• Journal of the Korea Concrete Institute
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• v.18 no.2 s.92
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• pp.189-198
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• 2006

The composition of most engineering materials is heterogeneous at some degree. It is simply a question of scale at which the level of heterogeneity becomes apparent. In the case of cementitious granular materials such as concrete the heterogeneity appears at the mesoscale where it is comprised of aggregate particles, a hardened cement paste and voids. Since it is difficult to consider each separate particle in the topological description explicitly, numerical models of the meso-structure are normally confined to two-phase matrix particle composites in which only the larger inclusions are accounted for. 2-D and 3-D concrete blocks(Representative Volume Element, RVE) are used to simulating heterogeneous concrete meso-structures in the form of aggregates in the hardened mortar with nearly zero-thickness linear or planar interfaces. The numerical sensitivity of these meso-structures are Investigated with respect to the different morphologies of heterogeneity and the different level of coupling constant among fracture mode I, II and III. In addition, a numerically homogenized concrete block in 3-D using Hashin-Shtrikman variational bounds provides an evidence of the effective cracking paths which are quite different with those of heterogenous concrete block. However, their average force-displacement relationship show a pretty close match each other.

• 한국생물공학회:학술대회논문집
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• 2000.04a
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• pp.125-128
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• 2000

A recycling reactor system operated under sequential anoxic and oxic conditions for the swine wastewater has been developed, in which piggery slurry is fermentatively and aerobically treated and then part of the effluent recycled to the pigsty. This system significantly removes offensive smells (at both pigsty and treatment plant), BOD and other loads, and appears to be costeffective for the small-scale farms. The most dominant heterotrophs were Alcaligenes faecalis, Brevundimonas diminuta and Streptococcus sp. in order while lactic acid bacteria were dominantly observed in the anoxic tank. We propose a novel monitoring system for a recycling piggery slurry treatment system through neural networks. Here we tried to model treatment process for each tank(influent, fermentation, aeration, first sedimentation and fourth sedimentation tanks) in the system based on population densities of heterotrophic and lactic acid bacteria. Principle component analysis(PCA) was first applied to identify a relation between input(microbial densities and parameters for the treatment such as population densities of heterotrophic and lactic acid bacteria, suspended solids (SS), COD, $NH_3-N$, ortho-P, and total-P) and output, and then multilayer neural networks were employed to model the treatment process for each tank. PCA filtration of input data as microbial densities was found to facilitate the modeling procedure for the system monitoring even with a relatively lower number of input. Neural networks independently trained for each treatment tank and their subsequent combinatorial data analysis allowed a successful prediction of the treatment system for at least two days.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.22 no.1
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• pp.81-90
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• 2004

Because satellite images include geometry distortions according to photographing conditions and sensor property, and their spatial and radiational resolution and spectrum resolution are different, it is so difficult to make a precise results of analysis. For comparing more than two images, the precise geometric corrections should be preceded because it necessary to eliminate systematic errors due to basic sensor information difference and non-systematic errors due to topographical undulations. In this study, we did sensor modeling using satellite sensor information to make a basic map of change detection for artificial topography. We eliminated the systematic errors which can be occurred in photographing conditions using GCP and DEM data. The Kompsat EOC images relief could be reduced by precise rectification method. Classifying images which was used for change detections by city and forest zone, the accuracy of the matching results are increased by 10% and the positioning accuracies also increased. The result of change detection using basic map could be used for basic data fur GIS application and topographical renovation.

