• 한국자기학회:학술대회 개요집
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• 한국자기학회 2015년도 자성 및 자성재료 국제학술대회
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• pp.61-62
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• 2015

• 한국자기학회:학술대회 개요집
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• 한국자기학회 2016년도 자성 및 자성재료 국제학술대회
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• pp.196-196
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• 2016

• 한국자기학회:학술대회 개요집
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• 한국자기학회 2016년도 임시총회 및 하계학술연구발표회
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• pp.61-61
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• 2016

• 한국자기학회:학술대회 개요집
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• 한국자기학회 2016년도 임시총회 및 하계학술연구발표회
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• pp.62-62
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• 2016

• 한국자기학회:학술대회 개요집
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• 한국자기학회 2016년도 자성 및 자성재료 국제학술대회
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• pp.155-155
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• 2016

• 한국자기학회:학술대회 개요집
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• 한국자기학회 2016년도 자성 및 자성재료 국제학술대회
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• pp.21-21
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• 2016

• Near Infrared Analysis
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• 제2권1호
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• pp.55-58
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• 2001

The object of this work was to investigate the influence of growing district and harvest year on calibration for sweetness (Brix) determination of Fuji apple fruit using near infrared (NIR) reflectance spectroscopy, and to develop the robust calibration across these variation. The calibration models was based on wavelength range of 1100∼2500 nm using a stepwise multiple linear regression. A calibration model by sample set of one growing district was not transferable to other growing districts. The combined calibration (data of three growing districts) predicted reasonable well against a population set drawn from all growing districts (SEP=0.69, Bias=0.075). A calibration model by sample set of one harvest year was not also transferable to other harvest years. The combined calibration (data of three harvest years) predicted well against a population set drawn from all harvest years (SEP=0.53, Bias=0.004).

• 한국균학회지
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• 제44권1호
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• pp.31-35
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• 2016

큰느타리버섯 수확후배지를 재배병수의 20%(건조량으로 환산한 무게의 15%) 첨가한 결과, 배지의 물리성 및 수량성이 첨가하지 않은 배지와 큰 차이를 보이지 않았으며, 15%에 해당하는 배지재료비를 절감하여 1일 1만병 재배규모의 경우 연간 52,425천원 정도의 소득 증가 효과를 볼 수 있었다.

• 스마트미디어저널
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• 제12권10호
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• pp.9-18
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• 2023

Harvest forecasting is the great demand of multiple aspects like temperature, rain, environment, and their relations. The existing study investigates the climate conditions and aids the cultivators to know the harvest yields before planting in farms. The proposed study uses federated learning. In addition, the additional widespread techniques such as bagging classifier, extra tees classifier, linear discriminant analysis classifier, quadratic discriminant analysis classifier, stochastic gradient boosting classifier, blending models, random forest regressor, and AdaBoost are utilized together. These presented nine algorithms achieved exemplary satisfactory accuracies. The powerful contributions of proposed algorithms can create exact harvest forecasting. Ultimately, we intend to compare our study with the earlier research's results.

• Archives of Reconstructive Microsurgery
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• 제10권2호
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• pp.124-130
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• 2001

Both of latissimus dorsi and rectus abdominis muscles are workhorse for various reconstructive surgeries. These muscle flaps have been used widely for soft tissue coverage, tissue augmentation, and functional muscle transfer. However, the traditional method for muscle harvest requires a long incision that often results in an unsightly scar and becomes the main concern of the patient. The purpose of this study is to introduce our clinical experience of endoscopic harvest of latissimus dorsi muscle and rectus abdominis muscle, and to make comparison with traditional harvest of these two muscle flaps. Of the 13 rectus abdominis muscles free flaps, 6 muscles were harvested traditionally and 7 muscles were harvested with endoscopic assistance. Of the 21 latissimus dorsi muscle free flaps, 12 muscles were harvested traditionally and 9 muscles were harvested with endoscopic assistence. Follow up period was between 6 months and 24 months. The patients age ranged from 7 to 70 years old. The result revealed no statistically significant differences in the amount of intraoperative bleeding, incidence of postoperative hematoma and seroma, and the incidence of donor-site wound infection. However, patients feel less pain and start earlier and better movement after the operation with endoscopically assisted harvest. This technique is easy to learn, is safe, and can reduce substantially the donor site morbidity comparing traditional harvesting technique.