• The Korean Journal of Food And Nutrition
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• v.19 no.4
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• pp.435-447
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• 2006

This study was carried out to investigate foodservice management of child care centers in Ansan and to suggest the basic data for foodservice management improvement. A questionnaire survey of 48 child care centers in Ansan was undertaken. Child care centers were categorized large (children eve. 100) and small(children less than 100) by size and public and private by type. Survey questionnaires consisted of general background, employee, food inspection and storage, kitchen, cooking facilities, food distribution and hygiene utensils. The results of this study are summarized as follows: because 46.9% to 56.3% of the centers took a dietitian in employment, foodservices in most of centers were not managed by professionals. The average of employee were 0.77 persons in smalll centers and 1.65 persons in large centers. The average space of kitchen were 3.86 pyung in smalll center, 6.06 pyung (1 pyung=$3.3058m^2$) in large centers. According to the data analyzed from Food inspection and storage, kitchen, cooking facilities, food distribution and hygiene utensils, the results indicate that the foodservice management of child care centers were in a relatively poor state. The director in child care centers should recognize the importance of the sanitation management and pay more attention to food service facilities. To improve foodservice performance at child care centers, it is required fur the Ministry of Gender Equality and Family to develop both the kitchen facility model based on the general sanitation standards and guidelines for child care centers.

• The KIPS Transactions:PartC
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• v.12C no.2 s.98
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• pp.191-200
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• 2005

The brilliant achievements in computers and the internet technology make it easy for users to get useful information. But at the same time, the damages caused by intrusions and denial of service attacks are getting more worse. Specially because denial of service attacks by internet worm incapacitate computers and networks, we should draw up a disposal plan against it. So far many rule-based intrusion detection systems have been developed, but these have the limits of these ability to detect new internet worms. In this paper, we propose a system to detect intrusion and generate detection rule against scan-based internet worm, paying attention to the fact that internet worms scan network to infect hosts. The system detects internet worms using detection rule. And if it detects traffic causing by a new scan-based internet worm, it generates new detection nile using traffic information that is gathered. Therefore it can response to new internet worms early. Because the system gathers packet payload, when it is being necessary only, it can reduce system's overhead and disk space that is required.

• Journal of the Korean Ceramic Society
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• v.53 no.4
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• pp.417-428
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• 2016

In this review, an attempt is made to calculate one-dimensional (1-D) electron density profiles from experimentally determined (00l) XRD intensities and possible structural models as well in an effort to understand the collective intracrystalline structures of intercalant molecules of two-dimensional (2-D) nanohybrids with heterostructures. 2-D ceramics, including layered metal oxides and clays, have received much attention due to their potential applicability as catalysts, electrodes, stabilizing agents, and drug delivery systems. 2-D nanohybrids based on such layered ceramics with various heterostructures have been realized through intercalation reactions. In general, the physico-chemical properties of such 2-D nanohybrids are strongly correlated with their heterostructures, but it is not easy to solve the crystal structures due to their low crystallinity and high anisotropic nature. However, the powder X-ray diffraction (XRD) analysis method is thought to be the most powerful means of understanding the interlayer structures of intercalant molecules. If a proper number of well-developed (00l) XRD peaks are available for such 2-D nanohybrids, the 1-D electron density along the crystallographic c-axis can be calculated via a Fourier transform analysis to obtain structural information about the orientations and arrangements of guest species in the interlayer space.

• Journal of Industrial Convergence
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• v.21 no.10
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• pp.13-19
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• 2023

This study classified sensory affordances, functional affordances, and perceptual affordances, and verified their effects on consumers' participation and intention to stay in the metaverse. As a result of the study, sensory affordance, functional affordance, and perceptual affordance all had a positive effect on consumer participation, and sensory affordance had the greatest effect. In addition, consumer participation was found to increase the intention to stay. Service companies that provide metaverse platforms will have to pay more attention to realizing virtual space through various senses and physical elements when building a metaverse in order to encourage customers to actively participate in the service process. Since services based on the 4th industry, the participation of consumers needs to be more actively reviewed. From the perspective of affordance, it is expected that the realistic implementation of the metaverse environment and the interaction with various contents or avatars in the space will increase consumer participation.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.548-553
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• 2001

Recently, much attention is imposed on the design of the fuel assemblies in the Pressurized Light Water Reactor (PWR). Spacer grid is one of the main structural components in a fuel assembly. It supports fuel rods, guides cooling water and protects the system from the external impact loads. Various space grids have been proposed and new designs are also being created. In this research, a new spacer grid is designed by the axiomatic approach. The Independence Axiom is utilized for the design. For conceptual design, functional requirements (FRs) are defined and corresponding design parameters (DPs) are found to satisfy FRs in sequence. Overall configuration and shapes are determined in this process. Detail design is carried out based on the result of the axiomatic design. For the detail design, the system performances are evaluated by using linear and nonlinear finite element analysis. The dimensions are determined by optimization. Some commercial codes are utilized for the analysis and design.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.5
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• pp.2607-2627
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• 2017

Nonnegative matrix factorization (NMF) has received considerable attention due to its effectiveness of reducing high dimensional data and importance of producing a parts-based image representation. Most of existing NMF variants attempt to address the assertion that the observed data distribute on a nonlinear low-dimensional manifold. However, recent research results showed that not only the observed data but also the features lie on the low-dimensional manifolds. In addition, a few hard priori label information is available and thus helps to uncover the intrinsic geometrical and discriminative structures of the data space. Motivated by the two aspects above mentioned, we propose a novel algorithm to enhance the effectiveness of image representation, called Dual graph-regularized Constrained Nonnegative Matrix Factorization (DCNMF). The underlying philosophy of the proposed method is that it not only considers the geometric structures of the data manifold and the feature manifold simultaneously, but also mines valuable information from a few known labeled examples. These schemes will improve the performance of image representation and thus enhance the effectiveness of image classification. Extensive experiments on common benchmarks demonstrated that DCNMF has its superiority in image classification compared with state-of-the-art methods.

