A Customizable Camera-based Human Computer Interaction System Allowing People With Disabilities Autonomous Hands Free Navigation of Multiple Computing Task

Many people suffer from conditions that lead to deterioration of motor control and makes access to the computer using traditional input devices difficult. In particular, they may loose control of hand movement to the extent that the standard mouse cannot be used as a pointing device. Most current alternatives use markers or specialized hardware to track and translate a user's movement to pointer movement. These approaches may be perceived as intrusive, for example, wearable devices. Camera-based assistive systems that use visual tracking of features on the user's body often require cumbersome manual adjustment. This paper introduces an enhanced computer vision based strategy where features, for example on a user's face, viewed through an inexpensive USB camera, are tracked and translated to pointer movement. The main contributions of this paper are (1) enhancing a video based interface with a mechanism for mapping feature movement to pointer movement, which allows users to navigate to all areas of the screen even with very limited physical movement, and (2) providing a customizable, hierarchical navigation framework for human computer interaction (HCI). This framework provides effective use of the vision-based interface system for accessing multiple applications in an autonomous setting. Experiments with several users show the effectiveness of the mapping strategy and its usage within the application framework as a practical tool for desktop users with disabilities.

Applications of finite element computer modelling and thermal infrared remote sensing to the study of geothermal anomalies

Buried heat sources can be investigated by examining thermal infrared images and comparing these with the results of theoretical models which predict the thermal anomaly a given heat source may generate. Key factors influencing surface temperature include the geometry and temperature of the heat source, the surface meteorological environment, and the thermal conductivity and anisotropy of the rock. In general, a geothermal heat flux of greater than 2% of solar insolation is required to produce a detectable thermal anomaly in a thermal infrared image. A heat source of, for example, 2-300K greater than the average surface temperature must be a t depth shallower than 50m for the detection of the anomaly in a thermal infrared image, for typical terrestrial conditions. Atmospheric factors are of critical importance. While the mean atmospheric temperature has little significance, the convection is a dominant factor, and can act to swamp the thermal signature entirely. Given a steady state heat source that produces a detectable thermal anomaly, it is possible to loosely constrain the physical properties of the heat source and surrounding rock, using the surface thermal anomaly as a basis. The success of this technique is highly dependent on the degree to which the physical properties of the host rock are known. Important parameters include the surface thermal properties and thermal conductivity of the rock. Modelling of transient thermal situations was carried out, to assess the effect of time dependant thermal fluxes. One-dimensional finite element models can be readily and accurately applied to the investigation of diurnal heat flow, as with thermal inertia models. Diurnal thermal models of environments on Earth, the Moon and Mars were carried out using finite elements and found to be consistent with published measurements. The heat flow from an injection of hot lava into a near surface lava tube was considered. While this approach was useful for study, and long term monitoring in inhospitable areas, it was found to have little hazard warning utility, as the time taken for the thermal energy to propagate to the surface in dry rock (several months) in very long. The resolution of the thermal infrared imaging system is an important factor. Presently available satellite based systems such as Landsat (resolution of 120m) are inadequate for detailed study of geothermal anomalies. Airborne systems, such as TIMS (variable resolution of 3-6m) are much more useful for discriminating small buried heat sources. Planned improvements in the resolution of satellite based systems will broaden the potential for application of the techniques developed in this thesis. It is important to note, however, that adequate spatial resolution is a necessary but not sufficient condition for successful application of these techniques.

The development of a computer model to optimize the performance of a 50kWp photovoltaic system

A computer model has been developed to optimize the performance of a 50kWp photovoltaic system which supplies electrical energy to a dairy farm at Fota Island in Cork Harbour. Optimization of the system involves maximising the efficiency and increasing the performance and reliability of each hardware unit. The model accepts horizontal insolation, ambient temperature, wind speed, wind direction and load demand as inputs. An optimization program uses the computer model to simulate the optimum operating conditions. From this analysis, criteria are established which are used to improve the photovoltaic system operation. This thesis describes the model concepts, the model implementation and the model verification procedures used during development. It also describes the techniques which are used during system optimization. The software, which is written in FORTRAN, is structured in modular units to provide logical and efficient programming. These modular units may also be used in the modelling and optimization of other photovoltaic systems.

