• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.1
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• pp.9-18
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• 2021

Recently, the rapid proliferation, introduction, and application of the fourth industrial revolution technology has emerged as a trend in the construction market. Building Information Model (BIM) technology is a multidimensional information system that forms the basis of the fourth industrial revolution technology. The river sector utilizing this information-based system is also being actively reviewed, for example, the current measures for maintenance. In recent years, active research and current work should be done to reflect the need for river experts to introduce BIM into the river field. In addition, the development of tools and support software for establishing various information systems is essential for the activation of facility maintenance information systems reflecting advanced technology and to establish and operate management plans. A study on the maintenance of river facilities involves using existing drawings to build a three-dimensional (3D) information model, check the damage utilizing it, and inform it, and utilize it as the data for maintenance reinforcement. This study involved determining a method to build a river facility without the existing information system and using the property maintenance information with 3D modeling to provide a more effective and highly utilized management plan to check maintenance operations and manage damages.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.1
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• pp.43-50
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• 2021

A Leg Mating Unit (LMU) is a device utilized during the float-over installation of offshore structures that include hyperelastic pads and mating part. The hyperelastic pads absorb the loads, whereas the mating part works as guidance between topside and supporting structures during the mating sequence of float-over installation. In this study, the design optimization of an LMU for the float-over installation of floating-type offshore structures is conducted to enhance the performance and to satisfy the requirements defined by classification society regulations. The initial dimensions of the LMU are referred to the dimensions of those used in fixed-type float-over installation because only the location and the number of LMUs are known. The two-parameter Mooney-Rivlin model is adopted to describe the hyperelastic pads under given material parameters. Geometric variables, such as the thickness, height, and width of members, as well as configuration variables, such as the angle and number of members, are defined as design variables and are parameterized. A sampling-based design sensitivity analysis based on latin hypercube sampling method is performed to filter the important design variables. The design optimization problem is formulated to minimize the total mass of the LMU under maximum von Mises stress and reaction force constraints.

• Journal of The Korean Association of Information Education
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• v.24 no.5
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• pp.495-509
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• 2020

This study is a theoretical research to explore ways to effectively learn AI in the age of intelligent information driven by artificial intelligence (hereinafter referred to as AI). The emphasis is on presenting a teaching method to make AI education accessible not only to students majoring in mathematics, statistics, or computer science, but also to other majors such as humanities and social sciences and the general public. Given the need for 'Explainable AI(XAI: eXplainable AI)' and 'the importance of storytelling for a sensible and intelligent machine(AI)' by Patrick Winston at the MIT AI Institute [33], we can find the significance of research on AI storytelling learning model. To this end, we discuss the possibility through a pilot study targeting general students of an university in Daegu. First, we introduce the AI storytelling(AI+ST) learning method[30], and review the educational goals, the system of contents, the learning methodology and the use of new AI tools in the method. Then, the results of the learners are compared and analyzed, focusing on research questions: 1) Can the AI+ST learning method complement algorithm-driven or developer-centered learning methods? 2) Whether the AI+ST learning method is effective for students and thus help them to develop their AI comprehension, interest and application skills.

• Journal of Korean Society of Rural Planning
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• v.27 no.1
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• pp.57-70
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• 2021

The degree of benefits of living services related to the quality of life can solve the depopulation problem, and it is necessary to be able to quantitatively analyze problems related to the quality of life in rural areas in order to cope with the rural depopulation. The purpose of this study was to develop the assessment model of a village-level rural living service that reflects the regional characteristics of rural villages to evaluate the level of rural living services for response rural depopulation. Based on the review of previous related studies, the evaluation index was composed of seven sectors of education, health, welfare, culture, environment, safety, and convenience, and the assessment model of a rural living service was established. This model was evaluated through a sample survey of 90 villages in Nonsan-si, Seongju-gun, and Pyeongchang-gun. As a result of the rural life services evaluation by Si and Gun, Seongju-gun, which is affected by nearby large cities, has the largest variation by village level and is assessed at a lower level overall than other Si and Gun. As a result of the rural life services evaluation by 7 sectors, in the case of health and welfare, low scores were shown in the assessment model, but the level of residents' satisfaction was mid-level. In particular, in the case of Seongju-gun, there were significant differences in the assessment model and the survey results of the level of residents' satisfaction in the health and welfare sectors due to the influence of nearby large cities. As a result of analyzing the number of villages corresponding to the top 30% and the bottom 30% of the evaluation results for each sector, it was analyzed that the villages with the highest evaluation results in Pyeongchang-gun in both the assessment model and the level of residents' satisfaction. It implies that quantitative analysis of data based index and accessibility as well as level satisfaction of residents are necessary.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.5
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• pp.95-102
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• 2020

For the purpose of developing a PE fiber-reinforced highly ductile cementitious composite having high tensile strain capacity more than 2% under the condition of containing aggregates with large particle size, this study investigated the tensile behavior of composites according to the particle size and distribution of aggregates in the composite. Compared with the mixture containing silica sand of which particle size is less than 0.6 mm, mixtures containing river sand and/or gravel with the maximum particle size of 2.36 mm, 4.75 mm, 5.6 mm, 6.7 mm were considered in the experimental design. The particle size distributions of aggregates were adjusted for the optimized distribution curves obtained from modified A&A model by blending different sizes of aggregates. All the mixtures presented clear strain-hardening behavior in the direct tensile tests. The mixtures with the blended aggregates to meet the optimum curves of aggregate size distributions showed higher tensile strain capacity than the mixture with silica sand. It was also found that the tensile strain capacity was improved as the maximum size of aggregate increased which resulted in wider particle size distribution. The mixtures with the maximum size of 5.6 mm and 6.7 mm presented very high tensile strain capacities of 4.83% and 5.89%, respectively. This study demonstrated that it was possible to use coarse aggregates in manufacturing highly ductile fiber-reinforced cementitous composite by adjusting the particle size distribution.

