• Journal of agriculture & life science
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• v.46 no.1
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• pp.189-194
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• 2012

Measurement of compositions and somatic cells in raw milk by chemical methods usually requires a lot of time, skilled labor and expensive analytical equipments. Recently, near-infrared reflectance spectroscopy (NIRS), which is a rapid, cost-effective and non-destructive technique, has been extensively used for safety and quality evaluation in the field of dairy products. However, less study has been performed to evaluate the effect of transmitted light on milk quality during NIRS analysis. Therefore, the objective of this study was to analyze the changes in milk quality using transmitted light. Raw milk samples collected from dairy farm from Siga prefecture in Japan were analyzed for fat, protein, lactose, solids not fat, total solids, milk urea and citric acid using the Milko scan 4000. Somatic cells in raw milk samples were counted by the Fossomatic 5000. Transmittance spectra of 50 ml raw milk samples were obtained by the Lax-Cute lighter in the 400 nm or less, 689 nm, 773 nm, 900 nm and 979 nm. As a result, milk fat as well as somatic cell count was increased by 2.6% and 9.0%, respectively. The other compositions were, however, changed within the relative error of the measurement. Further studies are needed to apply raw milk quality evaluation using the UV band by accumulating more samples and more data.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.164-175
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• 2019

The Tor Tong Daeng Irrigation Project with the irrigation area of 61,400 hectares is located in the Ping Basin of the Upper Central Plain of Thailand where farmers depended on both surface water and groundwater. In the drought year, water storage in the Bhumipol Dam is inadequate to allocate water for agriculture, and caused water deficit in many irrigation projects. Farmers need to find extra sources of water such as water from farm pond or groundwater as a supplement. The operation of Bhumipol Dam and irrigation demand estimation are vital for irrigation water allocation to help solve water shortage issue in the irrigation project. The study aims to determine the smart dam operation system to mitigate water shortage in this irrigation project via introduction of machine learning to improve dam operation and irrigation demand estimation via soil moisture estimation from satellite images. Via ANN technique application, the inflows to the dam are generated from the upstream rain gauge stations using past 10 years daily rainfall data. The input vectors for ANN model are identified base on regression and principal component analysis. The structure of ANN (length of training data, the type of activation functions, the number of hidden nodes and training methods) is determined from the statistics performance between measurements and ANN outputs. On the other hands, the irrigation demand will be estimated by using satellite images, LANDSAT. The Enhanced Vegetation Index (EVI) and Temperature Vegetation Dryness Index (TVDI) values are estimated from the plant growth stage and soil moisture. The values are calibrated and verified with the field plant growth stages and soil moisture data in the year 2017-2018. The irrigation demand in the irrigation project is then estimated from the plant growth stage and soil moisture in the area. With the estimated dam inflow and irrigation demand, the dam operation will manage the water release in the better manner compared with the past operational data. The results show how smart system concept was applied and improve dam operation by using inflow estimation from ANN technique combining with irrigation demand estimation from satellite images when compared with the past operation data which is an initial step to develop the smart dam operation system in Thailand.

• Journal of Sasang Constitutional Medicine
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• v.14 no.2
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• pp.10-17
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• 2002

1. Objects of Research This research is purposed to find Dong-mu's thought on 'Knowing-Airing(知行), through summarizing sentences related to 'Knowing-Acting(知行)'proposed in his writings. 2. Methods of Research It was researched bibliologically with Dong-mu's chief medical writings such as ${\ulcorner}$Gyukchigo(格致業)${\lrcorner}$, ${\ulcorner}$Dongyi Soose Bowon(東醫壽世保元)${\lrcorner}$ , ${\ulcorner}$Dongyi Soose Bowon Sasang Chobongyun(東醫壽世保元四象草本卷${\lrcorner}$, ${\ulcorner}$Dong-mu's posthumos work(東武遺葉)${\lrcorner}$. 3. Results and Conclusions 1.'Knowing(知)'is related to recognition of 'Mind(心)' and 'Acting(行)' is related to practice of 'Body(身)' in ${\ulcorner}$Gyukchigo(格致藁)${\lrcorner}$ . 'Knowing-Acting(知行)' in ${\ulcorner}$Gyukchigo(格致藁)${\lrcorner}$ is regard as a important factor to reach the state of 'Golden mean(中庸)' by 'Perception of Man(知人)' 2. 'Knowing-Acting(知行)' in ${\ulcorner}$Dongyi Soose Bowon Sasang Chobongyun(東醫壽世保元四象草本卷${\lrcorner}$ is thought to recognize and practice marals such as 'Humanity Justice propriety Wisdom(仁義禮智)' and 'Loyality Filialpiety Friendahip Fraternity(忠孝友悌)'. It was proposed that people are classified into Sasang Constition by 'Knowing-Acting(知行)' in ${\ulcorner}$Dongyi Soose Bowon Sasang Chobongyun(東醫壽世保元四象草本卷${\lrcorner}$ 3. 'Knowing-Acting(知行)' in ${\ulcorner}$Dongyi Soose Bowon(東醫壽世保元四象草本卷)${\lrcorner}$ is difffrent from 'Knowing-Acting(知行)' in ${\ulcorner}$Dongyi Soose Bowon Sasang Chobongyun(束醫壽世保元圖象草本卷${\lrcorner}$ 'Knowing(知)'is conception of marals such as 'Humanity Jusrire propriety Wisdom(仁義禮智)' and Loyality Filialpiety Friendship Fraternity(忠孝友悌)'. 'Acting(行)' is conception of productivity such as 'Scholar Farm Engineer Merchannt(士農工商)' and 'Field Residence District Nation (田業邦國). 4. 'Knowing-Acting(知行)' in ${\ulcorner}$Dong-mu's posthumos work(東武遺葉)${\ulcorner}$ was c1assified into large and small one. The large one is private and the small one is public. It is imponant to become sincere and respectful for achieve 'Ideal medium of Knowing-Acting.'.

