• 대기
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• 제24권4호
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• pp.491-502
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• 2014

As a part of the KIAPS (Korea Institute of Atmospheric Prediction Systems) Package for Observation Processing (KPOP), we have developed the modules for Advanced Microwave Sounding Unit-A (AMSU-A) pre-processing and its bias correction. The KPOP system calculates the airmass bias correction coefficients via the method of multiple linear regression in which the scan-corrected innovation and the thicknesses of 850~300, 200~50, 50~5, and 10~1 hPa are respectively used for dependent and independent variables. Among the four airmass predictors, the multicollinearity has been shown by the Variance Inflation Factor (VIF) that quantifies the severity of multicollinearity in a least square regression. To resolve the multicollinearity, we adopted simple linear regression and Principal Component Regression (PCR) to calculate the airmass bias correction coefficients and compared the results with those from the multiple linear regression. The analysis shows that the order of performances is multiple linear, principal component, and simple linear regressions. For bias correction for the AMSU-A channel 4 which is the most sensitive to the lower troposphere, the multiple linear regression with all four airmass predictors is superior to the simple linear regression with one airmass predictor of 850~300 hPa. The results of PCR with 95% accumulated variances accounted for eigenvalues showed the similar results of the multiple linear regression.

• Journal of Communications and Networks
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• 제17권4호
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• pp.351-361
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• 2015

In this paper, a new decoding scheme is proposed to improve the error correcting performance of low-density parity-check (LDPC) codes in high signal-to-noise ratio (SNR) region by using post-processing. It behaves as follows: First, a conventional LDPC decoding is applied to received LDPC codewords one by one. Then, we count the number of word errors in a predetermined number of decoded codewords. If there is no word error, nothing needs to be done and we can move to the next group of codewords with no delay. Otherwise, we perform a proper post-processing which produces a new soft-valued codeword (this will be fully explained in the main body of this paper) and then apply the conventional LDPC decoding to it again to recover the unsuccessfully decoded codewords. For the proposed decoding scheme, we adopt a simple product code structure which contains LDPC codes and simple algebraic codes as its horizontal and vertical codes, respectively. The decoding capability of the proposed decoding scheme is defined and analyzed using the parity-check matrices of vertical codes and, especially, the combined-decodability is derived for the case of single parity-check (SPC) codes and Hamming codes used as vertical codes. It is also shown that the proposed decoding scheme achieves much better error correcting capability in high SNR region with little additional decoding complexity, compared with the conventional LDPC decoding scheme.

• Journal of Information Processing Systems
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• 제11권3호
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• pp.370-388
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• 2015

The localization of multi-agents, such as people, animals, or robots, is a requirement to accomplish several tasks. Especially in the case of multi-robotic applications, localization is the process for determining the positions of robots and targets in an unknown environment. Many sensors like GPS, lasers, and cameras are utilized in the localization process. However, these sensors produce a large amount of computational resources to process complex algorithms, because the process requires environmental mapping. Currently, combination multi-robots or swarm robots and sensor networks, as mobile sensor nodes have been widely available in indoor and outdoor environments. They allow for a type of efficient global localization that demands a relatively low amount of computational resources and for the independence of specific environmental features. However, the inherent instability in the wireless signal does not allow for it to be directly used for very accurate position estimations and making difficulty associated with conducting the localization processes of swarm robotics system. Furthermore, these swarm systems are usually highly decentralized, which makes it hard to synthesize and access global maps, it can be decrease its flexibility. In this paper, a simple pyramid RAM-based Neural Network architecture is proposed to improve the localization process of mobile sensor nodes in indoor environments. Our approach uses the capabilities of learning and generalization to reduce the effect of incorrect information and increases the accuracy of the agent's position. The results show that by using simple pyramid RAM-base Neural Network approach, produces low computational resources, a fast response for processing every changing in environmental situation and mobile sensor nodes have the ability to finish several tasks especially in localization processes in real time.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 춘계학술대회
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• pp.169-171
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• 2021

자율주행, CCTV, 휴대폰 보안, 주차시설 등 카메라를 통한 이미지 처리는 실생활의 많은 문제를 해결하기 위해 사용되고 있다. 간단한 구분의 경우는 이미지 처리를 통해 해결하지만, 복잡하게 섞인 물체의 이미지 또는 이미지 내 특징을 찾아내기 어렵다. 이런 특징점 해결을 위해 사람에 가깝게 생각하고 판단할 수 있도록 영상데이터에 분류, 탐지, 분할에서 딥러닝 기술을 도입하고 있다. 물론 이미지 처리만 수행하는 것보다 결과가 좋지만, 딥러닝을 사용한 영상 분할의 방법에서 판단된 결과물이 실제 객체와 편차가 있는 것을 확인하였다. 본 논문에서는 영상 분할의 정밀도를 높이기 위해 딥러닝 영상 분할의 결과물을 출력하기 직전 간단한 이미지 처리를 통하여 정확도 향상을 수행하는 방법에 관해 연구하였다.

