• Journal of Intelligence and Information Systems
• /
• v.26 no.3
• /
• pp.149-169
• /
• 2020

"The Urban Renewal New Deal project", one of the government's major national projects, is about developing underdeveloped areas by investing 50 trillion won in 100 locations on the first year and 500 over the next four years. This project is drawing keen attention from the media and local governments. However, the project model which fails to reflect the original characteristics of the area as it divides project area into five categories: "Our Neighborhood Restoration, Housing Maintenance Support Type, General Neighborhood Type, Central Urban Type, and Economic Base Type," According to keywords for successful urban regeneration in Korea, "resident participation," "regional specialization," "ministerial cooperation" and "public-private cooperation", when local governments propose urban regeneration projects to the government, they can see that it is most important to accurately understand the characteristics of the city and push ahead with the projects in a way that suits the characteristics of the city with the help of local residents and private companies. In addition, considering the gentrification problem, which is one of the side effects of urban regeneration projects, it is important to select and implement urban regeneration types suitable for the characteristics of the area. In order to supplement the limitations of the 'Urban Regeneration New Deal Project' methodology, this study aims to propose a system that recommends urban regeneration types suitable for urban regeneration sites by utilizing various machine learning algorithms, referring to the urban regeneration types of the '2025 Seoul Metropolitan Government Urban Regeneration Strategy Plan' promoted based on regional characteristics. There are four types of urban regeneration in Seoul: "Low-use Low-Level Development, Abandonment, Deteriorated Housing, and Specialization of Historical and Cultural Resources" (Shon and Park, 2017). In order to identify regional characteristics, approximately 100,000 text data were collected for 22 regions where the project was carried out for a total of four types of urban regeneration. Using the collected data, we drew key keywords for each region according to the type of urban regeneration and conducted topic modeling to explore whether there were differences between types. As a result, it was confirmed that a number of topics related to real estate and economy appeared in old residential areas, and in the case of declining and underdeveloped areas, topics reflecting the characteristics of areas where industrial activities were active in the past appeared. In the case of the historical and cultural resource area, since it is an area that contains traces of the past, many keywords related to the government appeared. Therefore, it was possible to confirm political topics and cultural topics resulting from various events. Finally, in the case of low-use and under-developed areas, many topics on real estate and accessibility are emerging, so accessibility is good. It mainly had the characteristics of a region where development is planned or is likely to be developed. Furthermore, a model was implemented that proposes urban regeneration types tailored to regional characteristics for regions other than Seoul. Machine learning technology was used to implement the model, and training data and test data were randomly extracted at an 8:2 ratio and used. In order to compare the performance between various models, the input variables are set in two ways: Count Vector and TF-IDF Vector, and as Classifier, there are 5 types of SVM (Support Vector Machine), Decision Tree, Random Forest, Logistic Regression, and Gradient Boosting. By applying it, performance comparison for a total of 10 models was conducted. The model with the highest performance was the Gradient Boosting method using TF-IDF Vector input data, and the accuracy was 97%. Therefore, the recommendation system proposed in this study is expected to recommend urban regeneration types based on the regional characteristics of new business sites in the process of carrying out urban regeneration projects."

• Journal of Intelligence and Information Systems
• /
• v.20 no.1
• /
• pp.177-193
• /
• 2014

