• 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.

• Korean Journal of Organic Agriculture
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• v.15 no.3
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• pp.319-330
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• 2007

This study analyzed physical and chemical characteristics of peat soil to use peat soil as the materials fur pot media and investigated seedling quality of horticultural plants in order to use peat soil as the raw materials fur pot media. The summary of the results is as follows; The chemical characteristics of peat soil, which is main ingredient of pot media are as follows; pH was 4.9, EC was less than $2.0ds{\cdot}m^{-1}$, which interferes the growth of the plant and organic ingredient was 33%. When looking into the germination characteristics of plants according to the mixture of pot media, red pepper showed 54.2% speed of germination and 97% germination rate in peat soil single treatment. Therefore the peatsoil was appropriate for the pot media for red pepper. In case of cucumbers, in the 50 : 50 treatment of main ingredient (peat soil) and auxiliary ingredients (vermiculite, peat moss and perlite) they showed 100% speed of germination and 100% germination rate. Therefore 50 : 50 treatment was appropriate fur the pot media for cucumbers. In case of chinese cabbage, peat soil, perlite and peat moss mixture (50 : 25 : 25) treatment showed the highest speed of germination (77.5%), while the germination rate was a little lower (92.15%) than comparative soil. However, it was appropriate for the pot media for chinese cabbage. In case of watermelon, germination was bad because of the influence of EC when the teat soil ingredient is over 80%. However, in the mixture of peat soil and vermiculite (50:50) treatment, they showed 91.6% speed of germination and 100% germination rate. Therefore it was appropriate for the pot media for watermelon. When looking into the growth of the plants according to the mixture of ingredients, peat soil and perlite (50:50) mixture showed excellent seedling quality for cucumbers, peat soil and perlite (50:50) mixture showed excellent seedling quality and it was proven to be appropriate for the pot media for cucumbers. In case of watermelon, peat soil, peat moss and perlite (80 : 10 : 10) mixture showed excellent seedling quality and it was proven to be appropriate for the pot media for watermelon.

• Food Science and Preservation
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• v.19 no.6
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• pp.799-806
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• 2012

This experiment was conducted to establish the optimum conditions for high $CO_2$ gas treatment in combination with a proper gas-permeable packaging film to maintain the quality of fig fruit (Ficus carica L). Among the fig fruits with different high $CO_2$ treatments, the quality change was most effectively controlled during storage in the 70%-$CO_2$-treated fig fruit. Harvested fig fruit was packaged using microperforated oriented polypropylene (MP) film to maintain the optimum gas concentrations in the headspace of packaging for the modified-atmosphere system. MP film had an oxygen transmission rate of about $10,295cm^3/m^2$/day/atm at $25^{\circ}C$. The weight loss, firmness, soluble-solid content (SSC), acidity (pH), skin color (Hunter L, a, b), and decay ratio of the fig fruits were monitored during storage at 5 and $25^{\circ}C$. The results of this study showed that the OPP film, OPP film + 70% $CO_2$, and MP film+70% $CO_2$ were highly effective in reducing the loss rate, firmness and decay occurrence rate of fig fruits that were packaged with them during storage. In the case of using treatments with packages of OPP film and OPP film+70% $CO_2$, however, adverse effects like package bursting or physiological injury of the fig may occur due to the gas pressure or long exposure to $CO_2$. Therefore, the results indicated that MP film containing 70% $CO_2$ can be used as an effective treatment to extend the freshness of fig fruits for storage at a proper low temperature.

• Journal of Korean Society of Forest Science
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• v.110 no.3
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• pp.406-418
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• 2021

This study was conducted to evaluate optimal storage techniques for bare root plants and container seedlings of Quercus variabilis and Zelkova serrata in order to maintain high quality of seedlings until planting. Refrigerated storage treatments were given at two temperatures (-2℃ [freezing] and 2℃ [cooling]) for nine different durations (0, 15, 30, 60, 120, 180, 240, 300, and 360 days after storage). We analyzed total nonstructural carbohydrate (TNC) content and measured shoot moisture content (SMC) during the storage stage and survival rate (SR) and dry weight during the planting stage of seedlings. The TNC content and SMC of the seedlings of the two species decreased with an increase in storage duration. The TNC content of seedlings rapidly decreased after 180~240 days of storage. The TNC reduction rate in the freezing treatment was lower than that in the cooling treatment. Also, with an increase in the storage duration of the two species, the SMC reduction rate in the cooling treatment increased in comparison with that in the freezing treatment. In both the species, the SR after planting decreased rapidly after 60 days of cooling storage and 180 days of freezing storage, respectively. The SR after planting was less than 60% when the TNC content for both the species dropped below 20 mg g^-1. In addition, the SR was lower than 80% when SMC measured before storage decreased by approximately 30% and 20% for Q. variabilis and Z. serrata, respectively. Our results suggest that cooling (1~2℃) storage is recommended for a short-term period (2 months or less), whereas freezing (-2~-4℃) storage is suitable for longer periods (2~6 months). These optimal storage techniques, allied with seedling harvesting and handling systems, will improve the quality of seedling production in nursery stages and increase seedling growth performances in plantations.

