• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.28 no.2B
• /
• pp.177-185
• /
• 2008

Accurate monitoring of snow cover is a key component for studying climate and global as well as for daily weather forecasting and snowmelt runoff modelling. The few observed data related to snowmelt was the major cause of difficulty in extracting snowmelt factors such as snow cover area, snow depth and depletion curve. Remote sensing technology is very effective to observe a wide area. Although many researchers have used remote sensing for snow observation, there were a few discussions on the characteristics of spatial and temporal variation. Snow cover maps were derived from NOAA AVHRR images for the winter seasons from 1997 to 2006. Distributed snow depth was mapped by overlapping between snow cover maps and interpolated snowfall maps from 69 meteorological observation stations. Model parameters (Snow Cover Area: SCA, snow depth, Snow cover Depletion Curve: SDC) were built for 7 major watersheds in South Korea. The decrease pattern of SCA for time (day) was expressed as exponentially decay function, and the determination coefficient was ranged from 0.46 to 0.88. The SCA decreased 70% to 100% from the maximum SCA when 10 days passed.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.26 no.2C
• /
• pp.99-108
• /
• 2006

In this study a series of bench scale test are conducted to increase the undrained shear strength of clayey soils using by Electro-kinetic injection stabilization method. The sodium silicate was injected in anode reservoir and its concentration was changed with 500, 1000, 1500, 2000, 2500mM for configuration of applicability of Electro-kinetic injection stabilization method. Also, the treatment time and electric gradient was changed to acquire the optical influence factors. For increasing the shear strength to maximum values, the calcium chloride and aluminium hydroxide, which concentration was changed with 50, 250, 500, 750, 1000mM, were added at anode reservoir for 5 days after the treatment of sodium silicate in 5 days as the 2nd additives. The test of results in determination of sodium silicate concentration show that the undrained shear strength at each point had a tendency to converge into a constant value when the concentration of sodium silicate came to 1000mM and above. The maximum shear strength increasement was 800% compared with initial value. After a series of test, the electric gradient and treatment time for application of electric fielld were 1V/cm and 6 days. In case of 2nd additives test, the concentration for maximum shear strength is 250mM in all additives and the effects of shear strength improvement was developed approximately 20~30% in comparison to addition of single injection material.

• The Korean Journal of Woman Psychology
• /
• v.16 no.3
• /
• pp.303-329
• /
• 2011

In Korea, recent women's educational standard is more higher than any other period but rate of using human resources is the lowest level among the OECD nations. As the reason of this phenomenon, the career choice attract attention. Traditionally, job is classified female-dominated job from male-dominated job, and most women still avoid male-dominated job. If this unequal concentrated phenomenon is relieved, diversity using of human resource will be available. For the purpose, this study try to determine the experience structure and the career decision-making process of the female undergraduate who want the male-dominated job through the qualitative study method, and to determine factors that work negative or positive on the process to use for the career consult. Grounded theory based data analyses resulted in 61 concepts, 27 sub-categories, and 12 categories from the recorded data of 8 female undergraduates who want the male-dominated job. The core category was "For the special life, keeping challenging with the will". A paradigm model consist of the casual condition, central phenomenon, contextual condition, intervening condition, actions/reactions and the result was proposed. And the participants went through five stages with time in their career decision-making process: the stage of awareness about the trait and aspiration, the stage of internal determination, the stage of support and accept, the stage of challenge and overcome, and the stage of affirmation and confidence. Implications of the findings and suggestions for the future research are discussed.

• Korean Journal of Culture and Social Issue
• /
• v.17 no.2
• /
• pp.241-260
• /
• 2011

This study was to develop the fun perception scale measuring what conditions employees experience fun feeling in work and to examine the construct validity of it. For this, the pre-studies(open-ended questionnaire, in-depth interviews, literature survey, pre-survey) were conducted to develop the preliminary questions of fun scale. In main study, 250 employees(male: 125, female, 125) were responded to a questionnaire consisted of 40 questions of fun perception scale extracted by pre-studies. The results were as follow. First, through the item analysis, factor analysis and reliability analysis, 7 factors composed of 29 items were extracted: 'self-determination', 'extrinsic reward', 'goal achievement', 'pleasure in the process', 'contribution to the company', 'worthless', 'challenge'. Cronbach's alpha reliability coefficient of each factor was suitable. Secondly, EFA was conducted to test the construct validity of fun scale with AMOS 16.0. Several goodness of fit indexes were used to assess model fit: X2/df, TLI, CFI, RMSEA. The results were revealed that all the indexes were acceptable with no additional modification. Based on these findings, the theoretical and the practical implications of fun perception scale were discussed.

