• The Korean Journal of Food And Nutrition
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• v.30 no.4
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• pp.635-643
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• 2017

The properties of rice were studied, and 8 rice flour cultivars were used to study the effect of particle size on the physicochemical properties, color value, RVA viscosities, water absorption index (WAI), and water solubility index (WSI) of rice flours. The mean particle size by the 3 particle size classification of 150 mesh, 200 mesh, and 250 mesh was, $90.75{\mu}m$, $60.73{\mu}m$, $39.94{\mu}m$, respectively. Thai rice had the highest amylose content and Samkwang rice had the lowest amylose content. Protein content of rice flours prepared was decreased as the particle size of rice flour decreased. In terms of color values, the L-value and the a-value of rice flour were increased as the particle size of rice flours decreased, while the b-value was decreased as the particle size of rice flours decreased. Using a rapid visco analyzer (RVA), the initial pasting temperature of Thai rice cultivar was found to be the highest; the peak viscosities of Sunpum cultivar and Misomi cultivar, and Samkwang rice were higher than those of other rice flours. The water absorption index and water solubility index were increased as the particle size of rice flour decreased. In order to use processed rice flour for the development of processed foods, proper characteristics of the cultivars and particle size should be considered.

• Journal of the Mineralogical Society of Korea
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• v.18 no.1
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• pp.19-31
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• 2005

A study on the beneficiation of illite occurring in Youngdong province is performed with applying selective grinding and air classification techniques. Quartz and illite are occurred as major components, and sulfide minerals such as pyrite, chalcopyrite are associated as minor components. The result of sieving test shows that contents of Al₂O₃, K₂O and ignition loss are increased, whereas SiO₂ is decreased with particle size decrease. Fe₂O₃ content is almost same in all the particle size range but slightly lower at coarse particles. The yield of fine particles is increased with increasing rotor speed in both grinding stage and air classification stage. When the selective grinding and air classification are carried out at optimal condition, yield of the concentrate is 76.16 wt.%. The chemical compositions of the concentrate are SiO₂70.13%, Al₂O₃ 19.40%, Fe₂O₃ 1.62%, K₂O 5.20%, and ignition loss 2.77%. The beneficiation process developed in the current study is very effective method which purification and particle size control can be achieved simultaneously.

• Journal of Korean Society on Water Environment
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• v.33 no.6
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• pp.728-735
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• 2017

Many restoration projects are underway to revive disturbed streams. In order to achieve successful stream restoration, a variety of microhabitats should be created to promote biological diversity. Research on biological classification of microhabitats is essential for biological diversity. However, research on classification using only physical environmental factors has been carried out. The purpose of this study is to classify and quantify the microhabitat of the stream by using macroinvertebrates systematically. In this study, eight wadeable streams and four non-wadeable streams were surveyed to identify the benthic macroinvertebrates in these various microhabitats. Among the physical environmental factors (current velocity, water depth, substrate), the particle size of the substrate was the most influential factor in the emergence of the Habitat Orientaion Groups. Among the HOGs, clinger and burrower were highly correlated with physical environment factors and showed the opposite tendency. The distribution of clinger and burrower according to the physical environmental factors showed two tendencies based on the current velocity (0.3 m/s) and water depth (0.4 m). In addition, the particle size of the substrate showed three trends (${\leq}-5.0$, -5.0 < mean diameter ${\leq}-2.0$, > -2.0). Based on the abundance tendency of these two HOGs, the microhabitats were classified into nine types, from a eupotamic microhabitat to a lentic microhabitat. Classification of the microhabitats using HOGs can be employed for creating microhabitats to promote biological diversity in future stream restoration plans.

• Korean Journal of Materials Research
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• v.19 no.4
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• pp.212-219
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• 2009

A study on the dry beneficiation of sericite occurring in the Daehyun Mine of the Republic of Korea region as performed by applying selective grinding and air classification techniques. Quartz and sericite occurred in the raw ore as major components. The results of liberation using a ball mill and an impact mill showed that the contents of $R_2O$ were increased while $SiO_2$ was decreased in proportion to decreasing particle size. According to the XRD, XRF analysis and the EDS of SEM analysis, the ball mill gave a better grade product in $R_2O$ content than the impact mill when the particle size was the same. When the raw ore was ground by the impact mill with arotor speed 57.6 m/sec and then followed by 15,000rpm classification using an air classifier, the chemical composition of the over flowed product was 49.65wt% $SiO_2$, 32.15wt% $Al_2O_3$, 0.13wt% $Fe_2O_3$, 10.37wt% $K_2O$, and 0.14wt% $Na_2O$. This result indicates that the $R_2O$ contents were increased by 49.5% compared to that of the raw ore. From these results described above, it is suggested that hard mineral such as Quartz little ground by selective grinding using impact mill whereas soft mineral such as sericite easily ground to small size. As a result of that hard minerals can be easily removed from the finely ground sericite by air classification and the $R_2O$ grade of thus obtained concentrate was improved to higher than 10wt% which can be used for ceramics raw materials.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.6
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• pp.688-696
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• 2012

