• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.1
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• pp.75-80
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• 2005

In this paper, a 3-dimensional analysis of magnetic road and a position sensing system for an autonomous vehicle system is described. Especially, a new position sensing system, end of the important component of an autonomous vehicle, is proposed. In a magnet based autonomous vehicle system, to sense the vehicle position, the sensor measures the field of magnetic road. The field depends on the sensor position of the vehicle on the magnetic road. As the rotation between the magnetic field and the sensor position is highly complex, it is difficult that the relation is stored in memory. Thus, a neural network is used to learn the mapping from th field to the position. The autonomous vehicle system with the proposed position sensing system is tested in experimental setup.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.07b
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• pp.719-722
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• 2003

Ferroelectric $Pb(Zr_{1-x}Ti_x)O_3$ (PZT) films were deposited on (001) MgO single crystals using sol-gel method. Structural properties and surface morphologies of PZT films were investigated using an X-ray diffractometer and a scanning electron microscopy, respectively. The dielectric properties of PZT films were investigated with the dc bias field using interdigitated capacitors (IDC) which were fabricated on PZT films using a thick metal layer by photolithography and dry etching process. The small signal dielectric properties of PZT films were calculated by a modified conformal mapping method with low and high frequency data, such as capacitance measured by an impedance gain/phase analyzer at 100 kHz and reflection coefficient (S-parameter) measured by a HP 8510C vector network analyzer at 1 -20 GHz. The IDC on PZT films exhibited about 67% of capacitance change with an electric field of 135 kV/cm at 10 GHz. These PZT thin films can be applied to tunable microwave devices such as phase shifters, tunable resonators and tunable filters.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.4
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• pp.402-409
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• 2006

In recent years, several methods in distributed environment have been proposed in which a user-centered multimedia service may be efficiently provided. However, problems such as the improvement of QoS, streaming and the dynamic service of data for distributed service of multimedia data are introduced. In this paper we propose $POX -H_{r}$ structure for user-centered multimedia service in distributed network environment. The proposed $POX -H_{r}$ structure are constructed by disjunct, conjunct, semantic and filtering mapping scheme, and its structure are updated by $M_{filtering}$ scheme. The comparison results shows that the proposed method provides the better than the other methods.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.124-129
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• 1992

The goal of the proposed Intelligent Assisting System - IAS is to assist human operators in an intelligent way, while leaving decision and goal planning instances for the human. To realize the IAS the very important issue of manipulation skill identification and analysis has to be solved, which then is stored in a Skill Data Base. Using this data base the IAS is able to perform complex manipulations on the motion control level and to assist the human operator flexibly. We propose a model for manipulation skill based on the dynamics of the grip transformation matrix, which describes the dynamic transformation between object space and finger joint space. Interaction with a virtual world simulator allows the calculation and feedback of appropriate forces through controlled actuators of the sensor glove with 10 degrees-of-freedom. To solve the sensor glove calibration problem, we learn the nonlinear calibration mapping by an artificial neural network(ANN). In this paper we also describe the experimental system setup of the skill acquisition and transfer system as a first approach to the IAS. Some simple manipulation examples and simulation results show the feasibility of the proposed manipulation skill model.

• Journal of Korean Society of Rural Planning
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• v.19 no.3
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• pp.1-12
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• 2013

Climate change has increased the number of floods and inundation on farmland. Recently various mobile applications through inundation mapping, flood forecasts and evacuation routes have been developed for the prevention and reduction of flood damages. However, most of current prevention systems for farmland flooding are still web-based systems relying on the field survey which needs a lot of human and time resources although mobile devices has been rapidly improved and widely used. The purpose of this study is to design a mobile application for preventing and reducing farmland flood and inundation damages and collecting damage information in real time. We put advanced mobile device functions such as GPS, network communications, cameras into our system design. This system implement 2way communication and intuitive application that will increase information efficiency and decrease flood damage. Our design has been tested through previous flooding data of Jinju city in 2010.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.4
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• pp.487-493
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• 1998

