• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2005.10a
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• pp.231-234
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• 2005

The high temperature deformation behavior of AZ 31 Mg alloy was investigated by designing a back propagation neural network that uses a gradient descent-learning algorithm. A neural network modeling is an intelligent technique that can solve non-linear and complex problems by learning from the samples. Therefore, some experimental data have been firstly obtained from continuous compression tests performed on a thermo-mechanical simulator over a range of temperatures $(250-500^{\circ}C)$ with strain rates of $0.0001-100s^{-1}$ and true strains of 0.1 to 0.6. The inputs for neural network model are strain, strain rate, and temperature and the output is flow stress. It was found that the trained model could well predict the flow stress for some experimental data that have not been used in the training. Workability of a material can be evaluated by means of power dissipation map with respect to strain, strain rate and temperature. Power dissipation map was constructed using the flow stress predicted from the neural network model at finer Intervals of strain, strain rates and subsequently processing maps were developed for hot working processes for AZ 31 Mg alloy. The safe domains of hot working of AZ 31 Mg alloy were identified and validated through microstructural investigations.

• Communications of the Korean Mathematical Society
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• v.34 no.3
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• pp.951-965
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• 2019

Let $f:X{\rightarrow}X$ be a continuous map on a compact metric space (X, d) and for an arbitrary $x{\in}X$, $${\mathcal{SC}}_d(x,f):=\{y{\mid}x{\text{ can be strong }}d-{\text{chain to }}y\}$$. We give an example to show that ${\mathcal{SC}}_d(x,f)$ is dependent on the metric d on X but it is a closed and f-invariant set. We prove that if ${\mathcal{SC}}_d(x,f){\supseteq}{\Omega}(f)$ or f has the asymptotic-average shadowing property, then ${\mathcal{SC}}_d(x,f)=X$. Also, we show that if f has the shadowing property, then ${\lim}\;{\sup}_{n{\in}{\mathbb{N}}}\{f^n\}={\mathcal{SC}}_d(f)$ where ${\mathcal{SC}}_d(f)=\{(x,y){\mid}y{\in}{\mathcal{SC}}_d(x,f)\}$. For each $n{\in}{\mathbb{N}}$, we give an example in which ${\mathcal{SCR}}_d(f^n){\neq}{\mathcal{SCR}}_d(f)$. In spite of it, we prove that if $f^{-1}:(X,d){\rightarrow}(X,d)$ is an equicontinuous map, then ${\mathcal{SCR}}_d(f^n)={\mathcal{SCR}}_d(f)$ for all $n{\in}{\mathbb{N}}$.

• Journal of Environmental Impact Assessment
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• v.18 no.3
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• pp.143-150
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• 2009

The present study investigates the effects of the flight paths of military aircraft on noise map and its WECPNL(Weighted Equivalent Continuous Perceived Noise Level) distribution. Aircraft noise modeling and simulation have been performed on a Korean military air base by means of INM(Integrated Noise Model) with the input data of airfield location, aircraft specifications, flight paths and aircraft's operation schedules. The result of noise modelling has been verified in comparison with the result of measured noise level. The flight path of military aircraft, as the key parameter of the present study, was modeled by combining takeoff, overfly, approach and touch-and-go modes. The present INM simulations have been conducted for various flight path cases with different takeoff, approach modes and overfly modes. The simulation results showed that the change of flight path can remarkably affect the noise influence region and the WECPNL distribution around the airfield.

• Proceedings of the IEEK Conference
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• 2001.06e
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• pp.203-206
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• 2001

The fMRI which can express the function of brain as MR image is now being studied. The study on the functional image has usually been performed with the MRI in 4 tesla class in goneral, but if gradient echo imaging method could be used, it might make the most of what it has with the MRI in 1.5 tesla class. However, the lack of adequate image post-processing software prevents it from being used as widely as it could be. For the image post-processing algorithm of the functional image, subtraction method and several statistical methods are used with continuous introduction of new method recently. In this paper, we suggest adaptation of wavelet algorithm for obtaining a more reliable brain function map.

