• Transactions of the Korean Society of Mechanical Engineers B
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• v.21 no.4
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• pp.494-502
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• 1997

Experiments on corresponding jet flames with stagnant point diffusion flames have been carried out in initial injection periods. A compensated measurement of maximum flame temperature, which is based on the ion signal, has been employed to inspect flame responses to time-varying strain rates. The flame responses are obtained at two conditions for the slowly time-varying strain rate and the case of flame extinction, and analyzed to confirm similarity between a stagnant point diffusion flame and an evolving jet diffusion flame. Nonsteady effects are addressed via the comparison between several time scales. The time variation with low strain rates, in which illustrates the flame behavior of the upper branch far from extinction in the well-known S-curve, is confirmed to produce a quasi-steady flame response through the nonsteady experiments. The time variation with strain rates in the case of flame extinction indicates an unsteady effect of flame response. It is therefore found that the flame responses near jet tip depend on time histories of characterized strain rates in the developing process.

• Human Ecology Research
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• v.56 no.6
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• pp.619-626
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• 2018

This study investigated the impact of the amount of time online on cyberbullying perpetration of middle school students as well as examined if the justice sensitivity (victim sensitivity and penetrator sensitivity) moderated the relationship between the amount of time online and cyberbullying perpetration. The participants in this study were 236 students (120 boys and 116 girls) from two middle schools located in Seoul and Incheon. The levels of cyberbullying perpetration and justice sensitivity were measured by scales developed by Campfield (2008) and Schmitt et al. (2010), respectively. The participants were also asked to report on how much time they spent online a day. The data were analyzed via descriptive statistics, hierarchical regression, and procedures mentioned by Baron and Kenny (1986). The results revealed that the more the students used the Internet, the more likely they were to become a cyberbullying perpetrator. However, such a tendency was observed only for the students who had a higher level of victim sensitivity, and not for those with a lower level of victim sensitivity. This suggested that victim sensitivity moderated the effect of the amount of time spent on the Internet on cyberbullying perpetration; but, penetrator sensitivity had no moderating effect.

• The Journal of Engineering Geology
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• v.34 no.2
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• pp.173-191
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• 2024

Landslides pose significant threats to many countries globally, yet the development and implementation of effective landslide early warning systems (LEWS) remain challenging due to multifaceted complexities spanning scientific, technological, and political domains. Addressing these challenges demands a holistic approach. Technologically, integrating thresholds, such as rainfall thresholds, with real-time data within accessible, open-source software stands as a promising solution for LEWS. This article introduces LandScient_EWS, a PHP-based program tailored to address this need. The software facilitates the comparison of real-time measured data, such as rainfall, with predefined landslide thresholds, enabling precise calculations and graphical representation of real-time landslide advisory levels across diverse spatial scales, including regional, basin, and hillslope levels. To illustrate its efficacy, the program was applied to a case study in Medellin, Colombia, where a rainfall event on August 26, 2008, triggered a shallow landslide. Through pre-defined rainfall intensity and duration thresholds, the software simulated advisory levels during the recorded rainfall event, utilizing data from a rain gauge positioned within a small watershed and a single grid cell (representing a hillslope) within that watershed. By identifying critical conditions that may lead to landslides in real-time scenarios, LandScient_EWS offers a new paradigm for assessing and responding to landslide hazards, thereby improving the efficiency and effectiveness of LEWS. The findings underscore the software's potential to streamline the integration of rainfall thresholds into both existing and future landslide early warning systems.

• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.175-186
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• 1999

Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support fer multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To date, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques' results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.03a
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• pp.175-186
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• 1999

Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support for multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To data, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

• Journal of The Korean Dental Society of Anesthesiology
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• v.3 no.1 s.4
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• pp.10-18
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• 2003

Background: Studies on the pain have been dealing with many different ways for last several centuries. Especially, preemptive analgesia is being used as a method to control the postoperative pain. Many studies on its efficacy have been processed in different ways about various drugs, administration methods and times for various operations. And the value of preemptive analgesia are still controversial regarding the results of other clinical studies. The authors performed a clinical study on efficacy of preemptive analgesia using an non-steroidal anti-inflammatory drug (NSAID) for the surgical extraction of impacted third molar teeth and present the more effective pain treatment after oral surgery with literature review. Methods: Using a randomized double blind test design, this study compared the analgesic efficacies of an NSAID, Talniflumate 370 mg. This drug administrated first either 1 hour preoperatively (experimental group) or when the pain developed moderately to severely over 5 scale of verbal rating scales (0-10) to respective 30 patients undergoing the removal of impacted third molars. Pain intensity and the time from the end of surgery were assessed postoperatively whenever the patients demanded additional drug over 5 scale for forty eight hours using same verbal rating scales. Results: The sex distribution, the age of the patients. and the time required for surgery in two groups were similar. The average first time for demanding additional drug after surgery was 163.9 minutes in experimental group and 191.5 minutes in control group. At this time, the average pain intensity was 5.8 in experimental group and 6.1 in control group. And the average second time for demanding additional drug was 365.5 minutes in experimental group and 351.8 minutes in control group. At this time. the average pain intensities were 6.6 in experimental group and 6.2 in control group. No statistically significant difference was found between the average first times and second times, and the average pain intensities at first and second times in two groups. Conclusions: From these results the efficacy of preemptive analgesia used in this study was not appeared. This clinical study indicates that many NSAIDs administrated preoperatively in present practices have weak efficacy of preemptive analgesia for postoperative pain, thus the authors recommend that only postoperative analgesics are adequate without preoperative use of analgesics.

