• International Journal of Advanced Culture Technology
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• v.5 no.2
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• pp.19-25
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• 2017

The research is to identify social networks of problems that have an influence on the quality of ageing people's lives by using social network analysis, based on the premise that there are differences in networks of ageing problems in urban and rural areas. From analyzing network of ageing people's problems using NodeXL, vertices in the networks of both urban and rural areas are well-connected. For urban areas, financial poverty is the core problem related to the quality of life. It has direct connections with illness and health, family responsibility, housing, role loss in community, and employment, which have positive or negative interactions with the quality of older people's lives. For rural areas, on the other hand, role loss in community is the major problem. It has direct connections with the elderly abuse, financial poverty, leisure activity, divorce, isolation and loneliness from society, education, and suicide. As a result, the research shows that the problems of ageing people have strong linkages and interactive effects with a structure of network, and the networks are different depending on types of places for living.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.9
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• pp.36-43
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• 2019

Turning, a main machining process, is a widespread process in metal cutting industries. Many researchers have investigated the effects of process parameters on the machining process. In the turning process, input variables including cutting speed, feed, and depth of cut are generally used. Surface roughness and electric current consumption are used as output variables in this study. We construct a simulation model for the turning process using a neural network, which predicts the output values based on input values. In the neural network, obtaining the appropriate set of weights, which is called training, is crucial. In general, back propagation (BP) is widely used for training. In this study, techniques such as ant colony optimization (ACO) and particle swarm optimization (PSO) as well as BP were used to obtain the weights in the neural network. Particularly, two combined techniques of ACO_BP and PSO_BP were utilized for training the neural network. Finally, the performances of the two techniques are compared with each other.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.11
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• pp.1012-1018
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• 2016

We perform a electromagnetic analysis method for indirect effects of a high-conductive structure such as an aircraft exposed by lightning, by using the finite-difference time-domain(FDTD) method. The lightning waveform used to analyze indirect effects has low frequency spectrum and high-conductive materials such as aluminum and carbon fiber composite materials have very short skin depths, and thus, it requires large memory and long computation time using conventional three dimensional FDTD analysis method. We develop an efficient electromagnetic analysis method suitable for lightning and high-conductive structures. The developed analysis method is based on two dimensional FDTD and impedance network boundary condition(INBC) algorithms and we investigate the indirect effects on the structures exposed to lightning.

• Journal of the Korea Institute of Military Science and Technology
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• v.6 no.2
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• pp.73-82
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• 2003

For measurements and analysis of dielectric characteristics of planar slabs of microwave absorbing materials, I have applied a free-space method in the frequency range of 8~14 GHz. The measurement system for free-space method consists of transmit and receive antennas, mode transitions, precision coaxal cables, the network analyzer, and a computer Special Spot-focused horn lens antenna was used to eliminate diffraction effects. Diffraction effects at the edges of the sample are minimized by satisfying the condition for minimum transverse dimension of the plate and the beamwidth of the antennas at the focus. The time-domain gating feature of the network analyzer and the thru, reflect, and line(TRL) calibration technique were used to eliminate the effects of undesirable multiple reflections. The complex coefficients of reflection and transmission, $S_{11}$ and $S_{21}$, of planar samples were measured for standard materials such as Teflon, Rexolite$\textregistered$ 2200. The results were compared with existing measurement method. And I applied a free-space method for measurement to measure dielectric constants of some electromagnetic absorbing materials. Dielectric properties for the same samples were also measured with a 7mm coxial transmission line method for purposes of comparison with the free-space method.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.171-174
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• 2006

A large number of service providers in countries all over the world have established GNSS reference station networks in the last years and are using network software today to provide a correction stream to the user as a routine service. In current GNSS network processing, all the geometric related information such as ionospheric free carrier phase ambiguities from all stations and satellites, tropospheric effects, orbit errors, receiver and satellite clock errors are estimated in one centralized Kalman filter. Although this approach provides an optimal solution to the estimation problem, however, the processing time increases cubically with the number of reference stations in the network. Until now one single Personal Computer with Pentium 3.06 GHz CPU can only process data from a network consisting of no more than 50 stations in real time. In order to process data for larger networks in real time and to lower the computational load, a federated filter approach can be considered. The main benefit of this approach is that each local filter runs with reduced number of states and the computation time for the whole system increases only linearly with the number of local sensors, thus significantly reduces the computational load compared to the centralized filter approach. This paper presents the technical aspect and performance analysis of the federated filter approach. Test results show that for a network of 100 reference stations, with the centralized approach, the network processing including ionospheric modeling and network ambiguity fixing needs approximately 60 hours to process 24 hours network data in a 3.06 GHz computer, which means it is impossible to run this network in real time. With the federated filter approach, only less than 1 hour is needed, 66 times faster than the centralized filter approach. The availability and reliability of network processing remain at the same high level.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.2
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• pp.867-872
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• 2016