• Journal of Mechanical Science and Technology
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• 제18권6호
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• pp.879-894
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• 2004

The image processing technique is simple and, in principle, can handle particles with various shapes since it is based on direct visualization. Moreover, a wide measurement area can be covered with appropriate optical arrangement. In the present paper, various techniques of image processing for sizing and counting particles are reviewed and recent developments are introduced. Two major subjects are discussed in detail: identification of particles (i.e., boundary detection and pattern recognition) and determination of in-focus criteria. Finally, an overall procedure for image processing of spray particles is suggested.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2003년도 추계종합학술대회 논문집
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• pp.181-184
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• 2003

예전의 영상처리 장비는 독립적으로 구현이 되었다고 하여도 단순히 디스플레이만 하는 정도였지만 현재 여러 가지 칩들의 발전으로 인한 그 응용에 있어 활용 범위가 다양해졌다. 본 연구에서는 아날로그 영상신호를 디지털로 컨버터 하여 PC없이 독립적으로 영상 데이터를 처리하는 시스템을 설계하고, 일반 아날로그 비디오 영상의 데이터에서 모션파라미터를 추출하여 시뮬레이터에 가상의 움직임을 만들어 낸다. 모션벡터를 추출하여 시뮬레이터를 구동하고, 영상 제어 알고리즘에 대하여 분석한다.

• Journal of information and communication convergence engineering
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• 제16권3호
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• pp.160-165
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• 2018

This paper designed and developed the image processing system of integrating feature extraction and matching by using convolutional neural network (CNN), rather than relying on the simple method of processing feature extraction and matching separately in the image processing of conventional image recognition system. To implement it, the proposed system enables CNN to operate and analyze the performance of conventional image processing system. This system extracts the features of an image using CNN and then learns them by the neural network. The proposed system showed 84% accuracy of recognition. The proposed system is a model of recognizing learned images by deep learning. Therefore, it can run in batch and work easily under any platform (including embedded platform) that can read all kinds of files anytime. Also, it does not require the implementing of feature extraction algorithm and matching algorithm therefore it can save time and it is efficient. As a result, it can be widely used as an image recognition program.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2008년도 추계학술발표대회
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• pp.874-877
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• 2008

Nowadays the existing data processing systems can only support some simple query for sensor network. It is increasingly important to process the vast data streams in sensor network, and achieve effective acknowledges for users. In this paper, we propose a holistic distributed k-means algorithm for sensor network. In order to verify the effectiveness of this method, we compare it with central k-means algorithm to process the data streams in sensor network. From the evaluation experiments, we can verify that the proposed algorithm is highly capable of processing vast data stream with less computation time. This algorithm prefers to cluster the data streams at the distributed nodes, and therefore it largely reduces redundant data communications compared to the central processing algorithm.

• 정보처리학회논문지C
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• 제12C권1호
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• pp.129-136
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• 2005

웹데브(WebDAV)는 HTTP/1.1의 확장된 프로토콜로서 인터넷을 통하여 분산된 저작과 버전관리를 지원한다. 웹데브의 주요 기능인 속성관리는 저장소의 역할과 함께 자원의 추가 정보를 관리하고 활용할 수 있는 장점을 가지고 있다. 지금까지 대부분의 웹데브를 지원하는 응용 시스템은 속성 관리 기능의 활용보다는 단순 저장소의 역할로 웹데브를 사용하고 있다. 그러나 협업 지원 시스템과 같은 웹데브 기반의 고급 응용 프로그램을 개발하기 위해서는 웹데브 사용자 정의 속성의 설계와 활용이 매우 중요하다. 본 논문에서는 웹데브 사용자 정의 속성을 정의한 XML 형식의 환경 설정 속성과 그 처리 수행 절차를 기술한 DavSUDP(WebDAV Simple User-defined Property Definition Protocol) 프로토콜을 제안한다. DavSUDP는 웹데브 기반의 응용 시스템을 개발하는데 있어서 웹데브 서버가 사용자 정의 속성을 효과적으로 관리할 수 있게 하여준다. 이를 보이기 위하여 아파치의 $mod{\_}dav$ 모듈이 DavSUDP를 지원하도록 확장하였으며, 이를 이용하여 iPlace 협업 지원 시스템의 공개작업장을 개발하였다.

• 인간식물환경학회지
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• 제24권3호
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• pp.277-283
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• 2021

Background and objective: This study was conducted to increase understanding of agriculture through agricultural experience programs for adolescents living in self-reliance residence hall, and to investigate changes in work performance ability through changes in hand function. Methods: There were 11 subjects, and the average age was 18.2 years, all males without disabilities. The agricultural experience program consists of a total of 10 sessions including orientation and watching videos on future agriculture, creating vegetable gardens, planting, managing each crop, harvesting, visiting the processing room, and selling at a local food store. Results: The change in agricultural literacy by the agricultural experience program positively improved from a score of 113.73 to 127.91 (p = .008). The changes by sub-item are as follows. The value and safety of agri-foods (p = .020) and agriculture and natural environment (p = .007) were significantly improved. The function and value of rural areas (p = .050), production of agricultural products (p = .160), processing and distribution of agricultural products (p = .248), and agricultural policies (p = .058) were not significantly changed. The simple function of the hands was measured by the number of pegs inserted during 30 seconds, and the assembly function was measured by the number of pegs inserted during 60 seconds. In the case of simple function, the dominant hand was improved from 14.82 to 15.83 (p = .014), andthe non-dominant hand was also significantly improved from 13.79 to 15.01 (p = .002). There was no significant improvement in the simple function (p = .153) and assembly function (p = .770) of both hands. Conclusion: It is considered that the agricultural experience program will enable youths living in self-reliance residence halls to enhance their understanding of agriculture as an occupation, and enable them to play a role as wise consumers by positively affecting improvements in their agricultural literacy and simple hand functions.