Over the past decade, there has been a rapid diffusion of electronic commerce and a rising number of interconnected networks, resulting in an escalation of security threats and privacy concerns. Electronic commerce has a built-in trade-off between the necessity of providing at least some personal information to consummate an online transaction, and the risk of negative consequences from providing such information. More recently, the frequent disclosure of private information has raised concerns about privacy and its impacts. This has motivated researchers in various fields to explore information privacy issues to address these concerns. Accordingly, the necessity for information privacy policies and technologies for collecting and storing data, and information privacy research in various fields such as medicine, computer science, business, and statistics has increased. The occurrence of various information security accidents have made finding experts in the information security field an important issue. Objective measures for finding such experts are required, as it is currently rather subjective. Based on social network analysis, this paper focused on a framework to evaluate the process of finding experts in the information security field. We collected data from the National Discovery for Science Leaders (NDSL) database, initially collecting about 2000 papers covering the period between 2005 and 2013. Outliers and the data of irrelevant papers were dropped, leaving 784 papers to test the suggested hypotheses. The co-authorship network data for co-author relationship, publisher, affiliation, and so on were analyzed using social network measures including centrality and structural hole. The results of our model estimation are as follows. With the exception of Hypothesis 3, which deals with the relationship between eigenvector centrality and performance, all of our hypotheses were supported. In line with our hypothesis, degree centrality (H1) was supported with its positive influence on the researchers' publishing performance (p<0.001). This finding indicates that as the degree of cooperation increased, the more the publishing performance of researchers increased. In addition, closeness centrality (H2) was also positively associated with researchers' publishing performance (p<0.001), suggesting that, as the efficiency of information acquisition increased, the more the researchers' publishing performance increased. This paper identified the difference in publishing performance among researchers. The analysis can be used to identify core experts and evaluate their performance in the information privacy research field. The co-authorship network for information privacy can aid in understanding the deep relationships among researchers. In addition, extracting characteristics of publishers and affiliations, this paper suggested an understanding of the social network measures and their potential for finding experts in the information privacy field. Social concerns about securing the objectivity of experts have increased, because experts in the information privacy field frequently participate in political consultation, and business education support and evaluation. In terms of practical implications, this research suggests an objective framework for experts in the information privacy field, and is useful for people who are in charge of managing research human resources. This study has some limitations, providing opportunities and suggestions for future research. Presenting the difference in information diffusion according to media and proximity presents difficulties for the generalization of the theory due to the small sample size. Therefore, further studies could consider an increased sample size and media diversity, the difference in information diffusion according to the media type, and information proximity could be explored in more detail. Moreover, previous network research has commonly observed a causal relationship between the independent and dependent variable (Kadushin, 2012). In this study, degree centrality as an independent variable might have causal relationship with performance as a dependent variable. However, in the case of network analysis research, network indices could be computed after the network relationship is created. An annual analysis could help mitigate this limitation.

• Journal of Intelligence and Information Systems
• /
• v.26 no.2
• /
• pp.1-25
• /
• 2020

In this paper, we suggest an application system architecture which provides accurate, fast and efficient automatic gasometer reading function. The system captures gasometer image using mobile device camera, transmits the image to a cloud server on top of private LTE network, and analyzes the image to extract character information of device ID and gas usage amount by selective optical character recognition based on deep learning technology. In general, there are many types of character in an image and optical character recognition technology extracts all character information in an image. But some applications need to ignore non-of-interest types of character and only have to focus on some specific types of characters. For an example of the application, automatic gasometer reading system only need to extract device ID and gas usage amount character information from gasometer images to send bill to users. Non-of-interest character strings, such as device type, manufacturer, manufacturing date, specification and etc., are not valuable information to the application. Thus, the application have to analyze point of interest region and specific types of characters to extract valuable information only. We adopted CNN (Convolutional Neural Network) based object detection and CRNN (Convolutional Recurrent Neural Network) technology for selective optical character recognition which only analyze point of interest region for selective character information extraction. We build up 3 neural networks for the application system. The first is a convolutional neural network which detects point of interest region of gas usage amount and device ID information character strings, the second is another convolutional neural network which transforms spatial information of point of interest region to spatial sequential feature vectors, and the third is bi-directional long short term memory network which converts spatial sequential information to character strings using time-series analysis mapping from feature vectors to character strings. In this research, point of interest character strings are device ID and gas usage amount. Device ID consists of 12 arabic character strings and gas usage amount consists of 4 ~ 5 arabic character strings. All system components are implemented in Amazon Web Service Cloud with Intel Zeon E5-2686 v4 CPU and NVidia TESLA V100 GPU. The system architecture adopts master-lave processing structure for efficient and fast parallel processing coping with about 700,000 requests per day. Mobile device captures gasometer image and transmits to master process in AWS cloud. Master process runs on Intel Zeon CPU and pushes reading request from mobile device to an input queue with FIFO (First In First Out) structure. Slave process consists of 3 types of deep neural networks which conduct character recognition process and runs on NVidia GPU module. Slave process is always polling the input queue to get recognition request. If there are some requests from master process in the input queue, slave process converts the image in the input queue to device ID character string, gas usage amount character string and position information of the strings, returns the information to output queue, and switch to idle mode to poll the input queue. Master process gets final information form the output queue and delivers the information to the mobile device. We used total 27,120 gasometer images for training, validation and testing of 3 types of deep neural network. 22,985 images were used for training and validation, 4,135 images were used for testing. We randomly splitted 22,985 images with 8:2 ratio for training and validation respectively for each training epoch. 4,135 test image were categorized into 5 types (Normal, noise, reflex, scale and slant). Normal data is clean image data, noise means image with noise signal, relfex means image with light reflection in gasometer region, scale means images with small object size due to long-distance capturing and slant means images which is not horizontally flat. Final character string recognition accuracies for device ID and gas usage amount of normal data are 0.960 and 0.864 respectively.

