• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.4
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• pp.327-339
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• 2020

Transpiration is the movement of water into the atmosphere through leaf stomata of plant, and it accounts for more than half of evapotranspiration from the land surface. The measurements of transpiration could be conducted in various ways including eddy covariance and water balance method etc. However, the transpiration measurements of individual trees are necessary to quantify and compare the water use of each species and individual component within stands. For the measurement of the transpiration by individual tree, the thermometric methods such as heat dissipation and heat pulse methods are widely used. However, it is difficult and labor consuming to maintain the transpiration measurements of individual trees in a wide range area and especially for long-term experiment. Therefore, the sharing of sapflow data through database should be useful to promote the studies on transpiration and water balance for large spatial scale. In this paper, we present sap flow database, which have Granier type sap flux data from 18 Korean pine (Pinus koraiensis) since 2011 and 16 (Quercus aliena) since 2013 in Mt.Taehwa Seoul National University forest and 18 needle fir (Abies holophylla), seven (Quercus serrata), three (Carpinus laxiflora and C. cordata each since 2013 in Gwangneung. In addition, the database includes the sapling transpiration of nine species (Prunus sargentii, Larix kaempferii, Quercus accutisima, Pinus densiflora, Fraxinus rhynchophylla, Chamecypans obtuse, P. koraiensis, Betulla platyphylla, A. holophylla, Pinus thunbergii), which were measured using heat pulse method since 2018. We believe this is the first database to share the sapflux data in Rep. of Korea, and we wish our database to be used by other researchers and contribute a variety of researches in this field.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1449-1463
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• 2020

As recent global warming and climate changes become more serious, the importance of CO2 absorption by forests is increasing to cope with the greenhouse gas issues. According to the UN Framework Convention on Climate Change, it is required to calculate national CO2 absorptions at the local level in a more scientific and rigorous manner. This paper presents the gridded expansion of forest flux observations and mapping of daily CO2 absorption by the forests in Korea using numerical weather prediction data and satellite images. To consider the sensitive daily changes of plant photosynthesis, we built a machine learning model to retrieve the daily RACA (reference amount of CO2 absorption) by referring to the climax forest in Gwangneung and adopted the NIFoS (National Institute of Forest Science) lookup table for the CO2 absorption by forest type and age to produce the daily AACA (actual amount of CO2 absorption) raster data with the spatial variation of the forests in Korea. In the experiment for the 1,095 days between Jan 1, 2013 and Dec 31, 2015, our RACA retrieval model showed high accuracy with a correlation coefficient of 0.948. To achieve the tier 3 daily statistics for AACA, long-term and detailed forest surveying should be combined with the model in the future.

• Journal of the Korean Society of Earth Science Education
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• v.15 no.2
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• pp.213-223
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• 2022

The purpose of this study is to identify the types of essential inquiry activities presented in elementary science textbooks for grades 5-6, and to find out what difficulties teachers have in the actual teaching process. To this end, the essential research activities presented in the textbook were analyzed into six types: experimentation/observation, investigation/discussion and presentation, data interpretation, discussion/discussion, simulation activity, and expression. In addition, 108 elementary school teachers were investigated for the suitability of inquiry activity achievement standards, suitability at the student's level, student interest, and difficulty in teaching instruction. To summarize the research results, the most frequently suggested type was the experiment/observation type, followed by simulation activity type and data interpretation type. It was analyzed that there was no discussion/discussion type in the 5th grade textbooks, and the 6th graders did not present research activities that correspond to the research/discussion/presentation type and the expression type in the textbook. In the results of teachers' responses to the suitability of achievement standards for inquiry activities presented in textbooks and the suitability of the student's level, 5th graders showed lower average scores than 6th graders, and showed similar average scores in student interest and instructional difficulty. Also, it was confirmed that improvement was required for a total of 17 inquiry activities. Specifically, teachers responded that they had difficulty in guiding inquiry activities when the experimental results did not appear as intended in the textbook, when students' interest in inquiry activities was low, and when students and teachers had low understanding of related science concepts. Teachers pointed out practical problems such as difficulties in long-term observation in astronomy-related units, and students in upper elementary school not actively participating in dynamic play activities.

