• Geomechanics and Engineering
• /
• v.28 no.6
• /
• pp.599-611
• /
• 2022

Tendon reinforced cemented soil is applied extensively in foundation stabilisation and improvement, especially in areas with soft clay. To solve the deterioration problem led by steel corrosion, the glass fiber-reinforced polymer (GFRP) tendon is introduced to substitute the traditional steel tendon. The interface bond strength between the cemented soil matrix and GFRP tendon demonstrates the outstanding mechanical property of this composite. However, the lack of research between the influence factors and bond strength hinders the application. To evaluate these factors, back propagation neural network (BPNN) is applied to predict the relationship between them and bond strength. Since adjusting BPNN parameters is time-consuming and laborious, the particle swarm optimisation (PSO) algorithm is proposed. This study evaluated the influence of water content, cement content, curing time, and slip distance on the bond performance of GFRP tendon-reinforced cemented soils (GTRCS). The results showed that the ultimate and residual bond strengths were both in positive proportion to cement content and negative to water content. The sample cured for 28 days with 30% water content and 50% cement content had the largest ultimate strength (3879.40 kPa). The PSO-BPNN model was tuned with 3 neurons in the input layer, 10 in the hidden layer, and 1 in the output layer. It showed outstanding performance on a large database comprising 405 testing results. Its higher correlation coefficient (0.908) and lower root-mean-square error (239.11 kPa) were obtained compared to multiple linear regression (MLR) and logistic regression (LR). In addition, a sensitivity analysis was applied to acquire the ranking of the input variables. The results illustrated that the cement content performed the strongest influence on bond strength, followed by the water content and slip displacement.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.45 no.3
• /
• pp.57-65
• /
• 2022

DEA(data envelopment analysis) is a technique for evaluation of relative efficiency of decision making units (DMUs) that have multiple input and output. A DEA model measures the efficiency of a DMU by the relative position of the DMU's input and output in the production possibility set defined by the input and output of the DMUs being compared. In this paper, we proposed several DEA models measuring the multi-period efficiency of a DMU. First, we defined the input and output data that make a production possibility set as the spanning set. We proposed several spanning sets containing input and output of entire periods for measuring the multi-period efficiency of a DMU. We defined the production possibility sets with the proposed spanning sets and gave DEA models under the production possibility sets. Some models measure the efficiency score of each period of a DMU and others measure the integrated efficiency score of the DMU over the entire period. For the test, we applied the models to the sample data set from a long term university student training project. The results show that the suggested models may have the better discrimination power than CCR based results while the ranking of DMUs is not different.

• Journal of Convergence for Information Technology
• /
• v.12 no.3
• /
• pp.252-258
• /
• 2022

In this study, we propose a method for analyzing students' understanding of probability and statistics in small lectures at universities. A computer-based test for probability and statistics was performed on 95 science and engineering college students. After dividing the students' responses into 7 clusters using the Robust PCA and the Gaussian mixture model, the achievement of each subject was analyzed for each cluster. High-ranking clusters generally showed high achievement on most topics except for statistical estimation, and low-achieving clusters showed strengths and weaknesses on different topics. Compared to the widely used PCA-based dimension reduction followed by clustering analysis, the proposed method showed each group's characteristics more clearly. The characteristics of each cluster can be used to develop an individualized learning strategy.

• Journal of Korean Society of Rural Planning
• /
• v.29 no.4
• /
• pp.27-34
• /
• 2023

Recently, worldwide to respond to climate change and secure sustainability. Korea aimed to increase water use efficiency by implementing integrated management according to the water management unification policy. Therefore, the necessity of establishing and operating governance is expanding to ensure the sustainability of agricultural water. In this study aims to evaluate the importance of agricultural water governance components and provide essential data for the participation of stakeholders in the efficient use of agricultural water in Korea. For this study, a total of 19 respondents to the ANP survey for this study were composed of experts in agricultural water and governance in Korea. As a result, the ranking for the main components was in the order of law, policy, and systems(0.222), core subjects(0.191), information sharing and communication(0.180), budget support(0.178), mutual learning(0.124), and external experts(0.105). The most important components for the operation of agricultural water governance are laws, policies, and systems. Since Korea's agricultural water management is a public management system, national standards are considered the first priority. This study, which is the purpose of the agricultural water governance model, evaluated the importance of the constituent components for participating in demand management with a sense of responsibility. Moreover, if agricultural water governance is expanded nationwide by reflecting agricultural and water resource policies in the future, it is believed that positive effects can be achieved in increasing utilization efficiency and securing sustainability through agricultural water saving.

