This study was carried out to investigate the proper wattage and installation distance for the efficient use of nano-carbon fiber infrared heating lamp (NCFIHL), a heating device advantageous for heating energy saving, when the production of watermelon plug seedlings in the plug seedling nursery in winter season. Six small beds were divided into plastic film, and 700 W and 900 W nano-carbon fiber infrared heating lamps were installed at 100 cm above the bed. 1 lamp at central (control), 60 cm interval (2 lamps), and 40 cm interval (3 lamps) heating lamps were installed in each bed inside the greenhouse. All treatments, except the control, were set to keep the night air temperature at 20℃ after lighting the NCFIHL. The leaf temperature showed a tendency to increase fast as the install distance was narrow. The leaf length and leaf width tended to increase as the installation distance of the 700 W heating lamp was narrow. The compactness was high in 700 W heating lamp with 40 cm of installation distance. Therefore, in consideration of maintaining the set temperature at night, installing 700 W electric lamps at 40 cm was an efficient power and installation distance for watermelon grafted seedlings considering economic feasibility.

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.

This study aimed to analyze causality of climatic factors that affecting the yield of whole crop barley (WCB) by constructing a network within the natural ecosystem via the structural equation model. The WCB dataset (n=316) consisted of data on the forage information and climatic information. The forage information was collected from numerous experimental reports from New Cultivars of Winter Crops (1993-2012) and included details of fresh and dry matter yield, and the year and location of cultivation. The climatic information included details of the daily mean temperature, precipitation, and sunshine duration from the weather information system of the Korea Meteorological Administration. The variables were growing days, accumulated temperature, precipitation, and sunshine duration in the season for the period of seeding to harvesting. The data was collected over 3 consecutive seasons—autumn, winter, and the following spring. We created a causality network depicting the effect of climatic factors on production by structural equation modeling. The results highlight: (i) the differences in the longitudinal effects between autumn and next spring, (ii) the factors that directly affect WCB production, and (iii) the indirect effects by certain factors, via two or more paths. For instance, the indirect effect of precipitation on WCB production in the following spring season via its effect on temperature was remarkable. Based on absolute values, the importance of WCB production in decreasing order was: the following spring temperature (0.45), autumn temperature (0.35), wintering (-0.16), and following spring precipitation (0.04). Therefore, we conclude that other climatic factors indirectly affect production through the final pathway, temperature and growing days in the next spring, in the climate-production network for WCB including temperature, growing days, precipitation and sunshine duration.

본 연구에서는 겉보리를 고체 기질로 사용하여 액체발효(LSF)와 고 체발효(SSF)를 수행하였으며, 또한 겉보리의 발아(germination) 에 따른 SSF 및 A. oryzae NIBRFGC000501965와 A. pullulans KCCM60122의 혼합발효를 통해 효소 및 β-glucan 생산에 대한 고체발효 연구를 수행하였다. 이러한 연구결과들은 기존의 고체발 효법에서 효소 및 β-glucan 생산에 있어 효율적인 발효공정의 기 초자료로 유용한 정보를 제공할 것으로 판단된다.

