• Journal of the Korean Geotechnical Society
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• v.38 no.7
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• pp.25-37
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• 2022

In this paper, a small-scale model testing system was developed using a series of small-scale model tests to analyze the mechanism of compaction pile formation and evaluate the quality of controlled grading aggregates proposed as an alternative material to the sand compaction pile (SCP) method and granular compaction pile (GCP). These are the most typical ground improvement methods in field practice, particularly for soft grounds. However, the SCP has faced difficulties due to the supply shortage of natural sand and the corresponding price surge of sand. The GCP is limited in marine soft grounds because of the failure occurring at the pile tip caused by excessive expansion of the deeper bulbs, leading to uneven bulb formation. The uniformity of compacted pile bulbs is critical to ensuring the bearing capacity and quality of the compaction pile. This study aims to evaluate the performance of the new material and controlled grading aggregates using small-scale model tests simulating field compaction process to investigate its potential application in comparison with SCP. The compaction piles are examined in four cases according to different materials used for compaction pile and clay strength. The compaction pile materials, which are made of sand and controlled grading aggregates, used in this study were compared to reveal the mechanism of the bulb creation. The experimental data confirm that the bulb formation quality of the traditional sand and the new material, controlled grading aggregates are comparable. The compaction pile made of controlled grading aggregates presents higher bearing capacity than that of marine sand.

• Computers and Concrete
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• v.32 no.3
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• pp.247-261
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• 2023

Due to the non-uniform distribution of meso-structure, the diffusion of chloride ions in concrete show the characteristics of characteristics of randomness and fuzziness, which leads to the non-uniform distribution of chloride ions and the non-uniform corrosion of steel rebar in concrete. This phenomenon is supposed as the main reason causing the uncertainty of the bearing capacity deterioration of reinforced concrete structures. In order to analyze and predict the durability of reinforced concrete structures under chloride environment, the random features of chloride ions transport in concrete were studied in this research from in situ meso-structure of concrete. Based on X-ray CT technology, the spatial distribution of coarse aggregates and pores were recognized and extracted from a cylinder concrete specimen. In considering the influence of ITZ, the in situ mesostructure of concrete specimen was reconstructed to conduct a numerical simulation on the diffusion of chloride ions in concrete, which was verified through electronic microprobe technology. Then a stochastic study was performed to investigate the distribution of chloride ions concentration in space and time. The research indicates that the influence of coarse aggregate on chloride ions diffusion is the synthetic action of tortuosity and ITZ effect. The spatial distribution of coarse aggregates and pores is the main reason leading to the non-uniform distribution of chloride ions both in spatial and time scale. The chloride ions concentration under a certain time and the time under a certain concentration both satisfy the Lognormal distribution, which are accepted by Kolmogorov-Smirnov test and Chi-square test. This research provides an efficient method for obtain mass stochastic data from limited but representative samples, which lays a solid foundation for the investigation on the service properties of reinforced concrete structures.

• Journal of Korea Trade
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• v.26 no.4
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• pp.1-22
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• 2022

