• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.865-868
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• 1993

This paper describes a simple random signal generator employing by CMOS analog technology in current mode. The system is a nonlinear dynamical system described by a difference equation, such as x(t＋1) = f(x(t)) , t = 0,1,2, ... , where f($.$) is a nonlinear function of x(f). The tent map is used as a nonlinear function to produce the random signals with the uniform distribution. The prototype is implemented by using transistor array devices fabricated in a mass product line. It can be easily realized on a chip. Uniform randomness of the signal is examined by the serial correlation test and the $\chi$2 test.

• BMB Reports
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• v.35 no.5
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• pp.465-471
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• 2002

From fruiting bodies of L. edodes strain L-54, single-spore isolates (SSIs) were collected. Two parental types of L-54 were regenerated via monokaryotization. By means of random-amplified polymorphic DNA (RAPD), DNA samples from L-54, its two parental types, and 32 SSIs were amplified with arbitrary primers. Dedikaryotization was demonstrated, and 91 RAPD-based molecular markers were generated. RAPD markers that were segregated at a 1:1 ratio were used to construct a linkage map of L. edodes. This RAPD-linkage map greatly enhanced the mapping of other inheritable and stable markers [such as those that are linked to a phenotype (the mating type), a known gene (priA) and a sequenced DNA fragment (MAT)] with the aid of mating tests, bulked-segregant analysis, and PCR-single-strand conformational polymorphism. These markers comprised a genetic map of L. edodes with 14 linkage groups and a total length of 622.4 cM.

• Journal of the Korean Mathematical Society
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• v.39 no.1
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• pp.51-60
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• 2002

Some random fixed point theorems for nonexpansive and *-nonexpansive random operators defined on convex and star-shaped sets in a Frechet space are proved. Our work extends recent results of Beg and Shahzad and Tan and Yaun to noncontinuous multivalued random operators, sets analogue to an earlier result of Itoh and provides a random version of a deterministic fixed point theorem due to Singh and Chen.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.1
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• pp.145-151
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• 2014

This paper proposes an image haze removal algorithm for a single image. The conventional Dark Channel Prior(DCP) algorithm estimates a transmission map using the dark information in an image, and the haze regions are then detected using a matting algorithm. However, since the DCP algorithm uses block-based processing, block artifacts are invariably formed in the transmission map. To solve this problem, the proposed algorithm generates a modified transmission map using a Hidden Markov Random Field(HMRF) and Expectation-Maximization(EM) algorithm. Experimental results confirm that the proposed algorithm is superior to conventional algorithms in image haze removal.

• Bulletin of the Korean Mathematical Society
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• v.41 no.2
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• pp.327-335
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• 2004

In this paper, we reformulate a snapshot attractor([5]), ($K,\;\={\mu_{\iota}}$) generated by a random baker's map with a sequence of probability measures {\={\mu_{\iota}}} on K. We obtain bounds of the correlation dimensions of ($K,\;\={\mu_{\iota}}$) for all ${\iota}\;{\geq}\;1$.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.12
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• pp.3688-3693
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• 2009

In this paper the design methode of a separated composition state machine based on the compositive map with connecting two chaotic maps together - sawtooth map $S_2(x)$ and tent map $T_2(x)$ and the result of that is proposed. this paper gives a graph of the chaotic states generated by the composition state machine using the compositive logic of two different chaotic maps - sawtooth map and tent map and also shows that the period of pseudo-random states has the length according to the precision of the discreet truth table.

• The Journal of Korea Robotics Society
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• v.7 no.2
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• pp.150-159
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• 2012

In this paper, we propose a cost-aware Rapidly-exploring Random Tree (RRT) path planning algorithm for mobile robots. A mobile robot is presented with a cost map of the field of interest and assigned to move from one location to another. As a robot moves, the robot is penalized by the cost at its current location according to the cost map. The overall cost of the robot is determined by the trajectory of the robot. The goal of the proposed cost-aware RRT algorithm is to find a trajectory with the minimal cost. The cost map of the field can represent environmental parameters, such as temperature, humidity, chemical concentration, wireless signal strength, and stealthiness. For example, if the cost map represents packet drop rates at different locations, the minimum cost path between two locations is the path with the best possible communication, which is desirable when a robot operates under the environment with weak wireless signals. The proposed cost-aware RRT algorithm extends the basic RRT algorithm by considering the cost map when extending a motion segment. We show that the proposed algorithm gives an outstanding performance compared to the basic RRT method. We also demonstrate that the use of rejection sampling can give better results through extensive simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.5
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• pp.450-456
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• 2006

Monte Carlo localization is known to be one of the most reliable methods for pose estimation of a mobile robot. Although MCL is capable of estimating the robot pose even for a completely unknown initial pose in the known environment, it takes considerable time to give an initial pose estimate because the number of random samples is usually very large especially for a large-scale environment. For practical implementation of MCL, therefore, a reduction in sample size is desirable. This paper presents a novel approach to reducing the number of samples used in the particle filter for efficient implementation of MCL. To this end, the topological information generated through the thinning technique, which is commonly used in image processing, is employed. The global topological map is first created from the given grid map for the environment. The robot then scans the local environment using a laser rangefinder and generates a local topological map. The robot then navigates only on this local topological edge, which is likely to be similar to the one obtained off-line from the given grid map. Random samples are drawn near the topological edge instead of being taken with uniform distribution all over the environment, since the robot traverses along the edge. Experimental results using the proposed method show that the number of samples can be reduced considerably, and the time required for robot pose estimation can also be substantially decreased without adverse effects on the performance of MCL.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.12C
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• pp.738-743
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• 2011

For the high quality 3-D broadcasting, depth maps are important data. Although commercially available depth cameras capture high-accuracy depth maps in real time, their resolutions are much smaller than those of the corresponding color images due to technical limitations. In this paper, we propose the depth map up-sampling method using a high-resolution color image and a low-resolution depth map. We define a random walk probability model in an operation unit which has nearest seed pixels. The proposed method is appropriate to match boundaries between the color image and the depth map. Experimental results show that our method enhances the depth map resolution successfully.