• Human Ecology Research
• /
• v.61 no.4
• /
• pp.521-541
• /
• 2023

The purpose of this study is to demonstrate the antecedent and consequential factors of satisfaction with the flexible working system. Organizational culture was examined as an antecedent factor, while job satisfaction, work performance, organizational commitment, turnover intention, and quality of life were examined as outcome factors. The data of 2,785 public officials who used the flexible work system in the Korea Institute of Public Administration (2022) data set were analyzed using SPSS 28.0. and PROCESS macro's Model 4. The main research findings are as follows. First, organizational cultures that respect individuality and cooperation, supports management, and aims for work autonomy all positively and significantly affect satisfaction with the flexible working system. When ranking the size of influence by the type of organizational culture, work autonomy, respect for individuality, and a cooperative organizational culture had a positive impact in that order, with work autonomy being the most influential factor. In addition, the public officials' age, job preparation period, self-evaluation of workload, and overtime working hours are significant antecedents of satisfaction with the flexible work system. Second, when examining consequential factors, a high level of satisfaction with the flexible working system affects job satisfaction (+), work performance (+), organizational commitment (+), turnover intention (-), and quality of life (+). Job satisfaction was an especially valid mediator between satisfaction with the flexible working system and other consequential factors, including work performance, organizational commitment, turnover intention, and quality of life.

• Journal of the Korean Institute of Gas
• /
• v.27 no.4
• /
• pp.116-122
• /
• 2023

In addition to analyzing the hydrogen economy trends of the international community (Korea, the United States, Europe, Japan, etc.), which is being promoted to realize a carbon-neutral society, this study compared and analyzed the differences between the gaseous hydrogen refueling station, which is a key hydrogen-using facility close to the people, and a liquefied hydrogen refueling station that is scheduled to be built in the future. In addition, SAFETI, a quantitative risk assessment program, was used to analyze the safety of liquefied hydrogen refueling stations and In consideration of the individual and societal risks and the ranking of risks by facility, which are conditional allowable areas, a plan to improve safety such as facility layout was proposed

• Asia pacific journal of information systems
• /
• v.29 no.2
• /
• pp.308-327
• /
• 2019

The concept of sharing economy has received rich attention in recent years. As a typical type of business model in the sharing economy, online short rent has been paid attention by both industry and academia. In this study, we find trust to be a critical determinant to the success of online short rent platforms. Based on three dimensions of trust theory, i.e., ability, benevolence and integrity, we investigate the factors influencing tenant' willingness to participate in online short rent. We further examine the extent to which trust can influence the number of sales and comments of rooms listed at online short-term rent platforms, which can represent tenant' willingness to participate in the sharing economy. The results show that the trust dimensions represented by a landlord's personal characteristics have significant positive correlations with the number of sales and comments. For example, the real name authentication and the sesame score can represent the trust integrity; online replay ratio and the average confirmation time representing the trust sincerity, and the order acceptance ratio representing the trust ability. On this basis, we proposed some recommendations for both platforms and landlords. For example, the landlords can improve the tenants' trust by authenticating his/her real name, replying actively and timely. For platforms, when they make housing list ranking rules, they can take the landlord's personal attributes that may affect trust into consideration. Moreover, platforms can also allow landlords to supply value-added services to improve service quality and ultimately promote the virtuous circle of the platform ecosphere. Through conducting the empirical research on a particular application of the sharing economy, we aim to fill the research gap of this field in China and provide theoretical and practical contributions to the future development of online short rent.