Assessing the impulse control of violent offenders using computer-based cognitive performance tasks

The topic of this thesis is impulsivity. The meaning and measurement of impulse control is explored, with a particular focus on forensic settings. Impulsivity is central to many areas of psychology; it is one of the most common diagnostic criteria of mental disorders and is fundamental to the understanding of forensic personalities. Despite this widespread importance there is little agreement as to the definition or structure of impulsivity, and its measurement is fraught with difficulty owing to a reliance on self-report methods. This research aims to address this problem by investigating the viability of using simple computerised cognitive performance tasks as complementary components of a multi-method assessment strategy for impulse control. Ultimately, the usefulness of this measurement strategy for a forensic sample is assessed. Impulsivity is found to be a multifaceted construct comprised of a constellation of distinct sub-dimensions. Computerised cognitive performance tasks are valid and reliable measures that can assess impulsivity at a neuronal level. Self-report and performance task methods assess distinct components of impulse control and, for the optimal assessment of impulse control, a multi-method battery of self-report and performance task measures is advocated. Such a battery is shown to have demonstrated utility in a forensic sample, and recommendations for forensic assessment in the Irish context are discussed.

The application of computer modelling to develop a methodology for ‘existing building’ upgrades to move towards carbon-neutral buildings

The retrofitting of existing buildings for decreased energy usage, through increased energy efficiency and for minimum carbon dioxide emissions throughout their remaining lifetime is a major area of research. This research area requires development to provide building professionals with more efficient building retrofit solution determination tools. The overarching objective of this research is to develop a tool for this purpose through the implementation of a prescribed methodology. This has been achieved in three distinct steps. Firstly, the concept of using the degree-days modelling method as an adequate means of basing retrofit decision upon was analysed and the results illustrated that the concept had merit. Secondly, the concept of combining the degree-days modelling method and the Genetic Algorithms optimisation method is investigated as a method of determining optimal thermal energy retrofit solutions. Thirdly, the combination of the degree-days modelling method and the Genetic Algorithms optimisation method were packaged into a building retrofit decision-support tool and named BRaSS (Building Retrofit Support Software). The results demonstrate clearly that, fundamental building information, simplified occupancy profiles and weather data used in a static simulation modelling method is a sufficient and adequate means to base retrofitting decisions upon. The results also show that basing retrofit decisions upon energy analysis results are the best means to guide a retrofit project and also to achieve results which are optimum for a particular building. The results also indicate that the building retrofit decision-support tool, BRaSS, is an effective method to determine optimum thermal energy retrofit solutions.

Biased group decision-making and the effect of computer-mediated communication: separating the effects of anonymity, voting and blind picking

The influence of communication technology on group decision-making has been examined in many studies. But the findings are inconsistent. Some studies showed a positive effect on decision quality, other studies have shown that communication technology makes the decision even worse. One possible explanation for these different findings could be the use of different Group Decision Support Systems (GDSS) in these studies, with some GDSS better fitting to the given task than others and with different sets of functions. This paper outlines an approach with an information system solely designed to examine the effect of (1) anonymity, (2) voting and (3) blind picking on decision quality, discussion quality and perceived quality of information.

The Design and Implementation of an Educational Computer Game and Its Study as a Motivational Tool for Middle School ESOL Students

Gemstone Team ILL (Interactive Language Learning)

Of Mice and Men: An Ergonomic and Market Assessment of Current Computer Mice

Gemstone Team MICE (Modifying and Improving Computer Ergonomics)

Computer vision tools for low-cost and noninvasive measurement of autism-related behaviors in infants.

