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During the software lifecycle, the software structure is subject to many changes in order to fulfill the customer's requirements. In Distributed Object Oriented systems, software engineers face many challenges to solve the software-hardware mismatch problem in which the software structure does not match the customer's underlying hardware. A major design problem of Object Oriented software systems is the efficient distribution of software classes among the different nodes in the system while maintaining two features: low-coupling and high software quality. In this paper, we present a new methodology for efficiently restructuring Distributed Object Oriented software systems to improve the overall system performance and to solve the softwarehardware mismatch problem. Our method has two main phases. In the first phase, we use the hierarchical clustering method to restructure the target software application. As a result, all the possible clustering solutions that could be applied to the target software application are generated. In the second phase, we decide on the best-fit clustering solution according to the customer hardware organization.
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The primary purpose of this study was to investigate the feasibility of using simulated data from the United Kingdom Meteorological Office (UKMO) global climate mathematical model to serve as boundary values for a regional model RM3 which has been used by NASA to make predictions about climate dynamics in West Africa. In the past, historical data has been used successfully as boundary data but this approach limits outcomes to time periods in the past. The advantage of using the UKMO data is its potential to provide input boundary data for future time periods resulting in future regional predictions. This study has provided NASA scientists with graphical and statistical summaries including visual animations that provide qualitative and quantitative information necessary for evaluating whether the UKMO data can be used as a driving force for the RM3 model. One definite conclusion of this investigation is that both spatial and temporal interpolation of UKMO results will be necessary in order to make its results compatible with the RM3 model.
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The software restructuring techniques present solutions for the software-hardware mismatch problem in which the software structure does not match the available hardware platform. In Distributed Object Oriented (DOO) systems, software engineers face many challenges to solve the software-hardware mismatch problem. One important aspect of DOO software systems is the efficient distribution of software classes among the different nodes while maintaining low-coupling and high software quality. In this paper, we present a new methodology for efficiently restructuring the DOO software systems to improve the performance and to solve the software-hardware mismatch problem. In our method, we use the hierarchical clustering technique to opt the classes to be grouped together and according to the customer hardware organization, we pick the level of the hierarchy that have the appropriate number of clusters to be allocated to the set of available nodes in the customer distributed system.
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The use of Transmission Electron Microscopy (TEM) to characterize the microstructure of a material continues to grow in importance as technological advancements become increasingly more dependent on nanotechnology 1. Since nanoparticle properties such as size (diameter) and size distribution are often important in determining potential applications, a particle analysis is often performed on TEM images. Traditionally done manually, this has the potential to be labor intensive, time consuming, and subjective 2. To resolve these issues, automated particle analysis routines are becoming more widely accepted within the community 3. When using such programs, it is important to compare their performance, in terms of functionality and cost. The primary goal of this study was to apply one such software package, ImageJ to grayscale TEM images of nanoparticles with known size. A secondary goal was to compare this popular open-source general purpose image processing program to two commercial software packages. After a brief investigation of performance and price, ImageJ was identified as the software best suited for the particle analysis conducted in the study. While many ImageJ functions were used, the ability to break agglomerations that occur in specimen preparation into separate particles using a watershed algorithm was particularly helpful 4. © 2009 SPIE-IS&T.
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