• Journal of Korean Society of Environmental Engineers
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• v.36 no.6
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• pp.421-428
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• 2014

For the analysis of water supply network, demand-driven and pressure-driven analysis methods have been proposed. Of the two methods, demand-driven analysis (DDA) can only be used in a normal operation condition to evaluate hydraulic status of a pipe network. Under abnormal conditions, i.e., unexpected pipe destruction, or abnormal low pressure conditions, pressure-driven analysis (PDA) method should be used to estimate the suppliable flowrate at each node in a network. In order to carry out the pressure-driven analysis, head-outflow relationship (HOR), which estimates flowrate at a certain pressure at each node, should be first determined. Most previous studies empirically suggested that each node possesses its own characteristic head-outflow relationship, which, therefore, requires verification by using actual field data for proper application in PDA modeling. In this study, a model pipe network was constructed, and various operation scenarios of normal and abnormal conditions, which cannot be realized in real pipe networks, were established. Using the model network, data on pressure and flowrate at each node were obtained at each operation condition. Using the data obtained, previously proposed HOR equations were evaluated. In addition, head-outflow relationship at each node was analyzed especially under multiple pipe destruction events. By analyzing the experimental data obtained from the model network, it was found that flowrate reduction corresponding to a certain pressure drop (by pipe destruction at one or multiple points on the network) followed intrinsic head-outflow relationship of each node. By comparing the experimentally obtained head-outflow relationship with various HOR equations proposed by previous studies, the one proposed by Wagner et al. showed the best agreement with the exponential parameter, m of 3.0.

• Economic and Environmental Geology
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• v.31 no.3
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• pp.185-199
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• 1998

Hydrogeochemical and environmental isotope studies were undertaken for various kinds of water samples collected in 1995-1996 from the Bugok geothermal area. Physicochemical data indicate the occurrence of three distinct groups of natural water: Group I ($Na-S0_4$ type water with high temperatures up to $77^{\circ}C$, occurring from the central part of the geothermal area), Group II (warm $Na-HCO_{3}-SO_{4}$ type water, occurring from peripheral sites), Group III ($Ca-HCO_3$ type water, occurring as surface waters and/or shallow cold groundwaters). The Group I waters are further divided into two SUbtypes: Subgroup Ia and Subgroup lb. The general order of increasing degrees of hydrogeochemical evolution (due to the degrees of water-rock interaction) is: Group III$\rightarrow$Group II$\rightarrow$Group I. The Group II and III waters show smaller degrees of interaction with rocks (largely calcite and Na-plagioclase), whereas the Group I waters record the stronger interaction with plagioclase, K-feldspar, mica, chlorite and pyrite. The concentration and sulfur isotope composition of dissolved sulfate appear as a key parameter to understand the origin and evolution of geothermal waters. The sulfate was derived not only from oxidation of sedimentary pyrites in surrounding rocks (especially for the Subgroup Ib waters) but also from magmatic hydrothermal pyrites occurring in restricted fracture channels which extend down to a deep geothermal reservoir (typically for the Subgroup Ia waters). It is shown that the applicability of alkaliion geothermometer calculations for these waters is hampered by several processes (especially the mixing with Mg-rich near-surface waters) that modify the chemical composition. However, the multi-component mineral/water equilibria calculation and available fluid inclusion data indicate that geothermal waters of the Bugok area reach temperatures around $125^{\circ}C$ at deep geothermal reservoir (possibly a cooling pluton). Environmental isotope data (oxygen-18, deuterium and tritium) indicate the origin of all groups of waters from diverse meteoric waters. The Subgroup Ia waters are typically lower in O-H isotope values and tritium content, indicating their derivation from distinct meteoric waters. Combined with tritium isotope data, the Subgroup Ia waters likely represent the older (at least 45 years old) meteoric waters circuated down to the deep geothermal reservoir and record the lesser degrees of mixing with near-surface waters. We propose a model for the genesis and evolution of sulfate-rich geothermal waters.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.119-142
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• 2015