• Journal of the Korea Organic Resources Recycling Association
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• v.19 no.4
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• pp.74-83
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• 2011

In this study, to estimate the transforming (runoff and leachate) rate of the livestock resources applying to agricultural crop land as fertilizer, field scale test was conducted and the results were obtained as follows. According to results of livestock resources effect to agricultural land, the total amount of harvested crop from testing bed was $0.437kg/m^2$, and nutrient contents were $0.024{\pm}0.006%$ and $0.020{\pm}0.004%$ for N and P, respectively. Dynamics of contaminants in the livestock resources to be supplied to agricultural crop land showed that concentrations were continuously decreased to the level of blank test bed until 60 days of planting. The amount of runoff from farm land showed the tendency to increase according to the increase of rainfall intensity. Run-off ratio of 10mm/h rainfall intensity for agricultural land showed that each contaminant concentration was increased due to rainfall intensity with 8 mm/h, specifically SS showed the highest increase.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.3
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• pp.187-195
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• 2019

The needs for precise diagnostics and farm management-decision aids have increased to reduce the risk of climate change and environmental stress. Crop simulation models have been widely used to search optimal solutions for effective cultural practices. However, limited knowledge on physiological responses to environmental variation would make it challenging to apply crop simulation models to a wide range of studies. Advanced research facilities would help investigation of plant response to the environment. In the present study, the sunlit controlled environment chambers, known as Korean SPAR (Soil-Plant-Atmosphere-Research) system, was developed by renovating existing SPAR system. The Korean SPAR system controls and monitors major environmental variables including atmospheric carbon dioxide concentration, temperature and soil moisture. Furthermore, plants are allowed to grow under natural sunlight. Key physiological and physical data such as canopy photosynthesis and respiration, canopy water and nutrient use over the whole growth period are also collected automatically. As a case study, it was shown that the Korean SPAR system would be useful for collection of data needed for understanding the growth and developmental processes of a crop, e.g., soybean. In addition, we have demonstrated that the canopy photosynthetic data of the Korean SPAR indicate the precise representation of physiological responses to environment variation. As a result, physical and physiological data obtained from the Korean SPAR are expected to be useful for development of an advanced crop simulation model minimizing errors and confounding factors that usually occur in field experiments.

• Journal of the Korean Solar Energy Society
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• v.39 no.5
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• pp.1-10
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• 2019

Recently, the installation capacity of PV (photovoltaic) systems has been increasing not only field installation but also floating PV, farm land, BIPV/BAPV. For this reason, the new design and materials of PV module are needed. In particular, in order to apply a PV system to a building, lightweight of the PV module is essential. PV modules made of generally used texturing glass are excellent in output and reliability, but there is a limit to the weight that can be reduced. For the lightweight of the PV module, it necessary to use a film instead of a glass. However, the application of film rather than a glass may cause various problems such as decrease in photocurrent by decrease in transmittance and a increase of CTM (cell to module) loss, a degradation of the reliability, and so on. In this paper, PV modules using Ultra barrier film, which is recently a lot of interest as a substitute for a glass, its characteristic analysis and reliability test were conducted. The transmittance and UV characteristics of each material were verified, and the output of the fabricated 1 cell PV module was measured. In addition, 24 cell PV modules were fabricated at the lab-scale and its reliability tests were conducted. As a result of the experiment, the reliability characteristics of the ultra barrier film PV module were excellent, and it was confirmed that it could be used as the front material of the PV module instead of glass

