• Information Systems Review
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• v.25 no.4
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• pp.131-159
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• 2023

Recently, amidst the backdrop of the COVID-19 pandemic shifting towards an endemic phase, there has been a rise in discussions and debates about the future of the metaverse. Simultaneously, major metaverse platforms like Roblox have been launching services integrated with generative AI, and Apple's mixed reality hardware, Vision Pro, has been announced, creating new expectations for the metaverse. In this situation where the outlook for the metaverse is divided, it is crucial to diagnose the metaverse from an ecosystem perspective, examine its key ecological features, driving forces for development, and future possibilities for advancement. This study utilized Wang's (2021) Information Ecology Theory (IET) framework, which is representative of ecosystem research in the field of Information Systems (IS), to derive the Metaverse Industrial Ecosystem (MIE). The analysis revealed that the MIE consists of four main domains: Tech Landscape, Category Ecosystem, Metaverse Platform, and Product/Service Ecosystem. It was found that the MIE exhibits characteristics such as digital connectivity, the integration of real and virtual worlds, value creation capabilities, and value sharing (Web 3.0). Furthermore, the interactions among the domains within the MIE and the four characteristics of the ecosystem were identified as driving forces for the development of the MIE at an ecosystem level. Additionally, the development of the MIE at an ecosystem level was categorized into three distinct stages: Narrow Ecosystem, Expanded Ecosystem, and Everywhere Ecosystem. It is anticipated that future advancements in related technologies and industries, such as robotics, AI, and 6G, will promote the transition from the current Expanded Ecosystem level of the MIE to an Everywhere Ecosystem level, where the connection between the real and virtual worlds is pervasive. This study provides several implications. Firstly, it offers a foundational theory and analytical framework for ecosystem research, addressing a gap in previous metaverse studies. It also presents various research topics within the metaverse domain. Additionally, it establishes an academic foundation that integrates concept definition research and impact studies, which are key areas in metaverse research. Lastly, referring to the developmental stages and conditions proposed in this study, businesses and governments can explore future metaverse markets and related technologies. They can also consider diverse metaverse business strategies. These implications are expected to guide the exploration of the emerging metaverse market and facilitate the evaluation of various metaverse business strategies.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.205-225
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• 2018

Convolutional Neural Network (ConvNet) is one class of the powerful Deep Neural Network that can analyze and learn hierarchies of visual features. Originally, first neural network (Neocognitron) was introduced in the 80s. At that time, the neural network was not broadly used in both industry and academic field by cause of large-scale dataset shortage and low computational power. However, after a few decades later in 2012, Krizhevsky made a breakthrough on ILSVRC-12 visual recognition competition using Convolutional Neural Network. That breakthrough revived people interest in the neural network. The success of Convolutional Neural Network is achieved with two main factors. First of them is the emergence of advanced hardware (GPUs) for sufficient parallel computation. Second is the availability of large-scale datasets such as ImageNet (ILSVRC) dataset for training. Unfortunately, many new domains are bottlenecked by these factors. For most domains, it is difficult and requires lots of effort to gather large-scale dataset to train a ConvNet. Moreover, even if we have a large-scale dataset, training ConvNet from scratch is required expensive resource and time-consuming. These two obstacles can be solved by using transfer learning. Transfer learning is a method for transferring the knowledge from a source domain to new domain. There are two major Transfer learning cases. First one is ConvNet as fixed feature extractor, and the second one is Fine-tune the ConvNet on a new dataset. In the first case, using pre-trained ConvNet (such as on ImageNet) to compute feed-forward activations of the image into the ConvNet and extract activation features from specific layers. In the second case, replacing and retraining the ConvNet classifier on the new dataset, then fine-tune the weights of the pre-trained network with the backpropagation. In this paper, we focus on using multiple ConvNet layers as a fixed feature extractor only. However, applying features with high dimensional complexity that is directly extracted from multiple ConvNet layers is still a challenging problem. We observe that features extracted from multiple ConvNet layers address the different characteristics of the image which means better representation could be obtained by finding the optimal combination of multiple ConvNet layers. Based on that observation, we propose to employ multiple ConvNet layer representations for transfer learning instead of a single ConvNet layer representation. Overall, our primary pipeline has three steps. Firstly, images from target task are given as input to ConvNet, then that image will be feed-forwarded into pre-trained AlexNet, and the activation features from three fully connected convolutional layers are extracted. Secondly, activation features of three ConvNet layers are concatenated to obtain multiple ConvNet layers representation because it will gain more information about an image. When three fully connected layer features concatenated, the occurring image representation would have 9192 (4096+4096+1000) dimension features. However, features extracted from multiple ConvNet layers are redundant and noisy since they are extracted from the same ConvNet. Thus, a third step, we will use Principal Component Analysis (PCA) to select salient features before the training phase. When salient features are obtained, the classifier can classify image more accurately, and the performance of transfer learning can be improved. To evaluate proposed method, experiments are conducted in three standard datasets (Caltech-256, VOC07, and SUN397) to compare multiple ConvNet layer representations against single ConvNet layer representation by using PCA for feature selection and dimension reduction. Our experiments demonstrated the importance of feature selection for multiple ConvNet layer representation. Moreover, our proposed approach achieved 75.6% accuracy compared to 73.9% accuracy achieved by FC7 layer on the Caltech-256 dataset, 73.1% accuracy compared to 69.2% accuracy achieved by FC8 layer on the VOC07 dataset, 52.2% accuracy compared to 48.7% accuracy achieved by FC7 layer on the SUN397 dataset. We also showed that our proposed approach achieved superior performance, 2.8%, 2.1% and 3.1% accuracy improvement on Caltech-256, VOC07, and SUN397 dataset respectively compare to existing work.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.52 no.3
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• pp.239-248
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• 2007

