• The Journal of Korean Academy of Prosthodontics
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• v.47 no.2
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• pp.156-163
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• 2009

Statement of problem: Recently, there have been increased esthetic needs for posterior dental restorations. The failure of posterior dental ceramic restoration are possible not only by the characters of the component materials but also by the type of food. Purpose: The research aim was to compare the in vitro fracture resistance of simulated first molar crowns fabricated using 4 dental ceramic systems, full-porcelain-occlusal-surfaced PFG, half-porcelain-occlusal-surfaced PFG, Empress 2, Ice Zirkon and selected Korean foods. Material and methods: Eighty axisymmetric crowns of each system were fabricated to fit a preparation with 1.5- to 2.0-mm occlusal reduction. The center of the occlusal surface on each of 15 specimens per ceramic system was axially loaded to fracture in a Instron 4465, and the maximum load(N) was recorded. Afterwards, selected Korean foods specimens(boiled crab, boiled chicken with bone, boiled beef rib, dried squid, dried anchovy, round candy, walnut shell) were prepared. 15 specimens per each food were placed under the Instron and the maximum fracture loads for them were recorded. The 95% confidence intervals of the characteristic failure load were compared between dental ceramic systems and Korean foods. Afterwards, on the basis of previous results, 14Hz cyclic load was applied on the 4 systems of dental ceramic restorations in MTS. The reults were analyzed by analysis of variance and Post Hoc tests. Results: 95% confidence intervals for mean of fracture load 1. full porcelain occlusal surfaced PFG Crown: 2599.3 to 2809.1 N 2. half porcelain occlusal surfaced PFG Crown: 3689.4 to 3819.8 N 3. Ice Zirkon Crown: 1501.2 to 1867.9 N 4. Empress 2 Crown: 803.2 to 1188.5 N 5. boiled crab: 294.1 to 367.9 N 6. boiled chicken with bone: 357.1 to 408.6 N 7. boiled beef rib: 4077.7 to 4356.0 N 8. dried squid: 147.5 to 190.5 N 9. dried anchovy: 35.6 to 46.5 N 10. round candy: 1900.5 to 2615.8 N 11. walnut shell: 85.7 to 373.1 N under cyclic load(14Hz) in MTS, fracture load and masticatory cycles are: 1. full porcelain occlusal surfaced PFG Crown fractured at 95% confidence intervals of 4796.8-9321.2 cycles under 2224.8 N(round candy)load, no fracture under smaller loads. 2. half porcelain occlusal surfaced PFG Crown fractured at 95% confidence intervals of 881705.1-1143565.7 cycles under 2224.8 N(round candy). no fracture under smaller loads. 3. Ice Zirkon Crown fractured at 95% confidence intervlas of 979993.0-1145773.4 cycles under 382.9 N(boiled chicken with bone). no fracture under smaller loads. 4. Empress 2 Crown fractured at 95% confidence intervals of 564.1-954.7 cycles under 382.9 N(boiled chicken with bone). no fracture under smaller loads. Conclusion: There was a significant difference in fracture resistance between experimental groups. Under single load, Korean foods than can cause fracture to the dental ceramic restorations are boiled beef rib and round candy. Even if there is no fracture under single load, cyclic dynamic load can fracture dental posterior ceramic crowns. Experimental data with 14 Hz dynamic cyclic load are obtained as follows. 1. PFG crown(full porcelain occlusion) was failed after mean 0.03 years under fracture load for round candy(2224.8 N). 2. PFG crown(half porcelain occlusion) was failed after mean 4.1 years under fracture load for round candy(2224.8 N). 3. Ice Zirkon crown was failed after mean 4.3 years under fracture load for boiled chicken with bone(382.9 N). 4. Empress 2 crown was failed after mean 0.003 years under fracture load for boiled chicken with bone(382.9 N).

