Florida International University College of Medicine and Mount Sinai Medical Center Partner to Establish New Teaching Program

Press Release from Florida International University 's Office of Media Relations on the partnership between the Florida International University College of Medicine and Mt. Sinai Medical Center to establish a new teaching program.

The commercial bark harvest of the African cherry (Prunus africana) on Mount Oku, Cameroon: Effects on traditional uses and population dynamics

Bark extracts of the African cherry (Prunus africana) are used to treat benign prostatic hyperplasia. This study examined the effects of commercial bark harvest on population dynamics in the Kilum-Ijim Forest Preserve on Mount Oku, Cameroon and on traditional uses. P. africana is valued for its timber and as fuel although its greatest value is as a traditional medicine for human and animal ailments. Harvest has depleted the resource and has eroded traditional forest protection practices. I constructed matrix models to examine the effects of bark harvest on population structure and on population dynamics in harvested and unharvested populations. Harvesting simulations examined the effect on the population growth rate (λ) with differing levels of mortality of harvest-sized and large trees and differing harvest frequencies. Size class frequencies for the entire forest decreased in a reverse j-shaped curve, indicating adequate recruitment in the absence of harvest. Individual plots showed differences from the overall forest data, suggesting effects of natural and man-made perturbations, particularly due to bark harvest. One plot (harvested in the 1980s) showed a temporal difference in λ and fluctuated around one, due to alternating high and low fruiting years; other unharvested plots showed smaller temporal differences. Harvested plots (harvested illegally in 1997) had values of λ less than one and showed small temporal differences. The control plot also showed λ less than one, due to poor recruitment in the closed canopy forest. The value of λ for the combined data was 0.9931 suggesting a slightly declining population. The elasticity matrix for the combined data indicated the population growth rate was most sensitive to the survival of the large reproductive trees (42.5% of the elasticity). In perturbation analyses, reducing the survival of the large trees caused the largest reductions in λ. Simulations involving harvesting frequency indicated λ returns to pre-harvest conditions if trees are re-harvested after 10–15 years, but only if the large trees are left unharvested. Management scenarios suggest harvest can be sustainable if seedlings and small saplings are planted in the forest and actively managed, although large-scale plantations may be the only feasible option to meet market demand. ^

Field programmable gate array based target detection and gesture recognition

The move from Standard Definition (SD) to High Definition (HD) represents a six times increases in data, which needs to be processed. With expanding resolutions and evolving compression, there is a need for high performance with flexible architectures to allow for quick upgrade ability. The technology advances in image display resolutions, advanced compression techniques, and video intelligence. Software implementation of these systems can attain accuracy with tradeoffs among processing performance (to achieve specified frame rates, working on large image data sets), power and cost constraints. There is a need for new architectures to be in pace with the fast innovations in video and imaging. It contains dedicated hardware implementation of the pixel and frame rate processes on Field Programmable Gate Array (FPGA) to achieve the real-time performance. ^ The following outlines the contributions of the dissertation. (1) We develop a target detection system by applying a novel running average mean threshold (RAMT) approach to globalize the threshold required for background subtraction. This approach adapts the threshold automatically to different environments (indoor and outdoor) and different targets (humans and vehicles). For low power consumption and better performance, we design the complete system on FPGA. (2) We introduce a safe distance factor and develop an algorithm for occlusion occurrence detection during target tracking. A novel mean-threshold is calculated by motion-position analysis. (3) A new strategy for gesture recognition is developed using Combinational Neural Networks (CNN) based on a tree structure. Analysis of the method is done on American Sign Language (ASL) gestures. We introduce novel point of interests approach to reduce the feature vector size and gradient threshold approach for accurate classification. (4) We design a gesture recognition system using a hardware/ software co-simulation neural network for high speed and low memory storage requirements provided by the FPGA. We develop an innovative maximum distant algorithm which uses only 0.39% of the image as the feature vector to train and test the system design. Database set gestures involved in different applications may vary. Therefore, it is highly essential to keep the feature vector as low as possible while maintaining the same accuracy and performance^