Although high nutritional values and continuous identification of important functional substances of soybean [Glycine max (L.) Merrill.] promote consumption of soybean products worldwide, informations on quality of brand soybean is not enough for consumers. Total of 100 brand soybeans [32 for soypaste and source, 45 black testa (lage), and 17 black testa (small) or medicinal soybean and beansprout soybean] were collected at supermarkets and several external quality factors were analyzed. Brand soybeans were marked with the environmental friendly and intimating words along with soybean (white or yellow), black soybean (black-, frost-, late frost-, green or inner-green-), medicinal soybean and beansprout soybean. Among 100 brand soybeans 30% was 1 kg package and 59% was 500 g package, difference between printed and actual weights of 70% brand soybeans was ${\pm}1%$ and weights of 2/3 of brand soybeans were higher than printed weight. Range of 100 seed weights of soypaste and source, black testa (large) and black testa (small) and beansprout soybeans were $23.7{\sim}47.8g$, $21.9{\sim}44.5g$ and $9.5{\sim}15.0g$, respectively. Although ranges of 100 seed weights of soypaste and source and black testa (large) soybeans were similar, 63% of soypaste and source were less than 29 g, while 78% of black testa (large) soybeans were higher than 30 g. Although average and highest percentages of seeds separated with 6.7 mm sieve were similar with 87.4% and 99.9% for soypaste and source soybean and 86.5% and 99.5% for black testa (large) soybean, respectively, the lowest percentages were 70.7% for soypaste and source soybean and 14.4% for black testa (large) soybean. When 100 seed weight was greater than 35 g, 90% of seeds were remained on 6.7 mm sieve. On the other hand 100 g weight and percentage of seeds remained on 6.7 mm sieve showed significantly positive correlations [r=0.7488** for soypaste and source soybean and r=0.7874** for black testa (large) soybean when 100 seed weight was $20{\sim}30g$. Based on hilum color and/or appearance, 76% of brand soybeans collected (more than 90% in yellow testa soybeans) were found to be mixed more than 10% with other cultivars or landraces. Foreign materials such as sand, piece of clothe, wood piece, dead insects, other soybeans were found in 20% of brand soybeans. Average test weight of brand soybeans was 762g $L^{-1}$ with a range of $645{\sim}820g\;L^{-1}$. Soybeans from local markets were as good as brand soybeans in 100 seed weight, uniformity of seeds, weight of foreign materials and test weight.

