A tool for generating three dimensional animation on computers

Ankara : The Department of Graphic Design and the Institute of Fine Arts of Bilkent Univ. , 1991.Thesis (Master's) -- Bilkent University, 1991.Includes bibliographical references leaves 31-32.In this work, a three dimensional computer animation system has been designed to be employed in schools, for the training of art students on basic three dimensional animation techniques. Puppet Theater, as we have called the system, utilizes the flexibility and effectiveness of the low-end hardware, namely IBM PC™ computers supported with Targa 16™ graphics board and gives special emphasis to user friendliness. It Is basically a software to design three dimensional objects and choreograph the object data in the computer's memory, before rendering the resulting scenery with shading methods. The system is the result of reflecting the recent advances in the field of computer graphics and pushing the potentials of the existing platform. Software is Implemented in C language, thus the code is transportable. A custom designed object oriented windowing system called WODNTW is used as the user Interface. This open windowing system supports pull-down menus, interactive buttons, scalable windows and other popular user interface elements.Türün, Cemil ŞinasiM.S

Sensor-based automated path guidance of a robot tool

The objective of the research is to develop a robot capability for a simultaneous measurement of the orientation (surface normal) and position of a 3-dimensional unknown object for a precise tool path guidance and control. The proposed system can guide the robot manipulator while maintaining specific orientation between the robot end-effector and the workpiece and also generate a measured geometric CAD database; The first phase involves the computer graphics simulation of an automated guidance and control of a robot tool using the proposed scheme. In the simulation, an object of known geometry is used for camera image data generation and subsequently determining the position and orientation of surface points based only on the simulated camera image information. Based on this surface geometry measurement technique, robot tool guidance and path planning algorithm is developed; The second phase involves the laboratory experiment. To demonstrate the validity of the proposed measurement method, the result of CCD image processing (grey to binary image conversion, thinning of binary image, detection of cross point, etc) and the calibration of the cameras/lighting source are performed. (Abstract shortened by UMI.)

AutoGraff: towards a computational understanding of graffiti writing and related art forms.

The aim of this thesis is to develop a system that generates letters and pictures with a style that is immediately recognizable as graffiti art or calligraphy. The proposed system can be used similarly to, and in tight integration with, conventional computer-aided geometric design tools and can be used to generate synthetic graffiti content for urban environments in games and in movies, and to guide robotic or fabrication systems that can materialise the output of the system with physical drawing media. The thesis is divided into two main parts. The first part describes a set of stroke primitives, building blocks that can be combined to generate different designs that resemble graffiti or calligraphy. These primitives mimic the process typically used to design graffiti letters and exploit well known principles of motor control to model the way in which an artist moves when incrementally tracing stylised letter forms. The second part demonstrates how these stroke primitives can be automatically recovered from input geometry defined in vector form, such as the digitised traces of writing made by a user, or the glyph outlines in a font. This procedure converts the input geometry into a seed that can be transformed into a variety of calligraphic and graffiti stylisations, which depend on parametric variations of the strokes

Modelling graft survival after kidney transplantation using semi-parametric and parametric survival models

A dissertation submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, South Africa, in ful lment of the requirements for the degree of Master of Science in Statistics November, 2017This study presents survival modelling and evaluation of risk factors of graft survival in the context of kidney transplant data generated in South Africa. Beyond the Kaplan-Meier estimator, the Cox proportional hazard (PH) model is the standard method used in identifying risk factors of graft survival after kidney transplant. The Cox PH model depends on the proportional hazard assumption, which is rarely met. Assessing and accounting for this assumption is necessary before using this model. When the PH assumption is not valid, modi cation of the Cox PH model could o er more insight into parameter estimates and the e ect of time-varying predictors at di erent time points. This study aims to identify the survival model that will e ectively describe the study data by employing the Cox PH and parametric accelerated failure time (AFT) models. To identify the risk factors that mediate graft survival after kidney transplant, secondary data involving 751 adults that received a single kidney transplant in Charlotte Maxeke Johannesburg Academic Hospital between 1984 and 2004 was analysed. The graft survival of these patients was analysed in three phases (overall, short-term and long-term) based on the follow-up times. The Cox PH and AFT models were employed to determine the signi cant risk factors. The purposeful method of variable selection based on the Cox PH model was used for model building. The performance of each model was assessed using the Cox-Snell residuals and the Akaike Information Criterion. The t of the appropriate model was evaluated using deviance residuals and the delta-beta statistics. In order to further assess how appropriately the best model t the study data for each time period, we simulated a right-censored survival data based on the model parameter-estimates. Overall, the PH assumption was violated in this study. By extending the standard Cox PH model, the resulting models out-performed the standard Cox PH model. The evaluation methods suggest that the Weibull model is the most appropriate in describing the overall graft survival, while the log-normal model is more reasonable in describing short-and long-term graft survival. Generally, the AFT models out-performed the standard Cox regression model in all the analyses. The simulation study resulted in parameter estimates comparable with the estimates from the real data. Factors that signi cantly in uenced graft survival are recipient age, donor type, diabetes, delayed graft function, ethnicity, no surgical complications, and interaction between recipient age and diabetes. Statistical inferences made from the appropriate survival model could impact on clinical practices with regards to kidney transplant in South Africa. Finally, limitations of the study are discussed in the context of further studies.MT 201

