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박광호,이재철,윤석철,Park, K.H.,Lee, J.C.,Yun, S.C. 국립한국농수산대학교 교육개발센터 2001 현장농업연구지 = Journal of practical agricultural resear Vol.3 No.1
This research was performed to develope a stable direct seeding method in rice cultivation using by a direct seeder with soil application. A principle of this methodology was introduced from seeding nursery system of machine transplanting enable to increase high seeding establishment direct seeding method with soil application was high of 89-95% while that of water seeding was 68%. During seeding growth plant height was ralatively small but seeding health was high. A total soil consumption of this methodology was 145kg/10a in dirll seeding and 26kg/10a in hill seeding respectively, there was 100% erected in direct seeding with soil application while water seeding was 45% in erected seeding stand. In direct seeding method with soil application total carbohydrate content was higher than that of water seeding. This machine was manufactured to attach and/or detach to a machine transplanter with riding type and machine cultivator with multipurpose. In the farmer's demonstrated rice field this method was well performed like machine transplanting in terms of rice growth and development. There was highly cost reduction for rice production like other direct seeding methods.
웨이브렛 계수에 근거한 Fuzzy-ART 네트워크를 이용한 PVC 분류
박광리,이경중,이윤선,윤형로,Park, K. L,Lee, K. J.,lee, Y. S.,Yoon, H. R. 대한의용생체공학회 1999 의공학회지 Vol.20 No.4
본 연구에서는 PVC를 분류하기 위하여 웨이브렛 계수를 기반으로 하는 fuzzy-ART 네트워크를 설계하였다. 설계된 네트워크는 feature를 추출하는 부분과 fuzzy-ART 네트워크를 학습시키는 부분으로 구성된다. 우선 feature의 문턱치 구간을 설정하기 위하여 심전도 신호의 QRS를 검출하였고, 검출된 QRS는 Haar 웨이브렛을 이용한 웨이브렛 변환에 의해 주파수 분할하였다. 분할된 주파수 중에서 입력 feature를 추출하기 위하여 저주파 영역의 6번째 계수(D6)만을 선택하였다. D6신호는 입력 feature를 구성하기 위한 문턱치를 적용하여 fuzzy-ART 네트워크의 2진수 입력 feature로 전환하였고, PVC를 분류하기 위하여 fuzzy-ART네트워크를 학습시켰다. 본 연구의 성능을 평가하기 위하여 PVC가 포함된 MIT/BIH 데이터 베이스가 사용되었으며, fuzzy-ART 네트워크의 분류성능은 96.25%이었다. A fuzzy-ART(adaptive resonance theory) network for the PVC(premature ventricular contraction) classification using wavelet coefficient is designed. This network consists of the feature extraction and learning of the fuzzy-ART network. In the first step, we have detected the QRS from the ECG signal in order to set the threshold range for feature extraction and the detected QRS was divided into several frequency bands by wavelet transformation using Haar wavelet. Among the low-frequency bands, only the 6th coefficient(D6) are selected as the input feature. After that, the fuzzy-ART network for classification of the PVC is learned by using input feature which comprises of binary data converted by applying threshold to D6. The MIT/BIH database including the PVC is used for the evaluation. The designed fuzzy-ART network showed the PVC classification ratio of 96.52%.
박광호,김형석,Park, K.H.,Kim, H.S. 국립한국농수산대학교 교육개발센터 2007 현장농업연구지 = Journal of practical agricultural resear Vol.9 No.1
The special project was conducted at the cooperative farm where located at Yakjeon-ri Sukcheon-gun Pyeongannam-do, the Democratic People's Republic of Korea. This farm was firstly introduced a newly developed technology-"Bokto seeding technology" for rice cultivation from the Republic of Korea. Total acreage of rice paddy field cultivated by this technology was 800ha and the average yield was 7.17t/ha with paddy rice which was higher by 109.2% than that of the transplanting method for rice cultivation. In general rice disease was decreased at the Bokto seeded rice plant compared to the transplanted rice plant and root activity was higher in Bokto seeded rice. Optimum seeding amount was determined at rate of 90kg/ha in Pyeongdo 5(early ripening variety) and 110kg/ha at Pyeongdo 11(medium ripening variety) and Pyeongyang 43(late ripening variety), respectively. A recommended sowing time was within late April for late ripening variety like Pyeongyang 43, May 1-5 for medium ripening variety, and May 5-15 for early ripening variety.