• Economic and Environmental Geology
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• v.40 no.5
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• pp.635-649
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• 2007

Geochemical composition, stable isotopes $({\delta}^{18}O,\;{\delta}D,\;{\delta}^{34}S)$ and noble gases(He, Ne and Ar) of nine hot spring water and three groundwater for five hot springs(Jukam, Hwasun, Dokog, Jirisan, Beunsan) from the Honam area were analyzed to investigate the hydrogeochemical characteristics and the hydrogeochemical evolution of the hot spring waters, and to interpret the source of sulfur, helium and argon dissolved in the hot spring waters. The hot spring waters show low water temperature ranging from 23.0 to $30.5^{\circ}C$ and alkaline characteristics of pH 7.67 to 9.98. Electrical conductivity of hot spring waters is $153{\sim}746{\mu}S/cm$. Groundwaters in this area were characterized by the acidic to neutral pH range$(5.85{\sim}7.21)$, the wide electrical conductivity range $(44{\sim}165{\mu}S/cm)$. The geochemical compositions of hot spring and groundwaters can be divided into three water types: (1) $Na-HCO_3$ water type, (2) Na-Cl water type and (3) $Ca-HCO_3$ water type. The hot spring water of $Ca-HCO_3$ water type in early stage have been evolved through $Ca(Na)-HCO_3$ water type into $Na-HCO_3$ type in final stage. In particular, Jurim alkaline(pH 9.98) hot spring water plotted at the end point of $Na-HCO_3$ type in the Piper diagram is likely to arrive into the final stage in geochemical evolution process. Hydrogen and oxygen isotopic data of the hot spring water samples indicate that the hot spring waters originated from the local meteoric water showing latitude and altitude effects. The ${\delta}^{34}S$ value for sulfate of the hot spring waters varies widely from 0.5 to $25.9%o$. The sulfur source of most hot spring waters in this area is igneous origin. However, The ${\delta}^{34}S$ also indicates the sulfur of JR1 hot water is originated from marine sulfur which might be derived ken ancient seawater sulfates. The $^3He/^4He\;and\;^4He/^{20}Ne$ ratios of the hot spring waters range from $0.0143{\times}10^{-6}\;to\;0.407{\times}10^{-6}\;and\;6.49{\sim}584{\times}10^{-6}$, respectively. The hot spring waters are plotted on the mixing line between air and crustal components. It means that the He gas in the hot spring waters was mainly originated from crustal sources. However, the JR1 hot spring water show a little mixing ratio of the helium gas of mantle source. The $^{40}Ar/^{36}Ar$ ratios of hot spring water are in the range from $292.3{\times}10^{-6}\;to\;304.1{\times}10^{-6}$, implying the atmospheric argon source.

• Journal of Global Scholars of Marketing Science
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• v.18 no.3
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• pp.89-114
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• 2008