The early detection of developmental disorders is key to child outcome, allowing interventions to be initiated which promote development and improve prognosis. Research on autism spectrum disorder (ASD) suggests that behavioral signs can be observed late in the first year of life. Many of these studies involve extensive frame-by-frame video observation and analysis of a child's natural behavior. Although nonintrusive, these methods are extremely time-intensive and require a high level of observer training; thus, they are burdensome for clinical and large population research purposes. This work is a first milestone in a long-term project on non-invasive early observation of children in order to aid in risk detection and research of neurodevelopmental disorders. We focus on providing low-cost computer vision tools to measure and identify ASD behavioral signs based on components of the Autism Observation Scale for Infants (AOSI). In particular, we develop algorithms to measure responses to general ASD risk assessment tasks and activities outlined by the AOSI which assess visual attention by tracking facial features. We show results, including comparisons with expert and nonexpert clinicians, which demonstrate that the proposed computer vision tools can capture critical behavioral observations and potentially augment the clinician's behavioral observations obtained from real in-clinic assessments.

Computer vision tools for the non-invasive assessment of autism-related behavioral markers

The early detection of developmental disorders is key to child outcome, allowing interventions to be initiated that promote development and improve prognosis. Research on autism spectrum disorder (ASD) suggests behavioral markers can be observed late in the first year of life. Many of these studies involved extensive frame-by-frame video observation and analysis of a child's natural behavior. Although non-intrusive, these methods are extremely time-intensive and require a high level of observer training; thus, they are impractical for clinical and large population research purposes. Diagnostic measures for ASD are available for infants but are only accurate when used by specialists experienced in early diagnosis. This work is a first milestone in a long-term multidisciplinary project that aims at helping clinicians and general practitioners accomplish this early detection/measurement task automatically. We focus on providing computer vision tools to measure and identify ASD behavioral markers based on components of the Autism Observation Scale for Infants (AOSI). In particular, we develop algorithms to measure three critical AOSI activities that assess visual attention. We augment these AOSI activities with an additional test that analyzes asymmetrical patterns in unsupported gait. The first set of algorithms involves assessing head motion by tracking facial features, while the gait analysis relies on joint foreground segmentation and 2D body pose estimation in video. We show results that provide insightful knowledge to augment the clinician's behavioral observations obtained from real in-clinic assessments.

Facial and expression recognition for the blind using computer vision

Gemstone Team FACE

A noisy linear map underlies oscillations in cell size and gene expression in bacteria.

During bacterial growth, a cell approximately doubles in size before division, after which it splits into two daughter cells. This process is subjected to the inherent perturbations of cellular noise and thus requires regulation for cell-size homeostasis. The mechanisms underlying the control and dynamics of cell size remain poorly understood owing to the difficulty in sizing individual bacteria over long periods of time in a high-throughput manner. Here we measure and analyse long-term, single-cell growth and division across different Escherichia coli strains and growth conditions. We show that a subset of cells in a population exhibit transient oscillations in cell size with periods that stretch across several (more than ten) generations. Our analysis reveals that a simple law governing cell-size control-a noisy linear map-explains the origins of these cell-size oscillations across all strains. This noisy linear map implements a negative feedback on cell-size control: a cell with a larger initial size tends to divide earlier, whereas one with a smaller initial size tends to divide later. Combining simulations of cell growth and division with experimental data, we demonstrate that this noisy linear map generates transient oscillations, not just in cell size, but also in constitutive gene expression. Our work provides new insights into the dynamics of bacterial cell-size regulation with implications for the physiological processes involved.

Spectrotemporal CT data acquisition and reconstruction at low dose.

