• Safety and Health at Work
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• v.7 no.1
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• pp.43-48
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• 2016

Background: Work Ability Index (WAI) is a well-known and valid self-report tool that has been widely used in various studies to identify and avoid early retirement and work-related disability. Nevertheless, very few studies have been carried out to evaluate work ability in Iran. We aimed to investigate the WAI and the effect of work-related stress on it among Iranian workers. Methods: A cross-sectional, descriptive and analytic study was carried out among 449 workers from five working sectors in three big cities of Iran. Work ability and work-related stress were measured using the Persian version of WAI and the Persian version of Health and Safety Executive Stress Indicator Tool. Results: More than a third of the workers surveyed (34.70%) did not have an appropriate level of work ability (WAI < 37). There was a significant correlation between subscales of work-related stress and the mean score of WAI. Furthermore, the variables of body mass index, sleep quality, exercise activity, job tenure, and three subscales of work-related stress including demands, supervisor support, and role were significant predictors of WAI. Conclusion: According to the results of this study, the interventional programs must be focused on improving supervisors support, eliminating ambiguity and conflicts in the role of workers in their job and organization, reducing job demands, improving sleep quality, and increasing exercise activity.

• Korean Journal of Remote Sensing
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• v.24 no.1
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• pp.45-55
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• 2008

The impact on streamflow and groundwater recharge considering future potential climate and land use change was assessed using SLURP (Semi-distributed Land-Use Runoff Process) continuous hydrologic model. The model was calibrated and verified using 4 years (1999-2002) daily observed streamflow data for a $260.4km^2$ which has been continuously urbanized during the past couple of decades. The model was calibrated and validated with the coefficient of determination and Nash-Sutcliffe efficiency ranging from 0.8 to 0.7 and 0.7 to 0.5, respectively. The CCCma CGCM2 data by two SRES (Special Report on Emissions Scenarios) climate change scenarios (A2 and B2) of the IPCC (Intergovemmental Panel on Climate Change) were adopted and the future weather data was downscaled by Delta Change Method using 30 years (1977 - 2006, baseline period) weather data. The future land uses were predicted by CA (Cellular Automata)-Markov technique using the time series land use data of Landsat images. The future land uses showed that the forest and paddy area decreased 10.8 % and 6.2 % respectively while the urban area increased 14.2 %. For the future vegetation cover information, a linear regression between monthly NDVI (Normalized Difference Vegetation Index) from NOAA/AVHRR images and monthly mean temperature using five years (1998 - 2002) data was derived for each land use class. The future highest NDVI value was 0.61 while the current highest NDVI value was 0.52. The model results showed that the future predicted runoff ratio ranged from 46 % to 48 % while the present runoff ratio was 59 %. On the other hand, the impact on runoff ratio by land use change showed about 3 % increase comparing with the present land use condition. The streamflow and groundwater recharge was big decrease in the future.

• Journal of Digital Convergence
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• v.17 no.9
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• pp.71-78
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• 2019

This study aims to identify good borrowers within the context of P2P lending. P2P lending is a growing platform that allows individuals to lend and borrow money from each other. Inherent in any loans is credit risk of borrowers and needs to be considered before any lending. Specifically in the context of P2P lending, traditional models fall short and thus this study aimed to rectify this as well as explore the problem of class imbalances seen within credit risk data sets. This study implemented an over-sampling technique known as Synthetic Minority Over-sampling Technique (SMOTE). To test our approach, we implemented five benchmarking classifiers such as support vector machines, logistic regression, k-nearest neighbor, random forest, and deep neural network. The data sample used was retrieved from the publicly available LendingClub dataset. The proposed SMOTE revealed significantly improved results in comparison with the benchmarking classifiers. These results should help actors engaged within P2P lending to make better informed decisions when selecting potential borrowers eliminating the higher risks present in P2P lending.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.6
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• pp.784-792
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• 2018

In this study, we designed the area except the development market and the traditional market, where large scale shops were concentrated by realizing the real estate center of the alley commercial area. In addition, we have developed an area setting method for the alley area where reliability and rationality can be ensured by utilizing the actual data such as the business statistics, the survey data of the business, and the store business DB, which are managed by the local government or the state. The alley commercial areas were classified into five groups according to density. It is thought that users can distinguish the commercial areas from dense commercial areas to the commercial areas in order to utilize various commercial areas.

