• Journal of Korean Society of Environmental Engineers
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• v.31 no.11
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• pp.1007-1018
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• 2009

Hydrocyclone is widely used in industry, because of its simplicity in design, high capacity, low maintenance and operational cost. The separation action of a hydrocyclone treating particulate slurry is a consequence of the swirling flow that produces a centrifugal force on the fluid and suspended particles. In spite of hydrocyclone have many advantage, the application for treatment of urban stormwater case study were rare. We conducted a laboratory scale study on treatable potential of micro particles using hydrocyclone filter (HCF) that was a combined modified hydrocyclone with perlite filter cartridge. Since it was not easy to use actual storm water in the scaled-down hydraulic model investigations, it was necessary to reproduce ranges of particles sizes with synthetic materials. The synthesized storm runoff was made with water and addition of particles; ion exchange resin, road sediment, commercial area manhole sediment, and silica gel particles. Experimental studies have been carried out about the particle separation performance of HCF-open system and HCF-closed system. The principal structural differences of these HCFs are underflow zone structure and vortex finder. HCF was made of acryl resin with 120 mm of diameter hydrocyclone and 250 mm of diameter filter chamber and overall height of 800 mm. To determine the removal efficiency for various influent concentrations of suspended solids (SS) and chemical oxygen demand (COD), tests were performed with different operational conditions. The operated maximum of surface loading rate was about 700 $m^3/m^2$/day for HCF-open system, and 1,200 $m^3/m^2$/day for HCF-closed system. It was found that particle removal efficiency for the HCF-closed system is better than the HCF-open system under same surface loading rate. Results showed that SS removal efficiency with the HCF-closed system improved by about 8~20% compared with HCF-open system. The average removal efficiency difference for HCF-closed system between measurement and CFD particle tracking simulation was about 4%.

• Radiation Oncology Journal
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• v.21 no.4
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• pp.291-298
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• 2003

Purpose: We report upon a web-based system for Patterns of Care Study (PCS) devised for Korean radiation oncology. This PCS was designed to establish standard tools for clinical quality assurance, to determine basic parameters for radiation oncology processes, to offer a solid system for cooperative clinical studies and a useful standard database for comparisons with other national databases. Materials and Methods: The system consisted of a main server with two back-ups in other locations. The program uses a Linux operating system and a MySQL database. Cancers with high frequencies in radiotherapy departments in Korea from 1998 to 1999 were chosen to have a developmental priority. Results: The web-based clinical PCS .system for radiotherapy in www.pcs.re.kr was developed in early 2003 for cancers of the breast, rectum, esophagus, larynx and lung, and for brain metastasis. The total number of PCS study items exceeded one thousand. Our PCS system features user-friendliness, double entry checking, data security, encryption, hard disc mirroring, double back-up, and statistical analysis. Alphanumeric data can be input as well as image data. In addition, programs were constructed for IRB submission, random sampling of data, and departmental structure. Conclusion: For the first time in the field of PCS, we have developed a web-based system and associated working programs. With this system, we can gather sample data in a short period and thus save, cost, effort and time. Data audits should be peformed to validate input data. We propose that this system should be considered as a standard method for PCS or similar types of data collection systems.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.243-264
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• 2018