• The Korean Journal of Nuclear Medicine
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• v.38 no.6
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• pp.516-521
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• 2004

Background: Radioactive iodine (RAI) therapy and whole-body scanning are the fundamentals of treatment and follow-up of patients with differentiated thyroid cancer. It is generally accepted that a Thyroid-Stimulating Hormone (TSH) level of at least 30 ${\mu}U/ml$ is a prerequisite for the effective use of RAI, and that it requires 4-6 weeks of off-thyroxine to attain these levels. Because thyroxine withdrawal and the consequent hypothyroidism are often poorly tolerated, and occasionally might be hazardous, it is important to be certain that these assumptions are correct. We have measured serial changes in serum TSH after total thyroidectomy or withdrawl of thyroxine in patients with thyroid cancer. Subjects and Methods: Serum TSH levels were measured weekly after thyroidectomy in 10 patients (group A) and after the discontinuation of thyroxine in 12 patients (group B). Symptoms and signs of hypothyroidism were also evaluated weekly by modified Billewicz diagnostic index. Results: By the second week, 78% of group A patients and 17% of group B patients had serum TSH levels ${\geq}30{\mu}U/ml$. By the third week, 89% of group A patients and 90% of group B patients had serum TSH levels ${\geq}30{\mu}U/ml$. By the fourth week, all patients in two groups achieved target TSH levels and there were no overt hypothyroidism. Conclusion: in all patients, serum TSH elevated to the target concentration (${\geq}30{\mu}U/ml$) within 4 weeks without significant manifestation of hypothyroidism. The schedule of RAI administration could be adjusted to fit the needs and circumstances of individual patients with a shorter preparation period than the conventional.

• Journal of Intelligence and Information Systems
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• v.16 no.2
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• pp.19-32
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• 2010

Volatility plays a central role in both academic and practical applications, especially in pricing financial derivative products and trading volatility strategies. This study presents a novel mechanism based on generalized autoregressive conditional heteroskedasticity (GARCH) models that is able to enhance the performance of intelligent volatility trading systems by predicting Korean stock market volatility more accurately. In particular, we embedded the concept of the volatility asymmetry documented widely in the literature into our model. The newly developed Korean stock market volatility index of KOSPI 200, VKOSPI, is used as a volatility proxy. It is the price of a linear portfolio of the KOSPI 200 index options and measures the effect of the expectations of dealers and option traders on stock market volatility for 30 calendar days. The KOSPI 200 index options market started in 1997 and has become the most actively traded market in the world. Its trading volume is more than 10 million contracts a day and records the highest of all the stock index option markets. Therefore, analyzing the VKOSPI has great importance in understanding volatility inherent in option prices and can afford some trading ideas for futures and option dealers. Use of the VKOSPI as volatility proxy avoids statistical estimation problems associated with other measures of volatility since the VKOSPI is model-free expected volatility of market participants calculated directly from the transacted option prices. This study estimates the symmetric and asymmetric GARCH models for the KOSPI 200 index from January 2003 to December 2006 by the maximum likelihood procedure. Asymmetric GARCH models include GJR-GARCH model of Glosten, Jagannathan and Runke, exponential GARCH model of Nelson and power autoregressive conditional heteroskedasticity (ARCH) of Ding, Granger and Engle. Symmetric GARCH model indicates basic GARCH (1, 1). Tomorrow's forecasted value and change direction of stock market volatility are obtained by recursive GARCH specifications from January 2007 to December 2009 and are compared with the VKOSPI. Empirical results indicate that negative unanticipated returns increase volatility more than positive return shocks of equal magnitude decrease volatility, indicating the existence of volatility asymmetry in the Korean stock market. The point value and change direction of tomorrow VKOSPI are estimated and forecasted by GARCH models. Volatility trading system is developed using the forecasted change direction of the VKOSPI, that is, if tomorrow VKOSPI is expected to rise, a long straddle or strangle position is established. A short straddle or strangle position is taken if VKOSPI is expected to fall tomorrow. Total profit is calculated as the cumulative sum of the VKOSPI percentage change. If forecasted direction is correct, the absolute value of the VKOSPI percentage changes is added to trading profit. It is subtracted from the trading profit if forecasted direction is not correct. For the in-sample period, the power ARCH model best fits in a statistical metric, Mean Squared Prediction Error (MSPE), and the exponential GARCH model shows the highest Mean Correct Prediction (MCP). The power ARCH model best fits also for the out-of-sample period and provides the highest probability for the VKOSPI change direction tomorrow. Generally, the power ARCH model shows the best fit for the VKOSPI. All the GARCH models provide trading profits for volatility trading system and the exponential GARCH model shows the best performance, annual profit of 197.56%, during the in-sample period. The GARCH models present trading profits during the out-of-sample period except for the exponential GARCH model. During the out-of-sample period, the power ARCH model shows the largest annual trading profit of 38%. The volatility clustering and asymmetry found in this research are the reflection of volatility non-linearity. This further suggests that combining the asymmetric GARCH models and artificial neural networks can significantly enhance the performance of the suggested volatility trading system, since artificial neural networks have been shown to effectively model nonlinear relationships.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.95-118
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• 2017