• Journal of the Korea Society for Simulation
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• v.29 no.4
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• pp.9-19
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• 2020

The number of customers on Social Network Services(SNS) is rapidly increasing with the spread of smartphones. As of 2018, about 2.7 billion people of the world population (about 7.1 billion people) and more than 31.2 million people of the total population of South Korea (about 50.1 million) use SNS. There are several studies have been conducted on increasing SNS market. Most of them, however, were not quantitative but qualitative studies. This study is conducted on domestic SNS market to identify the competitive relationship among SNS platforms with great proportion in South Korea, such as Facebook, Instagram and Twitter. The objective is to suggest some hypotheses of the competitive relations, test them, and finally verify the trend of domestic SNS market. Competitive Lotka-Volterra (LV) model is used to find out the competitive relationships and Moving Window is also used to show the changes of them over time. In order to test the hypotheses on the relationships, some experiments are performed with Moving Window technique. Thus, the relations among the platforms and the changes of them over time are identified.

• Clean Technology
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• v.27 no.1
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• pp.47-54
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• 2021

The adsorption of Acid Fuchsin (AF) on granular activated carbon (GAC) was investigated for isothermal adsorption and kinetics and thermodynamic parameters by experimenting with the initial concentration, contact time, temperature, and pH of the dye as adsorption parameters. In the pH effect experiment, the adsorption of AF on activated carbon showed a bathtub type with increased adsorption at pH 3 and 11. The adsorption equilibrium data of AF fit well with the Freundlich isotherm model, and the calculated separation factor (1/n) value was found in which activated carbon can effectively remove AF. The pseudo-second-order kinetic model fits well within 7.88% of the error percent in the adsorption process. According to Weber and Morris's model plot, it was divided into two straight lines. The intraparticle diffusion rate was slow because the stage 2 (intraparticle diffusion) slope was smaller than that of stage 1 (boundary layer diffusion). Therefore, it was confirmed that the intraparticle diffusion was a rate-controlling step. The activation energy of AF (13.00 kJ mol-1) corresponded to the physical adsorption process (5 - 40 kJ mol-1). The free energy change of the AF adsorption by activated carbon showed negative values at 298-318 K. As the spontaneity increased with increasing temperature. The adsorption of AF was an endothermic reaction (ΔH = 22.65 kJ mol-1).

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.1
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• pp.53-59
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• 2021

The marine transport industry generally applies new technologies later than other transport industries, such as airways and railways. Vessels require efficient operation, and their performance and lifespan depend on the level of maintenance and management. Many studies have shown that corrective maintenance (CM) and time-based maintenance (TBM) have restrictions with respect to enabling efficient maintenance of workload and cost to improve operational efficiency. Predictive maintenance (PdM) is an advanced technology that allows monitoring the condition and performance of a target machine to predict its time of failure and helps maintain the key machinery in optimal working conditions at all times. This study presents the development of a marine predictive maintenance (MPdM; maritime predictive maintenance) method based on applying PdM to the marine environment. The MPdM scheme is designed by considering the special environment of the marine transport industry and the extreme marine conditions. Further, results of the study elaborates upon the concept of MPdM and its necessity to advancing marine transportation in the future.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.3
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• pp.71-80
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• 2021

The selection of an appropriate neural network algorithm is an important step for accurate data prediction in machine learning. Many algorithms based on basic artificial neural networks have been devised to efficiently predict future data. These networks include deep neural networks (DNNs), recurrent neural networks (RNNs), long short-term memory (LSTM) networks, and gated recurrent unit (GRU) neural networks. Developers face difficulties when choosing among these networks because sufficient information on their performance is unavailable. To alleviate this difficulty, we evaluated the performance of each algorithm by comparing their errors and processing times. Each neural network model was trained using a tax dataset, and the trained model was used for data prediction to compare accuracies among the various algorithms. Furthermore, the effects of activation functions and various optimizers on the performance of the models were analyzed The experimental results show that the GRU and LSTM algorithms yields the lowest prediction error with an average RMSE of 0.12 and an average R2 score of 0.78 and 0.75 respectively, and the basic DNN model achieves the lowest processing time but highest average RMSE of 0.163. Furthermore, the Adam optimizer yields the best performance (with DNN, GRU, and LSTM) in terms of error and the worst performance in terms of processing time. The findings of this study are thus expected to be useful for scientists and developers.

• Journal of the Korean Institute of Gas
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• v.24 no.6
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• pp.18-27
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• 2020

This study presents flow assurance analysis in subsea pipeline considering system availability of topside in LNG-FPSO. A hydrate management strategy was established, which consisted of PVCap experiments, system availability analysis of LNG-FPSO topside, hydrate risk analysis in the pipeline, and calculation of PVCap injection concentration. The experimental data required for the determination of PVCap injection concentration were obtained by measuring the hydrate induction time of PVCap at the subcooling temperatures of 6.1, 9.2, and 12.1℃. The availability of LNG-FPSO topside system for 20 years was 89.3%, and the longest downtime of 50 hours occurred 2.9 times per year. The subsea pipeline model for multiphase flow simulation was created using field geometry data. As a result of risk analysis of hydrate plugging using subsea pipeline model, hydrate was formed at the end of flowline in 23.2 hours under the condition of 50 hours shutdown. The injection concentration of PVCap was determined based on the PVCap experiment results. The hydrate plugging in subsea pipeline of LNG-FPSO can be completely prevented by injecting PVCap 0.25 wt% 2.9 times per year.