• Journal of Korean Society of Rural Planning
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• v.19 no.4
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• pp.149-160
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• 2013

In this study, it propose what the landscape elements is to be improved urgently and how to improve landscape by reflecting the rural village characteristics away from the spatial integrated landscape planning. The study area for landscape research is selected as the 9 rural villages in Chungcheongbuk-do, and research is done by using village unit landscape diagnostic index(VULDI). the result is shown that average VULDI value of the rural village zones is bigger than one of the town village zones with difference of 15%. Two zones of Chilseong-myeon and Sangchon-myeon among the town village zones are appeared to be similar with the rural village zones in landscape level by VULDI value. Generally, the rural villages to maintain the good landscape have the low population and high engagement rate in agriculture. Looking political support criteria at the landscape level, the seven zones except Deoksan-myeon and Maengdong-myeon have high VULDI value more than 60%, which means that it seems unnecessary to support political landscape improvement. However, when it is divided into two parts of the village inside landscape and the surrounding landscape, 8 rural village zones except one zone of Sangchon-myeon have low VULDI value less than 60%, which means it is necessary to support political landscape improvement. It is important to give the intensive support of ever urgent landscape improvements and high priority landscape elements on the results of the diagnostic before planning of the rural landscape formation.

• Journal of Forest and Environmental Science
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• v.24 no.1
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• pp.27-34
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• 2008

Level and distribution of genetic diversity in seven populations of Albizia lucida Benth. in eastern region of the Indian sub-continent were estimated using ISSR markers. Relatively higher level of genetic diversity within populations was observed in seven populations of A. lucida (mean of 0.38). From the result of AMOVA, majority of genetic diversity was allocated within populations (96.2%) resulting in a moderate degree of population differentiation. The observed distribution pattern of I-SSR variant among the populations was coincided with the typical pattern of long-lived woody tree species. Genetic relationships among the populations, reconstructed by UPGMA method, revealed two genetic groups. The population of Anugul and Bargarh turned out to be the most closely related despite a distance location between them. These formations will be of great value in the development of conservation plans for species exhibiting high levels of genetic differentiation due to fragmentation, such as indication of conservation unit size, which populations should be chosen as priority in conservation plans and which samples should be introduced in areas with a low number of individuals of A. lucida.

• Asian Journal of Atmospheric Environment
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• v.11 no.3
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• pp.194-201
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• 2017

This study investigates the factors that affect China's air pollution using city-level panel data and spatial econometric models. We address three air pollutants ($PM_{10}$, $SO_2$, and $NO_2$) present in 30 cities in China between 2004-2012 using global OLS and spatial models. To develop the spatial econometric analysis, we create a spatial weights matrix to define spatial patterns based on two neighborhood criteria - the queen contiguity and k nearest neighbors. The results show that the estimated coefficients are relatively consistent across different spatial weight criteria. The OLS models indicate that the effect of green spaces is statistically significant in decreasing the concentrations of all air pollutants. In the $PM_{10}$ and $SO_2$ analyses, the OLS models find that the number of buses and population density are also positively related to a reduction in the concentration of air pollutants. In addition, an increase in the temperature and the presence of secondary industries increase $SO_2$ and $NO_2$ concentrations, respectively. All spatial models capture a positive and significant effect of green spaces on reducing the concentration of each air pollutant. Our results suggest that green spaces in cities should receive priority consideration in local planning aimed at sustainable development. Furthermore, policymakers need to be able to discern the differences among pollutants when establishing environmental policies.

• Health Policy and Management
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• v.6 no.1
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• pp.29-58
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• 1996

This study was conducted to identify the factors that affect the output of health conters. An analystical model employed in this study was developed by modifying 'input-output model' and 'organizational behavior model'. Data were collected form two source; the 1995 report of thealth center which was submitted to the Ministry of Health and Welfare and a mail survey questionary of officers at health center, including 66 directors and 1,768 staffs of the health centers in southern region. The major findings are as follows: That analysis has identified the factors associated with dependent variables: medical services provided by the health center and health program performance(HPP). The number of primary medical facilities was negatively associated with health center performance while the number of staffs, job satisfaction, and professional background of health center directors were positively associated. These independent variables accounted for 40.1% of the variance of dependent variables. The variance of HPP was significantly explained by the number of health subcenter and primary health post, priority level of public health program by hief executive officers(CEOs) and legislator. A significant relationship was found between leadership types of health center directors and the performance of maternal and child health program. Considering these results, the authors suggested that the role in medical care service of health center in the should be rearranged at local level because medical care service of the health center is competing with primary medical facilities in the same region. It is also suggested that educational efforts be made to improve leadership of the health center directors and concern with public health program by the CEOs and legislators of local governments.

