• Journal of Mushroom
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• v.16 no.2
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• pp.111-117
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• 2018

This study was conducted to compare the composition and antioxidant activity of 1- and 2-year-old Poria cocos Wolf cultivated at a mortuary and cemetery. An elemental analyzer test showed oxygen, carbon, hydrogen, nitrogen, and sulfur to be present at concentrations of 45~46%, 39~41%, 6.06~6.1%, 0.21~0.22%, and 0%, respectively. No differences in composition were observed among samples. Eleven minerals (S, Ca, Mg, P, As, Se, Cu, Fe, Pb, Zn, and Cd) found in P. cocos cultivated at the mortuary and cemetery were analyzed by inductively coupled plasma mass spectrometry (ICP). The levels of S, Fe, Mg, and Zn in P. cocos were higher in cemetery-cultivated samples than in mortuary-cultivated samples. A 1,1-diphenyl-2-picrylhydrazyl (DPPH) assay for antioxidant activity revealed half-maximal inhibitory concentration ($IC_{50}$)values of P. cocos to be 8.601 mg/mL (mortuary, 1 year old), 12.85 mg/mL (cemetery, 1 year old), 1.23 mg/mL (mortuary, 2 years old), and 1.18 mg/mL (landfill, 1 year old). A 2,2'-azino-bis-3-ethylbenzothiazoline-6-sulfonic acid (ABTS) assay revealed $IC_{50}$ values of 15.85 mg/mL (mortuary, 1 year old),14.59 mg/mL(cemetery, 1 year old), 3.9 mg/mL (mortuary, 2 years old), and 14.92 mg/mL (cemetery, 1 year old). The results showed a concentration-dependent effect. Two-year-old mortuary-cultivated P. cocos had the highest antioxidant activity among samples. Ultrastructure analysis with a field emission scanning electron microscope (FE-SEM) showed no obvious differences among samples.

• Journal of Bio-Environment Control
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• v.9 no.4
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• pp.207-211
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• 2000

This study was conducted to investigate the effect of soil zone temperature on the growth responses of two grapevine varieties. Campbell Early was cultivated under unprotected environment and Black Olympia was cultivated in the greenhouse. As responses, growth, photosynthetic rate and contents of mineral elements as affected by four different soil zone temperatures (10, 15, 20, and $25^{\circ}C$)were examined. Weights of leaves, stems and roots were higher at 20 and $25^{\circ}C$ than at 10 or 15$^{\circ}C$ root zone temperature in both varieties. Chlorophyll concentration and photosynthetic rate were the greatest at 2$0^{\circ}C$ root zone temperature. Contents of phosphate, potassium, and calcium increased with increasing root zone temperature.

• KIISE Transactions on Computing Practices
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• v.20 no.11
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• pp.586-591
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• 2014

In recent years, we can access to video contents anywhere and at any time. Therefore distributed video is easily copied, transformed and republished. Since it brings copyright problem, similarity/duplicate detection and measurement is essential to identify the excessive content duplication. In this paper, we analysed various discernment of video which has been transformed with various ways using MPEG-7 Video Signature. MPEG-7 Video Signature, one of video copy detection algorithms, is block based abstraction. Thus we assume Video Signature is weak for spatial transform. The experiments show that MPEG-7 Video Signature is very weak for spatial transform which could occur general as we have assumed.

• Journal of the Korean Society for information Management
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• v.28 no.1
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• pp.69-88
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• 2011

The idea behind Open Source Software(OSS) that permits users to study, change, and improve, is similar to the spirit of the library that has been developed through cooperations and resource sharing rather than competition. OSS is regarded as an alternative, low-cost technical innovation based on librarian's creative idea and standardized business process. Enthusiasm of the community is fundamental to successful installations and sustainable development. This study analyzed two community-based OSS ILS, namely KOHA and Next_L and suggested a future direction for domestic libraries. In the case of Korea, it is desirable for a library consortium to develop an OSS ILS for small- and medium-sized libraries. Most importantly, strong consensus about OSS ILS among the practiting librarians should be developed first.

