The engineered barrier system of high-level radioactive waste disposal must maintain its performance in the long term, because it must play a role in slowing the rate of leakage to the surrounding rock mass even if a radionuclide leak occurs from the canister. In particular, it is very important to clarify gas dilation flow phenomenon clearly, that occurs only in a medium containing a large amount of clay material such as a bentonite buffer, which can affect the long-term performance of the bentonite buffer. Accordingly, DECOVALEX-2019 Task A was conducted to identify the hydraulic-mechanical mechanism for the dilation flow, and to develop and verify a new numerical analysis technique for quantitative evaluation of gas migration phenomena. In this study, based on the conventional two-phase flow and mechanical behavior with effective stresses in the porous medium, the hydraulic-mechanical model was developed considering the concept of damage to simulate the formation of micro-cracks and expansion of the medium and the corresponding change in the hydraulic properties. Model verification and validation were conducted through comparison with the results of 1D and 3D gas injection tests. As a result of the numerical analysis, it was possible to model the sudden increase in pore water pressure, stress, gas inflow and outflow rate due to the dilation flow induced by gas pressure, however, the influence of the hydraulic-mechanical interaction was underestimated. Nevertheless, this study can provide a preliminary model for the dilation flow and a basis for developing an advanced model. It is believed that it can be used not only for analyzing data from laboratory and field tests, but also for long-term performance evaluation of the high-level radioactive waste disposal system.
In this study, smart farm technology was used by farmers cultivating 'CHIKUMASSHU T-011' in order to develop an optimal growth model for the precision cultivation of bottle-grown winter mushroom and the results of the same are mentioned herein. Farmers participating in the experiment used 60 ㎡ of bed area with 4 rows and 13 columns of shelf shape, 20 horsepower refrigerator, 100T of sandwich panel for insulation, 6 ultrasonic humidifiers, 12 kW of heating, and 20,000 bottles of Flammulina velutipes mushroom spores. The temperature, humidity, and carbon dioxide concentrations, which directly affect the growth of the mushroom, were collected and analyzed from the environmental sensors installed at the winter mushroom cultivation area. The initial temperature was found to be 14.5℃, which was maintained at 14℃ to 15℃ until the 10th day. In the restriction phase, the initial temperature was 4℃ and was maintained between 2℃ and 3℃ until the 15th day, while during the growth phase, it was maintained between 7.5℃ to 9.5℃. Analysis of the humidity data revealed initial humidity to be 100%, which varied between 88% to 98% during primordia formation period. The humidity remained between 77% to 96% until the 15th day, in the restriction phase and between 75% to 83% during the growth phase. The initial carbon dioxide concentration was 3,500 ppm and varied between 3,500 ppm to 6,000 ppm during primordia formation period and was maintained at 6,000 ppm until the 15th day. During the growth phase, the carbon dioxide concentration was found to be over 6,000 ppm. Fruiting body characteristics of 'CHIKUMASSHU T-011' cultivated in the farmhouse were as follows: Pileus diameter of 7.5 mm and thickness of 4.1 mm, stipe thickness of 3.3 mm, and length of 154.2 mm. The number of valid fruiting bodies was 1,048 unit per 1,400 mL bottle, and the individual weight was 0.71 g per unit. The yield of fruiting bodies was 402.8 g per 1,400 mL bottle.
Kim, Mi-Hui;Na, Hyun-Jung;Chae, Ki-Joon;Bang, Hyo-Chan;Na, Jung-Chan
Journal of KIISE:Information Networking
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v.32
no.3
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pp.279-290
/
2005
Recently, as the serious damage caused by DDoS attacks increases, the rapid detection and the proper response mechanisms are urgent. However, existing security mechanisms do not effectively defend against these attacks, or the defense capability of some mechanisms is only limited to specific DDoS attacks. In this paper, we propose a detection architecture against DDoS attack using data mining technology that can classify the latest types of DDoS attack, and can detect the modification of existing attacks as well as the novel attacks. This architecture consists of a Misuse Detection Module modeling to classify the existing attacks, and an Anomaly Detection Module modeling to detect the novel attacks. And it utilizes the off-line generated models in order to detect the DDoS attack using the real-time traffic. We gathered the NetFlow data generated at an access router of our network in order to model the real network traffic and test it. The NetFlow provides the useful flow-based statistical information without tremendous preprocessing. Also, we mounted the well-known DDoS attack tools to gather the attack traffic. And then, our experimental results show that our approach can provide the outstanding performance against existing attacks, and provide the possibility of detection against the novel attack.