Most of the extant studies on communication effects have been devoted to the typical issue, "what types of communication activities are more effective for brand awareness or brand attitudes?" However, little research has addressed another question on communication decisions, "what makes communication activities less effective?" Our study focuses on factors negatively influenced on the efficiency of communication activities, especially of Advertising. Some studies have introduced concepts closely related to our topic such as consumer confusion, brand confusion, or belief confusion. Studies on product belief confusion have found some factors misleading consumers to misunderstand the physical features of products. Studies on brand confusion have uncovered factors making consumers confused on brand names. Studies on advertising confusion have tested the effects of ad models' employed by many other firms for different products on communication efficiency. We address a new concept, Ad noises, which are any factors interfering with consumers exposed to a particular advertisement in understanding messages provided by advertisements. The objective of this study is to understand the effects of ad noises caused by ad models on brand awareness and brand attitude. There are many different types of AD noises. Particularly, we study the effects of AD noises generated from ad model selection decision. Many companies want to employ celebrities as AD models while the number of celebrities who command a high degree of public and media attention are limited. Inevitably, several firms have been adopting the same celebrities as their AD models for different products. If the same AD model is adopted for TV commercials for different products, consumers exposed to those TV commercials are likely to fail to be aware of the target brand due to interference of TV commercials, for other products, employing the same AD model. This is an ad noise caused by employing ad models who have been exposed to consumers in other advertisements, which is the first type of ad noises studied in this research. Another type of AD noises is related to the decision of AD model replacement for the same product advertising. Firms sometimes launch another TV commercial for the same products. Some firms employ the same AD model for the new TV commercial for the same product and other firms employ new AD models for the new TV commercials for the same product. The typical problem with the replacement of AD models is the possibility of interfering with consumers in understanding messages of the TV commercial due to the dissimilarity of the old and new AD models. We studied the effects of these two types of ad noises, which are the typical factors influencing on the effect of communication: (1) ad noises caused by employing ad models who have been exposed to consumers in other advertisements and (2) ad noises caused by changing ad models with different images for same products. First, we measure the negative influence of AD noises on brand awareness and attitudes, in order to provide the importance of studying AD noises. Furthermore, our study unveiled the mediating conditions(variables) which can increase or decrease the effects of ad noises on brand awareness and attitudes. We study the effects of three mediating variables for ad noises caused by employing ad models who have been exposed to consumers in other advertisements: (1) the fit between product image and AD model image, (2) similarity between AD model images in multiple TV commercials employing the same AD model, and (3) similarity between products of which TV commercial employed the same AD model. We analyze the effects of another three mediating variables for ad noises caused by changing ad models with different images for same products: (1) the fit of old and new AD models for the same product, (2) similarity between AD model images in old and new TV commercials for the same product, and (3) concept similarity between old and new TV commercials for the same product. We summarized the empirical results from a field survey as follows. The employment of ad models who have been used in advertisements for other products has negative effects on both brand awareness and attitudes. our empirical study shows that it is possible to reduce the negative effects of ad models used for other products by choosing ad models whose images are relevant to the images of target products for the advertisement, by requiring ad models of images which are different from those of ad models in other advertisements, or by choosing ad models who have been shown in advertisements for other products which are not similar to the target product. The change of ad models for the same product advertisement can positively influence on brand awareness but positively on brand attitudes. Furthermore, the effects of ad model change can be weakened or strengthened depending on the relevancy of new ad models, the similarity of previous and current ad models, and the consistency of the previous and current ad messages.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.10
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• pp.1-43
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• 1971

