• The Mathematical Education
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• v.62 no.4
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• pp.491-513
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• 2023

High achievement in mathematics is a very complex process in which various factors such as cognitive factors, affective factors, and social and environmental factors work respectively and complementary. A number of previous studies conducted so far have shown that there are certain factors affecting math learning and these factors have positive or negative effects on it. However, these studies were conducted with limited variables and it was not possible to present a comprehensive analysis of what would be necessary to get good achievements in mathematics learning. Therefore, in this study, we analyzed the process of experience of students who experienced success in mathematics learning using the analysis method of the grounded theory. In addition, the collected data was analyzed to explain the process of leading to the successful experience in mathematics learning. As a result of the analysis, it was revealed that students form their identity as successful learners through the processes of 'new phase stage', 'experience accumulation stage', 'stand-up stage', and 'maintenance effort stage'. Through this study, we were able to get implications for what actions are needed to experience success in math learning by looking at the process of the experience what interviewees have gone through.

• Information Systems Review
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• v.23 no.1
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• pp.1-22
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• 2021

This study aims to analyze online game user's game items transacting behaviors for the two game genres such as MMORPG and sports game. For the sake of conducting the analysis, we adopted a fuzzy logic agent-based modeling. In the online game fields, game items transactions are crucial to game company's profitability. However, there are lack of previous studies investigating the online game user's game items transacting activities. Since many factors need to be addressed in a complicated way, ABM (agent-based modeling) simulation mechanism is adopted. Besides, a fuzzy logic is also considered due to the fact that a number of uncertainties and ambiguities exist with respect to online game user's complex behaviors in transacting game items. Simulation results from applying the fuzzy logic ABM method revealed that MMORPG game users are motivated to pay expensive price for high-performance game items, while sports game users tend to transact game items within a reasonable price range. We could conclude that the proposed fuzzy logic ABM simulation mechanism proved to be very useful in organizing an effective strategy for online game items management and customers retention.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.2
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• pp.207-216
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• 2024

As big data was built due to the 4th Industrial Revolution, personalized services increased rapidly. As a result, the amount of personal information collected from online services has increased, and concerns about users' personal information leakage and privacy infringement have increased. Online service providers provide privacy policies to address concerns about privacy infringement of users, but privacy policies are often misused due to the long and complex problem that it is difficult for users to directly identify risk items. Therefore, there is a need for a method that can automatically check whether the privacy policy is safe. However, the safety verification technique of the conventional blacklist and machine learning-based privacy policy has a problem that is difficult to expand or has low accessibility. In this paper, to solve the problem, we propose a safety verification technique for the privacy policy using the GPT-3.5 API, which is a generative artificial intelligence. Classification work can be performed evenin a new environment, and it shows the possibility that the general public without expertise can easily inspect the privacy policy. In the experiment, how accurately the blacklist-based privacy policy and the GPT-based privacy policy classify safe and unsafe sentences and the time spent on classification was measured. According to the experimental results, the proposed technique showed 10.34% higher accuracy on average than the conventional blacklist-based sentence safety verification technique.

• Journal of the Korean Geosynthetics Society
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• v.23 no.2
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• pp.53-62
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• 2024

Recently, development of non-traditional energy such as oil sands has been actively conducted in the cold region such as Canada. Frozen soil has different thermal and mechanical characteristics from general soil due to its high organic contents. This study evaluated the impact of organic matter content on the thermal and mechanical behavior of frozen soil samples collected from Alberta, Canada, and Gangwon Province, South Korea. As the organic content increases, the maximum dry unit weight decreases and the optimum moisture content increases in compaction tests. In uniaxial compression tests under frozen conditions, the strength of the frozen specimens increased as the temperature decreased. The strength of Canada soil sample increased with higher organic matter content at low temperatures. However, the strength of frozen soil was not significantly affected by organic matter content due to the complex behavior and unfrozen water content. Thermal conductivity tests showed higher thermal conductivity in frozen conditions compared to unfrozen conditions, due to the higher thermal conductivity of ice compared to water. These findings provide essential data for geotechnical design and construction in large-scale projects such as oil sands development in cold regions. Further research is needed to explore the impact of organic matter content on different types of frozen soils.

• The Transactions of the Korea Information Processing Society
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• v.13 no.4
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• pp.199-207
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• 2024

Local reservoirs are crucial sources for agricultural water supply, necessitating stable water level management to prepare for extreme climate conditions such as droughts. Water level prediction is significantly influenced by local climate characteristics, such as localized rainfall, as well as seasonal factors including cropping times, making it essential to understand the correlation between input and output data as much as selecting an appropriate prediction model. In this study, extensive multivariate data from over 400 reservoirs in Jeollabuk-do from 1991 to 2022 was utilized to train and validate a water level prediction model that comprehensively reflects the complex hydrological and climatological environmental factors of each reservoir, and to analyze the impact of each input feature on the prediction performance of water levels. Instead of focusing on improvements in water level performance through neural network structures, the study adopts a basic Feedforward Neural Network composed of fully connected layers, batch normalization, dropout, and activation functions, focusing on the correlation between multivariate input data and prediction performance. Additionally, most existing studies only present short-term prediction performance on a daily basis, which is not suitable for practical environments that require medium to long-term predictions, such as 10 days or a month. Therefore, this study measured the water level prediction performance up to one month ahead through a recursive method that uses daily prediction values as the next input. The experiment identified performance changes according to the prediction period and analyzed the impact of each input feature on the overall performance based on an Ablation study.

