• Journal of the Korean Vacuum Society
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• v.17 no.6
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• pp.518-522
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• 2008

The miniaturization of device size and multilevel interlayers have been developed by ULSI circuit devices. These submicron processes cause serious problems in conventional metallization due to the solubility of silicon and metal at the interface, such as an increasing contact resistance in the contact hole and interdiffusion between metal and silicon. Therefore it is necessary to implement a barrier layer between Si and metal. Thus, the size of multilevel interconnection of ULSI devices is critical metallization schemes, and it is necessary reduce the RC time delay for device speed performance. So it is tendency to study the Cu metallization for interconnect of semiconductor processes. However, at the submicron process the interaction between Si and Cu is so strong and detrimental to the electrical performance of Si even at temperatures below $200^{\circ}C$. Thus, we suggest the tungsten-carbon-nitrogen (W-C-N) thin film for Cu diffusion barrier characterized by nano scale indentation system. Nano-indentation system was proposed as an in-situ and nanometer-order local stress analysis technique.

• Korea journal of population studies
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• v.31 no.1
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• pp.1-26
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• 2008

This research examines the effect of area level characteristics on individual health, particularly focusing on the vulnerable populations in Seoul. We consider adult individuals whose family income is under 1.5 million won, who are aged 65 and over, or who have neither spouse nor job but aged 40 and over as vulnerable populations. Using the 2005 Seoul Citizens' Health Interview Survey, we conducted multilevel analyses to simultaneously investigate the effect of area and individual level characteristics on health. Between-area variance of self-rated health status was greater for the elderly population than for all populations. Area material deprivation index and happiness index were associated with the self-rated health of economically disadvantaged populations. Vulnerable populations showed greater between-area variances in emotional health than the same for all populations. Area happiness index, material deprivation index, the proportion of households below poverty line and street safety showed statistically significant association with emotional health. The effect of area characteristics were particularly salient for the emotional health of elderly population and its between area variance was also notable.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.7
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• pp.299-306
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• 2022

In recent, sensors embedded in robots, equipment, and circuits have become common, and research for diagnosing device failures by learning measured sensor data is being actively conducted. This failure diagnosis study is divided into a classification model for predicting failure situations or types and a regression model for numerically predicting failure conditions. In the case of a classification model, it simply checks the presence or absence of a failure or defect (Class), whereas a regression model has a higher learning difficulty because it has to predict one value among countless numbers. So, the reason that regression modeling is more difficult is that there are many irregular situations in which it is difficult to determine one output from a similar input when predicting by matching input and output. Therefore, in this paper, we focus on input and output data with periodicity, analyze the input/output relationship, and secure regularity between input and output data by performing sliding window-based input data patterning. In order to apply the proposed method, in this study, current and temperature data with periodicity were collected from MMC(Modular Multilevel Converter) circuit system and learning was carried out using ANN. As a result of the experiment, it was confirmed that when a window of 2% or more of one cycle was applied, performance of 97% or more of fit could be secured.

• Korean Journal of School Psychology
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• v.18 no.2
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• pp.249-267
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• 2021

This study examined how social withdrawal as an individual factor and discrimination as a contextual factor contributed to depression caused by peer victimization among middle school students. Self-reported data of 1,611 students from 86 classrooms in 7 middle schools was analyzed, using multilevel path analysis. The results indicate that peer victimization had a significant partial mediating effect on the relation between social withdrawal and depression at the individual level. Social withdrawal had a direct positive effect on depression as well as an indirect positive effect on depression via high levels of peer victimization. Discrimination also positively predicted peer victimization at the classroom level. Moreover, classroom-level discrimination moderated the individual-level relations between social withdrawal and peer victimization. The relation between social withdrawal and peer victimization was much stronger as the levels of discrimination in the classroom were higher. These findings shed light on the importance of considering both individual and contextual factors when intervening to prevent peer victimization.

• Journal of Cadastre & Land InformatiX
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• v.52 no.2
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• pp.189-210
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• 2022

Cities around the world have paid attention to public transportation as an alternative to reducing traffic congestion caused by automobile usage, excessive energy consumption, and environmental pollution. This study measures accessibility to subway stations in Seoul using a supply-demand-based accessibility technique. Then, the impacts were analyzed through land prices by use and segment. As a result of analysis using the multilevel hedonic price models, accessibility considering both supply and demand for the subway had a positive effect on both residential and non-residential land prices. The effect was stronger for residential than for non-residential. Further, among the accessibility measured by the three functions, the accessibility by the Exponential function was most suitable for the residential land price, and the accessibility measured by the Power function for the non-residential land price had the highest explanatory power. Also, looking at the impacts by land price segments, it was found that higher access to metro stations had the greatest positive impacts on the most expensive segment of residential and non-residential land prices. The results of this study can be applied not only to identify the impacts of public investment on neighborhoods, but also to support real estate valuation.