Purpose - This paper empirically investigates the effect of a rise in the global value chain (GVC) on the industry-level efficiency of resource allocation (based on plant-level inefficiency measures) in Korea, with a focus on various channels through which a rise in the GVC can increase competition among firms and thus induce resources to be allocated more efficiently across firms. Design/methodology - We empirically investigate the relationship between the industry-specific importance of GVC and the industry-level allocative inefficiency that is measured as the dispersion of the plant-level marginal revenue of capital (MRK) as in Hsieh and Klenow's (2009) influential model. We compute MRK dispersion for industries sorted by various characteristics that are closely related to firm/industry sensitivity to the GVC. In other words, we compute the average industry-level MRK dispersion for industries sorted by industry-specific importance of GVC and compute the difference between the two groups of industries (higher vs. lower than the median GVC); we also calculate the difference between industries sorted by industry-specific export (import) intensity. This is our difference-in-difference estimate of the MRK dispersion associated with the GVC for the export (import)-intensive industry versus the non-export (non-import)-intensive industry. This difference-in-difference estimate of the MRK dispersion conditional vs. unconditional on firm-level productivity is then calculated further (triple-difference estimate). Findings - A rise in GVC is associated with a decrease in the MRK dispersion in the export-intensive industry compared to the non-export-intensive industry. The same is true for industries that rely heavily on imports versus those that do not (i.e., import intensive vs. non-intensive). Furthermore, the reduction in the MRK dispersion in the export-intensive industry associated with an increase in the GVC is disproportionately greater for high-productivity firms. In contrast, the negative relationship between GVC and MRK dispersion in the import-intensive industry is disproportionately smaller for high-productivity firms. Originality/value - Existing studies focus on the relationship between GVC and aggregate output, exports, and imports at the country level. We investigate detailed firm/industry-level mechanisms that determine the relationship between GVC, trade, and productivity. Using the plant-level data in South Korea, we investigate how GVC is related to the cross-firm MRK dispersion, an important measure of allocative inefficiency, based on Hsieh and Klenow's (2009) influential economic theory. This is the first study to provide plant-level evidence of how GVC affects MRK dispersion. Furthermore, we examine how the relationship between GVC and MRK-dispersion varies across export intensity, import intensity, and firm-level productivity, providing insight into how GVC can affect firms' exposure to competition in the global market differently depending on market conditions and thus generate trade-related productivity gains.

• Advances in concrete construction
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• v.13 no.3
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• pp.215-221
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• 2022

Considering their similar mass densities, an attempt was made to optimize the mix design of micro-concrete that used barite sand as an aggregate by substituting marble powder (5%, 10%, 20%, 30%, 40%, 50%, 70%), clay brick powder (30%, 50%, 70%), and fly ash (30%, 50%, 70%) for the concrete (by mass) to form specimens for shaking table tests. The test results showed that for these three groups of materials, the substitutions had little effect on the density. The barite sand played a decisive role in the density, and the overall density of the specimens reached approximately 2.9 g/cm³. The compressive strength and elastic modulus decreased with an increase in the substitution rates for the three types of materials. Among them, the 28 day compressive strength values of the 40% and 50% marble powder groups were 11.73 MPa and 8.33 MPa, respectively, which were 58.7% and 70.7% lower than the control group, respectively. Their elastic modulus values were 1.33×10⁴ MPa and 1.42×10⁴ MPa, respectively, which were 39.1% and 35% lower than those of the control group, respectively. The 28 day compressive strength values of the 50% and 70% clay brick powder groups were 13.13 MPa and 5.8 MPa, respectively, which were 53.8% and 79.6% lower than the control group, respectively. Their elastic modulus values were 1.54×10⁴ MPa and 1.19×10⁴ MPa, respectively, which were 29.7% and 45.4% lower than those of the control group, respectively. The 28 day compressive strength values of the 50% and 70% fly ash groups were 13.5 MPa and 7.1 MPa, respectively, which were 52.5% and 75% lower than those of the control group, respectively. Their elastic modulus values were 1.36×10⁴ MPa and 0.95×10⁴ MPa, respectively, which were 37.9% and 56.6% lower than those of the control group, respectively. There was a linear relationship between the 28 day compressive strength and elastic modulus, with the correlation coefficient reaching a value higher than 0.88. The test results showed that the model materials met the high density, low compressive strength, and low elastic modulus requirements for shaking table tests, and the test data of the three groups of different alternative materials were compared and analyzed to provide references and assistance for relevant model testers.

