• Title/Summary/Keyword: production equipment

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Text Mining of Successful Casebook of Agricultural Settlement in Graduates of Korea National College of Agriculture and Fisheries - Frequency Analysis and Word Cloud of Key Words - (한국농수산대학 졸업생 영농정착 성공 사례집의 Text Mining - 주요단어의 빈도 분석 및 word cloud -)

  • Joo, J.S.;Kim, J.S.;Park, S.Y.;Song, C.Y.
    • Journal of Practical Agriculture & Fisheries Research
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    • v.20 no.2
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    • pp.57-72
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    • 2018
  • In order to extract meaningful information from the excellent farming settlement cases of young farmers published by KNCAF, we studied the key words with text mining and created a word cloud for visualization. First, in the text mining results for the entire sample, the words 'CEO', 'corporate executive', 'think', 'self', 'start', 'mind', and 'effort' are the words with high frequency among the top 50 core words. Their ability to think, judge and push ahead with themselves is a result of showing that they have ability of to be managers or managers. And it is a expression of how they manages to achieve their dream without giving up their dream. The high frequency of words such as "father" and "parent" is due to the high ratio of parents' cooperation and succession. Also 'KNCAF', 'university', 'graduation' and 'study' are the results of their high educational awareness, and 'organic farming' and 'eco-friendly' are the result of the interest in eco-friendly agriculture. In addition, words related to the 6th industry such as 'sales' and 'experience' represent their efforts to revitalize farming and fishing villages. Meanwhile, 'internet', 'blog', 'online', 'SNS', 'ICT', 'composite' and 'smart' were not included in the top 50. However, the fact that these words were extracted without omission shows that young farmers are increasingly interested in the scientificization and high-tech of agriculture and fisheries Next, as a result of grouping the top 50 key words by crop, the words 'facilities' in livestock, vegetables and aquatic crops, the words 'equipment' and 'machine' in food crops were extracted as main words. 'Eco-friendly' and 'organic' appeared in vegetable crops and food crops, and 'organic' appeared in fruit crops. The 'worm' of eco-friendly farming method appeared in the food crops, and the 'certification', which means excellent agricultural and marine products, appeared only in the fishery crops. 'Production', which is related to '6th industry', appeared in all crops, 'processing' and 'distribution' appeared in the fruit crops, and 'experience' appeared in the vegetable crops, food crops and fruit crops. To visualize the extracted words by text mining, we created a word cloud with the entire samples and each crop sample. As a result, we were able to judge the meaning of excellent practices, which are unstructured text, by character size.

Development of deep learning network based low-quality image enhancement techniques for improving foreign object detection performance (이물 객체 탐지 성능 개선을 위한 딥러닝 네트워크 기반 저품질 영상 개선 기법 개발)

  • Ki-Yeol Eom;Byeong-Seok Min
    • Journal of Internet Computing and Services
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    • v.25 no.1
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    • pp.99-107
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    • 2024
  • Along with economic growth and industrial development, there is an increasing demand for various electronic components and device production of semiconductor, SMT component, and electrical battery products. However, these products may contain foreign substances coming from manufacturing process such as iron, aluminum, plastic and so on, which could lead to serious problems or malfunctioning of the product, and fire on the electric vehicle. To solve these problems, it is necessary to determine whether there are foreign materials inside the product, and may tests have been done by means of non-destructive testing methodology such as ultrasound ot X-ray. Nevertheless, there are technical challenges and limitation in acquiring X-ray images and determining the presence of foreign materials. In particular Small-sized or low-density foreign materials may not be visible even when X-ray equipment is used, and noise can also make it difficult to detect foreign objects. Moreover, in order to meet the manufacturing speed requirement, the x-ray acquisition time should be reduced, which can result in the very low signal- to-noise ratio(SNR) lowering the foreign material detection accuracy. Therefore, in this paper, we propose a five-step approach to overcome the limitations of low resolution, which make it challenging to detect foreign substances. Firstly, global contrast of X-ray images are increased through histogram stretching methodology. Second, to strengthen the high frequency signal and local contrast, we applied local contrast enhancement technique. Third, to improve the edge clearness, Unsharp masking is applied to enhance edges, making objects more visible. Forth, the super-resolution method of the Residual Dense Block (RDB) is used for noise reduction and image enhancement. Last, the Yolov5 algorithm is employed to train and detect foreign objects after learning. Using the proposed method in this study, experimental results show an improvement of more than 10% in performance metrics such as precision compared to low-density images.

Field Survey on Pig Slurry Utilization for Crop Cultivation in the Agricultural Farm (양돈분뇨 액비를 이용한 경종농가의 작물재배 실태조사)

  • Choi, D.Y.;Noh, J.S.;Lee, S.C.;Kim, H.N.;Ahn, K.J.;Cho, I.K.
    • Journal of Animal Environmental Science
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    • v.12 no.3
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    • pp.141-150
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    • 2006
  • To optimise the efficient use of nutrients in pig slurry is to cultivate friendly environmental crops. This field survey is to investigate the actual conditions of pig slurry utilization for cultivation of crops in the agricultural farm, based on the survey for 407 selected farms in 9 provinces included 78 counties in Korea. The results obtained in this survey were summarized as follow ; The motive which came to use pig slurry in the agricultural farm were production of friendly environmental crops (29.7%), economy of chemical fertilizer (25.1%), spontaneously (19.2%), inducement of neighboring farmhouse (16.0%), increase of soil fertility (9.3%), and the others (0.7%), respectively. The proportions of pig slurry application land were 56.5% for.ice paddy, 22.6% for dry field, 13.3% for orchard, 4.4% for controlled agriculture and 3.2% for other, respectively. The number of times of pig slurry utilization per year were once (48.9%), twice (31.9%), thrice (14.0%), and the others (5.2%), respectively. The controversial points of pig slurry utilization were malodor (54.1%), insufficiency of spread equipment (22.1%), inconvenience (14.5%), over application (3.4%), over cost (2.9%), heavy metal (1.7%), sanitation (1.0%) and the other (0.2%), respectively. The results indicated that pig slurry could be used as fertilizer source of friendly environmental crops, but further studies are needed to determine the application method and value of the pig slurry for crop cultivation.

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