Experiment I: The objective of this study was to know variation in some selected agronomic characters of sweet sorghum when planted in several growing seasons. The 17 different sweet sorghum varieties having various maturities, and plant, syrup and sugar types were used in this study which had been carried out for the period of two years from 1968 to 1969 at Industrial Crops Division of Crop Experiment Station in Suwon. These varieties were planted at an interval of 20 days from April 5 to August 25 both in 1968 and 1969. The experimental results could be summarized as follows: 1. As planting was made early, the number of days from sowing to germination was getting prolonged while germination took place early when planted at the later date of which air temperature was relatively higher. However, such a tendency was not observed beyond the planting on August 25. In general, a significant negative correlation was found between the number of days from sowing to germination and the average daily temperature but a positive correlation was found between the former and the total accumulated average temperature during the growth period. 2. The period from sowing to heading was generally shortened as planting was getting delayed. The average varietal difference in number of days from sowing to heading was as much as 30.2 days. All the varieties were grouped into early-, medium and late-maturing groups based upon a difference of 10 days in heading. The average number of days from sowing to heading was 78.5$\pm$4.5 days in the early-maturing varieties, 88.5$\pm$4.5 days in the medium varieties and 98.5$\pm$4.5 days in the late-maturing varieties, respectively. The early-maturing varieties had the shortest period to heading when planted from July 15 to August 5, the medium varieties did when planted before July 15 and the late-maturing varieties did when planted before June 5. 3. The relationship between the sowing date (x) and number of days from sowing to heading could be expressed in an equation of y=a+bx. A highly positive correlation was found between the coefficient of the equation(shortening rate in heading time) and the average number of days from sowing to heading. 4. The number of days from sowing to heading was shortened as the daily average temperature during the growth period was getting higher. Early-maturing varieties had the shortest period to heading at a temperature of 24.2$^{\circ}C$, medium varieties at 23.8$^{\circ}C$ and late-maturing varieties at 22.9$^{\circ}C$, respectively. In other words, the number of days from sowing to heading was shortened rapidly in case that the average temperature for 30 days before heading was 22$^{\circ}C$ to $25^{\circ}C$. It prolonged relatively when the temperature was lower than 21$^{\circ}C$. 5. There was a little difference in plant height among varieties. In case of early planting, no noticeable difference in the height was observed. The plant height shortened generally as planting season was delayed. Elongation of plant height was remarkably accelerated as planting was delayed. This tendency was more pronounced in case of early-maturing varieties rather than late-maturing varieties. As a result, the difference in plant height between the maximum and the minimum was greater in late-maturing varieties than in early-maturing varieties. 6. Diameter of the stalk was getting thicker as planted earlier in late-maturing varieties. On the other hand, medium or early-maturing varieties had he thickest diameter when they were planted on April 25. 7. In general, a higher stalk yield was obtained when planted from April 25 to May 15. However, the planting time for the maximum stalk yield varied from one variety to another depending upon maturity of variety. Ear]y-maturing varieties produced the maximum yield when planted about April 25, medium varieties from April 25 to May 15 and late-maturing varieties did when planted from April 5 to May 15 respectively. The yield decreased linearly when they were planted later than the above dates. 8. A varietal difference in Brix % was also observed. The Brix % decreased linearly when the varieties were planted later than May 15. Therefore, a highly negative relationship between planting date(x) and Brix %(y) was detected. 9. The Brix % during 40 to 45 days after leading was the highest at the 1st to the 3rd internodes from the top while it decreased gradually from the 4th internode. It increased again somewhat at the 2nd internode from the ground level. However, it showed a reverse relationship between the Brix % and position of internode before heading. 10. Sugar content in stalk decreased gradually as planting was getting delayed though one variety differed from another. It seemed that sweet sorghum which planted later than June had no value as a sugar crop at all. 11. The Brix % and sugar content in stalk increased from heading and reached the maximum 40 to 45 days after heading. The percentage of purity showed the same tendency as the mentioned characters. Accordingly, a highly positive correlation was observed between. percentage of purity and Brix % or sugar content in stalk. 12. The highest refinable sugar yield was obtained from the planting on April 25 in late-maturing varieties and from that on May 15 in early-maturing varieties. The yield rapidly decreased when planted later than those dates. Such a negative correlation between planting date(x) and refinable sugar yield(y) was highly significant at 1% level. 13. Negative correlations or linear regressions between delayed planting and the number of days from sowing to germination. accumulated temperature during germination period, number of days to heading, accumulated temperature to heading, plant height, stem diameter, stalk weight, Brix %. sugar content, refinable sugar yield or Purity % were obtained. On the other hand, highly positive correlations between the number of days from sowing to heading(x) and Brix %, sugar content, purity %, refinable sugar yield, plant height or stalk yield, between Brix %(x) and purity %, refinable sugar yield or stalk yield, between sugar content(x) and purity% or refinable sugar yield(y), between purity %(x) and refinable sugar yield and between daylength at heading(x) and Brix %. number of days from sowing to heading, sugar content, purity % or refinable sugar yield (y), were found, respectively. Experiment II: The 11 varieties were selected out of the varieties used in Experiment I from ecological and genetic viewpoints. Complete diallel cross were made among them and the heading date, stalk length, stalk yield, Brix %, syrup yield, combining ability and genetic behavior of F$_1$ plants and their parental varieties were investigated. The results could be summarized as follows: 1. In general, number of days to heading showed a partial dominance over earliness or late maturity or had a mid-value, though there were some specific combinations showing a complete dominance or transgressive segregation in maturity. Some combinations showed relatively high general or specific combining abilities in maturity. Therefore, a 50 to 50 segregation ratio in heading date could be estimated in this study and it might be positive to have a selection in early generation since heritability of the character was relatively high. 2. A vigorous hybrid vigor was observed in stalk length. A complete or partial dominant effect of long stalk was obtained. The general combining ability and specific combining ability of stalk length were generally high. Long and short stalks segregated in a ratio of 50:50 and its heritability was relatively low. 3. Except for several specific combinations, high stalk yield seemed to be partial dominant over the low yield. Some varieties demonstrated relatively high general as well as specific combining abilities. It was assumed that several recessive genes were involved in expression of this character. The interaction among regulating recessive genes was also obtained. Accordingly, the heritability of stalk yield seemed to be rather low. 4. The Brix % of hybrid plants located around mid-parental value though some of them showed much higher or lower percentage. It could be explained by the fact that such behavior might be due to partial dominance of Brix %. The varieties with, relatively higher Brix % were high both in general. and specific combining abilities. Therefore, it could be recommended to use the varieties having higher sugar content in order to develop higher-sugar varieties. 5. The syrup yield seemed to be transgressively segregated or completely dominant over low yield. Hybrid vigor of syrup yield was relatively high. No-consistent relationship between general combining ability and specific combining ability was observed. However, some cases demonstrated that the varieties with relatively higher general combining ability had relatively lower specific combining ability. It was assumed that the frequencies of dominant and recessive alleles were almost same.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.2
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• pp.26-32
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• 2010

