• Journal of the Institute of Convergence Signal Processing
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• v.12 no.4
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• pp.267-273
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• 2011

In this paper, we proposed the method to detect brain tumor region in MR images. Our method is composed of 3 parts, detection of tumor slice, detection of tumor region and tumor boundary detection. In the tumor slice detection step, a slice which contains tumor regions is distinguished using symmetric analysis in 3D brain volume. The tumor region detection step is the process to segment the tumor region in the slice distinguished as a tumor slice. And tumor region is finally detected, using spatial feature and symmetric analysis based on the cluster information. The process for detecting tumor slice and tumor region have advantages which are robust for noise and requires less computational time, using the knowledge of the brain tumor and cluster-based on symmetric analysis. And we use the level set method with fast marching algorithm to detect the tumor boundary. It is performed to find the tumor boundary for all other slices using the initial seeds derived from the previous or later slice until the tumor region is vanished. It requires less computational time because every procedure is not performed for all slices.

• Fire Science and Engineering
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• v.11 no.4
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• pp.3-14
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• 1997

The smoke filling process for the atrium space containing a fire source is simulated using two types of deterministic fire model : Zone model and Field model. The zone model used is the CFAST(version 1.6) model developed at the Building and Fire Research Laboratories, NIST in the USA. The field model is a self-developed frie field model based on Computational Fluid Dynamic (CFD) theories. This article is focused on finding out the smoke movement and temperature distribution in atrium space which is cubic in shape. For solving the liked set of velocity and pressure equation, the PISO algorithm, which strengthened the velocity-pressure coupling, was used. Since PISO algorithm is a time-marching procedure, computing time si very fast. A computational procedure for predicting velocity and temperature distribution in fire-induced flow is based on the solution, in finite volume method and non-staggered grid system, of 3-dimensional equations for the conservation of mass, momentum, energy, species and so forth. The fire model i.e Zone model and Field model predicted similar results for clear heights and the smoke layer temperature.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.4
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• pp.407-416
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• 2020

Recent complex battle field demands Network Centric Warfare(NCW) ability to control various parts into a cohesive unit. In path planning filed, the NCW ability increases complexity of path planning algorithm, and it has to consider a communication coverage map as well as traditional parameters such as minimum radar exposure and survivability. In this paper, pros and cons of various propagation models are summarized, and we suggest a coverage map generation method using a Longley-Rice propagation model. Previous coverage map based on line of sight has significant discontinuities that limits selection of path planning algorithms such as Dijkstra and fast marching only. If there is method to remove discontinuities in the coverage map, optimization based path planning algorithms such as trajectory optimization and Particle Swarm Optimization(PSO) can also be used. In this paper, the Longley-Rice propagation model is used to calculate continuous RF strengths, and convert the strength data using smoothed leaky BER for the coverage map. In addition, we also suggest other types of rough coverage map generation using a lookup table method with simple inputs such as terrain type and antenna heights only. The implemented communication coverage map can be used various path planning algorithms, especially in the optimization based algorithms.