• KDI Journal of Economic Policy
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• v.30 no.2
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• pp.1-26
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• 2008

This paper attempts to re-evaluate the size of housing wealth effect in Korea. Our focus is on the size of 'genuine' housing wealth effect, i.e., the response of consumption spending by home-owners to the changes in housing wealth. Two issues show up while we estimate the 'genuine' wealth effects using aggregate time series data: the issues around home ownership and proper measure of consumption. We first argue that it is more appropriate to use non-housing consumption, because housing consumption is in large part not of the choice of home owners but the imputed rents they do not actually choose to pay. We then proceed to address the issue of home ownership, by examining how much to revise the estimates of housing wealth effect obtained from aggregate non-housing consumption data. We construct two structural models and estimate the share of home-owners' consumption in those models' context. It is found that, if properly revised in light of the estimated consumption shares of home-owners, the magnitude of resulting housing wealth effects are larger than what simple time series regressions imply.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.1
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• pp.417-425
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• 2020

In this paper, value relevance of the level of dependence on separate accounts in non-life-insurance companies is studied. As noted by Shim et al. (2015), the separate accounts of insurance companies consist of contracts with different attributes from the general accounts, so it is likely that firm value will vary depending on the insurer's dependence on the separate accounts. Thus, in this paper, an empirical analysis has been conducted using quarterly financial data and stock price data from domestic listed non-life-insurance companies from 2011 to 2018. The analysis shows that variables representing the level of dependence on separate accounts have a significant negative relevance to firm value. These results may suggest that changes in the proportion of a non-life-insurer's separate accounts may result in a change to its firm value under the same net assets and net income scales in aggregate accounts. This study provides management implications for the operation of separate accounts from the perspective of maximizing firm value. In addition, this study suggests that disclosure system improvement would be necessary to more directly report the operational performance of the separate accounts.

• Journal of KIISE:Information Networking
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• v.36 no.5
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• pp.456-469
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• 2009

We develop a new wireless link quality metric, ECOT(Estimated Channel Occupancy Time) that enables a high throughput route setup in wireless mesh networks. The key feature of ECOT is to be applicable to diverse mesh network environments where IEEE 802.11 MAC (Medium Access Control) variants are used. We take into account the exact operational features of 802.11 MAC protocols, such as 802.11 DCF(Distributed Coordination Function), 802.11e EDCA(Enhanced Distributed Channel Access) with BACK (Block Acknowledgement), and 802.11n A-MPDU(Aggregate MAC Protocol Data Unit), and derive the integrated link metric based on which a high throughput end-to-end path is established. Through extensive simulation in random-topology settings, we evaluate the performance of proposed link metric and present that ECOT shows 8.5 to 354.4% throughput gain over existing link metrics.

• Journal of dental hygiene science
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• v.22 no.3
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• pp.191-198
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• 2022

Background: The purpose of this study was to evaluate the composition of the crystal phases of various calcium silicate-based materials (CSMs): ProRoot white MTA^Ⓡ (mineral trioxide aggregate) (WMTA), Ortho MTA^Ⓡ (OM), Endocem MTA^Ⓡ (EM), Retro MTA^Ⓡ (RM), Endocem Zr^Ⓡ (EN-Z), Biodentine^TM (BD), EZ-seal^TM (EZ), and OrthoMTA III (OM3). Methods: In a sample holder, 5 g of the powder sample was placed and the top surface of the material was packed flat using a sterilized glass slide. The prepared slides were mounted on an X-ray diffraction (XRD) instrument (D8 Advance; Bruker AXS GmbH, Germany). The X-ray beam 2θ angle range was set at 10~90° and scanned at 1.2° per minute. The Cu X-ray source set to operate at 40 kV and 40 mA in the continuous mode. The peaks in the diffraction pattern of each sample were analyzed using the software Diffrac (version 2.1). Then, the peaks were compared and matched with those of standard materials in the corresponding Powder Diffraction File (PDF-2, JCPDS International Center for Diffraction Data). A powder samples of the materials were analyzed using XRD and the peaks in diffraction pattern were compared to the Powder Diffraction File data. Results: Eight CSMs showed a similar diffraction pattern because their main component was calcium silicate. Eight CSMs showed similar diffraction peaks because calcium silicate was their main component. Two components were observed to have been added as radiopacifiers: bismuth oxide was detected in WMTA, OM, and EM while zirconium oxide was detected in RM, EN-Z, BD, EZ, and OM3. Unusual patterns were detected for the new material, OM3, which had strong peaks at low angles. Conclusion: It was caused by the presence of Brushite, which is believed to have resulted in crystal growth in a particular direction for a specific purpose.

