• Korean Journal of Soil Science and Fertilizer
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• v.44 no.5
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• pp.779-787
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• 2011

This study was conducted to evaluate the usefulness of ground-based remote sensing for the estimation of rice yield and application rate of N-fertilizer during growing season. Dongjin-1, Korean cultivar of rice was planted on May 30, 2006 and harvested on October 9, 2006. Chlorophyll content and LAI (leaf area index) were measured using Minolta SPAD-502 and AccuPAR model LP-80, respectively. Reflectance indices were determined with passive sensors using sunlight and four types of active sensors using modulated light, respectively. Reflectance indices and growth rate were measured three times from 29 days to 87 days after rice plating and at harvesting day. The result showed that values of growing characteristics and reflectance indices were highly correlated. Growing characteristics to show significant correlation with reflectance indices were in order of followings: fresh weight > N uptake > dry weight > height > No. of tiller > N content. Chlorophyll contents measured by chlorophyll meter (SPAD 502) showed high correlation with nitrogen concentration (r=$0.743^{**}$), although the correlation coefficients between remote sensing data and nitrogen concentration were higher. LAI was highly correlated with dry weight (r=$0.931^{**}$), but relationship between LAI and nitrogen concentration (r=$0.505^*$) was relatively low. The data of CC-passive sensor were negatively correlated with those of the near-infrared. NDVI correlation coefficients found more useful to identify the growth characteristics rather than data from single wavelength. Both passive sensor and active sensor were highly significantly correlated with growth characteristics. Consequently, quantifying the growth characteristics using reflectance indices of ground-based remote sensing could be a useful tool to determine the application rate of N fertilizer non-destructively and in real-time.

• Journal of Korea Water Resources Association
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• v.54 no.10
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• pp.819-833
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• 2021

This study is to evaluate applicability of linkage modeling using PHABSIM (Physical Habitat Simulation System) and SWAT (Soil and Water Assessment Tool) and to estimate ecological flow for target fishes of Andong downstream (4,565.7 km²). The SWAT was established considering 2 multi purpose dam (ADD, IHD) and 1 streamflow gauging station (GD). The SWAT was calibrated and validated with 9 years (2012 ~ 2020) data of 1 stream (GD) and 2 multi-purpose dam (ADD, IHD). For streamflow and dam inflows (GD, ADD and IHD), R², NSE and RMSE were 0.52 ~ 0.74, 0.48 ~ 0.71, and 0.92 ~ 2.51 mm/day respectively. As a result of flow duration analysis for 9 years (2012 ~ 2020) using calibrated streamflow, the average Q185 and Q275 were 36.5 m³/sec (-1.4%) and 23.8 m³/sec (0%) respectively compared with the observed flow duration and were applied to flow boundary condition of PHABSIM. The target stream was selected as the 410 m section where GD is located, and stream cross-section and hydraulic factors were constructed based on Nakdong River Basic Plan Report and HEC-RAS. The dominant species of the target stream was Zacco platypus and the sub-dominant species was Puntungia herzi Herzenstein, and the HSI (Habitat Suitability Index) of target species was collected through references research. As the result of PHABSIM water level and velocity simulation, error of Q185 and Q275 were analyzed -0.12 m, +0.00 m and +0.06 m/s, +0.09 m/s respectively. The average WUA (Weighted Usable Area) and ecological flow of Zacco platypus and Puntungia herzi Herzenstein were evaluated 76,817.0 m²/1000m, 20.0 m³/sec and 46,628.6 m²/1000m, 9.0 m³/sec. This results indicated Zacco platypus is more adaptable to target stream than Puntungia herzi Herzenstein.

• Journal of Bio-Environment Control
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• v.30 no.4
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• pp.419-428
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• 2021

