• Clean Technology
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• v.26 no.2
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• pp.151-157
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• 2020

Rapid urbanization has elevated the risk of urban flooding due to the increase in the impervious surface, causing environmental disasters and environmental pollution problems, such as lowering the groundwater level and increasing water pollution. In Korea, low impact development (LID) techniques have been introduced to minimize these environmental impacts and maintain the water cycle soundness. However, most small-scale development projects are in blind spots because there is no legal basis for rainfall runoff management. Small-scale development projects that increase the surface runoff of rainwater are required to mandate the application of LID facilities in accordance with the polluters' responsibility principle. Therefore, it is necessary to implement a preliminary consultation system for water cycle recovery. This study focuses on the cost-benefit analysis on the application of LID techniques for small-scale development projects. The scale of nationwide small-scale development projects used for cost-benefit analysis were defined as buildings with a land area of more than 1,000 ㎡ or a total floor area of 1,500 ㎡. As a result of analyzing the cost-benefits from the installation of LID facilities, they were found to be much lower than the economic standard value of 1. This might be due to the high cost of facilities compared to the scale of the project. However, considering the overall environmental value of improving the water environment and air quality by the installation of LID facilities and the publicity of reducing the operating cost of sewage treatment facilities, the introduction of a prior consultation for small-scale development projects is inevitable. In the future, institutional and financial support from local governments is required to improve the cost-benefits with the introduction of a prior consultation for small-scale development projects.

• Journal of the Korean Society of Food Science and Nutrition
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• v.40 no.8
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• pp.1172-1178
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• 2011

The purpose of this study was to investigate the status of a school foodservice menu evaluation and the perception of the school's dietitian on menu evaluation. Questionnaires were distributed to 448 school dietitians with an official letter, and a total of 292 responses were used for analysis. More than 90% of the respondents stated that a menu evaluation for the school foodservice was necessary. The major barriers to menu evaluation were "excessive workload" and a "lack of know-how", and the expected benefits were "increased satisfaction of customers" and "increased foodservice efficiency". The menu evaluation for "student preferences", "health improvement", and "ease of quality management" categories were performed in more than 45% of schools. The proportion of subjects who answered that "customer satisfaction" and "increased efficiency of foodservice" were expected benefits of menu evaluation were significantly higher in the menu evaluation group (p<0.05).

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.159-172
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• 2010

The recommender system is one of the possible solutions to assist customers in finding the items they would like to purchase. To date, a variety of recommendation techniques have been developed. One of the most successful recommendation techniques is Collaborative Filtering (CF) that has been used in a number of different applications such as recommending Web pages, movies, music, articles and products. CF identifies customers whose tastes are similar to those of a given customer, and recommends items those customers have liked in the past. Numerous CF algorithms have been developed to increase the performance of recommender systems. Broadly, there are memory-based CF algorithms, model-based CF algorithms, and hybrid CF algorithms which combine CF with content-based techniques or other recommender systems. While many researchers have focused their efforts in improving CF performance, the theoretical justification of CF algorithms is lacking. That is, we do not know many things about how CF is done. Furthermore, the relative performances of CF algorithms are known to be domain and data dependent. It is very time-consuming and expensive to implement and launce a CF recommender system, and also the system unsuited for the given domain provides customers with poor quality recommendations that make them easily annoyed. Therefore, predicting the performances of CF algorithms in advance is practically important and needed. In this study, we propose an efficient approach to predict the performance of CF. Social Network Analysis (SNA) and Artificial Neural Network (ANN) are applied to develop our prediction model. CF can be modeled as a social network in which customers are nodes and purchase relationships between customers are links. SNA facilitates an exploration of the topological properties of the network structure that are implicit in data for CF recommendations. An ANN model is developed through an analysis of network topology, such as network density, inclusiveness, clustering coefficient, network centralization, and Krackhardt's efficiency. While network density, expressed as a proportion of the maximum possible number of links, captures the density of the whole network, the clustering coefficient captures the degree to which the overall network contains localized pockets of dense connectivity. Inclusiveness refers to the number of nodes which are included within the various connected parts of the social network. Centralization reflects the extent to which connections are concentrated in a small number of nodes rather than distributed equally among all nodes. Krackhardt's efficiency characterizes how dense the social network is beyond that barely needed to keep the social group even indirectly connected to one another. We use these social network measures as input variables of the ANN model. As an output variable, we use the recommendation accuracy measured by F1-measure. In order to evaluate the effectiveness of the ANN model, sales transaction data from H department store, one of the well-known department stores in Korea, was used. Total 396 experimental samples were gathered, and we used 40%, 40%, and 20% of them, for training, test, and validation, respectively. The 5-fold cross validation was also conducted to enhance the reliability of our experiments. The input variable measuring process consists of following three steps; analysis of customer similarities, construction of a social network, and analysis of social network patterns. We used Net Miner 3 and UCINET 6.0 for SNA, and Clementine 11.1 for ANN modeling. The experiments reported that the ANN model has 92.61% estimated accuracy and 0.0049 RMSE. Thus, we can know that our prediction model helps decide whether CF is useful for a given application with certain data characteristics.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.97-121
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• 2013