• Membrane Journal
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• v.34 no.2
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• pp.87-95
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• 2024

Recent studies explore a wide array of desalination and water treatment methods, encompassing membrane processes such as reverse osmosis (RO), nanofiltration (NF), and electrodialysis (ED) to advanced capacitive deionization (CDI) and its membrane variant (MCDI). Comparative analyses reveal ED's cost-effectiveness in low-salinity scenarios, while hybrid systems (NF-MCDI, RO-NF-MCDI) show improved salt removal and energy efficiency. Novel ion separation methods (NF-CDI, NF-FCDI) offer enhanced efficacy and energy savings. These studies also highlight the efficiency of these methods in treating complex wastewater specific to various industries. Environmental impact assessments emphasize the need for sustainability in system selection. Additionally, the integration of microfabricated sensors into membranes allows real-time monitoring, advancing technology development. These studies underscore the variety and promise of emerging desalination and water treatment technologies. They provide valuable insights for enhancing efficiency, minimizing energy usage, tackling industry-specific issues, and innovating to surpass conventional method limitations. The future of sustainable water treatment appears bright, with continual advancements focused on improving efficiency, minimizing environmental impact, and ensuring adaptability across diverse applications.

• Information Systems Review
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• v.22 no.4
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• pp.185-203
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• 2020

With the advent of 4th industrial revolution, the manufacturing industry is converging with ICT and changing into the era of smart manufacturing. In the smart factory, all machines and facilities are connected based on ICT, and thus security should be further strengthened as it is exposed to complex security threats that were not previously recognized. To reduce the risk of security incidents and successfully implement smart factories, it is necessary to identify key security factors to be applied, taking into account the characteristics of the industrial environment of smart factories utilizing ICT. In this study, we propose a 'hierarchical classification model of security factors in smart factory' that includes terminal, network, platform/service categories and analyze the importance of security factors to be applied when developing smart factories. We conducted an assessment of importance of security factors to the groups of smart factories and security experts. In this study, the relative importance of security factors of smart factory was derived by using AHP technique, and the priority among the security factors is presented. Based on the results of this research, it contributes to building the smart factory more securely and establishing information security required in the era of smart manufacturing.

• Journal of the Korea Society for Simulation
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• v.33 no.2
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• pp.1-11
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• 2024

A cyber-physical system is a technology that connects the physical systems of a manufacturing environment with a cyber space to enable simulation. One of the major challenges in this technology is the seamless communication between these two environments. In complex manufacturing processes, it is crucial to adapt to various protocols of manufacturing equipment and ensure the transmission and reception of a large volume of data without delays or errors. In this study, we propose a method for constructing agent models for real-time simulation-capable cyberphysical systems. To achieve this, we design data collection units as independent agent models and effectively integrate them with existing simulation tools to develop the overall system architecture. To validate the proposed structure and ensure reliability, we conducted empirical testing by integrating various equipment from a real-world smart microfactory system to assess the data collection capabilities. The experiments involved testing data delay and data gaps related to data collection cycles. As a result, the proposed approach demonstrates flexibility by enabling the application of various internal data collection methods and accommodating different data formats and communication protocols for various equipment with relatively low communication delays. Consequently, it is expected that this approach will promote innovation in the manufacturing industry, enhance production line efficiency, and contribute to cost savings in maintenance.

• Korean Journal of Clinical Laboratory Science
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• v.55 no.4
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• pp.269-275
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• 2023

Echocardiography is a non-invasive method that is useful for diagnosing pulmonary arterial hypertension. It is known that echocardiography depends on the experience, education, and knowledge level of the cardiac sonographer. This study aimed to compare the agreement values between cardiac sonographer with different practical experiences in the diagnosis of pulmonary arterial hypertension using echocardiography. Three readers re-evaluated the echocardiography images of 148 patients who were diagnosed with pulmonary arterial hypertension at the S Medical Center from January 1, 2020, to December 31, 2020. The echocardiography values measured by each reader were compared and analyzed. The results of the analysis of discrete variables revealed that the agreement values of the cardiac sonographers showed excellent consistency for both reader 3 and the cardiologist group, indicating that more experience leads to better predictive accuracy for diagnosis of the condition. Furthermore, in terms of continuous variables, all the cardiac sonographer demonstrated good agreement in the measured values of the right atrium, which was easier to assess and clearer than the structurally complex measurements of the right ventricle. This study represents the first analysis in Korea of the agreement values measured by medical technologists who are cardiac sonographers.

• Journal of the Korean Regional Science Association
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• v.40 no.2
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• pp.75-89
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• 2024

As the problem of lowering the efficiency of urban services in small and medium-sized cities in the non-metropolitan area intensifies, the necessity of developing a railway station area is being emphasized to form a compressed urban space through regional bases. Although major station areas in large cities are being developed in the form of complex, the analysis of the development location characteristics of the small and medium-sized city station areas is insufficient. The purpose of this study is to analyze the characteristics of development project conditions and potential demand in the high-speed rail station areas across the country, identify the differences in locational characteristics according to the type of city, such as 'metropolitan city', 'large city in non-metropolitan city', 'medium and small city in non-metropolitan city', and find out the appropriate development method. As a result of the analysis, it was analyzed that the 'metropolitan area metropolitan area' has high potential demand and poor business conditions. On the other hand, in the case of the non-metropolitan area, it was analyzed that the 'small and medium-sized city station area' has good business conditions and low potential demand characteristics, and the 'large city station area' has intermediate characteristics. This suggests the need for different development methods in the development of metropolitan and small and medium-sized city station areas. The analysis results of this study show that it is desirable to encourage private participation in large-scale metropolitan station areas, which require large-scale input, to maximize potential demand, and to encourage private participation through public-led projects based on favorable business conditions or development based on regional characteristics.