In order to develope a mobile-based greenhouse energy calculation program, firstly, the overall thermal transmittance of 10 types of major covers and 16 types of insulation materials were measured. In addition, to estimate the overall thermal transmittance when the cover and insulation materials were installed in double or triple layers, 24 combinations of double installations and 59 combinations of triple installations were measured using the hotbox. Also, the overall thermal transmittance value for a single material and the thermal resistance value were used to calculate the overall thermal transmittance value at the time of multi-layer installation of covering and insulating materials, and the linear regression equation was derived to correct the error with the measured values. As a result of developing the model for estimating thermal transmittance when installing multiple layers of coverings and insulating materials based on the value of overall thermal transmittance of a single-material, the model evaluation index was 0.90 (good when it is 0.5 or more), indicating that the estimated value was very close to the actual value. In addition, as a result of the on-site test, it was evaluated that the estimated heat saving rate was smaller than the actual value with a relative error of 2%. Based on these results, a mobile-based greenhouse energy calculation program was developed that was implemented as an HTML5 standard web-based mobile web application and was designed to work with various mobile device and PC browsers with N-Screen support. It had functions to provides the overall thermal transmittance(heating load coefficient) for each combination of greenhouse coverings and thermal insulation materials and to evaluate the energy consumption during a specific period of the target greenhouse. It was estimated that an energy-saving greenhouse design would be possible with the optimal selection of coverings and insulation materials according to the region and shape of the greenhouse.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.7
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• pp.271-278
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• 2021

As the current cyber attacks become more intelligent, the existing Intrusion Detection System is difficult for detecting intelligent attacks that deviate from the existing stored patterns. In an attempt to solve this, a model of a deep learning-based intrusion detection system that analyzes the pattern of intelligent attacks through data learning has emerged. Intrusion detection systems are divided into host-based and network-based depending on the installation location. Unlike network-based intrusion detection systems, host-based intrusion detection systems have the disadvantage of having to observe the inside and outside of the system as a whole. However, it has the advantage of being able to detect intrusions that cannot be detected by a network-based intrusion detection system. Therefore, in this study, we conducted a study on a host-based intrusion detection system. In order to evaluate and improve the performance of the host-based intrusion detection system model, we used the host-based Leipzig Intrusion Detection-Data Set (LID-DS) published in 2018. In the performance evaluation of the model using that data set, in order to confirm the similarity of each data and reconstructed to identify whether it is normal data or abnormal data, 1D vector data is converted to 3D image data. Also, the deep learning model has the drawback of having to re-learn every time a new cyber attack method is seen. In other words, it is not efficient because it takes a long time to learn a large amount of data. To solve this problem, this paper proposes the Siamese Convolutional Neural Network (Siamese-CNN) to use the Few-Shot Learning method that shows excellent performance by learning the little amount of data. Siamese-CNN determines whether the attacks are of the same type by the similarity score of each sample of cyber attacks converted into images. The accuracy was calculated using Few-Shot Learning technique, and the performance of Vanilla Convolutional Neural Network (Vanilla-CNN) and Siamese-CNN was compared to confirm the performance of Siamese-CNN. As a result of measuring Accuracy, Precision, Recall and F1-Score index, it was confirmed that the recall of the Siamese-CNN model proposed in this study was increased by about 6% from the Vanilla-CNN model.

• The Korean Journal of Archival Studies
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• no.23
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• pp.3-43
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• 2010

Finding aids are tools which facilitate to locate and understand archives and records. Traditionally there are two types of archival finding aids: vertical and horizontal. Vertical finding aids such as inventories have multi-level descriptions based on provenance, while horizontal ones such as catalogs and index are tools to guide to the vertical finding aids based on the subject. In the web environment, traditional finding aids are evolving into more dynamic forms. Respecting the principles of provenance and original order, vertical finding aids are changing to multi-entity structures with development of ISAD(G), ISAAR(CPF) and ISDF as standards for describing each entity. However, vertical finding aids can be too difficult, complicated, and boring for many users, who are accustomed to the easy and exciting searching tools in the internet world. Complementing them, new types of finding aids are appearing to provide easy, interesting, and extensive access channels. This study investigates the development and limitation of vertical finding aids, and the recent trend of evolving new finding aids complementing the vertical ones. The study finds three new trends of finding aid development. They are (i) mixture, (ii) integration, and (iii) openness. In recent days, certain finding aids are mixed with stories and others provide integrated searches for the collections of various heritage institutions. There are cases for experimenting user participation in the development of finding aids using Web 2.0 applications. These new types of finding aids can also cause some problems such as decontextualised description and prejudices, especially in the case of mixed finding aids and quality control of user contributed annotations and comments. To solve these problems, the present paper suggests to strengthen the infrastructure of vertical finding aids and to connect them with various new ones and to facilitate interactions with users of finding aids. It is hoped that the present paper will provide impetus for archives including the National Archives of Korea to set up and evaluate the development strategies for archival finding aids.

