• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.952-955
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• 1996

It is difficult to determine the feeding rate of coagulant in water treatment process, due to nonlinearity, multivariables and slow response characteristics etc. To deal with this difficulty, the fusion of genetic algorithms and fuzzy inference system was used in determining of feeding rate of coagulant. The genetic algorithms are excellently robust in complex operation problems, since it uses randomized operators and searches for the best chromosome without auxiliary information from a population consists of codings of parameter set. To apply this algorithms, we made the look up table and membership function from the actual operation data of water treatment process. We determined optimum dosages of coagulant (PAC, LAS etc.) by the fuzzy operation, and compared it with the feeding rate of the actual operation data.

• 한국전자통신학회논문지
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• 제19권1호
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• pp.189-196
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• 2024

지능형 선별 관제 시스템의 잦은 오탐지로 인해 관제 요원들의 업무 능률 및 시장 신뢰도 저하 문제가 꾸준히 보고되고 있다. 오탐지 문제 개선을 위해 새 AI 모델을 개발하거나 교체하는 것은 기회비용이 크므로, 훈련 데이터 세트 품질을 향상하여 문제를 개선하는 것이 현실적이다. 그러나 소규모 조직은 데이터 세트 수집 및 정제 역량이 부족한 실정이다. 이에 본 논문에서는 사람 자세 추정 모델을 중심으로 엣지 디바이스와 카메라 센서 퓨전을 활용한 사람 자세 데이터 자동 수집 시스템을 제안한다. 이 시스템은 네트워크 말단에서 현장 데이터를 직접 수집하고 레이블링하는 과정을 실시간으로 처리하도록 만들어, 중앙으로 집중되는 연산 부하를 분산시킨다. 또한 현장 데이터를 직접 레이블링하므로 새로운 훈련 데이터 구축에 도움을 준다.

• 한국정밀공학회지
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• 제28권9호
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• pp.1040-1047
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• 2011

This paper proposes a novel method based on error back propagation neural networks to fuse laser sensor data and ultrasonic sensor data for enhancing the accuracy of mapping. For navigation of single robot, the robot has to know its initial position and accurate environment information around it. However, due to the inherent properties of sensors, each sensor has its own advantages and drawbacks. In our system, the robot equipped with seven ultrasonic sensors and a laser sensor navigates to map two different corridor environments. The experimental results show the effectiveness of the heterogeneous sensor fusion using an error backpropagation algorithm for mapping.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1791-1796
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• 2004

Recently, great improvements have been made in developing autonomous underwater vehicles (AUVs) using stateof- the-art technologies for various kinds of sophisticated underwater missions. To meet increasing demands posed on AUVs, a powerful on-board computer system and an accurate sensor system with an well-organized control system architecture are needed. In this paper, a new control system architecture is proposed for AUV, ORCA (Oceanic Reinforced Cruising Agent) which is being currently developed by Korea Research Institute of Ships and Ocean Engineering (KRISO). The proposed architecture uses a hybrid architecture that combines a hierarchical architecture and a behavior based control architecture with an evaluator for coordinating between the architectures. This paper also proposed a sensor fusion structure based on the definition of 4 categories of sensors called grouping and 5-step data processing procedure. The development of the AUV, ORCA involving the system architecture, vehicle layout, and hardware configuration of on-board system are described.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 제13회 신호처리 합동 학술대회 논문집
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• pp.915-918
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• 2000

In this paper, we propose an efficient feature vector extraction and decision fusion methods for the automatic classification of power system disturbances. Here, FFT and WPT(wavelet packet transform) are und to extract an appropriate feature for classifying power quality disturbances with variable properties. In particular, the WPT can be utilized to develop an adaptable feature extraction algorithm using best basis selection. Furthermore. the extracted feature vectors are applied as input to the decision fusion system which combines the decisions of several classifiers having complementary performances, leading to improvement of the classification performance. Finally, the applicability of the proposed approach is demonstrated using some simulations results obtained by analyzing power quality disturbances data generated by using Matlab.

• 천문학회지
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• 제42권6호
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• pp.155-159
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• 2009

In order to determine color excess in the $uvby\beta$ color system for high amplitude $\delta$ Scuti stars, reddening free $[m_1]$, $[c_1]$, and $\beta$ indices data were obtained from the existing literature for 21 stars. Then, the three intrinsic relations of $(b-y)_0$ - $[m_1]$, $(b-y)_0$ - $[c_1]$, and $(b-y)_0$ - $\beta$ were investigated. Among these, it was shown that the $(b-y)_0$-$[c_1]$ relation is the most useful. By establishing intrinsic $(b-y)_0$-$[c_1]$ relations for six reddening calibration stars, color excesses of other stars were determined.