• Korean journal of applied entomology
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• v.16 no.3 s.32
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• pp.171-179
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• 1977

Since the outbreak of the brown planthopper (Nilaparvata lugens) in 1915 caused tremendous losses in rice production, one of the more effective method of prevention of such a disaster could be the establishment of longterm forecasting system, In 1916 the author indicated there was a correlation between sunspot activities and brown planthopper and the white back planthopper outbreaks. However, the examples seem to be too small size to state a definite correlation. The purpose of the present study IS to revi~w the history of the brown planthopper outbreaks, and to establish a more effective forcasting system. The present forcasting methods are based on light trap catches of adults which already migrate into this country from mainland China. The regular cycle of 11.2 years of sunspot activity began in 1710, and was continued to present. To gather more records of brown planthopper, the author checked 'Joseon Wangjo Silrok' and analized the so-called 'Hwang' 'Hwang-chung' and 'Chung' which have multiple meanings, together with 'Samguk Sagi' 'Goryo Sa' and 'Munheon Bigo.' The results obtained by the about from review of these old literature citations revealed that ten species of insect and unknown species were involved: i. e., pine moth (Dendrolimus spectabilis), army worm (Mythimna separata), brown planthopper (Nilarvata lugens), white-back planthopper (Sogatella furcifera), migratory locust (Locutsa migratoria), rice stem borer (Chilo suppressalis,), mole cricket (Gryllotalpa africana), rice-plant weevil (Echinocnemus squameus), cut worm (Euxoa segetum), and mulberry pyralid Margaronia pyloalis) The suspected incidence of planthopper in old records expressed by 'Hwang' or 'Chung' revealed a total or 25 out of 37 in 'Samguk sagi,' 21 out of 49 in 'Goryo sa,' 9 of 73 in 'Wanjo-silrog,' and none of 8 in 'Munheon bigo' were planthoppers. Therefore, a total of 36 out of 167 records of insect incidence in the old literature can be possibly attributed to planthoppers. The brown planthopper and white-back planthopper migrate together to Korea every year from mainland China, However, the number of each species are differ by year. In 1975 outbreak the brown planthopper was dominant; and the white-back planthopper prevailed in 1946 and 1977 outbreaks, During the course of this study, the author was able to add a new record of outbreak of planthop per. In 1916 the white-back planthopper outbreak caused serious losses in Chungcheong-namdo and Jeonla-namdo, with losses estimated as high as 160 and 190 thousand seok (23.2 and 27.5 thousand M/T), in Naju and Secheon county, respectively. Since 1912, major outbreaks of brown planthopper or white-back planthopper have been recored 5 times. These occurrences coincide and well matched the period of minimum number of sunspots, With these authenticated records of planthoppers, the author believes there is a close correlation between brown planthopper and white-back planthopper outbreaks in Korea and sunspot activities. Therefore, in years of low number of sunspots, we should watch for and expect outbreaks of these. insects. At this time, it will be necessary to provide all possible prevention measures.

• Journal of Sericultural and Entomological Science
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• v.52 no.2
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• pp.110-116
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• 2014

Recently the number of the butterflies, Mellicta ambigua, had been decreasing rapidly, and already disappeared at many habitat. In this studies, we investigated ecological environment of Mellicta ambigua for preparing of primary research data recovering habitat, and studied on bionomical characteristics. Two different habitat, Jindo and Inje, were selected for investigation of ecological environment. We investigated four times during 3-month, from June to August in 2012. In Jindo, we observed more than 100 butterflies and a lot of host plants, Melampyrum roseum var. japonicum. But only 5 butterflies and only a few host plants, Veronicastrum sibiricum were observed in Inje. We could not observe the eggs, the larva and pupa on the host plants at all. For finding of bionomical characteritics, we reared butterflies at natural conditions. Collected 3-female butterflies from Jindo laid 465 eggs on the leaves of 3-host plants, Veronicastrum sibiricum. 120 ~ 186 eggs per each female were laid in the shape of cluster. An egg was globular shape, 0.6 mm diameter and 0.7 mm height. The egg periods were $9.96{\pm}0.4days$ after ovipositioning, and the hatchability was 95.% at natural condition. The larval periods were $4.1{\pm}0.6days$ (1st instar), $2.1{\pm}1.0days$ (2nd), $8.1{\pm}0.7days$ (3rd), $239.2{\pm}10.9days$ (4th), $12.3{\pm}1.3days$ (5th), $17.1{\pm}1.1days$ (6th), $10.5{\pm}1.0days$ (7th) each other. The larva of 4th instar overwintered in the nest that had been made into the leaf of host plant with secreted thread as a group until early March next year. In the early March next year, overwintered larva went around their nest in search of host plants, and went to other host plants, Veronica persica and Plantago asiatica, sometimes. The overwintered larva of Mellicta ambigua could grow up on two other host plants normally. In the following experiment, the butterflies of Mellicta ambigua laid eggs on the leaves of Plantago asiatica, but the 1st instar larva from eggs died all. The headwidth of each developmental larval stage were $0.28{\pm}0.02mm$ (1st), $0.45{\pm}0.02mm$ (2nd), $0.58{\pm}0.02mm$ (3rd), $0.75{\pm}0.03mm$ (4th), $0.89{\pm}0.05mm$ (5th), $1.23{\pm}0.06mm$ (6th), $2.13{\pm}0.11mm$ (7th). The pupal ratio was 92.0%. The pupal period were $9.1{\pm}1.6days$, and the emergence rate was 88.6%. As a result we determined that Mellicta ambigua can rear at natural conditions. But indoor-rearing is considered to be difficult and not useful industrially, because they have long term larval stage and only one life cycle per an year.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.27-65
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• 2020

