• Journal of the Korean Home Economics Association
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• v.36 no.12
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• pp.25-41
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• 1998

HALS(Hypermedia-Aided Learning System) is very useful computer networking educational system in high information society, and was developed by Kyungwon University. This system has three characteristics; 1) face to face learning, 2) ultra high speed information networing, 3) web based hypermedia courseware. So, the purpose of this study is to try the application to pre-parent eucational program(session 4 : becoming parents through the experience of pregnancy and childbirth). For this purpose it is described the definition and characteristics of HALS. Next, it is represented the model of pre-parent educational program applied to HALS and the pictures of the session 4 (initial window, help function window, etc).

• Journal of Welding and Joining
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• v.32 no.2
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• pp.43-47
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• 2014

Famous artificial neural network (ANN) is applied to predict proper process window of arc welding. Target weldment is variously combined lap joint fillet welding of automotive steel plates. ANN's system variable such as number of hidden layers, perceptrons and transfer function are carefully selected through case by case test. Input variables are welding condition and steel plate combination, for example, welding machine type, shield gas composition, current, speed and strength, thickness of base material. The number of each input variable referred in welding experiment is counted and provided to make it possible to presume the qualitative precision and limit of prediction. One of experimental process windows is excluded for predictability estimation and the rest are applied for neural network training. As expected from basic ANN theory, experimental condition composed of frequently referred input variables showed relatively more precise prediction while rarely referred set showed poorer result. As conclusion, application of ANN to arc welding process window derivation showed comparatively practical feasibility while it still needs more training for higher precision.

• ETRI Journal
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• v.16 no.1
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• pp.17-34
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• 1994

In this paper, we present an architecture of the constant false alarm rate (CFAR) detector called the generalized order statistics (GOS) CFAR detector, which covers various order statistics (OS) and cell-averaging (CA) CFAR detectors as special cases. For the proposed GOS CFAR detector, we obtain unified formulas for the false alarm and detection probabilities. By properly choosing coefficients of the GOS CFAR detector, one can utilize any combination of ordered samples to estimate the background noise level. Thus, if we use a reference window of size N, we can realize $(2^N-1)$ kinds of CFAR processors and obtain their performances from the unified formulas. Some examples are the CA, the OS, the censored mean level, and the trimmed mean CFAR detectors. As an application of the GOS CFAR detector to multiple target detection, we propose an algorithm called the adaptive mean level detector, which censors adaptively the interfering target returns in a reference window.

• Nuclear Engineering and Technology
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• v.49 no.6
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• pp.1172-1180
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• 2017

The application of Monte Carlo (MC) to large-scale fixed-source problems has recently become possible with new hybrid methods that automate generation of parameters for variance reduction techniques. Two common variance reduction techniques, weight windows and source biasing, have been automated and popularized by the consistent adjoint-driven importance sampling (CADIS) method. This method uses the adjoint solution from an inexpensive deterministic calculation to define a consistent set of weight windows and source particles for a subsequent MC calculation. One of the motivations for source consistency is to avoid the splitting or rouletting of particles at birth, which requires computational resources. However, it is not always possible or desirable to implement such consistency, which results in inconsistent source biasing. This paper develops an original framework that mathematically expresses the coupling of the weight window and source biasing techniques, allowing the authors to explore the impact of inconsistent source sampling on the variance of MC results. A numerical experiment supports this new framework and suggests that certain classes of problems may be relatively insensitive to inconsistent source sampling schemes with moderate levels of splitting and rouletting.

• Journal of the Semiconductor & Display Technology
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• v.17 no.3
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• pp.108-112
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• 2018

In this paper, a respiration measurement method using FMCW signal for off-the-shelf smartphone is presented and investigated. The proposed algorithm transmits FMCW signal periodically instead of transmitting continuously so that one can reduce the power consumption from speaker in smartphone and the algorithm complexity. In order to eliminate the clicking noise generated when transmitting FMCW signal, Tukey window with ${\alpha}=0.01$ is applied to prevent the noise from being heard. An application program for Android OS which can transmit FMCW signal through speaker and record the reflected signals through MIC has been developed. Since the total duration of the signal transmission is set to 20msec per 1 second for the experiments, the power consumption can be decreased by 80% compared to the continuous transmission. It was confirmed that the clicking noise is inaudible as long as a smartphone is located at more than 10cm from ears. In the experiments on a sleeping child, the breathing signal of about 0.27Hz was measured.

