• Title/Summary/Keyword: 분석단위

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Comparative study of Seed Productivity of Spring Sown Italian Ryegrass(Lolium multiflorum Lam.) Depending on Seeding Distance in Gangwon Highland (강원 고지대에서 봄 파종 이탈리안 라이그라스(Lolium multiflorum Lam.)의 파종 간격에 따른 종자 생산성 비교 연구)

  • Jeong, Eun Chan;Li, Yan Fen;Kim, Hak Jin;Kim, Meing Joong;Ji, Hee Chung;Kim, Jong Geun
    • Journal of The Korean Society of Grassland and Forage Science
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    • v.41 no.1
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    • pp.16-22
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    • 2021
  • This experiment was conducted to study on the growth characteristics and seed productivity of Italian ryegrass (Lolium multiflorum Lam., IRG) planted in the Spring in Gangwon Highland according to the seeding distance (20, 30 and 40 cm). The field was located in highland around 600 m above sea level. The experimental design was randomized block design with three replication and the tested IRG variety was 'Greencall' developed by National Institute of Animal Science (NIAS). IRG was sown on March 26, 2020, and harvested on July 2. The plant height was the shortest at 80.5 cm in the 40 cm seeding distance plot (P<0.05), and there was no significant difference between the 20 and 30 cm seeding distance. The number of spike per square meter (㎡) was significantly higher in the 20 cm seeding distance plot than that of 40 cm (937 vs. 571). The dry matter (DM) content of seed and straw after harvesting was 49.70 and 33.36 % on average, and there was no significant difference between treatments (P>005). However, there was a significant difference in the fresh and DM yield of seeds and straw (P<0.05). DM yield of seeds was significantly higher in 20 cm distance than that of 40 cm, and the yield of straw was the same trend. On the other hand, there was no significant difference in DM yield between 20 cm and 30 cm and also in the feed value of straw after seed harvesting among seeding distance. The average CP, ADF, NDF, and TDN contents were 6.91, 36.76, 61.75 and 59.86%, respectively, and the RFV value was 91. Considering the above results, the production of Italian ryegrass seeds sown in the spring in the highlands of the Gangwon is lower than that of autumn sowing, but it is judged that it needs to be reviewed in case it is unavoidable. In the future, there should be an economic analysis and the development of technology that can increase production.

A Comparison between the Reference Evapotranspiration Products for Croplands in Korea: Case Study of 2016-2019 (우리나라 농지의 기준증발산 격자자료 비교평가: 2016-2019년의 사례연구)

  • Kim, Seoyeon;Jeong, Yemin;Cho, Subin;Youn, Youjeong;Kim, Nari;Lee, Yangwon
    • Korean Journal of Remote Sensing
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    • v.36 no.6_1
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    • pp.1465-1483
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    • 2020
  • Evapotranspiration is a concept that includes the evaporation from soil and the transpiration from the plant leaf. It is an essential factor for monitoring water balance, drought, crop growth, and climate change. Actual evapotranspiration (AET) corresponds to the consumption of water from the land surface and the necessary amount of water for the land surface. Because the AET is derived from multiplying the crop coefficient by the reference evapotranspiration (ET0), an accurate calculation of the ET0 is required for the AET. To date, many efforts have been made for gridded ET0 to provide multiple products now. This study presents a comparison between the ET0 products such as FAO56-PM, LDAPS, PKNU-NMSC, and MODIS to find out which one is more suitable for the local-scale hydrological and agricultural applications in Korea, where the heterogeneity of the land surface is critical. In the experiment for the period between 2016 and 2019, the daily and 8-day products were compared with the in-situ observations by KMA. The analyses according to the station, year, month, and time-series showed that the PKNU-NMSC product with a successful optimization for Korea was superior to the others, yielding stable accuracy irrespective of space and time. Also, this paper showed the intrinsic characteristics of the FAO56-PM, LDAPS, and MODIS ET0 products that could be informative for other researchers.

Seed Productivity by Varieties of Italian Ryegrass(Lolium multiflorum Lam.) Sown in Spring in Gangwon Highlands (강원 고지대에서 봄 파종한 이탈리안 라이그라스(Lolium multiflorum Lam.)의 품종에 따른 종자 생산성)

