• Communications for Statistical Applications and Methods
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• v.8 no.2
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• pp.327-336
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• 2001

This work concerns estimating a regression function, which is not linear, using aggregate data. In much of the empirical research, data are aggregated for various reasons before statistical analysis. In a traditional parametric approach, a linear estimation of the non-linear function with aggregate data can result in unstable estimators of the parameters. More serious consequence is the bias in the estimation of the non-linear function. The approach we employ is the kernel regression smoothing. We describe the conditions when the aggregate data can be used to estimate the regression function efficiently. Numerical examples will illustrate our findings.

• Computers and Concrete
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• v.8 no.2
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• pp.163-176
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• 2011

By virtue of chord-length density function from the field of statistical physics, this paper introduced a quantitative approach to estimate the distribution of cement paste thickness between aggregates in concrete. Dynamics mixing method based on molecular dynamics was employed to generate one model structure, then image analysis algorithm was used to obtain the distribution of thickness of cement paste in model structure for the purpose of verification. By comparison of probability density curves and cumulative probability curves of the cement paste thickness among neighboring aggregates, it is found that the theoretical results are consistent with the simulation. Furthermore, for the model mortar and concrete mixtures with practical volume fraction of Fuller-type aggregate, this analytical formula was employed to predict the influence of aggregate volume fraction and aggregate fineness. And evolution of its mean values were also investigated with the variation of volume fraction of aggregate as well as the fineness of aggregates in model mortars and concretes.

• The KIPS Transactions:PartD
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• v.9D no.1
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• pp.21-30
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• 2002

The active database system introduces the active rules detecting specified state. As the condition evaluation of the active rules is performed every time an event occurs, the performance of the system has a great influence, depending on the conditions processing method. In this paper, we propose the conditions processing system with the preprocessor which determines the delta tree structure, constructs the classification tree, and generates the aggregate function table. Due to the characteristics of the active database through which the active rules can be comprehended beforehand, the preprocessor can be introduced. In this paper, the delta tree which can effectively process the join, selection operations, and the aggregate function is suggested, and it can enhance the condition evaluation performance. And we propose the classification tree which effectively processes the join operation and the aggregate function table processing the aggregate function which demands high cost. In this paper, the conditions processing system can be expected to enhance the performance of conditions processing in the active rules as the number of conditions comparison decreases because of the structure which is made in the preprocessor.

• Journal of KIISE:Databases
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• v.30 no.4
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• pp.372-380
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• 2003

Temporal databases support time-varying events so that conventional aggregate functions are extended to be processed with time for temporal aggregate functions. In the previous approach, it is done repeatedly to find time intervals and is calculated the result of each interval whenever target events are different. This paper proposes a method which processes temporal aggregate function queries using time point sequence. We can make time point sequence storing the start time and the end time of events in temporal databases in advance. It is also needed to update time point sequence due to insertion or deletion of events in temporal databases. Because time point sequence maintains the information of time intervals, it is more efficient than the previous approach when temporal aggregate function queries are continuously requested, which have different target events.

• The Journal of the Korean dental association
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• v.48 no.11
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• pp.803-812
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• 2010

Regenerative endodontic procedure (REP) is a treatment option to replace damaged pulp tissue with the viable tissue which restores the normal function of the pulp-dentin complex. Possible reason for doing REP is not clearly known, however, clinicians perform REP in order to recover the histological structure as well as function of the traumatized and diseased tooth so that this tooth can restore its original root shape and thickness. This REP can be explained by the concept of revascularization or revitalization after induction of blood clot formation in the canal space. For this purpose, several treatment strategies have been suggested. In this regard, the rationale for the application of triantibiotics, calcium hydroxide or mineral trioxide aggregate is discussed in this paper. As a result, we will try to find the best method for REP by reviewing each available technique and their advantages and disadvantages.

• Management Science and Financial Engineering
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• v.2 no.1
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• pp.73-101
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• 1996

We show assets can be classified into diversifiable risks and non-diversifiable risks based on aggregate endowment and spanning so that in equilibrium agents eliminate diversifiable risks which must have zero values. Consequently, the benchmark portfolio that represents a pricing operator should have only a non-diversifiable risk, aggregate endowment should earn a positive risk premium over a riskless asset, and, even in incomplete markets, there should be a pricing operator represented by a function of aggregate endowment if any asset mean-independent of aggregate endowment is diversifiable. These results apply to both the CAPM and a representative agent model.

• Korean Chemical Engineering Research
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• v.60 no.2
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• pp.260-266
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• 2022

Average aggregate size in particulate suspensions is estimated with scaling theories based on fractal concept and elasticity of colloidal gel. The scaling theories are used to determine structure parameters of the aggregates, i.e., fractal dimension and power-law exponent for aggregate size reduction with shear stress using scaling behavior of elastic modulus and shear yield stress as a function of particle concentration. The structure parameters are utilized to predict aggregate size which varies with shear stress through rheological modeling. Experimentally rheological measurement is conducted for aqueous suspension of zinc oxide particles with average diameter of 110 nm. The predicted aggregate size is about 1135 nm at 1 s^-1 and 739 nm at 1000 s^-1 on the average over the particle concentrations. It has been found that the predicted aggregate size near 0.1 s^-1 agrees with that the measured one by a dynamic light scattering analyzer operated un-sheared.

• Journal of Computing Science and Engineering
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• v.1 no.2
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• pp.211-232
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• 2007

In this paper we investigate some issues and solutions related to the design of a Data Warehouse (DW), storing several aggregate measures about trajectories of moving objects. First we discuss the loading phase of our DW which has to deal with overwhelming streams of trajectory observations, possibly produced at different rates, and arriving in an unpredictable and unbounded way. Then, we focus on the measure presence, the most complex measure stored in our DW. Such a measure returns the number of distinct trajectories that lie in a spatial region during a given temporal interval. We devise a novel way to compute an approximate, but very accurate, presence aggregate function, which algebraically combines a bounded amount of measures stored in the base cells of the data cube. We conducted many experiments to show the effectiveness of our method to compute such an aggregate function. In addition, the feasibility of our innovative trajectory DW was validated with an implementation based on Oracle. We investigated the most challenging issues in realizing our trajectory DW using standard DW technologies: namely, the preprocessing and loading phase, and the aggregation functions to support OLAP operations.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2006.05a
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• pp.111-114
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• 2006

Recently, it is increased on the concern for the reuse of waste concrete because of the shortage of natural aggregate and the increase of waste concrete. And recycled coarse aggregate is used variously, but the existing wet method producted recycled fine aggregate has problem like the high price facilities, the long time progress of the work and the poor of recycled fine aggregate. The aim of this study is to investigate outline and performance evaluation of the drying specific gravity separation method to product high duality recycled fine aggregate. Finally, this study is shown investigate process flowing of drying separation type with gravity manufacture, producte system and function of detail devices. The performance of the method of drying specific gravity separation is certificated as the qualities of recycled fine aggregate satisfied the KS

• Journal of the Computational Structural Engineering Institute of Korea
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• v.25 no.3
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• pp.227-235
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• 2012

The void distribution in concrete materials strongly affects its material properties. Therefore, the identification of spatial distribution of void is important to understand and estimate material behavior. To examine and quantify the void distribution inside lightweight aggregates, CT(computed tomography) image is used. 3D lightweight aggregate images are generated by stacking of cross-sectional images from CT. Spatial distribution of void of aggregate along the direction is visualized on the sphere using probability distribution function. Stiffness of lightweight aggregate for the directions is also examined. It is confirmed that direction-based probability distribution and stiffness from CT images are effective in characterizing void distributions of aggregates.