• Geomechanics and Engineering
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• v.37 no.3
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• pp.253-262
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• 2024

Dynamic properties are pivotal in soil analysis, yet their experimental determination is hampered by complex methodologies and the need for costly equipment. This study aims to predict dynamic soil properties using static properties that are relatively easier to obtain, employing machine learning techniques. The static properties considered include soil cohesion, friction angle, water content, specific gravity, and compressional strength. In contrast, the dynamic properties of interest are the velocities of compressional and shear waves. Data for this study are sourced from 26 boreholes, as detailed in a geotechnical investigation report database, comprising a total of 130 data points. An importance analysis, grounded in the random forest algorithm, is conducted to evaluate the significance of each dynamic property. This analysis informs the prediction of dynamic properties, prioritizing those static properties identified as most influential. The efficacy of these predictions is quantified using the coefficient of determination, which indicated exceptionally high reliability, with values reaching 0.99 in both training and testing phases when all input properties are considered. The conventional method is used for predicting dynamic properties through Standard Penetration Test (SPT) and compared the outcomes with this technique. The error ratio has decreased by approximately 0.95, thereby validating its reliability. This research marks a significant advancement in the indirect estimation of the relationship between static and dynamic soil properties through the application of machine learning techniques.

• Proceedings of the KSRS Conference
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• v.1
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• pp.352-355
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• 2006

In this study, the seasonal and inter-annual variation of sea surface current in the Gulf of Thailand were revealed through the use of WOD temperature and salinity data and monthly sea surface dynamic heights (SSDH) from TOPEX/Poseidon and ERS-2 altimetry data during 1995-2001. The mean dynamic height and mean geostrohic current were derived from the climatological data while SSDH data gave monthly dynamic heights and their geopstrophic currents. The mean geostrophic current showed strong southward and westward flow of South China Sea water along the gulf entrance. Counterclockwise eddy in the inner gulf and the western side of the gulf entrance associated with upwelling in the area. Seasonal geostrophic currents show basin-wide counterclockwise circulation during the southwest monsoon season and clockwise circulation during the northeast monsoon season. Upwelling was enhanced during the southwest monsoon season. The circulation patterns varied seasonally and inter-annually probably due to the variation in wind regime. And finally we found that congregation, spawning, and migration routes of short-bodied mackerel conform well with coastal upwelling and surface circulation in the gulf.

• Asian Journal of Business Environment
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• v.14 no.1
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• pp.23-30
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• 2024

Purpose: The purpose of this research is to explore the macroeconomic model through both static and dynamic equations. The primary objective of this study is to investigate the variations in the elasticity of substitution across changing economic variables within the framework of the Allen-Uzawa production functions. Research, design, data and methodology: The data were drawn from the World Bank's annual central statistical office database from 2010 to 2021 in the United States of America. The level of expenditures and of the public finance sector, macroeconomic data like output, inflation rates, and labor are examined. Results: This study demonstrates the interaction of two equations, clarifying that the macroeconomic model is practical to determining the stability of both static and dynamic equation systems analytically. The Allen-Uzawa equations allow for the verification of macroeconomic model properties, and study results demonstrate an increase in the range of capital uses as a form of mechanization. A constant elasticity of substitution function is derived from the macroeconomic variables. Conclusion: The macroeconomic model, though the analysis of the static and dynamic Allen - Uzawa model, not only facilitates the examination of long-term trends in crucial endogenous variables but also overcomes challenges commonly associated with other mathematical methods. Overall, the analysis promotes economic growth, investment, and employment. The levels of expenditures and the public finance sector, along with macroeconomic data such as output, inflation rates, and labor, are examined.

• Journal of KIISE:Databases
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• v.35 no.4
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• pp.319-332
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• 2008

Data cube, which is multi-dimensional data model, have been successfully applied in many cases of multi-dimensional data analysis, and is still being researched to be applied in data stream analysis. Data stream is being generated in real-time, incessant, immense, and volatile manner. The distribution characteristics of data arc changing rapidly due to those characteristics, so the primary rule of handling data stream is to check once and dispose it. For those characteristics, users are more interested in high support attribute values observed rather than the entire attribute values over data streams. This paper propose dynamic data cube for applying data cube to data stream environment. Dynamic data cube specify user's interested area by the support ratio of attribute value, and dynamically manage the attribute values by grouping each other. By doing this it reduce the memory usage and process time. And it can efficiently shows or emphasize user's interested area by increasing the granularity for attributes that have higher support. We perform experiments to verify how efficiently dynamic data cube works in limited memory usage.