• Annual Conference of KIPS
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• 2018.10a
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• pp.561-564
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• 2018

최근 빠르게 발생하는 빅데이터 스트림이 다양한 분야에서 활용되고 있다. 이러한 빅데이터 전체를 수집하고 처리하는 것은 매우 비경제적이므로, 데이터 스트림 중 필요한 데이터를 걸러내는 필터링 과정이 필요하다. 본 논문에서는 아파치 스톰(Apache Storm)을 사용하여 데이터 스트림의 질의 필터링 시스템을 구축한다. 스톰은 대용량 데이터 스트림을 처리하기 위한 실시간 분산 병렬 처리 프레임워크이다. 하지만, 스톰은 입력 데이터 구조나 알고리즘 변경 시, 코드의 수정과 재배포, 재시작 등이 필요하다. 따라서, 본 논문에서는 이 같은 문제를 해결하기 위해 아파치 카프카(Apache Kafka)를 사용하여 데이터 수집 모듈과 스톰의 처리 모듈을 분리함으로써 시스템의 가용성을 크게 높인다. 또한, 시스템을 웹 기반 클라이언트-서버 모델로 구현하여 사용자가 언제 어디에서든 질의 필터링 시스템을 사용할 수 있게 하며, 웹 클라이언트를 통해 입력한 질의를 자동적 분석하는 쿼리 파서를 구현하여 별도의 프로그램의 수정 없이 질의 필터링을 적용할 수 있다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.6A
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• pp.185-190
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• 2008

The devices for the digital home in ubiquitous environment aim at providing multimedia services which are not limited to the time and space. However, it does not ensure the fair use of digital contents and causes damage to the contents providers because of indiscriminate distribution of digital contents and the use of illegal contents. DRM system for solving this problems cannot protect the license stored on digital home devices and manage license by redistribution of contents. In this paper, digital forensic model that enables the misuse detection and previous interception of large-scale illegal distribution for contents and license, and also enables the creation and management of digital evidence for legal countermeasure.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.53-53
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• 2017

연구목적: 국내 과일 산업의 한 단계 도약과 대외 경쟁력을 높이기 위해서는 수확작업의 기계화가 시급함. 이 연구는 국내외 과일 수확 기계화 현황과 문제점을 분석하고, 향후 수확작업 기계화 방향을 제시하고자 수행 수확기계 실용화 현황 및 고찰 (국내) 과일을 직접 수확이 아닌 수확 작업을 보조해주는 고지 작업기(수동형, 모터 진동형)와 고소 작업차가 대부분임. 수동형은 사과 감 등을 수확하지만, 작업능률이 낮고 작업자가 쉽게 피로하여 장시간 작업이 불가능하므로 실질적인 대안이 되지 못함. 진동형은 자체 동력을 이용하여 나무에 진동을 가하여 주로 대추 매실 등 소과류 수확에 이용되고, 수확능률은 우수하나 충격 손상이 많아 개선이 요구됨. 고소작업차는 동력원에 따라 충전식과 엔진식으로 구분되고, 충전식은 엔진식에 비해 진동 소음이 적어 쾌적하지만, 작업시간이 배터리 용량에 제한을 받음. 또한 작업대 작동방식에 따라 리프트형과 붐형으로 구분함. 리프트형은 리프트를 이용하여 작업대를 상하로 구동하는 방식으로 높은 위치의 과실 수확이 어렵고, 작업대 넓이 만큼의 작업 공간(과수간의 거리)이 필요함. 붐형은 필요한 곳으로 접근성이 우수하나 무거운 무게를 지탱하기 어렵기 때문에 본체를 무겁게 하거나 수시로 수확된 과일을 하차시켜야 함. (국외) 수확 후 가공되는 과일류와 포도 올리브 오렌지 매실 등 소과류 수확이 기계화되었지만, 사과 복숭아 등 신선과일은 아직도 외국의 값싼 노동자들에 의존하여 수확되고 있음. 현재 실용화된 수확 기계는 진동식 수확기계와 터널식 수확기계가 대표적임. 진동식은 집게형의 부착기를 나무 줄기에 고정한 후 트랙터 동력원으로 나무에 진동을 가하여 수확하고, 올리브 대추 등과 같은 소과류와 과피가 두꺼운 오렌지 등에 적용되고, 수확 작업능률이 매우 높으나 과일의 낙하 상처를 피할 수 없는 단점이 있음. 터널형은 규격화(과수 크기 및 형태, 재식거리)된 과수원에 잘 적응하도록 설계 제작되어, 과수 위를 지나가면서 내부에 설치된 진동장치와 컨테이너로 과일을 수확하고, 와인용 포도 수확기가 대표적임. 기계수확이 가능하도록 과수원 조성단계에서부터 재배양식(과수 좌우 및 전후 거리)을 기계의 제원(바퀴 간격, 작업부 간격 등)에 맞추어 재배함. 과일 수확로봇에 관한 연구는 활발하고 일부에서 실증시험단계에 있음. 결론: 구체적인 추진방향을 제시하면, 단기적으로는 과일 수확작업자의 작업편이성과 노동강도를 줄일 수 있도록 소형 저가 범용성이 우수한 보조기구/기계의 보급을 확대하고, 중장기적으로는 수확기계/수확로봇 개발을 위한 연구개발비 투자를 늘리는 동시에, 기계/로봇이 과수원에 잘 적응할 수 있도록 수형 재식거리 등 재배양식의 표준화가 추진되어야 함.