Although the worldwide battery market is recently spurring the development of lithium secondary battery, lead acid batteries (rechargeable batteries) which have good-performance and can be reused are consumed in a wide range of industry fields. However, lead-acid batteries have a serious problem in that deterioration of a battery makes progress quickly in the presence of that degradation of only one cell among several cells which is packed in a battery begins. To overcome this problem, previous researches have attempted to identify the mechanism of deterioration of a battery in many ways. However, most of previous researches have used data obtained in a laboratory to analyze the mechanism of deterioration of a battery but not used data obtained in a real world. The usage of real data can increase the feasibility and the applicability of the findings of a research. Therefore, this study aims to develop a model which predicts the battery deterioration using data obtained in real world. To this end, we collected data which presents change of battery state by attaching sensors enabling to monitor the battery condition in real time to dozens of golf carts operated in the real golf field. As a result, total 16,883 samples were obtained. And then, we developed a model which predicts a precursor phenomenon representing deterioration of a battery by analyzing the data collected from the sensors using machine learning techniques. As initial independent variables, we used 1) inbound time of a cart, 2) outbound time of a cart, 3) duration(from outbound time to charge time), 4) charge amount, 5) used amount, 6) charge efficiency, 7) lowest temperature of battery cell 1 to 6, 8) lowest voltage of battery cell 1 to 6, 9) highest voltage of battery cell 1 to 6, 10) voltage of battery cell 1 to 6 at the beginning of operation, 11) voltage of battery cell 1 to 6 at the end of charge, 12) used amount of battery cell 1 to 6 during operation, 13) used amount of battery during operation(Max-Min), 14) duration of battery use, and 15) highest current during operation. Since the values of the independent variables, lowest temperature of battery cell 1 to 6, lowest voltage of battery cell 1 to 6, highest voltage of battery cell 1 to 6, voltage of battery cell 1 to 6 at the beginning of operation, voltage of battery cell 1 to 6 at the end of charge, and used amount of battery cell 1 to 6 during operation are similar to that of each battery cell, we conducted principal component analysis using verimax orthogonal rotation in order to mitigate the multiple collinearity problem. According to the results, we made new variables by averaging the values of independent variables clustered together, and used them as final independent variables instead of origin variables, thereby reducing the dimension. We used decision tree, logistic regression, Bayesian network as algorithms for building prediction models. And also, we built prediction models using the bagging of each of them, the boosting of each of them, and RandomForest. Experimental results show that the prediction model using the bagging of decision tree yields the best accuracy of 89.3923%. This study has some limitations in that the additional variables which affect the deterioration of battery such as weather (temperature, humidity) and driving habits, did not considered, therefore, we would like to consider the them in the future research. However, the battery deterioration prediction model proposed in the present study is expected to enable effective and efficient management of battery used in the real filed by dramatically and to reduce the cost caused by not detecting battery deterioration accordingly.

• 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 Life Science
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• v.20 no.3
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• pp.381-387
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• 2010

To find offspring of Jeju Black cattle (JBC) produced by embryo transfer (ET) and artificial insemination (AI), a molecular genetic study was carried out in candidate cattle populations collected from cattle farms in Jeju Island, Korea. The genetic marker set was composed of 11 ISAG microsatellite (MS) markers, 11 SAES MS markers selected by our preliminary analysis for population diversity of JBC and two major coat color related genes: MC1R and ASIP. The results showed a combined non-exclusion probability for first parent (NE-P1) that was higher than that recommended by ISAG (above 0.9995), and a combined non-exclusion probability for sib identity of $5.3{\times}10^{-10}$. Parentage analysis showed that the cases identified the candidate's father only (77.0%), mother only (54.0%), and both parents (40.5%) in the candidate offspring population. The ET and AI calves were identified as 14.7% in the in vitro fertilized eggs provided and 32.4% in total population, respectively. However, the result from ISAG marker analysis showed 3 identical allele-combinations in 7 calves, and that from ISAG/SAES MS marker combination also showed 1 identical allele-combination in 2 calves. Data from MS and coat-color gene analyses provided information for complete identification of all animals tested. Because the present JBC population was mostly bred using small nuclear founders through bioengineering techniques such as AI and ET, the genetic diversity levels obtained from MS analysis in the JBC population were relatively lower than those of other cattle populations, including Hanwoo. The results suggested that the more efficient marker combinations, including coat color related genotypes, should be studied and used for constructing a system for identification and molecular breeding of JBC as well.