Recent centrally the downtown area, the transaction between the row housing and multiplex housing is activated and platform services such as Zigbang and Dabang are growing. The row housing and multiplex housing is a blind spot for real estate information. Because there is a social problem, due to the change in market size and information asymmetry due to changes in demand. Also, the 5 or 25 districts used by the Seoul Metropolitan Government or the Korean Appraisal Board(hereafter, KAB) were established within the administrative boundaries and used in existing real estate studies. This is not a district classification for real estate researches because it is zoned urban planning. Based on the existing study, this study found that the city needs to reset the Seoul Metropolitan Government's spatial structure in estimating future housing prices. So, This study attempted to classify the area without spatial heterogeneity by the reflected the property price characteristics of row housing and Multiplex housing. In other words, There has been a problem that an inefficient side has arisen due to the simple division by the existing administrative district. Therefore, this study aims to cluster Seoul as a new area for more efficient real estate analysis. This study was applied to the hedonic model based on the real transactions price data of row housing and multiplex housing. And the K-Means Clustering algorithm was used to cluster the spatial structure of Seoul. In this study, data onto real transactions price of the Seoul Row housing and Multiplex Housing from January 2014 to December 2016, and the official land value of 2016 was used and it provided by Ministry of Land, Infrastructure and Transport(hereafter, MOLIT). Data preprocessing was followed by the following processing procedures: Removal of underground transaction, Price standardization per area, Removal of Real transaction case(above 5 and below -5). In this study, we analyzed data from 132,707 cases to 126,759 data through data preprocessing. The data analysis tool used the R program. After data preprocessing, data model was constructed. Priority, the K-means Clustering was performed. In addition, a regression analysis was conducted using Hedonic model and it was conducted a cosine similarity analysis. Based on the constructed data model, we clustered on the basis of the longitude and latitude of Seoul and conducted comparative analysis of existing area. The results of this study indicated that the goodness of fit of the model was above 75 % and the variables used for the Hedonic model were significant. In other words, 5 or 25 districts that is the area of the existing administrative area are divided into 16 districts. So, this study derived a clustering method of row housing and multiplex housing in Seoul using K-Means Clustering algorithm and hedonic model by the reflected the property price characteristics. Moreover, they presented academic and practical implications and presented the limitations of this study and the direction of future research. Academic implication has clustered by reflecting the property price characteristics in order to improve the problems of the areas used in the Seoul Metropolitan Government, KAB, and Existing Real Estate Research. Another academic implications are that apartments were the main study of existing real estate research, and has proposed a method of classifying area in Seoul using public information(i.e., real-data of MOLIT) of government 3.0. Practical implication is that it can be used as a basic data for real estate related research on row housing and multiplex housing. Another practical implications are that is expected the activation of row housing and multiplex housing research and, that is expected to increase the accuracy of the model of the actual transaction. The future research direction of this study involves conducting various analyses to overcome the limitations of the threshold and indicates the need for deeper research.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.35-55
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• 2013