• Journal of Life Science
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• v.29 no.4
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• pp.492-498
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• 2019

Previously, three kinds of lipases, lipAD1, lipAD2, and lipAD3, and lipase chaperone, lipBD, of Acinetobacter schindleri DYL129 isolated from soil sample were reported. In this report, three lipase and lipase chaperone were cloned into the pET32a(+) or pGEX-6P-1 vectors for protein expression in Escherichia coli, and named as pETLAD1, pETLAD2, pETLAD3 and pETLBD or pGEXLAD1, pGEXLAD 2, pGEXLAD3 and pGEXLBD, respectively. Protein expression rate was higher in pET system than in pGEX system. Although LipAD1 and LipAD2 were produced as inclusion bodies, their expression levels were high. So LipAD1 and LipAD2 could be solubilized in 8 M urea buffer and purified. LipAD3 and LipBD were overexpressed in soluble form and purified. Those proteins were purified by His-tag affinity chromatography connected in AKTA prime system. The activities of the purified lipases were demonstrated with 1% tributyrin agar plate. After purification, molecular mass was determined with sodium dodecyl sulfate-polyacrylamide gel electrophoresis. LipAD1 showed high activity toward ${\rho}$-nitrophenyl acetate and ${\rho}$-nitrophenyl butyrate, LipAD2 showed high activity toward ${\rho}$-nitrophenyl acetate and ${\rho}$-nitrophenyl myristate, and LipAD3 showed high activity toward ${\rho}$-nitrophenyl acetate, ${\rho}$-nitrophenyl butyrate, and ${\rho}$-nitrophenyl miristate, respectively. Three lipases, LipAD1, LipAD2, and LipAD3, showed optimal reaction at $50^{\circ}C$ using ${\rho}$-nitrophenyl butyrate, as substrate.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.31 no.1
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• pp.28-39
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• 2019

In the design process of counter measures against the beach erosion, information like the main sediment transport mode and yearly net amount of longshore and cross shore transport is of great engineering value. In this rationale, we numerically analyzed the yearly sediment budget of the Mang-Bang beach which is suffering from erosion problem. For the case of cross sediment transport, Bailard's model (1981) having its roots on the Bagnold's energy model (1963) is utilized. In doing so, longshore sediment transport rate is estimated based on the assumption that longshore transport rate is determined by the available wave energy influx toward the beach. Velocity moments required for the application of Bailard's model (1981) is deduced from numerical simulation of the nonlinear shoaling process over the Mang-Bang beach of the 71 wave conditions carefully chosen from the wave records. As a wave driver, we used the consistent frequency Boussinesq Eq. by Frelich and Guza (1984). Numerical results show that contrary to the Bailard's study (1981), Irribaren NO. has non negligible influence on the velocity moments. We also proceeds to numerically simulate the yearly sediment budget of Mang-Bang beach. Numerical results show that for ${\beta}=41.6^{\circ}$, the mean orientation of Mang-Bang beach, north-westwardly moving longshore sediment is prevailing over the south-eastwardly moving sediment, the yearly amount of which is simulated to reach its maxima at $125,000m^3/m$. And the null pint where north-westwardly moving longshore sediment is balanced by the south-eastwardly moving longshore sediment is located at ${\beta}=47^{\circ}$. For the case of cross shore sediment, the sediment is gradually moving toward the shore from the April to mid October, whereas these trends are reversed by sporadically occurring energetic wind waves at the end of October and March. We also complete the littoral drift rose of the Mang-Bang beach, which shows that even though the shore line is temporarily retreated, and as a result, the orientation of Mang-Bang beach is larger than the orientation of null pont, south-eastwardly moving longshore sediment is prevailing. In a case that the orientation of Mang-Bang beach is smaller than the orientation of null pont, north-westwardly moving longshore sediment is prevailing. And these trend imply that the Mang-Bang beach is stable one, which has the self restoring capability once exposed to erosion.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.3
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• pp.149-155
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• 2021