• Computational Structural Engineering
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• v.10 no.4
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• pp.303-313
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• 1997

Though many techniques for the damage assessment of structures have been studied recently, most of them can be only applied to simple structures. Therefore, practical damage assessment techniques that evaluate the damage location and the damage state for large structures need to be developed. In this study, a damage assessment technique using a neural network is developed, in which the bilevel damage assessment procedure is proposed to evaluate the damage of a large structure from the limited monitoring data. The procedure is as follows ; first, for the rational selection of damage critical members, the members that affect the probability of failure or unusual structural behavior are selected by sensitivity analysis. Secondly, the monitoring points and the number of sensors that are sensitive to the damage severity of the selected members are also selected through the sensitivity analysis with a proposed sensitivity measurement format. The validity and applicability of the developed technique are demonstrated by various examples, and it has been shown that the practical information on the damage state of the selected critical members can be assessed even though the limited monitoring data have been used.

• Journal of the Korea institute for structural maintenance and inspection
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• v.10 no.2
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• pp.123-133
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• 2006

The main objective of this study is to develop an optimization algorithm of framed structures with rigid and various semi-rigid connections using the multilevel dynamic programming and the sequential unconstrained minimization techniques (SUMT). The second-order elastic analysis is performed for steel framed structures. The second order elastic analysis is developed based on nonlinear beam-column theory considering the bowing effect. The following semi-rigid connections are considered; double web angle, top-seat angle and top-seat angle with web angle. We considered the three connection models, such as modified exponential, polynomial and three parameter model. The total weight of the structural steel is used as the objective function in the optimization process. The dimensions of steel cross section are selected as the design variables. The design constraints consist of strength requirements for axial, shear and flexural resistance and serviceability requirements.

• Journal of Convergence for Information Technology
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• v.12 no.5
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• pp.100-106
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• 2022

A longitudinal study refers to a research method based on longitudinal data repeatedly measured on the same object. Most of the longitudinal analysis methods are suitable for prediction or inference, and are often not suitable for use in exploratory study. In this study, an exploratory method to analyze longitudinal data is presented, which is to find the longitudinal trajectory after determining the best number of clusters by clustering longitudinal data using self-organizing map technique. The proposed methodology was applied to the longitudinal data of the Employment Information Service, and a total of 2,610 samples were analyzed. As a result of applying the methodology to the actual data applied, time-series clustering results were obtained for each panel. This indicates that it is more effective to cluster longitudinal data in advance and perform multilevel longitudinal analysis.

• Journal of Positioning, Navigation, and Timing
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• v.4 no.4
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• pp.161-171
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• 2015

Alternative binary offset carrier (AltBOC) signals can be approximated by four synchronized direct sequence spread spectrum (DSSS) signals, each pair of which is a quadrature phase shift keyed (QPSK) signal at a different frequency. Therefore, depending on the strength of an incoming AltBOC signal, an acquisition technique can reduce the mean acquisition time (MAT) by searching the four DSSS signals asynchronously; the search for each of the four DSSS signals can start at one of the evenly separated hypotheses on the two-dimensional hypothesis space. And detection sensitivity can be improved by multiple levels when different numbers of search results for the same hypothesis are combined. In this paper, we propose a fast AltBOC acquisition technique that has an asynchronous search strategy and efficiently utilizes the output of the four search results to increase the sensitivity level when sensitivity improvement is needed. We provide a complete theoretical analysis and demonstrate with numerous Monte Carlo simulations that the MAT of the proposed technique is much smaller than conventional AltBOC acquisition techniques.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.12 no.3
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• pp.397-406
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• 1999

A new solution procedure for approximate reanalysis, using the staged hybrid methods with substructuring, is proposed in this study. Displacements are calculated with two step mixed procedures. First step is to introduce the conservative approximation, which is a hybrid form of the linear and reciprocal approximation, as local approximation. In the next step, it is combined with the global approximation by reduced basis approach. Stresses are evaluated from the displacements by matrix transformation. The quality of reanalyzed quantities can be greatly improved through these staged hybrid approximations, specially for large changes in the design. Overall procedures are based on substructuring scheme. Several numerical examples illustrate the validity and effectiveness of the proposed methods.