• Journal of Preventive Medicine and Public Health
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• v.49 no.5
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• pp.253-259
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• 2016

Objectives: Central obesity plays a major role in the development of many chronic diseases, including cardiovascular disease and cancer. Chronic stress may be involved in the pathophysiology of central obesity. Although several large-scale genome-wide association studies have reported susceptibility genes for central adiposity, the effects of interactions between genes and psychosocial stress on central adiposity have rarely been examined. A recent study focusing on Caucasians discovered the novel gene early B-cell factor 1 (EBF1), which was associated with central obesity-related traits via interactions with stress levels. We aimed to evaluate EBF1 gene-by-stress interaction effects on central adiposity traits, including visceral adipose tissue (VAT), in Korean adults. Methods: A total of 1467 Korean adults were included in this study. We selected 22 single-nucleotide polymorphisms (SNPs) in the EBF1 gene and analyzed their interactions with stress on central adiposity using additive, dominant, and recessive genetic modeling. Results: The four SNPs that had strong linkage disequilibrium relationships (rs10061900, rs10070743, rs4704967, and rs10056564) demonstrated significant interactions with the waist-hip ratio in the dominant model ($p_{int}$<0.007). In addition, two other SNPs (rs6556377 and rs13180086) were associated with VAT by interactions with stress levels, especially in the recessive genetic model ($p_{int}$<0.007). As stress levels increased, the mean values of central adiposity traits according to SNP genotypes exhibited gradual but significant changes (p<0.05). Conclusions: These results suggest that the common genetic variants for EBF1 are associated with central adiposity through interactions with stress levels, emphasizing the importance of managing stress in the prevention of central obesity.

• The KIPS Transactions:PartB
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• v.15B no.5
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• pp.477-486
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• 2008

Facial expression, which changes face geometry, usually has an adverse effect on the performance of a face recognition system. To improve the face recognition rate, we propose a normalization method of facial expression to diminish the difference of facial expression between probe and gallery faces. Two approaches are used to facial expression modeling and normalization from single still images using a generic facial muscle model without the need of large image databases. The first approach estimates the geometry parameters of linear muscle models to obtain a biologically inspired model of the facial expression which may be changed intuitively afterwards. The second approach uses RBF(Radial Basis Function) based interpolation and warping to normalize the facial muscle model as unexpressed face according to the given expression. As a preprocessing stage for face recognition, these approach could achieve significantly higher recognition rates than in the un-normalized case based on the eigenface approach, local binary patterns and a grey-scale correlation measure.

• Journal of the Korean Society of Costume
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• v.58 no.4
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• pp.58-71
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• 2008

The demand for personalized products and service of apparel product has increased dramatically. In order to acquire a personalized apparel product, consumers may have to sacrifice more expense or time. The purpose of this study was to investigate various personalization strategies in apparel business and to identify antecedents that influence the process. Clothing involvement and two price related variables (clothing expense and willingness to pay more) were included in the study as antecedents. Four personalization strategies were included in the study: design selection, size customization, in-store service and promotion personalization. For an empirical study, a conceptual model was designed and research questionnaire was developed. A measure of personalization of apparel shopping was developed based on existing scale items of prior research and a pilot study. Data from 766 men and women in their twenties to forties were used for statistical analysis. Structural Equation Modeling was used for the data analysis. Results indicated that the conceptual model was a good fit to data. Structural paths indicated that there was significant influence of clothing involvement on design selection and sales promotion personalization strategies. Involved consumers spent more on chothing products and were likely to pay more on personalized products and services. Monthly clothing expense influenced size customization significantly. It also had negative influence on service related personalization strategies. Consumers were willing to pay more when it comes to product related personalization strategies such as design and size but not necessarily to service related strategies. This study was an attempt to provide an in-depth and synthesized approach on consumer attitudes toward personalization of apparel products.

• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.1
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• pp.5-19
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• 2015