Background: Esophageal cancer is one of the most serious malignancies. Due to the aggressive nature of this cancer, the prognosis is poor. A network meta-analysis with simultaneous comparison of multiple treatments can help determine better treatment options that have higher effects on overall survival of patients with lower adverse events. The aim of this review is to simultaneously compare efficacy and adverse events of treatment interventions for esophageal cancer. Materials and Methods: In this review, only randomized control trials (RCT) will be considered for network meta-analysis. All international electronic databases including Medline, Web of Sciences, Scopus, Cochran's library, EMBASE and Cancerlit will be searched to find randomized control trials which compared two or more treatment interventions for esophageal cancer. A network plot will be drawn for visual representation of all available treatment interventions. Bayesian approach will be used to combine the direct and indirect evidence. Treatment effects (e.g. hazard ratio for time to event outcomes, risk ratio for binary outcomes, and rate ratio for count outcomes with 95% credible interval) will be reported. Moreover, cumulative probability of the treatment ranks will be reported using the surface under the cumulative ranking (SUCRA) graphs. Consistency assumption will be assessed by the loop-specific and design-by-treatment interaction approaches. Conclusions: The results of this study may be helpful for the patients, clinicians and health policy makers in selecting treatments that have the best effect on survival and lowest adverse events.

• Journal of Digital Convergence
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• v.15 no.6
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• pp.29-38
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• 2017

The purpose of this study was to examine the effects of users' organization-public relationship of the donation activities of corporate via social network service on corporate image and reputation focused on social network service users. The subjects were 228 SNS users selected. The data were analyzed by the correlation analysis, reliability analysis and structural equation modeling analysis using SPSS 21 and AMOS 21 program. The results were as follow. First, Organization-public relationships influenced positively on corporate image. Second, Organization-public relationships influenced positively on corporate reputation. Third, Corporate image influenced positively on corporate reputation. These results will contribute to develop a marketing strategy via social network service of corporate.

• Journal of Digital Contents Society
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• v.14 no.2
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• pp.223-233
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• 2013

This paper studied the effects of service quality and system quality that affect customer's satisfaction and continued usage intention regarding mobile network conditions. The hypotheses and research models were completed using research factors of service quality(reactivity, empathy) and system quality(connectivity, ease of use, channel-mobility) borrowed from previous studies on DMB and IPTV. The hypotheses and research models were verified through experiments and surveys. The key finding showed that customer's expectation on service quality and system quality under fast network(Wifi) was higher than that of under slow network(3G). Furthermore, it showed that users react more sensitive to service quality than to system quality such as network speed. Based on the results, this study has the implication for expanding the understanding of the factors used in previous DMB and IPTV studies by applying them in N-screen domain.

• Atmosphere
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• v.29 no.2
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• pp.183-196
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• 2019

High-quality and high-resolution meteorological information is essential to reduce damages due to disastrous weather phenomena such as flash flood, strong wind, and heat/cold waves. There are many meteorological observation stations operated by Korea Meteorological Administration (KMA) in Seoul Metropolitan Area (SMA). Nonetheless, they are still not enough to represent small-scale weather phenomena like convective storm cells due to its poor resolution, especially over urban areas with high-rise buildings and complex land use. In this study, feasibilities to use additional pre-existing networks (e.g., operated by local government and private company) are tested by investigating the effects of network density on the gridded horizontal distribution of two meteorological variables (temperature and precipitation). Two heat wave event days and two precipitation events are chosen, respectively. And the automatic weather station (AWS) networks operated by KMA, local-government, and SKTechX in Incheon area are used. It is found that as network density increases, correlation coefficients between the interpolated values with a horizontal resolution of 350 m and observed data also become large. The range of correlation coefficients with respect to the network density shows large in nighttime rather than in daytime for temperature. While, the range does not depend on the time of day, but on the precipitation type and horizontal distribution of convection cells. This study suggests that temperature and precipitation sensors should be added at points with large horizontal inhomogeneity of land use or topography to represent the horizontal features with a resolution higher than 350 m.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.1
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• pp.68-74
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• 2008

In this paper, a novel neural fuzzy control method is proposed to control nonlinear systems. A standard PD-like fuzzy controller is designed and used as a main controller for the system. Then a neural network controller is added to the reference trajectories to form a neural-fuzzy control structure and used to compensate for nonlinear effects. Two neural-fuzzy control schemes based on two well-known neural network control schemes, the feedback error learning scheme and the reference compensation technique scheme as well as the standard PD-like fuzzy control are studied. Those schemes are tested to control the angle and the position of the inverted pendulum and their performances are compared.