• Journal of Korea Water Resources Association
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• v.56 no.10
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• pp.655-665
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• 2023

In this study, unit hydrographs are calculated when precipitations of 10 scales instantaneously occurs in a virtual watershed with a constant slope and roughness. Then, the relationship between the peak flow rate and the peak occurrence time of the unit hydrograph was calculated for the precipitation scale, respectively. At this time, the virtual watershed simplified with a rhombic shape, a constant slope, and a flow condition with a certain roughness was applied instead of a natural watershed in order to understand the effect the precipitation scale has on the peak value of the unit hydrograph. And it was assumed that the precipitation in the basin was effective rainfall and the runoff was direct runoff, and the runoff flowed in a straight, uniform flow from the drop point to the outlet. The relationship between the peak flow and the peak occurrence time of the unit hydrograph was calculated in the case of 10 types of precipitation scales of 10 mm, 40 mm, 90 mm, 160 mm, 250 mm, 360 mm, 640 mm, 1,000 mm, 1,210 mm, and 1,690 mm of effective precipitation. A noteworthy achievement of this study is that, even without the storage effect of the watershed, as the scale of precipitation increases, the depth of runoff increases, so the flow rate in the watershed increases and the distance per unit time increases, so the peak flow rate increases and the peak occurrence time increases. This is a nonlinear characteristic of watershed runoff.

• Korean Journal of Child Studies
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• v.26 no.5
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• pp.311-330
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• 2005

The purpose of this study was to examine the paternal involvement tendency and its effect on adolescent's self-esteem for boys and girls. Subjects were 607 1st and 2nd grade middle school students in Busan. The data were analyzed by t-test, one-way Anova, Pearson's correlation, and multiple regression analysis. The results were as follows. The scores on paternal involvement were influenced by the amount of time spent with parents, 5days work a week of father, flexibility of leaving work-time of mother, regularity of holiday work of mother as well as adolescents' and fathers' sociodemographic characteristic. For boys, self-esteem was influenced by all sub-scales of paternal involvement : the leisure-life, proffering information, academic support, eveηday life, material support, discipline, and tradition-inheritance. For girls, self-esteem was influenced by leisure-life, proffering information, academic support, everyday life, and material supports.

• 한국연소학회:학술대회논문집
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• 2003.05a
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• pp.209-214
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• 2003

The Saffman-Taylor instability mechanisms in laminar premixed flames in a Hele-Shaw cell are investigated using two-dimensional numerical simulations with Poiseuille assumption for the viscous effect. The baseline calculations considering the Darrieus-Landau and diffusive-thermal instability modes show the results consistent with the classical linear instability theory. With the Saffrnan-Taylor instability mechanism. the overall effect is to enhance the destabilizing mechanism by providing an increased viscous force in the product gas. The linear instability behavior is found to qualitatively similar to the Darrieus-Landau mechanism. However, the results in the nonlinear range demonstrate that there may exist distinct characteristic time scales associated with Darrieus-Landau and Saffman-Taylor mechanisms, such that the latter effect sustains longer in time, contributing to a higher overall flame speed.

• ETRI Journal
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• v.29 no.2
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• pp.201-211
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• 2007

This paper focuses on the scheduling problem with the objective of maximizing system throughput, while guaranteeing long-term quality of service (QoS) constraints for non-realtime data users and short-term QoS constraints for realtime multimedia users in multiclass service high-speed uplink packet access (HSUPA) systems. After studying the feasible rate region for multiclass service HSUPA systems, we formulate this scheduling problem and propose a multi-constraints HSUPA opportunistic scheduling (MHOS) algorithm to solve this problem. The MHOS algorithm selects the optimal subset of users for transmission at each time slot to maximize system throughput, while guaranteeing the different constraints. The selection is made according to channel condition, feasible rate region, and user weights, which are adjusted by stochastic approximation algorithms to guarantee the different QoS constraints at different time scales. Simulation results show that the proposed MHOS algorithm guarantees QoS constraints, and achieves high system throughput.