Learning a language can be hard. Learning a language that contains tones to convey meaning is even harder. This dissertation presents a novel methodology for creating a language practice using augmented reality that has never been used before. The design of a new app in AR and non-AR versions can evaluate the same practice methodology. This methodology was applied to new software and was examined in regard to the importance of this software. Although the study results are inconclusive, progress has been made in answering research questions on the effectiveness of AR versus non-AR and the reliability of peer assessment. This study is essential for developing future language applications using design and methodologies in AR and peer evaluation.

Interactive software applications which need to render large terrain meshes can suffer from slow frame rates if the geometry of the terrain is sufficiently dense. However, the viewing angle to many distant features of the terrain does not change rapidly with respect to time. If the movement of the viewing position is limited to continuous motion and restrained to a known speed, many terrain features may be rendered once in high detail and reused for several frames. This thesis proposes a method to increase the rendering speed of large complex terrains by splitting the terrain into contiguous chunks. If a given chunk is far enough away from the camera and its viewing angle will not change quickly, it is rendered into an image buffer. This buffer is then used to texture map a simplified version of the terrain mesh. The simplified and textured mesh is rendered in place of the original chunk of geometrically complex terrain. The simplified mesh is used to approximate parallax effects as the viewing angle changes in small increments. This technique is shown to as much as double the rendering speed of large terrain meshes without reducing the quality of the final image.

Simulations allow people to experience events as if they were happening in the real world in a way that is safer and less expensive than live training. Despite improvements in realism in simulated environments, one area that still presents a challenge is interpersonal interactions. The subtleties of what makes an interaction rich are difficult to define. We may never fully understand the complexity of human interchanges, however there is value in building on existing research into how individuals react to virtual characters to inform future investments. Virtual characters can either be automated through computational processes, referred to as agents, or controlled by a human, referred to as an avatar. Knowledge of interactions with virtual characters will facilitate the building of simulated characters that support training tasks in a manner that will appropriately engage learners. Ultimately, the goal is to understand what might cause people to engage or disengage with virtual characters. To answer that question, it is important to establish metrics that would indicate when people believe their interaction partner is real, or has agency. This study makes use of three types of measures: objective, behavioral and self-report. The objective measures were neural, galvanic skin response, and heart rate measures. The behavioral measure was gestures and facial expressions. Surveys provided an opportunity to gain self-report data. The objective of this research study was to determine what metrics could be used during social interactions to achieve the sense of agency in an interactive partner. The results provide valuable feedback on how users need to see and be seen by their interaction partner to ensure non-verbal cues provide context and additional meaning to the dialog. This study provides insight into areas of future research, offering a foundation of knowledge for further exploration and lessons learned. This can lead to more realistic experiences that open the door to human dimension training.

Any kind of graphics simulation can be thought of like a fancy flipbook. This notion is, of course, nothing new. For instance, in a game, the central computing unit (CPU) needs to process frame by frame, figuring out what is happening, and then finally issues draw calls to the graphics processing unit (GPU) to render the frame and display it onto the monitor. Traditionally, the CPU has to process a lot of things: from the creation of the window environment for the processed frames to be displayed, handling game logic, processing artificial intelligence (AI) for non-player characters (NPC), to the physics, and issuing draw calls; and all of these have to be done within roughly 0.0167 seconds to maintain real-time performance of 60 frames per second (fps). The main goal of this thesis is to move the physics pipeline of any kind of simulation to the GPU instead of the CPU. The main tool to make this possible would be the usage of OpenGL Compute Shaders. OpenGL is a high-performance graphics application programming interface (API), used as an abstraction layer for the CPU to communicate with the GPU. OpenGL was created by the Khronos Group primarily for graphics, or drawing frames only. In the later versions of OpenGL, the Khronos Group has introduced Compute Shader, which can be used for general-purpose computing on the GPU (GPGPU). This means the GPU can be used to process any arbitrary math computations, and not limited to only process the vertices and fragments of polygons. This thesis features Broad Phase and Narrow Phase collision detection stages, and a collision Resolution Phase with Sequential Impulses entirely on the GPU with real-time performance.

Learning in the classroom can occur as a combination of students' personal effort to study class material, the instructor's attempt to present class material, and the interaction that takes place between instructor and students. In a more traditional setting, instructors can lecture by writing notes on a chalkboard or a whiteboard. If instructors want to display prepared lecture slides, they can use the overhead projector and write additional notes on top of these overhead transparencies. With many technological advances, various researchers are advocating towards integration between technology and learning. With the advent of tablet PCs, researchers recognize the potential usefulness of its functions within the classroom. Not only can electronic materials be presented via the computer, tablet PCs allow instructors to handwrite notes on top of the slides, mimicking manual devices such as the overhead. Even though the use of tablet PCs can be advantageous to instructors and students, no research found so far has focused on the issue of how well tablet PC features address varying learning styles of students (e.g. visually oriented vs. text-based learning). According to Felder, "understanding learning style differences is thus an important step in designing balanced instruction that is effective for all students” [22]. Hence, this research explores the correlation between tablet-based presentation systems and learning styles by taking two approaches: performing a pilot study and distributing a survey. The results from these approaches are evaluated to yield statistically significant conclusions on how well tablet-based presentation systems encompass the different learning needs of student.