The doctoral research abstracts. Vol:8 2015 / Institute of Graduate Studies, UiTM

Foreword: THIRTY FIRST October 2015 marks the celebration of 47 PhD doctorates receiving their scroll during UiTM 83rd Convocation Ceremony. This date is significant to UiTM since it is an official indication of 47 more scholarly contributions to the world of knowledge and innovation through the novelty of their research. To date UiTM has contributed 471 producers of knowledge through their doctoral research ranging from the field of Science and Technology, Business and Administration, and Social Science and Humanities. This Doctoral Abstracts epitomizes knowledge par excellence and a form of tribute to the 47 doctorates whose achievement we proudly celebrate. To the graduands, your success in achieving the highest academic qualification has demonstrated that you have indeed engineered your destiny well. The action of registering for a PhD program was not by chance but by choice. It was a choice made to realise your self-actualization level that is the highest level in Maslow’s Hierarchy of Needs, while at the same time unleashing your potential in the scholarly research. Do not forget that life is a treasure and that its contents continue to be a mystery, thus, your journey of discovery through research has not come to an end but rather, is just the beginning. Enjoy life through your continuous discovery of knowledge, and spearhead innovation while you are at it. Make your alma mater proud through this continuous discovery as alumni of UiTM. As you soar upwards in your career, my advice will be to continuously be humble and ‘plant’ your feet firmly on the ground. Congratulations once again and may you carry UiTM as ‘Sentiasa di Hatiku’. Tan Sri Dato’ Sri Prof Ir Dr Sahol Hamid Abu Bakar, FASc, PEng Vice Chancellor Universiti Teknologi MAR

Neural activity inspired asymmetric basis function TV-NARX model for the identification of time-varying dynamic systems

Inspired by the unique neuronal activities, a new time-varying nonlinear autoregressive with exogenous input (TV-NARX) model is proposed for modelling nonstationary processes. The NARX nonlinear process mimics the action potential initiation and the time-varying parameters are approximated with a series of postsynaptic current like asymmetric basis functions to mimic the ion channels of the inter-neuron propagation. In the model, the time-varying parameters of the process terms are sparsely represented as the superposition of a series of asymmetric alpha basis functions in an over-complete frame. Combining the alpha basis functions with the model process terms, the system identification of the TV-NARX model from observed input and output can equivalently be treated as the system identification of a corresponding time-invariant system. The locally regularised orthogonal forward regression (LROFR) algorithm is then employed to detect the sparse model structure and estimate the associated coefficients. The excellent performance in both numerical studies and modelling of real physiological signals showed that the TV-NARX model with asymmetric basis function is more powerful and efficient in tracking both smooth trends and capturing the abrupt changes in the time-varying parameters than its symmetric counterparts

Developing clinical prediction models for diabetes classification and progression

