• Transactions on Control, Automation and Systems Engineering
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• v.3 no.3
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• pp.146-151
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• 2001

Optical disk drive has excellent advantage of random accessibility of which performance is measured by access time. However, due to the increased rotational velocity of the disk and constraints of mechanical structure, two-stage seek algorithm which executes coarse and fine seeks sequentially has been adopted in most commercial optical disk drives. Although the laser spot is moved to a target track by a single seek operation, the limited operation range of the fine actuator restricts the application of the fine seek algorithm below a few hundreds of tracks. Especially, excessive movement of the objective lens causes a failure in generation of track-cross pulse and results in an unstable seek operation. In this paper, a new control algorithm for extending the fine seek range is proposed with an appropriate control structure. The coarse actuator is utilized to reduce the misalignment between the objective lens and the laser beam axis, and the fine actuator is controlled to follow the reference velocity trajectory. The proposed algorithm is applied to a CD-ROM drive to show its feasibility and some experimental results are presented.

• Computers and Concrete
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• v.21 no.1
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• pp.87-94
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• 2018

This paper presents the results of an experimental study to investigate the influences of high temperatures on the mechanical properties of concrete containing recycled fine aggregate. A total of 150 concrete prisms ($100{\times}100{\times}300mm$) and 150 concrete cubes ($100{\times}100{\times}100mm$) are cast and heated under five different temperatures ($20^{\circ}C$, $200^{\circ}C$, $400^{\circ}C$, $600^{\circ}C$, $800^{\circ}C$) for test. The results show that the mass loss, compressive strength, elastic modulus, splitting tensile strength of concrete specimens containing recycled fine aggregate decline significantly as the temperature rise. At the same temperature, the compressive strength, splitting tensile strength, elastic modulus of concrete specimens containing recycled coarse aggregate and recycled fine aggregate (RHC) is lower than that of concrete specimens containing natural coarse aggregate and recycled fine aggregate (RFC). The shape of stress-strain curves of concrete specimens at different temperatures is different, and the shape of that become flatter as the temperature rises. Normal concrete has better energy absorption capacity than concrete containing recycled fine aggregate.

• Korean Journal of Food Science and Technology
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• v.28 no.3
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• pp.506-513
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• 1996

Soybean hull was microparticulated at cut-off wheel speed of 9,000 rpm and air-classified into fine and coarse fraction at air classifying wheel speeds (ACWS) of 10.000, 15,000 and 20,000 rpm. respectively. Proximate analysis of the coarse and fine fractions of the microparticulated/air-classified soybean hull showed that ash, protein and lipid were enriched in the coarse fractions and carbohydrates in the fine fraction. Dietary fiber were enriched in coarse fractions and dietary fiber and dietary fiber content increased with decreasing ACWS. Mean particle size of fine fractions ranged from $3.1{\mu}m\;to\;5.5{\mu}m$ that of coarse fractions ranged from $9.9{\mu}m\;to\;20.0{\mu}m$ and both increased with decreasing ACWS. The particles were mostly oval-shaped regardless of the fractions. Generally the fraction of low ACWS showed higher viscosity. In water holding capacity, oil absorption and emulsion capacity, there was significant difference between coarse and fine fractions while there was no significant difference as a function of different ACWS. Oil absorption of flying batter was decreased significantly in the fraction of ACWS 15,000. when cakes and cooking were prepared partially substituted with soybean hull fraction, there was no significant changes on their physical and sensory properties up to 10% substitution.

• Asian Journal of Atmospheric Environment
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• v.11 no.4
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• pp.313-321
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• 2017

$PM_{10}$ and $PM_{2.5}$ were collected at the Gosan Site on Jeju Island from 2013 to 2015, and their ionic and elemental species were analyzed to examine the variations in their chemical compositional characteristics related to different meteorological conditions. Concentrations of nss-$SO_4{^{2-}}$ and $NH_4{^+}$ were respectively 6.5 and 4.7 times higher in the fine particle mode ($PM_{2.5}$) compared to the coarse particle mode ($PM_{10-2.5}$), however $NO_3{^-}$ concentrations were 2.4 times higher in the coarse mode compared to the fine particle mode. During Asian dust days, the concentrations of nss-$Ca^{2+}$ and $NO_3{^-}$ increased to 8.2 and 5.0 times higher in $PM_{10}$, and 3.5 and 6.0 times higher in $PM_{2.5}$, respectively. During haze days, the concentrations of secondary pollutants increased by 3.1-4.7 and 3.2-7.9 in $PM_{10}$ and $PM_{2.5}$, respectively, and they were, respectively, 1.2-2.1 and 0.9-2.1 times higher on mist days. The aerosols were acidified largely by sulfuric and nitric acids, and neutralized mainly by ammonia in the fine particle mode during the haze days, but neutralized by calcium carbonate in coarse particle mode during the Asian dust days. Clustered back trajectory analysis showed that concentrations of nss-$SO_4{^{2-}}$, $NO_3{^-}$, and $NH_4{^+}$ were relatively high when air masses travelled from China.

