• 한국산학기술학회논문지
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• 제19권5호
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• pp.563-569
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• 2018

본 논문은 아두이노를 기반으로 윈도우 팜 수경재배를 자동으로 모니터링하는 시스템의 구현에 관한 논문으로 4차산업혁명의 아이콘으로 떠오르고 있는 아두이노의 오픈소스를 활용한다. 창문형 수경재배를 의미하는 윈도우 땅은 도시에서의 바쁜 일상에서 벗어나 식물을 재배하고 싶은 사람들의 욕망을 채울 수 있는 대안으로 제시되고 있다. 본 논문에서 제안한 시스템은 아두이노 우노 보드와 4채널 모터쉴드, 그리고 온습도, 조도센서, 리얼타임 클럭모듈을 이용하여 창문형 수경재배 환경을 실시간으로 자동 모니터링하는 시스템을 개발하였다. 수경재배를 위한 모듈은 다양한 형태로 발전되어 왔으나 대부분 일반천원과 모터 등을 활용하기 때문에 전력사용량이 높다. 그리고 자동으로 모니터링 하는 시스템이 아니기 때문에 관리자가 늘 시스템의 동작상태를 관리해야 하는 단점이 있다. 본 시스템은 IOT 센서로 활용되고 있는 온습도, 조도센서를 활용하여 식물의 생장환경에 가장 적절한 물공급 체계를 갖추고 있다. 또한 리얼타임 클럭모듈을 이용하여 계절과 시간에 맞는 물공급을 조절할 수 있다. 그리고 본 시스템은 라즈베리파이3와 아두이노 우노를 이용하여 Linux환경에서 스케치 코프로 구현하였다.

• 한국농공학회지
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• 제16권2호
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• pp.3395-3409
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• 1974

The purpose of this study is to test and compare the efficiency of heating-system for materials and construction of the wall, ceiling and window in soil brick house, cement house and boulder house respectively, in order to construct ideal farm houses in rural area. The results obtained were as follows: 1. In heat conservation due to construction of walls the thermal efficiency of cement brick house was equivalent to 66.3% of that of soil brick house, and boulder house 60.3% 2. In the case of ceiling, the thermal efficiency of paper ceiling was amounted to 84.2% of that of the composite ceiling (thickness 6mm veneer+thickness. l0m chaffs), and the common ceiling putting on soil above the ceiling, 76% of the composite while the efficiency of the ceiling putting on chaffs above them was 15.8% higher than that of the paper. 3. In the case of improving the window, the double type was 12% higher than. the efficiency of single type. 4. The warming velocity of conventional house was slower but the velocity of radiation was quicker than that of experimental one. It was thought to be due to unscietific constructions of the room bottom, fire inlet and chimney, 5. The temperature gradient line was not dependad upon the amount of throwing into fuel in the rural farm house. 6. It was concluded that the final thermal efficiency of the conventional farm house was 10.6% lower than that of experimental farm house.

• 인간식물환경학회지
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• 제23권6호
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• pp.655-665
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• 2020

Background and objective: This study was conducted to compare the cultivation environment, growth of cut flowers, and management performance of conventional farms and smart farms growing the standard cut chrysanthemum, 'Jinba'. Methods: Conventional and smart farms were selected, and facility information, cultivation environment, cut flower growth, and management performance were investigated. Results: The conventional and smart farms were located in Muan, Jeollanam-do, and conventional farming involved cultivating with soil culture in a plastic greenhouse, while the smart farm was cultivating with hydroponics in a plastic greenhouse. The conventional farm did not have sensors for environmental measurement such as light intensity and temperature and pH and EC sensors for fertigation, and all systems, including roof window, side window, thermal screen, and shading curtain, were operated manually. On the other hand, the smart farm was equipped with sensors for measuring the environment and nutrient solution, and was automatically controlled. The day and night mean temperatures, relative humidity, and solar radiation in the facilities of the conventional and the smart farm were managed similarly. But in the floral differentiation stage, the floral differentiation was delayed, as the night temperature of conventional farm was managed as low as 17.7℃ which was lower than smart farm. Accordingly, the harvest of cut flowers by the conventional farm was delayed to 35 days later than that of the smart farm. Also, soil moisture and EC of the conventional farm were unnecessarily kept higher than those of the smart farm in the early growth stage, and then were maintained relatively low during the period after floral differentiation, when a lot of water and nutrients were required. Therefore, growth of cut flower, cut flower length, number of leaves, flower diameter, and weight were poorer in the conventional farm than in the smart farm. In terms of management performance, yield and sales price were 10% and 38% higher for the smart farm than for the conventional farm, respectively. Also, the net income was 2,298 thousand won more for the smart farm than for the conventional farm. Conclusion: It was suggested that the improved growth of cut flowers and high management performance of the smart farm were due to precise environment management for growth by the automatic control and sensor.