With the explosive growth in the volume of information, Internet users are experiencing considerable difficulties in obtaining necessary information online. Against this backdrop, ever-greater importance is being placed on a recommender system that provides information catered to user preferences and tastes in an attempt to address issues associated with information overload. To this end, a number of techniques have been proposed, including content-based filtering (CBF), demographic filtering (DF) and collaborative filtering (CF). Among them, CBF and DF require external information and thus cannot be applied to a variety of domains. CF, on the other hand, is widely used since it is relatively free from the domain constraint. The CF technique is broadly classified into memory-based CF, model-based CF and hybrid CF. Model-based CF addresses the drawbacks of CF by considering the Bayesian model, clustering model or dependency network model. This filtering technique not only improves the sparsity and scalability issues but also boosts predictive performance. However, it involves expensive model-building and results in a tradeoff between performance and scalability. Such tradeoff is attributed to reduced coverage, which is a type of sparsity issues. In addition, expensive model-building may lead to performance instability since changes in the domain environment cannot be immediately incorporated into the model due to high costs involved. Cumulative changes in the domain environment that have failed to be reflected eventually undermine system performance. This study incorporates the Markov model of transition probabilities and the concept of fuzzy clustering with CBCF to propose predictive clustering-based CF (PCCF) that solves the issues of reduced coverage and of unstable performance. The method improves performance instability by tracking the changes in user preferences and bridging the gap between the static model and dynamic users. Furthermore, the issue of reduced coverage also improves by expanding the coverage based on transition probabilities and clustering probabilities. The proposed method consists of four processes. First, user preferences are normalized in preference clustering. Second, changes in user preferences are detected from review score entries during preference transition detection. Third, user propensities are normalized using patterns of changes (propensities) in user preferences in propensity clustering. Lastly, the preference prediction model is developed to predict user preferences for items during preference prediction. The proposed method has been validated by testing the robustness of performance instability and scalability-performance tradeoff. The initial test compared and analyzed the performance of individual recommender systems each enabled by IBCF, CBCF, ICFEC and PCCF under an environment where data sparsity had been minimized. The following test adjusted the optimal number of clusters in CBCF, ICFEC and PCCF for a comparative analysis of subsequent changes in the system performance. The test results revealed that the suggested method produced insignificant improvement in performance in comparison with the existing techniques. In addition, it failed to achieve significant improvement in the standard deviation that indicates the degree of data fluctuation. Notwithstanding, it resulted in marked improvement over the existing techniques in terms of range that indicates the level of performance fluctuation. The level of performance fluctuation before and after the model generation improved by 51.31% in the initial test. Then in the following test, there has been 36.05% improvement in the level of performance fluctuation driven by the changes in the number of clusters. This signifies that the proposed method, despite the slight performance improvement, clearly offers better performance stability compared to the existing techniques. Further research on this study will be directed toward enhancing the recommendation performance that failed to demonstrate significant improvement over the existing techniques. The future research will consider the introduction of a high-dimensional parameter-free clustering algorithm or deep learning-based model in order to improve performance in recommendations.

• Korean Journal of Soil Science and Fertilizer
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• v.33 no.2
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• pp.92-99
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• 2000

To compare the effect of food waste compost(FWC) application on the sodicity of paddy and upland soil, laboratory experiment was conducted. Six kinds of FWC made of various mixing ratio of food waste and pig slurry as raw material were applied to paddy soil under submerged condition and to upland soil in field water capacity, and were kept at $25^{\circ}C$ under laboratory incubation. The higher the mixing ratio of food waste on making FWC, the higher the FWC showed Na content and EC. Mineralized ratio of cations in FWC during incubation showed no difference between paddy and upland soil. It was high in the order of Na>K>Mg>Ca as 99, 94, 71, and 71%, respectively. NaCl contents of FWC applied to soils against SAR and ESP were fitted well to first linear regression with extremely high significance($R^2=0.99$). Increasing rate of SAR and ESP was higher in upland soil than paddy soil by 2.3 times. The difference was considered to be caused by dilution effect which was exerted by the application of more soil to water ratio to paddy soil than to upland soil on SAR analysis in consideration of cultivating condition. The calculated values of $([Ca^{2+}+Mg^{2+}]/2)^{1/2}$ used as a denominator on SAR calculation showed a little difference among FWC treatments by 2.1~2.4, while [$Na^+$] used as a numerator showed much variance by 3.1~9.5. Therefore, as a parameter for the assessment of FWC quality affecting soil sodicity, the use of only Na content in FWC was proposed without regarding Ca and Mg contents. Soil Ex. Na contents showed extremely high correlation($R^2=0.99$) with ESP. Moreover, because the former can be more easily determined than the latter, soil Ex. Na content was proposed as a new sodicity index.

