• Journal of Advanced Marine Engineering and Technology
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• v.31 no.4
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• pp.343-349
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• 2007

This cryogenic miniature globe valve is used to transfer the liquified natural gas which temperature is $-169^{\circ}C$, supplied pressure is 30bar(3.0MPa). In the present work the temperature distribution and thermal deformation is calculated numerical the FE method is useful to predict the thermal matter of cryogenic miniature globe valve. For this reason, to optimum design of the cryogenic miniature globe valve the analysis of the parameter about bonnet has been studied. It's used 3-D modeling to analyze cryogenic globe valve, which is 1/2". Numerical study used 3-D modeling makes a decision of efficient process of product before producing in the factory. A commercial software(ANSYS 10.0) is used in the structural analysis for cryogenic globe valve.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.03a
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• pp.24-29
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• 1996

The seniconductor, which is precision product, requires many inspection processes. The surface conditions of the semiconductor chip effect on the functions of the semiconductors. The defects of the chip surface is crack or void. Because general inspection method requires many inspection processes, the inspection system which searches immediately and preciselythe defects of the semiconductor chip surface. We propose the inspection method by using the computer vision system. This study presents an image processing algorithm for inspecting the surface defects(crack, void)of the semiconductor test samples. The proposed image processing algorithm aims to reduce inspection time, and to analyze those experienced operator. This paper regards the chip surface as random texture, and deals with the image modeling of randon texture image for searching the surface defects. For texture modeling, we consider the relation of a pixel and neighborhood pixels as noncasul model and extract the statistical characteristics from the radom texture field by using the 2D AR model(Aut oregressive). This paper regards on image as the output of linear system, and considers the fidelity or intelligibility criteria for measuring the quality of an image or the performance of the processing techinque. This study utilizes the variance of prediction error which is computed by substituting the gary level of pixel of another texture field into the two dimensional AR(autoregressive model)model fitted to the texture field, estimate the parameter us-ing the PAA(parameter adaptation algorithm) and design the defect detection filter. Later, we next try to study the defect detection search algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.10
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• pp.843-850
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• 2005

FBA(flux balance analysis) with Boolean rules for representing regulatory events has correctly predicted cellular behaviors, such as optimal flux distribution, maximal growth rate, metabolic by-product, and substrate concentration changes, with various environmental conditions. However, until now, since FBA has not taken into account a hierarchical regulatory network, it has limited the representation of the whole transcriptional regulation mechanism and interactions between specific regulatory proteins and genes. In this paper, in order to solve these problems, we describe the construction of hierarchical regulatory network with defined symbols and the introduction of a weight for representing interactions between symbols. Finally, the whole cellular behaviors with time were simulated through the linkage of a hierarchical regulatory network module and dynamic simulation module including FBA. The central metabolic network of E. coli was chosen as the basic model to identify our suggested modeling method.

• Journal of Korean Society for Quality Management
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• v.30 no.4
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• pp.58-67
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• 2002

Since the inception of off-line quality control, it has drawn a particular attention from research community and it has been implemented in a wide variety of industries mainly due to its extensive applicability to numerous real situations. Emphasizing design issues rather than control issues related to manufacturing processes, off-line quality control has been recognized as a cost-effective approach to quality improvement. It mainly consists of three design stages: system design, parameter design, and tolerance design which are implemented in a sequential manner. Utilizing experimental designs and optimization techniques, off-line quality control is aimed at achieving product performance insensitive to external noises by reducing process variability. In spite of its conceptual soundness and practical significance, however, off-line quality control has also been criticized to a great extent due to its heuristic nature of investigation. In addition, it has also been pointed out that the process optimization procedures are inefficient. To enhance the current practice of off-line quality control, this study proposes an integrated optimization model by utilizing a well-established statistical tool, so called response surface methodology (RSM), and a tolerance - cost relationship.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.11
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• pp.953-960
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• 2015

The thermoforming process has been widely used to manufacture medium- and large-sized plastic parts because of the relatively low cost and high productivity, as compared with other plastic forming processes. One of current salient issues of thermoforming industries is the reduction of trial and error during the production of the thermoformed product. Hence, there is a significant increasing interest in the thermoforming analysis by the thermoforming industries. The goal of this paper is to investigate a methodology of the three-dimensional thermoforming analysis for medium- and large-sized plastic parts. There is a discussion about methodologies of thermoforming analysis, as well as material modeling, and three-dimensional finite element analysis. Furthermore, there is an examination, through case studies, about the applicability of the proposed methodology concerning the thermoforming analysis.

