than that obtained from the model compounds, in addition to a bio-oil with a low nitrogen content of 4.6%. No propylene was recovered from the alternative non-PHB producing cyanobacterial strains screened, suggesting that PHB is the source of propylene. PHB producing microorganisms could therefore be used as a feedstock for a biorefinery to produce polypropylene and advanced biofuels, with the level of propylene being proportional to the accumulated amount of PHB.

Co-production of bio-oil and propylene through the hydrothermal liquefaction of polyhydroxybutyrate producing cyanobacteria

A polyhydroxybutyrate (PHB) producing cyanobacteria was converted through hydrothermal liquefaction (HTL) into propylene and a bio-oil suitable for advanced biofuel production. HTL of model compounds demonstrated that in contrast to proteins and carbohydrates, no synergistic effects were detected when converting PHB in the presence of algae. Subsequently, Synechocystis cf. salina, which had accumulated 7.5wt% PHB was converted via HTL (15% dry weight loading, 340°C). The reaction gave an overall propylene yield of 2.6%, higher than that obtained from the model compounds, in addition to a bio-oil with a low nitrogen content of 4.6%. No propylene was recovered from the alternative non-PHB producing cyanobacterial strains screened, suggesting that PHB is the source of propylene. PHB producing microorganisms could therefore be used as a feedstock for a biorefinery to produce polypropylene and advanced biofuels, with the level of propylene being proportional to the accumulated amount of PHB.

The dynamics of neutrino-driven supernova explosions after shock revival in 2D and 3D

We study the growth of the explosion energy after shock revival in neutrino-driven explosions in two and three dimensions (2D/3D) using multi-group neutrino hydrodynamics simulations of an 11.2 M⊙ star. The 3D model shows a faster and steadier growth of the explosion energy and already shows signs of subsiding accretion after one second. By contrast, the growth of the explosion energy in 2D is unsteady, and accretion lasts for several seconds as confirmed by additional long-time simulations of stars of similar masses. Appreciable explosion energies can still be reached, albeit at the expense of rather high neutron star masses. In 2D, the binding energy at the gain radius is larger because the strong excitation of downward-propagating g modes removes energy from the freshly accreted material in the downflows. Consequently, the mass outflow rate is considerably lower in 2D than in 3D. This is only partially compensated by additional heating by outward-propagating acoustic waves in 2D. Moreover, the mass outflow rate in 2D is reduced because much of the neutrino energy deposition occurs in downflows or bubbles confined by secondary shocks without driving outflows. Episodic constriction of outflows and vertical mixing of colder shocked material and hot, neutrino-heated ejecta due to Rayleigh–Taylor instability further hamper the growth of the explosion energy in 2D. Further simulations will be necessary to determine whether these effects are generic over a wider range of supernova progenitors.

Parametric CAD model based shape optimization using adjoint functions

Adjoint methods have proven to be an efficient way of calculating the gradient of an objective function with respect to a shape parameter for optimisation, with a computational cost nearly independent of the number of the design variables [1]. The approach in this paper links the adjoint surface sensitivities (gradient of objective function with respect to the surface movement) with the parametric design velocities (movement of the surface due to a CAD parameter perturbation) in order to compute the gradient of the objective function with respect to CAD variables.
For a successful implementation of shape optimization strategies in practical industrial cases, the choice of design variables or parameterisation scheme used for the model to be optimized plays a vital role. Where the goal is to base the optimization on a CAD model the choices are to use a NURBS geometry generated from CAD modelling software, where the position of the NURBS control points are the optimisation variables [2] or to use the feature based CAD model with all of the construction history to preserve the design intent [3]. The main advantage of using the feature based model is that the optimized model produced can be directly used for the downstream applications including manufacturing and process planning.
This paper presents an approach for optimization based on the feature based CAD model, which uses CAD parameters defining the features in the model geometry as the design variables. In order to capture the CAD surface movement with respect to the change in design variable, the “Parametric Design Velocity” is calculated, which is defined as the movement of the CAD model boundary in the normal direction due to a change in the parameter value.
The approach presented here for calculating the design velocities represents an advancement in terms of capability and robustness of that described by Robinson et al. [3]. The process can be easily integrated to most industrial optimisation workflows and is immune to the topology and labelling issues highlighted by other CAD based optimisation processes. It considers every continuous (“real value”) parameter type as an optimisation variable, and it can be adapted to work with any CAD modelling software, as long as it has an API which provides access to the values of the parameters which control the model shape and allows the model geometry to be exported. To calculate the movement of the boundary the methodology employs finite differences on the shape of the 3D CAD models before and after the parameter perturbation. The implementation procedure includes calculating the geometrical movement along a normal direction between two discrete representations of the original and perturbed geometry respectively. Parametric design velocities can then be directly linked with adjoint surface sensitivities to extract the gradients to use in a gradient-based optimization algorithm.
The optimisation of a flow optimisation problem is presented, in which the power dissipation of the flow in an automotive air duct is to be reduced by changing the parameters of the CAD geometry created in CATIA V5. The flow sensitivities are computed with the continuous adjoint method for a laminar and turbulent flow [4] and are combined with the parametric design velocities to compute the cost function gradients. A line-search algorithm is then used to update the design variables and proceed further with optimisation process.