  • Jeong, Eun Chan;Kim, Hak Jin;Li, Yan Fen;Kim, Meing Joong;Ji, Hee Chung;Kim, Jong Geun
    • Journal of The Korean Society of Grassland and Forage Science
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    • v.40 no.4
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    • pp.221-226
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    • 2020
  • This experiment was conducted to compare the seed productivity of the Italian ryegrass(Lolium multiflorum Lam.) varieties sown in the spring in Gangwon region. The experiment was randomized block design with three replications. The Experimental field was located in alpine areas of about 600 m above sea level in Gangwon province. The tested Italian Ryegrass varieties were 'Greenfarm', 'Greencall' and 'Kowinearly' developed by National Institute of Animal Science, RDA. Italian Ryegrass varieties were sown on March 26, 2020, and the harvest was on the 60th day of mean heading date, July 2. The heading date of Kowinearly was May 8, but Greenfarm and Greencall was May 4. The plant length was the largest in the Kowinearly variety. However, the Kowinearly suffered severe lodging. There was no significant difference in the length of spike among varieties, and the number of seeds per spike was the lowest in Greenfarm at 118.5 seed/spike. As for the seed weight per spike, the Greenfarm variety was significantly lower at 0.56 g/spike, but the 1,000 seed weight was the heaviest in the Greenfarm at 2.5g.. The number of spike per unit area was the highest in Greenfarm at 906/㎡. The dry matter content of seeds was the highest in Greenfarm at 54.3%, and for straw, Kowinearly was the highest at 35.3%. Seed productivity was not significant among varieties, and the average was 1,493 kg/ha. The yield of straw after seed production was also not significant among varieties (P>0.05), and the average was 3,172 kg/ha. From the above results, the production of Italian ryegrass seeds through spring sowing in the Gangwon region is not much than autumn seeding, requiring the input of various technologies to increase productivity in the future, and it is desirable to determine the production cost through economic analysis was judged.

Estimation of irrigation return flow from paddy fields on agricultural watersheds (농업유역의 논 관개 회귀수량 추정)

  • Kim, Ha-Young;Nam, Won-Ho;Mun, Young-Sik;An, Hyun-Uk;Kim, Jonggun;Shin, Yongchul;Do, Jong-Won;Lee, Kwang-Ya
    • Journal of Korea Water Resources Association
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    • v.55 no.1
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    • pp.1-10
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    • 2022
  • Irrigation water supplied to the paddy field is consumed in the amount of evapotranspiration, underground infiltration, and natural and artificial drainage from the paddy field. Irrigation return flow is defined as the excess of irrigation water that is not consumed by evapotranspiration and crop, and which returns to an aquifer by infiltration or drainage. The research on estimating the return flow play an important part in water circulation management of agricultural watershed. However, the return flow rate calculations are needs because the result of calculating return flow is different depending on irrigation channel water loss, analysis methods, and local characteristics. In this study, the irrigation return flow rate of agricultural watershed was estimated using the monitoring and SWMM (Storm Water Management Model) modeling from 2017 to 2020 for the Heungeop reservoir located in Wonju, Gangwon-do. SWMM modeling was performed by weather data and observation data, water of supply and drainage were estimated as the result of SWMM model analysis. The applicability of the SWMM model was verified using RMSE and R-square values. The result of analysis from 2017 to 2020, the average annual quick return flow rate was 53.1%. Based on these results, the analysis of water circulation characteristics can perform, it can be provided as basic data for integrated water management.

Construction Techniques of Earthen Fortifications in the Hanseong Period of Baekje Kingdom (백제 한성기 토성의 축조기술)

  • LEE, Hyeokhee
    • Korean Journal of Heritage: History & Science
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    • v.55 no.2
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    • pp.168-184
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    • 2022
  • This paper examined the construction techniques of the earthen fortifications in the Hanseong Period of Baekje Kingdom, which has been researched most frequently among the Three Kingdoms. The construction processes of the Earthen Fortifications were reviewed and dividing into 'selection of location and construction of the base', 'construction of the wall', and 'finish, extension and repair'. The results show that various techniques were mobilized for building these earthen fortifications. Techniques which were adequate for the topography were utilized for reinforcing the base, and several other techniques were used for constructing the wall. In particular, techniques for wall construction may be clearly divided into those of the fill(盛土) and panchuk(版築) techniques. The fill method has been assumed since the 2000s to have been more efficient than the panchuk technique. This method never uses the structure of the panchuk technique and is characterized by a complex soil layer line, an alternate fill, use of 'earth mound(土堤)'/'clay clod(土塊)', and junctions of oval fill units. The fill method allows us to understand active technological sharing and application among the embankment structures in the period of the Three Kingdoms. The panchuk technique is used to construct a wall using a stamped earthen structure. This technique is divided into types B1 and B2 according to the height, scale, and extension method of the structure. Type B1 precedes B2, which was introduced in the late Hanseong Period. Staring with the Pungnap Earthen Fortification in Seoul, the panchuk technique seems to have spread throughout South Korea. The techniques of the fill and panchuk techniques coexisted at the time when they appeared, but panchuk earthen fortifications gradually dominated. Both techniques have completely different methods for the soil layers, and they have opposite orders of construction. Accordingly, it is assumed that both have different technical systems. The construction techniques of the earthen fortifications began from the Hanseong Period of Baekje Kingdom and were handed down and developed until the Woongjin-Sabi Periods. In the process, it seems that there existed active interactions with other nations. Recently, since studies of the earthen fortifications have been increasing mainly in the southern areas, it is expected that comparative analysis with neighboring countries will be done intensively.