• Korean Journal of Community Nutrition
• /
• v.29 no.2
• /
• pp.114-128
• /
• 2024

Objectives: The purpose of this study was to investigate the perception of nutrition teachers and the factors influencing their intention toward sustainable dietary education utilizing the theory of planned behavior (TPB). Methods: The self-administered online survey was completed by nutrition teachers in Jeollanam-do, South Korea. A total of 151 valid questionnaires were analyzed. Factor analysis and multiple regressions were employed to test the research model. Results: The study findings demonstrated that all TPB variables significantly influenced the sustainable dietary educational intention, with the degree of influence ranking as follows: external perceived behavioral control (β = 0.417), attitude (β = 0.240), internal perceived behavioral control (β = 0.207), and subjective norms (β = 0.181). For external perceived behavioral control, nutrition teachers and elementary schools exhibited higher levels compared to dietitians and middle/high schools, respectively. The participants in sustainable dietary education training programs exhibited a higher level of internal perceived behavioral control compared to those who did not participate. The highest perception levels were reported for attitude (4.26), followed by subjective norms (4.02), internal perceived behavioral control (3.67), and external perceived behavioral control (3.20). Conclusions: This study affirmed that the TPB variables elucidated the sustainable dietary educational intentions of nutrition teachers. The significant impacts of external and internal perceived behavioral control, attitude, and subjective norms on educational intentions were confirmed. Consequently, proactive support from schools and governments is essential to enhance the facilitating factors and mitigate the barriers toward sustainable dietary education in schools.

• Journal of Korea Port Economic Association
• /
• v.31 no.1
• /
• pp.85-110
• /
• 2015

The purpose of this paper is to show the clustering trend and the empirical comparison and to choose the clustering ports for 3 Korean ports(Busan, Incheon and Gwangyang Ports) by using the Fuzzy(Average Index Transformation) DEA and Cross-efficiency models for 38 Asian ports during 11 years(2001-2011) with 4 input variables(birth length, depth, total area, and number of crane) and 1 output variable(container TEU). The main empirical results of this paper are as follows. First, clustering results by using Fuzzy(AIT)DEA show that 3 Korean ports[Busan(56.29%), Incheon(57.96%), and Gwangyang(66.80%) each]can increase the efficiency. Second, according to Cross-efficiency model, Busan(Hongkong, Kobe, Manila, Singapore, and Kaosiung etc.), Incheon(Aquaba, Dammam, Karachi, Mohammad Byin Oasim and Davao), and Gwangyang(Damman, Yokohama, Nogoya, Keelong, Kaosiung, and Bangkok) should be clustered with those ports in parentheses. Third, when both Fuzzy(AIT)DEA and Cross-efficiency models are mixed, the empirical result shows that 3 Korean ports[Busan(71.38%), Incheon(103.89%), and Gwangyang(168.55%) each]can increase the efficiency. The efficiency ranking comparison among the three models by using Wilcoxon Signed-rank Test was matched with the average level of 66%-67%. The policy implication of this paper is that Korean port policy planner should introduce the Fuzzy(AIT)DEA, and Cross-efficiency models with the mixed two models when clustering is needed among the Asian ports for enhancing the efficiency of inputs and outputs. Also, the results of SWOT analysis among the clustering ports should be considered.

• Journal of Food Hygiene and Safety
• /
• v.27 no.3
• /
• pp.312-316
• /
• 2012

This study was to present the proper probability distribution models that based on the data for surveys of food cold storage temperatures as the input variables to the further MRA (Microbial risk assessment). The temperature was measured by directly visiting 7 food plants. The overall mean temperature for food cold storages in the survey was $2.55{\pm}3.55^{\circ}C$, with 2.5% of above $10^{\circ}C$, $-3.2^{\circ}C$ and $14.9^{\circ}C$ as a minimum and maximum. Temperature distributions by space-locations was $0.80{\pm}1.69^{\circ}C$, $0.59{\pm}1.68^{\circ}C$, and $0.65{\pm}1.46^{\circ}C$ as an upper (2.4~4 m), middle (1.5~2.4 m), and lower (0.7~1.5 m), respectively. Probability distributions were also created using @RISK program based on the measured temperature data. Statistical ranking was determined by the goodness of fit (GOF) to determine the proper probability distribution model. This result showed that the LogLogistic (-4.189, 5.9098, 3.2565) distribution models was found to be the most appropriate for relative MRA conduction.