• Honam Mathematical Journal
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• v.38 no.3
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• pp.625-642
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• 2016

The recent papers [7, 12] developed two maps named by an LA- [7] and an LMA-map [12]. The present paper studies their properties and further, develops generalized versions of an LA- and an LMA-map, which makes the LA- [7] and the LMA-map [12] improved.

• Honam Mathematical Journal
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• v.35 no.2
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• pp.319-327
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• 2013

In this paper we compare the notion of proper map in the category of topological spaces with that in the category of semialgebraic sets. To do this, we find some equivalence conditions for semialgebraically proper maps. In particular, we prove that a continuous semialgebraic map is semialgebraically proper if and only if it is proper. Moreover, we compare the semialgebraically proper map with the proper map in the sense of Delfs and Knebush [4].

• Journal of applied mathematics & informatics
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• v.14 no.1_2
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• pp.277-288
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• 2004

In this paper, we discuss a continuous self-map of an interval and the existence of an uncountable strongly chaotic set. It is proved that if a continuous self-map of an interval has positive topological entropy, then it has an uncountable strongly chaotic set in which each point is recurrent, but is not almost periodic.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.10
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• pp.397-406
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• 2014

In order to answer the questions successfully on behalf of the human in DeepQA environments such as Jeopardy! of the American quiz show, the computer is required to have the capability of fast temporal and spatial reasoning on a large-scale commonsense knowledge base. In this paper, we present a scalable spatial reasoning algorithm for deriving efficiently new directional and topological relations using the MapReduce framework, one of well-known parallel distributed computing environments. The proposed reasoning algorithm assumes as input a large-scale spatial knowledge base including CSD-9 directional relations and RCC-8 topological relations. To infer new directional and topological relations from the given spatial knowledge base, it performs the cross-consistency checks as well as the path-consistency checks on the knowledge base. To maximize the parallelism of reasoning computations according to the principle of the MapReduce framework, we design the algorithm to partition effectively the large knowledge base into smaller ones and distribute them over multiple computing nodes at the map phase. And then, at the reduce phase, the algorithm infers the new knowledge from distributed spatial knowledge bases. Through experiments performed on the sample knowledge base with the MapReduce-based implementation of our algorithm, we proved the high performance of our large-scale spatial reasoner.

• Journal of the Korea Society of Computer and Information
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• v.18 no.4
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• pp.27-34
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• 2013

Mobile robot has the exploration function in order to perform its own task. Robot exploration can be used in many applications such as surveillance, rescue and resource detection. The workspace that robots performed in was complicated or quite wide, the multi search using the several mobile robots was mainly used. In this paper, we proposed a scheme that all areas are searched for by using one robot. The method to be proposed extract a area that can be explored in the workspace then the robot investigates the area and updates the map at the same time. The explored area is saved as a hybrid map that combines the nice attributes of the grid and topological maps. The robot can produce the safe navigation route without the obstacles by using hybrid map. The proposed hybrid map uses less memory than a grid map, but it can be used for complete coverage with the same efficiency of a topological map. Experimental results show that the proposed scheme can generate a map of an environment with only 6% of the memory that a grid map requires.

• The Pure and Applied Mathematics
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• v.14 no.2 s.36
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• pp.63-70
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• 2007

In this paper, we introduce the concepts of r-gp-open map, weakly r-gp-open map, intuitionistic fuzzy r-compactness, nearly intuitionistic fuzzy r-compactness and almost intuitionistic fuzzy r-compactness defined by intuitionixtic gradations of openness, and obtain some characterizations.

• Korean Journal of Mathematics
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• v.12 no.2
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• pp.177-183
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• 2004

In this paper, we introduce the concepts of half-interior, half-closure, half-gp-maps and half-gp-open maps defined by intuitionistic gradations of openness.

• The KIPS Transactions:PartB
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• v.8B no.5
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• pp.515-522
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• 2001

Feature-based similarity retrieval become an important research issue in image database systems. The features of image data are useful to discrimination of images. In this paper, we propose the highspeed k-Nearest Neighbor search algorithm based on Self-Organizing Maps. Self-Organizing Map(SOM) provides a mapping from high dimensional feature vectors onto a two-dimensional space. A topological feature map preserves the mutual relations (similarity) in feature spaces of input data, and clusters mutually similar feature vectors in a neighboring nodes. Each node of the topological feature map holds a node vector and similar images that is closest to each node vector. We implemented about k-NN search for similar image classification as to (1) access to topological feature map, and (2) apply to pruning strategy of high speed search. We experiment on the performance of our algorithm using color feature vectors extracted from images. Promising results have been obtained in experiments.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.37-42
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• 2005

This paper presents an autonomous system for reconstruction of three-dimensional indoor environments using a mobile robot. The system is composed of a mobile robot, a three-dimensional scanning system, and a notebook computer for registration, observation planning and real-time three-dimensional data transferring. Three-dimensional scanning system obtains three-dimensional environmental data and performs filtering of dynamic objects. Then, it registers multiple three-dimensional scans into one coordinate system and performs observation planning which finds the next scanning position by using the layered hexahedral-map and topological-map. Then, the mobile robot moves to the next scanning position, and repeats all procedures until there is no scanning tree in topological-map. In concurrence with data scanning, three-dimensional data can be transferred through wireless-LAN in real-time. This system is experimented successfully by using a mobile robot named KARA.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1039-1043
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• 2005

Despite the many significant advances made in robot architecture, the basic approaches are deliberative and reactive methods. They are quite different in recognizing outer environment and inner operating mechanism. For this reason, they have almost opposite characteristics. Later, researchers integrate these two approaches into hybrid architecture. In such architecture, Reactive module also called low-level motion control module have advantage in real-time reacting and sensing outer environment; Deliberative module also called high-level task planning module is good at planning task using world knowledge, reasoning and intelligent computing. This paper presents a framework of the integrated planning and control for mobile robot navigation. Unlike the existing hybrid architecture, it learns topological map from the world map by using MST (Minimum Spanning Tree)-based SOFM (Self-Organizing Feature Map) algorithm. High-level planning module plans simple tasks to low-level control module and low-level control module feedbacks the environment information to high-level planning module. This method allows for a tight integration between high-level and low-level modules, which provide real-time performance and strong adaptability and reactivity to outer environment and its unforeseen changes. This proposed framework is verified by simulation.