• Korean Journal of Plant Tissue Culture
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• v.25 no.4
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• pp.257-261
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• 1998

The repeated subcultures of in vitro plant materials in wasabi became highly vitrified and the capacity for multiple shoot formation from the vitrified plant materials was very low. In order to improve the quality of in vitro propagated planting materials, the experiments were carried out using culture vessels capped with membrane filter(MF). When vitrified shoots were cultured on MS medium with 0.2mg/L BA in the vessels with MF or without MF for 60 days, the shoots in the vessels with MF did not vitrified. In contrast, the shoots grown in the vessels without MF vitrified at 65%. The stomates of vitrified leaves were circular and inflated, whereas those of normal leaves acclimatizated in the vessels with MF were ovate in shape. The hardened shoots were also cultured on MS media without sucrose containing 0.01mg/L IBA in vessels with(photoautotrophic culture) or without(control) MF. Sucrose was necessary for survival of the in vitro plantlets in the vessels without MF. After 20 days of culture, the shoots in the vessels without MF on the sucrose-free media turned yellow and died. But the shoots in the vessels with MF in the sucrose-free media produced a lot of roots. When shoots were cultured on MS medium with 2% sucrose containing 0.01mg/L IBA in the vessels with(photomixotrophic culture) or without(heterotrophic culture) MF, best growth occured in photomixotrophic culture.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.4
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• pp.317-324
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• 2015

GNSS was firstly proposed for application in weather forecasting in the mid-1980s. It has continued to demonstrate the practical uses in GNSS meteorology, and other relevant researches are currently being conducted. Precipitable Water Vapor (PWV), calculated based on the GNSS signal delays due to the troposphere of the Earth, represents the amount of the water vapor in the atmosphere, and it is therefore widely used in the analysis of various weather phenomena such as monitoring of weather conditions and climate change detection. In this study we calculated the PWV through the meteorological information from an Automatic Weather Station (AWS) as well as GNSS data processing of a Continuously Operating Reference Station (CORS) in order to analyze the heavy snowfall of the Ulsan area in early 2014. Song’s model was adopted for the weighted mean temperature model (T_m), which is the most important parameter in the calculation of PWV. The study period is a total of 56 days (February 2013 and 2014). The average PWV of February 2014 was determined to be 11.29 mm, which is 11.34% lower than that of the heavy snowfall period. The average PWV of February 2013 was determined to be 10.34 mm, which is 8.41% lower than that of not the heavy snowfall period. In addition, certain meteorological factors obtained from AWS were compared as well, resulting in a very low correlation of 0.29 with the saturated vapor pressure calculated using the empirical formula of Magnus. The behavioral pattern of PWV has a tendency to change depending on the precipitation type, specifically, snow or rain. It was identified that the PWV showed a sudden increase and a subsequent rapid drop about 6.5 hours before precipitation. It can be concluded that the pattern analysis of GNSS PWV is an effective method to analyze the precursor phenomenon of precipitation.

• Journal of agriculture & life science
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• v.44 no.3
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• pp.41-52
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• 2010

This study was conducted to estimate genetic parameters for growth traits using multivariate animal models in Yorkshire breed. For the study, 16,202 records for growth traits collected between the year 1999 and 2005 from Yorkshire pigs in K GGP were used. The effects of environmental factors such as sex, birth year, birth season, parity and birth weight group affected growth traits significantly (p<0.01). Birth weight tended to be positively correlated with average daily gain (ADG) and lean percent. But it seemed to affect age at 90 kg, average adjusted backfat thickness (BF), and eye muscle ares (EMA) negatively. For average pig suckling weight (ASW) and total weight at suckling (TWS), the higher birth weight is the better performance. But, in case of total number of born and number of suckling, the result was shown vice versa. Approximately 10~30% lower heritability estimates were obtained for growth traits by using the model that includes descriptions of common litter effects (CL) than by using the model that ignores those (NCL) for more accurate estimation of heritability. The estimates of heritabilities were 0.468, and 0.328 for ADG, 0.474 and 0.326 for age at 90 kg, 0.452, and 0.396 for BF, 0.240 and 0.200 for EMA and, 0.458, and 0.380 for lean percent in NCL and CL, respectively. Therefore, in order to estimate optimal genetic parameters, it could be inferred that the statistical model which considers litter effects must be applied.