With the growing importance of knowledge for sustainable competitive advantages and innovation in a volatile environment, many researches on knowledge sharing have been conducted. However, previous researches have mostly relied on the questionnaire survey which has inherent perceptive errors of respondents. The current research has drawn the relationship among primary participant behaviors towards the participation level in knowledge sharing, basically from online user behaviors on Wikipedia, a representative community for online knowledge collaboration. Without users' participation in knowledge sharing, knowledge collaboration for creating knowledge cannot be successful. By the way, the editing patterns of Wikipedia users are diverse, resulting in different revisiting periods for the same number of edits, and thus varying results of shared knowledge. Therefore, we illuminated the participation level of knowledge sharing from two different angles of number of edits and revisiting period. The behavioral dimensions affecting the level of participation in knowledge sharing includes the article talk for public discussion and user talk for private messaging, and community registration, which are observable on Wiki platform. Public discussion is being progressed on article talk pages arranged for exchanging ideas about each article topic. An article talk page is often divided into several sections which mainly address specific type of issues raised during the article development procedure. From the diverse opinions about the relatively trivial things such as what text, link, or images should be added or removed and how they should be restructured to the profound professional insights are shared, negotiated, and improved over the course of discussion. Wikipedia also provides personal user talk pages as a private messaging tool. On these pages, diverse personal messages such as casual greetings, stories about activities on Wikipedia, and ordinary affairs of life are exchanged. If anyone wants to communicate with another person, he or she visits the person's user talk page and leaves a message. Wikipedia articles are assessed according to seven quality grades, of which the featured article level is the highest. The dataset includes participants' behavioral data related with 2,978 articles, which have reached the featured article level, with editing histories of articles, their article talk histories, and user talk histories extracted from user talk pages for each article. The time period for analysis is from the initiation of articles until their promotion to the featured article level. The number of edits represents the total number of participation in the editing of an article, and the revisiting period is the time difference between the first and last edits. At first, the participation levels of each user category classified according to behavioral dimensions have been analyzed and compared. And then, robust regressions have been conducted on the relationships among independent variables reflecting the degree of behavioral characteristics and the dependent variable representing the participation level. Especially, through adopting a motivational theory adequate for online environment in setting up research hypotheses, this work suggests a theoretical framework for the participation level of online knowledge sharing. Consequently, this work reached the following practical behavioral results besides some theoretical implications. First, both public discussion and private messaging positively affect the participation level in knowledge sharing. Second, public discussion exerts greater influence than private messaging on the participation level. Third, a synergy effect of public discussion and private messaging on the number of edits was found, whereas a pretty weak negative interaction effect of them on the revisiting period was observed. Fourth, community registration has a significant impact on the revisiting period, whereas being insignificant on the number of edits. Fifth, when it comes to the relation generated from private messaging, the frequency or depth of relation is shown to be more critical than the scope of relation for the participation level.