• Steel and Composite Structures
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• v.50 no.5
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• pp.595-608
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• 2024

In this study, aluminum lathe waste was used by replacing aggregates in certain proportions in order to obtain expansive concrete using recycled materials. For this reason, five different aluminum wastes of 1%, 2%, 3%, 4% and 5% were selected and also reference without aluminum waste was produced. Based on the mechanical tests conducted, which included slump, compression, splitting tensile, and flexural tests, it was evident that the workability of the material declined dramatically once the volume ratio of aluminum exceeded 2%. As determined by the compressive strength test (CST), the CS of concrete (1% aluminum lathe wastes replaced with aggregate) was 11% reducer than that of reference concrete. It was noted that the reference concrete's CS values, which did not include aluminum waste, were greater than those of the concrete that contained 5% aluminum. When comparing for splitting tensile strength (STS), it was observed that the results of STS generally follow the parallel inclination as the CS. The reduction in these strengths when 1% aluminum is utilized is less than 10%. These ratios modified 18% when flexural strength (FS) is considered. Therefore, 1% of aluminum waste is recommended to obtain expansive concrete with recycled materials considering minimum loss of strength. Moreover, Scanning Electron Microscope (SEM) analysis was performed and the results also confirm that there was expansion in the aluminum added concrete. The presence of pores throughout the concrete leads to the formation of gaps, resulting in its expansion. Additionally, for practical applications, basic equations were developed to forecast the CS, STS, and FS of the concrete with aluminum lathe waste using the data already available in the literature and the findings of the current study. In conclusion, this study establishes that aluminum lathe wastes are suitable, readily available in significant quantities, locally sourced eco-materials, cost-effective, and might be selected for construction using concrete, striking a balance among financially and ecological considerations.

• Journal of the Korean Geotechnical Society
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• v.40 no.5
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• pp.7-20
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• 2024

Ground improvement techniques through soil densification are widely used to enhance the cyclic resistance and seismic performance of liquefiable soils. However, most studies have primarily focused on the increase in soil strength before and after ground improvement, with limited investigation into changes in spatial statistical characteristics. This study aims to identify the changes in soil strength and spatial variability due to ground improvement by analyzing data from 19 cases where ground improvement was conducted using timber piles, aggregate piers, and dynamic compaction, with a cone penetration test (CPT) performed pre- and post-improvement. The changes in cone tip resistance were evaluated by comparing cone tip resistance profiles before and after ground improvement, while changes in spatial variability were assessed by examining variations in three parameters of the random field: mean (or trend function), variance, and scale of fluctuation. The results indicate that cone tip resistance generally increased, while inherent variability tended to decrease. The scale of fluctuation, representing spatial autocorrelation, generally increased following ground improvement, with higher initial fluctuation parameters correlating with a greater rate of increase. Furthermore, the probabilistic analysis of liquefaction-induced settlement revealed that changes in the scale of fluctuation due to ground improvement significantly influenced the variability of settlement, underscoring the importance of considering this factor.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.1-27
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• 2017

