• Journal of Bio-Environment Control
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• v.31 no.1
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• pp.1-7
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• 2022

Strawberry is a stand-out cultivating fruit in Korea. The optimum production of strawberry is highly dependent on growing environment. Smart farm technology, and automatic monitoring and control system maintain a favorable environment for strawberry growth in greenhouses, as well as play an important role to improve production. Moreover, physiological parameters of strawberry plant and it is surrounding environment may allow to give an idea on production of strawberry. Therefore, this study intends to build a machine learning model to predict strawberry's yield, cultivated in greenhouse. The environmental parameter like as temperature, humidity and CO₂ and physiological parameters such as length of leaves, number of flowers and fruits and chlorophyll content of 'Seolhyang' (widely growing strawberry cultivar in Korea) were collected from three strawberry greenhouses located in Sacheon of Gyeongsangnam-do during the period of 2019-2020. A predictive model, Lasso regression was designed and validated through 5-fold cross-validation. The current study found that performance of the Lasso regression model is good to predict the number of flowers and fruits, when the MAPE value are 0.511 and 0.488, respectively during the model validation. Overall, the present study demonstrates that using AI based regression model may be convenient for farms and agricultural companies to predict yield of crops with fewer input attributes.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.30-30
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• 2023

This study aims to establish the multi-reservoir operation system model in the Upper Mun River Basin which includes 5 main dams namely, Mun Bon (MB), Lamchae (LC), Lam Takhong (LTK), Lam Phraphoeng (LPP), and Lower Lam Chiengkrai (LLCK) Dams. The knowledge and AI technology were applied aiming to develop innovative prototype for SMART dam-reservoir operation in future. Two different sorts of reservoir operation system model namely, Fuzzy Logic (FL) and Constraint Programming (CP) as well as the development of rainfall and reservoir inflow prediction models using Machine Learning (ML) technique were made to help specify the right amount of daily reservoir releases for the Royal Irrigation Department (RID). The model could also provide the essential information particularly for the Office of National Water Resource of Thailand (ONWR) to determine the short-term and long-term water resource management plan and strengthen water security against flood and drought in this region. The simulated results of base case scenario for reservoir operation in the Upper Mun from 2008 to 2021 indicated that in the same circumstances, FL and CP models could specify the new release schemes to increase the reservoir water storages at the beginning of dry season of approximately 125.25 and 142.20 MCM per year. This means that supplying the agricultural water to farmers in dry season could be well managed. In other words, water scarcity problem could substantially be moderated at some extent in case of incapability to control the expansion of cultivated area size properly. Moreover, using AI technology to determine the new reservoir release schemes plays important role in reducing the actual volume of water shortfall in the basin although the drought situation at LTK and LLCK Dams were still existed in some periods of time. Meanwhile, considering the predicted inflow and hydrologic factors downstream of 5 main dams by FL model and minimizing the flood volume by CP model could ensure that flood risk was considerably minimized as a result of new release schemes.

• Journal of Broadcast Engineering
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• v.27 no.1
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• pp.44-55
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• 2022

In order to automatically provide information on fruits in agricultural related broadcasting contents, instance image segmentation of target fruits is required. In addition, the information on the 3D pose of the corresponding fruit may be meaningfully used. This paper represents research that provides information about tomatoes in video content. A large amount of data is required to learn the instance segmentation, but it is difficult to obtain sufficient training data. Therefore, the training data is generated through a data augmentation technique based on a small amount of real images. Compared to the result using only the real images, it is shown that the detection performance is improved as a result of learning through the synthesized image created by separating the foreground and background. As a result of learning augmented images using images created using conventional image pre-processing techniques, it was shown that higher performance was obtained than synthetic images in which foreground and background were separated. To estimate the pose from the result of object detection, a point cloud was obtained using an RGB-D camera. Then, cylinder fitting based on least square minimization is performed, and the tomato pose is estimated through the axial direction of the cylinder. We show that the results of detection, instance image segmentation, and cylinder fitting of a target object effectively through various experiments.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.209-223
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• 2024

In the context of the fourth industrial revolution, data-driven decision-making has increasingly become pivotal. However, the integrity of data analysis is compromised if data quality is not adequately ensured, potentially leading to biased interpretations. This is particularly critical for water level data, essential for water resource management, which often encounters quality issues such as missing values, spikes, and noise. This study addresses the challenge of noise-induced data quality deterioration, which complicates trend analysis and may produce anomalous outliers. To mitigate this issue, we propose a noise removal strategy employing Wavelet Transform, a technique renowned for its efficacy in signal processing and noise elimination. The advantage of Wavelet Transform lies in its operational efficiency - it reduces both time and costs as it obviates the need for acquiring the true values of collected data. This study conducted a comparative performance evaluation between our Wavelet Transform-based approach and the Denoising Autoencoder, a prominent machine learning method for noise reduction.. The findings demonstrate that the Coiflets wavelet function outperforms the Denoising Autoencoder across various metrics, including Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Mean Squared Error (MSE). The superiority of the Coiflets function suggests that selecting an appropriate wavelet function tailored to the specific application environment can effectively address data quality issues caused by noise. This study underscores the potential of Wavelet Transform as a robust tool for enhancing the quality of water level data, thereby contributing to the reliability of water resource management decisions.