• Journal of Preventive Medicine and Public Health
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• v.27 no.3 s.47
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• pp.517-530
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• 1994

For the purpose of providing the basic data for health management of workers who are exposed to chromium and for improving the quality of working environment, the authors evaluated blood and urinary level of chromium, the occupational history. AST, ALT, Hb, Hct, nasal specular examinaton on 287 workers who have been dealed chromium compounds in 56 manufacturing Industries of five types, that is, 38 metal plating services(plating),4 manufacture of other fabricated metal products (fabricated metal product), 5 manufacturing of dyestuff(dyestuff), 6 dressing and dyeing of leather(leather), 3 others(manufacture of pottery and ceramic househod wares, motor vehicles, electronic valves and tubes and other electronic components) and also measured the level of chromium in air from February to October 1993. The results were as follows ; 1. The utilized type of chromium compounds was the hexavalent state in plating fabricated metal product dyestuff, leather and the trivalent state in .other, and atmosperic chromium concentration as geometric mean was $0.0138mg/m^3(0.001{\sim}0.068mg/m^3)$ in plating, $0.0115mg/m^3(0.006{\sim}0.015mg/m^3)$ in fabricated matal product, $0.068mg/m^3(0.002{\sim}0.019mg/m^3)$ in dyestuff, $0.0083mg/m^3(0.002{\sim}0.028mg/m^3)$ in leather $0.0039mg/m^3(0.003{\sim}0.005mg/m^3)$ in other by the type of industry and it exceeded TLV-TWA ($0.05mg/m^3$) in five (13.6%) of plating services. 2. The geometric mean of chromium in blood was $1.54{\mu}g/dl(0.10{\sim}3.62{\mu}g/dl)$ in Plantng, $0.94{\mu}g/dl(0.27{\sim}2.82{\mu}g/dl)$ in fabricated metal product, $0.51{\mu}g/dl(0.10{\sim}3.25{\mu}g/dl)$ in dyestuff, $0.87{\mu}g/dl(0.15{\sim}8.00{\mu}g/dl)$ in leather, $0.55{\mu}g/dl(0.20{\sim}2.28{\mu}g/dl)$ in other by the type of industry(p<0.001). 3. The geometric mean of chromium in urine was $14.47{\mu}g/l(6.90{\sim}28.00{\mu}g/l)$ in planting, $4.63{\mu}g/l(0.24{\sim}43.00{\mu}g/l)$ in fabricated metal product, $5.93{\mu}g/l(1.00{\sim}33.00{\mu}g/l)$ in dyestuff, $11.09{\mu}g/l(0.80{\sim}48.00{\mu}g/l)$ in leather, $12.41{\mu}g/l(10.10{\sim}41.00{\mu}g/l)$ in other by the type of industry(p<0.001). 4. As the result of nasal specular examination, twenty four cases (8.4%) of nasal septal perforation among 287 total subjects was observed, and there were 17 (9.7%) cases in plating, 4 csaes (14.3%) in dressing and dyeing of leather. In the comparison of chromium concentration in blood and urine between the perforated group and non-perforated group, the perforated group showed a significantly higher value as $1.883{\pm}3.055{\mu}g/dl\;and\;0.793{\pm}0.815{\mu}g/dl$(P<0.001), $21.31{\pm}34.610{\mu}g/L\;and\;9.304{\pm}11.079{\mu}g/L$ (P<0.001). 5. The mean concentration of chromium in blood, urine and the mean level of AST, ALT, Hb and Hct in exposure group were higher than those of control group(p<0.001).

• Horticultural Science & Technology
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• v.34 no.1
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• pp.172-182
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• 2016

This study was aimed to determine the changes in vitamin $B_5$ and $B_6$ contents compared to fresh materials after parboiling treatment of the main vegetables consumed in Korea. The specificity of accuracy and precision for vitamin $B_5$ and $B_6$ analysis method were validated using high-performance liquid chromatography (HPLC). The recovery rate of standard reference material (SRM) was excellent, and all analysis was under the control line based on the quality control chart for vitamin $B_5$ and $B_6$. The Z-score for vitamin $B_6$ in food analysis performance assessment scheme (FAPAS) proficiency test was -1.0, confirming reliability of analytical performance. The vitamin $B_5$ and $B_6$ contents in a total of 39 fresh materials and parboiled samples were analyzed. The contents of vitamin $B_5$ and $B_6$ ranged from 0.000 to 2.462 and from 0.000 to $0.127mg{\cdot}100g^{-1}$, respectively. The highest contents of vitamin $B_5$ and $B_6$ were $2.462mg{\cdot}100g^{-1}$ in fresh fatsia shoots (stem vegetables), and $0.127mg{\cdot}100g^{-1}$ in fresh spinach beet (leafy vegetables), respectively. Moreover, the vitamin $B_5$ and $B_6$ contents for parboiling treatment in most vegetables were reduced or not detected. In particular, the contents of vitamin $B_5$ in parboiled fatsia shoots and vitamin $B_6$ in parboiled yellow potato and spinach beet were decreased 20- and 4-fold compared with fresh material, respectively. These results can be used as important basic data for utilization and processing of various vegetable crops, information for dietary life, management of school meals, and national health for Koreans.