• 전기전자학회논문지
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• 제22권1호
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• pp.53-60
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• 2018

지속적인 IoT의 발전으로 인한 스마트팜 보급은 고령화와 일손부족 현상이 지속되고 있는 우리나라 농촌의 해결책으로 부각되고 있다. 이에 현재 스마트팜의 보급은 지속적으로 증가하고 있다. 스마트팜은 사람을 대신하여 온도, 습도, 이산화탄소, 그리고 날씨와 같이 작물 재배를 위한 환경을 모니터링하고 제어한다. 특히 작물을 재배함에 있어서 온도를 제어하는 것은 매우 중요하다. 온도를 제어하기 위해 스마트팜 내에서는 에어컨, 팬과 같이 온도를 제어할 수 있는 기기가 널리 사용되고 있다. 하지만 이러한 기기들은 전력소모가 심해 생산비의 증가를 초래한다. 본 논문은 인공지능을 이용하여 스마트팜 빅데이터를 학습하고 1시간후의 비닐하우스 최적온도를 예측하고 창문을 이용해 온도를 제어함으로써 다른 온도제어기기들보다 전력을 절약할 수 있는 전력절약형 스마트팜 시스템을 제시한다. 본 논문에서 연구한 방법을 이용한 시뮬레이션을 통해 기존에 사용하는 팬보다 특정 조건 하에서 83%전력소모가 절약될 수 있다는 것을 확인하였다.

• 농촌계획
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• 제25권1호
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• pp.21-38
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• 2019

Korean agricultural industry has weakened as demand for domestic agricultural products has declined due to accelerating market liberalization, aging and shrinking of rural population, and stagnating rural households' incomes. On the other hand, as the forth industrial revolution unfolds in earnest, tremendous changes are expected, and those changes won't be confined to certain industries but would shaken the world we know of entirely. Smart farm, which is one example of the fourth industrial revolution, is increasingly being recognized as a new growth engine for the future as smart farm and the science and technology behind it, not the size of arable land, will determine competitiveness of the agricultural industry and drive agricultural productivity and managerial efficiency. In consideration that John W. Kingdon's Multiple Streams Framework has recently been presented as an important theoretical model in the policy field, this study analyzed problem stream, policy stream, and political stream in the process of forming the smart farm policy, and looked into what role the government played as policy entrepreneur in policy window. The smart farm policy was put on policy agenda by the government and was approved when the government announced the Smart Farm Plan together with relevant ministries at the 5th Economy-Related Ministers' Meeting held in April 2018. This suggests that change of the government is the most critical factor in political stream, and explicitly indicates the importance of politics in formation of an agricultural policy. In addition, actual outcome of the policy and how policy alternatives that will enhance people's understanding will support it seem to be the key to success. It also shows that it is important that policy alternatives be determined based on sufficient discussion amongst stakeholders.

• 한국수산과학회지
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• 제28권3호
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• pp.309-315
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• 1995

This paper describes a monitoring system for fish farm formation effect based on personal computer by using an image processing technique. This method is based on image processing technique incorporating concept of window and threshold processing to track the target object and to distinguish it from background. The image processing program runs in the veal time so that all program modules are able to process multi-task. The effectiveness is evaluated through the comparative study on the motion of lantern net for the scallop culturing by wave action in an experimental wave tank.

• 한국해안·해양공학회논문집
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• 제27권5호
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• pp.358-363
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• 2015

서남해 해상풍력 실증단지 건설의 기초단계로 실증단지 예정부지에서 해상작업가능시간을 산정하고 분석하였다. 활용 자료로는 해모수 기상타워의 해양 및 기상자료와 기상청 수치모델 자료이다. 해상작업이 가능한 파고와 풍속 기준을 선정하고 기준별 작업시간을 산정한 결과 계절적으로는 고파랑이 지나가는 겨울의 작업시간이 봄, 가을보다 적은 것으로 나타났고 여름의 경우 작업시간이 가장 많은 것으로 나타났다. 그러나 월별로는 7,9월보다 5,6,8월에 가장 많은 작업시간이 나타났다. 그리고 파고1.5 m와 풍속 8 m/s 이상의 기상조건에서는 파고와 풍속이 증가하더라도 작업시간은 크게 변하지 않는 것을 확인할 수 있었다.