Information technology is a critical resource necessary for any company hoping to support and realize its strategic goals, which contribute to growth promotion and sustainable development. The selection of information technology and its strategic use are imperative for the enhanced performance of every aspect of company management, leading a wide range of companies to have invested continuously in information technology. Despite researchers, managers, and policy makers' keen interest in how information technology contributes to organizational performance, there is uncertainty and debate about the result of information technology investment. In other words, researchers and managers cannot easily identify the independent factors that can impact the investment performance of information technology. This is mainly owing to the fact that many factors, ranging from the internal components of a company, strategies, and external customers, are interconnected with the investment performance of information technology. Using an agent-based simulation technique, this research extracts factors expected to affect investment performance on information technology, simplifies the analyses of their relationship with economic modeling, and examines the performance dependent on changes in the factors. In terms of economic modeling, I expand the model that highlights the way in which product quality moderates the relationship between information technology investments and economic performance (Thatcher and Pingry, 2004) by considering the cost of information technology investment and the demand creation resulting from product quality enhancement. For quality enhancement and its consequences for demand creation, I apply the concept of information quality and decision-maker quality (Raghunathan, 1999). This concept implies that the investment on information technology improves the quality of information, which, in turn, improves decision quality and performance, thus enhancing the level of product or service quality. Additionally, I consider the effect of word of mouth among consumers, which creates new demand for a product or service through the information diffusion effect. This demand creation is analyzed with an agent-based simulation model that is widely used for network analyses. Results show that the investment on information technology enhances the quality of a company's product or service, which indirectly affects the economic performance of that company, particularly with regard to factors such as consumer surplus, company profit, and company productivity. Specifically, when a company makes its initial investment in information technology, the resultant increase in the quality of a company's product or service immediately has a positive effect on consumer surplus, but the investment cost has a negative effect on company productivity and profit. As time goes by, the enhancement of the quality of that company's product or service creates new consumer demand through the information diffusion effect. Finally, the new demand positively affects the company's profit and productivity. In terms of the investment strategy for information technology, this study's results also reveal that the selection of information technology needs to be based on analysis of service and the network effect of customers, and demonstrate that information technology implementation should fit into the company's business strategy. Specifically, if a company seeks the short-term enhancement of company performance, it needs to have a one-shot strategy (making a large investment at one time). On the other hand, if a company seeks a long-term sustainable profit structure, it needs to have a split strategy (making several small investments at different times). The findings from this study make several contributions to the literature. In terms of methodology, the study integrates both economic modeling and simulation technique in order to overcome the limitations of each methodology. It also indicates the mediating effect of product quality on the relationship between information technology and the performance of a company. Finally, it analyzes the effect of information technology investment strategies and information diffusion among consumers on the investment performance of information technology.

• Korean Journal of Heritage: History & Science
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• v.44 no.1
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• pp.196-221
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• 2011