• Journal of KIISE:Software and Applications
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• v.34 no.9
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• pp.857-868
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• 2007

The good classifier ensemble should have a high complementarity among classifiers in order to produce a high recognition rate and its size is small in order to be efficient. This paper proposes a classifier ensemble selection algorithm with coarse-to-fine stages. for the algorithm to be successful, the original classifier pool should be sufficiently diverse. This paper produces a large classifier pool by combining several different classification algorithms and lots of feature subsets. The aim of the coarse selection is to reduce the size of classifier pool with little sacrifice of recognition performance. The fine selection finds near-optimal ensemble using genetic algorithms. A hybrid genetic algorithm with improved searching capability is also proposed. The experimentation uses the worldwide handwritten numeral databases. The results showed that the proposed algorithm is superior to the conventional ones.

• Journal of Korean Society for Atmospheric Environment
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• v.18 no.E4
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• pp.203-213
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• 2002

Receptor modeling is one of statistical methods to achieve reasonable air pollution strategies. In order to maintain and manage ambient air quality, it is necessary to identify sources and to apportion its sources for ambient particulate matters. The main purpose of the study was to survey seasonal trends of inorganic elements in the coarse and fine particles. Second, this study has attempted emission sources qualitatively by a receptor method, the PMF mo-del. After that. both PMF (positive matrix factorization) model and TTFA (target transformation factor analysis) model were applied to compare and to estimate mass contribution of coarse and fine particle sources at the receptor. A total of 138 sets of samples was collected from 1989 to 1996 by a low volume cascade impactor with 9 size fraction stages at Kyung Hee University in Korea. Sixteen chemical species (Si, Ca, Fe, K, Pb, Na, Zn, Mg, Ba, Ni, V, Mn, Cr, Br, Cu. Co) were characterized by XRF. The study result showed that the weighted arithmetic mean of coarse and fine particles were 51.3 and 54.4 $\mu\textrm{g}$/㎥, respectively. Contribution of both particle fractions were esti-mated using TTFA and PMF models. The number of estimated sources was seven according to TTFA model and 8 according to PMF model. Comparison of TTFA and PMF revealed that both methodologies exhibited similar trends in their contribution pattern. However, large differences between contributions were observed in some sour-ces. The results of this study may help to suggest control strategies in local countries where known source profiles do not exist.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1883-1886
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• 2005

In this paper, a decoupled dual servo (DDS) stage for ultra-precision scanning system with large working range is introduced. In general, dual servo systems consist of a fine stage for short range and a coarse stage for long range. The proposed DDS also consists of a $XY\theta$ fine stage for handling and carrying workpieces and one axis coarse stage. Its coarse stage consists of air bearing guide system and a coreless linear motor with force ripple. The fine has four voice coil motors(VCM) as its actuator. According to a VCM's nature, there are no mechanical connections between coils and magnetic circuits. Moreover, VCM doesn't have force ripples due to imperfections of commutation components of linear motor systems - currents and flux densities. However, due to the VCM's mechanical constraints the working range of the fine is about $25mm^2$. To break that hurdle, the coarse stage with linear motors is used to move the fine about 500mm. Because of the above reasons, the proposed DDS can achieve higher precision scanning than other stages with only one servo. With MATLAB's Sequential Quadratic Programming (SQP), the VCMs are optimally designed for the highest force under conditions and constraints such as thermal dissipations due to its coil, its size, and so on. And for their movements without any frictions, guide systems of the DDS are composed of air bearings. To get precisely their positions, a linear scale with 5nm resolution are used for the coarse stage's motion and three plane mirror laser interferometers with 5nm for the fine's $XY\theta$ motions. With them, on scanning the two stages have same trajectories. The control algorithm is named Parallel method. The embodied ultra-precision scanning system has sub 100nm following error and in-positioning stability.