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.6
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• pp.553-560
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• 2020

This paper presents an algorithm for identifying and eliminating errors by seagrasses in coastal bathymetry surveying using drone and HD camera. Survey errors due to seagrasses were identified, segmentated and eliminated using a L∗a∗b color space model. Bathymetry survey using a drone and HD camera has many advantages over conventional survey methods such as ship-board acoustic sounder or manual level survey which are time consuming and expensive. However, errors caused by sea bed reflectance due to seagrasses habitat hamper the development of new surveying tool. Seagrasses are the flowering plants which start to grow in November and flourish to maximum density until April in Korea. We developed a new algorithm for identifying seagrasses habitat locations and eliminating errors due to seagrasses to get the accurate depth survey data. We tested our algorithm at Wolpo beach. Bathymetry survey data which were obtained using a drone with HD camera and calibrated to eliminate errors due to seagrasses, were compared with depth survey data obtained using ship-board multi-beam acoustic sounder. The abnormal bathymetry data which are defined as the excess of 1.5 times of a standard deviation of random errors, are composed of 8.6% of the test site of area of 200 m by 300 m. By applying the developed algorithm, 92% of abnnormal bathymetry data were successfully eliminated and 33% of RMS errors were reduced.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.503-514
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• 2021

Rice production with adequate level of area is important for decision making of rice supply and demand policy. It is essential to grasp rice cultivation areas in advance for estimating rice production of the year. This study was carried out to classify paddy rice cultivation in Gimje-si using sentinel-1 SAR (synthetic aperture radar) and UAV imagery in early July. Time-series Sentinel-1A and 1B images acquired from early May to early July were processed to convert into sigma naught (dB) images using SNAP (SeNtinel application platform, Version 8.0) toolbox provided by European Space Agency. Farm map and parcel map, which are spatial data of vector polygon, were used to stratify paddy field population for classifying rice paddy cultivation. To distinguish paddy rice from other crops grown in the paddy fields, we used the decision tree method using threshold levels and random forest model. Random forest model, trained by mainly rice cultivation area and rice and soybean cultivation area in UAV image area, showed the best performance as overall accuracy 89.9%, Kappa coefficient 0.774. Through this, we were able to confirm the possibility of early estimation of rice cultivation area in Gimje-si using UAV image.

• Journal of Mushroom
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• v.18 no.4
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• pp.297-302
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• 2020

Five varieties of mushrooms, including Sae-do, were examined using farm field tests to determine their morphological characteristics and quality by performing harvest flush. Considering the cultivation characteristics of the varieties studied, the parts related to mushroom generation and production showed almost similar characteristics. Overall, the mycelial forces were similar; however, in the evaluation of plantation tests performed by farmers, "saedo" was found to be the strongest and "saehan" was considered to be the weakest. Weights of fruiting bodies were related more for compost status and regimen of use than for breeding, and it was difficult to distinguish between the weights of fruiting bodies of the varieties studied. Regardless of the variety, pileus diameter, pileus thickness, and stem length of Dalseong-gun, Yongin-si, and Boryeong-si decreased as the harvest flush progressed. However, stem thickness tended to increase in the second and third flush compared to that in the first flush, regardless of the variety. However, the Gyeongju-si farms could not identify any trends attributable to varieties and harvest flushes. The pileus size and stem length of the fruiting bodies of varieties from Buyeo farms decreased with the progression of the harvest flush. However, pileus thickness and stem thickness did not show any specific tendency of growth among the varieties studied. The differences in the morphological characteristics of mushroom varieties in each harvest cycle are expected to be caused by differences in the supply of nutrients in the medium, the quality of the compost used, and the cultivation environment rather than the variety.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.6
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• pp.561-568
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• 2020

Wave measurements using X-band radar have many advantages compared to other wave gauges including wave-rider buoy, P-u-v gauge and Acoustic Doppler Current Profiler (ADCP), etc.. For example, radar system has no risk of loss/damage in bad weather conditions, low maintenance cost, and provides spatial distribution of waves from deep to shallow water. This paper presents new methods for estimating significant wave heights of X-band marine radar images using Artificial Neural Network (ANN). We compared the time series of estimated significant wave heights (Hs) using various estimation methods, such as signal-to-noise ratio (${\sqrt{SNR}}$), both and ${\sqrt{SNR}}$ the peak period (TP), and ANN with 3 parameters (${\sqrt{SNR}}$, TP, and Rval > k). The estimated significant wave heights of the X-band images were compared with wave measurement using ADCP(AWC: Acoustic Wave and Current Profiler) at Hujeong Beach, Uljin, Korea. Estimation of Hs using ANN with 3 parameters (${\sqrt{SNR}}$, TP, and Rval > k) yields best result.