Disseminating Object-Oriented Applications in Large Scale Environments

The conventional wisdom in the scientific computing community is that the best way to solve large-scale numerically intensive scientific problems on today's parallel MIMD computers is to use Fortran or C programmed in a data-parallel style using low-level message-passing primitives. This approach inevitably leads to nonportable codes and extensive development time, and restricts parallel programming to the domain of the expert programmer. We believe that these problems are not inherent to parallel computing but are the result of the programming tools used. We will show that comparable performance can be achieved with little effort if better tools that present higher level abstractions are used. The vehicle for our demonstration is a 2D electromagnetic finite element scattering code we have implemented in Mentat, an object-oriented parallel processing system. We briefly describe the application. Mentat, the implementation, and present performance results for both a Mentat and a hand-coded parallel Fortran version.

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Pine wilt disease detection in high-resolution UAV images using object-oriented classification

Journal of Forestry Research ◽

10.1007/s11676-021-01420-x ◽

2021 ◽

Author(s):

Zhao Sun ◽

Yifu Wang ◽

Lei Pan ◽

Yunhong Xie ◽

Bo Zhang ◽

...

Keyword(s):

High Resolution ◽

Large Scale ◽

Digital Camera ◽

Object Oriented ◽

Pine Wilt Disease ◽

Wilt Disease ◽

Segmentation Algorithm ◽

Tree Crown ◽

Multi Scale ◽

Pine Wilt

AbstractPine wilt disease (PWD) is currently one of the main causes of large-scale forest destruction. To control the spread of PWD, it is essential to detect affected pine trees quickly. This study investigated the feasibility of using the object-oriented multi-scale segmentation algorithm to identify trees discolored by PWD. We used an unmanned aerial vehicle (UAV) platform equipped with an RGB digital camera to obtain high spatial resolution images, and multi-scale segmentation was applied to delineate the tree crown, coupling the use of object-oriented classification to classify trees discolored by PWD. Then, the optimal segmentation scale was implemented using the estimation of scale parameter (ESP2) plug-in. The feature space of the segmentation results was optimized, and appropriate features were selected for classification. The results showed that the optimal scale, shape, and compactness values of the tree crown segmentation algorithm were 56, 0.5, and 0.8, respectively. The producer’s accuracy (PA), user’s accuracy (UA), and F1 score were 0.722, 0.605, and 0.658, respectively. There were no significant classification errors in the final classification results, and the low accuracy was attributed to the low number of objects count caused by incorrect segmentation. The multi-scale segmentation and object-oriented classification method could accurately identify trees discolored by PWD with a straightforward and rapid processing. This study provides a technical method for monitoring the occurrence of PWD and identifying the discolored trees of disease using UAV-based high-resolution images.

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Crop Mapping in the Sanjiang Plain Using an Improved Object-Oriented Method Based on Google Earth Engine and Combined Growth Period Attributes

Remote Sensing ◽

10.3390/rs14020273 ◽

2022 ◽

Vol 14 (2) ◽

pp. 273

Author(s):

Mengyao Li ◽

Rui Zhang ◽

Hongxia Luo ◽

Songwei Gu ◽

Zili Qin

Keyword(s):

Large Scale ◽

Vegetation Index ◽

Object Oriented ◽

Growth Period ◽

Sanjiang Plain ◽

Google Earth ◽

Utilization Rate ◽

Growth Stages ◽

The Sanjiang Plain ◽

Growth Method

In recent years, the scale of rural land transfer has gradually expanded, and the phenomenon of non-grain-oriented cultivated land has emerged. Obtaining crop planting information is of the utmost importance to guaranteeing national food security; however, the acquisition of the spatial distribution of crops in large-scale areas often has the disadvantages of excessive calculation and low accuracy. Therefore, the IO-Growth method, which takes the growth stage every 10 days as the index and combines the spectral features of crops to refine the effective interval of conventional wavebands for object-oriented classification, was proposed. The results were as follows: (1) the IO-Growth method obtained classification results with an overall accuracy and F1 score of 0.92, and both values increased by 6.98% compared to the method applied without growth stages; (2) the IO-Growth method reduced 288 features to only 5 features, namely Sentinel-2: Red Edge1, normalized difference vegetation index, Red, short-wave infrared2, and Aerosols, on the 261st to 270th days, which greatly improved the utilization rate of the wavebands; (3) the rise of geographic data processing platforms makes it simple to complete computations with massive data in a short time. The results showed that the IO-Growth method is suitable for large-scale vegetation mapping.

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Object-Oriented Optimization for Small- and Large-Scale Seismic Inversion Procedures

10.3997/2214-4609.202181003 ◽

2021 ◽

Author(s):

E. Biondi ◽

G. Barnier ◽

R. Clapp ◽

F. Picetti ◽

S. Farris

Keyword(s):

Large Scale ◽

Object Oriented ◽

Seismic Inversion

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Object-Oriented Applications in Marine Hydrodynamics

10.5957/smc-2012-a31 ◽

2012 ◽

Author(s):

Piotr J. Bandyk ◽

Justin Freimuth ◽

George Hazen

Keyword(s):

Large Scale ◽

Object Oriented ◽

System Of Systems ◽

Object Oriented Programming ◽

Marine Hydrodynamics ◽

Natural Approach ◽

Complex Problems ◽

Systems Model

Object-oriented programming offers a natural approach to solving complex problems by focusing on individual aspects, or objects, and describing the ways in which they interact using interfaces. Modularity, extensibility, and code re-use often make OOP more appealing than its procedural counterpart. Code can be implemented in a more intuitive way and often mirrors the theory it derives from. Two examples are given in the form of real programs: a 3D panel code solver and a system-of-systems model for seabasing and environment sensing. Both are examples of large-scale frameworks and leverage the benefits offered by the object-oriented paradigm.

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GenASiS Basics: Object-oriented utilitarian functionality for large-scale physics simulations (Version 3)

Computer Physics Communications ◽

10.1016/j.cpc.2019.05.014 ◽

2019 ◽

Vol 244 ◽

pp. 483-486

Author(s):

Reuben D. Budiardja ◽

Christian Y. Cardall

Keyword(s):

Large Scale ◽

Object Oriented

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Development of an Object-Oriented Program With Adaptive Mesh Refinement for Heat Transfer Simulations

ASME/JSME 2007 Thermal Engineering Heat Transfer Summer Conference, Volume 1 ◽

10.1115/ht2007-32897 ◽

2007 ◽

Author(s):

Jianhu Nie ◽

David A. Hopkins ◽

Yitung Chen ◽

Hsuan-Tsung Hsieh

Keyword(s):

Heat Transfer ◽

Adaptive Mesh Refinement ◽

Large Scale ◽

Mesh Refinement ◽

Object Oriented ◽

Adaptive Mesh ◽

Time Cost ◽

Test Bed ◽

Element Analysis ◽

Cpu Time

A 2D/3D object-oriented program with h-type adaptive mesh refinement method is developed for finite element analysis of the multi-physics applications including heat transfer. A framework with some basic classes that enable the code to be built accordingly to the type of problem to be solved is proposed. The program consists of different modules and classes, which ease code development for large-scale complex systems, code extension and program maintenance. The developed program can be used as a “test-bed” program for testing new analysis techniques and algorithms with high extensibility and flexibility. The overall mesh refinement causes the CPU time cost to greatly increase as the mesh is refined. However, the CPU time cost does not increase very much with the increase of the level of h-adaptive mesh refinement. The CPU time cost can be saved by up to 90%, especially for the simulated system with a large number of elements and nodes.

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