The Royal Private Shrines or the Samyo(私廟), were dedicated to members of Choseon's royal family who could not be enshrined at the (official) Royal Ancestral Shrine, the Jongmyo(宗廟). The Samyo were constructed at the national level and were systematically managed as such. Because these private Shrines were dedicated to those who couldn't belong to the Jongmyo but were still very important, such as the ruling king's biological father or mother. The details of all royal constructions were included in the State Event Manuals, and with them, the two-dimensional layouts of the Samyo also. From the remaining "Hyunsa-gung Private Tomb Construction Layout Record(顯思宮別廟營建都監儀軌)" of 1824, which is the construction record of Gyeongwoo-gung Shrine(景祐宮) dedicated to Subin, the mother of King Sunjo(純祖), it became possible to investigate the so far unknown "The Painting of Gyeongwoo-gung Shrine", in terms of the year produced, materials used and other situational contexts. The investigation revealed that the "The Painting of Gyeongwoo-gung Shrine" is actually the "Hyunsa-gung Private Tomb Layout" produced by the Royal Construction Bureau. The bureau painted this to build Hyunsa-gung Private Shrine in a separately prepared site outside the court in 1824, according to the royal verdict to close down and move the temporary shrine inside the courtyard dedicated to Subin who had passed away in 1822. As the Construction Bureau must have also produced the Gyeongwoo-gung Shrine Layout, the painter(s) of this layout should exist among the official artists listed in the State Event Manual, but sadly, as their paintings have not survived to this day, we cannot compare their painting styles. The biggest stylistic character of the Painting of Gyeongwoo-gung Shrine is its perfect diagonal composition method and detailed and neat portrayalof the many palace buildings, just as seen in Donggwoldo(東闕圖, Painting of a panoramic view for Changdeokgung and Changgyeonggung Palaces). A well-perceiving architectural painting employs a specific point of view chosen to fit the purpose of the painting, or it can opt to the multi-viewpoint. Korean traditional architectural paintings in early ages utilized the diagonal composition method, the bird-eye viewpoint, or the multi-viewpoint. By the 18th century, detailed but also artistic architectural paintings utilizing the diagonal method are observed. In the early 19th century, the peak of such techniques is exhibited in Donggwoldo(Painting of a panoramic view for Changdeokgung and Changgyeonggung Palaces). From the perfect diagonal composition method employed and the details of the palace buildings numbering almost two hundreds, we can determine that the Painting of Gyeongwoo-gung Shrine also belongs to the same category of the highly technical architectural paintings as Donggwoldo(Painting of a panoramic view for Changdeokgung and Changgyeonggung Palaces). We can also confirm this hypothesis by comparing the painting techniques employed in these two paintings in detailthe way trees and houses are depicted, and the way ground texture is expressed, etc. The unique characteristic of the Painting of Gyeongwoo-gung Shrine is, however, that the area surrounding the central shrine building(正堂), the most important area of the shrine, is drawn using not the diagonal method but the bird-eye viewpoint with the buildings lying flat on both the left and right sides, just as seen in the "Buildings Below the Central Shrine(正堂以下諸處)" in the State Event Manual's Painting Method section. The same viewpoint method is discovered in some other concurrent paintings of common residential buildings, so it is not certain that this particular viewpoint had been a distinctive feature for shrine paintings in general. On the other hand, when the diagonalmethod pointing to the left direction is chosen, the top-left and bottom-right sections of the painting become inevitably empty. This has been the case for the Painting of Gyeongwoo-gung Shrine, but in contrast, Donggwoldo shows perfect screen composition with these empty margins filled up with different types of trees and other objects. Such difference is consistent with the different situational contexts of these two paintings: the Painting of Gyeongwoo-gung Shrine is a simple single-sheet painting, while Donggwoldo is a perfected work of painting book given an official title. Therefore, if Donggwoldo was produced to fulfill the role of depiction and documentation as well as the aesthetic purpose, contrastingly, the Painting of Gyeongwoo-gung Shrine only served the purpose of copying the circumstances of the architecture and projecting them onto the painting.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.179-196
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• 2019