A Finite Element to Perform 3D Shakedown Analysis for Limited Kinematic Hardening Materials

The use of the Design by Analysis (DBA) route is a modern trend in pressure vessel and piping international codes in mechanical engineering. However, to apply the DBA to structures under variable mechanical and thermal loads, it is necessary to assure that the plastic collapse modes, alternate plasticity and incremental collapse (with instantaneous plastic collapse as a particular case), be precluded. The tool available to achieve this target is the shakedown theory. Unfortunately, the practical numerical applications of the shakedown theory result in very large nonlinear optimization problems with nonlinear constraints. Precise, robust and efficient algorithms and finite elements to solve this problem in finite dimension has been a more recent achievements. However, to solve real problems in an industrial level, it is necessary also to consider more realistic material properties as well as to accomplish 3D analysis. Limited kinematic hardening, is a typical property of the usual steels and it should be considered in realistic applications. In this paper, a new finite element with internal thermodynamical variables to model kinematic hardening materials is developed and tested. This element is a mixed ten nodes tetrahedron and through an appropriate change of variables is possible to embed it in a shakedown analysis software developed by Zouain and co-workers for elastic ideally-plastic materials, and then use it to perform 3D shakedown analysis in cases with limited kinematic hardening materials

An algoritmh for the estimation of 3D surfaces using competitive learning

This paper addresses the estimation of object boundaries from a set of 3D points. An extension of the constrained clustering algorithm developed by Abrantes and Marques in the context of edge linking is presented. The object surface is approximated using rectangular meshes and simplex nets. Centroid-based forces are used for attracting the model nodes towards the data, using competitive learning methods. It is shown that competitive learning improves the model performance in the presence of concavities and allows to discriminate close surfaces. The proposed model is evaluated using synthetic data and medical images (MRI and ultrasound images).

Relating Innovative 2D Ideas into 3D Garments in Terms of Structure, Using ‘Sculptural Form Giving’ as an Intermediate Step in Creation.

This research focuses on finding a fashion design methodology to reliably translate innovative two-dimensional ideas on paper, via a structural design sculpture, into an intermediate model. The author, both as a fashion designer and a researcher, has witnessed the issues which arise, regarding the loss of some of the initial ideas and distortion during the two-dimensional creative sketch to three-dimensional garment transfer process. Therefore, this research is concerned with fashion designers engaged in transferring a two-dimensional sketch through the method ‘sculptural form giving’. This research method applies the ideal model of conceptual sculpture, in the fashion design process, akin to those used in the disciplines of architecture. These parallel design disciplines share similar processes for realizing design ideas. Moreover, this research investigates and formalizes the processes that utilize the measurable space between the garment and the body, to help transfer garment variation and scale. In summation, this research proposition focuses on helping fashion designers to produce a creative method that helps the designer transfer their imaginative concept through intermediate modeling.

3D Ionospheric Effects on HF Propagation and Heating

The thesis uses a three-dimensional, first-principles model of the ionosphere in combination with High Frequency (HF) raytracing model to address key topics related to the physics of HF propagation and artificial ionospheric heating. In particular: 1. Explores the effect of the ubiquitous electron density gradients caused by Medium Scale Traveling Ionospheric Disturbances (MSTIDs) on high-angle of incidence HF radio wave propagation. Previous studies neglected the all-important presence of horizontal gradients in both the cross- and down-range directions, which refract the HF waves, significantly changing their path through the ionosphere. The physics-based ionosphere model SAMI3/ESF is used to generate a self-consistently evolving MSTID that allows for the examination of the spatio-temporal progression of the HF radio waves in the ionosphere. 2. Tests the potential and determines engineering requirements for ground- based high power HF heaters to trigger and control the evolution of Equatorial Spread F (ESF). Interference from ESF on radio wave propagation through the ionosphere remains a critical issue on HF systems reliability. Artificial HF heating has been shown to create plasma density cavities in the ionosphere similar to those that may trigger ESF bubbles. The work explores whether HF heating may trigger or control ESF bubbles. 3. Uses the combined ionosphere and HF raytracing models to create the first self-consistent HF Heating model. This model is utilized to simulate results from an Arecibo experiment and to provide understanding of the physical mechanism behind observed phenomena. The insights gained provide engineering guidance for new artificial heaters that are being built for use in low to middle latitude regions. In accomplishing the above topics: (i) I generated a model MSTID using the SAMI3/ESF code, and used a raytrace model to examine the effects of the MSTID gradients on radio wave propagation observables; (ii) I implemented a three- dimensional HF heating model in SAMI3/ESF and used the model to determine whether HF heating could artificially generate an ESF bubble; (iii) I created the first self-consistent model for artificial HF heating using the SAMI3/ESF ionosphere model and the MoJo raytrace model and ran a series of simulations that successfully modeled the results of early artificial heating experiments at Arecibo.