Many companies on information and communication technology make public their own developed AI technology, for example, Google's TensorFlow, Facebook's PyTorch, Microsoft's CNTK. By releasing deep learning open source software to the public, the relationship with the developer community and the artificial intelligence (AI) ecosystem can be strengthened, and users can perform experiment, implementation and improvement of it. Accordingly, the field of machine learning is growing rapidly, and developers are using and reproducing various learning algorithms in each field. Although various analysis of open source software has been made, there is a lack of studies to help develop or use deep learning open source software in the industry. This study thus attempts to derive a strategy for adopting the framework through case studies of a deep learning open source framework. Based on the technology-organization-environment (TOE) framework and literature review related to the adoption of open source software, we employed the case study framework that includes technological factors as perceived relative advantage, perceived compatibility, perceived complexity, and perceived trialability, organizational factors as management support and knowledge & expertise, and environmental factors as availability of technology skills and services, and platform long term viability. We conducted a case study analysis of three companies' adoption cases (two cases of success and one case of failure) and revealed that seven out of eight TOE factors and several factors regarding company, team and resource are significant for the adoption of deep learning open source framework. By organizing the case study analysis results, we provided five important success factors for adopting deep learning framework: the knowledge and expertise of developers in the team, hardware (GPU) environment, data enterprise cooperation system, deep learning framework platform, deep learning framework work tool service. In order for an organization to successfully adopt a deep learning open source framework, at the stage of using the framework, first, the hardware (GPU) environment for AI R&D group must support the knowledge and expertise of the developers in the team. Second, it is necessary to support the use of deep learning frameworks by research developers through collecting and managing data inside and outside the company with a data enterprise cooperation system. Third, deep learning research expertise must be supplemented through cooperation with researchers from academic institutions such as universities and research institutes. Satisfying three procedures in the stage of using the deep learning framework, companies will increase the number of deep learning research developers, the ability to use the deep learning framework, and the support of GPU resource. In the proliferation stage of the deep learning framework, fourth, a company makes the deep learning framework platform that improves the research efficiency and effectiveness of the developers, for example, the optimization of the hardware (GPU) environment automatically. Fifth, the deep learning framework tool service team complements the developers' expertise through sharing the information of the external deep learning open source framework community to the in-house community and activating developer retraining and seminars. To implement the identified five success factors, a step-by-step enterprise procedure for adoption of the deep learning framework was proposed: defining the project problem, confirming whether the deep learning methodology is the right method, confirming whether the deep learning framework is the right tool, using the deep learning framework by the enterprise, spreading the framework of the enterprise. The first three steps (i.e. defining the project problem, confirming whether the deep learning methodology is the right method, and confirming whether the deep learning framework is the right tool) are pre-considerations to adopt a deep learning open source framework. After the three pre-considerations steps are clear, next two steps (i.e. using the deep learning framework by the enterprise and spreading the framework of the enterprise) can be processed. In the fourth step, the knowledge and expertise of developers in the team are important in addition to hardware (GPU) environment and data enterprise cooperation system. In final step, five important factors are realized for a successful adoption of the deep learning open source framework. This study provides strategic implications for companies adopting or using deep learning framework according to the needs of each industry and business.

• Journal of Bio-Environment Control
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• v.5 no.2
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• pp.215-235
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• 1996