Early warning systems for weather risk management in the agricultural sector have been developed to predict potential wind damage to crops. These systems take into account the daily maximum wind speed to determine the critical wind speed that causes fruit drops and provide the weather risk information to farmers. In an effort to increase the accuracy of wind risk predictions, an artificial neural network for binary classification was implemented. In the present study, the daily wind speed and other weather data, which were measured at weather stations at sites of interest in Jeollabuk-do and Jeollanam-do as well as Gyeongsangbuk- do and part of Gyeongsangnam- do provinces in 2019, were used for training the neural network. These weather stations include 210 synoptic and automated weather stations operated by the Korean Meteorological Administration (KMA). The wind speed data collected at the same locations between January 1 and December 12, 2020 were used to validate the neural network model. The data collected from December 13, 2020 to February 18, 2021 were used to evaluate the wind risk prediction performance before and after the use of the artificial neural network. The critical wind speed of damage risk was determined to be 11 m/s, which is the wind speed reported to cause fruit drops and damages. Furthermore, the maximum wind speeds were expressed using Weibull distribution probability density function for warning of wind damage. It was found that the accuracy of wind damage risk prediction was improved from 65.36% to 93.62% after re-classification using the artificial neural network. Nevertheless, the error rate also increased from 13.46% to 37.64%, as well. It is likely that the machine learning approach used in the present study would benefit case studies where no prediction by risk warning systems becomes a relatively serious issue.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.129-149
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• 2021

Recently, interest in social robots that can socially interact with humans is increasing. Thanks to the development of ICT technology, social robots have become easier to provide personalized services and emotional connection to individuals, and the role of social robots is drawing attention as a means to solve modern social problems and the resulting decline in the quality of individual lives. Along with the interest in social robots, the spread of social robots is also increasing significantly. Many companies are introducing robot products to the market to target various target markets, but so far there is no clear trend leading the market. Accordingly, there are more and more attempts to differentiate robots through the design of social robots. In particular, anthropomorphism has been studied importantly in social robot design, and many approaches have been attempted to anthropomorphize social robots to produce positive effects. However, there is a lack of research that systematically describes the mechanism by which anthropomorphism for social robots is formed. Most of the existing studies have focused on verifying the positive effects of the anthropomorphism of social robots on consumers. In addition, the formation of anthropomorphism of social robots may vary depending on the individual's motivation or temperament, but there are not many studies examining this. A vague understanding of anthropomorphism makes it difficult to derive design optimal points for shaping the anthropomorphism of social robots. The purpose of this study is to verify the mechanism by which the anthropomorphism of social robots is formed. This study confirmed the effect of the human-likeness of social robots(Within-subjects) and the construal level of consumers(Between-subjects) on the formation of anthropomorphism through an experimental study of 3×2 mixed design. Research hypotheses on the mechanism by which anthropomorphism is formed were presented, and the hypotheses were verified by analyzing data from a sample of 206 people. The first hypothesis in this study is that the higher the human-likeness of the robot, the higher the level of anthropomorphism for the robot. Hypothesis 1 was supported by a one-way repeated measures ANOVA and a post hoc test. The second hypothesis in this study is that depending on the construal level of consumers, the effect of human-likeness on the level of anthropomorphism will be different. First, this study predicts that the difference in the level of anthropomorphism as human-likeness increases will be greater under high construal condition than under low construal condition.Second, If the robot has no human-likeness, there will be no difference in the level of anthropomorphism according to the construal level. Thirdly,If the robot has low human-likeness, the low construal level condition will make the robot more anthropomorphic than the high construal level condition. Finally, If the robot has high human-likeness, the high construal levelcondition will make the robot more anthropomorphic than the low construal level condition. We performed two-way repeated measures ANOVA to test these hypotheses, and confirmed that the interaction effect of human-likeness and construal level was significant. Further analysis to specifically confirm interaction effect has also provided results in support of our hypotheses. The analysis shows that the human-likeness of the robot increases the level of anthropomorphism of social robots, and the effect of human-likeness on anthropomorphism varies depending on the construal level of consumers. This study has implications in that it explains the mechanism by which anthropomorphism is formed by considering the human-likeness, which is the design attribute of social robots, and the construal level of consumers, which is the way of thinking of individuals. We expect to use the findings of this study as the basis for design optimization for the formation of anthropomorphism in social robots.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.151-176
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• 2021