Qualitative Study on Experiences of Responding to COVID-19 of Therapists in Long-term Care Hospitals (요양병원 치료사의 코로나19 대응 경험에 대한 질적 연구)

  • Bae, Won-Jin;Park, Ju-Young
    • Journal of Korea Entertainment Industry Association
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    • v.15 no.4
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    • pp.337-347
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    • 2021
  • This study is a qualitative study conducted to provide basic data for therapists working in long-term care hospitals to improve their countermeasure strategies for new infectious diseases and improvement of the treatment room infection management system, and to help therapists understand their infection management work. Colaizzi's phenomenological research method was applied as the research method. Telephone interviews were conducted with nine occupational therapists and physical therapists working in nursing hospitals. The contents of the interview were recorded with the consent of the study subjects, and additional confirmation was received by email. The recorded content was analyzed after transcription, and the meaning and nature of the experience coping with COVID-19 were described. The content was organized into 6 themes, 17 main meaning and 49 meaning units. In accordance with the COVID-19 situation, the infection control system has been strengthened by reinforcing infection control education in nursing hospitals, practicing infection control, and supervising infection control outside business hours. It was found that the treatment environment was changed due to the restriction of treatment activities by practicing distancing in the treatment room, adjusting rest and meal times during working hours, and strengthening infection control. In addition, the therapist's role has been expanded and the paradigm of treatment has changed, such as considering the untact intervention, and they have experienced cohort quarantine, pre-tested for COVID-19, vaccinations, and side effects from COVID-19. However, due to the infection work, the therapist's work burden is increased, and the person is experiencing fear, depression, and work stress from the spread of COVID-19. They were also aware of the need for nursing hospital care personnel support, such as guaranteeing rest after vaccination and providing infection control tools and equipment. The results of this study are expected to be used as basic data for human and physical support for the development of infectious disease response strategy programs in nursing hospital treatment rooms and for infection control in nursing hospitals.

A study on the derivation and evaluation of flow duration curve (FDC) using deep learning with a long short-term memory (LSTM) networks and soil water assessment tool (SWAT) (LSTM Networks 딥러닝 기법과 SWAT을 이용한 유량지속곡선 도출 및 평가)

  • Choi, Jung-Ryel;An, Sung-Wook;Choi, Jin-Young;Kim, Byung-Sik
    • Journal of Korea Water Resources Association
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    • v.54 no.spc1
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    • pp.1107-1118
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    • 2021
  • Climate change brought on by global warming increased the frequency of flood and drought on the Korean Peninsula, along with the casualties and physical damage resulting therefrom. Preparation and response to these water disasters requires national-level planning for water resource management. In addition, watershed-level management of water resources requires flow duration curves (FDC) derived from continuous data based on long-term observations. Traditionally, in water resource studies, physical rainfall-runoff models are widely used to generate duration curves. However, a number of recent studies explored the use of data-based deep learning techniques for runoff prediction. Physical models produce hydraulically and hydrologically reliable results. However, these models require a high level of understanding and may also take longer to operate. On the other hand, data-based deep-learning techniques offer the benefit if less input data requirement and shorter operation time. However, the relationship between input and output data is processed in a black box, making it impossible to consider hydraulic and hydrological characteristics. This study chose one from each category. For the physical model, this study calculated long-term data without missing data using parameter calibration of the Soil Water Assessment Tool (SWAT), a physical model tested for its applicability in Korea and other countries. The data was used as training data for the Long Short-Term Memory (LSTM) data-based deep learning technique. An anlysis of the time-series data fond that, during the calibration period (2017-18), the Nash-Sutcliffe Efficiency (NSE) and the determinanation coefficient for fit comparison were high at 0.04 and 0.03, respectively, indicating that the SWAT results are superior to the LSTM results. In addition, the annual time-series data from the models were sorted in the descending order, and the resulting flow duration curves were compared with the duration curves based on the observed flow, and the NSE for the SWAT and the LSTM models were 0.95 and 0.91, respectively, and the determination coefficients were 0.96 and 0.92, respectively. The findings indicate that both models yield good performance. Even though the LSTM requires improved simulation accuracy in the low flow sections, the LSTM appears to be widely applicable to calculating flow duration curves for large basins that require longer time for model development and operation due to vast data input, and non-measured basins with insufficient input data.

