• The Journal of Korea Robotics Society
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• v.18 no.4
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• pp.487-495
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• 2023

This paper presents a method for autonomous exploration of indoor environments using a 2-dimensional Light Detection And Ranging (LiDAR) scanner. The proposed frontier-based exploration method considers navigability from the current robot position to extracted frontier targets. An approach to constructing the point cloud grid map that accurately reflects the occupancy probability of glass obstacles is proposed, enabling identification of safe frontier grids on the safety grid map calculated from the point cloud grid map. Navigability, indicating whether the robot can successfully navigate to each frontier target, is calculated by applying the skeletonization-informed rapidly exploring random tree algorithm to the safety grid map. While conventional exploration approaches have focused on frontier detection and target position/direction decision, the proposed method discusses a safe navigation approach for the overall exploration process until the completion of mapping. Real-world experiments have been conducted to verify that the proposed method leads the robot to avoid glass obstacles and safely navigate the entire environment, constructing the point cloud map and calculating the navigability with low computing time deviation.

• Macromolecular Research
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• v.10 no.3
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• pp.145-149
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• 2002

Transesterification between poly(trimethylene terephthalate) (PTT) and bisphenol-A-polycarbonate (PC) is studied by differential scanning calorimetry (DSC) and nuclear magnetic resonance (NMR) spectroscopy. When the blend of PTT/PC is annealed at higher temperatures, the samples do not show any melting peak at an initial stage, indicating the samples completely lose their crystallinity due to the formation of random copolymers. However, when the random copolymer is annealed at temperatures lower than the melting temperature of PTT, a melting peak is observed, indicating that the random copolymers are sequentially reordered. The melting point and the heat of fusion of crystals formed from the crystallization-induced sequential reordering depend upon the annealing temperature and time. The average sequence length determined from NMR is increased as the blocks are regenerated.

• Journal of the Institute of Convergence Signal Processing
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• v.16 no.1
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• pp.9-14
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• 2015

Outlier detection and removal is a crucial step needed for various image processing applications such as image registration. Random Sample Consensus (RANSAC) is known to be the best algorithm so far for the outlier detection and removal. However RANSAC requires a cosiderable computation time. To drastically reduce the computation time while preserving the comparable quality, a outlier detection and removal method based on modified K-means is proposed. The original K-means was conducted first for matching point pairs and then cluster merging and member exclusion step are performed in the modification step. We applied the methods to various images with highly repetitive patterns under several geometric distortions and obtained successful results. We compared the proposed method with RANSAC and showed that the proposed method runs 3~10 times faster than RANSAC.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.5
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• pp.859-870
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• 2011

The purpose of this paper is to develop reliability analysis procedures for repairable systems with interval failure time data and apply the procedures for assessing the storage reliability of a subsystem of a certain type of guided missile. In the procedures, the interval failure time data are converted to pseudo failure times using the uniform random generation method, mid-point method or equispaced intervals method. Then, such analytic trend tests as Laplace, Lewis-Robinson, Pair-wise Comparison Nonparametric tests are used to determine whether the failure process follows a renewal or non-renewal process. Monte Carlo simulation experiments are conducted to compare the three conversion methods in terms of the statistical performance for each trend test when the underlying process is homogeneous Poisson, renewal, or non-homogeneous Poisson. The simulation results show that the uniform random generation method is best among the three. These results are applied to actual field data collected for a subsystem of a certain type of guided missile to identify its failure process and to estimate its mean time to failure and annual mean repair cost.

• KDI Journal of Economic Policy
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• v.38 no.2
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• pp.1-20
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• 2016

In this paper, we conduct uniform inference of two widely used versions of the Phillips curve, specifically the random-walk Phillips curve and the New-Keynesian Phillips curve (NKPC). For both specifications, we propose a potentially time-varying natural unemployment (NAIRU) to address the uncertainty surrounding the inflation-unemployment trade-off. The inference is conducted through the construction of what is known as the uniform confidence band (UCB). The proposed methodology is then applied to point-ahead inflation forecasting for the Korean economy. This paper finds that the forecasts can benefit from conducting UCB-based inference and that the inference results have important policy implications.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.20 no.5
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• pp.471-479
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• 2009

In this paper, we proposed an improved ray tracing method with an amelioration of visible tree structure, a visible face determination method, and non-uniform random test point method. In a proposed visible tree structure, it reduces tree nodes by means of merging similar nodes. In a visible face determination method, it shows that a ray hit test with a packet ray method can reduce a test time. A ray tracing method involving with a packet ray hit test method can improve a tree construction time up to 3.3 times than a ray tracing method with a single ray hit test method. Furthermore, by seeding a non-uniform and random test point on a face, tree construction time is improved up to 1.11 times. Received powers from the proposed ray tracing results and measured results have good agreement with 1.9 dB RMS error.

• Communications for Statistical Applications and Methods
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• v.20 no.6
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• pp.439-454
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• 2013

This study presents a Bayesian multiple change-point detection approach to segment and classify the observations that no longer come from an initial population after a certain time. Inferences are based on the multiple change-points in a sequence of random variables where the probability distribution changes. Bayesian multiple change-point estimation is classifies each observation into a segment. We use a truncated Poisson distribution for the number of change-points and conjugate prior for the exponential family distributions. The Bayesian method can lead the unsupervised classification of discrete, continuous variables and multivariate vectors based on latent class models; therefore, the solution for change-points corresponds to the stochastic partitions of observed data. We demonstrate segmentation with real data.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.04a
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• pp.427-431
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• 1994

The objective of this paper is to provide an inventory control policy for the system that carries a single item with a multiple demand classes, when the demand is Poisson distributed random variable. The inventory control process includes the process of determining the reorder point, and the process of inventory control during the lead time. The goal of the optimization process is to achieve the service level of each demand class as well as the system-wide total service level at a preset desired service level while sustaining a minimum average inventory.

• Journal of Korean Institute of Industrial Engineers
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• v.21 no.4
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• pp.555-570
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• 1995

We consider a preventive replacement policy for a cold-standby system with N components, in which only one component is in operation at a time. If the component in operation fails, a standby component is immediately switched into operation. If all components fail, the system fails. The system is inspected at random poins in time to determine whether it is to be replaced or not. If the number of failed components at the time of inspection exceeds a threshold value r, the system is replaced. Otherwise the decision is put off until the next inspection point arrives. Under the cost structure which includes a replacement cost, a system down-time cost and a holding cost of the components, we develop an efficient procedure to find the optimal control values N and r, which minimize the expected cost per unit time.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.49 no.3
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• pp.169-176
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• 2000

The partial discharge(PD) signal, may seems to be stochastic and merely random, was investigated using the method to discern between chaos and random signal, e.g. correlation integral, Lyapunov characteristic exponents and etc. For the purpose of obtaining experimental data, partial discharge detecting system via computer aided acoustic sensor, detect PD signal from the insulating system, was used. While this method is very different from typical statistical analysis from the point of view of a nonlinear analysis, it can provide better interpretable criterion according to the time evolution with a degradation process in the same type insulating system.