As the information technology industry develops, various kinds of data are being created, and it is now essential to process them and use them in the industry. Analyzing and utilizing various digital data collected online and offline is a necessary process to provide an appropriate experience for customers in the industry. In order to create new businesses, products, and services, it is essential to use customer data collected in various ways to deeply understand potential customers' needs and analyze behavior patterns to capture hidden signals of desire. However, it is true that research using data analysis and UX methodology, which should be conducted in parallel for effective service development, is being conducted separately and that there is a lack of examples of use in the industry. In thiswork, we construct a single process by applying data analysis methods and UX methodologies. This study is important in that it is highly likely to be used because it applies methodologies that are actively used in practice. We conducted a survey on the topic to identify and cluster the associations between factors to establish customer classification and target customers. The research methods are as follows. First, we first conduct a factor, regression analysis to determine the association between factors in the happiness data survey. Groups are grouped according to the survey results and identify the relationship between 34 questions of psychological stability, family life, relational satisfaction, health, economic satisfaction, work satisfaction, daily life satisfaction, and residential environment satisfaction. Second, we classify clusters based on factors affecting happiness and extract the optimal number of clusters. Based on the results, we cross-analyzed the characteristics of each cluster. Third, forservice definition, analysis was conducted by correlating with keywords related to happiness. We leverage keyword analysis of the thumb trend to derive ideas based on the interest and associations of the keyword. We also collected approximately 11,000 news articles based on the top three keywords that are highly related to happiness, then derived issues between keywords through text mining analysis in SAS, and utilized them in defining services after ideas were conceived. Fourth, based on the characteristics identified through data analysis, we selected segmentation and targetingappropriate for service discovery. To this end, the characteristics of the factors were grouped and selected into four groups, and the profile was drawn up and the main target customers were selected. Fifth, based on the characteristics of the main target customers, interviewers were selected and the In-depthinterviews were conducted to discover the causes of happiness, causes of unhappiness, and needs for services. Sixth, we derive customer behavior patterns based on segment results and detailed interviews, and specify the objectives associated with the characteristics. Seventh, a typical persona using qualitative surveys and a persona using data were produced to analyze each characteristic and pros and cons by comparing the two personas. Existing market segmentation classifies customers based on purchasing factors, and UX methodology measures users' behavior variables to establish criteria and redefine users' classification. Utilizing these segment classification methods, applying the process of producinguser classification and persona in UX methodology will be able to utilize them as more accurate customer classification schemes. The significance of this study is summarized in two ways: First, the idea of using data to create a variety of services was linked to the UX methodology used to plan IT services by applying it in the hot topic era. Second, we further enhance user classification by applying segment analysis methods that are not currently used well in UX methodologies. To provide a consistent experience in creating a single service, from large to small, it is necessary to define customers with common goals. To this end, it is necessary to derive persona and persuade various stakeholders. Under these circumstances, designing a consistent experience from beginning to end, through fast and concrete user descriptions, would be a very effective way to produce a successful service.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.79-105
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• 2023

Due to unprecedented extreme weather events such as global warming and climate change, many parts of the world suffer from severe pain, and economic losses are also snowballing. In order to address these problems, 'The Paris Agreement' was signed in 2016, and an intergovernmental consultative body was formed to keep the average temperature rise of the Earth below 1.5℃. Korea also declared 'Carbon Neutrality in 2050' to prevent climate catastrophe. In particular, it was found that the increase in temperature caused by greenhouse gas emissions hurts the environment and society as a whole, as well as the export-dependent economy of Korea. In addition, as the diversification of transportation types is accelerating, the change in means of choice is also increasing. As the development paradigm in the low-growth era changes to urban regeneration, interest in idle railway sites is rising due to reduced demand for routes, improvement of alignment, and relocation of urban railways. Meanwhile, it is possible to partially achieve the solar power generation goal of 'Renewable Energy 3020' by utilizing already developed but idle railway sites and take advantage of being free from environmental damage and resident acceptance issues surrounding the location; but the actual use and plan for these solar power facilities are still lacking. Therefore, in this study, using the big data provided by the Korea National Railway and the Renewable Energy Cloud Platform, we develop an algorithm to discover and analyze suitable idle sites where solar power generation facilities can be installed and identify potentially applicable areas considering conditions desired by users. By searching and deriving these idle but relevant sites, it is intended to devise a plan to save enormous costs for facilities or expansion in the early stages of development. This study uses various cluster analyses to develop an optimal algorithm that can derive solar power plant locations on idle railway sites and, as a result, suggests 202 'actively recommended areas.' These results would help decision-makers make rational decisions from the viewpoint of simultaneously considering the economy and the environment.