• International Journal of Highway Engineering
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• v.16 no.5
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• pp.91-98
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• 2014

PURPOSES : This study is to develop a automate road mapping system using ARASEO(Automated Road Analysis and Safety Evaluation TOol) for road management. METHODS : The road survey van named ARASEO(Automated Road Analysis and Safety Evaluation TOol) was used to generate highway drawings for Korea National Road number 37 automatically. In order to generate the highway drawings for purpose of road management, it is required to acquired the information for highway alignment, road width and road facilities such as safety barrier and road sign. Therefore the survey van acquired and analyzed the road width, median and guardrail data using rear side laser sensor of ARASEO and recognized the traffic control sign and chevron sign using foreside camera images. Also the highway alignment which is the basic information for highway drawing can be analyzed by acquisition the every 1m positional and attitude data using GPU and IMU sensor and developed algorithm. Finally, in this research the CAD based drawing software was developed to draw highway drawing using the analysis result from ARASEO. RESULTS : This study showed the comparison result of the surveyed road width and drawing data. To make the drawing of the road, we made the Autocad ARX program witch run in CAD menu interface. CONCLUSIONS : Using this program we can create the road center line, every 500m horizontal and vertical ground plan drawing automatically.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.521_523
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• 2009

최근 고유가에 따른 발전비용 증가와 교토의정서 발휘로 인한 $CO_2$ 저감의무 등 환경보전이라는 사회적 요구와 맞물려 새로운 신재생에너지 분야에 관심이 고조되고 있는 실정이다. 이러한 신재생에너지로 대표되는 풍력, 태양광, 연료전지 등을 이용하는 발전방식은 저용량의 발전으로 대규모 집중형 전원이 아니 전력 수요지 근방에서 설치되는 비교적 작은 규모의 분산형전원(DG;Distribution Generator)으로 배전선로에 직접 연계됨에 따라 배전계통에도 큰 변화가 일고 있다. 분산전원(DG)이 배전계통에 연계됨에 따라 전압변동에 따른 전압조정, 고조파 계통유입에 따른 전기품질, 계통고장시의 분산전원의 단독운전 방지, 고장전류의 분산에 따른 선로의 보호협조 등 다양한 새로운 문제점이 대두되고 있고 이를 해결하기 위해 연구개발 및 신기자재개발 등이 활발히 진행되고 있다. 현재 배전자동화시스템에 적용되고 있는 고장검출 알고리즘은 단방향으로 전기를 공급하던 전통적인 배전방식에서 단순 과전류요소에 의해 고장검출하는 알고리즘을 적용하고 있기 때문에 분산전원이 연계된 양방향 전기공급 배전계통에서는 정확하게 고장구간을 검출하기 어렵다. 이로 인해 고장판단 문제점과 보호기기의 오동작 등으로 정확하게 고장구간을 판단하지 못하여 광역정전이 발생되고 고장복구가 장시간 소요되고 있는 실정이다. 본 논문에서는 이를 해소하기 위해 양방향 전기공급 배전계통에서 고장이 발생시 고장점으로 유입되는 고장전류의 파형형태를 분석하여 고장 구간을 판단하는 알고리즘을 소개하고자 한다. 또한 다기능 mFRTU(mFRTUmulti-function Feeder Remote Terminal Unit) 의 고장 구간 판단 알고리즘의 신뢰성을 검증하기 위해 실선로에서 실증시험을 시행하였으며, 그 결과를 분석하여 타당성을 제시하고자 한다.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.30 no.8
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• pp.133-140
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• 2002

In this paper, the structure of integrated navigation computer for experiment is proposed. It is designed for considering the real time processing and data storage capacity. It will be used in missile, aircraft, submarine system and experimental vehicle. The I/O device supports IMU, GPS, odometer, altimeter, depth sensor, inclinometer etc. And the main storage device uses the tape device. That can improve the system stability. Therefore it can be used in a high dynamic or shock environment. The embedded linux is used as an Operating System. For the real time capability, sensor data processing and algorithm processing units are seperated. The time synchronization is referenced by IMU data.

• Journal of Korea Multimedia Society
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• v.15 no.10
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• pp.1247-1256
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• 2012

There are many filter based image processing algorithms and they usually require a huge amount of computations and memory accesses making it hard to attain a real-time performance, expecially in embedded applications. In this paper, we propose a pipelined hardware structure of the filter based face detection algorithm to show that the real time performance can be achieved by hardware design. In our design, the whole computation is divided into three pipeline stages: resizing the image (Resize), Transforming the image (ICT), and finding candidate area (Find Candidate). Each stage is optimized by considering the parallelism of the computation to reduce the number of cycles and utilizing the line memory to minimize the memory accesses. The resulting hardware uses 507 KB internal SRAM and occupies 9,039 LUTs when synthesized and configured on Xilinx Virtex5LX330 FPGA. It can operate at maximum 165MHz clock, giving the performance of 108 frame/sec, while detecting up to 20 faces.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.27-29
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• 2007

