• Journal of the Korean Home Economics Association
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• v.51 no.1
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• pp.89-95
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• 2013

The purpose of this study is to identify a causal relationship among green consumer behavior, environmental knowledge and environmental attitudes of students at the university of education. A total of 366 copies of questionnaires were used for the data analysis; 31 copies were excluded due to lack of response to any given question. To ensure the reliability and validity of the questions, technical statistics were performed, such as frequency, ratio, average, standard deviation, skewness, and kurtosis via SPSS 15.0, item-total correlation and the totality, and reliability analysis. A structural analysis was undertaken via AMOS 7.0 in a bootstrapping method in order to perform a path analysis among variables as well as to assess the suitability of the model. The findings of the study were led to the following conclusions: First, the causal model among green consumer behavior, environmental knowledge and environmental attitudes of students at the university of education is suitable to the empirical analysis on research variables. Second, the environmental attitudes of students at the university of education has a direct, positive effect on green consumer behavior. Third, the environmental knowledge of students at the university of education has an indirect, positive effect on green consumer behavior.

• Journal of KIISE:Software and Applications
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• v.32 no.6
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• pp.473-485
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• 2005

UML activity diagram is useful to model business process and workflow by reason of its suitability to present dynamic aspect of system. However it Is difficult to present precise semantics which is taken as important in workflow system with the guide provided by OMG to the UML activity diagram. This paper suggests workfolw system modelling methodology by applying ASM semantics to the activity diagram after extending its semantics to correspond to workflow system characteristics. Through the exact definition to formal semactics based on ASM it is possible to effectively model workflow.

• Journal of the Korean Solar Energy Society
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• v.34 no.6
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• pp.39-47
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• 2014

Daylighting has a great effect on people inside the room. It is also closely related to the lighting energy consumption. Daylight factor(DF) is a very important index for evaluation of the daylighting in overcast sky. The objective of this study is to verify the suitability of the Tregenza's Modified Split Flux formula for the calculation of the daylight factor. We compared the daylight factors calculated by two methods; one by a measurement with 1/5 scale model and the other by the Daysim program. We used variables for verification as window wall ratios(WWR) and angles of the sky visible. As a result, daylight factor calculated by Modified Split Flux is similar to the measurement when more daylight enters the inside. And error is significantly increased when the angle of the sky visible is $50^{\circ}$.

• Journal of the Korean Society for Railway
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• v.10 no.4
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• pp.444-450
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• 2007

The bi-modal tram guided by the magnetic guidance system has two car-bodies and three axles. Each axle of the vehicle has an independent suspension to lower the floor of the car and improve ride quality. The turning radius of the vehicle may increase as a consequence of the long wheel base. Therefore, the vehicle is equipped with the All-Wheel-Steering(AWS) system for safe driving on a curved road. Front and rear axles should be steered in opposite directions, which means a negative mode, to minimize the turning radius. On the other hand, they also should be steered in the same direction, which means a positive mode, for the stopping mode. Moreover, only the front axle is steered for stability of the vehicle upon high-speed driving. In summary, steering angles and directions of the each axle should be changed according to the driving environment and steering mode. This paper proposes an appropriate AWS control algorithm for stable driving of the bi-modal tram. Furthermore, a multi-body model of the vehicle is simulated to verify the suitability of the algorithm. This model can also analyze the different dynamic characteristics between 2WS and AWS.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.327-327
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• 2018

돌발홍수, 집중호우 등 강우가 발생 원인되는 자연재해에 효과적으로 대응하기 위한 연구가 활발히 이루어지고 있으나 강우의 시공간 변동성과 발생과정의 복잡한 물리과정으로 인해 강우 추정에 한계를 가진다. 일반적으로 강우 추정은 물리적, 추계학적 모형을 이용하며 추계학적 모형의 점과정(point process)을 이용하여 강우를 생산한다. 추계학적 강우 모형은 관측 강우의 시간 스케일, 강우발생 빈도, 강우 강도 등 강우 구조의 특성을 반영 할 수 있다는 장점을 가지고 있으나 생산되는 강우의 구조가 추정되는 매개변수에 크게 의존한다는 점에서 실제 강우에 적합한 매개변수 추정이 중요하다. 본 연구에서는 낙동강 유역내에 있는 20개의 강우관측 지점을 대상으로 1973년-2017년까지의 강우 관측자료를 수집하였으며 추계학적 강우생성 모형으로 점과정을 이용하는 추계학적 강우생성 모형인 NSRPM(Neymann-Scott rectangular pulse model)을 선정하였다. NSRPM모형의 매개변수를 추정하기위한 최적기법으로 DFP(Davidon-Fletcher-Powell), GA(genetic algorithm), Nelder-Mead, DE(differential evolution)를 이용하여 추정된 매개변수의 적합성을 분석하고 지역특성을 고려한 매개변수 추정 기법을 제시하였다. 추정된 모형의 매개변수를 분석한 결과 DE와 Nelder-Mead 기법이 높은 적합성을 보였으며 DFP, GA기법이 상대적으로 낮은 적합도를 보였다.