• Laboraroty Animal Research
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• v.34 no.4
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• pp.311-316
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• 2018

Laboratory inbred mice are used widely and commonly in biomedical research, but inbred mice do not have a big enough gene pool for the research. In this study, genetic and morphometric analyses were performed to obtain data on the characteristics of a newly developing inbred strain (KWM/Hym) captured from Chuncheon, Korea. All of five Korean wild male mice have the zinc-finger Y (ZfY) gene. Also, all of 19 Korean wild mice used in this analysis have the AKV-type murine leukemia virus gene, indicating that Korean wild mice might be Mus musculus musculus. To identify the genetic polymorphism in KWM/Hym, SNP analysis was performed. In a comparison with 28 SNP markers, there was a considerable difference between KWM/Hym and several inbred strains. The homogeneity between KWM/Hym and the inbred strains was as follows: C57BL/6J (39.3%), BALB/c AJic (42.9%), and DBA/2J (50%). KWM/Hym is most similar to the PWK/PhJ inbred strain (96.4%) derived from wild mice (Czech Republic). To identify the morphometric characteristics of KWM/Hym, the external morphology was measured. The tail ratio of male and female was $79.60{\pm}3.09$ and $73.55{\pm}6.14%$, respectively. KWM/Hym has short and agouticolored hairs and its belly is white with golden hair. Taking these results together, KWM/Hym, a newly developing inbred mouse originated from wild mouse, might be use as new genetic resources to overcome the limitations of the current laboratory mice.

• Journal of Digital Convergence
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• v.17 no.4
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• pp.13-18
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• 2019

The purposes of the present study were finding out educational implications and enhancing the efficient use of computer-based assessments (CBA) in class designes. This paper examined associations of CBA perceptional typology, academic achievement, personality, and computer efficacy. Participants were fifty senior students who took more than 50% of CBA classes in a university that introduces online learning-based system (LMS) with CBA. As a result, there were significant differences between CBA types and GPA and between CBA types and personality. In other words, the CBA adjustment type showed the highest GPA score and CBA dissatisfaction/paper test preference type showed the lowest GPA. Similarly, in terms of personality, CBA adjustment typology was significantly higher conscientiousness than other types. CBA dissatisfaction type had the lowest score of conscientiousness. In addition, the higher the level of conscientiousness, agreeableness and neuroticism, the higher the GPA score. This study is meaningful in that it is the first attempt to seek links CBA type with academic achievement and personality.

• Journal of Cadastre & Land InformatiX
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• v.49 no.1
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• pp.113-121
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• 2019

The fourth industrial revolution technology focused on the fusion of infrastructure and various advanced technologies related city. Therefore, technical cooperation in various fields of research is essential. In order to activating the fourth industrial revolution technologies, it is necessary to research the state of technology in various fields. Consequently, this paper aims to analysis of domestic and foreign research trends on technology to the fourth industrial revolution using SNA and text mining for web site. We collected text, date data of research paper and report in web site for five years, that is, from January 1st in 2014 to December 31st in 2018. Next, we have deduced the major keywords in public data through analyzing the morphemes. Then we have analyzed the core and related keyword lists through an SNA. In Korea, the focus is on R&D and legal/institutional solution in relation to the fourth industrial revolution technology. On the other hand, in the case of foreign, there was focus on practical technologies for urban services in detail aspects.

• Journal of the Korea Convergence Society
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• v.10 no.10
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• pp.7-13
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• 2019

The natural gas (NG), mostly methane leaks into the air, it is a big problem for the climate. detected NG leaks under U.S. city streets and collected data. In this paper, we introduced a Deep Neural Network (DNN) classification of prediction for a level of NS leak. The proposed method is OrdinalEncoder(OE) based K-means clustering and Multilayer Perceptron(MLP) for predicting NG leak. The 15 features are the input neurons and the using backpropagation. In this paper, we propose the OE method for labeling target data using k-means clustering and compared normalization methods performance for NG leak prediction. There five normalization methods used. We have shown that our proposed OE based MLP method is accuracy 97.7%, F1-score 96.4%, which is relatively higher than the other methods. The system has implemented SPSS and Python, including its performance, is tested on real open data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.2
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• pp.111-116
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• 2019

New technologies such as the IoT, Big Data, and Artificial Intelligence, starting from the Web, mobile, and smart device, enable new business models that did not exist before, and various types of Internet companies based on these business models has been emerged. In this research, we examine the factors that influence the success and failure of Internet companies. To do this, we review the recent studies on business model and examine the variables affecting the success of Internet companies in terms of network effect, user interface, cooperation with actors, creating value for users. Using the five derived variables, we will select 14 Internet companies that succeeded and failed in seven commercial business model categories. We derive decision tree by applying inductive learning based on ID3 algorithm to the analysis result and derive rules that affect success and failure based on derived decision tree. With these rules, we want to present the strategic implications for actors to succeed in Internet companies.

• Journal of The Korean Association For Science Education
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• v.39 no.1
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• pp.129-141
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• 2019

As the number of minority students such as multicultural, North Korean defectors, and low-income groups increases, more research is needed in science education to help their learning. Due to the various growth backgrounds and learning environments of the underprivileged students, there is a big difference in the individual characteristics of the group rather than the whole group characteristics. In this study, we conducted about 50 hours of science lessons for seven students in the underprivileged class, categorized them by observing and interviewing the characteristics of their science learning. Seven underprivileged students showed five different learning patterns, these are 'I love science', 'I think I know science', 'I want to know science', 'I need to know science', and 'I don't know what I want'. Although the scientific activities they experienced were not all of an excellent educational quality, their interest in science learning has increased with their experience in science activities. It shows the need to provide more abundant science experience and educational opportunities for these minority students who can only experience science learning under the public educational system.