A Neural Network Structure for Prediction of Chemical Agent Fate

This work presents the development of a multi-input, multi-output neural network structure to predict the time dependent concentration of chemical agents as they participate in chemical reaction with environmental substrates or moisture content within these substrates. The neural network prediction is based on a computationally or experimentally produced database that includes the concentration of all chemicals presents (reactants and products) as a function of the chemical agent droplet size, wind speed, temperature, and turbulence. The utilization of this prediction structure is made userfriendly via an easy-to-use graphical user interface. Furthermore, upon the knowledge of the time-varying environmental parameters (wind speed and temperature that are usually recorded and available), the time varying concentration of all chemicals can be predicted almost instantaneously by recalling the previously trained network. The network prediction was compared with actual open air test data and the results were found to match

Realtime LabVIEW implementation of cochlear implant signal processing on PDA platforms

This paper presents the real-time implementation of a cochlear implant signal processing system on PDAs. The PDAs were chosen as they provide portable and costeffective computation platforms. To gain software flexibility and interactivity, the LabVIEW graphical programming environment is used. The paper discusses the optimization steps which are taken to achieve a real-time throughput. These steps consist of using dynamic link libraries, utilizing efficient memory allocation, and performing fixed-point arithmetic. These steps are general purpose in the sense that the same steps can be deployed for real-time implementation of other clinical or industrial signal processing applications on PDAs. 1

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A constant-time algorithm for erosions/dilations with applications to morphological texture feature computation

A computationally efficient algorithm for computing erosions and dilations by one-dimensional grayscale structuring elements with constant slope is proposed. The computational complexity of this algorithm is independent of the size of the support of the structuring function. This is a generalization of the method proposed by Van Herk for the case of erosion and dilation by flat one-dimensional structuring elements. By appropriate combinations of these structuring elements, it is possible to approximate many useful structuring elements. This enables efficient computation of granulometries where the number of operations depends linearly on the number of openings. Theoretical and experimental results comparing the complexity of this algorithm with other standard techniques is presented. Two memory efficient algorithms are then presented. Several implementation issues in computing a granulometry and moments of the associated morphological pattern spectrum are then addressed. An efficient implementation of granulometries for large images on machines with limited memory, by dividing the image into smaller rectangular patches is then discussed. The optimum size of these patches is a function of the specific hardware and has been obtained experimentally for three different hardware platforms. Finally, parallel implementation of the different algorithms on two multiprocessor machines is discussed

A generic software-framework for distributed, high-performance processing of multi-view video

This paper presents a software framework providing a platform for parallel and distributed processing of video data on a cluster of SMP computers. Existing video-processing algorithms can be easily integrated into the framework by considering them as atomic processing tiles (PTs). PTs can be connected to form processing graphs that model the data flow of a specific application. This graph also defines the data dependencies that determine which tasks can be computed in parallel. Scheduling of the tasks in this graph is carried out automatically using a pool-of-tasks scheme. The data format that can be processed by the framework is not restricted to image data, such that also intermediate data, like detected feature points or object positions, can be transferred between PTs. Furthermore, the processing can optionally be carried out efficiently on special-purpose processors with separate memory, since the framework minimizes the transfer of data. Finally, we describe an example application for a multi-camera view-interpolation system that we successfully implemented on the proposed framework