• The Korean Journal of Vision Science
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• v.20 no.4
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• pp.543-551
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• 2018

Purpose : The purposes of this study were to evaluate the changes of intraocular pressure according to corneal ablation amount after corneal refractive surgery and the changes of intraocular pressure according to refractive errors before corneal refractive surgery. Methods : The mean age of adults who underwent LASIK corneal refractive surgery were $37.34{\pm}7.42years$, and 108 adults(48 males, 60 females) were participated in this study. Refractive errors, intraocular pressure, and corneal ablation amount were measured using an autorefractor, a noncontact tonometer, and an excimer laser. All test values were considered statistically significant when p<0.05. Results : The mean intraocular pressure before corneal refractive surgery was $15.08{\pm}2.60mmHg$ in males and $14.16{\pm}2.67mmHg$ in females. The decrease of intraocular pressure after corneal refractive surgery were 4.22mmHg in males and 3.61mmHg in females. Spherical equivalent power were $-3.89{\pm}2.17D$ in males and $-4.45{\pm}2.92D$ in females before corneal refractive surgery, and $-0.10{\pm}0.46D$ in males and $-0.04{\pm}0.46D$ in females after corneal refractive surgery. The corneal ablation amount after corneal refractive surgery were statistically significant, with $53.95{\mu}m$ in males and $61.26{\mu}m$ in females. There was significant correlation between corneal ablation amount and decrease of intaocluar pressure(r=0.2299, p<0.001). As the growth of corneal ablation amount in males, the decrease of intraocular pressure was significantly increased. As the growth of refractive error, the amount of decrease in intraocular pressure was also significant. The decrease of intraocualr pressure were $3.04{\pm}2.18mmHg$ in low refractive error, $4.10{\pm}2.16mmHg$ in middle refractive error, and $4.65{\pm}3.29mmHg$ in high refractive error. Conclusion : We found that intraocular pressure decreased after corneal refractive surgery by noncontact tonometer and the change of intraocular pressure which is an important index for glaucoma diagnosis, may affect the judgment of eye disease. We think that a preliminary questionnaire whether corneal refractive surgery is necessary for the measurement of intraocular pressure.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.29 no.2
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• pp.87-93
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• 2018

Background and Objectives : Laryngopharyngeal reflux disease (LPRD) is relatively common disease. N-acetyl cysteine (NAC) has both mucolytic and antioxidant effect, also may be beneficial in inflammatory airway diseases. The purpose of this study was to evaluate the efficacy and safety of inhaled NAC therapy in LPRD. Materials and Method : We retrospectively reviewed the medical records of 525 LPRD patients at 12 medical centers. Finally 401 patients subjected to inhaled NAC therapy for 2 months were enrolled in the study. We analyzed the change of Reflux Symptom Index (RSI) and Reflux Finding Score (RFS) after use of NAC for 4 weeks and 8 weeks in addition to the patient's compliance of the treatment. Results : The RSI score significantly decreased from $19.87{\pm}6.34$ to $12.78{\pm}6.93$ after 4 weeks and to $10.65{\pm}7.47$ after 8 weeks. The RFS score also significantly decreased from $9.29{\pm}3.4$ to $7.17{\pm}3.41$ after 4 weeks and to $6.1{\pm}3.73$ after 8 weeks (p<0.05). During the treatment periods, 42 patients (10.4%) reported to have 80 episodes of discomfort. Throat discomfort (33%) and nausea (28%) were most common complaints, but the duration of discomfort was usually less than 4 weeks. Conclusion : Inhaled NAC treatment is highly effective for the reduction of both subjective and objective findings in LPRD patients. This study will provide the evidence of new treatment option for patients with LPRD. However, further studies will be needs to assess the real effect of inhaled NAC therapy as a standard treatment regimen of LPRD.

• Journal of Environmental Impact Assessment
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• v.27 no.6
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• pp.548-561
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• 2018