• Asian Journal of Turfgrass Science
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• v.23 no.2
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• pp.331-344
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• 2009

Buffalograss is an important turfgrass species with excellent cold, heat, and drought tolerance. Understanding the physiological integration of buffalograss under heterogeneous conditions helps to develop cultural practices that better use limited resources for uniform turf quality. The objective of this study was to evaluate physiological integration of buffalograss under water deficit stress and the involvement of lipid peroxidation and antioxidants in the process. In one experiment, buffalograss was planted in the center of a four-compartment growth unit. Watering frequencies, once a week(+) and once in two weeks(-), were combined with the sand(S) or peat(P) in each unit to generate five total treatments(P+S-P-S+, P+P+P+P+, S-S-S-S-, P-P-P-P-, and S+S+S+S+). The average number of shoot established from the heterogeneous root-zone medium was higher than the average of four possible homogeneous media. In second experiment, single ramet in Hoagland solution($S_0$) or single ramet in Hoagland solution with 20% PEG-6000($S_s$) were compared with two connectedramets under different treatments. Treatments for connected ramets were young ramet in Hoagland solution($Y_{os}$) and old ramet in Hoagland solution with 20% PEG-6000($O_{os}$), and old ramet in Hoagland solution($O_{ys}$) and young ramet in Hoagland solution with 20% PEG-6000($Y_{ys}$). Lipid peroxidation, antioxidants, and proline showedphysiological integration between ramets subjected to different levels of water stress. Superoxide dismutase(SOD), Guaiacol peroxidase(G-POD), malondialdehyde(MDA), and free proline also showed different time courses and relative activities during the physiological integration.

• Journal of Korea Water Resources Association
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• v.54 no.10
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• pp.835-848
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• 2021

In Jeju Island which has peculiarity for its geological features and hydrology system, hydrological factor analysis for the effective water management is necessary. Because in-situ hydro-meteorological data is affected by surrounding environment, the in-situ dataset could not be the spatially representative for the study area. For this reason, remote sensing data may be used to overcome the limit of the in-situ data. In this study, applicability assessment of MOD16 evapotranspiration data, Globas Land Data Assimilation System (GLDAS) based evapotranspiration/soil moisture data, and Advanced SCATterometer (ASCAT) soil moisture product which were evaluated their applicability on other study areas was conducted. In the case of evapotranspiration, comparison with total precipitation and flux-tower based evapotranspiration were conducted. And for soil moisture, 6 in-situ data and ASCAT soil moisture product were compared on each site. As a result, 57% of annual precipitation was calculated as evapotranspiration, and the correlation coefficient between MOD16 evapotranspiration and GLDAS evapotranspiration was 0.759, which was a robust value. The correlation coefficient was 0.434, indicating a relatively low fit. In the case of soil moisture, in the case of the GLDAS data, the RMSE value was less than 0.05 at all sites compared to the in-situ data, and a statistically significant result was obtained as a result of the significance test of the correlation coefficient. However, for satellite data, RMSE over than 0.05 were found at Wolgak and there was no correlation at Sehwa and Handong points. It is judged that the above results are due to insufficient quality control and spatial representation of the evapotranspiration and soil moisture sensors installed in Jeju Island. It is estimated as the error that appears when adjacent to the coast. Through this study, the necessity of improving the existing ground observation data of hydrometeorological factors is emphasized.