• Communications for Statistical Applications and Methods
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• v.28 no.4
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• pp.393-410
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• 2021

The Korean Long-Term Care Insurance (K-LTCI) provides financial support for long-term care service to people who need various types of assistance with daily activities. As the number of elderly people in Korea is expected to increase in the future, the demand for long-term care insurance would also increase over time. Projection of future expenditure on K-LTCI depends on the number of beneficiaries within the grading system of K-LTCI based on the test scores of applicants. This study investigated the suitability of mixture distributions to the model K-LTCI score distribution using recent empirical data on K-LTCI, provided by the National Health Insurance Service (NHIS). Based on the developed mixture models, the number of beneficiaries in each grade and its variability under the current grading system were estimated by simulation. It was observed that a mixture model is suitable for K-LTCI score distribution and may prove useful in devising a funding plan for K-LTCI benefit payment and investigating the effects of any possible revision in the K-LTCI grading system.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.378-385
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• 2023

The importance of wearing respiratory protective equipment has been highlighted even more during the COVID-19 pandemic. Even if the suitability of respiratory protection has been confirmed through testing in a laboratory environment, there remains the potential for leakage points in the respirators due to improper application by the wearer, damage to the equipment, or sudden movements in real working conditions. In this paper, we propose a method to detect the occurrence of leak holes by measuring the pressure changes inside the mask according to the wearer's breathing activity by attaching an IoT sensor to a full-face respirator. We designed 9 experimental scenarios by adjusting the degree of leak holes of the respirator and the breathing cycle time, and acquired respiratory data for the wearer of the respirator accordingly. Additionally, we analyzed the respiratory data to identify the duration and pressure change range for each breath, utilizing this data to train a neural network model for detecting leak holes in the respirator. The experimental results applying the developed neural network model showed a sensitivity of 100%, specificity of 94.29%, and accuracy of 97.53%. We conclude that the effective detection of leak holes can be achieved by incorporating affordable, small-sized IoT sensors into respiratory protective equipment.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.398-403
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• 2023

Process-based K-cabbage model is based on physiological processes such as photosynthesis and phenology, making it possible to predict crop growth under different climate conditions that have never been experienced before. Current first-stage process-based models can be used to assess climate impact through yield prediction based on climate change scenarios, but no comparison has been performed between big data obtained from the main production area and model prediction so far. The aim of this study was to find out the direction of model improvement when using the current model for yield prediction. For this purpose, model performance evaluation was conducted based on data collected from farmers growing 'Chungwang' cabbage in Taebaek and Samcheok, the main producing areas of Chinese cabbage in highland region. The farms surveyed in this study had different cultivation methods in terms of planting date and soil water and nutrient management. The results showed that the potential biomass estimated using the K-cabbage model exceeded the observed values in all cases. Although predictions and observations at the time of harvest did not show a complete positive correlation due to limitations caused by the use of fresh weight in the model evaluation process (R²=0.74, RMSE=866.4), when fitting the model based on the values 2 weeks before harvest, the growth suitability index was different for each farm. These results are suggested to be due to differences in soil properties and management practices between farms. Therefore, to predict attainable yields taking into account differences in soil and management practices between farms, it is necessary to integrate dynamic soil nutrient and moisture modules into crop models, rather than using arbitrary growth suitability indices in current K-cabbage model.

• Journal of Korean Society of Transportation
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• v.26 no.3
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• pp.211-221
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• 2008

This dissertation studied the psychological cost, which converted the mental pain suffered by the victim of a traffic accident and his/her family, friends and people around him/her into social costs. Three methodologies - Choice Experiments, Direct Question and Dichotomous Choice Question - were used to design questionnaires, and models were built for each questionnaire design method. When building models, a logit model was used, which is used most frequently in probabilistic choice model. And the tobitmodel was used to make direct questionnaires. When verifying these models, although there were some differences in each model, suitability of most models and credibility of each coefficient were meaningful around the credibility level of 95%. According to the analysis, domestic psychological cost produced through the assessment model of psychological cost was 15.63 million won per person or 5.1 trillion in total, assuming 37.1% of total traffic accident cost.

• Journal of Digital Convergence
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• v.14 no.5
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• pp.341-348
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• 2016

Because VPN(Virtual Private Network) uses internet network, the security technique should support it and evaluation technique based on standard should support it. Therefore the method should be organized that can evaluate the security of VPN based on the related standard. In this study, we intended to construct the security evaluation model through combining CC(Common Criteria) which is a evaluation standard and a part of security(Confidentiality, Integrity, Non-repudiation, Accountability, Authenticity) evaluation of ISO which is the standard of software quality evaluation. For this, we analyzed the quality requirements about intra-technology and security of VPN and constructed the evaluation model related to the quality characteristics of two international standard. Through this, we are able to construct a convergence model for security evaluation of VPN. Through accumulating the evaluation practices for VPN in the future, the suitability and validity of the evaluation model must be improved.