• Journal of Labour Economics
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• v.32 no.2
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• pp.95-124
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• 2009

In this article, I were trying to analyze the listed manufacturing companies' trend of productivity and the corporate education & training effect after the financial crisis. According to the analysis, the listed manufacturing companies have decreased their productivity since financial crisis, and from such declining trend. jobless growth and a growth without physical and human capital investment has been observed. Furthermore, there is no efficient labor force coordination within the manufacturing industry; In order to analyze the effect of education & training investment on productivity more deeply, I have practiced the dynamic panel data analysis from constructing the micro panel data which consists of company level information 1997~2008. According to the consequences, dynamic panel data analysis solved the problem of the overestimating education & training effect fairly well.

• Proceedings of the Korean Geotechical Society Conference
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• 2004.03b
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• pp.245-252
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• 2004

When some enormous earthquake hazards broke out in the neighboring Japan and Taiwan, many Korean earthquake engineers thought that seismic guidelines must be adjusted safely and economically to consider the moderate earthquake characteristics. In the present aseismic guideline for liquefaction potential assessment, a simplified method using SPT-N value and a detail method based on the dynamic lab-tests were introduced. However, it is said that these methods based on the equivalent stress concept to simplify an irregular earthquake are not reliable to simulate the kaleidoscopical characteristics of earthquake loading correctly. Especially, even though various data from the dynamic lab-test can be obtained, only two data, a maximum cyclic load and a number of cycle at an initial liquefaction are used to determine the soil resistance strength in the detailed method. In this study, a new assessment of liquefaction potential is proposed and verified. In the proposed assessment, various data from dynamic lab-tests are used to determine the unique soil resistance characteristic and a site specific analysis is introduced to analyze the irregular earthquake time history itself. Also, it is found that the proposed assessment is reasonable because it is devised to reflect the changeable soil behavior under dynamic loadings resulted from the generation and development of excess pore water pressure.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.537-543
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• 2003

This paper presents the improved procedure to assess static and dynamic strength of crawler type excavators. A fully integrated model including front attachment and chassis was prepared for structural analysis. In this paper, two types of loading input methods were investigated and the method imposing digging force directly on bucket tooth was more convenient than imposing cylinder reaction force on cylinder pin even if the two methods showed no discrepancy in analysis results. Static strength analysis was carried out for eight analysis scenarios based on two extreme digging positions, maximum digging reach position and maximum digging force positions. The results from static strength analysis were compared with measured stresses, cylinder pressures and digging forces and showed a good quantitative agreement with measured data. Dynamic strength analysis was carried out for simple reciprocation of boom cylinders. It was recognized that the effect of compressive stiffness of hydraulic oil was very important for dynamic structural behavior. The results from dynamic strength analysis including hydraulic oil stiffness were also compared with measured acceleration data and showed a qualitative agreement with measured data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1286-1306
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• 2022

Searchable symmetric encryption (SSE) provides a safe and effective solution for retrieving encrypted data on cloud servers. However, the existing SSE schemes mainly focus on single keyword search in single client, which is inefficient for multiple keywords and cannot meet the needs for multiple clients. Considering the above drawbacks, we propose a scheme enabling dynamic multi-client and Boolean query in searchable symmetric encryption for cloud storage system (DMC-SSE). DMC-SSE realizes the fine-grained access control of multi-client in SSE by attribute-based encryption (ABE) and novel access control list (ACL), and supports Boolean query of multiple keywords. In addition, DMC-SSE realizes the full dynamic update of client and file. Compared with the existing multi-client schemes, our scheme has the following advantages: 1) Dynamic. DMC-SSE not only supports the dynamic addition or deletion of multiple clients, but also realizes the dynamic update of files. 2) Non-interactivity. After being authorized, the client can query keywords without the help of the data owner and the data owner can dynamically update client's permissions without requiring the client to stay online. At last, the security analysis and experiments results demonstrate that our scheme is safe and efficient.

• Journal of KIISE
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• v.41 no.12
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• pp.1126-1135
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• 2014

In recent years, RDF partitioning schemes have been studied for the effective distributed storage and management of large-scale RDF data. In this paper, we propose an RDF dynamic partitioning scheme to support load balancing in dynamic environments where the RDF data is continuously inserted and updated. The proposed scheme creates clusters and sub-clusters according to the frequency of the RDF data used by queries to set graph partitioning criteria. We partition the created clusters and sub-clusters by considering the workloads and data sizes for the servers. Therefore, we resolve the data concentration of a specific server, resulting from the continuous insertion and update of the RDF data, in such a way that the load is distributed among servers in dynamic environments. It is shown through performance evaluation that the proposed scheme significantly improves the query processing time over the existing scheme.

• Journal of the Korean Data and Information Science Society
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• v.18 no.2
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• pp.375-384
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• 2007

As teachings that use the ICT are more popular, many studies on the dynamic geometry environment(DGE) are under way. An important factor emphasized in the studies is to practical use learning activities of learners. In this study, we first define the learning history data in DGE. Second we develop a prototype of the DGE that is able to collect and analyze the learning history data automatically. The environment enables not only to grasp leaning history but also to create and manage new learning objects.