• Journal of Bio-Environment Control
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• v.31 no.3
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• pp.230-236
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• 2022

This study was carried out to produce two-flowered seedlings, harvest them early in a greenhouse, and extend the harvest period. This study was carried out to effectively produce the second truss blooming seedlings to harvest tomatoes early and extend the harvest period. For production of the second truss blooming seedlings (one stem), the nutrient solution EC was supplied at 1.5, 2.0, 2.5 dS·m^-1, and dynamic management (3.0 → 3.5 → 4.5 dS·m^-1). The seedling period was 60 days, which was 20-40 days longer than conventional seedlings, and 10 days longer than the first truss blooming seedlings (cube seedlings). The plant height was 78 and 77 cm in EC 2.5 dS·m^-1 and dynamic management respectively, which was shorter than EC 1.5 dS·m^-1 with 88 cm. As for the EC in the cube before formulation, dynamic management had the highest EC 5.5 dS·m^-1, and the cube supplied with EC 1.5 dS·m^-1 had the lowest. The production yield by treatment did not a difference among in the second truss blooming seedlings, but the first truss blooming seedlings showed lower productivity than second truss blooming seedlings. The second truss blooming seedling were harvested 35 days after planting on June 4, the first harvest date, and the first truss blooming were harvested in 42 days on June 11th. There was no difference in plant height and root growth due to bending at frequency planting. In the study on the production of the second truss blooming seedlings (two stem), the nutrient solution EC was supplied under 2.0, 2.5, 3.0 dS·m^-1, and dynamic management (3.0 → 3.5 → 4.5 dS·m^-1). The seedling period was 90 days, which was 40-50 days longer than conventional seedlings and 10 days longer than the first truss blooming seedlings (cube seedlings). Plant height was 80 and 81 cm in EC 2.0 dS·m^-1 and 2.5 dS·m^-1 respectively, but was the shortest at 73 cm in dynamic management. EC in the medium increased as the seeding period increased in all treatments. The dynamic management was the highest with EC 5.1 dS·m^-1. There was no difference in yield among EC treatments in the second truss blooming seedlings, which had a longer seeding period of about 10 days, produced 15% more than the first truss blooming seedlings. In order to shorten the plant height of the second truss blooming seedlings, it is judged that the most efficient method is increasing the concentration of nutrient solution.

• Korean Journal of Culture and Social Issue
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• v.26 no.1
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• pp.25-45
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• 2020

Intentionality judgement in criminal cases is a core area of fact finding that is root of guilty and sentencing judgment on the defendant. However, the third party is not sure the intentionality because it reflects subjective aspect of agent. Thus, mechanism behind intentionality judgment is an important factor to be properly understood by the academia and the criminal justice system. However, previous studies regarding intentionality judgment models have shown inconsistent results. Mental-state models proposed foreseeability(belief) and desire of agent at the time of the offence as key factors in intentionality judgment. These factors consistent with central things on intentionality judgment in criminal law. However, key factors in moral-evaluation models are blameworthiness of agent and badness of outcome reflected on the consequent aspect of act. Recently, deep-self concordance model emerged suggesting important factors on intentionality judgment are not mental states and moral evaluations but individual's deep-self. However, these models are limited in that they do not consider the important features of criminal cases, that the consequence of the case is inevitably negative, and therefore the actor who is a party to legal punishment rarely expresses his or her mental state at the time of the act. Therefore, this study suggests that, based on the existing intentionality judgment studies and the characteristics of the criminal case, the inference about who the agent was originally will play a key role in judging the intentionality in the criminal case. This is the moral-character model. Futhermore, In this regard, this study discussed what the media and criminal justice institutions should keep in mind and the directions for future research.

