Meeting
Agenda Meeting
Agenda
Extensions to the texture-mapping support of the abstract graphics hardware pipeline and the OpenGL API are proposed to better support programmable shading, with a unified interface, on a variety of future graphics accelerator architectures. Our main proposals include better support for texture map coordinate generation and an abstract, programmable model for multitexturing.
As motivation, we survey several interactive rendering algorithms that target important visual phenomena. With hardware implementation of programmable multitexturing support, implementations of these effects that currently take multiple passes can be rendered in one pass. The generality of our proposed extensions enable efficient implementation of a wide range of other interactive rendering algorithms.
The intermediate level of abstraction of our API proposal enables high-level shader metaprogramming toolkits and relatively straightforward implementations, while hiding the details of multitexturing support that are currently fragmenting OpenGL into incompatible dialects.
We propose a new class of models, frailty measurement error models (FMEMs), for clustered survival data when covariates are measured with error. We explore FMEMs from two directions: bias analysis and parameter inference. We study the asymptotic bias when measurement error is ignored, and develop a structural model for parameter estimation using the nonparametric maximum likelihood (NPML) method. We prove the identifiability of the model, the existence of the NPML estimates (NPMLEs), and consistency and asymptotic normality of the NPMLEs. An EM algorithm is developed to calculate the NPMLEs. The proposed method is applied to the western Kenya parasitemia data and its performance is evaluated through simulations.The talk will be followed by coffee and cookies in MC 6123. ALL WELCOME!
Genetic testing is a concern for insurers if they are prohibited from using testing results in underwriting. We evaluate the impact of adverse selection in an insurance market with genetic testing for breast and ovarian cancer. We estimate increased forces of mortality resulting from a family history of cancer, or a positive test for a BRCA mutation. Using a continuous-time discrete-state Markov model, we estimate costs of adverse selection, assuming various testing and insurance purchase behaviours. We conclude that, at current testing rates, adverse selection should be controllable if companies apply strict underwriting rules, requesting cancer history and onset age for all first-degree relatives. If companies do not request precise family information, or are forbidden by law to obtain it, adverse selection costs would be so large that major disruptions in the insurance market would result.The talk will be followed by coffee and cookies in MC 6123. ALL WELCOME!
Talk sponsored by: Institute of Insurance and Pension Research
Software architecture recovery is receiving much attention due to the shift of research interest towards the higher level of abstraction in both forward and reverse engineering. Most approaches in this domain try to provide automation in the process of extracting high-level design of a legacy system from its lower level representation, e.g., source code.We propose an architectural design recovery based on design descriptions defined by the user in the form of structured queries. We call this formalism Architectural Query Language (AQL). The AQL allows the user to describe a conceptual architecture of the system in the form of modules and interconnections using a combination of placeholders and system's entities. A pattern matching engine is then searches for close matches in the source model to instantiate the placeholders with the system's entities.
We use Data Mining techniques to group the system's entities into clusters (source model) based on various relations between entities (e.g., function call, variable or datatype usage). A branch and bound search algorithm is used to provide an actual architecture for the described query in AQL. The algorithm uses association rules between the entities as a main guide to select architectural entities. The approach is promising in both being fast, and considering the correlation between entities as the clustering criteria.
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Few people know how to use graphics modeling packages, but everyone can build things out of blocks and clay. Starting from this premise, and with the goal of developing accessible modeling tools for building and populating virtual worlds, we have developed two novel object-modeling systems.The first system consists of Lego-like building blocks that self-describe the geometric structures into which they are assembled. In contrast to previously reported self-describing construction kits, our approach has advantages of scalability, configurability, and interactivity. Each building block contains a microcontroller (a simple microprocessor), and can communicate with the blocks to which it is physically connected. The blocks in an assembled structure use a distributed algorithm to first discover how they are connected to their immediate neighbors. This information is then relayed from brick to brick --- each of our block structures is essentially a self- configuring, store-and-forward computer network --- until it reaches the host computer. From the block connectivity data that it collects, and knowledge of the shape of each block, the host computer can recover the geometric structure of the assembled blocks. The structure can then be rendered in various styles, ranging from a literal rendition in which blocks look like Lego bricks, to decorative interpretations in which structural elements are identified automatically and augmented appropriately. Once rendered, the virtual models are available for viewing and manipulation by the user. Through the use of embedded sensors and transducers, the user can also interact with the virtual world through the block model.
The second system uses customized variants of known computer-vision techniques to recognize and parse clay models of common toy-like objects, such as people, animals, trees, houses, cars, boats, etc. Using a single calibrated camera to capture images of a clay model on a rotary table, we recover a volumetric scan of the model. The scanned volume is then matched against a small set of object templates. This process allows us to both classify the clay model and to identify its constituent parts. Using this information we can, for example, recognize and parse a clay model of an ambulatory object, and then animate it appropriately in a virtual world.
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For a complete abstract, please visit our website.
For Additional Information:
URL: http://www.math.uwaterloo.ca/CandO_Dept/Seminars/upcoming.html