• Journal of Institute of Control, Robotics and Systems
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• v.15 no.12
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• pp.1246-1253
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• 2009

To be high efficient for a navigation of unmanned ground vehicle, it must be able to distinguish between safe and hazardous regions in its immediate environment. We present an advanced method using laser range finder for building global 2D digital maps that include environment information. Laser range finder is used for mapping of obstacles and driving environment in the 2D laser plane. Rotary encoders are used for localization of UGV. The main contributions of this research are the development of an algorithm for global 2D map building and it will turn a UGV navigation based on map matching into a possibility. In this paper, a map building algorithm will be introduced and an assessment of algorithm reliability is judged at an each environment.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.386-386
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• 2000

Cell mapping is a powerful computational technique for analyzing the global behavior of nonlinear dynamic systems. It simplifies the task of analyzing a continuous phase space by partitioning it into a finite number of disjoint cells and approximating system trajectories as cell transitions. A cell map for the system is then constructed based on the allowable control actions. Next search algorithms are employed to identify the optimal or near-optimal sequence(s) of control actions required to drive the system from each cell to the target cell by an "unravelling algorithm." Errors resulting from the cell center-point approximation could be reduced and eliminated by fuzzifying the bonders of cells. The dynamic system control method based on the cell mapping has been demonstrated for a motor control problem.l problem.

• Journal of the Korean Society of Marine Environment & Safety
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• v.1 no.2
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• pp.39-52
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• 1995

There are numerous mapping, charting, geodetic systems and electronic digital products defined in various local geodetic datum. It becomes a straight forward requirement to simplify the complexity by referencing all the products to a common reference globally. WGS-84 is well known as a state-of-the-art global reference system based on the use of data, techniques and technology available within American Defence Mapping Agency(DMA). Its parameters can be translated into more accurate maps, charts and geodetic positioning compared to others previously. Since Global Positioning System(GPS/NAVSTAR), which is asssociated with World Geodetic System(WGS-84)in reference frame, has been widely used, the unified geodetic system has been required for GPS users in many fields.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.01a
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• pp.361-363
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• 2014

본 논문에서는 디지털 기기를 나타내는 모바일과 아날로그를 나타내는 팝업북을 통해 각 지역의 유명한 광관 명소나 지역적인 정보를 표현하는 컨텐츠를 제시하고자 한다. 팝업북 각각의 페이지에는 그 지역의 지형을 아웃라인으로 만들고 그 안의 평면에 3D로 지형을 구현한다. 사람들이 가지고 있는 모바일로 관광책자 Application을 실행한 뒤 데이터베이스에 저장된 해당 지역 데이터를 전송받아 지역 페이지로 실시간으로 바뀌게 되고 Application 안에는 명소가 있는 지역이나 건물이 담겨있어 버튼을 터치하면 그 명소가 팝업북 안에 프로젝션 맵핑으로 보여지고 그 옆에는 교통수단 및 특산품 등 다양한 정보를 담을 수 있다. 이러한 프로세스를 통한 새로운 관광 책자로 사용자들은 제한적인 정보를 담고 있는 책자를 넘어 3D로 실시간으로 볼 수 있어 더 효과적으로 여행 정보를 얻을 수 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.3981-4004
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• 2019

This paper proposes a novel method for locating objects in real space from a single remote image and measuring actual distances between them by automatic detection and perspective transformation. The dimensions of the real space are known in advance. First, the corner points of the interested region are detected from an image using deep learning. Then, based on the corner points, the region of interest (ROI) is extracted and made proportional to real space by applying warp-perspective transformation. Finally, the objects are detected and mapped to the real-world location. Removing distortion from the image using camera calibration improves the accuracy in most of the cases. The deep learning framework Darknet is used for detection, and necessary modifications are made to integrate perspective transformation, camera calibration, un-distortion, etc. Experiments are performed with two types of cameras, one with barrel and the other with pincushion distortions. The results show that the difference between calculated distances and measured on real space with measurement tapes are very small; approximately 1 cm on an average. Furthermore, automatic corner detection allows the system to be used with any type of camera that has a fixed pose or in motion; using more points significantly enhances the accuracy of real-world mapping even without camera calibration. Perspective transformation also increases the object detection efficiency by making unified sizes of all objects.