전남지역의 완도, 진도, 해남을 대상으로 난대상록활엽수림 복원 시 붉가시나무 종실 공급과 묘목 양성에 대한 정보 필요성에 따라 붉가시나무의 종실 생산량 및 종실 형질 특성을 조사 분석하였다. 조사 분석을 위해 표면적 1㎡의 종자 트랩을 10개(완도 8개, 해남 1개, 진도 1개) 방형구에 방형구 당 3개씩 총 30개를 설치하였다. 2013년부터 2016년 까지 매년 8월에서 12월까지 매월 말 종자 트랩 내로 낙하한 종실을 수거하였으며, 낙하 종실을 수거해 건전, 충해, 부후, 쭉정이 등으로 구분 후 종실 생산량을 산정하였다. 건전 종실의 경우 각두를 제거한 종실의 길이, 지름, 무게 등 종실 형질을 측정하였다. 조사한 종실 생산량 및 종실 형질은 연별, 임분별, 월별, 처리구별 등을 연평균 값 비교분석 을 위해 Duncan의 다중검정 등을 실시하였다. 각 방형구 내 종자 트랩 낙하 종실량은 2013년에 5~350립/3㎡, 2014년에 17~551립/3㎡, 2015년에 5~454립/3㎡, 2016년에 14~705립/3㎡로 방형구 간에 차이가 큰 것으로 나타났으며, 이는 방형구내 임목 밀도 등으로 인한 수광량의 유입차로 추정진다. 전체 연도별 종실 생산량을 ha당 산정한 결과 각각 2013년에 335,000립, 2014년에 932,000립, 2015년에 556,000립, 2016년에 1,037,000립이었으며, 2년을 주기로 다소 차이가 나타났다. 종실 생산량 증감은 임분 간 동시성을 보여 붉가시나무는 임목 개체 간 결실 풍흉 및 결실 시기의 주기성이 뚜렷한 것으로 판단된다. 9월에 가장 많은 종실이 낙하하였으나 충해종실의 피해 또한 많은 것으로 나타나 종실의 조기 낙하를 방제한다면 결실 기간을 높여 충실 종실의 대량생산이 가능할 것으로 판단된다. 지역별 연평균 종실 길이의 경우 유의성이 없었으며, 종실 지름과 종실 무게의 경우 해남 종실이 완도, 진도 종실에 비해 유의적으로 평균값이 높게 나타났다. 월별 연평균 종실 형질은 유의적 차이는 보이지 않았으며, 11월의 연평균 종실 길이, 지름, 무게가 각각 19.72㎜, 12.23㎜, 1.64g으로 8월~11월 중 최대치를 보였다.

Agrobacterium tumefaciens strain CP4 유래 5-enolpyruvylshikimate- 3-phosphate synthase (EPSPS) 유전자를 포함하는 유전자변형생물체 (Living modified organism, LMO)가 개발되었다. 이 같은 LMO는 국내 승인되어 사료용, 식품용, 가공용으로 이용 중이다. 간이면역 검사키트 개발을 위해서는 고효율의 단클론 항체 개발이 필수적이다. 본 연구에서는 대장균 BL21 (DE3)에서 재조합 CP4 EPSPS 단백질을 정제하였으며 SDS-PAGE와 MALDI-TOF MS 분석으로 단백질 특성을 분석하였다. 단클론 항체 제작은 ㈜앱 클론의 SOP 매뉴얼에 따라 진행하였다. 본 연구 결과 5개의 단클론 항체 클론 (2F2, 4B9, 6C11, 10A9, 10G9)를 확보하였다. 5종의 단클론 항체의 효율과 특이도 검정을 위해서 LM 면화 추출액을 이용한 western blotting 분석을 실시하였다. 모든 단클론 항체는 CP4 EPSPS를 함유하는 MON1445와 MON88913을 특이적으로 검출하였으며 비변형 면화 및 타종의 LM 면화에서는 검출되지 않았다. 이러한 결과들을 바탕으로 CP4 EPSPS 단클론 항체는 LMO 에 함유된 CP4 EPSPS 단백질을 타겟으로 항체 기반 검출법 개발에 활용될 것으로 사료된다.

리그닌 분해효소의 생산은 나선형 리본이 있는 새로운 형태의 회전식 통풍관 생물 반응기(RTB)를 사용하여 느타리(Pleurotus ostreatus) No.42에 의해 실시하였다. 락게 이즈(laccase)의 최대 생산량은 배양 3일 후 약 8,200 U/ bioreactor 수준에 도달한 후 감소하였다. 반면에, 망간퍼 옥시데이즈(MnP)의 최대 생산은 6일 배양 후 약 8,400 U/bioreactor의 수준에 도달하였다. 그러나 이 발효조에서 리그닌퍼옥시데이즈(LiP)는 검출되지 않았다. 그 결과 회전식 통풍관 생물 반응기(RTB)가 리그닌 분해효소를 대규모 생산을 위해 성공적으로 생산할 수 있음을 보여주었다. 이 발효기에서 망간퍼옥시데이즈의 정제 과정은 Sepharose CL-6B, Superdex 75 prep grade 및 Mono-Q에 대한 크로마토그래피를 포함하여 정제하였다. 이 주요 효소는 sodium dodecyl sulfate-polyacrylamide 겔 전기영동(SDS-PAGE)에서 분자량 36,400, pI 3.95의 등전점(IEF)으로 각각 확인되었다. 이 발효기의 주요 효소 N-말단 서열은 정치 및 진탕배양과 같은 다른 배양조건에서 보고된 MnP3 효소와 동일하였다.