Companies are trying to use enterprise SNS for collaboration and speedy decision-making. This study verified the mediating effect of communication between enterprise SNS and job performance, and proved the moderating effect of nationality between enterprise SNS and communication. This study collected survey data of 81 Korean and 81 Chinese from employees who have used enterprise SNS in Korea and China. As results of data analysis, first, enterprise SNS improved job performance through speedy information sharing and error reduction. Second, communication mediated the effect of enterprise SNS on job performance. Third, enterprise SNS increased the level of organizational communication through decreasing the burden of offline face-to-face communication. Compared with Chinese corporate organizations, Korean corporate organizations have high power distances, centralized control, and high superior authority. Therefore, in the off-line communication situation, the subordinate feels the social pressure to follow the command of the superior. Thus communication is one-way and closed. In this Korean organizational situation, corporate SNS can be used as a means to bypass rigid offline communication. In the online communication environment of non face-to-face corporate SNS, anxiety and stress of face-to-face communication can be reduced, so communication between the upper and lower sides can flow more smoothly. The contribution of this paper is that it proved that enterprise SNS promotes communication and improve job performance by reducing the anxiety or stress of offline communication, while according to prior research successful adoption of many types of information systems requires the fit between an organization and its organizational culture.
This study was carried out to separate the heavy toxic metals in eco-building materials by low-temperature pyrolysis, especially arsenic (As) compounds in CCA wood preservative as a solid in char. The pyrolysis was carried out to heat the CCA-treated Hemlock at $280^{\circ}C$, $300^{\circ}C$, $320^{\circ}C$, and $340^{\circ}C$ for 60 mins. Laboratory scale pyrolyzer composed of [preheater$\rightarrow$pyrolyzer$\rightarrow$1st water scrubber$\rightarrow$2nd bubbling flask with 1% $HNO_3$ solution$\rightarrow$vent], and was operated to absorb the volatile metal compound particulates at the primary water scrubber and the secondary nitric acid bubbling flask with cooling condenser of $4^{\circ}C$ under nitrogen stream of 20 mL/min flow rate. And the contents of copper, chromium and arsenic compounds in its pyrolysis such as carbonized CCA treated wood, 1st washing and 2nd washing liquors as well as its raw materials, were determined using ICP-AES. The results are as follows : 1. The yield of char in low-temperature pyrolysis reached about 50 percentage similar to the result of common pyrolytic process. 2. The higher the pyrolytic temperature was, the more the volatiles of CCA, and in particular, the arsenic compounds were to be further more volatile above $320^{\circ}C$, even though the more repetitive and sequential monitorings were necessary. 3. More than 85 percentage of CCA in CCA-treated wood was left in char in such low-temperature pyrolytic condition at $300^{\circ}C$. 4. Washing system for absorption of volatile CCA in this experiment required much more contacting time between volatile gases and water to prevent the loss of CCA compounds, especially the loss of arsenic compound. 5. Therefore, more complete recovery of CCA components in CCA-treated wood required the lower temperature than $320^{\circ}C$, and the longer contacting time of volatile gases and water needed the special washing and recovery system to separate the toxic and volatile arsenic compounds in vent gases.
Multifunctionality of agriculture which is not traded on the market now has been an important international issue in that it environmental and public benefits. We carried out to modify and to update the function of upland farming on flood prevention and fostering water resources. Economic values of environmental benefits were evaluated by replacement cost methods. Models to evaluate the function of preventing flood were selected as: (1)precipitation(flood-inducing) - runoff(A), (2) soil depth ${\times}$ soil air phase, (3) precipitation (flood-inducing) - runoff(B), (4) soil depth ${\times}$ effective porosity of soil. Models to estimate the function of fostering water resources were (1) saturated hydraulic conductivity (Ks) ${\times}$ duration of saturation(days) ${\times}$ (1-ratio of water flow directly into river), (2) precipitation ${\times}$ ratio of water fostered by rain resources ${\times}$ (area of upland/total land area), and (3) soil water retention quantity(under standing crop or tree) - SWRQ(in bare soil). Function of preventing flood was $883Mg\;ha^{-1}$ of water per year and 645 million Mg for the whole upland area. Function of fostering water resources was $94.1Mg\;ha^{-1}$ of water per year and 69 million Mg for the whole upland area. The value of flood-preventing function evaluated by replacement cost methods was estimated 1,428 billion won per year as compared to the cost for dam construction. The value of water resource fostering were estimated 8.6 billion won in the price of living water.
Journal of The Korean Society of Inherited Metabolic disease
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v.19
no.1
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pp.1-11
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2019
Purpose: Congenital hypothyroidism (CH) is the most common congenital endocrine disorder. The purpose of the present study was to determine the incidence of CH in South Korea during the period from January 1991 to March 2004. Methods: Central data from each city branch of SCL (Seoul Clinical Reference Laboratories) in Yongin, South Korea, was gathered and collectively analyzed. Newborn screening (NBS) for CH was based on measuring the levels of neonatal thyroid stimulating hormone (TSH) and free T4 (a cut-off of 20 mIU/L and less than 0.8 ng/dL, respectively). Results: During the study period, 671,805 live births were screened for CH based on TSH and free T4 ELISA assays. A total of 159 newborns were deemed positive for CH out of 671,805, with a corresponding incidence of 1 in 4,225. When a cut-off of 20 mIU/L was used in TSH assays, the associated sensitivity, specificity, and positive predictive values (PPV) were 100.0%, 99.7%, and 10.8%, respectively. When a cut-off of 0.8 ng/dL in free T4 assays was used, the associated sensitivity, specificity, and PPV were 100.0%, 98.5%, and 3.9%, respectively. Conclusion: CH incidence in South Korea as evidenced by the results of NBS was compared with its incidence and comparable to the other countries prior to 2004.