• Human Ecology Research
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• v.57 no.2
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• pp.185-199
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• 2019

This study examined the effects of considered attributes when purchase on consumption attitudes and consumption happiness as well as compared the effects for sensible consumption and sentimental consumption. Data was collected from 373 consumers in 20s and 30s from November 15th to 20th in 2017. IBM SPSS 25.0 was used for basic statistical analyses and for paired t-tests, and lavaan 0.6-3 package and semTools package in R 3.3.3(2017-03-06) was used for structural equation modeling. The results of this study are summarized as follows. First, there were almost no differences in product types between sentimental consumption and sensible consumption. Second, consumption attitudes toward sensible consumption were more positive than sensible consumption; however consumption happiness from sentimental consumption was higher than from sensible consumption. Third, considered attributes when making purchases were divided into subjective, objective, and symbolic with the effects of these attributes on consumption attitudes and consumption happiness analyzed by structural equation modeling. Regardless of sentimental or sensible consumption, objective selection attributes have a positive effect on consumption attitude, but subjective selection attributes have a positive effect on consumption happiness. This study implies that sentimental consumption has a positive value for contemporary consumers and that it should be counted as a feasible consumption activity to enhance consumption happiness.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.91-100
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• 2022

Major developed countries are seriously considering smart factories to increase their manufacturing competitiveness. Smart factory is a customized factory that incorporates ICT in the entire process from product planning to design, distribution and sales. This can reduce production costs and respond flexibly to the consumer market. The smart factory converts physical signals into digital signals, connects machines, parts, factories, manufacturing processes, people, and supply chain partners in the factory to each other, and uses the collected data to enable the smart factory platform to operate intelligently. Enhancing personalized value is the key. Therefore, it can be said that the success or failure of a smart factory depends on whether big data is secured and utilized. Standardized communication and collaboration are required to smoothly acquire big data inside and outside the factory in the smart factory, and the use of big data can be maximized through big data analysis. This study examines big data analysis and standardization in smart factory. Manufacturing innovation by country, smart factory construction framework, smart factory implementation key elements, big data analysis and visualization, etc. will be reviewed first. Through this, we propose services such as big data infrastructure construction process, big data platform components, big data modeling, big data quality management components, big data standardization, and big data implementation consulting that can be suggested when building big data infrastructure in smart factories. It is expected that this proposal can be a guide for building big data infrastructure for companies that want to introduce a smart factory.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.127-130
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• 2022

This paper is a study on singing voice synthesis modeling using a generator loss function, which analyzes various factors that may occur when applying BEGAN among deep learning algorithms optimized for image generation to Audio domain. and we conduct experiments to derive optimal quality. In this paper, we focused the problem that the L1 loss proposed in the BEGAN-based models degrades the meaning of hyperparameter the gamma(𝛾) which was defined to control the diversity and quality of generated audio samples. In experiments we show that our proposed method and finding the optimal values through tuning, it can contribute to the improvement of the quality of the singing synthesis product.

• Journal of Global Scholars of Marketing Science
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• v.20 no.2
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• pp.135-148
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• 2010

