• Journal of Electrical Engineering and Technology
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• v.10 no.2
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• pp.670-675
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• 2015

Medical imaging is one of the most powerful tools for gaining information about internal organs and tissues. It is a challenging task to develop sophisticated image analysis methods in order to improve the accuracy of diagnosis. The objective of this paper is to develop a Computer Aided Diagnostics (CAD) scheme for Brain Tumour detection from Magnetic Resonance Image (MRI) using active contour models and to investigate with several approaches for improving CAD performances. The problem in clinical medicine is the automatic detection of brain Tumours with maximum accuracy and in less time. This work involves the following steps: i) Segmentation performed by Fuzzy Clustering with Level Set Method (FCMLSM) and performance is compared with snake models based on Balloon force and Gradient Vector Force (GVF), Distance Regularized Level Set Method (DRLSE). ii) Feature extraction done by Shape and Texture based features. iii) Brain Tumour detection performed by various tree classifiers. Based on investigation FCMLSM is well suited segmentation method and Random Forest is the most optimum classifier for this problem. This method gives accuracy of 97% and with minimum classification error. The time taken to detect Tumour is approximately 2 mins for an examination (30 slices).

• Journal of computational fluids engineering
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• v.12 no.2
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• pp.21-25
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• 2007

A general purpose program NUFLEX has been extended for two-phase flows with topologically complex interface and cavitation flows with liquid-vapor phase change caused by large pressure drop. In analysis of two-phase flow, the phase interfaces are tracked by employing a LS(Level Set) method. Compared with the VOF(Volume-of-Fluid) method based on a non-smooth volume-fraction function, the LS method can calculate an interfacial curvature more accurately by using a smooth distance function. Also, it is quite straightforward to implement for 3-D irregular meshes compared with the VOF method requiring much more complicated geometric calculations. Also, the cavitation process is computed by including the effects of evaporation and condensation for bubble formation and collapse as well as turbulence in flows. The volume-faction and continuity equations are adapted for cavitation models with phase change. The LS and cavitation formulation are implemented into a general purpose program for 3-D flows and verified through several test problems.

• Advances in aircraft and spacecraft science
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• v.6 no.4
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• pp.333-348
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• 2019

Low fuel regression rate is the main drawback of hybrid rocket which should be overcome. One of the improvement techniques to this problem is usage of a solid fuel grain with a complicated geometry port, which has been promoted owing to the recent development of additive manufacturing technologies. In the design of a hybrid rocket fuel grain with a complicated geometry port, the understanding of fuel regression behavior is very important. Numerical investigations of fuel regression behavior requires a capturing method of solid fuel surface, i.e. gas-solid interface. In this study, level set method is employed as such a method and the preliminary numerical tool for capturing a hybrid rocket solid fuel surface is developed. At first, to test the adequacy of the numerical modeling, the simulation results for circular port are compared to the experimental results in open literature. The regression rates and oxidizer to fuel ratios show good agreements between the simulations and the experiments, after passing enough time. However, during the early period of combustion, there are the discrepancies between the simulations and the experiments, owing to transient phenomena. Second, the simulations of complicated geometry ports are demonstrated. In this preliminary step, a star shape is employed as complicated geometry of port. The slot number effect in star port is investigated. The regression rate decreases with increasing the slot number, except for the star port with many slots (8 slots) in the latter half of combustion. The oxidizer to fuel ratio increases with increasing the slot number.

• Journal of Korean Society for Quality Management
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• v.47 no.4
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• pp.701-711
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• 2019

Purpose: The problem of optimizing redundancy allocation in multi-level systems is considered when each item in a multi-level system has alternative items with the same function. The number of redundancy of multi-level system is allocated to maximize the reliability of the system under path set and cost limitation constraints. Methods: Based on cost limitation and path set constraints, a mathematical model is established to maximize system reliability. Particle swarm optimization is employed for redundant allocation and verified by numerical experiments. Results: Comparing the particle swarm optimization method and the memetic algorithm for the 3 and 4 level systems, the particle swarm optimization method showed better performance for solution quality and search time. Particularly, the particle swarm optimization showed much less than the memetic algorithm for variation of results. Conclusion: The proposed particle swarm optimization considerably shortens the time to search for a feasible solution in MRAP with path set constraints. PS optimization is expected to reduce search time and propose the better solution for various problems related to MRAP.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.147-147
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• 2018