• Computers and Concrete
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• v.33 no.1
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• pp.55-75
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• 2024

The present study introduces an optimum performance soft computing model for predicting the compressive strength of high-performance concrete (HPC) by comparing models based on conventional (kernel-based, covariance function-based, and tree-based), advanced machine (least square support vector machine-LSSVM and minimax probability machine regressor-MPMR), and deep (artificial neural network-ANN) learning approaches using a common database for the first time. A compressive strength database, having results of 1030 concrete samples, has been compiled from the literature and preprocessed. For the purpose of training, testing, and validation of soft computing models, 803, 101, and 101 data points have been selected arbitrarily from preprocessed data points, i.e., 1005. Thirteen performance metrics, including three new metrics, i.e., a20-index, index of agreement, and index of scatter, have been implemented for each model. The performance comparison reveals that the SVM (kernel-based), ET (tree-based), MPMR (advanced), and ANN (deep) models have achieved higher performance in predicting the compressive strength of HPC. From the overall analysis of performance, accuracy, Taylor plot, accuracy metric, regression error characteristics curve, Anderson-Darling, Wilcoxon, Uncertainty, and reliability, it has been observed that model CS4 based on the ensemble tree has been recognized as an optimum performance model with higher performance, i.e., a correlation coefficient of 0.9352, root mean square error of 5.76 MPa, and mean absolute error of 4.1069 MPa. The present study also reveals that multicollinearity affects the prediction accuracy of Gaussian process regression, decision tree, multilinear regression, and adaptive boosting regressor models, novel research in compressive strength prediction of HPC. The cosine sensitivity analysis reveals that the prediction of compressive strength of HPC is highly affected by cement content, fine aggregate, coarse aggregate, and water content.

• Journal of Korea Spatial Information System Society
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• v.9 no.2
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• pp.93-107
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• 2007

In this paper, an adaptive range aggregation spatial index method is proposed for spatial range query in ubiquitous sensor networks. As the ubiquitous sensor networks are the new information-oriented paradigm, many energy efficient spatial range query methods in ubiquitous sensor networks environment are studied vigorously. In sensor networks, users can monitor environment scalar data such as temperature and humidity during user defined time and spatial ranges. In order to execute spatial range query efficiently, rectangle based index methods are proposed, such as SPIX. But they define the return path as the opposite of its query transmit path. However, the sensor nodes in queried ranges are closed to each other, they can't aggregate the sensed value in a queried range because their query transmission paths are different. As a result, the previous methods waste energy unnecessarily to aggregate sensing data out of the queried range. In this paper, an adaptive aggregation index method is proposed that can aggregate values in a user defined range adaptively by using its neighbor information. It is shown that sensor power is saved efficiently by using the proposed method over the performance evaluation.

• Journal of the Korean Society for Railway
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• v.20 no.2
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• pp.265-274
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• 2017

For accurate demand forecasting of railway logistics, we estimated intercity freight mode choice models based on the binary logit model and using production-consumption data from the Korea Transport Database. We estimated two types of models and compared the results by major item of railway logistics, such as container, cement, and steel: 1) The aggregate freight mode choice models are based on the revealed preference (RP) data and 2) The disaggregate models are based on the stated preference (SP) data. With respect to the container, the travel time variable was found to be statistically significant; however, the travel cost variable was not statistically significant in the RP model, while the travel cost variable was statistically significant in the SP model. For cement and steel, the travel cost variables were statistically significant but the travel time variables were not statistically significant in either the RP or the SP models. These results are inconsistent with results from previous studies based on SP data, which showed that the travel time variables were significant. Consequently, it can be concluded that the travel time factor should be considered in container transport, but that this factor is negligible for cement and steel transport.

