• The Journal of the Petrological Society of Korea
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• v.17 no.4
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• pp.191-205
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• 2008

In order to use the geologic information data such as industrialization of rock resources, site enlargement and development planning, distributive ratios of rock types and geologic ages were obtained by the ArcGIS 9.2 program, and digital geologic and geographic maps of 1:250,000 scale, in the Chungbug, Chungnam and Daejeon areas, respectively. In the Chungbug area, 64 rock kinds are developed and their geologic ages can be classified into 8 large groups. In the geologic ages, the ratios are decreasing in the order of Jurassic, Precambrian, Age-unknown, Cretaceous, Quaternary, Cambro-Ordovician and Carboniferous-Triassic ages, all of which comprise most ratios of 98.48% in the area. In the rock types, the ratios show the decreasing order of Jurassic Daebo granite, Precambrian banded gneiss of Gyeonggi metamorphic complex, Cretaceous biotite granite, Quaternary alluvium, Great limestone group, Lower phyllite zone and Meta-sandy rock zone of age-unknown Ogcheon group, Triassic Cheongsan granite, Precambrian granitic gneiss of Gyeonggi gneiss complex, Pebble bearing phyllite zone of age-unknown Ogcheon group and biotite gneiss of Sobaegsan metamorphic complex, all of which comprise the prevailing ratio of 84.27% in the area. In the Chungnam area, 35 rock types are developed and their geologic ages can be classified into 6 large groups. In the geologic ages, the ratios are decreasing in the order of Precambrian, Jurassic and Quaternary ages, which occupy the prevailing ratio of 87.55% in the area. In the rock types, the ratios show the decreasing order of Jurassic Daebo granite, Precambrian banded gneiss of Gyeonggi metamorphic complex, Quaternary alluvium, Precambrian granite and granitic gneiss of Gyeonggi gneiss complex, Cretaceous acidic dykes, Lower phyllite zone and Pebble bearing phyllite zone of age-unknown Ogcheon group and Quaternary reclaimed land, which occupy the ratios of 74.28% in the area. In the Daejeon area, 11 rock types are developed and their geologic ages can be classified into 5 large groups. In the ages, the ratios are decreasing in the order of Jurassic, Age-unknown and Quaternary, which occupy most ratios of 93.40% in the area. In the rock types, the ratios show the decreasing order of Jurassic Daebo granite, Quaternary alluvium and Lower phyllite zone and Pebble bearing phyllite zone of age-unknown Ogcheon group, which occupy the prevailing ratios of 91.09% in the area.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.4
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• pp.305-314
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• 2015

The work presented in this paper deals with a navigation problem for multiple mobile robot system in unknown indoor environments. The environment is completely unknown for all the robots and the surrounding information should be detected by the proximity sensors installed on the robots' bodies. In order to guide all the robots to move along collision-free paths and reach the goal positions, a navigation method based on the combination of a set of primary strategies has been developed. The indoor environments usually contain convex and concave obstacles. In this work, a danger judgment strategy in accordance with the sensors' data is used for avoiding small convex obstacles or moving objects which include both dynamic obstacles and other robots. For big convex obstacles or concave ones, a wall following strategy is designed for dealing with these special situations. In this paper, a state memorizing strategy is also proposed for the "infinite repetition" or "dead cycle" situations. Finally, when there is no collision risk, the robots will be guided towards the targets according to a target positioning strategy. Most of these strategies are achieved by the means of fuzzy logic controllers and uniformly applied for every robot. The simulation experiments verified that the proposed method has a positive effectiveness for the navigation problem.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.1 s.94
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• pp.253-264
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• 1999

Most autonomous mobile robots view only things in front of them, and as a result, they may collide with objects moving from the side or behind. To overcome this problem. an Active Omni-directional Range Sensor System has been built that can obtain an omni-directional range data through the use of a laser conic plane and a conic mirror. Also, mobile robot has to know its current location and heading angle by itself as accurately as possible to successfully navigate in real environments. To achieve this capability, we propose a self-localization algorithm of a mobile robot using an active omni-directional range sensor in an unknown environment. The proposed algorithm estimates the current position and head angle of a mobile robot by a registration of the range data obtained at two positions, current and previous. To show the effectiveness of the proposed algorithm, a series of simulations was conducted and the results show that the proposed algorithm is very efficient, and can be utilized for self-localization of a mobile robot in an unknown environment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.3
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• pp.268-276
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• 1992

In this paper, we present an discrimination method of unknown digital modulated signals in noisy communication environment. We propose the use of an identification procedure based on time domain signal parameters. First, We extract instantaneous envelope. Frequency and difference phase as the basic feature informations from received signals. In order to identify signals using the extracted feature informations, we design the two dimensional feature space. The extracted feature infomations are mapped into2Dfeature space using 2D feature points. The procedure has been tested by simulations on a computer in noisy communication environment, and the considered signals are ASK-W, ASK-4, BPSK, QPSK, 8PSK, FSK, and QAM.