• Journal of the Economic Geographical Society of Korea
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• v.8 no.1
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• pp.171-188
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• 2005

Da-san Jeong Yak-yong(정약용) was one of the notable realist in the late 18th century, the second half of Chosun Dynasty. He accentuate the need of national riches and stabilization of the public welfare through his reformat proposal on actual condition. He regarded geography as the necessary knowledge to achieve the national riches and stabilization of the people's livelihood. We can read the contents on agricultural policy and encouragement of farming in Mokminsimseo(목민심서). In Mokminsimseo(목민심서), as coverage on economic geography, he present various policy of encouragement of agriculture as device of agricultural promotion and urges governors initiative on this. On policy of encouragement of agriculture, he insisted that the farmers have side job like horticulture, sericulture and live-stock farming far their rural economy. In sum, Da-san Jeong Yak-yong regarded economic geography as a important subject under realism which aims at improving and reforming contemporary world against 주자학 oriented Confucian classics.

• Journal of Agricultural Extension & Community Development
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• v.13 no.1
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• pp.149-171
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• 2006

This is a pilot study on rural women's psychological trap to define some obstacles to self directed learning. During few decades, according to major crop of each farm household has shifted from rice to other crops like as vegetables, fruits, horticultures, livestock, etc., women's role or labor sharing of women in farming has been also increased. Although women are important human resources, till now, there is no a research or an approach to rural woman on the view of individual human being. Therefore this study will contribute to understand woman's behavior or attitudes based on psychological description at each person's experiences. For this study, the data was collected from 23 women leaders who participated in a training course in 2005, through the scale of Jeffrey E. Young & Janet S. Klosko which was developed to improvement of one's repetitious behavior based on cognitive psychological care. It was categorized into 11types of psychological trap of one person, named as follows; (1) trap of being deserted by someone (2) trap of disbelief and being ill-treated (3) trap of weakness (4) trap of dependence (5) trap of emotional deprivation (6) trap of feelings of alienation among society (7) trap of deficiency (8) trap of anxiety to failure (9) trap of subordination (10) trap of the merciless standard by self-estimation (11) trap of the sense of privilege. From the data, the average age of subjects was 52.8years old, and the educational back of subjects was higher than general rural women. In both of the trap of weakness and the trap of the merciless standard by self-estimation, the ratio of over and 4 point score of 6 points was 71.4% and 76.2%. It means most of subjects have experienced fear of unexpected calamity(trap of weakness), and mental press hard for efforts to meet one's ideal standard(trap of the merciless standard by self-estimation). Especially the trap of the merciless standard by self-estimation may have relation with rural women's over burden from farming and local society activities.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.162-162
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• 2017

구글에서 공개한 Tensorflow를 이용한 여러 학문 분야의 연구가 활발하다. 농업 시설환경을 대상으로 한 빅데이터의 축적이 증가함과 아울러 실효적인 정보 획득을 위한 각종 데이터 분석 및 마이닝 기법에 대한 연구 또한 활발한 상황이다. 한편, 타 분야의 성공적인 심층학습기법 응용사례에 비하여 농업 분야에서의 응용은 초기 성장 단계라 할 수 있다. 이는 농업 현장에서 취득한 정보의 난해성 및 완성도 높은 생육/환경 모델링 정보의 부재로 실효적인 전과정 처리 기술 도출에 소요되는 시간, 비용, 연구 환경이 상대적으로 부족하기 때문일 것이다. 특히, 센서 기반 데이터 취득 기술 증가에 따라 비약적으로 방대해진 수집 데이터를 시간 복잡도가 높은 심층 학습 모델링 연산에 기계적으로 단순 적용할 경우 시간 효율적인 측면에서 성공적인 결과 도출에 애로가 있을 것이다. 매우 높은 시간 복잡도를 해결하기 위하여 제시된 하드웨어 가속 기능의 경우 일부 개발환경에 국한이 되어 있다. 일례로, 구글의 Tensorflow는 오픈소스 기반 병렬 클러스터링 기술인 MPICH를 지원하는 알고리즘을 공개하지 않고 있다. 따라서, 본 연구에서는 심층학습 기법 연구에 있어서, 예상 가능한 다양한 자원을 활용하여 최대한 연산의 결과를 빨리 도출할 수 있는 하드웨어적인 접근 방법을 모색하였다. 호스트에서 수행하는 일방적인 학습 알고리즘과 달리 이기종간 심층 학습이 가능하기 위해선 우선, NFS(Network File System)를 이용하여 데이터 계층이 상호 연결이 되어야 한다. 이를 위해서 고속 네트워크를 기반으로 한 NFS의 이용이 필수적이다. 둘째로 제한된 자원의 한계를 극복하기 위한 메모 공유 라이브러리가 필요하다. 셋째로 이기종간 프로세서에 최적화된 병렬 처리용 컴파일러를 이용해야 한다. 가장 중요한 부분은 이기종간의 처리 능력에 따른 작업을 고르게 분배할 수 있는 작업 스케쥴링이 수행되어야 하며, 이는 처리하고자 하는 데이터의 형태에 따라 매우 가변적이므로 해당 데이터 도메인에 대한 엄밀한 사전 벤치마킹이 수행되어야 한다. 이러한 요구조건을 대부분 충족하는 Open-CL ver1.2(https://www.khronos.org/opencl/)를 이용하였다. 최신의 Open-CL 버전은 2.2이나 본 연구를 위하여 준비한 4가지 이기종 시스템에서 모두 공통적으로 지원하는 버전은 1.2이다. 실험적으로 선정된 4가지 이기종 시스템은 1) Windows 10 Pro, 2) Linux-Ubuntu 16.04.4 LTS-x86_64, 3) MAC OS X 10.11 4) Linux-Ubuntu 16.04.4 LTS-ARM Cortext-A15 이다. 비교 분석을 위하여 NVIDIA 사에서 제공하는 Pascal Titan X 2식을 SLI로 구성한 시스템을 준비하였다. 개별 시스템에서 별도로 컴파일 된 바이너리의 이름을 통일하고, 개별 시스템의 코어수를 동일하게 균등 배분하여 100 Hz의 데이터로 입력이 되는 온도 정보와 조도 정보를 입력으로 하고 이를 습도정보에 Linear Gradient Descent Optimizer를 이용하여 Epoch 10,000회의 학습을 수행하였다. 4종의 이기종에서 총 32개의 코어를 이용한 학습에서 17초 내외로 연산 수행을 마쳤으나, 비교 시스템에서는 11초 내외로 연산을 마치는 결과가 나왔다. 기보유 하드웨어의 적절한 활용이 가능한 심층학습 기법에 대한 연구를 지속할 것이다