• Journal of the Korea Institute of Military Science and Technology
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• v.19 no.1
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• pp.57-65
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• 2016

Threat evaluation is a process to estimate the threat score which enemy aerial threat poses to defended assets. The objective of threat evaluation is concerned with making an engagement priority list for optimal weapon allocation. Traditionally, the threat evaluation of massive air threats has been carried out by air defence experts, but the human decision making is less effective in real aerial attack situations with massive enemy fighters. Therefore, automation to enhance the speed and efficiency of the human operation is required. The automatic threat evaluation by air defense experts who will perform multi-variable judgment needs formal models to accurately quantify their linguistic evaluation of threat level. In this paper we propose a threat evaluation model by using a fuzzy rule-based inference method. Fuzzy inference is an appropriate method for quantifying threat level and integrating various threat attribute information. The performance of the model has been tested with a simulation that reflected real air threat situation and it has been verified that the proposed model was better than two conventional threat evaluation models.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.2993-3010
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• 2021

The job shop scheduling problem (JSSP) plays a critical role in smart manufacturing, an effective JSSP scheduler could save time cost and increase productivity. Conventional methods are very time-consumption and cannot deal with complicated JSSP instances as it uses one optimal algorithm to solve JSSP. This paper proposes an effective scheduler based on deep learning technology named self-supervised long-short term memory (SS-LSTM) to handle complex JSSP accurately. First, using the optimal method to generate sufficient training samples in small-scale JSSP. SS-LSTM is then applied to extract rich feature representations from generated training samples and decide the next action. In the proposed SS-LSTM, two channels are employed to reflect the full production statues. Specifically, the detailed-level channel records 18 detailed product information while the system-level channel reflects the type of whole system states identified by the k-means algorithm. Moreover, adopting a self-supervised mechanism with LSTM autoencoder to keep high feature extraction capacity simultaneously ensuring the reliable feature representative ability. The authors implemented, trained, and compared the proposed method with the other leading learning-based methods on some complicated JSSP instances. The experimental results have confirmed the effectiveness and priority of the proposed method for solving complex JSSP instances in terms of make-span.

• Journal of muscle and joint health
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• v.27 no.3
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• pp.211-218
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• 2020

Purpose: This study aimed to identify and prioritize the content needs of patients with osteoarthritis (OA) for developing self-management mobile applications. Methods: A total of 126 participants with OA were recruited from two orthopedic hospitals. They completed the self-report questionnaires after providing written informed consent. The Borich needs assessment model was used to assess the perceived level of competence and perceived level of importance regarding 21 items for self-management of OA. The collected data were weighted and ranked in order of priority. Results: The top five content items needed by OA patients were 'How to avoid excessive use of the joints' (15.03); 'Lifestyle tips on the prevention and management of arthritis' (13.69); 'Exercise types and procedures for OA' (12.54); 'Good and bad exercises for the joints' (9.80); and 'Precautions for exercise (duration, frequency, safety)' (8.88). Need rankings related to causes and treatment of OA were relatively low. Conclusion: OA patients requested self-management competencies that should be practiced in daily activities to reduce the discomfort. The results of this study have practical implications for defining the content of self-management applications for patients with OA. Based on the results, developing a self-management intervention program for OA patients using a mobile is recommended.

• Korean Journal of Construction Engineering and Management
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• v.5 no.2 s.18
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• pp.136-143
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• 2004

This study presents a risk management methodology using fuzzy theory for early construction stage and is focused on risk identification and risk analysis. This study identifies various risk factors associated with activities clearly construction stage, then establishes the Risk Breakdown Structure(RBS) by classifying the risks into the three groups; Common risks, risks for Earth works, and risks for Foundation works. The risk analysis method presented in this study is based on the RBS that has two levels such as upper level and lower level. The risk exposure of lower level risk factors is assessed by fuzzy inference. The weight of risks is estimated by fuzzy measure. Then, the estimated risk exposures and weights are aggregated to assess the risk exposure of upper level risks by Choquet fuzzy integral. The risk exposure of upper level risks determine the priority of risk factors in view of risk management. This study performs case study to validate the proposed method. The result of case study shows that the methodology suggested in this thesis would be utilized well in evaluating risk exposure.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.9
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• pp.219-228
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• 2020

The study investigates the impact of inflation rate on economic growth to find the best-fit model for economic growth in Vietnam. The study applied Vector Autoregressive (VAR), cointegration models, and unit root test for the time-series data from 1996 to 2018 to test the inflation impact on the economic growth in the short and long term. The study showed that the two variables are stationary at lag first difference I(1) with 1%, 5% and 10%; trace test indicates two cointegrating equations at the 0.05 level, the INF does not granger cause GDP, the optimal lag I(1) and the variables are closely related as R2 is 72%. It finds that the VAR model's results are the basis to perform economic growth; besides, the inflation rate is positively related to economic growth. The results support the monetary policy. This study identifies issues for Government to consider: have a comprehensive solution among macroeconomic policies, monetary policy, fiscal policy and other policies to control and maintain the inflation and stimulate growth; set a priority goal for sustainable economic growth; not pursue economic growth by maintaining the inflation rate in the long term, but take appropriate measures to stabilize the inflation at the best-fitted VAR forecast model.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2002.03a
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• pp.13-19
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• 2002

In inner harbour of Inchon Port, there are two lock gates (50KT, 10KT) which have two gates per lock gate in inner/outer sides except a gate in inner harbour side 7f 10KT. Due to the lack of the fore-mentioned gate, the use of 10KT lock gate Is suspended in every 3 years for regular maintenance. Now an additional gate is under construction in order to improve the efficiency of the 10KT lock gate. This paper will be aimed to evaluate the operational utilization levels of lock gates in present and future. The present operational utilization levels of lock gates are 0.2119 in 10KT lock gate, 0.2051 in 50KT lock gate which were considered the 46.5 closed days every 3 years for 10KT regular maintenance. The levels are estimated to 0.2246(10KT), 0.2539(50KT) in 2006 and 0.2241(10KT), 0.2560(50KT) in 2011. The levels of 50KT lock gate are evaluated to be more rapidly increased up to 24.5% in 2011.