• Journal of Korean Society of Forest Science
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• v.86 no.1
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• pp.25-34
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• 1997

The optimum global natural vegetation mapping(GNVM) system was selected as a series of the study to estimate potential forest area of the globe. To select the system, three types of GNVM systems which are simple system with Light Climatic Dataset(LCD), altitude-allowed system with LCD and altitude-allowed system with Heavy Climatic Dataset(HCD) were established and compared. The three GNVM systems spherically interpolate such spotty climate data as those observed at weather stations the world over onto $1^{\circ}{\times}1^{\circ}$ grid points, product vegetation type classification, and produce a potential natural vegetation(PNV) map and a PNV area. As a result of comparison with three GNVM systems, altitude-allowed LCD system represented natural vegetation distribution better than other versions. The difference between the simple system versus the one with altitude allowance indicated that the simple version tends to over-represent the warmer climate areas and under-represent cold and hostile climate areas. In the difference between altitude-allowed versions of LCD and HCD, HCD version tended to overestimate moist climate areas and to underestimate dry climate areas.

• International Journal of Knowledge Content Development & Technology
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• v.11 no.3
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• pp.29-44
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• 2021

The study provides a quantitative and qualitative description of global research in the domain of quantum machine learning (QML) as a way to understand the status of global research in the subject at the global, national, institutional, and individual author level. The data for the study was sourced from the Scopus database for the period 1999-2020. The study analyzed global research output (1374 publications) and global citations (22434 citations) to measure research productivity and performance on metrics. In addition, the study carried out bibliometric mapping of the literature to visually represent network relationship between key countries, institutions, authors, and significant keyword in QML research. The study finds that the USA and China lead the world ranking in QML research, accounting for 32.46% and 22.56% share respectively in the global output. The top 25 global organizations and authors lead with 35.52% and 16.59% global share respectively. The study also tracks key research areas, key global players, most significant keywords, and most productive source journals. The study observes that QML research is gradually emerging as an interdisciplinary area of research in computer science, but the body of its literature that has appeared so far is very small and insignificant even though 22 years have passed since the appearance of its first publication. Certainly, QML as a research subject at present is at a nascent stage of its development.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10a
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• pp.124-140
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• 1995

The merit of fuzzy rule based systems stems from their capability of encoding qualitative knowledge of experts into quantitative rules. Recent advancement in automatic tuning or self-organization of fuzzy rules from experimental data further enhances their power, allowing the integration of the top-down encoding of knowledge with the bottom-up learning of rules. In this paper, methods of self-organizing fuzzy rules and of performing defuzzification and inference is presented based on a multi-resolution radial basis function network. The network learns an arbitrary input-output mapping from sample distribution as the union of hyper-ellipsoidal clusters of various locations, sizes and shapes. The hyper-ellipsoidal clusters, representing fuzzy rules, are self-organized based of global competition in such a way as to ensute uniform mapping errors. The cooperative interpolation among the multiple clusters associated with a mapping allows the network to perform a bidirectional many-to-many mapping, representing a particular from of defuzzification. Finally, an inference engine is constructed for the network to search for an optimal chain of rules or situation transitions under the constraint of transition feasibilities imposed by the learned mapping. Applications of the proposed network to skill acquisition are shown.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.414-419
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• 2008

3D rendering is a critical process for a movie production, advertisement, interior simulation, medical and many other fields. Recently, several effective rendering methods have been developed for the photo-realistic image generation. With a rapid performance enhancement of graphics hardware, physically based 3D rendering algorithm can now often be approximated in real-time games. However, the high quality of global illumination, required for the image generation in the 3D animation production community is a still very expensive process. In this paper, we propose a new rendering method to create photo-realistic global illumination effect efficiently by harnessing the high power of the recent GPUs. Final gathering routines in our global illumination module are accelerated by programmable graphics hardware. We also simulate physically based light transport on a ray tracing based rendering algorithm with photon mapping effectively.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.5
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• pp.555-563
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• 2009

When a mobile mapping system or a robot is equipped with only a GPS (Global Positioning System) and multiple stereo camera system, a transformation from a local camera coordinate system to GPS coordinate system is required to link camera poses and 3D data by V-SLAM (Vision based Simultaneous Localization And Mapping) to GIS data or remove the accumulation error of those camera poses. In order to satisfy the requirements, this paper proposed a novel method that calculates a camera rotation in the GPS coordinate system using the three pairs of camera positions by GPS and V-SLAM, respectively. The propose method is composed of four simple steps; 1) calculate a quaternion for two plane's normal vectors based on each three camera positions to be parallel, 2) transfer the three camera positions by V-SLAM with the calculated quaternion 3) calculate an additional quaternion for mapping the second or third point among the transferred positions to a camera position by GPS, and 4) determine a final quaternion by multiplying the two quaternions. The final quaternion can directly transfer from a local camera coordinate system to the GPS coordinate system. Additionally, an update of the 3D data of captured objects based on view angles from the object to cameras is proposed. This paper demonstrated the proposed method through a simulation and an experiment.