• Journal of Korea Entertainment Industry Association
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• v.15 no.3
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• pp.75-88
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• 2021

The film won the Golden Palm Award at the Cannes Film Festival, and received the Academy Award for a non-English-speaking film in February 2020, respectively. It has received a monumental evaluation in the world film history. Overall, this film is about class conflict, and critics evaluate the theme of the film as "badly twisted class gap" and "anger from class." The film expresses an intrinsic conflict embodied in culture as a "tragedy in which no bad person appears," rather than the dichotomous composition of the classical class struggle from Marxism. In other words, this can be seen as expressing the substrated class relationship of the modern society that Pierre Bourdieu had argued. This film has been focused as a controversial target under Korea society with excess of ideology. Politics used to adopt the keyword, 'parasite', for political disputes not only in culture contents world. Paradoxically socialism China did not allow to release film 'Parasite.' On the other hand, Lee O-Yong argues that the movie "Parasite" does not look at social phenomena through a dichotomous perspective, but is viewed through a "double perspective" and evaluates that it does not lose eyes looking at humans through tension. This view is based upon 'Vital Capitalism'. Lee. O-Yong looks at the movie "Parasite" from the perspective of "Vital Capitalism". The theory of Vital Capitalism does not seek to find the root of historical development in class struggle conflicts, but rather figuring out history and society pays attention onto the intrinsic characteristics of life, Topophilia, Neophilia, and Biophilia. Lee Eo-ryeong argues that the development of civilization theory evolved from the stage of Hobbes' Darwinism or predatism to the stage of host vs. parasite of Michel Serres, and onto the stage of Margulis's 'Win-Win (inter-dependence)'. In this paper, after overview of vital capital concept and preceeding research, re-interpretations were tried onto scenes based upon fields from habitus, culture capital. This exploration looks for a alternative for excess of ideology in Korea society.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1125-1139
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• 2022

In an unmanned aerial vehicles (UAVs) system, a physical offset can be existed between the global positioning system/inertial measurement unit (GPS/IMU) sensor and the observation sensor such as a hyperspectral sensor, and a lidar sensor. As a result of the physical offset, a misalignment between each image can be occurred along with a flight direction. In particular, in a case of multi-sensor system, an observation sensor has to be replaced regularly to equip another observation sensor, and then, a high cost should be paid to acquire a calibration parameter. In this study, we establish a precise sensor model equation to apply for a multiple sensor in common and propose an independent physical offset estimation method. The proposed method consists of 3 steps. Firstly, we define an appropriate rotation matrix for our system, and an initial sensor model equation for direct-georeferencing. Next, an observation equation for the physical offset estimation is established by extracting a corresponding point between a ground control point and the observed data from a sensor. Finally, the physical offset is estimated based on the observed data, and the precise sensor model equation is established by applying the estimated parameters to the initial sensor model equation. 4 region's datasets(Jeon-ju, Incheon, Alaska, Norway) with a different latitude, longitude were compared to analyze the effects of the calibration parameter. We confirmed that a misalignment between images were adjusted after applying for the physical offset in the sensor model equation. An absolute position accuracy was analyzed in the Incheon dataset, compared to a ground control point. For the hyperspectral image, root mean square error (RMSE) for X, Y direction was calculated for 0.12 m, and for the point cloud, RMSE was calculated for 0.03 m. Furthermore, a relative position accuracy for a specific point between the adjusted point cloud and the hyperspectral images were also analyzed for 0.07 m, so we confirmed that a precise data mapping is available for an observation without a ground control point through the proposed estimation method, and we also confirmed a possibility of multi-sensor fusion. From this study, we expect that a flexible multi-sensor platform system can be operated through the independent parameter estimation method with an economic cost saving.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1723-1735
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• 2022

Landslides are one of the most prevalent natural disasters, threating both humans and property. Also landslides can cause damage at the national level, so effective prediction and prevention are essential. Research to produce a landslide susceptibility map with high accuracy is steadily being conducted, and various models have been applied to landslide susceptibility analysis. Pixel-based machine learning models such as frequency ratio models, logistic regression models, ensembles models, and Artificial Neural Networks have been mainly applied. Recent studies have shown that the kernel-based convolutional neural network (CNN) technique is effective and that the spatial characteristics of input data have a significant effect on the accuracy of landslide susceptibility mapping. For this reason, the purpose of this study is to analyze landslide vulnerability using a pixel-based deep neural network model and a patch-based convolutional neural network model. The research area was set up in Gangwon-do, including Inje, Gangneung, and Pyeongchang, where landslides occurred frequently and damaged. Landslide-related factors include slope, curvature, stream power index (SPI), topographic wetness index (TWI), topographic position index (TPI), timber diameter, timber age, lithology, land use, soil depth, soil parent material, lineament density, fault density, normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were used. Landslide-related factors were built into a spatial database through data preprocessing, and landslide susceptibility map was predicted using deep neural network (DNN) and CNN models. The model and landslide susceptibility map were verified through average precision (AP) and root mean square errors (RMSE), and as a result of the verification, the patch-based CNN model showed 3.4% improved performance compared to the pixel-based DNN model. The results of this study can be used to predict landslides and are expected to serve as a scientific basis for establishing land use policies and landslide management policies.