The thermal analysis by mathematical model simulation makes it possible to reasonably predict heating and/or cooling requirements of certain greenhouses located under various geographical and climatic environment. It is another advantages of model simulation technique to be able to make it possible to select appropriate heating system, to set up energy utilization strategy, to schedule seasonal crop pattern, as well as to determine new greenhouse ranges. In this study, the control pattern for greenhouse microclimate is categorized as cooling and heating. Dynamic model was adopted to simulate heating requirements and/or energy conservation effectiveness such as energy saving by night-time thermal curtain, estimation of Heating Degree-Hours(HDH), long time prediction of greenhouse thermal behavior, etc. On the other hand, the cooling effects of ventilation, shading, and pad ||||&|||| fan system were partly analyzed by static model. By the experimental work with small size model greenhouse of 1.2m$\times$2.4m, it was found that cooling the greenhouse by spraying cold water directly on greenhouse cover surface or by recirculating cold water through heat exchangers would be effective in greenhouse summer cooling. The mathematical model developed for greenhouse model simulation is highly applicable because it can reflects various climatic factors like temperature, humidity, beam and diffuse solar radiation, wind velocity, etc. This model was closely verified by various weather data obtained through long period greenhouse experiment. Most of the materials relating with greenhouse heating or cooling components were obtained from model greenhouse simulated mathematically by using typical year(1987) data of Jinju Gyeongnam. But some of the materials relating with greenhouse cooling was obtained by performing model experiments which include analyzing cooling effect of water sprayed directly on greenhouse roof surface. The results are summarized as follows : 1. The heating requirements of model greenhouse were highly related with the minimum temperature set for given greenhouse. The setting temperature at night-time is much more influential on heating energy requirement than that at day-time. Therefore It is highly recommended that night- time setting temperature should be carefully determined and controlled. 2. The HDH data obtained by conventional method were estimated on the basis of considerably long term average weather temperature together with the standard base temperature(usually 18.3$^{\circ}C$). This kind of data can merely be used as a relative comparison criteria about heating load, but is not applicable in the calculation of greenhouse heating requirements because of the limited consideration of climatic factors and inappropriate base temperature. By comparing the HDM data with the results of simulation, it is found that the heating system design by HDH data will probably overshoot the actual heating requirement. 3. The energy saving effect of night-time thermal curtain as well as estimated heating requirement is found to be sensitively related with weather condition: Thermal curtain adopted for simulation showed high effectiveness in energy saving which amounts to more than 50% of annual heating requirement. 4. The ventilation performances doting warm seasons are mainly influenced by air exchange rate even though there are some variations depending on greenhouse structural difference, weather and cropping conditions. For air exchanges above 1 volume per minute, the reduction rate of temperature rise on both types of considered greenhouse becomes modest with the additional increase of ventilation capacity. Therefore the desirable ventilation capacity is assumed to be 1 air change per minute, which is the recommended ventilation rate in common greenhouse. 5. In glass covered greenhouse with full production, under clear weather of 50% RH, and continuous 1 air change per minute, the temperature drop in 50% shaded greenhouse and pad ＆ fan systemed greenhouse is 2.6$^{\circ}C$ and.6.1$^{\circ}C$ respectively. The temperature in control greenhouse under continuous air change at this time was 36.6$^{\circ}C$ which was 5.3$^{\circ}C$ above ambient temperature. As a result the greenhouse temperature can be maintained 3$^{\circ}C$ below ambient temperature. But when RH is 80%, it was impossible to drop greenhouse temperature below ambient temperature because possible temperature reduction by pad ||||&|||| fan system at this time is not more than 2.4$^{\circ}C$. 6. During 3 months of hot summer season if the greenhouse is assumed to be cooled only when greenhouse temperature rise above 27$^{\circ}C$, the relationship between RH of ambient air and greenhouse temperature drop($\Delta$T) was formulated as follows : $\Delta$T= -0.077RH＋7.7 7. Time dependent cooling effects performed by operation of each or combination of ventilation, 50% shading, pad ＆ fan of 80% efficiency, were continuously predicted for one typical summer day long. When the greenhouse was cooled only by 1 air change per minute, greenhouse air temperature was 5$^{\circ}C$ above outdoor temperature. Either method alone can not drop greenhouse air temperature below outdoor temperature even under the fully cropped situations. But when both systems were operated together, greenhouse air temperature can be controlled to about 2.0-2.3$^{\circ}C$ below ambient temperature. 8. When the cool water of 6.5-8.5$^{\circ}C$ was sprayed on greenhouse roof surface with the water flow rate of 1.3 liter/min per unit greenhouse floor area, greenhouse air temperature could be dropped down to 16.5-18.$0^{\circ}C$, whlch is about 1$0^{\circ}C$ below the ambient temperature of 26.5-28.$0^{\circ}C$ at that time. The most important thing in cooling greenhouse air effectively with water spray may be obtaining plenty of cool water source like ground water itself or cold water produced by heat-pump. Future work is focused on not only analyzing the feasibility of heat pump operation but also finding the relationships between greenhouse air temperature(T$_{g}$ ), spraying water temperature(T$_{w}$ ), water flow rate(Q), and ambient temperature(T$_{o}$).