• 품질경영학회지
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• 제49권4호
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• pp.569-579
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• 2021

Purpose: The purpose of this study is the time series analysis for predicting the yield of crops applicable to each farm using environmental variables measured by smart farms cultivating tomato. In addition, it is intended to confirm the influence of environmental variables using a deep learning model that can be explained to some extent. Methods: A time series analysis was performed to predict production using environmental variables measured at 75 smart farms cultivating tomato in two periods. An LSTM-based encoder-decoder model was used for cases of several farms with similar length. In particular, Dual Attention Mechanism was applied to use environmental variables as exogenous variables and to confirm their influence. Results: As a result of the analysis, Dual Attention LSTM with a window size of 12 weeks showed the best predictive power. It was verified that the environmental variables has a similar effect on prediction through wieghtss extracted from the prediction model, and it was also verified that the previous time point has a greater effect than the time point close to the prediction point. Conclusion: It is expected that it will be possible to attempt various crops as a model that can be explained by supplementing the shortcomings of general deep learning model.

• 한국통신학회논문지
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• 제25권8A호
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• pp.1115-1123
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• 2000

현재 대부분의 웹 프락시 또는 웹 캐쉬는 대규모 기관을 중심으로 사용되고 있다 하지만 인터넷을 사용하는 이용자 현화을 보면 오히려 대규모 조직에 속하는 이용자보다는 벤처나 PC 방과 같은 소규모 기관에 속해 있는 경우가 많다. 소규모 기관들은 사용 망 및 시스템의 용량 제한으로 인해 필요로하는 웹 문서를 원활히 제공받지 못하고 있다 또한 상용자들은 여러 윈도우를 열어놓고 다양한 종류의 URL에 접속하고 있으며 비교적 짧은 시간내에 또 다른 URL로 바꾸어 가면서 사용하고 실정이다. 본 논문에서는 근접한 지역에 위치하면서 특성이 유사한 소규모집단을 연결하는 웹캐쉬 구성 방안과 동일한 캐쉬용량으로도 적중률이 높고 웹 문서 사용자들이 요구하는 URL이 급격히 바뀌어도 적중률 저하를 차단할 수 있는 캐쉬알고리즘을 제시한다 제안 알고리즘은 요청된 URL이 속한 네트워크 경로에 따라 웹 문서 사용 특성을 분류하고 서로다른 경로에 속하는 웹문서를 서로 다른 저장 장소에 캐쉬를 하는 형태이다 제안 알고리즘을 실제 사이트에 적용하여 얻은 실험 결과를 분석하여 보면 적은 비용으로 기존 알고리즘보다 적중률 및 응답 시간 면에서 현저\ulcorner게 뛰어남을 알수 있다.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1154-1154
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• 2001

Near infra-red (NIR) spectroscopy has been used for the non-invasive assessment of intact fruit for eating quality attributes such as total soluble solids (TSS) content. However, little information is available in the literature with respect to the robustness of such calibration models validated against independent populations (however, see Peiris et al. 1998 and Guthrie et al. 1998). Many studies report ‘prediction’ statistics in which the calibration and prediction sets are subsets of the same population (e. g. a three year calibration validated against a set from the same population, Peiris et al. 1998; calibration and validation subsets of the same initial population, Guthrie and Walsh 1997 and McGlone and Kawano 1998). In this study, a calibration was developed across 84 melon fruit (R$^2$= 0.86$^{\circ}$Brix, SECV = 0.38$^{\circ}$Brix), which predicted well on fruit excluded from the calibration set but taken from the same population (n = 24, SEP = 0.38$^{\circ}$Brix with 0.1$^{\circ}$Brix bias), relative to an independent group (same variety and farm but different harvest date) (n = 24, SEP= 0.66$^{\circ}$ Brix with 0.1$^{\circ}$Brix bias). Prediction on a different variety, different growing district and time was worse (n = 24, SEP = 1.2$^{\circ}$Brix with 0.9$^{\circ}$Brix bias). Using an ‘in-line’ unit based on a silicon diode array spectrometer, as described in Walsh et al. (2000), we collected spectra from fruit populations covering different varieties, growing districts and time. The calibration procedure was optimized in terms of spectral window, derivative function and scatter correction. Performance of a calibration across new populations of fruit (different varieties, growing districts and harvest date) is reported. Various calibration sample selection techniques (primarily based on Mahalanobis distances), were trialled to structure the calibration population to improve robustness of prediction on independent sets. Optimization of calibration population structure (using the ISI protocols of neighbourhood and global distances) resulted in the elimination of over 50% of the initial data set. The use of the ISI Local Calibration routine was also investigated.