It is known that the economic sentiment index and macroeconomic indicators are closely related because economic agent's judgment and forecast of the business conditions affect economic fluctuations. For this reason, consumer sentiment or confidence provides steady fodder for business and is treated as an important piece of economic information. In Korea, private consumption accounts and consumer sentiment index highly relevant for both, which is a very important economic indicator for evaluating and forecasting the domestic economic situation. However, despite offering relevant insights into private consumption and GDP, the traditional approach to measuring the consumer confidence based on the survey has several limits. One possible weakness is that it takes considerable time to research, collect, and aggregate the data. If certain urgent issues arise, timely information will not be announced until the end of each month. In addition, the survey only contains information derived from questionnaire items, which means it can be difficult to catch up to the direct effects of newly arising issues. The survey also faces potential declines in response rates and erroneous responses. Therefore, it is necessary to find a way to complement it. For this purpose, we construct and assess an index designed to measure consumer economic sentiment index using sentiment analysis. Unlike the survey-based measures, our index relies on textual analysis to extract sentiment from economic and financial news articles. In particular, text data such as news articles and SNS are timely and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. There exist two main approaches to the automatic extraction of sentiment from a text, we apply the lexicon-based approach, using sentiment lexicon dictionaries of words annotated with the semantic orientations. In creating the sentiment lexicon dictionaries, we enter the semantic orientation of individual words manually, though we do not attempt a full linguistic analysis (one that involves analysis of word senses or argument structure); this is the limitation of our research and further work in that direction remains possible. In this study, we generate a time series index of economic sentiment in the news. The construction of the index consists of three broad steps: (1) Collecting a large corpus of economic news articles on the web, (2) Applying lexicon-based methods for sentiment analysis of each article to score the article in terms of sentiment orientation (positive, negative and neutral), and (3) Constructing an economic sentiment index of consumers by aggregating monthly time series for each sentiment word. In line with existing scholarly assessments of the relationship between the consumer confidence index and macroeconomic indicators, any new index should be assessed for its usefulness. We examine the new index's usefulness by comparing other economic indicators to the CSI. To check the usefulness of the newly index based on sentiment analysis, trend and cross - correlation analysis are carried out to analyze the relations and lagged structure. Finally, we analyze the forecasting power using the one step ahead of out of sample prediction. As a result, the news sentiment index correlates strongly with related contemporaneous key indicators in almost all experiments. We also find that news sentiment shocks predict future economic activity in most cases. In almost all experiments, the news sentiment index strongly correlates with related contemporaneous key indicators. Furthermore, in most cases, news sentiment shocks predict future economic activity; in head-to-head comparisons, the news sentiment measures outperform survey-based sentiment index as CSI. Policy makers want to understand consumer or public opinions about existing or proposed policies. Such opinions enable relevant government decision-makers to respond quickly to monitor various web media, SNS, or news articles. Textual data, such as news articles and social networks (Twitter, Facebook and blogs) are generated at high-speeds and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. Although research using unstructured data in economic analysis is in its early stages, but the utilization of data is expected to greatly increase once its usefulness is confirmed.

• KDI Journal of Economic Policy
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• v.32 no.4
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• pp.1-34
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• 2010

We conduct a comprehensive risk analysis of household debt in Korea for the first time using the whole sample credit bureau (CB) data of 2.2 million individual debtors. After analysing debt service capacity profiles of debtor groups classified by the borrower characteristics such as income, age, occupation, credit scoring, and the type of creditor business companies, we investigate the impact of interest rate and income changes on debt service-to-income ratios (DTIs) and default rates of respective debtor groups. Empirical results indicate that debt service burdens are relatively high for low income wage earners, high income self-employed, low income capital and card loan holders, and high income mutual savings loan holders. We also find that debtors from multiple financial companies are particularly weak in their debt service capacity. The scenario analysis indicates that financial companies, with the current level of capital buffers, may be able to absorb negative consequences arising from the increase in DTIs and loan default rates if the interest rate and income changes remain modest. However, the negative consequences may fall disproportionately on non-bank financial companies such as capital, credit card, and mutual savings banks, whose debtors' DTIs are already high. We also find that the refinancing risk of household debt is relatively high in Korea as more than half of household mortgage debts are bullet loans. As the DTIs of mortgage loan holders are already high, under the current DTI regulation, mortgage loans may not be readily refinanced especially when the interest rate rises. Disruptions in mortgage loan refinancing may put downward pressure on housing prices, which may in turn magnify refinancing risk under the current loan-to-value (LTV) regulation. Overall our analysis suggests that, for more effective monitoring of household debt risk, it is necessary to combine existing surveillance schemes based on macro aggregate indicators with more comprehensive and detailed risk analyses based on micro individual data.

