• Journal of Magnetics
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• v.14 no.2
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• pp.66-70
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• 2009

The dynamic magneto-mechanical behaviors in a type of iron-nickel-based ferromagnetic alloy with constant elasticity were investigated as a function of both the DC bias magnetic field ($H_{dc}$) and the frequency. The rectangular plate-like samples were excited to vibrate at a half-wavelength, longitudinal resonance by an AC magnetic field superimposed with various $H_{dc}$. The experimental results found that the strain coefficient at resonance reached 819.34 nm/A and the effective mechanical quality factor ($Q_m$) was greater than 2000. The ratio of the maximum variation of the Young's modulus over $H_{dc}$ to the value of the Young's modulus at a zero bias field was only ${\sim}0.83%o$ because of the so-called constant elasticity. The resonant strain coefficients and $Q_m$ are strongly dependent on $H_{dc}$, which indicates a promising potential for use in DC and quasistatic magnetic field sensing.

• Journal of Radiation Protection and Research
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• v.47 no.3
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• pp.158-166
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• 2022

Background: The effects of radiation on the health of radiation workers who are constantly susceptible to occupational exposure must be assessed based on an accurate and reliable reconstruction of organ-absorbed doses that can be calculated using personal dosimeter readings measured as H_p(10) and dose conversion coefficients. However, the data used in the dose reconstruction contain significant biases arising from the lack of reality and could result in an inaccurate measure of organ-absorbed doses. Therefore, this study quantified the biases involved in organ dose reconstruction and calculated the bias-corrected H_p(10)-to-organ-absorbed dose coefficients for the use in epidemiological studies of Korean radiation workers. Materials and Methods: Two major biases were considered: (a) the bias in H_p(10) arising from the difference between the dosimeter calibration geometry and the actual exposure geometry, and (b) the bias in air kerma-to-H_p(10) conversion coefficients resulting from geometric differences between the human body and slab phantom. The biases were quantified by implementing personal dosimeters on the slab and human phantoms coupled with a Monte Carlo method and considered to calculate the bias-corrected H_p(10)-to-organ-absorbed dose conversion coefficients. Results and Discussion: The bias in H_p(10) was significant for large incident angles and low energies (e.g., 0.32 for right lateral at 218 keV), whereas the bias in dose coefficients was significant for the posteroanterior (PA) geometry only (e.g., 0.79 at 218 keV). The bias-corrected H_p(10)-to-organ-absorbed dose conversion coefficients derived in this study were up to 3.09- fold greater than those from the International Commission on Radiological Protection publications without considering the biases. Conclusion: The obtained results will aid future studies in assessing the health effects of occupational exposure of Korean radiation workers. The bias-corrected dose coefficients of this study can be used to calculate organ doses for Korean radiation workers based on personal dose records.

• Fashion & Textile Research Journal
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• v.11 no.3
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• pp.453-459
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• 2009

The purpose of this study was to provide the basic knowledge to determine the proper seam finish according to the design of sewing products. Four seam finishes(no seam finishes, over-edged seam finishes, turned-and-stitched seam finishes, and bias-bound seam finishes) were constructed with seams in warp, weft and bias directions of the fabric. Using a drape measurement system involving two 18cm diameter supporting disks and a digital camera, the images of draped specimens were captured and processed. Drape behavior was evaluated in terms of drape coefficient, node number, and drape profile. Drape coefficients of the fabrics increased with seam formation and varied by the seam finishes, however no significant differences in drape coefficients by the seam finishes were observed on the heavier fabric. Node numbers of heavier fabric were more deeply affected by the seam finishes than those of lighter fabric. The specimens with turned-and-stitched seam finishes and bias-bound seam finishes showed significantly smaller node numbers compared to the specimens with no seam finishes and over-edged seam finishes on heavier fabric. The length of the seamed part showed positive correlation with the weight of the specimens and negative correlation with the number of nodes in each seam direction. The maximum length of all draped specimens was found in the same direction as the seam direction. In the case of the lighter fabric, the seam and the seam finish had a great influence on the shape of the draped profile.

• Journal of Korea Water Resources Association
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• v.46 no.3
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• pp.229-243
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• 2013

Hydrological simulation Program-Fortran (HSPF) model was used to simulate streamflow and snow depth at Pyengchang watershed. The selected Global Climate Models (GCMs) provided by the Coupled Model Intercomparision Project Phase 3 (CMIP3) were utilized to evaluate streamflow and snow depth driven by future climate scenarios, including A1, A1B, and B1. Bias-correlation and temporal downscaling processes have been performed to minimize systematic errors between GCMs and HSPF. Based on simulated monthly streamflow and snow depth after calibration, the results indicate that HSPF performs well. The correlation coefficient between the observed and simulated monthly streamflow is 0.94. Snow depth simulations also show high correlation coefficient, which is 0.91. The results indicate that snow depth in 2018 at Pyongchang winter olympic venues will decrease by 17.62%, 9.38%, and 7.25% in January, February, and March respectively, based on streamflow realizations induced by all GCMs ensembles.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.19 no.5
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• pp.467-475
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• 2007