Recently, the "Smart Consumer" has been emerging. He or she is increasingly inclined to search for and purchase products by taking into account personal judgment or expert reviews rather than by relying on information delivered through manufacturers' advertising. This is especially true when purchasing cosmetics. Because cosmetics act directly on the skin, consumers respond seriously to dangerous chemical elements they contain or to skin problems they may cause. Above all, cosmetics should fit well with the purchaser's skin type. In addition, changes in global cosmetics consumer trends make it necessary to study this field. The desire to find one's own individualized cosmetics is being revealed to consumers around the world and is known as "Finding the Holy Grail." Many consumers show a deep interest in customized cosmetics with the cultural boom known as "K-Beauty" (an aspect of "Han-Ryu"), the growth of personal grooming, and the emergence of "self-culture" that includes "self-beauty" and "self-interior." These trends have led to the explosive popularity of cosmetics made in Korea in the Chinese and Southeast Asian markets. In order to meet the customized cosmetics needs of consumers, cosmetics manufacturers and related companies are responding by concentrating on delivering premium services through the convergence of ICT(Information, Communication and Technology). Despite the evolution of companies' responses regarding market trends toward customized cosmetics, there is no "Intelligent Data Platform" that deals holistically with consumers' skin condition experience and thus attaches emotions to products and services. To find the Holy Grail of customized cosmetics, it is important to acquire and analyze consumer data on what they want in order to address their experiences and emotions. The emotions consumers are addressing when purchasing cosmetics varies by their age, sex, skin type, and specific skin issues and influences what price is considered reasonable. Therefore, it is necessary to classify emotions regarding cosmetics by individual consumer. Because of its importance, consumer emotion analysis has been used for both services and products. Given the trends identified above, we judge that consumer emotion analysis can be used in our study. Therefore, we collected and indexed data on consumers' emotions regarding their cosmetics experiences focusing on consumers' language. We crawled the cosmetics emotion data from SNS (blog and Twitter) according to sales ranking ($1^{st}$ to $99^{th}$), focusing on the ample/serum category. A total of 357 emotional adjectives were collected, and we combined and abstracted similar or duplicate emotional adjectives. We conducted a "Consumer Sentiment Journey" workshop to build a "Consumer Sentiment Dictionary," and this resulted in a total of 76 emotional adjectives regarding cosmetics consumer experience. Using these 76 emotional adjectives, we performed clustering with the Self-Organizing Map (SOM) method. As a result of the analysis, we derived eight final clusters of cosmetics consumer sentiments. Using the vector values of each node for each cluster, the characteristics of each cluster were derived based on the top ten most frequently appearing consumer sentiments. Different characteristics were found in consumer sentiments in each cluster. We also developed a cosmetics experience pattern map. The study results confirmed that recommendation and classification systems that consider consumer emotions and sentiments are needed because each consumer differs in what he or she pursues and prefers. Furthermore, this study reaffirms that the application of emotion and sentiment analysis can be extended to various fields other than cosmetics, and it implies that consumer insights can be derived using these methods. They can be used not only to build a specialized sentiment dictionary using scientific processes and "Design Thinking Methodology," but we also expect that these methods can help us to understand consumers' psychological reactions and cognitive behaviors. If this study is further developed, we believe that it will be able to provide solutions based on consumer experience, and therefore that it can be developed as an aspect of marketing intelligence.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.23-46
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• 2021

Collaborative filtering, which is often used in personalization recommendations, is recognized as a very useful technique to find similar customers and recommend products to them based on their purchase history. However, the traditional collaborative filtering technique has raised the question of having difficulty calculating the similarity for new customers or products due to the method of calculating similaritiesbased on direct connections and common features among customers. For this reason, a hybrid technique was designed to use content-based filtering techniques together. On the one hand, efforts have been made to solve these problems by applying the structural characteristics of social networks. This applies a method of indirectly calculating similarities through their similar customers placed between them. This means creating a customer's network based on purchasing data and calculating the similarity between the two based on the features of the network that indirectly connects the two customers within this network. Such similarity can be used as a measure to predict whether the target customer accepts recommendations. The centrality metrics of networks can be utilized for the calculation of these similarities. Different centrality metrics have important implications in that they may have different effects on recommended performance. In this study, furthermore, the effect of these centrality metrics on the performance of recommendation may vary depending on recommender algorithms. In addition, recommendation techniques using network analysis can be expected to contribute to increasing recommendation performance even if they apply not only to new customers or products but also to entire customers or products. By considering a customer's purchase of an item as a link generated between the customer and the item on the network, the prediction of user acceptance of recommendation is solved as a prediction of whether a new link will be created between them. As the classification models fit the purpose of solving the binary problem of whether the link is engaged or not, decision tree, k-nearest neighbors (KNN), logistic regression, artificial neural network, and support vector machine (SVM) are selected in the research. The data for performance evaluation used order data collected from an online shopping mall over four years and two months. Among them, the previous three years and eight months constitute social networks composed of and the experiment was conducted by organizing the data collected into the social network. The next four months' records were used to train and evaluate recommender models. Experiments with the centrality metrics applied to each model show that the recommendation acceptance rates of the centrality metrics are different for each algorithm at a meaningful level. In this work, we analyzed only four commonly used centrality metrics: degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality. Eigenvector centrality records the lowest performance in all models except support vector machines. Closeness centrality and betweenness centrality show similar performance across all models. Degree centrality ranking moderate across overall models while betweenness centrality always ranking higher than degree centrality. Finally, closeness centrality is characterized by distinct differences in performance according to the model. It ranks first in logistic regression, artificial neural network, and decision tree withnumerically high performance. However, it only records very low rankings in support vector machine and K-neighborhood with low-performance levels. As the experiment results reveal, in a classification model, network centrality metrics over a subnetwork that connects the two nodes can effectively predict the connectivity between two nodes in a social network. Furthermore, each metric has a different performance depending on the classification model type. This result implies that choosing appropriate metrics for each algorithm can lead to achieving higher recommendation performance. In general, betweenness centrality can guarantee a high level of performance in any model. It would be possible to consider the introduction of proximity centrality to obtain higher performance for certain models.