PURPOSE: X-ray computed tomography (CT) is widely used, both clinically and preclinically, for fast, high-resolution anatomic imaging; however, compelling opportunities exist to expand its use in functional imaging applications. For instance, spectral information combined with nanoparticle contrast agents enables quantification of tissue perfusion levels, while temporal information details cardiac and respiratory dynamics. The authors propose and demonstrate a projection acquisition and reconstruction strategy for 5D CT (3D+dual energy+time) which recovers spectral and temporal information without substantially increasing radiation dose or sampling time relative to anatomic imaging protocols. METHODS: The authors approach the 5D reconstruction problem within the framework of low-rank and sparse matrix decomposition. Unlike previous work on rank-sparsity constrained CT reconstruction, the authors establish an explicit rank-sparse signal model to describe the spectral and temporal dimensions. The spectral dimension is represented as a well-sampled time and energy averaged image plus regularly undersampled principal components describing the spectral contrast. The temporal dimension is represented as the same time and energy averaged reconstruction plus contiguous, spatially sparse, and irregularly sampled temporal contrast images. Using a nonlinear, image domain filtration approach, the authors refer to as rank-sparse kernel regression, the authors transfer image structure from the well-sampled time and energy averaged reconstruction to the spectral and temporal contrast images. This regularization strategy strictly constrains the reconstruction problem while approximately separating the temporal and spectral dimensions. Separability results in a highly compressed representation for the 5D data in which projections are shared between the temporal and spectral reconstruction subproblems, enabling substantial undersampling. The authors solved the 5D reconstruction problem using the split Bregman method and GPU-based implementations of backprojection, reprojection, and kernel regression. Using a preclinical mouse model, the authors apply the proposed algorithm to study myocardial injury following radiation treatment of breast cancer. RESULTS: Quantitative 5D simulations are performed using the MOBY mouse phantom. Twenty data sets (ten cardiac phases, two energies) are reconstructed with 88 μm, isotropic voxels from 450 total projections acquired over a single 360° rotation. In vivo 5D myocardial injury data sets acquired in two mice injected with gold and iodine nanoparticles are also reconstructed with 20 data sets per mouse using the same acquisition parameters (dose: ∼60 mGy). For both the simulations and the in vivo data, the reconstruction quality is sufficient to perform material decomposition into gold and iodine maps to localize the extent of myocardial injury (gold accumulation) and to measure cardiac functional metrics (vascular iodine). Their 5D CT imaging protocol represents a 95% reduction in radiation dose per cardiac phase and energy and a 40-fold decrease in projection sampling time relative to their standard imaging protocol. CONCLUSIONS: Their 5D CT data acquisition and reconstruction protocol efficiently exploits the rank-sparse nature of spectral and temporal CT data to provide high-fidelity reconstruction results without increased radiation dose or sampling time.

Participant, rater, and computer measures of coherence in posttraumatic stress disorder.

We examined the coherence of trauma memories in a trauma-exposed community sample of 30 adults with and 30 without posttraumatic stress disorder. The groups had similar categories of traumas and were matched on multiple factors that could affect the coherence of memories. We compared the transcribed oral trauma memories of participants with their most important and most positive memories. A comprehensive set of 28 measures of coherence including 3 ratings by the participants, 7 ratings by outside raters, and 18 computer-scored measures, provided a variety of approaches to defining and measuring coherence. A multivariate analysis of variance indicated differences in coherence among the trauma, important, and positive memories, but not between the diagnostic groups or their interaction with these memory types. Most differences were small in magnitude; in some cases, the trauma memories were more, rather than less, coherent than the control memories. Where differences existed, the results agreed with the existing literature, suggesting that factors other than the incoherence of trauma memories are most likely to be central to the maintenance of posttraumatic stress disorder and thus its treatment.

Adapting Behavioral Parent Training as an Interactive Computer Game

Behavioral Parent Training (BPT) is a well-established therapy that reduces child externalized behaviors and parent stress. Although BPT was originally developed for parents of children with defiant behaviors, the program’s key concepts are relevant to parenting all children. Since parents might not fully utilize BPT due to cost and program location, we created an online game as a low-cost, easily accessible alternative or complement to BPT. We tested the game with nineteen undergraduate students at the University of Maryland. The experimental group completed pretest survey on core BPT knowledge, played the game, and completed a BPT posttest, while the control group completed a pretest and posttest survey over a three week period. Participants in the experimental group also completed a survey to indicate their satisfaction with the overall program. The experimental group demonstrated significantly higher levels of BPT knowledge than the control group and high levels of satisfaction. This suggests that an interactive, online BPT platform is an engaging and accessible way for parents to learn key concepts.