Arab boycotts of Danish products, Australian boycotts of French products and Chinese consumer aversion toward Japanese products are all examples of how adverse actions at the country level might impact consumers' behavior. The animosity literature has examined how consumers react to the adverse actions of other countries, and how such animosity impacts consumers' attitudes and preferences for products from the transgressing country. For example, Chinese consumers are less likely to buy Japanese products because of Japanese atrocities during World War II and the unjust economic dealings of the Japanese (Klein, Ettenson and Morris 1998). The marketing literature, however, has not examined how consumers react to adverse actions committed by their own country against other countries, and whether such actions affect their attitudes towards purchasing products that originated from the adversely affected country. The social psychology literature argues that consumers will experience a feeling called collective guilt, in response to such adverse actions. Collective guilt stems from the distress experienced by group members when they accept that their group is responsible for actions that have harmed another group (Branscombe, Slugoski, and Kappenn 2004). Examples include Americans feeling guilty about the atrocities committed by the U.S. military at Abu Ghraib prison (Iyer, Schamder and Lickel 2007), and the Dutch about their occupation of Indonesia in the past (Doosje et al. 1998). The primary aim of this study is to examine consumers' perceptions of adverse actions by members of one's own country against another country and whether such perceptions affected their attitudes towards products originating from the country transgressed against. More specifically, one objective of this study is to examine the perceptual antecedents of collective guilt, an emotional reaction to adverse actions performed by members of one's country against another country. Another objective is to examine the impact of collective guilt on consumers' perceptions of, and preference for, products originating from the country transgressed against by the consumers' own country. If collective guilt emerges as a significant predictor, companies originating from countries that have been transgressed against might be able to capitalize on such unfortunate events. This research utilizes the animosity model introduced by Klein, Ettenson and Morris (1998) and later expanded on by Klein (2002). Klein finds that U.S. consumers harbor animosity toward the Japanese. This animosity is experienced in response to events that occurred during World War II (i.e., the bombing of Pearl Harbor) and more recently the perceived economic threat from Japan. Thus this study argues that the events of Word War II (i.e., bombing of Hiroshima and Nagasaki) might lead U.S. consumers to experience collective guilt. A series of three hypotheses were introduced. The first hypothesis deals with the antecedents of collective guilt. Previous research argues that collective guilt is experienced when consumers perceive that the harm following a transgression is illegitimate and that the country from which the transgressors originate should be responsible for the adverse actions. (Wohl, Branscombe, and Klar 2006). Therefore the following hypothesis was offered: H1a. Higher levels of perceived illegitimacy for the harm committed will result in higher levels of collective guilt. H1b. Higher levels of responsibility will be positively associated with higher levels of collective guilt. The second and third hypotheses deal with the impact of collective guilt on the preferences for Japanese products. Klein (2002) found that higher levels of animosity toward Japan resulted in a lower preference for a Japanese product relative to a South Korean product but not a lower preference for a Japanese product relative to a U.S. product. These results therefore indicate that the experience of collective guilt will lead to a higher preference for a Japanese product if consumers are contemplating a choice that inv olves a decision to buy Japanese versus South Korean product but not if the choice involves a decision to buy a Japanese versus a U.S. product. H2. Collective guilt will be positively related to the preference for a Japanese product over a South Korean product, but will not be related to the preference for a Japanese product over a U.S. product. H3. Collective guilt will be positively related to the preference for a Japanese product over a South Korean product, holding constant product judgments and animosity. An experiment was conducted to test the hypotheses. The illegitimacy of the harm and responsibility were manipulated by exposing respondents to a description of adverse events occurring during World War II. Data were collected using an online consumer panel in the United States. Subjects were randomly assigned to either the low levels of responsibility and illegitimacy condition (n=259) or the high levels of responsibility and illigitemacy (n=268) condition. Latent Variable Structural Equation Modeling (LVSEM) was used to test the hypothesized relationships. The first hypothesis is supported as both the illegitimacy of the harm and responsibility assigned to the Americans for the harm committed against the Japanese during WWII have a positive impact on collective guilt. The second hypothesis is also supported as collective guilt is positively related to preference for a Japanese product over a South Korean product but is not related to preference for a Japanese product over a U.S. product. Finally there is support for the third hypothesis, since collective guilt is positively related to the preference for a Japanese product over a South Korean product while controlling for the effect of product judgments about Japanese products and animosity. The results of these studies lead to several conclusions. First, the illegitimacy of harm and responsibility can be manipulated and that they are antecedents of collective guilt. Second, collective guilt has an impact on a consumers' decision when they face a choice set that includes a product from the country that was the target of the adverse action and a product from another foreign country. This impact however disappears from a consumers' decision when they face a choice set that includes a product from the country that was the target of the adverse action and a domestic product. This result suggests that collective guilt might be a viable factor for company originating from the country transgressed against if its competitors are foreign but not if they are local.

• Korean Journal of Computational Design and Engineering
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• v.9 no.2
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• pp.167-174
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• 2004

As the networks connect the world, enterprises tend to move manufacturing activities into virtual spaces. Since different applications use different data terminology, it becomes a problem to interoperate, interchange, and manage electronic data among different systems. According to RTI, approximately one billion dollar has been being spent yearly for product data exchange and interoperability. As commercial CAD systems have brought in the concept of design feature for the sake of interoperability, terminologies of design feature need to be harmonized. In order to define design feature terminology for integration, knowledge about feature definitions of different CAD systems should be considered. STEP (Standard for the Exchange of Product model data) have attempted to solve this problem, but it defines only syntactic data representation so that semantic data integration is unattainable. In this paper, we utilize the ontology concept to build a data model of design feature which can be a semantic standard of feature definitions of CAD systems. Using feature ontology, we implement an integrated virtual database and a simple system which searches and edits design features in a semantic way. This paper proposes a methodology for integrating modeling features of CAD systems.