본 연구는 기계학습을 통한 수량예측모델을 이용하여 이상기상에 따른 WCM의 DMY 피해량을 산출하기 위한 목적으로 수행하였다. 수량예측모델은 WCM 데이터 및 기상 데이터를 수집 후 가공하여 8가지 기계학습을 통해 제작하였으며 실험지역은 경기도로 선정하였다. 수량예측모델은 기계학습 기법 중 정확성이 가장 높은 DeepCrossing (R2=0.5442, RMSE=0.1769) 기법을 통해 제작하였다. 피해량은 정상기상 및 이상기상의 DMY 예측값 간 차이로 산출하였다. 정상기상에서 WCM의 DMY 예측값은 지역에 따라 차이가 있으나 15,003~17,517 kg/ha 범위로 나타났다. 이상기온, 이상강수량 및 이상풍속에서 WCM의 DMY 예측 값은 지역 및 각 이상기상 수준에 따라 차이가 있었으며 각각 14,947~17,571 kg/ha, 14,986~17,525 kg/ha 및 14,920~17,557 kg/ha 범위로 나타났다. 이상기온, 이상강수량 및 이상풍속에서 WCM의 피해량은 각각 –68~89 kg/ha, -17~17 kg/ha 및 – 112~121 kg/ha 범위로 피해로 판단할 수 없는 수준이었다. WCM의 정확한 피해량을 산출하기 위해서는 수량예측모델에 이용하는 이상기상 데이터 수의 증가가 필요하다.

본 실험은 Holstein 비육후기에 홍삼박, 광물질 및 설탕을 첨 가 급여하여 건물채식량, 일당증체량, 육질특성 및 경제성에 미치는 영향을 조사하고자 수행하였다. 시험구는 4처리로서 홍삼박, 광물질 및 흑설탕을 급여하지 않는 처리구를 대조구(C), 홍삼박 200g 첨가 급여 구는 T1, 홍삼박 100g과 광물질 50g 첨가 급여구는 T2 그리고 광물질 50g과 흑설탕 20g 첨가 급여한 구를 T3 로 나누어 실시하였다. 그리고 본 실험에서 얻어진 결과를 요약해 보면 다음과 같다. 총 사료섭취량 및 1일 채식량은 T2 및 T3구가 C구에 비하여 유의적으로 높게 나타났다(p<0.05). 또한 채식량 이 많았던 T2 및 T3구에서 총 증체량 및 일당 증체량이 높게 나 타났지만 유의적인 차이는 없었다. 사료 요구율은 C구가 다른 구 (T1, T2, T3)에 비하여 유의적으로 높게 나타났지만(p<0.05), T1, T2 및 T3 구간에는 유의적인 차이가 없었다. 등지방두께, 등심단 면적 및 육량등급은 처리구 상호간 유의적인 차이가 없었다. 근내 지방은 T3(4.5) > T1(4.0) > T2(2.7) > C(2.5)구순으로 높게 나타났다(p<0.05). 그러나 육색, 지방색, 조직감 및 성숙도는 상호 처리 간 유의적인 차이가 없었다. 육질등급은 상호 처리 간 유의적인 차이는 보이지 않았지만 T3 > T1 > T2 > C 순으로 높은 경향을 보였다. 경제적 조수익성은 T3 > T1 > T2 > C구순으로 나타 났다. 이상의 결과를 종합해 볼 때, 배합사료와 조사료 만 급여하는 체계(C) 보다는 홍삼박, 광물질 및 흑설탕을 첨가 급여(T1,T2, T3)하는 체계가 도체등급 및 수익성 증대에 유리하며, 특히 증체량, 육질등급 및 경제성을 고려하였을 때 T3구가 가장 좋은 급여체계로 나타났다.

Today’s manufacturers must respond quickly to customer needs. In particular, make-to-order companies are constantly striving to satisfy customer demand for products in order to secure more favorable conditions in the future through bidding. In this bidding process, quotations play a very important role in providing favorable conditions. And the most important content that companies strive to satisfy their customers is the product's performance. Therefore, a company can attract customers and secure economic profits through good quotations, but it can be said that the first priority is to match the performance of the products requested by the customers. That is, when a company creates a quotation, it is important to structure the quotation according to the performance of the product. Thus, this paper intends to present a quotation management framework and a quotation BOM information model for constructing quotations efficiently in make-to-order manufacturing. And, in order to prove the usefulness of the proposed quotation management framework, we presents an case of the construction of an quotation management system based on the JAVA platform. As a result, the integrated quotation management system based on the proposed quotation management framework and quotation BOM has been successfully operated in a make-to-order company that manufactures marine engines.