• Korean Journal of Remote Sensing
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• v.26 no.5
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• pp.477-487
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• 2010

In North Korea, forests were intensively degraded by forest land reclamation for food production and firewood collection since the mid-1970s. These degraded forests have to be certainly recovered for economic support, environmental protection and disaster prevention. In order to provide detailed land cover information of forest recovery project (A/R CDM), this study was focused to develop an improved classification method for degraded forest using 2.5m SPOT-5 pan-sharpened image. The degraded forest of North Korea shows various different types of texture. This study used GLCM texture bands of segmented image with spectral bands during forest cover classification. When scale factor 40/shape factor 0.3 was used as a parameter set to generate segment image, segment image was generated on suitable segment scale that could classify types of degraded forest. Forest land cover types were classified with an optimum band combination of Band1, Band2, band3, GLCM dissimilarity (band2), GLCM homogeneity (band2) and GLCM standard deviation (band3). Segment-based classification method using spectral bands and texture bands reached an 80.4% overall accuracy, but the method using only spectral bands yielded an 70.3% overall accuracy. As using spectral and texture bands, a classification accuracy of stocked forest and unstocked forest showed an increase of 23~25%. In this research, SPOT-5 pan-sharpened high-resolution satellite image could provide a very useful information for classifying the forest cover of North Korea in which field data collection was not available for ground truth data and verification directly. And segment-based classification method using texture information improved classification accuracy of degraded forest.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.5
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• pp.187-200
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• 2019

The main purpose of this study is to investigate the effects of motivation of the employment in Korea with gender, nationality, motivation of studying in Korea, major satisfaction and Korean proficiency level of foreign students who are studying in Korea. The second purpose is to analyze the current factors, to leverage educational management and to make and support some policy of Minister of Education for international students in order to promote utilization of employment of the students in Korea during 4 years of studying. This paper is used by IBM SPSS Statistics 24 Version for data analysis. As a result of the analysis, the average of students in Southeast Asia, Central Asia and South and North America Africa was higher than Japan and China in terms of motivation of employment in Korea. First, the external motivation to study in Korea has affected TOPIK with positive influence. Second, in the relationship between motivation to study in Korea and the majors satisfaction, the higher the internal motivation of study, the higher the majors' satisfaction level. Third, in the relationship between motivation to study in Korea and motivation of the employment in Korea, internal motivation to study has a positive effect on motivation of the employment. As internal motivation increases, grade of the motivation of the employment increases. Fourth, the relationship between major satisfaction and employment showed positive (+) effect. In other words, the higher the major satisfaction, the higher the motivation of the employment. Fifth, TOPIK has a negative effect on motivation of the employment. It means that external motivation was the main factor that positively influenced TOPIK and internal motivation was also main factors that positively influenced both major satisfaction and motivation of the employment in Korea. Sixth, when the internal motivation has an effect on motivation of Korea employment, the higher the major satisfaction as the parameter, the higher the motivation of Korea employment. Therefore, it will be helpful to understand the meaning of studying motivation and major satisfaction of international students, and to be used as basic data on education policies of universities and governments supporting the career and employment for international students.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.66 no.2
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• pp.171-181
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• 2021

The purposes of this study were to determine how changes in temperature affect germination rates and growth of hulled and dehulled barley, malting barley, and naked oat plants, and to measure chlorophyll content, photosynthetic efficiency, and secondary compounds (total phenol, total flavonoid, and 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity) in plants grown at 13℃ or 25℃). Various types of barley seeds were collected from areas with ideal conditions for barley cultivation, hereinafter referred to as IA, and also from areas where barley cultivation is more difficult due to lower temperatures, hereinafter referred to as LTA. Seeds were tested for seed vigor. While there were significant differences in the electrical conductivity values between seeds collected from certain specific areas, no significant differences were evident between IA and LTA seeds, regardless of the type of barley seed. When plants were grown at 25℃, there were no significant differences in germination rates, plant height, root length and shoot fresh weight between plants originating from IA and LTA. However, there were differences in the measured parameters of some specific seeds. Similarly, under the low temperature condition of 13℃, no differences in the emergence rate, plant height, and shoot fresh weight were evident between plants originating from IA or LTA, regardless of the type of barley. However, there were differences between some specific seeds. One parameter that did vary significantly was the emergence date. Hulled barley and malting barley emerged 5 days after sowing, whereas naked oats emerged 7 days after sowing. There were no differences in the chlorophyll content and photosynthetic efficacy, regardless of the type of barley. There were no significant differences in total phenol, total flavonoid content, and DPPH radical scavenging activity between plants originating from IA and LTA, regardless of the type of barley. However, there were differences between some specific seeds. In particular, for malting barley the total flavonoid content differed in the order of Gangjin > Changwon > Haenam = Jeonju > Naju. The results indicate that crop growth, yield and content of secondary compounds in various types of barley may be affected by climate change.