Camera calibration is the process of determining the coordinate relationship between a camera image and its real world space. Accurate calibration of a camera is necessary for the applications that involve quantitative measurement of camera images. However, if the camera plane is parallel or near parallel to the calibration board on which 2 dimensional objects are defined(this is called "ill-conditioned"), existing solution procedures are not well applied. In this paper, we propose a neural network-based approach to camera calibration for 2D images formed by a mono-camera or a pair of cameras. Multi-layer perceptrons are developed to transform the coordinates of each image point to the world coordinates. The validity of the approach is tested with data points which cover the whole 2D space concerned. Experimental results for both mono-camera and stereo-camera cases indicate that the proposed approach is comparable to Tsai's method［8］. Especially for the stereo camera case, the approach works better than the Tsai's method as the angle between the camera optical axis and the Z-axis increases. Therefore, we believe the approach could be an alternative solution procedure for the ill -conditioned camera calibration.libration.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.2
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• pp.209-217
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• 2014

Of several approaches for future Internet, separating two properties of IP address into locator and identifier, is being considered as a highly likely solution. IETF's LISP (Locator ID Separation Protocol) is proposed for this architecture. In particular, the LISP model easily allows for device mobility through simple update of information at MS (Mapping Server) without a separate protocol. In recent years, some of the models supporting device mobility using such LISP attributes have emerged; however, most of them have the limitation for seamless mobility support due to the frequent MS information updates and the time required for the updates. In this paper, PMIPv6 (Proxy Mobile IPv6) model is applied for mobility support in LISP model. PMIPv6 is a method that can support mobility based on network without the help of device; thus, this we define anew the behavior of functional modules (LMA, MAG and MS) to fit this model to the LISP environment and present specifically procedures of device registration, data transfer, route optimization and handover. In addition, our approach improves the communication performance using three tunnels identified with locators between mobile node and corresponding node and using a route optimized tunnel between MN's MAG and CN's MAG. Finally, it allows for seamless mobility by designing a sophisticated handover procedure.

• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.21-24
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• 2001

본 논문은 신경 회로망을 이용하여, 전화망 대역의 음성, 즉, narrowband 음성에서 wideband 음성을 복원하고자 했다. BP 알고리즘을 사용하는 기존의 신경 회로망의 경우에는 음성과 같이 복잡하고 크기가 큰 훈련데이터에 대해서는 훈련이 제대로 되지 않는 단점이 있다. 그러므로 븐 논문에서는 이를 해결하기 위해 입력으로 들어온 LPC 켑스트럼 벡터를 k-means 알고리즘을 이용하여 미리 정한 개수의 cluster로 나눈 다음, 각각의 cluster에 대해 독립적인 신경 회로망을 적용했다 이로 인해 각각의 신경 회로망은 제한되고 서로 상관관계가 많은 음성들만 훈련하면 되므로, 기존의 신경 회로망에서 생기는 훈련의 정체를 개선할 수 있었다. 또 clustering 과정에서 생기는 오류를 보완하기 위해 후보신경 로망들의 출력에 fuzzy 개념을 적용해서 최종 출력을 내도록 했다 실험 결과에서, 제안한 알고리즘은 기존의 codebook mapping 알고리즘보다 스펙트럼 거리척도에 의한 비교 및 주관적인 음질 평가 양쪽에서 개선된 성능을 보였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.9
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• pp.4418-4437
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• 2017

In this paper a three-phase secure compressive sensing (CS) and received signal strength (RSS) based target localization approach is proposed to mitigate the effect of malicious node attack. RSS measurements are first arranged into a group of subsets where the same measurement can be included in multiple subsets. Intermediate target position estimates are then produced using individual subsets of RSS measurements and the CS technique. From the intermediate position estimates, the residual error vector and residual error square vector are formed. The least median of residual error square is utilized to define a verifier parameter. The selected residual error vector is utilized along with a threshold to determine whether a node or measurement is under attack. The final target positions are estimated by using only the attack-free measurements and the CS technique. Further, theoretical analysis is performed for parameter selection and computational complexity evaluation. Extensive simulation studies are carried out to demonstrate the advantage of the proposed CS-based secure localization approach over the existing algorithms.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.2
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• pp.233-237
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• 2010

The recent advance of sensor networks and ubiquitous techniques allow collecting and analyzing of the data which overcome the limitation imposed by time and space in real-time for making decisions. Also, analysis and prediction of collected data can support useful and necessary information to users. The collected data in sensor networks environment is the stream data which has continuous, unlimited and sequential properties. Because of the continuous, unlimited and large volume properties of stream data, managing stream data is difficult. And the stream data needs dynamic processing method because of the memory constraint and access limitation. Accordingly, we analyze correlation stream data using principal component analysis. And using result of analysis, it helps users for making decisions.