• Korean Journal of Soil Science and Fertilizer
• /
• v.42 no.1
• /
• pp.58-64
• /
• 2009

The objectives of this study were to investigate the aggregate fragmentation in wet-sieving and to evaluate the relationship between the aggregate fragmentation fractal dimension and macro-porosity of upland soils, using three different textural types of soils including Gopyeng series (Fine, Typic Hapludalfs), Gyuam series (Fine silty over coarse silty, Fluvaquentic Eutrudepts), and Jungdong series (Coarse loamy, Typic Udifluvents) located in Gyeonggi province. Undisturbed soil samples with five replicates were seasonally sampled and used for measuring water stable aggregate, macropores, and physico-chemical properties of soils. The aggregate stability in wet-sieving was digitalized as three types of fragmentation fractal dimension ($D_f$), geometric mean diameter (GMD), and mean weight diameter (MWD). $D_f$ had higher correlation with GMD than with MWD. Seasonal aggregate stability showed the highest values in summer, and decreased in the order of spring and autumn. The macroporosity had higher in topsoil, in autumn, and in ridge, than in plow pan layer, in summer, and in row, respectively. The relationship between $D_f$ and macroporosity, especially more than 99 m, showed high correlation only in soils with $D_f$ less than 3.1, which means more aggregated soils compared to soils with $D_f$ more than 3.1. Besides, in the soils with the fractal dimension less than 3.1, the power function relation between saturated hydraulic conductivity and macroporosity more than 99 m had relatively high determinant coefficient, and vice versa. Therefore, it could be thought that fragmentation fractal dimension is available for confirming macroporosity induced from aggregation.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.32 no.4
• /
• pp.61-75
• /
• 2007

In ubiquitous computing, shared environments are required to adapt to people intelligently. Based on information about user preferences, the shared environments should be adjusted so that all users in a group are satisfied as possible. Although many group recommender systems have been proposed to obtain this purpose, they only consider average and misery. However, a broad range of philosophical approaches suggest that high inequality reduces social agreeability, and consequently causes users' dissatisfactions. In this paper, we propose social welfare functions, which consider inequalities in users' preferences, as alternative aggregation functions to achieve a social agreeability. Using an example in a previous work[7], we demonstrate the effectiveness of proposed welfare functions as socially agreeable aggregate functions in group recommender systems.

• Proceedings of the Korea Concrete Institute Conference
• /
• 2002.05a
• /
• pp.545-550
• /
• 2002

Concrete is one of the essential structural materials in the construction. But, concrete consists of many materials and is affected by many factors such as properties of materials, site environmental situations, and skill of constructor. Therefore, concrete mixes depend on experiences of experts. However, it is more and more difficult to determine concrete mixes design by empirical means because more ingredients like mineral and chemical admixtures are included. Artificial Neural Networks(ANN) are a mimic models of human brain to solve a complex nonlinear problem. They are powerful pattern recognizers and classifiers, also their computing abilities have been proven in the fields of prediction, estimation and pattern recognition. Here, among them, the back propagation network and radial basis function network are used. Compositions of high-performance concrete mixes are eight components(water, cement, fine aggregate, coarse aggregate, fly ash, silica fume, superplasticizer and air-entrainer). Compressive strength and slump are measured. The results show that neural networks are proper tools to minimize the uncertainties of the design of concrete mixtures.

• Computers and Concrete
• /
• v.5 no.6
• /
• pp.559-572
• /
• 2008

The effects of fly ash and superplasticizer (SP) on workability of concrete are quite difficult to predict because they are dependent on other concrete ingredients. Because of high complexity of the relations between workability and concrete compositions, conventional regression analysis could be not sufficient to build an accurate model. In this study, a workability model has been built using artificial neural networks (ANN). In this model, the workability is a function of the content of all concrete ingredients, including cement, fly ash, blast furnace slag, water, superplasticizer, coarse aggregate, and fine aggregate. The effects of water/binder ratio (w/b), fly ash-binder ratio (fa/b), superplasticizer-binder ratio (SP/b), and water content on slump were explored by the trained ANN. This study led to the following conclusions: (1) ANN can build a more accurate workability model than polynomial regression. (2) Although the water content and SP/b were kept constant, a change in w/b and fa/b had a distinct effect on the workability properties. (3) An increasing content of fly ash decreased the workability, while raised the slump upper limit that can be obtained.

• Proceedings of the Korea Concrete Institute Conference
• /
• 2000.04a
• /
• pp.253-256
• /
• 2000

The functions of porous concrete were influenced by continuous void, and it differ greatly from the distribution and size shape of continuous void in the same void volume. And porous concrete has been few used because the strength level of porous concrete is lower than that of ordinary concrete at the present time. So the purpose of this study is to increase the strength of porous concrete at the range of satisfying its function, analyze those effects of the mixing ratio of aggregate, affecting the development of its strength.

