• Proceedings of the Korean Society of Plant Pathology Conference
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• 2003.10a
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• pp.108.2-109
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• 2003

The Gyeonggi-do Agricultural Research and Extension Services has developed a web-site (www.epilove.com) in collaboration with EPINET to provide information on agricultural weather and rice disease and insect pest management in Gyeonggi-do. Weather information includes near real-time weather data monitored by automated weather stations (AWS) installed at rice paddy fields of 11 Agricultural Technology Centers (ATC) in Gyeonggi-do, and weekly weather forecast by Korea Meteorological Administration (KMA). Map images of hourly air temperature and rainfall are also generated at 309m x 309m resolution using hourly data obtained from AWS installed at 191 locations by KMA. Based on near real-time weather data from 11 ATC, hourly infection risks of rice blast, sheath blight, and bacterial grain rot for individual districts are estimated by disease forecasting models, BLAST, SHBLIGHT, and GRAINROT. Users can diagnose various diseases and insects of rice and find their information in detail by browsing thumbnail images of them. A database on agrochemicals is linked to the system for disease and insect diagnosis to help users search for appropriate agrochemicals to control diseases and insect pests.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.10
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• pp.3211-3229
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• 2022

To solve the problems existing in the process of Weibo disaster rumor recognition, such as lack of corpus, poor text standardization, difficult to learn semantic information, and simple semantic features of disaster rumor text, this paper takes Sina Weibo as the data source, constructs a dataset for Weibo disaster rumor recognition, and proposes a deep learning model BERT_AT_Stacked LSTM for Weibo disaster rumor recognition. First, add adversarial disturbance to the embedding vector of each word to generate adversarial samples to enhance the features of rumor text, and carry out adversarial training to solve the problem that the text features of disaster rumors are relatively single. Second, the BERT part obtains the word-level semantic information of each Weibo text and generates a hidden vector containing sentence-level feature information. Finally, the hidden complex semantic information of poorly-regulated Weibo texts is learned using a Stacked Long Short-Term Memory (Stacked LSTM) structure. The experimental results show that, compared with other comparative models, the model in this paper has more advantages in recognizing disaster rumors on Weibo, with an F1_Socre of 97.48%, and has been tested on an open general domain dataset, with an F1_Score of 94.59%, indicating that the model has better generalization.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.147-150
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• 2008

This study refers to develop a semi-automatic extraction of agricultural land use and vegetation information using high resolution satellite images. Data of IKONOS satellite image (May 25 of 2001) and QuickBird satellite image (May 1 of 2006) which resembles with the spatial resolution and spectral characteristics of KOMPSAT3. The precise agricultural land use classification was tried using ISODATA unsupervised classification technique and the result was compared with on-screen digitizing land use accompanying with field investigation. For the extraction of vegetation information, three crops of paddy, com and red pepper were selected and the spectral characteristics were collected during each growing period using ground spectroradiometer. The vegetation indices viz. RVI, NDVI, ARVI, and SAVI for the crops were evaluated. The evaluation process is under development using the ERDAS IMAGINE Spatial Modeler Tool.

• Korean Journal of Agricultural and Forest Meteorology
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• v.6 no.2
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• pp.94-106
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• 2004

Determining those gaps in agricultural and other information to improve agrometeorological analyses for agriculture is a large task. The effective integration of appropriate data systems, including remote sensing systems, with agricultural systems modelling capability is described as a worthy outcome in this endeavour. Data issues, including those associated with data length, quality, maintenance, and archiving remain serious issues to be addressed. The role of remote sensing and geographic information systems in agrometeorology is important and is explored here. The value of simulation models to provide the synthesis for future agrometeorological requirements is further elucidated.