Purpose: It is to find the way to minimize occupationally exposed dose for workers in vivo tests in each working stage within the range of the working environment which does not ruin the examination and the performance efficiency. Materials and Methods: The process of the nuclear tests in vivo using a radioactive isotope consists of radioisotope distribution, a radioisotope injection ($^{99m}Tc$, $^{18}F$-FDG), and scanning and guiding patients. Using a measuring instrument of RadEye-G10 gamma survey meter (Thermo SCIENTIFIC), the exposure doses in each working stage are measured and evaluated. Before the radioisotope injection the patients are explained about the examination and educated about matters that require attention. It is to reduce the meeting time with the patients. In addition, workers are also educated about the outside exposure and have to put on the protected devices. When the radioisotope is injected to the patients the exposure doses are measured due to whether they are in the protected devices or not. It is also measured due to whether there are the explanation about the examination and the education about matters that require attention or not. The total exposure dose is visualized into the graph in using Microsoft office excel 2007. The difference of this doses are analyzed by wilcoxon signed ranks test in using SPSS (statistical package for the social science) program 12.0. In this case of p<0.01, this study is reliable in the statistics. Results: It was reliable in the statistics that the exposure dose of injecting $^{99m}Tc$-DPD 20 mCi in wearing the protected devices showed 88% smaller than the dose of injecting it without the protected devices. However, it was not reliable in the statistics that the exposure dose of injecting $^{18}F$-FDG 10 mCi with wearing protected devices had 26% decrease than without them. Training before injecting $^{99m}Tc$-DPD 20 mCi to patient made the exposure dose drop to 63% comparing with training after the injection. The dose of training before injecting $^{18}F$-FDG 10 mCi had 52% less then the training after the injection. Both of them were reliable in the statistics. Conclusion: In the examination of using the radioisotope $^{99m}Tc$, wearing the protected devices are more effective to reduce the exposure dose than without wearing them. In the case of using $^{18}F$-FDG, reducing meeting time with patients is more effective to drop the exposure dose. Therefore if we try to protect workers from radioactivity according to each radioisotope characteristic it could be more effective and active radiation shield from radioactivity.

• Journal of Distribution Science
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• v.8 no.3
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• pp.27-35
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• 2010