• Journal of Bio-Environment Control
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• v.31 no.1
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• pp.67-76
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• 2022

This study aimed to determine the photosynthesis and growth characteristics of Peucedanum japonicum T. grown under aquaponics in a plant factory (AP) by comparing those grown under hydroponic cultivation system (HP). The AP system raised 30 fishes at a density of 10.6 kg·m^-3 in a 367.5 L tank, and at HP, nutrient solution was controlled with EC 1.3 dS·m^-1 and pH 6.5. The pH level ranged from 4.0 to 7.1 for the AP system and 4.0 to 7.4 for the HP system. The pH level in the AP began to decrease with an increase in nitrate nitrogen (NO₃-N) and lasted bellower than pH 5.5 for 15-67 DAT. It was found that ammonium nitrogen (NH₄-N) continued to increase even under low pH conditions. EC was maintained at 1.3 to 1.5 dS·m^-1 in both systems. The concentration of major mineral elements in the fish tank was higher than that of the hydroponics, except for K and Mg. There was no significant difference in the photosynthesis characteristics, but the PIABS parameters were 30.4% lower in the AP compared to the HP at the 34DAT and 12.0% lower at the 74DAT. There was no significant difference in the growth characteristics, but the petiole length was 56% longer in the leaf grown under the AP system. While there was no significant difference in the fresh and dry weights of leaf and root, the leaf area ratio was 36.43% higher in the AP system. All the integrated results suggest that aquaponics is a highly-sustainable farming to safely produce food by recycling agricultural by-products, and to produce Peucedanum japonicum as much as hydroponics under a proper fish density and pH level.

• Journal of Bio-Environment Control
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• v.31 no.1
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• pp.14-21
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• 2022

Uniform scions and rootstocks should be produced to ensure grafting success. Light quality is an important environmental factor that regulates seedling growth. The effects of warm- and cool-white light emitting diode (LED) ratios on seedling growth were investigated. Scions and rootstocks of cucumber, tomato, and watermelon were grown in a closed transplant production system using LED as the sole lighting source. The LED treatments were W1C0 (only warm-white), W1C1 (warm-white: cool-white = 1:1), W3C1 (warm-white: cool-white = 3:1), and W5C2 (warm-white: cool-white = 5:2). The seedlings grown in W1C1 had the shortest hypocotyls, and the seedlings grown in W1C0 had the longest hypocotyls among the three tested vegetables. The hypocotyls of watermelon scions, watermelon rootstocks, and tomato rootstocks were shortest in W1C1, followed by those in W3C1, W5C2, and W1C0, but there was no significant difference between W3C1 and W5C2, which remained the same as the ratio of cool-white LEDs increased. In addition, tomato scions had the first and second longest hypocotyls in W1C0 and W3C1, respectively, and the shortest hypocotyls in W5C2 and W1C1, along with W5C2 and W1C1, although the difference was not significant. The stem diameter was highest in W1C0 except for tomato seedlings and rootstocks of watermelon. The shoot fresh weight of scions and rootstocks of cucumber and watermelon and the root fresh weight of cucumber scions were lowest in W1C1. These results indicated that different ratios of LED lighting sources had a strong effect on the hypocotyl elongation of seedlings.