As the quest for more realistic computer graphics marches steadily on, the demand for rich and detailed imagery is greater than ever. However, the current "sweet spot" in terms of price, power consumption, and performance is in commodity hardware. If we desire to render scenes with tens or hundreds of millions of polygons as cheaply as possible, we need a way of doing so that maximizes the use of the commodity hardware we already have at our disposal. Techniques such as normal mapping and level of detail have attempted to address the problem by reducing the amount of geometry in a scene. This is problematic for applications that desire or demand access to the scene's full geometric complexity at render time. More recently, out-of-core techniques have provided methods for rendering large scenes when the working set is larger than the available system memory. We propose a distributed rendering architecture based on message-passing that is designed to partition scene geometry across a cluster of commodity machines in a spatially coherent way, allowing the entire scene to remain in-core and enabling the construction of hierarchical spatial acceleration structures in parallel. The results of our implementation show roughly an order of magnitude speedup in rendering time compared to the traditional approach, while keeping memory overhead for message queuing around 1%.

Neuronal activities in the brain encode every decision, desire, or intention. Multiple brain regions are involved in translating intention into action. Detecting and decoding intentions directly from the brain could allow impaired individuals to communicate and interact with their environment despite central nervous system dysfunction. Brain-computer interface (BCI) systems access neuronal activities and translate them into actions using a computer. BCIs are used in research studies to replace, restore, or replace neuromuscular functions. In addition, BCIs provide new insights into how the brain works, aiding in new treatments for neurological conditions. BCI studies commonly target the primary motor cortex, the region of the brain most closely associated with volitional muscle control, with the expectation that signals from its neurons will be best suited for control of external effectors. Consequently, other brain regions are underrepresented in BCI studies. This thesis focuses on two brain regions in primates with access to higher-order control over intention and movement: The prefrontal cortex and the basal ganglia system. These areas are vital for naturalistic movement and must be more widely explored for decoding intentions. We aim to find the movement information while the intentions have yet to transfer into planning. One study in macaque monkeys explored eye movement intention, learning, and memory-related circuitry in the lateral prefrontal cortex (LPFC). In an eight-target saccade task, we could decode the target to which the monkeys would saccade before the eye movement began. Moreover, we decoded the abstract rule information acquired by the monkeys to find the correct target from the neuronal activities recorded from LPFC. In addition, the memory-related activities in LPFC were linked to monkeys' behaviour as evidence of the presence of working- and long-term memory circuitry in the prefrontal cortex. In another study on Parkinson's disease (PD) patients, we explored the possibility of volitional control of brain activities, which can lead to a self-induced procedure to reduce the symptoms of PD. We recorded the local field potentials (LFP) of the subthalamic nucleus (STN) of nine PD patients performing a cognitive task during deep brain stimulation surgery. The patients could modulate their brain activities to change the colour of a central sphere to match the colour of a peripheral cue in a virtual reality task. They modulated the signal power in beta frequencies (13-30 Hz) and the rate of beta bursts (the fast episodes of changing amplitude in a short period in LFP's beta frequencies) based on the task conditions. Both beta power and beta bursts are associated with the pathological state in PD patients. A decodable volitional modulation of both presents the STN as a valuable region for BCI studies which could lead to self-regulation of PD symptoms. The findings of this thesis contribute to the advancement of therapeutic systems used for various brain disorders like PD and Amyotrophic lateral sclerosis (ALS), as well as patients with disabilities that can benefit from assistive communicative technologies. The study on the LPFC increased the decoding accuracy of saccade intentions compared to previous studies. Additionally, decoding associative rules is beyond the complexity of previous studies. We also showed the effects of previously learned associations on the learning rate of new rules and how this memory-retrieved information modulates neuronal activities. Moreover, the study on the STN showed the volitional control of beta power and beta burst rates by PD patients, which can be used as therapeutic methods to improve the severity of the symptoms of PD.

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This report surveys many of the interfacing techniques currently in use on emerging military training devices. The primary focus of this report is associated with the hardware aspects of computer interfacing. After a brief introduction into the various aspects of military training devices, this study presents various computer related interfacing techniques used on military training devices. Topics addressed in the study include custom designed interfaces, commercial packages, serial communications with an emphasis on RS-232, -422, -423, and -449 serial standards as well as local area networks. Then, a number of bus standards are presented and finally, interface products pertaining to computers previously used for most training device applications are summarized