As the population, buying power, and intensity of self-expression of the elderly generation increase, its importance as a market segment is also growing. Therefore, the mass marketing strategy for the elderly generation must be changed to a micro-marketing strategy based on the results of sub-segmentation that suitably captures the characteristics of this generation. Furthermore, as a customer access strategy is decided by sub-segmentation, proper segmentation is one of the key success factors for micro-marketing. Segments or sub-segments are different from sectors, because segmentation or sub-segmentation for micro-marketing is based on the homogeneity of customer needs. Theoretically, complete segmentation would reveal a single voice. However, it is impossible to achieve complete segmentation because of economic factors, factors that affect effectiveness, etc. To obtain a single voice from a segment, we sometimes need to divide it into many individual cases. In such a case, there would be a many segments to deal with. On the other hand, to maximize market access performance, fewer segments are preferred. In this paper, we use the term "sub-segmentation" instead of "segmentation," because we divide a specific segment into more detailed segments. To sub-segment the elderly generation, this paper takes their lifestyles and life stages into consideration. In order to reflect these aspects, various surveys and several rounds of expert interviews and focused group interviews (FGIs) were performed. Using the results of these qualitative surveys, we can define six sub-segments of the elderly generation. This paper uses five rules to divide the elderly generation. The five rules are (1) mutually exclusive and collectively exhaustive (MECE) sub-segmentation, (2) important life stages, (3) notable lifestyles, (4) minimum number of and easy classifiable sub-segments, and (5) significant difference in voices among the sub-segments. The most critical point for dividing the elderly market is whether children are married. The other points are source of income, gender, and occupation. In this paper, the elderly market is divided into six sub-segments. As mentioned, the number of sub-segments is a very key point for a successful marketing approach. Too many sub-segments would lead to narrow substantiality or lack of actionability. On the other hand, too few sub-segments would have no effects. Therefore, the creation of the optimum number of sub-segments is a critical problem faced by marketers. This paper presents a method of evaluating the fitness of sub-segments that was deduced from the preceding surveys. The presented method uses the degree of homogeneity (DoH) to measure the adequacy of sub-segments. This measure uses quantitative survey questions to calculate adequacy. The ratio of significantly homogeneous questions to the total numbers of survey questions indicates the DoH. A significantly homogeneous question is defined as a question in which one case is selected significantly more often than others. To show whether a case is selected significantly more often than others, we use a hypothesis test. In this case, the null hypothesis (H0) would be that there is no significant difference between the selection of one case and that of the others. Thus, the total number of significantly homogeneous questions is the total number of cases in which the null hypothesis is rejected. To calculate the DoH, we conducted a quantitative survey (total sample size was 400, 60 questions, 4~5 cases for each question). The sample size of the first sub-segment-has no unmarried offspring and earns a living independently-is 113. The sample size of the second sub-segment-has no unmarried offspring and is economically supported by its offspring-is 57. The sample size of the third sub-segment-has unmarried offspring and is employed and male-is 70. The sample size of the fourth sub-segment-has unmarried offspring and is not employed and male-is 45. The sample size of the fifth sub-segment-has unmarried offspring and is female and employed (either the female herself or her husband)-is 63. The sample size of the last sub-segment-has unmarried offspring and is female and not employed (not even the husband)-is 52. Statistically, the sample size of each sub-segment is sufficiently large. Therefore, we use the z-test for testing hypotheses. When the significance level is 0.05, the DoHs of the six sub-segments are 1.00, 0.95, 0.95, 0.87, 0.93, and 1.00, respectively. When the significance level is 0.01, the DoHs of the six sub-segments are 0.95, 0.87, 0.85, 0.80, 0.88, and 0.87, respectively. These results show that the first sub-segment is the most homogeneous category, while the fourth has more variety in terms of its needs. If the sample size is sufficiently large, more segmentation would be better in a given sub-segment. However, as the fourth sub-segment is smaller than the others, more detailed segmentation is not proceeded. A very critical point for a successful micro-marketing strategy is measuring the fit of a sub-segment. However, until now, there have been no robust rules for measuring fit. This paper presents a method of evaluating the fit of sub-segments. This method will be very helpful for deciding the adequacy of sub-segmentation. However, it has some limitations that prevent it from being robust. These limitations include the following: (1) the method is restricted to only quantitative questions; (2) the type of questions that must be involved in calculation pose difficulties; (3) DoH values depend on content formation. Despite these limitations, this paper has presented a useful method for conducting adequate sub-segmentation. We believe that the present method can be applied widely in many areas. Furthermore, the results of the sub-segmentation of the elderly generation can serve as a reference for mature marketing.