• Computers and Concrete
• /
• v.16 no.5
• /
• pp.775-793
• /
• 2015

Moisture transport in concrete in atmospheric environment was studied in this paper. Based on the simplified formula of the thickness of the adsorbed layer, the pore-size distribution function of cement paste was calculated utilizing the water adsorption isotherms. Taking into consideration of the hysteresis effect in cement paste, the moisture diffusivity of cement paste was obtained by the integration of the pore-size distribution. Concrete is regarded as a two-phase composite with cement paste and aggregate, neglecting the moisture diffusivity of aggregate, then moisture diffusivity of concrete was evaluated using the composite theory. Finally, numerical simulation of humidity response during both wetting and drying process was carried out by the finite difference method of partial differential equation for moisture transport, and the numerical results well capture the trend of the measured data.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.13 no.21
• /
• pp.101-110
• /
• 1990

This study presents a two-level inventory distribution system with one-upper level facility(warehouse) in first echelon and n-lower level facilities(stores) in the second echelon. The demand process at the upper level is induced by the aggregated backorder processes of n independently operated lower level facilities in parallel. For the upper level and the lower level we find the decision points and the distribution function of the aggregate backorders from n-stores. Optimal allocation units and expected system profits are obtained. If the product is of great enough importance to the customer, echelon structure will include a shadow installation. Also, this case is analyzed. Numerical examples are presented to illustrate the results for each case.

• Journal of Environmental Science International
• /
• v.16 no.10
• /
• pp.1169-1177
• /
• 2007

The main objective of this research was to evaluate the effects of process variables which were forming ability, flow displacement, effective stress, effective strain, fluid vector and products defects on manufactured artificial lightweight aggregate made of both incinerated sewage sludge ash and clay by means of the numerical analysis of a rigid-plastic finite element method. CATIA (3D CAD program) was used for an extrusion metal mold design that was widely used in designing aircraft, automobile and metallic molds. A metal forming analysis program (ATES Co.) had a function of a rigid-plastic finite element method was used to analyze the program. The result of extrusion forming analysis indicated clearly that a shape retention of the manufactured artificial light-weight aggregate could be maintained by increasing the extrusion ratio (increasing compressive strength inside of extrusion die) and decreasing the die angle. The stress concentration of metal mold was increased by increasing an extrusion ratio, and it was higher in a junction of punch and materials, friction parts between a bottom of the punch and inside of a container, a place of die angle and a place of die of metal mold. Therefore, a heat treatment as well as a rounding treatment for stress distribution in the higher stress concentration regions were necessary to extend a lifetime of the metallic mold. A deformity of the products could have made from several factors which were a surface crack, a lack of the shape retention and a crack of inside of the products. Specially, the surface crack in the products was the most notably affected by the extrusion ratio.

• Journal of Animal Reproduction and Biotechnology
• /
• v.39 no.1
• /
• pp.19-30
• /
• 2024

Background: Although an understanding of the proliferation and differentiation of fish female germline stem cells (GSCs) is very important, an appropriate threedimensional (3D) research model to study them is not well established. As a part of the development of stable 3D culture system for fish female GSCs, we conducted this study to establish a 3D aggregate culture system of ovarian cells in marine medaka, Oryzias dancena. Methods: Ovarian cells were separated by Percoll density gradient centrifugation and two different cell populations were cultured in suspension to form ovarian cell aggregates to find suitable cell populations for its formation. Ovarian cell aggregates formed from different cell populations were evaluated by histology and gene expression analyses. To evaluate the media supplements, ovarian cell aggregate culture was performed under different media conditions, and the morphology, viability, size, gene expression, histology, and E2 secretion of ovarian cell aggregates were analyzed. Results: Ovarian cell aggregates were able to be formed well under specific culture conditions that used ultra-low attachment 96 well plate, complete mESM2, and the cell populations from top to 50% layers after separation of ovarian cells. Moreover, they were able to maintain minimal ovarian function such as germ cell maintenance and E2 synthesis for a short period. Conclusions: We established basic conditions for the culture of O. dancena ovarian cell aggregates. Additional efforts will be required to further optimize the culture conditions so that the ovarian cell aggregates can retain the improved ovarian functions for a longer period of time.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.36 no.12A
• /
• pp.1006-1014
• /
• 2011

Recently, as CSMA technique has been increasingly adopted in various wireless networks, extensive researches to analyze the statistical characteristics of CSMA-based wireless networks have been done. Despite the ongoing efforts, there still remain many difficulties in the analysis because of unexpectable operational behavior of CSMA. Previous literature studying CSMA networks used the concept of the carrier sensing radius to reflect the carrier sensing function. However, since the carrier sensing radius based on the protocol model is not affected by the aggregate interference from other nodes, the derived statistical models cannot avoid approximation errors especially if the network is under high interference. In this paper, we propose an algorithm to derive the carrier sensing radius considering the physical model, where the carrier sensing radius reflecting the aggregate interference is found. For the purpose of this, we analyze the aggregate interference model and the behavior of CSMA function. Based on the analysis, we propose an iterative approximation algorithm for the physical carrier sensing radius. Extensive simulations and results show that the proposed algorithm can contribute to considerably reduce the statistical modeling error of a CSMA network under various channel conditions.