• Korean Journal of Heritage: History & Science
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• v.55 no.2
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• pp.200-211
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• 2022

The celadon stools with an openwork ring design which consist of four items as one collection were excavated from Gaeseong, Gyeonggi-do Province. The celadon stools were designated and managed as treasures due to their high arthistorical value in the form of demonstrating the excellence of celadon manufacturing techniques and the fanciful lifestyles during the Goryeo Dynasty. However, one of the items, which appeared to have been repaired and restored in the past, suffered a decline in aesthetic value due to the aging of the treatment materials and the lack of skill on the part of the conservator, raising the need for re-treatment as a result of structural instability. An examination of the conservation condition prior to conservation treatment found structural vulnerabilities because physical damage had been artificially inflicted throughout the area that was rendered defective at the time of manufacturing. The bonded surfaces for the cracked areas and detached fragments did not fit, and these areas and fragments had deteriorated because the adhesive trickled down onto the celadon surface or secondary contaminants, such as dust, were on the adhesive surface. The study identified the position, scope, and conditions of the bonded areas at the cracks UV rays and microscopy in order to investigate the condition of repair and restoration. By conducting Fourier-transform infrared spectroscopy(FT-IR) and portable x-ray fluorescence spectroscopy on the materials used for the former conservation treatment, the study confirmed the use of cellulose resins and epoxy resins as adhesives. Furthermore, the analysis revealed the addition of gypsum(CaSO₄·2H₂O) and bone meal(Ca₁₀ (PO₄)₆(OH)₂) to the adhesive to increase the bonding strength of some of the bonded areas that sustained force. Based on the results of the investigation, the conservation treatment for the artifact would focus on completely dismantling the existing bonded areas and then consolidating vulnerable areas through bonding and restoration. After removing and dismantling the prior adhesive used, the celadon stool was separated into 6 large fragments including the top and bottom, the curved legs, and some of the ring design. After dismantling, the remaining adhesive and contaminants were chemically and physically removed, and a steam cleaner was used to clean the fractured surfaces to increase the bonding efficacy of the re-bonding. The bonding of the artifact involved applying the adhesive differently depending on the bonding area and size. The cyanoacrylate resin Loctite 401 was used on the bonding area that held the positions of the fragments, while the acrylic resin Paraloid B-72 20%(in xylene) was treated on cross sections for reversibility in the areas that provided structural stability before bonding the fragments using the epoxy resin Epo-tek 301-2. For areas that would sustain force, as in the top and bottom, kaolin was added to Epo-tek 301-2 in order to reinforce the bonding strength. For the missing parts of the ring design where a continuous pattern could be assumed, a frame was made using SN-sheets, and the ring design was then modeled and restored by connecting the damaged cross section with Wood epos. Other restoration areas that occurred during bonding were treated by being filled with Wood epos for aesthetic and structural stabilization. Restored and filled areas were color-matched to avoid the feeling of disharmony from differences of texture in case of exhibitions in the future. The investigation and treatment process involving a variety of scientific technology was systematically documented so as to be utilized as basic data for the conservation and maintenance.