• Management & Information Systems Review
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• v.39 no.1
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• pp.35-57
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• 2020

Recently, research F&E(Facilities and Equipment) have become very important as tools and means to lead the development of science and technology. The government has been continuously expanding investment budgets for R&D and research F&E, and the need for efficient operation and systematic management of research F&E built up nationwide has increased. In December 2010, The government developed and completed a standardized classification system for national research F&E. However, accuracy and trust of information classification are suspected because information is collected by a method in which a user(researcher) directly selects and registers a classification code in NTIS. Therefore, in the study, we analyzed linearly using linear discriminant analysis(LDA) and analysis of variance(ANOVA), to measure the classification accuracy for the standardized classification system(8 major-classes, 54 sub-classes, 410 small-classes) of the national research facilities and equipment established in 2010, and revised in 2015. For the analysis, we collected and used the information data(50,271 cases) cumulatively registered in NTIS(National Science and Technology Service) for the past 10 years. This is the first case of scientifically verifying the standardized classification system of the national research facilities and equipment, which is based on information of similar classification systems and a few expert reviews in the in-outside of the country. As a result of this study, the discriminant accuracy of major-classes organized hierarchically by sub-classes and small-classes was 92.2 %, which was very high. However, in post hoc verification through analysis of variance, the discrimination power of two classes out of eight major-classes was rather low. It is expected that the standardized classification system of the national research facilities and equipment will be improved through this study.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.77-92
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• 2014

Recently, numerous documents including unstructured data and text have been created due to the rapid increase in the usage of social media and the Internet. Each document is usually provided with a specific category for the convenience of the users. In the past, the categorization was performed manually. However, in the case of manual categorization, not only can the accuracy of the categorization be not guaranteed but the categorization also requires a large amount of time and huge costs. Many studies have been conducted towards the automatic creation of categories to solve the limitations of manual categorization. Unfortunately, most of these methods cannot be applied to categorizing complex documents with multiple topics because the methods work by assuming that one document can be categorized into one category only. In order to overcome this limitation, some studies have attempted to categorize each document into multiple categories. However, they are also limited in that their learning process involves training using a multi-categorized document set. These methods therefore cannot be applied to multi-categorization of most documents unless multi-categorized training sets are provided. To overcome the limitation of the requirement of a multi-categorized training set by traditional multi-categorization algorithms, we propose a new methodology that can extend a category of a single-categorized document to multiple categorizes by analyzing relationships among categories, topics, and documents. First, we attempt to find the relationship between documents and topics by using the result of topic analysis for single-categorized documents. Second, we construct a correspondence table between topics and categories by investigating the relationship between them. Finally, we calculate the matching scores for each document to multiple categories. The results imply that a document can be classified into a certain category if and only if the matching score is higher than the predefined threshold. For example, we can classify a certain document into three categories that have larger matching scores than the predefined threshold. The main contribution of our study is that our methodology can improve the applicability of traditional multi-category classifiers by generating multi-categorized documents from single-categorized documents. Additionally, we propose a module for verifying the accuracy of the proposed methodology. For performance evaluation, we performed intensive experiments with news articles. News articles are clearly categorized based on the theme, whereas the use of vulgar language and slang is smaller than other usual text document. We collected news articles from July 2012 to June 2013. The articles exhibit large variations in terms of the number of types of categories. This is because readers have different levels of interest in each category. Additionally, the result is also attributed to the differences in the frequency of the events in each category. In order to minimize the distortion of the result from the number of articles in different categories, we extracted 3,000 articles equally from each of the eight categories. Therefore, the total number of articles used in our experiments was 24,000. The eight categories were "IT Science," "Economy," "Society," "Life and Culture," "World," "Sports," "Entertainment," and "Politics." By using the news articles that we collected, we calculated the document/category correspondence scores by utilizing topic/category and document/topics correspondence scores. The document/category correspondence score can be said to indicate the degree of correspondence of each document to a certain category. As a result, we could present two additional categories for each of the 23,089 documents. Precision, recall, and F-score were revealed to be 0.605, 0.629, and 0.617 respectively when only the top 1 predicted category was evaluated, whereas they were revealed to be 0.838, 0.290, and 0.431 when the top 1 - 3 predicted categories were considered. It was very interesting to find a large variation between the scores of the eight categories on precision, recall, and F-score.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.2
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• pp.88-99
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• 2019