• Journal of Chest Surgery
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• v.39 no.2 s.259
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• pp.106-110
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• 2006

Background: Bronchioloalveolar carcinoma (BAC) is an uncommon primary malignancy of the lung, and it accounts for $2{\~}14\%$ of all pulmonary malignancies. According to World Health Organization (WHO) categorisation, BAC is a subtype of adenocarcinoma. The current definition of BAC includes the following: malignant neoplasms of the lung that have no evidence of extrathoracic primary adenocarcinoma, an absence of a central bronchogenic source, a peripheral parenchymal location, and neoplastic cells growing along the alveolar septa. Previous reports had demonstrated a better prognosis following surgery for patients affected by BAC than those affected by other type of non-small cell lung cancer (NSCLC). We aim to analyse Asan Medical Center experiences of BAC. Material and Method: Between 1990 and 2002, 31 patients were received operations for BAC. We analyse retrosepectively sex, age, disease location, preoperative clinical stage, postoperative pathologic stage & complications, survival according to medical record. Result: There were 12 men and 19 women, the average age was 61.09$\pm$10.63 ($31{\~}79$) years. Tumor locations were 7 in RUL, 1 in RML, 4 in RLL, 8 in LUL, 11 in LLL. Operations were 28 lobectomies, 2 pneumonectomies. Postoperative pathologic stage were 12 T1N0M0, 15 T2N0M0, 1 T1N1M0, 1 T1N2M0, 1 T2N2M0, 1 T1N0M1. Mortality were 4 cases ($12.9\%$) and there were no early mortality. Cancer free death was 1 cases, other 3 were cancer related deaths. All of them were affected by distal metastasis and received chemotherapy and each metastatic locations were right rib, brain, and both lung field. The average follow up periods were 50.87$\pm$24.77 months. The overall 3, 5-year survival rate among all patients was $97.1\%,\;83.7\%$, stage I patients overall 2, 5year survival rate was $96.3\%$. The overall disease free 1, 2, 5-year survival rate among all patients was $100\%,\;90\%,\;76\%$ and 2, 5-year survival rate in cases of stage I was $96.4\%,\;90.6\%$. 7 cases ($22.58\%$) were chemotherapies, 1 case ($3.22\%$) was radiation therapy, and 2 cases ($6.45\%$) were chemoradiation therapies. Metastatic locations were 3 cases in lung, 1 case in bone, 1 cases in brain. Conclusion: BAC has a favourable survival and low recurrence rate compare with reported other NSCLC after operative resections.

• Journal of Chest Surgery
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• v.41 no.2
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• pp.210-215
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• 2008

Background: Drug-eluting stents are contributing to the exponential growth of percutaneous coronary intervention, and even in the patients with left main coronary artery disease, owing to the decreased restenosis rate. Our study aimed at comparing the one-year results after coronary artery bypass grafting versus percutaneous coronary intervention with drug-eluting stents in patients with left main coronary artery disease. Material and Method: Those patients who underwent coronary bypass surgery or stenting at our hospital under the diagnosis of left main coronary artery disease were divided in two groups. The variables for comparison were the preoperative disease severity, the length of the hospital stay, the early mortality and the cumulative incidence of mortality, myocardial infarction and repeated revascularization. Result: There were 101 cases in the surgery group and 78 cases in the stent group. Age, gender, the risk factors, the left ventricular ejection fraction and the proportion of acute coronary syndrome showed no significant differences between the two groups. The surgery group showed a more severe condition according to the Euroscore, a greater incidence of urgency, a longer hospital stay and a greater incidence of multi-vessel disease. The early mortality and one-year cumulative mortality were not different between the groups. The Euroscore-matched comparison for the surgery group (41 patients) and the stent group (78 patients) showed no significant differences in the Euroscore, age, gender, risk factors and the proportion of acute coronary syndrome. The surgery group in the Euroscore-matched comparison showed more multi-vessel disease and a longer hospital stay. The surgery group showed lower early mortality and lower one-year cumulative mortality, but this was statistically insignificant (0% vs 2.6%, respectively, p=0.55; 0% vs 6.6%, respectively, p=0.30). The rates of repeated revascularization and major adverse events (death or myocardial infarct) were lower in the CABG group, but this was not statistically significant (13.3% vs 6.3%, respectively, p=0.48; 10.0% vs 0%, respectively, p=0.09). Conclusion: Percutaneous coronary intervention using drug-eluting stents in low-risk patients with left main coronary artery disease resulted in a shortened length of the hospital stay, as compared with that of the CABG group of patients. However, the patients who underwent percutaneous coronary intervention using drug-eluting stents showed a tendency for an increased rate of repeated revascularization and higher one-year cumulative mortality. Further studies with large populations and longer follow-up will be necessary to reaffirm our findings.