• Journal of Korean Society for Atmospheric Environment
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• v.32 no.1
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• pp.67-81
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• 2016

In order to examine the variation characteristics of chemical compositions in accordance with the different meteorological conditions, $PM_{10}$ and $PM_{2.5}$ were collected at Gosan site of Jeju Island in 2014, and then their ionic and elemental species were analyzed. The concentrations of nss-$SO{_4}^{2-}$ and $NH_4{^+}$ were respectively 4.3 and 3.3 times higher in fine particle mode ($PM_{2.5}$) compared to coarse particle mode ($PM_{10-2.5}$), however $NO_3{^-}$ concentration was 1.6 times higher in coarse mode compared to fine particle mode. During Asian dust days, the concentrations of nss-$Ca^{2+}$ and $NO_3{^-}$ increased highly as 7.7 and 4.5 times in coarse particle mode, and 3.0 and 4.9 times higher in fine particles, respectively. Especially, the concentrations of the crustal species (Al, Fe, Ca, K, Mn, Ba, Sr, etc.) indicated a noticeable increase during the Asian dust days. For the haze days, the concentrations of secondary pollutants increased 2.2~2.7 and 2.9~6.0 times in coarse and fine particles, respectively, and they were 0.8~1.1 and 1.8~2.4 times, respectively, during the mist days. The aerosols were acidified largely by sulfuric and nitric acids, and neutralized mainly by ammonia in fine particle mode during the haze days, but neutralized by calcium carbonate in coarse particle mode during the Asian dust days. The clustered back trajectory analysis showed that the concentrations of nss-$SO{_4}^{2-}$, $NO_3{^-}$, and $NH_4{^+}$ were relatively high when the inflow pathway of air mass was from the southern part of China.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.22 no.1
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• pp.13-20
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• 2010

Airborne particulate matters have two modes of size distributions of coarse mode and fine mode. The coarse mode which is formed by break down mechanism of large particles has a peak around the $100\;{\mu}m$, and the fine mode formed by condensation and build up mechanism of evaporated vapors has a peak at several ${\mu}m$. The coarse mode particles can be removed easily by conventional collecting equipments such as a cyclone, an electrostatic precipitator, and a filter, however the fine mode particles can not be collected easily. Usually the fine mode particles are generated in the high temperature conditions especially through boilers and incinerators, so the high efficient and temperature filter is essential for the filtration. In this study, a nano ceramic filter for the removal of fine particles in the high temperature is developed and tested for several characteristics. The nano ceramic filter has double layer of micro and nano structure and the pressure drop and the filtration efficiency for $0.31\;{\mu}m$ at 3 cm/s are 15.45 mmAq, and 96.75%, respectively. The thermal conductivity is $0.038\;W/m{\cdot}K$, and the coefficient of water vapor permeability is $3.63\;g/m^2{\cdot}h{\cdot}mmHg$. It is considered that the sensible heat exchange rate is very poor because the low thermal conductivity but it has high potential to exchange latent heat.

• Korean Journal of Remote Sensing
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• v.33 no.1
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• pp.25-35
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• 2017

Spatial downscaling with fine resolution auxiliary variables has been widely applied to predict precipitation at fine resolution from coarse resolution satellite-based precipitation products. The spatial downscaling framework is usually based on the decomposition of precipitation values into trend and residual components. The fine resolution auxiliary variables contribute to the estimation of the trend components. The main focus of this study is on quantitative analysis of impacts of trend component estimates on predictive performance in spatial downscaling. Two regression models were considered to estimate the trend components: multiple linear regression (MLR) and geographically weighted regression (GWR). After estimating the trend components using the two models,residual components were predicted at fine resolution grids using area-to-point kriging. Finally, the sum of the trend and residual components were considered as downscaling results. From the downscaling experiments with time-series Tropical Rainfall Measuring Mission (TRMM) 3B43 precipitation data, MLR-based downscaling showed the similar or even better predictive performance, compared with GWR-based downscaling with very high explanatory power. Despite very high explanatory power of GWR, the relationships quantified from TRMM precipitation data with errors and the auxiliary variables at coarse resolution may exaggerate the errors in the trend components at fine resolution. As a result, the errors attached to the trend estimates greatly affected the predictive performance. These results indicate that any regression model with high explanatory power does not always improve predictive performance due to intrinsic errors of the input coarse resolution data. Thus, it is suggested that the explanatory power of trend estimation models alone cannot be always used for the selection of an optimal model in spatial downscaling with fine resolution auxiliary variables.