This study investigated whether there is a correlation between the occurrence of hazardous substances such as vibrio, norovirus, radioactivity, shellfish posion, hepatitis A, etc. and media reports, and whether the occurrence of hazardous substances and media reports affect the production, distribution and consumption of aquatic products. The main research results are as follows. First, it can be seen that there is a difference in the relationship between the occurrence of hazardous substances and media reports according to hazardous substances. Second, it suggests seen that the occurrence of hazardous substances and media reports can have a negative effect on the production and the prices of aquatic products. Third, it was found that the occurrence and reporting of hazardous substances had different effects on the distribution margin of aquatic products due to the complexity and rigidity of the distribution structure. Fourth, consumers feel a threat to aquatic products safety and significantly reduce consumption when hazardous substances occur. There is a possibility that concerns about one item may lead to a decrease in consumption of domestic and imported aquatic products that are not related at all to the occurrence of hazardous substances. In conclusion, aquatic products are exposed to various hazardous substances such as vibrio, norovirus, radioactivity, shellfish posion, and hepatitis A. It was found that the occurrence of hazardous substances and its media reports could cause damage to the fishery sector.

This study analyzed product conditions in terms of “size system,” “clothing construction depending on fit,” “details,” “colors,” and “prices,” with an emphasis on young contemporary brands for spring/summer 2021, in order to provide basic data for the development of small-sized women’s jackets. Out of 96 domestic and foreign brands, the study analyzed 254 small-sized jacket products from 23 brands that produce size-XS jackets. First, when examining the sizes for women’s jackets, we found that 8 out of the 23 brands offer a size-XXS option. After conducting tree analysis to analyze the factors affecting the production of size-XXS, the study found significant results in the areas of “distinction between domestic and foreign brands” and “product price.” Second, after categorizing small-sized women’s jackets into 3 categories— fit-slim, basic, and straight—the study analyzed clothing construction elements depending on fit. This seasons mainly feature straight-fit’s hip-line length jacket, a 4-panel pattern, and a panel without a waist dart. Third, the study, through the analysis of the colors of small-sized women’s jackets, found a higher frequency of colors in the order of black (23.0%), white (13.3%), and beige tones (10.1%), with additional colors such as sky blue, rose pink, and aquamarine in production, which exhibit the senses of the seasons. Price analysis revealed that small-sized jackets constituted a price range at the mid-to-low end, as in ₩50,000-100,000 (30.3%), ₩100,000- 150,000 (19.3%), and ₩150,000-200,000 (11.8%).

In this study, the sales status of female ball-jointed dolls and their parts were investigated and analyzed. Baseline data from 194 products and 54 brands on domestic and international Internet sites was gathered for the manufacture of ball-jointed dolls and the development of prototype costumes for them. The results are as follows. First, the sizes used for ball-jointed dolls are SD, USD, MSD, 13SD, and 70SD together with height. This study analyzed 39 sizes (15~70cm) by classifying them into numbered groups: 1 (15~22cm), 2 (23~33cm), 3 (35~51cm), 4 (53~62cm), and 5 (63~70cm). The price varied depending on the size; for example, 50cm dolls were approximately 45,000 won, while limited editions were sold at high prices, regardless of their size. They were classified into designs according to their body proportions and facial features as follows: 7- or 8-head-figure, 5-head figure, and 3-head figure, and were presented proportionally as images of women, adolescents, and infants. Second, the head was incised so that the top could be removed horizontally or the facial region vertically, allowing attachment of the eyeballs (which were either glass, resin, or acrylic) to the inside. More than 30 different colors were sold. Various wig styles were provided, including cut, short hair, and perm. These were made from human hair, heat-resistant fiber, and artificial hair. For the hands, there was a design expressing human hand gestures. For the feet, heels were in the form of wearing either high-heels or flat soles.