Human Ezrin: Prediction of the 3D structure and interactions with mTOR

The protein Ezrin, is a member of the ERM family (Ezrin, Radixin and Moesin) that links the F-actin to the plasma membrane. The protein is made of three domains namely the FERM domain, a central α-helical domain and the CERMAD domain. The residues in Ezrin such as Ser66, Tyr145, Tyr353 and Tyr477 regulate the function of the protein through phosphorylation. The protein is found in two distinct conformations of active and dormant (inactive) state. The initial step during the conformation change is the breakage of intramolecular interaction in dormant Ezrin by phosphorylation of residue Thr567. The dormant structure of human Ezrin was predicted computationally since only partial active form structure was available. The validation analysis showed that 99.7% residues were positioned in favored, allowed and generously allowed regions of the Ramachandran plot. The Z-score of Ezrin was −7.36, G-factor was 0.1, and the QMEAN score of the model was 0.61 indicating a good model for human Ezrin. The comparison of the conformations of the activated and dormant Ezrin showed a major shift in the F2 lobe (residues 142-149 and 161-177) while changes in the conformation induced mobility shifts in lobe F3 (residues 261 to 267). The 3D positions of the phosphorylation sites Tyr145, Tyr353, Tyr477, Tyr482 and Thr567 were also located. Using targeted molecular dynamic simulation, the molecular movements during conformational change from active to dormant were visualized. The dormant Ezrin auto-inhibits itself by a head-to-tail interaction of the N-terminal and C-terminal residues. The trajectory shows the breakage of the interactions and mobility of the CERMAD domain away from the FERM domain. Protein docking and clustering analysis were used to predict the residues involved in the interaction between dormant Ezrin and mTOR. Residues Tyr477 and Tyr482 were found to be involved in interaction with mTOR.

3D modelling of mango fruit skin blush in the tree canopy

The fruit of certain mango cultivars (e.g., 'Honey Gold') can develop blush on their skin. Skin blush due to red pigmentation is from the accumulation of anthocyanins. Anthocyanin biosynthesis is related to environmental determinants, including light received by the fruit. It has been observed that mango skin blush varies with position in the tree canopy. However, little investigation into this spatial relationship has been conducted. The objective of this preliminary study was to describe a 'Honey Gold' mango tree by capturing its three-dimensional (3D) architecture. A light path tracing model QuasiMC was then used to predict light received by fruit. The use of this 3D model was to better understand the relationship between mango fruit skin blush and fruit position in the canopy. The digitised mango tree mimicked the real tree at a high level of detail. Observations on mango skin blush distribution supported the proposition that sunlight exposure is an absolute requirement for anthocyanin development. No blush development occurred on shaded skin. It was affirmed that 3D mapping could allow for virtual experiments. For example, for virtual canopy thinning (e.g., 'window pruning') to admit more sunlight with a view to improve fruit blush. Improvements to 3D modelling of mango skin blush could focus on increasing accuracy, e.g., measurement of leaf light reflectance and transmission and the inclusion of the effect shading by branches.

Rapid hydrothermal cooling above the axial melt lens at fast-spreading mid-ocean ridge

Axial melt lenses sandwiched between the lower oceanic crust and the sheeted dike sequences at fast-spreading mid-ocean ridges are assumed to be the major magma source of oceanic crust accretion. According to the widely discussed "gabbro glacier'' model, the formation of the lower oceanic crust requires efficient cooling of the axial melt lens, leading to partial crystallization and crystal-melt mush subsiding down to lower crust. These processes are believed to be controlled by periodical magma replenishment and hydrothermal circulation above the melt lens. Here we quantify the cooling rate above melt lens using chemical zoning of plagioclase from hornfelsic recrystallized sheeted dikes drilled from the East Pacific at the Integrated Ocean Drilling Program Hole 1256D. Weestimate the cooling rate using a forward modelling approach based on CaAl-NaSi interdiffusion in plagioclase. The results show that cooling from the peak thermal overprint at 1000-10506 degrees C to 6006 degrees C are yielded within about 10-30 years as a result of hydrothermal circulation above melt lens during magma starvation. The estimated rapid hydrothermal cooling explains how the effective heat extraction from melt lens is achieved at fast-spreading mid-ocean ridges.