• Convergence Security Journal
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• v.18 no.1
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• pp.103-110
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• 2018

Modern society is increasingly demanding in many areas of big data processing technology to collect, aggregate, and analyze large amounts of data over the Internet and SNS. A typical application is to evaluate the reputation of a company or college. To measure and quantify a reputation, fair and precise data and efficient data processing are very important. For this purpose, a quantitative quotient was obtained using public data, a qualitative quotient was obtained through sentiment analysis using news articles, and a complex college reputation quotient was calculated. In this paper, a complex college reputation quotient was calculated based on the quantitative index, reflecting the sentimental reputation, and based on the proposed mixed university system. In this paper, the Complex College Reputation System(CCRS) was proposed, which produced the Complex College Reputation Quotient with an objective quantitative quotient and qualitative quotient reflecting the sentimental reputation to measure the college reputation.

• Journal of Korean Neurosurgical Society
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• v.30 no.sup2
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• pp.189-196
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• 2001

Objective : We tested the hypothesis that photodynamic therapy(PDT) with Photofrin inhibits tumor invasion of U87 human glioma cells using several in vitro assay to measure tumor invasiveness. The effects of PDT on cell growth, directional migration and cell invasion were investigated. Material and Method : Tumor cells were treated with Photofrin at various doses and at a fixed optical(632nm) dose of $100mJ/cm^2$. Cytotoxicity was tested using the MTT method. Invasion assays including the matrigelartificial basement membrane barrier migration and spheroid confrontation with confocal microscopic analysis were used to study the relationship between PDT and invasiveness. Result : U87 cells showed a dose dependent cytotoxic response to increasing Photofrin dose. Data from the matrigel artificial basement membrane assay indicate that PDT inhibits the U87 cell migration dose dependently. Low doses of subcytotoxic PDT treatment, such as 2.5ug/ml Photofrin dose, also appeared to significantly inhibit migration of U87 cells(p<0.05). In co-cultures between U87 cell spheroids and brain aggregates, progressive invasion with destruction of the brain aggregate occurs. The extent of tumor cell infiltration and proportion or intact brain aggregate remaining after 24h differs in Photofrin PDT treated versus Photofrin only control, with changes suggestive of a dose-response effect. Conclusion : our data indicate that PDT with Photofrin significantly inhibits the invasiveness of U87 cells, and this inhibition is dose dependent.

• Water Engineering Research
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• v.2 no.2
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• pp.139-148
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• 2001

The teleconnections between El Nino/Southern Oscillation (ENSO) and droughts in Korea and the continental United States(U.S.) are investigated using cross analysis. For this purpose, monthly ENSO data and Palmer Drought Severity Index (PDSI) for Korea and for seven states in the U.S. are used. This study shows that there are significant statistical associations between ENSO indices and PDSI for Korea; however, the associations are very weak. It is found that dry conditions in Korea are positively correlated with El Nino, while wet conditions with La Nina. SOI, SSt in the Nino 4 and Ship track 6 regions among ENSO indices are more strongly correlated with PDSI than the other ENSO indices when using the original standardized data, but the SST Nino 3, SST Nino 4, and Darwin SSP exhibit abetter correlations with PDSI when using filtered data to be removed autocorrelation components of the original standardized data. The response time lag for maximum correlation between ENSO indices and PDSI appears to be affected by filtering the data. This is expecially true for Korea than for state analyzed in U.S. In addition, it is found that the PDSI in the continental U.S. is more strongly correlated wiht ENSO than in Korea. Furthermore, in analyzing the El Nino and La Nina aggregate composite data, it is found that the dry anomalies in Korea occur from the year following El Nino to about tow years after while the wet anomalies occur from La Nina year for a period of about two years.