This study compared the sea surface wind pattern between model results from KMA operational model (RDAPS) and observational results from QuikSCAT in the 2005-2006 year. The mean spatial distributions of sea surface wind show the prominent seasonal patterns of summer and winter season adjacent to Korean Peninsular. The statistical analysis also shows well seasonal variation of sea surface wind patterns between model and observation results. The BIAS value represents less than -0.5 m/s and -1 m/s in summer and winter seasons, respectively. The spatially averaged correlation coefficient shows larger than 0.7 and 0.8 in summer and winter seasons, respectively. The correlation coefficient of winter season shows higher value than that of summer season in the comparison between model and observation. This results show that the RDAPS model simulate well strong sea surface wind in winter season rather than weak sea surface wind in summer season.

• KSTLE International Journal
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• v.9 no.1_2
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• pp.26-30
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• 2008

This study examined the surface modification characteristics of NBR using sealing in automobile. Surfaces of NBR were modified by RF power Ar plasma treatment. In experiment, pressure, flux, temperature were fixed and RF bias voltage. Treatment time was changed. In friction test, we used PTFE grease. After modification, surfaces of NBR showed many grooves, hydrophilic functional groups, and lipophilic functional groups. As increasing treating voltage and time, the amount of them was increased. And wetting angle and friction coefficient was decreased with increasing treating voltage and time. However, the pattern of changing friction coefficient was not fixed.

• Proceedings of the KIPE Conference
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• 2013.07a
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• pp.311-312
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• 2013

본 논문에서는 자성체의 직류중첩 (DC-Bias)특성이 영향을 미치는 공진형 컨버터의 효율을 계산하기 위한 시뮬레이션을 구성한다. 이를 위해 PSIM의 saturable core를 이용하여 core coefficient를 실제 설계 사양과 동일하게 적용 및 모델링한다. 시뮬레이션 결과를 통해, 자성체에 흐르는 전류의 크기에 따라 변화하는 투자율이 공진형 컨버터의 동작 및 효율에 미치는 영향을 분석한다.

• The Korean Journal of Applied Statistics
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• v.17 no.3
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• pp.459-473
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• 2004

It has well known that an exhaustive search algorithm suggested by Breiman et. a1.(1984) has a trend to select the variable having relatively many possible splits as an splitting rule. We propose an algorithm to overcome this variable selection bias problem and then construct unbiased regression trees based on the algorithm. The proposed algorithm runs two steps of selecting a split variable and determining a split rule for binary split based on the split variable. Simulation studies were performed to compare the proposed algorithm with Breiman et a1.(1984)'s CART(Classification and Regression Tree) in terms of degree of variable selection bias, variable selection power, and MSE(Mean Squared Error). Also, we illustrate the proposed algorithm with real data sets.

• Journal of Advanced Marine Engineering and Technology
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• v.30 no.8
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• pp.901-906
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• 2006

In this paper, the power amplifier using active bias circuits for LDMOS(Lateral Diffused Metal Oxide Semiconductor) MRF-21180 is designed and fabricated. According to change the temperature, the gate voltage of LDMOS is controlled by the fabricated active bias circuits which is made of PNP transistor to suppress drain current. The driving amplifier using MRF-21125 and MRF-21060 is made to drive the LDMOS MRF-21180 power amplifier. The variation of current consumption in the fabricated 60 watt power amplifier has an excellent characteristics of less than 0.1 A, whereas a passive biasing circuit dissipates more than 0.5 A. The implemented power amplifier has the gain over 9 dB, the gain flatness of less than $\pm$0.1 dB and input and output return loss of less than -6 dB over the frequency range 2.11 $\sim$ 2.17 GHz. The DC operation point of this power amplifier at temperature variation 0 $^{\circ}C$ to 60 $^{\circ}C$ is fixed by active bias circuit.

• The Journal of Natural Sciences
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• v.8 no.1
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• pp.5-15
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• 1995

The equation error formulation in the adaptive IIR filtering provides convergence to a global minimum regardless a local minimum with a large stability margin. However, the equation error formulation suffers from the bias in the coefficient estimates. In this paper, a new algorithm, which does not require a prespecification of the noise variance, is proposed for the equation error formulation. This algorithm is based on the equation error smoothing and provides an unbiased parameter estimate in the presence of white noise. Through simulations, it is demonstrated that the algorithm eliminates the bias in the parameter estimate while retaining good properties of the equation error formulation such as fast convergence speed and the large stability margin.