• The Korean Journal of Pesticide Science
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• v.16 no.4
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• pp.395-400
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• 2012

In order to survey the actual pesticide usage, this survey was carried out on the growers of 3 plant groups, fruit vegetables, fruits and rice field, from 2009 to 2011. 390 farmers were selected from main production areas to investigate their pesticide application during the growing seasons. Input amounts per area of domestic fruit vegetables was surveyed as 11.6 kg a.i./ha for red pepper of field culture, 2.0 kg a.i./ha for red pepper of greenhouse, 2.3 kg a.i./ha for strawberry, 2.2 kg a.i./ha for watermelon, 4.8 kg a.i./ha for cucumber, 1.5 kg a.i./ha for oriental melon and 2.1 kg a.i./ha for tomato, respectively. Input amounts per area on fruits and on rice field were surveyed as 11.7 kg a.i./ha for apple, 12.5 kg a.i./ha for pear, 7.7 kg a.i./ha for peach, 4.5 kg a.i./ha for grape, 40.0 kg a.i./ha for citrus 5.4 kg a.i./ha for persimmon, and 3.46 kg a.i./ha for rice, respectively. As a result of the actual pesticide usage survey, The safety guideline for pesticide use is generally kept well by all farmers of fruits vegetables, fruits and rice.

• Journal of Practical Agriculture & Fisheries Research
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• v.23 no.2
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• pp.87-97
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• 2021

To investigate the current pest management status in Korea, a survey was conducted from 151 students and graduates in the Korea National College of Agriculture and Fisheries (KNCAF) by on-line. The questionnaire consists of two divisions, basic questions and pest control questions. The basic questions were including the respondent's age, academic status, cultivating crops and cultivating area. The pest control questions were including pest control methods, pesticide selection rationale, and pest forecasting methods. As a summary of basic questions, the respondents in their 20s accounted for 91.2%. Moreover, 34.5% of the respondents had over 3 hectares of cultivating area. The cultivating methods were differed by cultivating crops. As a summary of pest control questions, major control methods were using the conventional chemicals (>66%). To understand the pesticide selection rationale, farmers/respondents made their own decisions based on existing control techniques (30%) or depended on the decisions of pesticide vendors (29%). As for the pest forecasting method, it was mainly conducted by the Rural Development Administration affiliated organization (29%) and the National Crop Pest Management System (27%). Regarding the reliability of the pest diagnosis and pesticide prescription of pesticide vendors, 97% of the respondents marked above average. However, there was no choice on strong reliability. Interestingly, 79% of the respondents agreed to train experts for pest diagnosis and pesticide prescription with high necessity and, in particular, 47% of respondents were very strongly supported. These results suggest that the farmers might be need more qualified experts in pest diagnosis and pesticide prescriptions. Taken together, these survey results would provide important information to understand the current status of pest management by farmers' point of view and useful to set the direction of pest control.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.823-833
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• 2020

In order to stably produce crops, there is an increasing demand for effective crop monitoring techniques in domestic agricultural areas. In this manuscript, a cultivation area extraction method by using deep learning model is developed, and then, applied to satellite imagery. Training dataset for crop cultivation areas were generated using RapidEye satellite images that include blue, green, red, red-edge, and NIR bands useful for vegetation and environmental analysis, and using this, we tried to estimate the crop cultivation area of onion and garlic by deep learning model. In order to training the model, atmospheric-corrected RapidEye satellite images were used, and then, a deep learning model using FC-DenseNet, which is one of the representative deep learning models for semantic segmentation, was created. The final crop cultivation area was determined as object-based data through combination with cadastral maps. As a result of the experiment, it was confirmed that the FC-DenseNet model learned using atmospheric-corrected training data can effectively detect crop cultivation areas.