This study aims to conduct a depth analysis of motivation and value of local residents and tourists based on means-end chain theory. The sampling of the study was conducted on local residents living near downtown area of Gyeong-ju City, and tourists through soft laddering and hard laddering methods. A mutual correlation model in relation with Hierarchical Value Map (HVM) for each group by conducting the analysis of factor loading (attributes, consequences, value) and cognitive structure (the correlations among attributes, consequences and value) was proposed and the comparisons of HVM for each group was also conducted. The structured questionnaires using Association Pattern Technique (APT) of hard laddering were utilized to analyze the means and end of value chain structures in terms of the attributes, consequences, value of Gyeong-ju Ancient Tombs. The findings propose that local residents are visiting Ancient Tombs Gyeong-ju City Center for 'Rest and take a walk' as the means, which results in 'Relieving stress' and eventually leads to the 'Improvement of historic and cultural cultivation' as the end. On the other hand, tourists also 'Rest and take a walk' as the mean, which also leads to 'Relieving stress'. However, unlike local residents, it eventually leads to 'Self-reflection and healing' as the end. It is expected that the findings of this study not only recommend us to consider preserving and managing cultural heritages and value of ancient tombs in developing "Ancient Tomb Park in Gyoneg-ju City Center" but also provides baseline data for the establishment of reasonable plans of utilizing tombs, historical and cultural heritages.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.374-390
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• 2021

Growth and yield of field vegetable crops would be affected by climate conditions, which cause a relatively large fluctuation in crop production and consumer price over years. The yield prediction system for these crops would support decision-making on policies to manage supply and demands. The objectives of this study were to compile literatures related to onion and garlic and to perform data-mining analysis, which would shed lights on the development of crop models for these major field vegetable crops in Korea. The literatures on crop growth and yield were collected from the databases operated by Research Information Sharing Service, National Science & Technology Information Service and SCOPUS. The keywords were chosen to retrieve research outcomes related to crop growth and yield of onion and garlic. These literatures were analyzed using text mining approaches including word cloud and semantic networks. It was found that the number of publications was considerably less for the field vegetable crops compared with rice. Still, specific patterns between previous research outcomes were identified using the text mining methods. For example, climate change and remote sensing were major topics of interest for growth and yield of onion and garlic. The impact of temperature and irrigation on crop growth was also assessed in the previous studies. It was also found that yield of onion and garlic would be affected by both environment and crop management conditions including sowing time, variety, seed treatment method, irrigation interval, fertilization amount and fertilizer composition. For meteorological conditions, temperature, precipitation, solar radiation and humidity were found to be the major factors in the literatures. These indicate that crop models need to take into account both environmental and crop management practices for reliable prediction of crop yield.

• Journal of the Korea Institute of Building Construction
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• v.22 no.5
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• pp.473-483
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• 2022

BIM(Building Information Modeling) is a technology that can manage information throughout the entire life cycle of the construction industry and serves as a platform for improving productivity and integrating the entire construction industry. Currently, BIM is actively applied in developed countries, and its use at various overseas construction sites is increasing This is unclear. due to air shortening and budget savings. However, there is still a lack of institutional basis and technical limitations in the domestic construction sector, which have led to the lack of utilization of BIM. Various activation measures and institutional frameworks will need to be established for the early establishment of these productive BIMs in Korea. Therefore, as part of the research for the domestic settlement and revitalization of BIM, this study derived a number of key factors necessary for the development of the construction industry through brainstorming and expert surveys using AHP techniques and analyzed the relative importance of each factor. In addition, prior surveys by a group of experts resulted in 1, 3 items in level, 2, 9 items in level, and 3, 27 items in level, and priorities analysis was performed through pairwise comparisons. As a result of the AHP analysis, it was found that the relative importance weight of policy aspects was highest in level 1, and the policy factors in level 2 and the cost-based and incentive system introduction factors were considered most important in level 3. These findings show that the importance of the policy guidance or institutions underlying the activation of BIM rather than research and development or corporate innovation is relatively high, and that the preparation of policy plans by public institutions should be the first priority. Therefore, it is considered that the development of a policy system or guideline must be prioritized before it can be advanced to the next activation stage. The use of BIM technologies will not only contribute to improving the productivity of the construction industry, but also to the overall development of the industry and the growth of the construction industry. It is expected that the results of this study can provide as useful information when establishing policies for activating BIM in central government, relevant local governments, and related public institutions.