• Journal of Digital Convergence
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• v.13 no.11
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• pp.481-491
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• 2015

This research has verified the efficacy of character education course in Liberal Art Curriculum in accordance with the objective of K Women's University of which is the 'mind sharing through mindfulness, SMART human resources development'. Most of the content of character education is organized aiming to promote values of "appreciation". The subjects are experimental group and control group, of which are 229. Research methods were t-test of between groups. The effects of the course have shown that the experimental group students were higher on the level of connectedness sub-scale in Gestalt Contact Boundary Scale than those of the control group students(t=2.323, p = .021). Although the 'character education' course increased connectedness, but it no positive effect on mindfulness skill and self-esteem. This results showed that character education course is effective to promote mind sharing and connectedness in part. It was discussed about a way of further refining course contents and the need to reflect educational philosophy of the K Women's University.

• Journal of Convergence Society for SMB
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• v.2 no.1
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• pp.41-50
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• 2012

In this research, we developed a scalable resource monitoring system for large scale scientific computing data centers. Usually, there are limitations and overheads for keeping track of every computing nodes because of the huge number of computing nodes. So, this research proposes a layered summarizing techniques during collection of all system resource information. The technique results in improved scalability by reducing the amount of information at higher layer. Our prototype system which is implemented with web service is applicable with the HTML5 mobile web technology on smart devices.

• Convergence Security Journal
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• v.8 no.2
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• pp.35-40
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• 2008

Software failure time presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing. For data analysis of software reliability model, data scale tools of trend analysis are developed. The methods of trend analysis are arithmetic mean test and Laplace trend test. Trend analysis only offer information of outline content. In this paper, we discuss forecasting failure time case of failure time censoring. The used software failure time data for forecasting failure time is random number of Weibull distribution(shaper parameter 1, scale parameter 0.5), Using this data, we are proposed to ARIMA(AR(1)) and simulation method for forecasting failure time. The practical ARIMA method is presented.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.6
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• pp.637-647
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• 2019

In this study, we analyzed seismic behavior of reinforced earth retaining wall through the model test in order to characterize the behavior of reinforced earth retaining wall during earthquake. A scale model test was performed based on similitude ratio in accordance with law of similitude due to time and financial constraints on real scale modeling experiments. Seismic resistance characteristics of each seismic waves were analyzed by assessing the variations measured through excitation of the excited acceleration of 0.05g, 0.1g, 0.15g, and 0.2g. The results of this study, it would be important to obtain reasonable and abundant data on ground properties and seismic design in preparation for earthquakes when assessing the safety of block type reinforced earth retaining wall confined to model experiment. Acquisition of those data and systematic analytical techniques are considered likely to have a significant effect on the decrease of structure damage caused by earthquakes in Korea which has recently witnessed frequent occurrence of earthquakes.

• Applied Science and Convergence Technology
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• v.23 no.4
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• pp.169-178
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• 2014

Fluid model based numerical analysis is done to simulate a low damage etch back system for 20 nm scale semiconductor fabrication. Etch back should be done conformally with very high material selectivity. One possible mechanism is three steps: reactive radical generation, adsorption and thermal desorption. In this study, plasma generation and transport steps are analyzed by a commercial plasma modeling software package, CFD-ACE+. Ar + $CF_4$ ICP was used as a model and the effect of reactive gas inlet position was investigated in 2D and 3D. At 200~300 mTorr of gas pressure, separated gas inlet scheme is analyzed to work well and generated higher density of F and $F_2$ radicals in the lower chamber region while suppressing ions reach to the wafer by a double layer conducting barrier.