• Journal of Bio-Environment Control
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• v.31 no.1
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• pp.28-34
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• 2022

This study was conducted to determine the changes in ginsenosides content according to additional UV-A, and UV-B LED irradiation before harvesting the ginseng sprouts. One-year-old ginseng seedlings (n=100) were transplanted in a tray containing a ginseng medium. The ginseng sprouts were grown for 37 days at a temperature of 20℃ (24h), a humidity of 70%, and an average light intensity of 80 µmol·m^-2·s^-1 (photoperiod; 24h) in a container-type plant factory. Ginseng sprouts were then transferred to a custom chamber equipped with UV-A (370 nm; 12.90 W·m^-2) and UV-B (300 nm; 0.31 W·m^-2) LEDs and treated for 3 days. Growth parameters and ginsenoside contents in shoot and root were conducted by harvesting on days 0 (control), 1, 2, and 3 of UV treatments, respectively. The growth parameters showed non-significant differences between the control and the UV treatments (wavelengths or the number of days). Ginsenoside contents of the shoot was highly improved by 186% in UV-A treatment compared to the control in 3 days of the treatment time. The ginsenoside contents of the roots was more improved in UV-A 1-day treatment and UV-B 3-day treatment, compared to the control by 171% and 160%, respectively. As a result of this experiment, it is thought that UV LED irradiation before harvesting can produce sprout ginseng with high ginsenoside contents in a plant factory.

• Journal of the Korean earth science society
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• v.43 no.5
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• pp.604-617
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• 2022

Sea surface temperature (SST) is a key variable that can be used to understand ocean-atmosphere phenomena and predict climate change. Satellite microwave remote sensing enables the measurement of SST despite the presence of clouds and precipitation in the sensor path. Therefore, considering the high utilization of microwave SST, it is necessary to continuously verify its accuracy and analyze its error characteristics. In this study, the validation of the microwave global precision measurement (GPM)/GPM microwave imager (GMI) SST around the Northwest Pacific and Korean Peninsula was conducted using surface drifter temperature data for approximately eight years from March 2014 to December 2021. The GMI SST showed a bias of 0.09K and an average root mean square error of 0.97K compared to the actual SST, which was slightly higher than that observed in previous studies. In addition, the error characteristics of the GMI SST were related to environmental factors, such as latitude, distance from the coast, sea wind, and water vapor volume. Errors tended to increase in areas close to coastal areas within 300 km of land and in high-latitude areas. In addition, relatively high errors were found in the range of weak wind speeds (<6 m s^-1) during the day and strong wind speeds (>10 m s^-1) at night. Atmospheric water vapor contributed to high SST differences in very low ranges of <30 mm and in very high ranges of >60 mm. These errors are consistent with those observed in previous studies, in which GMI data were less accurate at low SST and were estimated to be due to differences in land and ocean radiation, wind-induced changes in sea surface roughness, and absorption of water vapor into the microwave atmosphere. These results suggest that the characteristics of the GMI SST differences should be clarified for more extensive use of microwave satellite SST calculations in the seas around the Korean Peninsula, including a part of the Northwest Pacific.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.707-723
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• 2022

Although satellite-based sea surface temperature (SST) is advantageous for monitoring large areas, spatiotemporal data gaps frequently occur due to various environmental or mechanical causes. Thus, it is crucial to fill in the gaps to maximize its usability. In this study, daily SST composite fields with a resolution of 4 km were produced through a two-step machine learning approach using polar-orbiting and geostationary satellite SST data. The first step was SST reconstruction based on Data Interpolate Convolutional AutoEncoder (DINCAE) using multi-satellite-derived SST data. The second step improved the reconstructed SST targeting in situ measurements based on light gradient boosting machine (LGBM) to finally produce daily SST composite fields. The DINCAE model was validated using random masks for 50 days, whereas the LGBM model was evaluated using leave-one-year-out cross-validation (LOYOCV). The SST reconstruction accuracy was high, resulting in R² of 0.98, and a root-mean-square-error (RMSE) of 0.97℃. The accuracy increase by the second step was also high when compared to in situ measurements, resulting in an RMSE decrease of 0.21-0.29℃ and an MAE decrease of 0.17-0.24℃. The SST composite fields generated using all in situ data in this study were comparable with the existing data assimilated SST composite fields. In addition, the LGBM model in the second step greatly reduced the overfitting, which was reported as a limitation in the previous study that used random forest. The spatial distribution of the corrected SST was similar to those of existing high resolution SST composite fields, revealing that spatial details of oceanic phenomena such as fronts, eddies and SST gradients were well simulated. This research demonstrated the potential to produce high resolution seamless SST composite fields using multi-satellite data and artificial intelligence.