The particle depolarization ratios were retrieved from the observation with a multi-wavelength Raman lidar at Gwangju, Korea ($35.11^{\circ}N$, $126.54^{\circ}E$). The measurements were carried out on 24 February and 9 March 2004. Using the particle depolarization ratios, the non-dust aerosol particles were distinguished from the Asian dust plume, and the proportion of the non-dust particle to total dust plume was retrieved. The calculated proportion of the non-dust particle was used for the retrieval of backscatter coefficients at 355, 532, and 1064 nm and extinction coefficients at 355 and 532 nm of non-dust particles in the dust plume. Microphysical parameters of non-dust particles including single-scattering albedo at 532 nm were retrieved using retrieved optical values. The retrieved single-scattering albedo of non-dust particles was 0.92~0.95 below 1 km height and 0.82~0.91 above 1 km height on 24 February 2004 and $0.81{\pm}0.03$ on 9 March 2004.

• Particle and aerosol research
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• v.11 no.2
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• pp.29-36
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• 2015

The purpose of this research is to find out the collection property of nanoparticle in diffusion filter to know particle size dispersion of nanomaterial using inertial force and principle of Brownian diffusion motion. We used inertial filters which are two different type and diffusion filters made by various kinds of Wiremesh and the different pieces of filter to compare with particle size distribution using NaCl particles. Finally, We made a conclusion as follows : (1) the bigger available charging volume is and the larger specific surface area of inertial filter is, the better collection efficiency is. (2) The higher wire-mesh number of filter is, the more collection efficiency of small particle is increasing because the wire of the higher Wiremesh number filter is thinner and denser. (3) The more pieces of wire-mesh filter, the more collection efficiency is increasing because it makes the residence time longer.

• Journal of Korean Society for Atmospheric Environment
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• v.6 no.1
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• pp.11-21
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• 1990

To quantitatively estimate the effect of yellow sand(loess) fromt he Northern China, various soil sources having similar chemical compositions to yellow sands should be separated and identified. After that, mass contribution for yellow sand can be calculated. The study showed that it was impossible to solve this problem by the traditional bulk analyses. However, particle-by-particle analysis by a CCSEM (computer controlled scanning electron microscope) gave enormous potentials to solve it. To perform this study, seven soil source data analyzed by CCSEM were obtained from Texas, U.S.A. Initially, each soil date was classified into two groups, coarse and fine particle groups since the particle number distribution showed a minimum occurring at 5.2$\mu$m of aerodynamic diameter. Particles in each group were then classified into one of the 283 homogeneous particle classes by the universal classification rule which had been built by an expert system in the early study. Further, mass fractions and their uncertainties for each class in each source were calculated by the Jackknife method, and then source profile matrix for the 7 soil sources was created. To use the profile matrix in the study of source contribution, it is necessary to test the degree of collinearity among sources. The profiles were tested by the singular value decomposition method. As a result, each soil source characterized by artificially created variables was totally independent each other and is ready to use in source contribution studies as a receptor model.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1334-1337
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• 2004

This paper presents a novel method to speed up neural network (NN) based face detection systems. NN-based face detection can be viewed as a classification and search problem. The proposed method formulates the search problem as an integer nonlinear optimization problem (INLP) and expands the basic particle swarm optimization (PSO) to solve it. PSO works with a population of particles, each representing a subwindow in an input image. The subwindows are evaluated by how well they match a NN-based face filter. A face is indicated when the filter response of the best particle is above a given threshold. To achieve better performance, the influence of PSO parameter settings on the search performance was investigated. Experiments show that with fine-adjusted parameters, the proposed method leads to a speedup of 94 on 320${\times}$240 images compared to the traditional exhaustive search method.

• Proceedings of the Korea Concrete Institute Conference
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• 2009.05a
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• pp.329-330
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• 2009

This study is to investigate the effect of the combined use of fly ash(FA) and coarse particle cement(CC) collected in particle classification process of ordinary Portland cement(OPC) manufacturing on the hydration exothermic and strength development in the field application.

• ETRI Journal
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• v.39 no.6
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• pp.841-850
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• 2017

We investigate neural network image reconstruction for magnetic particle imaging. The network performance strongly depends on the convolution effects of the spectrum input data. The larger convolution effect appearing at a relatively smaller nanoparticle size obstructs the network training. The trained single-layer network reveals the weighting matrix consisting of a basis vector in the form of Chebyshev polynomials of the second kind. The weighting matrix corresponds to an inverse system matrix, where an incoherency of basis vectors due to low convolution effects, as well as a nonlinear activation function, plays a key role in retrieving the matrix elements. Test images are well reconstructed through trained networks having an inverse kernel matrix. We also confirm that a multi-layer network with one hidden layer improves the performance. Based on the results, a neural network architecture overcoming the low incoherence of the inverse kernel through the classification property is expected to become a better tool for image reconstruction.