Patients with type 1 and type 2 diabetes have very different treatment and care requirements. Overlapping phenotypes and lack of clear classification guidelines make it difficult for clinicians to differentiate between type 1 and type 2 diabetes at diagnosis. The rate of glycaemic deterioration is highly variable in patients with type 2 diabetes but there is no single test to accurately identify which patients will progress rapidly to requiring insulin therapy. Incorrect treatment and care decisions in diabetes can have life-threatening consequences. The aim of this thesis is to develop clinical prediction models that can be incorporated into routine clinical practice to assist clinicians with the classification and care of patient diagnosed with diabetes. We addressed the problem first by integrating features previously associated with classification of type 1 and type 2 diabetes to develop a diagnostic model using logistic regression to identify, at diagnosis, patients with type 1 diabetes. The high performance achieved by this model was comparable to that of machine learning algorithms. In patients diagnosed with type 2 diabetes, we found that patients who were GADA positive and had genetic susceptibility to type 1 diabetes progressed more rapidly to requiring insulin therapy. We built upon this finding to develop a prognostic model integrating predictive features of glycaemic deterioration to predict early insulin requirement in adults diagnosed with type 2 diabetes. The three main findings of this thesis have the potential to change the way that patients with diabetes are managed in clinical practice. Use of the diagnostic model developed to identify patients with type 1 diabetes has the potential to reduce misclassification. Classifying patients according to the model has the benefit of being more akin to the treatment needs of the patient rather than the aetiopathological definitions used in current clinical guidelines. The design of the model lends itself to implementing a triage-based approach to diabetes subtype diagnosis. Our second main finding alters the clinical implications of a positive GADA test in patients diagnosed with type 2 diabetes. For identifying patients likely to progress rapidly to insulin, genetic testing is only beneficial in patients who test positive for GADA. In clinical practice, a two-step screening process could be implemented - only patients who test positive for GADA in the first step would go on for genetic testing. The prognostic model can be used in clinical practice to predict a patient’s rate of glycaemic deterioration leading to a requirement for insulin. The availability of this data will enable clinical practices to more effectively manage their patient lists, prioritising more intensive follow up for those patients who are at high risk of rapid progression. Patients are likely to benefit from tailored treatment. Another key clinical use of the prognostic model is the identification of patients who would benefit most from GADA testing saving both inconvenience to the patient and a cost-benefit to the health service

Global-scale regionalization of hydrologic model parameters

Current state-of-the-art models typically applied at continental to global scales (hereafter called macroscale) tend to use a priori parameters, resulting in suboptimal streamflow (Q) simulation. For the first time, a scheme for regionalization of model parameters at the global scale was developed. We used data from a diverse set of 1787 small-to-medium sized catchments ( 10-10,000 km(2)) and the simple conceptual HBV model to set up and test the scheme. Each catchment was calibrated against observed daily Q, after which 674 catchments with high calibration and validation scores, and thus presumably good-quality observed Q and forcing data, were selected to serve as donor catchments. The calibrated parameter sets for the donors were subsequently transferred to 0.5 degrees grid cells with similar climatic and physiographic characteristics, resulting in parameter maps for HBV with global coverage. For each grid cell, we used the 10 most similar donor catchments, rather than the single most similar donor, and averaged the resulting simulated Q, which enhanced model performance. The 1113 catchments not used as donors were used to independently evaluate the scheme. The regionalized parameters outperformed spatially uniform (i.e., averaged calibrated) parameters for 79% of the evaluation catchments. Substantial improvements were evident for all major Koppen-Geiger climate types and even for evaluation catchments>5000 km distant from the donors. The median improvement was about half of the performance increase achieved through calibration. HBV with regionalized parameters outperformed nine state-of-the-art macroscale models, suggesting these might also benefit from the new regionalization scheme. The produced HBV parameter maps including ancillary data are available via

Genomic tools and sex determination in the extremophile brine shrimp Artemia franciscana

The aim of this study was the construction of a genomic Artemia toolkit. Sex-specific AFLP-based genetic maps were constructed based on 433 AFLP markers segregating in a 112 full-sib family, revealing 21 male and 22 female linkage groups (2n = 42). Fifteen putatively homologous linkage groups, including the sex linkage groups, were identified between the female and male linkage maps. Eight sex-linked markers, heterozygous in female animals, mapped to a single locus on a female linkage group, supporting the hypothesis of a WZ/ZZ genetic sex-determining system and showing primary sex determination is likely directed by a single gene. To fine-map the sex locus, bulked segregant analysis was performed. Candidate primary sex-determining genes were identified, including Cytochrome P450 which, through transcriptomic studies, is already known as a candidate sex-determining gene for Macrobrachium nipponense. The 1,310-Mbp Artemia draft genome sequence (N50 = 14,784 bp; GC-content = 35%; 176,667 scaffolds) was annotated, predicting 188,101 genes with an average length of 692 bp. Ninety-two percent of the transcriptome reads of Artemia in different conditions were present in the Artemia genome, indicating that the functional part of the genome under the RNAseq sampling conditions is virtually fully represented in the assembly. Several steps were taken in this study to introduce Artemia as a new genomic model for crustaceans. Although the functional part of the Artemia genome under the RNAseq sampling conditions is virtually fully represented in the assembly, thus making it useful for qualitative research, genome finishing strategies will still be necessary to complete the genome project. The further development of genomic resources for Artemia will add a completely new dimension to Artemia research and its use as live food in aquaculture