• Journal of Korean Society of Rural Planning
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• v.21 no.3
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• pp.33-45
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• 2015

The oversea export of agricultural-product about item and quantity has not increased recently; especially the fresh-product has a tough issue because of period of production, price large fluctuations, customs clearance, quarantine, and uncertainty about actual locality, we need the information based construction to exchange information quickly about whole range of export and to focus capacity of participation subject for increasing the export. In this study we design the agricultural-product transaction information system based on crowdsourcing to transact the agricultural-product and the information of influencing benefit directly, and the information offering about export-procedure from participation of customs clearance, finance, distribution, buyer, and producer's guild, etc. We expect the producer's guild about agriculture that has not participate the trade to be able to export the agricultural-product and the stabilization of price to transact the product of collapsed or boomed through the agricultural-product information system based on crowdsourcing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2012-2027
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• 2019

Nutritional disorders are one of the most common diseases of crops and they often result in significant loss of agricultural output. Moreover, the imbalance of nutrition element not only affects plant phenotype but also threaten to the health of consumers when the concentrations above the certain threshold. A number of disease identification systems have been proposed in recent years. Either the time consuming or accuracy is difficult to meet current production management requirements. Moreover, most of the systems are hard to be extended, only detect a few kinds of common diseases with great difference. In view of the limitation of current approaches, this paper studies the effects of different trace elements on crops and establishes identification system. Specifically, we analysis and acquire eleven types of tomato nutritional disorders images. After that, we explore training and prediction effects and significances of super resolution of identification model. Then, we use pre-trained enhanced deep super-resolution network (EDSR) model to pre-processing dataset. Finally, we design and implement of diagnosis system based on deep learning. And the final results show that the average accuracy is 81.11% and the predicted time less than 0.01 second. Compared to existing methods, our solution achieves a high accuracy with much less consuming time. At the same time, the diagnosis system has good performance in expansibility and portability.

• Journal of Industrial Convergence
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• v.21 no.9
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• pp.133-142
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• 2023

The use of digital information technology has become important in order to effectively respond to changes in production conditions in Korean agriculture, which are continuously worsening due to a decrease in the rural population, deepening aging, and climate change. Accordingly, this study analyzed the factors affecting farmers' adoption of information devices use and the effect of information devices use on agricultural product sales using the propensity score matching method. As a result of the analysis, it was found that low-age farmers, high-education farmers, and leading farmers are highly likely to adopt use of information devices. For farms with similar characteristics such as age, management size, and farming type, it has been confirmed that farms that have adopted information devices use in agricultural management have higher sales of agricultural products. Therefore, increasing farmers' access to information and the ability to use information devices provides implications that farm income can be improved. The government's informatization support project in the agricultural and rural sectors is important so that farmers can have the ability to distribute informatization devices and utilize agricultural information, and active investment should also be made in information infrastructure.

• Journal of Biosystems Engineering
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• v.29 no.6 s.107
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• pp.544-552
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• 2004

This study was conducted to suggest the efficient gathering and recycling method of disused agricultural machinery in rural environment. In order to suggest this methods, the keeping means, maintenance, disused period and kinds of agricultural machinery were investigated. The results obtained in this study were as follows : The disused agricultural machinery have been leaved on the vacant lot of a farmhouse and an around field for $2\~5\;years$. The leaving reason of the disused agricultural machinery was low interesting and gathering price for the disused agricultural machinery. The present situation for recycling method was using as a scrap iron, however to increase recycling percent the disassembling process has to divide as using and parts concretely. And the design of agricultural machinery was considered the easiness of a disassemble and assemble the agricultural machinery. To manage and supply efficiently for the second-hand parts of agricultural machinery need to the establishment of circulation information center and internet site for the parts.

• Agribusiness and Information Management
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• v.1 no.1
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• pp.3-18
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• 2009

This research aims to examine consumers' general types of information search and their unsatisfactory factors in purchasing agricultural products on electronic commerce and analyze consumers' behavioral characteristics. As study subjects, 802 consumers who have visited the home pages of 14 households or companies, whose home pages are actively managed, were sampled. As a research tool, pop-up post and e-mail were used as research tools and questionnaires were asked three times. The date on research result were analyzed using SPSS 13 statistics package in terms of frequency, percentage, descriptive statistics, one-way ANOVA and correlation analysis.

• Journal of Korean Society of Rural Planning
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• v.16 no.1
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• pp.9-20
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• 2010

The aim of this paper is to identify Korean agricultural and agri-manufacturing cluster using a multi-regional input-output model. This paper derives a representative set of five agricultural and agri-manufacturing clusters in Korea in terms of spatial and industrial interdependency. The results show that agriculture and agri-manufacturing clusters agglomerated in Seoul Metropolitan Area and Chungcheong Area are linked both production and manufacture functions, whereas Gangwon Area is more focused on production and Jeolla Area is more concentrated on manufacture.