본 연구는 이탈리안 라이그라스를 벼 입모중 파종 후 벼 수확시기에 따른 이탈리안 라이그라스 극조생종 품종 ‘그린팜’ 의 생육특성 및 생산성을 평가하기 위해 중부지역에 위치한 천안에서 2011–2012, 2012–2013 및 2013–2014까지 3년간 수행하였다. 1. 국내육성 이탈리안 라이그라스 극조생종 ‘그린팜’을 3년 간 9월 하순에 파종 후 10일(처리 1), 20일(처리2) 및 30일(처리 3) 간격으로 3회에 나누어 벼를 수확해서 재배하였을 때, 벼 수확시기가 늦어질수록 월동 전 분얼수, 초장, 월동율 및 건물수량은 감소하는 것으로 나타났다. 2. 월동 전 분얼수는 처리 1에 비해 처리 2 및 3의 평균이 각각 32% 및 52% 감소하는 것으로 나타났다. 3. 벼 수확 지연에 따른 월동율의 경우 처리 1에 비해 처리 2 및 3은 두 처리구 모두 평균 8% 감소하였으며, 건물수량은 각각 평균 32% 및 52% 감소하였다. 4. 벼 입모중 이탈리안 라이그라스 파종 재배시험에서 출수기는 매년 다르게 나타났으며, 봄철 이탈리안 라이그라스 수확 시 초장의 차이는 유의성이 있는 차이를 보이지 않았다. 5. 논에서 입모중 파종으로 극종생 이탈리안 라이그라스 품종 그린팜을 재배할 때는 파종 후 가능한 한 빨리 벼를 수확하여 생산성을 높이는 것이 방법임을 시사한다.

In the era of the 4th industrial revolution driven by the convergence of ICT(information and communication technology) and manufacturing, research on smart factories is being actively conducted. In particular, the manufacturing industry prefers smart factories that autonomously connect and analyze data. For the efficient implementation of smart factories, it is essential to have an integrated production system that vertically integrates separately operated production equipment and heterogeneous S/W systems such as ERP, MES. In addition, it is necessary to double-verify production data by using automatic data collection technology so that the production process can be traced transparently. In this study, we want to show a case of data-centered integration of a large aircraft parts processing factory that requires high precision, takes a long time, and has the characteristics of processing large raw materials. For this, the components of the data-oriented integrated production system were identified and the connection structure between them was explained. And we would like to share the experience gained through the design and implementation case. The integrated production system proposed in this study integrates internal components based on data, which is expected to serve as a basis for SMEs to develop into an advanced stage, and traces materials with RFID technology.

This article suggests the machine learning model, i.e., classifier, for predicting the production quality of free-machining 303-series stainless steel(STS303) small rolling wire rods according to the operating condition of the manufacturing process. For the development of the classifier, manufacturing data for 37 operating variables were collected from the manufacturing execution system(MES) of Company S, and the 12 types of derived variables were generated based on literature review and interviews with field experts. This research was performed with data preprocessing, exploratory data analysis, feature selection, machine learning modeling, and the evaluation of alternative models. In the preprocessing stage, missing values and outliers are removed, and oversampling using SMOTE(Synthetic oversampling technique) to resolve data imbalance. Features are selected by variable importance of LASSO(Least absolute shrinkage and selection operator) regression, extreme gradient boosting(XGBoost), and random forest models. Finally, logistic regression, support vector machine(SVM), random forest, and XGBoost are developed as a classifier to predict the adequate or defective products with new operating conditions. The optimal hyper-parameters for each model are investigated by the grid search and random search methods based on k-fold cross-validation. As a result of the experiment, XGBoost showed relatively high predictive performance compared to other models with an accuracy of 0.9929, specificity of 0.9372, F1-score of 0.9963, and logarithmic loss of 0.0209. The classifier developed in this study is expected to improve productivity by enabling effective management of the manufacturing process for the STS303 small rolling wire rods.

In this paper, a GAN-based data augmentation method is proposed for topology optimization. In machine learning techniques, a total amount of dataset determines the accuracy and robustness of the trained neural network architectures, especially, supervised learning networks. Because the insufficient data tends to lead to overfitting or underfitting of the architectures, a data augmentation method is need to increase the amount of data for reducing overfitting when training a machine learning model. In this study, the Ganerative Adversarial Network (GAN) is used to augment the topology optimization dataset. The produced dataset has been compared with the original dataset.