• 한국해양공학회지
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• 제11권3호
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• pp.170-179
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• 1997

This paper presents a hybrid navigation system for AUV to locate its position precisely in rough sea. The tracking system is composed of various sensors such as an inclinometer, a tri-axis magnetometer, a flow meter, and a super short baseline(SSBL) acoustic position tracking system. Due to the inaccuracy of the attitude sensors, the heading sensor and the flowmeter, the predicted position slowly drifts and the estimation error of position becomes larger. On the other hand, the measured position is liable to change abruptly due to the corrupted data of the SSBL system in the case of low signal to noise ratio or large ship motions. By introducing a sensor fusion technique with the position data of the SSBL system and those of the attitude heading flowmeter reference system (AHFRS), the hybrid navigation system updates the three-dimensional position robustly. A Kalman filter algorithm is derived on the basis of the error models for the flowmeter dynamics with the use of the external measurement from the SSBL. A failure detection algorithm decides the confidence degree of external measurement signals by using a fuzzy inference. Simulation is included to demonstrate the validity of the hybrid navigation system.

• 대한원격탐사학회지
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• 제33권2호
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• pp.149-158
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• 2017

시간해상도와 공간해상도가 높은 영상 자료는 효과적인 식생의 모니터링을 위해서 필수적이다. 하지만 단일 센서를 통한 영상은 공간해상도와 시간해상도가 높은 자료를 동시에 제공할 수 없는 한계점이 있다. 최근에는 위성영상의 공간적 해상도를 높이고 시간해상도를 보완하기 위해서 시공간 융합연구가 진행되고 있다. 그 중에서도 FSDAF(Flexible spatiotemporal data fusion) 방법론은 위성영상의 각 밴드를 융합하는 방법으로 적절한 것으로 나타났다. 본 연구에서는 FSDAF 융합기법을 활용하여 MODIS NDVI와 Landsat 영상으로 계산한 NDVI를 융합 후 검증을 실시하였으며 식생 계절 모니터링에서의 활용가능성을 제시하였다. 그 결과, 1월부터 12월까지 융합을 통해 NDVI 예측한 영상은 활엽수, 침엽수, 농지의 계절적인 특징을 잘 반영하고 있었다. 융합된 결과의 검증을 위하여 8월과 10월의 예측한 NDVI와 실제 값(Landsat NDVI) 간의 RMSE 값을 계산한 결과 각각 0.049와 0.085, 상관계수는 0.765, 0.642로 비교적 일치한 것으로 나타났다. 본 연구에서 활용된 FSDAF 시공간 융합 기법은 픽셀기반의 융합기법으로 다양한 공간스케일의 영상과도 융합 가능할 것이며 다양한 식생 관련 연구에 활용될 것으로 기대된다.

• International Journal of Internet, Broadcasting and Communication
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• 제12권4호
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• pp.11-17
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• 2020

This paper proposed the design of a new window signage system architecture, which utilized a window of a building, with attached LED for visible light communication. In this paper, the proposed method using the LED strip to transmit light data and receive the data through a HMD with a smart device camera. The LED strip attached to the existing building window, as a part of semi-transparent signage. Semi-transparent signage based on a controllable LED strip-modules and attached to the window used to provide entertainment contents and the information service to people through optical camera communication (OCC) as well. Also, this work suggests using the camera supplied Head Mounted Device (HMD) as an OCC receiver. The LED attached window signage system structure described in this paper can be utilized in various buildings infrastructure like house, shopping areas, industrial building, etc.

• Journal of Information Processing Systems
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• 제17권3호
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• pp.462-472
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• 2021

With an increase in the scale of recommender systems, users' rating data tend to be extremely sparse. Some methods have been utilized to alleviate this problem; nevertheless, it has not been satisfactorily solved yet. Therefore, we propose an effective pre-rating method based on users' dichotomous preferences and average ratings fusion. First, based on a user-item ratings matrix, a new user-item preference matrix was constructed to analyze and model user preferences. The items were then divided into two categories based on a parameterized dynamic threshold. The missing ratings for items that the user was not interested in were directly filled with the lowest user rating; otherwise, fusion ratings were utilized to fill the missing ratings. Further, an optimized parameter λ was introduced to adjust their weights. Finally, we verified our method on a standard dataset. The experimental results show that our method can effectively reduce the prediction error and improve the recommendation quality. As for its application, our method is effective, but not complicated.