• Journal of Powder Materials
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• v.24 no.2
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• pp.153-163
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• 2017

Transparent conducting electrodes (TCEs) are attracting considerable attention as an important component for emerging optoelectronic applications such as liquid crystal displays, touch panels, and solar cells owing to their attractive combination of low resistivity (<$10^{-3}{\Omega}cm$) and high transparency (>80%) in the visible region. The solution-based process has unique properties of an easy fabrication procedure, scalability, and low cost compared to the conventional vacuum-based process and may prove to be a useful process for fabricating TCEs for future optoelectronic applications demanding large scale and flexibility. In this paper, we focus on the introduction of a solution-based process for TCEs. In addition, we consider the powder materials used to fabricate solution-based TCEs and strategies to improve their transparent conducting properties.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.161-168
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• 2024

As the size of big data models grows, distributed training is emerging as an essential element for large-scale machine learning tasks. In this paper, we propose ParamHub for distributed data training. During the training process, this agent utilizes the provided data to adjust various conditions of the model's parameters, such as the model structure, learning algorithm, hyperparameters, and bias, aiming to minimize the error between the model's predictions and the actual values. Furthermore, it operates autonomously, collecting and updating data in a distributed environment, thereby reducing the burden of load balancing that occurs in a centralized system. And Through communication between agents, resource management and learning processes can be coordinated, enabling efficient management of distributed data and resources. This approach enhances the scalability and stability of distributed machine learning systems while providing flexibility to be applied in various learning environments.

• Journal of information and communication convergence engineering
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• v.20 no.2
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• pp.73-78
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• 2022

Based on experimental measurements conducted on many different practical wireless communication systems, ambient noise has been shown to be decidedly non-Gaussian owing to impulsive phenomena. However, most multiuser detection techniques proposed thus far have considered Gaussian noise only. They may therefore suffer from a considerable performance loss in the presence of impulsive ambient noise. In this paper, we consider a large-scale multiuser multiple-input multiple-output system in the presence of non-Gaussian noise and propose a genetic algorithm (GA) based detector for large-dimensional multiuser signal detection. The proposed algorithm is more robust than linear multi-user detectors for non-Gaussian noise because it uses a multi-directional search to manipulate and maintain a population of potential solutions. Meanwhile, the proposed GA-based algorithm has a comparable complexity because it does not require any complicated computations (e.g., a matrix inverse or derivation). The simulation results show that the GA offers a performance gain over the linear minimum mean square error algorithm for both non-Gaussian and Gaussian noise.

• Proceedings of the KSRS Conference
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• v.2
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• pp.725-727
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• 2006

The development of GIS and Location-Based Services requires a high-level database that will be able to allow real-time access to moving objects for spatial and temporal operations. MODB.MM is able to meet these requirements quite adequately, providing operations with the abilities of acquiring, storing, and querying large-scale moving objects. It enables a dynamic and diverse query mechanism, including searches by region, trajectory, and temporal location of a large number of moving objects that may change their locations with time variation. Furthermore, MODB.MM is designed to allow for performance upon main memory and the system supports the migration on out-of-date data from main memory to disk. We define the particular query for truncation of moving objects data and design two migration methods so as to operate the main memory moving objects database system and file-based location storage system with.

• Journal of the Korean Physical Society
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• v.73 no.11
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• pp.1604-1611
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• 2018

Utilizing Sb-based bulk epilayers on large-scale low-cost substrates such as GaAs for fabricating infrared (IR) photodetectors is presently attracting significant attention worldwide. For this study, three sample series of $GaAs_xSb_{1-x}$, $In_{1-x}Ga_xSb$, and $InAs_xSb_{1-x}$ with different compositions were grown on semi-insulating GaAs substrates by using molecular beam epitaxy (MBE) and appropriate InAs quantum dots (QDs) as a defect-reduction buffer layer. Photoluminescence (PL) signals from these samples were observed over a wide IR wavelength range from $2{\mu}m$ to $12{\mu}m$ in agreement with the expected bandgap, including bowing effects. In particular, interband PL signals from $InAs_xSb_{1-x}$ and $In_{1-x}Ga_xSb$ samples even at room temperature show promising potential for IR photodetector applications.