• Journal of Bio-Environment Control
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• v.28 no.1
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• pp.66-77
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• 2019

The present study investigated pine trees, which forms a major plantation species in Korea, with the objective of improving the survival rate of pine trees after planting. Growth responses and characteristics were assessed by controlling the level of fertilizer application, which is a basic controlling the growth of pine seedlings, to identify the optimal fertilization treatment. Pine tree seedlings were grown in 104 containers and were examined 8 weeks after planting. Stem height and were measured at 4-week intervals. In terms of fertilization treatment for 1-0 pine seedlings, the treatment group with gradually-increasing fertilizer concentration ($500{\rightarrow}1000{\rightarrow}1000{\rightarrow}1000mg{\cdot}L^{-1}$) had the biggest increase in stem height and diameter at the root. The survey results indicated that the increased concentration treatment group and the gradually-increasing concentration treatment group had more growth compared with that in the fixed concentration treatment group. The gradually-increasing concentration treatment group ($500{\rightarrow}1000{\rightarrow}1000{\rightarrow}1000mg{\cdot}L^{-1}$) had the highest total dry matter production. Nine weeks after fertilization, the tips of the pine leaves turned yellow in the fixed concentration treatment group ($3000mg{\cdot}L^{-1}$). The same phenomenon was observed in the treatment group in which the concentration was increased to $2000mg{\cdot}L^{-1}$, and in the gradually-increasing concentration treatment group, when the concentration was raised up to $2000mg{\cdot}L^{-1}$. We concluded that the optimal fertilization conditions for producing healthy pine 1-0 seedlings involve fertilizing once a week with Multifeed 19 at $500mg{\cdot}L^{-1}$ during the seedling period, Multifeed 19 at $1000mg{\cdot}L^{-1}$ during the rapid growth period, and Multifeed 32 at $1000mg{\cdot}L^{-1}$ during the maturation period.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.139-161
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• 2019

The utilization of the e-commerce market has become a common life style in today. It has become important part to know where and how to make reasonable purchases of good quality products for customers. This change in purchase psychology tends to make it difficult for customers to make purchasing decisions in vast amounts of information. In this case, the recommendation system has the effect of reducing the cost of information retrieval and improving the satisfaction by analyzing the purchasing behavior of the customer. Amazon and Netflix are considered to be the well-known examples of sales marketing using the recommendation system. In the case of Amazon, 60% of the recommendation is made by purchasing goods, and 35% of the sales increase was achieved. Netflix, on the other hand, found that 75% of movie recommendations were made using services. This personalization technique is considered to be one of the key strategies for one-to-one marketing that can be useful in online markets where salespeople do not exist. Recommendation techniques that are mainly used in recommendation systems today include collaborative filtering and content-based filtering. Furthermore, hybrid techniques and association rules that use these techniques in combination are also being used in various fields. Of these, collaborative filtering recommendation techniques are the most popular today. Collaborative filtering is a method of recommending products preferred by neighbors who have similar preferences or purchasing behavior, based on the assumption that users who have exhibited similar tendencies in purchasing or evaluating products in the past will have a similar tendency to other products. However, most of the existed systems are recommended only within the same category of products such as books and movies. This is because the recommendation system estimates the purchase satisfaction about new item which have never been bought yet using customer's purchase rating points of a similar commodity based on the transaction data. In addition, there is a problem about the reliability of purchase ratings used in the recommendation system. Reliability of customer purchase ratings is causing serious problems. In particular, 'Compensatory Review' refers to the intentional manipulation of a customer purchase rating by a company intervention. In fact, Amazon has been hard-pressed for these "compassionate reviews" since 2016 and has worked hard to reduce false information and increase credibility. The survey showed that the average rating for products with 'Compensated Review' was higher than those without 'Compensation Review'. And it turns out that 'Compensatory Review' is about 12 times less likely to give the lowest rating, and about 4 times less likely to leave a critical opinion. As such, customer purchase ratings are full of various noises. This problem is directly related to the performance of recommendation systems aimed at maximizing profits by attracting highly satisfied customers in most e-commerce transactions. In this study, we propose the possibility of using new indicators that can objectively substitute existing customer 's purchase ratings by using RFM multi-dimensional analysis technique to solve a series of problems. RFM multi-dimensional analysis technique is the most widely used analytical method in customer relationship management marketing(CRM), and is a data analysis method for selecting customers who are likely to purchase goods. As a result of verifying the actual purchase history data using the relevant index, the accuracy was as high as about 55%. This is a result of recommending a total of 4,386 different types of products that have never been bought before, thus the verification result means relatively high accuracy and utilization value. And this study suggests the possibility of general recommendation system that can be applied to various offline product data. If additional data is acquired in the future, the accuracy of the proposed recommendation system can be improved.