• Asia Marketing Journal
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• v.14 no.2
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• pp.157-176
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• 2012

Brand switching data frequently used in market structure analysis is adequate to analyze non- durable goods, because it can capture competition between specific two brands. But brand switching data sometimes can not be used to analyze goods like automobiles having long term duration because one of main assumptions that consumer preference toward brand attributes is not changed against time can be violated. Therefore a new type of data which can precisely capture competition among durable goods is needed. Another problem of using brand switching data collected from actual purchase behavior is short of explanation why consumers consider different set of brands. Considering above problems, main purpose of this study is to analyze market structure for durable goods with consideration set. The author uses exploratory approach and latent class clustering to identify market structure based on heterogeneous consideration set among consumers. Then the relationship between some factors and consideration set formation is analyzed. Some benefits and two demographic variables - age and income - are selected as factors based on consumer behavior theory. The author analyzed USA automotive market with top 11 brands using exploratory approach and latent class clustering. 2,500 respondents are randomly selected from the total sample and used for analysis. Six models concerning market structure are established to test. Model 1 means non-structured market and model 6 means market structure composed of six sub-markets. It is exploratory approach because any hypothetical market structure is not defined. The result showed that model 1 is insufficient to fit data. It implies that USA automotive market is a structured market. Model 3 with three market structures is significant and identified as the optimal market structure in USA automotive market. Three sub markets are named as USA brands, Asian Brands, and European Brands. And it implies that country of origin effect may exist in USA automotive market. Comparison between modal classification by derived market structures and probabilistic classification by research model was conducted to test how model 3 can correctly classify respondents. The model classify 97% of respondents exactly. The result of this study is different from those of previous research. Previous research used confirmatory approach. Car type and price were chosen as criteria for market structuring and car type-price structure was revealed as the optimal structure for USA automotive market. But this research used exploratory approach without hypothetical market structures. It is not concluded yet which approach is superior. For confirmatory approach, hypothetical market structures should be established exhaustively, because the optimal market structure is selected among hypothetical structures. On the other hand, exploratory approach has a potential problem that validity for derived optimal market structure is somewhat difficult to verify. There also exist market boundary difference between this research and previous research. While previous research analyzed seven car brands, this research analyzed eleven car brands. Both researches seemed to represent entire car market, because cumulative market shares for analyzed brands exceeds 50%. But market boundary difference might affect the different results. Though both researches showed different results, it is obvious that country of origin effect among brands should be considered as important criteria to analyze USA automotive market structure. This research tried to explain heterogeneity of consideration sets among consumers using benefits and two demographic factors, sex and income. Benefit works as a key variable for consumer decision process, and also works as an important criterion in market segmentation. Three factors - trust/safety, image/fun to drive, and economy - are identified among nine benefit related measure. Then the relationship between market structures and independent variables is analyzed using multinomial regression. Independent variables are three benefit factors and two demographic factors. The result showed that all independent variables can be used to explain why there exist different market structures in USA automotive market. For example, a male consumer who perceives all benefits important and has lower income tends to consider domestic brands more than European brands. And the result also showed benefits, sex, and income have an effect to consideration set formation. Though it is generally perceived that a consumer who has higher income is likely to purchase a high priced car, it is notable that American consumers perceived benefits of domestic brands much positive regardless of income. Male consumers especially showed higher loyalty for domestic brands. Managerial implications of this research are as follow. Though implication may be confined to the USA automotive market, the effect of sex on automotive buying behavior should be analyzed. The automotive market is traditionally conceived as male consumers oriented market. But the proportion of female consumers has grown over the years in the automotive market. It is natural outcome that Volvo and Hyundai motors recently developed new cars which are targeted for women market. Secondly, the model used in this research can be applied easier than that of previous researches. Exploratory approach has many advantages except difficulty to apply for practice, because it tends to accompany with complicated model and to require various types of data. The data needed for the model in this research are a few items such as purchased brands, consideration set, some benefits, and some demographic factors and easy to collect from consumers.