• Proceedings of the Korean Vacuum Society Conference
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• 2013.02a
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• pp.643-643
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• 2013

Recently, synthesis of low-dimensional nanostructures is gaining more importance due to their structural properties and growing potential applications. On the other hand, luminescent materials doped with rare earth ions have drawn immense attention. The commercial phosphors are based on many host materials. Among them, tungstates are being currently investigated by many research groups owing to a wide range of applications. Tungstates are formed by different metal cations (e.g., SrWO4, Na2WO4, NiWO4, Cr2WO6, and ZrW2O8) and their structure depends on the size of the metal cation. Tungstates with large bivalent cations (${\gg}0.1\;nm$) have the scheelite structure and the wolframite structure with smaller ions (＜0.1 nm). Strontium tungstate has the scheelite structure which is tetragonal with space group I41/a. The luminescent properties of the tungstate have been extensively explored in application fields such as sensors, detectors, lasers, photoluminiscent devices, photo catalysts, etc. In this work, we synthesized SrWO4 phosphors with different Eu3+ concentrations by using a facile route. The morphology was analyzed by using a field-emission scanning electron microscope, which exhibits the spherical shape. Transmission electron microscope image revealed the spheres composed of nanoparticles. X-ray diffraction patterns confirmed their tetragonal shape. The photoluminescence excitation and emission spectra were analyzed by varying the Eu3+ concentration, which shows a dominant red emission.

• Earthquakes and Structures
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• v.10 no.4
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• pp.757-768
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• 2016

In the past decades, effect of near field earthquake on the historical monuments has attracted the attention of researchers. So, many analyses in this regard have been presented. Tunnels as vital arteries play an important role in management after the earthquake crisis. However, digging tunnels and seismic effects of earthquake on the historical monuments have always been a challenge between engineers and historical supporters. So, in a case study, effect of near field earthquake on the historical monument was investigated. For this research, Finite Element Analysis (FEM) in soil environment and soil-structure interaction was used. In Plaxis 2D software, different accelerograms of near field earthquake were applied to the geometric definition. Analysis validations were performed based on the previous numerical studies. Creating a nonlinear relationship with space parameter, time, angular and numerical model outputs was of practical and critical importance. Hence, artificial Neural Network (ANN) was used and two linear layers and Tansig function were considered. Accuracy of the results was approved by the appropriate statistical test. Results of the study showed that buildings near and far from the tunnel had a special seismic behavior. Scattering of seismic waves on the underground tunnels on the adjacent buildings was influenced by their distance from the tunnel. Finally, a static test expressed optimal convergence of neural network and Plaxis.

• Journal of Information Processing Systems
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• v.18 no.4
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• pp.535-548
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• 2022

Using a rich resource language to classify sentiments in a language with few resources is a popular subject of research in natural language processing. Burmese is a low-resource language. In light of the scarcity of labeled training data for sentiment classification in Burmese, in this study, we propose a method of transfer learning for sentiment analysis of a language that uses the feature transfer technique on sentiments in English. This method generates a cross-language word-embedding representation of Burmese vocabulary to map Burmese text to the semantic space of English text. A model to classify sentiments in English is then pre-trained using a convolutional neural network and an attention mechanism, where the network shares the model for sentiment analysis of English. The parameters of the network layer are used to learn the cross-language features of the sentiments, which are then transferred to the model to classify sentiments in Burmese. Finally, the model was tuned using the labeled Burmese data. The results of the experiments show that the proposed method can significantly improve the classification of sentiments in Burmese compared to a model trained using only a Burmese corpus.

• Journal of Ecology and Environment
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• v.43 no.2
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• pp.191-201
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• 2019

Macroecologists and biogeographers continue to predict the distribution of species across space based on the relationship between biotic processes and environmental variables. This approach uses data related to, for example, species abundance or presence/absence, climate, geomorphology, and soils. Researchers have acknowledged in their statistical analyses the importance of accounting for the effects of spatial autocorrelation (SAC), which indicates a degree of dependence between pairs of nearby observations. It has been agreed that residual spatial autocorrelation (rSAC) can have a substantial impact on modeling processes and inferences. However, more attention should be paid to the sources of rSAC and the degree to which rSAC becomes problematic. Here, we review previous studies to identify diverse factors that potentially induce the presence of rSAC in macroecological and biogeographical models. Furthermore, an emphasis is put on the quantification of rSAC by seeking to unveil the magnitude to which the presence of SAC in model residuals becomes detrimental to the modeling process. It turned out that five categories of factors can drive the presence of SAC in model residuals: ecological data and processes, scale and distance, missing variables, sampling design, and assumptions and methodological approaches. Additionally, we noted that more explicit and elaborated discussion of rSAC should be presented in species distribution modeling. Future investigations involving the quantification of rSAC are recommended in order to understand when rSAC can have an adverse effect on the modeling process.