• Journal of Intelligence and Information Systems
• /
• v.29 no.4
• /
• pp.309-323
• /
• 2023

As the role of online reviews has become increasingly crucial, numerous studies have been conducted to utilize helpful reviews. Helpful reviews, perceived by customers, have been verified in various research studies to be influenced by factors such as ratings, review length, review content, and so on. The determination of a review's helpfulness is generally based on the number of 'helpful' votes from consumers, with more 'helpful' votes considered to have a more significant impact on consumers' purchasing decisions. However, recently written reviews that have not been exposed to many customers may have relatively few 'helpful' votes and may lack 'helpful' votes altogether due to a lack of participation. Therefore, rather than relying on the number of 'helpful' votes to assess the helpfulness of reviews, we aim to classify them based on review content. In addition, the text of the review emerges as the most influential factor in review helpfulness. This study employs text mining techniques, including topic modeling and sentiment analysis, to analyze the diverse impacts of content and emotions embedded in the review text. In this study, we propose a review helpfulness prediction model based on review content, utilizing movie reviews from IMDb, a global movie information site. We construct a review helpfulness prediction model by using an explainable Graph Neural Network (GNN), while addressing the interpretability limitations of the machine learning model. The explainable graph neural network is expected to provide more reliable information about helpful or non-helpful reviews as it can identify connections between reviews.

• Journal of the Korean Geotechnical Society
• /
• v.39 no.12
• /
• pp.37-46
• /
• 2023

Dynamic soil properties are essential factors for predicting the detailed behavior of the ground. However, there are limitations to gathering soil samples and performing additional experiments. In this study, we used an artificial neural network (ANN) to predict dynamic soil properties based on static soil properties. The selected static soil properties were soil cohesion, internal friction angle, porosity, specific gravity, and uniaxial compressive strength, whereas the compressional and shear wave velocities were determined for the dynamic soil properties. The Levenberg-Marquardt and Bayesian regularization methods were used to enhance the reliability of the ANN results, and the reliability associated with each optimization method was compared. The accuracy of the ANN model was represented by the coefficient of determination, which was greater than 0.9 in the training and testing phases, indicating that the proposed ANN model exhibits high reliability. Further, the reliability of the output values was verified with new input data, and the results showed high accuracy.

• Journal of Internet Computing and Services
• /
• v.25 no.1
• /
• pp.91-98
• /
• 2024

With the advancement of ICT (Information and Communication Technology), searching for judgments through the internet has become increasingly convenient. However, predicting sentencing based on judgments remains a challenging task for individuals. This is because sentencing involves a complex process of applying aggravating and mitigating factors within the framework of legal provisions, and it often depends on the subjective judgment of the judge. Therefore, this research aimed to develop a model for predicting sentencing using artificial intelligence by focusing on structuring the data from judgments, making it suitable for AI applications. Through theoretical and statistical analysis of previous studies, we identified variables with high explanatory power for predicting sentencing. Additionally, by analyzing 50 legal judgments related to serious crimes that are publicly available, we presented a framework for extracting essential information from judgments. This framework encompasses basic case information, sentencing details, reasons for sentencing, the reasons for the determination of the sentence, as well as information about offenders, victims, and accomplices evident within the specific content of the judgments. This research is expected to contribute to the development of artificial intelligence technologies in the field of law in the future.