Physicochemical and antioxidant properties of muffins with acai berry concentrate-loaded nanocapsules (아사이베리 농축액 함유 나노캡슐을 첨가한 머핀의 항산화 활성 및 품질 특성)

  • Park, Jae Bum;Lee, Kwang Yeon;Lee, Hyeon Gyu
    • Korean Journal of Food Science and Technology
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    • v.53 no.2
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    • pp.181-186
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    • 2021
  • In this study, the physical characteristics, antioxidant activity, and stability of muffins prepared with acai berry concentrate-loaded nanocapsules were evaluated. The size of the acai berry nanocapsules significantly increased with higher chitosan and lower Arabic gum concentrations. Based on the total phenolic content and antioxidant activity, the free acai berry concentrate showed significantly stronger antioxidant activity than that of the acai berry concentrate-loaded nanocapsules using chitosan and Arabic gum because of the entrapment of encapsulated acai berry. The physicochemical and textural properties of the muffin prepared with acai berry concentrate-loaded nanocapsules did not show notable differences compared with the control muffin. However, the stability of acai berry concentrate in terms of total phenolic content and antioxidant activity was effectively enhanced by nanoencapsulation while baking the muffin. This study suggested that acai berry concentrate-loaded nanocapsules are potential ingredients for bakery products.

Periodic Growth Monitoring and Final Age at Maturity in a Robinia pseudoacacia Stand (아까시나무 임분의 시계열적 생장 모니터링 및 벌기령 도출)

  • Jaeyeop, Kim;Sora, Kim;Jeongeun, Song;Sangmin, Sung;Jongsoo, Yim;Yeongmo, Son
    • Journal of Korean Society of Forest Science
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    • v.111 no.4
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    • pp.613-621
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    • 2022
  • The study aim was to investigate changes in the diameter, number of standing trees, stand volume per ha and site index by the forest survey order, climate zone (northern temperate, central temperate, southern temperate, and warm temperate regions), and altitude in 100 m intervals) by collecting samples of Robinia pseudoacacia from the fifth, sixth, and seventh national forest survey datasets. The rotation cutting age, which is a standard used for wood, was calculated. The changes were statistically analyzed by performing ANOVA and the Duncan multiple test. Diameter growth naturally increased according to the forest survey order and was lowest in the southern temperate region by climate zone and lowest at the 301-400 m altitude. The number of standing trees per ha did not change according to the forest survey order and altitude, and the density was highest in the central temperate region and lowest in the southern temperate region. The stand volume per ha increased according to the forest survey order, and the climate zone was divided into two groups: ① northern temperate region and central temperate region, ② southern temperate region and warm temperate region. The stand volume growth was highest at the 201-300 m point. Thesite index showed results similar to the change pattern of the stand volume per ha. The growth curve, which can be seen by the change in stand volume per ha, was estimated by applying theWeibull formula, and the stand volume per ha was estimated to reach approximately 200 m3/ha at 50-60 years. The rotation of the highest production in volume, which is the standard for using trees as wood rather than honey sources, was calculated to be 34 years.

A study on the rock mass classification in boreholes for a tunnel design using machine learning algorithms (머신러닝 기법을 활용한 터널 설계 시 시추공 내 암반분류에 관한 연구)

  • Lee, Je-Kyum;Choi, Won-Hyuk;Kim, Yangkyun;Lee, Sean Seungwon
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.23 no.6
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    • pp.469-484
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    • 2021
  • Rock mass classification results have a great influence on construction schedule and budget as well as tunnel stability in tunnel design. A total of 3,526 tunnels have been constructed in Korea and the associated techniques in tunnel design and construction have been continuously developed, however, not many studies have been performed on how to assess rock mass quality and grade more accurately. Thus, numerous cases show big differences in the results according to inspectors' experience and judgement. Hence, this study aims to suggest a more reliable rock mass classification (RMR) model using machine learning algorithms, which is surging in availability, through the analyses based on various rock and rock mass information collected from boring investigations. For this, 11 learning parameters (depth, rock type, RQD, electrical resistivity, UCS, Vp, Vs, Young's modulus, unit weight, Poisson's ratio, RMR) from 13 local tunnel cases were selected, 337 learning data sets as well as 60 test data sets were prepared, and 6 machine learning algorithms (DT, SVM, ANN, PCA & ANN, RF, XGBoost) were tested for various hyperparameters for each algorithm. The results show that the mean absolute errors in RMR value from five algorithms except Decision Tree were less than 8 and a Support Vector Machine model is the best model. The applicability of the model, established through this study, was confirmed and this prediction model can be applied for more reliable rock mass classification when additional various data is continuously cumulated.