The objectives of this study were to construct a three-dimensional (3D) hydrodynamic and water quality model (EFDC) for the river reach between the Daecheong dam and the Sejong weir, which are directly affected by Gap and Miho streams located in the middle of the Geum River, and to evaluate the trophic status and water quality improvement effect according to the flow control and pollutant load reduction scenarios. The EFDC model was calibrated with the field data including waterlevel, temperature and water quality collected from September, 2012 to April, 2013. The model showed a good agreement with the field data and adequately replicated the spatial and temporal variations of water surface elevation, temperature and water quality. Especially, it was confirmed that spatial distributions of nutrients and algae biomass have wide variation of transverse direction. Also, from the analysis of algal growth limiting factor, it was found that phosphorous loadings from Gap and Miho streams to Sejong weir induce eutrophication and algal bloom. The scenario of pollutant load reduction from Gap and Miho streams showed a significant effect on the improvement of water quality; 4.7~18.2% for Chl-a, 5.4~21.9% for TP at Cheongwon-1 site, and 4.2~ 17.3% for Chl-a and 4.7~19.4% for TP at Yeongi site. In addition, the eutrophication index value, identifying the tropic status of the river, was improved. Meanwhile, flow control of Daecheong Dam and Sejong weir showed little effect on the improvement of water quality; 1.5~2.4% for Chl-a, 2.5~ 3.8% for TP at Cheongwon-1 site, and 1.2~2.1% for Chl-a and 0.9~1.5% for TP at Yeongi site. Therefore, improvement of the water quality in Gap and Miho streams is essential and a prerequirement to meet the target water quality level of the study area.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.24 no.1
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• pp.54-63
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• 2019

As a part of the national marine ecosystem monitoring program, the temporal and spatial variation of sedimentary environment and pollution of organic matters and trace metals from four major tidal flats, i.e., Ganghwa Is., Garolim bay, Jeung Is., Suncheon bay, was investigated for 3 yerars from 2015 to 2017. The mean grain size of the sediment was $5.0-5.3{\varnothing}$ at Ganghwa Is, $4.5-4.8{\varnothing}$ at Garolim bay, $6.1-6.5{\varnothing}$ at Jeung Is, and $8.6-8.7{\varnothing}$ at Suncheon bay. The mean grain size (Mz) tended to decrease from the north (Ganghwa Is.) to the south (Suncheon bay). The ignition loss (IL) was 15.5% in Suncheon bay in 2015, which was relatively high compared to other sites, but gradually decreased over time from 8.3% in 2016 to 7.0% in 2017. In Jeung Is. and Suncheon bay, the concentration of Zn and As exceeded the threshold effect level (TEL) at some stations, but the range of trace metals in the other sites was below the level. In Jeung Is., the Mz and concentration of trace metals except Hg was positively correlated (r= 0.40-0.88, P<0.05). On the other hand, Mz was negatively correlated with trace metals (P<0.05) in Suncheon bay. The geoaccumulation index ($I_{geo}$) to evaluate contamination status of sediments for trace metal was less than 1(not contaminated) for Cu, Zn, Pb, Cd and Hg, and 2-3 (moderately to strongly polluted) for As at several stations in Suncheon bay and Jeung Is.

• Journal of Korea Water Resources Association
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• v.53 no.12
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• pp.1159-1172
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• 2020

This study applied deep convolution neural network based on U-Net and SegNet using long period weather radar data to very short-term rainfall prediction. And the results were compared and evaluated with the translation model. For training and validation of deep neural network, Mt. Gwanak and Mt. Gwangdeoksan radar data were collected from 2010 to 2016 and converted to a gray-scale image file in an HDF5 format with a 1km spatial resolution. The deep neural network model was trained to predict precipitation after 10 minutes by using the four consecutive radar image data, and the recursive method of repeating forecasts was applied to carry out lead time 60 minutes with the pretrained deep neural network model. To evaluate the performance of deep neural network prediction model, 24 rain cases in 2017 were forecast for rainfall up to 60 minutes in advance. As a result of evaluating the predicted performance by calculating the mean absolute error (MAE) and critical success index (CSI) at the threshold of 0.1, 1, and 5 mm/hr, the deep neural network model showed better performance in the case of rainfall threshold of 0.1, 1 mm/hr in terms of MAE, and showed better performance than the translation model for lead time 50 minutes in terms of CSI. In particular, although the deep neural network prediction model performed generally better than the translation model for weak rainfall of 5 mm/hr or less, the deep neural network prediction model had limitations in predicting distinct precipitation characteristics of high intensity as a result of the evaluation of threshold of 5 mm/hr. The longer lead time, the spatial smoothness increase with lead time thereby reducing the accuracy of rainfall prediction The translation model turned out to be superior in predicting the exceedance of higher intensity thresholds (> 5 mm/hr) because it preserves distinct precipitation characteristics, but the rainfall position tends to shift incorrectly. This study are expected to be helpful for the improvement of radar rainfall prediction model using deep neural networks in the future. In addition, the massive weather radar data established in this study will be provided through open repositories for future use in subsequent studies.