Jeong, Dae Hui;Kim, Ki Yoon;Park, Sung Hyuk;Jung, Chung Ryul;Jeon, Kwon Seok;Park, Hong Woo
Korean Journal of Plant Resources
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v.34
no.4
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pp.287-296
/
2021
Recently, the pace of global climate change has tremendously increased, causing extreme damage to crop production. Here, we aimed to examine the growth characteristics and useful components of Angelica gigas under extreme heat stress, providing fundamental data for its efficient cultivation. Plants were exposed to various experimental temperatures (28℃, 34℃, and 40℃), and their growth characteristics and content of useful components were analyzed. At the experimental site, the ambient and soil temperature were 19.38℃ and 21.34℃, ambient and soil humidity were 81.3 % and 0.18 m3/m3, solar radiation was 162.05 W/m2. Moreover, the soil was sandy-clay-loam (pH 6.65), with 2.66% organic matter, 868.52 mg/kg soil available phosphate, and 0.14% nitrogen. Values of most growth characteristics, including the survival rate (85%), plant height (38.66cm), and fresh and dry weight (41.3 g and 14.24 g), were the highest at 28℃. Although the highest content of useful components was observed at 34℃ (3.24%), there were no significant differences across temperatures. Growth characteristics varied across temperatures due to detrimental effects of heat stress, such as accelerated tissue aging, reduced photosynthesis, and delay of growth. Similar content of useful components across temperatures may be due to poor accumulation of anabolic products caused by impaired growth at extremely high temperatures.
Heo, Sol;Shin, Chung Hun;Jeong, Hyun Sook;Yoo, Soon Mi;Kim, Jeong Mi;Yun, In Ha;Hong, Seung Mo;Back, Geum Mun
The Journal of Korean Society for Radiation Therapy
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v.33
/
pp.47-54
/
2021
Purpose : In order to evaluate the usefulness of clinical application of the Pause & Resume methods by comparing and analyzing the data stability and dose reduction effect when repeat scan assuming irregular breathing and using the Pause & Resume method during chest 4D CT using QuasarTM Phantom. Materials and Methods : Using the QuasarTM Phantom, set the breathing rate per minute to 15 BPM and 7.5 BPM, and set the S15 point as an irregular breathing section, and then placed OSLD to this point and use the Pause & Resume method to measure the dose of S15. CTDIvol, DLP, and ALARA-CT were used for comparative analysis of radiation dose between Pause & Resume method and Repeat-scan. In order to evaluate the stability and usability of the data applying the Pause & Resume method, the captured images were sorted by Advanced Workstation Volume Share7 and then sent to EclipseTM, the diameter and volume were analyzed by forming a contour on the iron ball in the QuasarTM Phantom Results : When using Pause & Resume, the dose of OSLD measurement increased by 1.97 times in the section of S15. As a result of image evaluation, the average value of all volumes measured with and without the Pause & Resume method at 15 BPM and 7.5 BPM was 15.2 cm3±0.5%.Allthemeasuredvaluesfor the radius of iron ball were 3.1 cm regardless of whether Pause & Resume method was used or not. In the case of using Pause & Resume, 33% decreased from the lowest DLP value and 38% decreased from the highest DLP value of repeat scan, and the effective dose also decreased 32.1% from the minimum value and 37.6% from the maximum value. Conclusion: Irradiation dose was increased by Pause & Resume method because of the repeat scan on the S15 site where assuming irregular breathing occurred, However Pause & Resume method led to a significant reduction in dose on overall scan range. It also proved the usefulness of clinical application of the Pause & Resume method as a result of similar diameters and volumes of iron ball measurement.
Agricultural reservoirs are an important water resource nationwide and vulnerable to abnormal climate effects such as drought caused by climate change. Therefore, it is required enhanced management for appropriate operation. Although water-level tracking is necessary through continuous monitoring, it is challenging to measure and observe on-site due to practical problems. This study presents an objective comparison between multiple AI models for water-body extraction using radar images that have the advantages of wide coverage, and frequent revisit time. The proposed methods in this study used Sentinel-1 Synthetic Aperture Radar (SAR) images, and unlike common methods of water extraction based on optical images, they are suitable for long-term monitoring because they are less affected by the weather conditions. We built four AI models such as Support Vector Machine (SVM), Random Forest (RF), Artificial Neural Network (ANN), and Automated Machine Learning (AutoML) using drone images, sentinel-1 SAR and DSM data. There are total of 22 reservoirs of less than 1 million tons for the study, including small and medium-sized reservoirs with an effective storage capacity of less than 300,000 tons. 45 images from 22 reservoirs were used for model training and verification, and the results show that the AutoML model was 0.01 to 0.03 better in the water Intersection over Union (IoU) than the other three models, with Accuracy=0.92 and mIoU=0.81 in a test. As the result, AutoML performed as well as the classical machine learning methods and it is expected that the applicability of the water-body extraction technique by AutoML to monitor reservoirs automatically.
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