The visual implementation of 3-dimensional national environment is focused by the requirement and importance in the fields such as, national development plan, telecommunication facility deployment plan, railway construction, construction engineering, spatial city development, safety and disaster prevention engineering. The currently used DEM system using contour lines, which embodies national geographic information based on the 2-D digital maps and facility information has limitation in implementation in reproducing the 3-D spatial city. Moreover, this method often neglects the altitude of the rail way infrastructure which has narrow width and long length. There it is needed to apply laser measurement technique in the spatial target object to obtain accuracy. Currently, the LiDAR data which combines the laser measurement skill and GPS has been introduced to obtain high resolution accuracy in the altitude measurement. In this paper, we first investigate the LiDAR based researches in advanced foreign countries, then we propose data a generation scheme and an algorithm for the optimal manage and synthesis of railway facility system in our 3-D spatial terrain information. For this object, LiDAR based height data transformed to DEM, and the realtime unification of the vector via digital image mapping and raster via exactness evaluation is transformed to make it possible to trace the model of generated 3-dimensional railway model with long distance for 3D tract model generation.

• Journal of KIISE:Software and Applications
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• v.29 no.11
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• pp.818-825
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• 2002

Depth information is one of the most important factor for the recognition of a digital face image. Range images are very useful, when comparing one face with other faces, because of implicating depth information. As the processing for the whole fare produces a lot of calculations and data, face images ran be represented in terms of a vector of feature descriptors for a local area. In this paper, depth areas of a 3 dimensional(3D) face image were extracted by the contour line from some depth value. These were resampled and stored in consecutive location in feature vector using multiple feature method. A comparison between two faces was made based on their distance in the feature space, using Euclidian distance. This paper reduced the number of index data in the database and used fewer feature vectors than other methods. Proposed algorithm can be highly recognized for using local depth information and less feature vectors or the face.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.3
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• pp.558-566
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• 2015

LED, the next-generation light source, rapidly develops and has advantages of low power, high efficiency, and long life. Accordingly, an interest in lightings by using LED rises. If emotional lighting is implemented by using LED, all colors can be represented by using 3 primary colors of light, differently from the conventional single-color lighting. LED emotional lightings which can control human emotions continue to be developed thanks to these advantages. This study was conducted to design an algorithm for expressing LED emotional lighting in line with the situation and temperature by extracting colors for concentration and resting situations in indoor environment and mixing them with colors of the temperature felt by user. The LED emotional lighting designed with a neuro-fuzzy system was found to have effects on user's emotions during concentration and resting.

• The Transactions of the Korean Institute of Power Electronics
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• v.3 no.3
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• pp.214-221
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• 1998

A new control approach using neural network for the robust position control of a BRUSHLESS direct drive(BLDD) motor is presented. The linear quadratic controller plus feedforward neural network is employed to obtain the robust BLDD motor system approximately linearized using field-orientation method for an AC servo. The neural network is trained in on-line phases and this neural network is composed by a feedforward recall and error back-propagation training. Since the total number of nodes are only eight, this system will be easily realized by the general microprocessor. During the normal operation, the input-output response is sampled and the weighting value is trained by error back-propagation at each sample period to accommodate the possible variations in the parameters or load torque. And the state space analysis is performed to obtain the state feedback gains systematically. In addition, the robustness is also obtained without affecting overall system response.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.11B
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• pp.1285-1296
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• 2011

Packet classification is one of the basic and important functions of the Internet routers, and it became more important along with new emerging application programs requiring real-time transmission. Since packet classification should be accomplished in line-speed on each incoming input packet for multiple header fields, it becomes one of the challenges in designing Internet routers. Various packet classification algorithms have been proposed to provide the high-speed packet classification. Hierarchical approach achieves effective packet classification performance by significantly narrowing down the search space whenever a field lookup is completed. However, hierarchical approach involves back-tracking problem. In order to solve the problem, set-pruning trie and grid-of-trie algorithms are proposed. However, the algorithm either causes excessive node duplication or heavy pre-computation. In this paper, we propose a smart set-pruning trie which reduces the number of node duplication in the set-pruning trie by the simple merging of the lower-level tries. Simulation result shows that the proposed trie has the reduced number of copied nodes by 2-8% compared with the set-pruning trie.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1539-1544
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• 2005

The gauge control of the fishing mill is very important because more and more accurately sized hot rolled coils are demanded by customers recently. Because the mill constant and the plasticity coefficient vary with the specifications of the mill, the classification of steel, the strip width, the strip thickness and the slab temperature, the variation of these parameters should be considered in the automatic gauge control system(AGC). Generally, the AGC gain is used to minimize the effect of the uncertain parameters. In a practical field, operators set the AGC gain as a constant value calculated by FSU (Finishing-mill Set-Up model) and it is not changed during the operating time. In this paper, the thickness data signals that occupy different frequency bands are respectively extracted by adaptive filters and then the main cause of the thickness variation is analyzed. Additionally, the AGC gain is adaptively tuned to reduce this variation using the online tuning model. Especially ANFIS(Adaptive-Neuro-based Fuzzy Interface System) which unifies both fuzzy logics and neural networks, is used for this gain adjustment system because fuzzy logics use the professionals' experiences about the uncertainty and the nonlinearity of the system. Simulation is performed by using POSCO's data and the results show that proposed on-line gain adjustment algorithm has a good performance.