• Communications of the Korean Mathematical Society
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• v.9 no.4
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• pp.933-944
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• 1994

Let $\pi : P \to S^4$ be a principal G-bundle over $S^4$ whose the structure group G is a compact, connected, simple Lie group. Since $\pi_3(G) = \pi_4 (BG) = Z$, we can classify the principal bundle $P_k$ over $S^4$ by the map $S^4 \to BG$ of degree k. Atiyah and Jones [2] showed that $C_k = A_k/g^b_k$ is homotopy equivalent to $\Omega^3_k G \simeq \Omega^4_k BG$ where $A_k$ is the space of the all connections in $P_k$ and $g^b_k$ is the based gauge group which consists of all base point preserving automorphisms on $P_k$. Here $\Omega^nX$ is the space of all base-point preserving continuous map from $S^n$ to X. Let $M_k$ be the space of based gauge equivalence classes of all connections in $P_k$ satisfying the Yang-Mills self-duality equations, which we call the moduli space of G instantons.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.576-578
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• 2003

Hyperspectral image divides VNIR region to over 200 bands which can show continuous spectrum with 10 nm spectral resolution. This property is useful in geology where a spectral feature which is decided by chemical compositions and crystalline structures is recorded well. While this field has been studied variously in foreign countries, the studies are in the early stage in Korea. In this study, characteristic materials associated with AMD were classified by using EO-1 HYPERION data which is a spaceborne hyperspectral image and topographical map and DEM and geochemical map were analyzed in conjunction with the image in order to examine that classified minerals are secondary minerals by AMD.

• KCID journal
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• v.13 no.1
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• pp.39-49
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• 2006

Weather station based PET(Potential Evapotrarspiration) analysis has often been inadequate to meet the needs of regional-scale irrigation planning. A map of continuous PET surface would be better a solution for the spatial interpolation considering spatial variations. Using a normal PET data collected at the 54 meteorological stations in Korea, 10-days spatial distribution PET map was created using universal Kriging(UK). These estimation methods were evaluated by both visual assessments of the output maps and the quantitative comparison of error measures that were obtained from the cross validation. The universal Kriging method showed appropriate results in spatial interpolation from weather station based PET to spatial PET with low statistical errors.

• Korean Journal of Remote Sensing
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• v.21 no.5
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• pp.417-423
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• 2005

A fuzzy approach using an EM algorithm for image classification is presented. In this study, a double compound stochastic image process is assumed to combine a discrete-valued field for region-class processes and a continuous random field for observed intensity processes. The Markov random field is employed to characterize the geophysical connectedness of a digital image structure. The fuzzy classification is an EM iterative approach based on mixture probability distribution. Under the assumption of the double compound process, given an initial class map, this approach iteratively computes the fuzzy membership vectors in the E-step and the estimates of class-related parameters in the M-step. In the experiments with remotely sensed data, the MRF-based method yielded a spatially smooth class-map with more distinctive configuration of the classes than the non-MRF approach.

• ETRI Journal
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• v.41 no.5
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• pp.574-584
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• 2019

A new Mirai variant found recently was equipped with a dynamic update ability, which increases the level of difficulty for DDoS mitigation. Continuous development of 5G technology and an increasing number of Internet of Things (IoT) devices connected to the network pose serious threats to cyber security. Therefore, researchers have tried to develop better DDoS mitigation systems. However, the majority of the existing models provide centralized solutions either by deploying the system with additional servers at the host site, on the cloud, or at third party locations, which may cause latency. Since Internet service providers (ISP) are links between the internet and users, deploying the defense system within the ISP domain is the panacea for delivering an efficient solution. To cope with the dynamic nature of the new DDoS attacks, we utilized an unsupervised artificial neural network to develop a hierarchical two-layered self-organizing map equipped with a twofold feature selection for DDoS mitigation within the ISP domain.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.14-19
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• 2021

This paper presents LiDAR static obstacle map based vehicle dynamic state estimation algorithm for urban autonomous driving. In an autonomous driving, state estimation of host vehicle is important for accurate prediction of ego motion and perceived object. Therefore, in a situation in which noise exists in the control input of the vehicle, state estimation using sensor such as LiDAR and vision is required. However, it is difficult to obtain a measurement for the vehicle state because the recognition sensor of autonomous vehicle perceives including a dynamic object. The proposed algorithm consists of two parts. First, a Bayesian rule-based static obstacle map is constructed using continuous LiDAR point cloud input. Second, vehicle odometry during the time interval is calculated by matching the static obstacle map using Normal Distribution Transformation (NDT) method. And the velocity and yaw rate of vehicle are estimated based on the Extended Kalman Filter (EKF) using vehicle odometry as measurement. The proposed algorithm is implemented in the Linux Robot Operating System (ROS) environment, and is verified with data obtained from actual driving on urban roads. The test results show a more robust and accurate dynamic state estimation result when there is a bias in the chassis IMU sensor.