In this article, we use an open source software library: TensorFlow, developed for the purposes of conducting very complex machine learning and deep neural network applications. However, the system is general enough to be applicable in a wide variety of other domains as well. The proposed model based on a deep neural network model, LSTM (Long Short-Term Memory) to predict the river water level at Okcheon Station of the Guem River without utilization of rainfall - forecast information. For LSTM modeling, the input data is hourly water level data for 15 years from 2002 to 2016 at 4 stations includes 3 upstream stations (Sutong, Hotan, and Songcheon) and the forecasting-target station (Okcheon). The data are subdivided into three purposes: a training data set, a testing data set and a validation data set. The model was formulated to predict Okcheon Station water level for many cases from 3 hours to 12 hours of lead time. Although the model does not require many input data such as climate, geography, land-use for rainfall-runoff simulation, the prediction is very stable and reliable up to 9 hours of lead time with the Nash - Sutcliffe efficiency (NSE) is higher than 0.90 and the root mean square error (RMSE) is lower than 12cm. The result indicated that the method is able to produce the river water level time series and be applicable to the practical flood forecasting instead of hydrologic modeling approaches.

• KOGO NEWS
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• v.6 no.1
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• pp.29-33
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• 2006

Gene set analysis is a new concept and method. to analyze and interpret microarray gene expression data and tries to extract biological meaning from gene expression data at gene set level rather than at gene level. Compared with methods which select a few tens or hundreds of genes before gene ontology and pathway analysis, gene set analysis identifies important gene ontology terms and pathways more consistently and performs well even in gene expression data sets with minimal or moderate gene expression changes. Moreover, gene set analysis is useful for comparing multiple gene expression data sets dealing with similar biological questions. This review briefly summarizes the rationale behind the gene set analysis and introduces several algorithms and tools now available for gene set analysis.

• Journal of the Korea Computer Graphics Society
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• v.18 no.2
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• pp.9-15
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• 2012

In this paper, we propose a method to segment a color image into several meaningful regions. We suppose that the meaningful region has a set of colors with high frequency in the color image. To find these colors, the color image is represented as several sets of color points in RGB space. And when we use the density of points defined in this method, color belonging to a dense region of color points in RGB space refers to the color that appeared frequently in the image. Eventually, we can find meaningful regions by looking for regions with high density of color points using our level set function in RGB space. However, if a meaningful region does not have a contiguous region of the sufficient size in the image, this is not a meaningful region but meaningless region. Thus, the pixels in the meaningless region are assigned to the biggest meaningful region belonging to its neighboring pixels in the color image. Our method divides the color image into meaningful regions by applying the density of color points to level set function in RGB space. This is different from the existing level set method that is defined only in 2D image.

• Journal of Power Electronics
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• v.19 no.5
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• pp.1162-1170
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• 2019

Finite-control-set model predictive control (FCS-MPC) is a promising control scheme for two-level voltage-source inverters (TL-VSIs). However, two main issues arise in the classical FCS-MPC method: an exponentially-increasing computational time and a low steady-state performance. To solve these two issues, a novel FCS-MPC method has been proposed for n-phase TL-VSIs in this paper. The basic idea of the proposed method is to carry out the FCS-MPC scheme of TL-VSIs for one leg by one leg, like a "pipeline". Based on this idea, the calculations are reduced from exponential time to linear time and its current waveforms are improved by applying more switching states per sampling period. The cases of three-phase and five-phase TL-VSIs were tested to verify the effectiveness of proposed method.

• 한국전산유체공학회:학술대회논문집
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• 2005.04a
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• pp.202-206
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• 2005

A new numerical scheme for two-phase flows, the Hybrid VOF method has been developed for improved free surface capturing. The present new method is a volume capturing based VOF method coupled with a reinitialization procedure of a Level-set method. For validation, the proposed method is applied to two test cases: spherical bubble rising and dam breaking. The calculated results by using the Hybrid VOF method with the two previously applied VOF formulations are compared with available numerical and experimental data. It is found that the new method provides more accurate results than the two previous ones.

• Journal of the Society of Naval Architects of Korea
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• v.45 no.2
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• pp.132-143
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• 2008

The sloshing phenomena in a two-dimensional rectangular tank are investigated using a level set method based on finite volume method. The code validations are performed by comparing between the present results and previous numerical results, which gives a good agreement. We present the streamlines pattern, free surface shape, maximum free surface elevation and pressure fluctuation patterns in the tank under the pitch and surge motions with various frequencies. These two different motions cause the different flow structures in the tank. The time variations of surface elevation and pressure at the different locations in the tank strongly depend on the exciting frequency of tank moving.