• Journal of Ocean Engineering and Technology
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• v.25 no.4
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• pp.59-65
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• 2011

In structural health monitoring (SHM) using electro-mechanical impedance signatures, it is a critical issue for extremely large structures to extract the best damage diagnosis results, while minimizing unknown environmental effects, including temperature, humidity, and acoustic vibration. If the impedance signatures fluctuate because of these factors, these fluctuations should be eliminated because they might hide the characteristics of the host structural damages. This paper presents a long-term SHM technique under an unknown noisy environment for tidal current power plant structures. The obtained impedance signatures contained significant variations during the measurements, especially in the audio frequency range. To eliminate these variations, a continuous principal component analysis was applied, and the results were compared with the conventional approach using the RMSD (Root Mean Square Deviation) and CC (Cross-correlation Coefficient) damage indices. Finally, it was found that this approach could be effectively used for long-term SHM in noisy environments.

• International Journal of Aeronautical and Space Sciences
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• v.11 no.2
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• pp.98-109
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• 2010

This paper deals with a new method of unmanned aerial vehicle (UAV) recovery when a UAV fails to get a global positioning system (GPS) signal at an unprepared site. The proposed method is based on the simultaneous localization and mapping (SLAM) algorithm. It is a process by which a vehicle can build a map of an unknown environment and simultaneously use this map to determine its position. Extensive research on SLAM algorithms proves that the error in the map reaches a lower limit, which is a function of the error that existed when the first observation was made. For this reason, the proposed method can help an inertial navigation system to prevent its error of divergence with regard to the vehicle position. In other words, it is possible that a UAV can navigate with reasonable positional accuracy in an unknown environment without the aid of GPS. This is the main idea of the present paper. Especially, this paper focuses on path planning that maximizes the discussed ability of a SLAM algorithm. In this work, a SLAM algorithm based on extended Kalman filter is used. For simplicity's sake, a blimp-type of UAV model is discussed and three-dimensional pointed-shape landmarks are considered. Finally, the proposed method is evaluated by a number of simulations.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.37 no.2
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• pp.16-28
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• 2000

In this paper, we propose a navigation algorithm for a mobile robot, which is intelligently searching the goal location in unknown dynamic environments using an ultrasonic sensor. Instead of using "sensor fusion"method which generates the trajectory of a robot based upon the environment model and sensory data, "command fusion"method is used to govern the robot motions. The major factors for robot navigation are represented as a cost function. Using the data of the robot states and the environment, the weight value of each factor is determined for an optimal trajectory in dynamic environments. For the evaluation of the proposed algorithm, we peformed simulations in PC as well as real experiments with ZIRO. The results show that the proposed algorithm is apt to identify obstacles in unknown environments to guide the robot to the goal location safely.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.5
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• pp.367-372
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• 2001

This paper proposes a hierachically structured navigation algorithm for multiple mobile robots under unknown dynamic environment. The proposed algorithm consists of three basic parts as follows. The first part based on the fuzzy rule generates the turning angle and moving distance of the robot for goal approach without obstacles. In the second part, using both fuzzy and neural network, the angle and distance of the robot to avoid collision with dynamic and static obstacles are obtained. The final adjustment of the weighting factor based on fuzzy rule for moving and avoiding distance of the robots is provided in the third stage. Some simulation results show the effectiveness of the proposed algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.2
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• pp.180-185
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• 2003

This paper proposes an intelligent navigation algorithm for multiple mobile robots under unknown dynamic environment. The proposed algorithm consists of three basic parts as follows. The first part based on the fuzzy rule generates the turning angle and moving distance of the robot for goal approach without obstacles. In the second part, using both fuzzy and neural network, the angle and distance of the robot to avoid collision with dynamic and static obstacles are obtained. The final adjustment of the weighting factor based on fuzzy rule for moving and avoiding distance of the robots is provided in the third stage. The experiments which demonstrate the performance of the proposed intelligent controller is described.

• Economic and Environmental Geology
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• v.13 no.1
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• pp.21-27
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• 1980

${\delta}^{13}C$ and ${\delta}^{18}O$ values were determined for the Paleozoic limestones (Great Linestone Series) from the Taebaegsan region and the age-unknown limestones (Janggun Formation) from the Janggun mine, Korea. Limestones of the Great Limestone Series exhibit a range of carbon isotopic composition from -4.5 +1.3‰ with a mean ${\delta}^{13}C$ value of -1.1‰, relative to the PDB standard, and of oxygen isotpic composition from +8.8 to +23.3‰ with a mean ${\delta}^{18}O$ value of +16.0‰, relative to the SMOW, falling into the normal marine limestone range according to Keith and Weber (1964), and Degens and Epstein(1964). Carbon isotopic composition of limestones of the Great Limestone Series becomes progressively lighter from Pungchon limestone of middle Cambrian age to mid-Ordovician Maggol limestone, possibly due to change in depositional environment in the Taebaegsan basin. Variation in isotopic composition of limestones from Hwajeol to Dumugal formation offers the possibility or deposition in shallow sea environment, in which fresh waters were added in several stages. Janggun limestone of unknown age may be corelated with the Paleozoic limestones of Great Limestone Series as infered from the istopic composition ranging from -2.8 to + 0.7‰ of ${\delta}^{13}C$ and +13.4 to +22.4‰ of ${\delta}^{18}O$.