• Journal of Korean Society of Forest Science
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• v.94 no.6
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• pp.410-419
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• 2005

Community structure of evergreen broad-leaved forest of Mt. Yeogwi in Jin-do was investigated to secure sustainable conservation of evergreen broad-leaved forest. Twenty survey plots of $20m{\times}20m$ were established along the elevation from 200 m to 390 m above the sea level in the northwestern slope. The woody species were tallied at each plots. DBH distribution of the major evergreen broad-leaved trees was investigated to find out the spatial distribution. Cluster analysis was applied to a set of vegetation data, that is, importance value to classify the forest community. Species diversity, evenness and species correlation were analysed. Canonical correspondence analysis was also applied to vegetation data and soil environmental data. Cluster analysis showed that the forests of Mt. Yeogwi were classified into 2 community groups, such as Camellia japonica community group and Quercus acuta community group. C japonica community group was subdivided into C japonica- evergreen broad-leaved trees community, C. japonica-Neolitsea sericea community, and C. japonica-deciduous broad-leaved trees community. Q. acuta community group was subdivided into Q. acuta-C. japonica community, and Q. acuta community. C. japonica, Q. acuta, N. sericea, Machilus thunbergii and Illicium religiosum were dominant evergreen broad-leaved tree species, while Styrax japonica, Lindera erythrocarpa, Cornus kousa, Prunus sargentii, Albizzia julibrisin and Quercus acutissima were major deciduous tree species. Species diversity was greater in Q. acuta community group (0.8231 for Q. acuta-C. japonica community, and 0.8135 for Q. acuta community) than in C. japonica community group (0.7674 for C. japonica-evergreen broad-leaved trees community, 0.6164 for C. japonica-N. sericea community, and 0.7931 for C. japonica-deciduous broad-leaved trees community). DBH 2 cm~10 cm of major evergreen broad-leaved trees occupied 80% of all. C. japonica of less than DBH 5 cm tended to aggregate but distribute randomly or regularly with increasing DBH. Q. acuta distributed more aggregately than C. japonica and Machilus thunbergii for more than 15 cm of DBH. C. japonica correlated negatively with Q. acuta, I. religiosum and C. kousa, but positively with N. sericea. with significance at 1% level. Q. acuta correlated negatively with C. japonica, N. sericea and M. thunbergii but positively with l. religiosum. There were also negative correlation between N. sericea and C. kousa. CCA showed that forest communities were correlated with soil variables such as CEC, soil organic matter and soil pH. With increased soil organic matter and CEC, and decreased soil pH, C. japonica was dominant and forest community and Q. acuta and N. sericea tended to develop in the evergreen broad-leaved forest.

• Korean Journal of Legislative Studies
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• v.26 no.2
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• pp.113-140
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• 2020

This study is meaningful in that it is the first analysis of Korean elections using the concept of spatial autocorrelation. Spatial autocorrelation means that an event occurring in one location in space has a high correlation with an event occurring in the surrounding area. The voter turnout rate in the 21^st general election of Seoul area was divided into the early-voting turnout and voting-day turnout, and the spatial pattern of the turnout was examined. Most of the previous studies were based on the unit of the precinct and personal data, but this study analyzed on the basis of the lower unit, Eup-myeon-dong, and analyzed using spatial data and aggregate data. Moran I index showed a fairly high spatial autocorrelation of 0.261 in the voting-day turnout, while the index of the early-voting turnout was low at 0.095, indicating that there was little spatial autocorrelation despite statistical significance. The voting-day turnout, which showed strong spatial autocorrelation, was compared and analyzed using the OLS regression model and the spatial statistics model. In the general regression model, the coefficient of determination R² rose from 0.585261 to 0.656631 in the spatial error model, showing an increase in explanatory power of about 7 percentage points. This means that the spatial statistical model has high explanatory power. The most interesting result is the relationship between the early-voting turnout and the voting-day turnout. The higher the early-voting turnout is, the lower the voting-day turnout is. When the early-voing turnout increases by about 2%, the voting-day turnout drops by about 1%. In this study, the variables affecting the early-voting turnout and the voting-day turnout are very different. This finding is different from the previous researches.