• Communications for Statistical Applications and Methods
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• v.31 no.1
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• pp.87-104
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• 2024

Most functional magnetic resonance imaging (fMRI) studies in resting state have assumed that the functional connectivity (FC) between time series from distinct brain regions is constant. However, increased interest has recently been in quantifying possible dynamic changes in FC during fMRI experiments. FC study may provide insight into the fundamental workings of brain networks to brain activity. In this work, we focus on the specific problem of estimating the dynamic behavior of pairwise correlations between time courses extracted from two different brain regions. We compare the sliding-window techniques such as moving average (MA) and exponentially weighted moving average (EWMA), dynamic causality with vector autoregressive (VAR) model, dynamic conditional correlation (DCC) based on volatility, and the proposed alternative methods to use differencing and recursive residuals. We investigate the properties of those techniques in a series of simulation studies. We also provide an application with major depressive disorder (MDD) patient fMRI data to demonstrate studying dynamic correlations.

• The Journal of the Korea Contents Association
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• v.8 no.12
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• pp.214-221
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• 2008

Terrestrial magnetism has left traces through residues such as fossils of the terrestrial magnetism as time went by. An analysis of archaeological terrestrial magnetism is an estimation of dates of archaeological remains where baked earth is exposed by measuring the change of the past terrestrial magnetism through thermo-remnant magnetization of baked earth. This paper attempts to apply an analysis of the archaeological terrestrial magnetism to archaeological remains using fourteen soil samples extracted from a charcoal kiln with side window located at the Area Ⅰ of Maegokdong. The date of A.D.440${\pm}$15 the analysis of archaeological terrestrial magnetism came up with gives solid evidence, while an archeological chronicle used arrangements of surrounding artifacts because of the absence of remains and assumed uncertainly that a charcoal kiln with side window was from the three kingdom periods. This analysis of archaeological terrestrial magnetism has come to anchor as a main natural scientific analysis because it relatively easily removes pollutants and comes up with highly reliable results owing to its considerably narrow error tolerance of assumed dates.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.27 no.4
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• pp.203-208
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• 2014

In this study, Sputtering method was used to grow Al-dopes ZnO films on a CIGS absorber layer, in order to examine the effect of TCO on properties of CIGS solar cell devices. Structural, electrical and optical properties were investigated by varied thickness of Al-dopes ZnO films. Also, relation to the application as a window layer in CIGS thin film solar cell were studied. It was found that the electrical and structural properties of ZnO:Al film improved with increasing its thickness. However, the optical properties degraded. Jsc of the fabricated CIGS based solar cells was significantly influenced by the variation of the ZnO:Al window layer thickness. Because ZnO:Al window layer is one of the Rs factors in CIGS solar cell. Rs has the biggest influence on efficiency characteristic. In order to obtain high efficiency of CIGS solar cell, ZnO:Al window layer should be fabricated with electrically and optically optimized.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.126-129
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• 2007

Recently the use of wireless network increases according to it solves the hand-off and with path loss, pading, noise etc of wireless network the research for transmission error improvement is developed. TCP and SCTP of standard where it guarantees the reliability of wire network apply in wireless network the congestion control, flow control mechanism used it decreases the efficiency of data transfer throughputs. In this paper, It mixes SCTP and SNOOP for SCTP apply on wireless network, to improve BS(Basic Station) operation processes when the transmission error occurs in wireless network. BS send ZWP(Zero Window Probe) to MN(Mobile Node) when the transmission error occurs so, check path and status and update RWND and error status checked. It selects the new path, send ZWA(Zero Window Advertisement) to FH(Fixed Host) and the prevents call to congestion control or flow control and it does to make wait status standing. Continuously of data transfer after the connection of wireless network is stabilized, it make increase about 10% the transmission throughput of data.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.8 no.4
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• pp.110-121
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• 2009

It is essential to embed product quality in the design process to win the global competition. Many components found in many products including automobiles and electronic devices are fabricated using sheet metal forming processes. Wrinkle and fracture are two types of defects frequently found in the sheet metal forming process. Reducing such defects is a hard problem as they are affected by many uncontrollable factors. Attempts to solve the problem based on traditional deterministic optimization theories are often led to failures. Furthermore, the wrinkle and fracture are conflicting defects in such a way that reducing one defect leads to increasing the other. Hence, it is a difficult task to reduce both of them at the same time. In this research, a new design method for reducing the rates of conflicting defects under uncontrollable factors is presented by using operating window and a sequential search procedure. A new SN ratio is proposed to overcome the problems of a traditional SN ratio used in the operating window technique. The method is applied to optimizing the robust design of a sheet metal forming process. To show the effectiveness of the proposed method, a comparison is made between the traditional and the proposed methods using simulation software, applied to a design of particular sheet metal forming process problem. The results show that the proposed method always gives a more robust design that is less sensitive to noises than the traditional method.