A Robotic CAD System using a Bayesian Framework

We present in this paper a Bayesian CAD system for robotic applications. We address the problem of the propagation of geometric uncertainties and how esian CAD system for robotic applications. We address the problem of the propagation of geometric uncertainties and how to take this propagation into account when solving inverse problems. We describe the methodology we use to represent and handle uncertainties using probability distributions on the system's parameters and sensor measurements. It may be seen as a generalization of constraint-based approaches where we express a constraint as a probability distribution instead of a simple equality or inequality. Appropriate numerical algorithms used to apply this methodology are also described. Using an example, we show how to apply our approach by providing simulation results using our CAD system

Investigation of IGES for CAD/CAE data transfer

In a CAD/CAE facility there is always the possibility that one may want to transfer the design graphics database from the native system to a non-native system. This may occur because of dissimilar systems within an organization or a new CAD/CAE system is to be purchased. The Initial Graphics Exchange Specification (IGES) was developed in an attempt to solve this scenario. IGES is a neutral database format into which the CAD/CAE native database format can be translated to and from. Translating the native design database format to IGES requires a pre-processor and transling from IGES to the native database format requires a post-processor. IGES is an artifice to represent CAD/CAE product data in a neutral environment to allow interfacing applications, archive the database, interchange of product data between dissimilar CAD/CAE systems, and other applications. The intent here is to present test data on translating design product data from a CAD/CAE system to itself and to translate data initially prepared in IGES format to various native design formats. This information can be utilized in planning potential procurement and developing a design discipline within the CAD/CAE community

CAD Adjacency Computation Using Validated Numerics

We present an algorithm for computation of cell adjacencies for well-based cylindrical algebraic decomposition. Cell adjacency information can be used to compute topological operations e.g. closure, boundary, connected components, and topological properties e.g. homology groups. Other applications include visualization and path planning. Our algorithm determines cell adjacency information using validated numerical methods similar to those used in CAD construction, thus computing CAD with adjacency information in time comparable to that of computing CAD without adjacency information. We report on implementation of the algorithm and present empirical data.Comment: 20 page

Application of computer-aided dispatch in law enforcement: An introductory planning guide

A set of planning guidelines for the application of computer-aided dispatching (CAD) to law enforcement is presented. Some essential characteristics and applications of CAD are outlined; the results of a survey of systems in the operational or planning phases are summarized. Requirements analysis, system concept design, implementation planning, and performance and cost modeling are described and demonstrated with numerous examples. Detailed descriptions of typical law enforcement CAD systems, and a list of vendor sources, are given in appendixes

CAD-model-based vision for space applications

A pose acquisition system operating in space must be able to perform well in a variety of different applications including automated guidance and inspections tasks with many different, but known objects. Since the space station is being designed with automation in mind, there will be CAD models of all the objects, including the station itself. The construction of vision models and procedures directly from the CAD models is the goal of this project. The system that is being designed and implementing must convert CAD models to vision models, predict visible features from a given view point from the vision models, construct view classes representing views of the objects, and use the view class model thus derived to rapidly determine the pose of the object from single images and/or stereo pairs

Fractional flow reserve-guided management in stable coronary disease and acute myocardial infarction: recent developments

Coronary artery disease (CAD) is a leading global cause of morbidity and mortality, and improvements in the diagnosis and treatment of CAD can reduce the health and economic burden of this condition. Fractional flow reserve (FFR) is an evidence-based diagnostic test of the physiological significance of a coronary artery stenosis. Fractional flow reserve is a pressure-derived index of the maximal achievable myocardial blood flow in the presence of an epicardial coronary stenosis as a ratio to maximum achievable flow if that artery were normal. When compared with standard angiography-guided management, FFR disclosure is impactful on the decision for revascularization and clinical outcomes. In this article, we review recent developments with FFR in patients with stable CAD and recent myocardial infarction. Specifically, we review novel developments in our understanding of CAD pathophysiology, diagnostic applications, prognostic studies, clinical trials, and clinical guidelines

Computer-aided detection of pulmonary nodules in low-dose CT

A computer-aided detection (CAD) system for the identification of pulmonary nodules in low-dose multi-detector helical CT images with 1.25 mm slice thickness is being developed in the framework of the INFN-supported MAGIC-5 Italian project. The basic modules of our lung-CAD system, a dot enhancement filter for nodule candidate selection and a voxel-based neural classifier for false-positive finding reduction, are described. Preliminary results obtained on the so-far collected database of lung CT scans are discussed.Comment: 3 pages, 4 figures; Proceedings of the CompIMAGE - International Symposium on Computational Modelling of Objects Represented in Images: Fundamentals, Methods and Applications, 20-21 Oct. 2006, Coimbra, Portuga