• Steel and Composite Structures
• /
• v.50 no.6
• /
• pp.705-720
• /
• 2024

Analyzing the collapse behavior of thin-walled steel structures holds significant importance in ensuring their safety and longevity. Geometric imperfections present on the surface of metal materials can diminish both the durability and mechanical integrity of steel shells. These imperfections, encompassing local geometric irregularities and deformations such as holes, cavities, notches, and cracks localized in specific regions of the shell surface, play a pivotal role in the assessment. They can induce stress concentration within the structure, thereby influencing its susceptibility to buckling. The intricate relationship between the buckling behavior of these structures and such imperfections is multifaceted, contingent upon a variety of factors. The buckling analysis of thin-walled steel shell structures, similar to other steel structures, commonly involves the determination of crucial material properties, including elastic modulus, shear modulus, tensile strength, and fracture toughness. An established method involves the emulation of distributed geometric imperfections, utilizing real test specimen data as a basis. This approach allows for the accurate representation and assessment of the diversity and distribution of imperfections encountered in real-world scenarios. Utilizing defect data obtained from actual test samples enhances the model's realism and applicability. The sizes and configurations of these defects are employed as inputs in the modeling process, aiding in the prediction of structural behavior. It's worth noting that there is a dearth of experimental studies addressing the influence of geometric defects on the buckling behavior of cylindrical steel shells. In this particular study, samples featuring geometric imperfections were subjected to experimental buckling tests. These same samples were also modeled using Finite Element Analysis (FEM), with results corroborating the experimental findings. Furthermore, the initial geometrical imperfections were measured using digital image correlation (DIC) techniques. In this way, the response of the test specimens can be estimated accurately by applying the initial imperfections to FE models. After validation of the test results with FEA, a numerical parametric study was conducted to develop more generalized design recommendations for the stainless-steel shell structures with the initial geometric imperfection. While the load-carrying capacity of samples with perfect surfaces was up to 140 kN, the load-carrying capacity of samples with 4 mm defects was around 130 kN. Likewise, while the load carrying capacity of samples with 10 mm defects was around 125 kN, the load carrying capacity of samples with 14 mm defects was measured around 120 kN.

• Nuclear Engineering and Technology
• /
• v.56 no.7
• /
• pp.2875-2880
• /
• 2024

The development of nuclear power plants is in three phases. The first phase is a consideration before the decision on the NPP construction program is approved, the second phase is the preparatory work for making contracts and preparing for the construction of NPP after the NPP construction policy is approved, and the third phase is contracting, licensing and building the first NPP. As a volcanically active country, Indonesia contains over 130 active volcanoes that are part of the Pacific Ring of Fire. The volcanic aspect is one of the safety factors considered while deciding the location of an NPP. Research on the potential of natural external risks to the determination of nuclear power plants in Indonesia, including the volcanic aspect, has been conducted based on the safety reference or safety guide of the IAEA and the Nuclear Energy Regulatory Body (BAPETEN) Regulation. Due to technological advancements, safety needs have evolved so the existing Indonesia National Standard (SNI) must be updated to comply with BAPETEN regulations. The substance in SNI 18-2034-1990 relating to volcanic features seems less relevant in actual conditions, given that more complete and exact criteria for determining a site guarantee the safety and health of residents and surrounding the environment site. The study intends to conduct a gap analysis of volcanic issues in SNI and volcanic regulations. The method used is identification requirements for volcanic aspects in SNI 18-2034-1990 about Determining Site of Nuclear Reactor Guidance with BAPETEN Chairman Regulation (BCR) number 4 of 2018 about Nuclear Installation Site Evaluation Safety Provisions and BCR number 5 of 2015 about Evaluation of Nuclear Installation Sites for Volcanic Aspects, and analysis uses a qualitative method of inductive techniques. The outcome of this research applies to suggesting a revision of SNI number 18-2034-1990, especially the volcanic aspect.

• Industry Promotion Research
• /
• v.9 no.3
• /
• pp.163-174
• /
• 2024

MyData is a new entity that strengthens the rights of information subjects through the 'right to data portability' and utilizes data to enable hyper-personalized services using personal information. Korea's MyData system is recognized globally as an outstanding system in that it is creating a new MyData industry by granting the right to information self-determination through the 'right to request data transmission'. Now in its third year, this study evaluates Korea's MyData system from a consumer behavior perspective and identifies issues for improvement. To this end, this study reviewed previous research on the relationship between regulatory policy and consumer behavior to determine the applicability of a consumer behavior perspective in institutional evaluation. In addition, in a study on consumer behavior related to MyData, variables that affect the use of MyData were investigated and evaluation items from a consumer behavior perspective were derived. As a result of evaluating Korea's MyData system from a consumer behavior perspective, it was found that the factors considered important by consumers were appropriately reflected in the system. However, in cases where there are dual values of ease of use and personal information protection, regulatory aspects tend to take priority. Therefore, in order to revitalize the MyData industry, it is essential to implement market-friendly system improvements without compromising consumer rights. This study is differentiated from existing studies in that it attempted to derive a plan for system improvement by combining empirical consumer behavior research and regulatory policy research.