• Journal of Agricultural Extension & Community Development
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• v.21 no.3
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• pp.271-305
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• 2014

There is an inescapable requirement in public policy to provide evidence. For the evaluation of the EU Rural Development Policy, the European Commission has designed a Common Monitoring and Evaluation Framework(CMEF). The principal objectives of evaluations are to improve decision-making, resource allocation and accountability. In Korea, howerver, the opinion-based policy by expert is still rural development evaluation system. It does not provide the objective quantitative indicators for impact of rural development project. According to this, the budget-making body (parliament, government, etc.) have questioned the effectiveness of rural development projects, rural development projects often reduced or changed. To improve the accountability of rural development policy, it is necessary to build a reliable monitoring and evaluation system based on the evidence. First, rural development evaluation indicators should be considered the multipul goal of rural development, namely economic development, social development. Second, the purpose of the evaluation is necessary to be designed for the learning rather than reward. Third, the participation by local residents should be strengthened in evaluation process. Finally, it is necessary to establish rural development monitoring and evaluation system, such as CMEF of the EU (CMEF).

• Journal of Agricultural Extension & Community Development
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• v.21 no.3
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• pp.53-89
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• 2014

Immigrant farmers work in various social and economic fields of activity, settling in their rural community. In this study, I inquired into the way of acting of immigrant farmers, based on the texts which were made in the precedent studies. The texts were transcriptions that were made by interviews with immigrant farmers. I classified immigrant farmers' activities into 8 groups that were related to; farming, nonfarm business, off-farm business, volunteering, participating in community organization, lifelong learning, leisure and social interaction in everyday life. And, I tried to capture the characteristics and meanings of those activities. The implications from this analysis are as followings: 1) most of immigrant farmers have small family farm so that they need nonfarm or off-farm jobs, 2) pluri-acivities of immigrant farm households can contribute to their community's economic viability, 3) their economic activities should be observed carefully in the perspective of self-help approach in community development as well as farm households' livelihood strategy, 4) immigrant farmers have many difficulties to participate in community, nevertheless community participation will improve the social capital, 5) gender-sensitive policy should be developed.

• Journal of Agricultural Extension & Community Development
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• v.20 no.1
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• pp.71-103
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• 2013

The purpose of this study is the awareness about the experiences of immigrant women residing in rural areas of life in Korea. Immigrant women residing in Gyeonggi Province and Incheon was a self-reported survey. Data collected by utilizing the SAS(Statistical Analysis System), percentage, mean, standard deviation, frequency analysis, including descriptive statistics were used. Findings, more than half of the migrant women are satisfied with their lives, and showed a high level of satisfaction with the husband. Learning map awareness in the education of their children in the most difficult and the necessary support to the children the basic curriculum map, Children's education as a way to solve the problem of after-school and school education activated and was the language barrier. Hard life in Korea, the language is a problem, Place discrimination received was a public place. Adapt to Korean society, language communication, child education, community adjustment problems with the same level of help was most needed. Meetings or activities often involve religious organizations, their home country, and meeting friends. His native Koreans, when it is difficult to discuss in order. Based on the results of such, Korea and community well adapted to the social framework that can nurture children married immigrant women in rural areas communities and Korean society and institutional as well prepared, and In addition, the foundation will need to activate the program.