Literatures on open innovation have two major limitations. First, either on a firm level or on an industry level did they analyze the open innovation issues. The results of a firm's innovation can be diffused through the whole network and the firm can learn back from the network knowledge. Prior literatures did not consider the feedback loop among firms and network in which the firms are involved. Second, most open innovation research had a static perspective on firm's innovation performance. Since the diffusion, spill-over and learning among network members are involved over time, the open innovation is intrinsically dynamic. From the dynamic perspective, we can appreciate the fundamental attributes of the open innovation network which involves diverse firms, research institutes, and universities. In order to overcome the limitations, we suggest a dynamic model for open innovation network. We build an agent-based model which consists of heterogeneous firms. The firms are connected through a scale-free network which is formed by preferential attachment. Through the diverse scenario of simulation, we collect massive data on the firm level and analyze them both on firm and industry level. From the analysis, we found that, on industry level, the overall performance of open innovation increases as the internal research capability, absorptive capacity, and learning curve coefficient increase. Noticeably, as the deprecation rate of knowledge increases, the variability of knowledge increases. From the firm level analysis, we found that the industry-level variables had a significant effect on the firm's innovation performance lasting through all the time, whereas the firm-level variables had only on the early phase of innovation.

• Structural Monitoring and Maintenance
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• v.5 no.2
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• pp.231-242
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• 2018

Subway tunnel structure has been rapidly developed in many cities for its strong transport capacity. The model-based damage detection of subway tunnel structure is usually difficult due to the complex modeling of soil-structure interaction, the indetermination of boundary and so on. This paper proposes a new data-based method for the damage detection of subway tunnel structure. The root mean square acceleration and cross correlation function are used to derive a statistical pattern recognition algorithm for damage detection. A damage sensitive feature is proposed based on the root mean square deviations of the cross correlation functions. X-bar control charts are utilized to monitor the variation of the damage sensitive features before and after damage. The proposed algorithm is validated by the experiment of a full-scale two-rings subway tunnel lining, and damages are simulated by loosening the connection bolts of the rings. The results verify that root mean square deviation is sensitive to bolt loosening in the tunnel lining and X-bar control charts are feasible to be used in damage detection. The proposed data-based damage detection method is applicable to the online structural health monitoring system of subway tunnel lining.

• Nuclear Engineering and Technology
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• v.52 no.8
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• pp.1626-1637
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• 2020

This work covers an important point of the benchmark released by the expert group on Uncertainty Analysis in Modeling of Light Water Reactors. This ambitious benchmark aims to determine the uncertainty in light water reactors systems and processes in all stages of calculation, with emphasis on multi-physics (coupled) and multi-scale simulations. The Gesellschaft für Anlagen und Reaktorsicherheit methodology is used to propagate the thermal-hydraulic uncertainty of macroscopic parameters through TRACE5.0p3/PARCSv3.0 coupled code. The main innovative points achieved in this work are i) a new thermal-hydraulic model is developed with a highly-accurate 3D core discretization plus an iterative process is presented to adjust the 3D bypass flow, ii) a control rod insertion occurrence -which data is obtained from a real PWR test- is used as a transient simulation, iii) two approaches are used for the propagation process: maximum response where the uncertainty and sensitivity analysis is performed for the maximum absolute response and index dependent where the uncertainty and sensitivity analysis is performed at each time step, and iv) RESTING MATLAB code is developed to automate the model generation process and, then, propagate the thermal-hydraulic uncertainty. The input uncertainty information is found in related literature or, if not found, defined based on expert judgment. This paper, first, presents the Gesellschaft für Anlagen und Reaktorsicherheit methodology to propagate the uncertainty in thermal-hydraulic macroscopic parameters and, then, shows the results when the methodology is applied to a PWR reactor.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.5
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• pp.108-116
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• 1989

The simulator described here-LOSIM(LOgic SIMulator)-was developed to verify the logic design for VLSI(Very Large Scale Integrated) circuits at mixed level. In this paper, we present a modeling approach to obtain more accurate results than conventional logic simulators [5-6,9] for general elements, functional elements, transmission gates and tri-state gates using eight signal values and two gignal strengths. LOSIM has the capability which can perform timing and hazard analysis by using assignable rise and fall delays. We also prosent an efficient algorithm to accurately detectdynamic and static hazards which may be caused by the circuit delays. Our approach is based on five logic values and the scheduled time. LOSIM has been implemented on a UN-3/160 workstation running Berkeley 4.2 UNIX, and the program is written in C language. Static RAM cell and asynchronous circuit are illustrated as an example.