• Pediatric Gastroenterology, Hepatology & Nutrition
• /
• v.2 no.2
• /
• pp.153-163
• /
• 1999

Purpose: The purpose of our study is to provide useful information for diagnostic methods of fatty liver by childhood simple obesity and to provide correlation between serum alanine aminotransferase (ALT) for screening test and abdominal computerized tomography (CT) and liver biopsy for confirmative diagnostic methods of fatty liver. Methods: Among 78 obese childrens who visited our hospital, CT was carried out in 26 childrens. Of these, liver biopsy was carried out in 15 childrens who had high obesity index or severe elevated ALT. Based on the level of serum ALT, 26 cases were classified into 3 groups, and compared with physical measurements and degree of fatty infiltration on CT and liver biopsy. Results: 1) Correlation between ALT and physical measurements: Of 26 obese children, ALT was abnormally elevated (>30 IU/L) in 17 cases (67.4%) but there was no significant correlation between ALT and physical measurements (p>0.05). 2) Correlation between degree of fatty infiltration on CT and ALT: Of 26 cases, 13 cases (50%) revealed fatty liver on CT. The degree of fatty liver on CT had significant correlation with elevation of ALT (p<0.05). 3) Correlation between the degree of fatty infiltration on liver biopsy and ALT: Liver biopsy was performed in 15 cases of which 14 cases revealed fatty liver. But one case had normal hepatic histology with severe obesity and normal ALT. Fourteen fatty liver cases on liver biopsy were classified into 3 groups by the degree of fatty infiltration and analysed with obesity index and ALT. The histologic hepatic steatosis had no significant correlation with obesity index (p>0.05), but significant correlation with ALT (p<0.05). 4) Correlation between CT and liver biopsy finding: Both CT and liver biopsy were performed in 15 cases of which 6 cases revealed normal finding on CT and 9 cases manifested fatty liver. There was significant correlation between CT and liver biopsy findings (r=0.6094). Conclusion: The results of our study suggest that abdominal CT and liver biopsy are useful and accurate methods of estimating fatty liver in the childhood obesity. But biochemical abnormalities of routine liver function tests dot not correlate well with severity of the fatty liver and liver injury.

• Journal of Preventive Medicine and Public Health
• /
• v.29 no.4 s.55
• /
• pp.747-764
• /
• 1996

This study intended to obtain an useful information for health management of lead exposed workers and determine biological monitoring interval in early period of exposure by measuring the lead exposure indices and work duration in all male workers (n=433 persons) exposed less than 1 year in 6 storage battery industries and in 49 males who are not exposed to lead as control. The examined variables were blood lead concentration (PBB), Zinc-protoporphyrin concentration (ZPP), Hemoglobin (HB) and personal history; also measured lead concentration in air (PBA) in the workplace. According to the geometric mean of lead concentration in the air, the factories were grouped into three categories: A; When it is below $0.05mg/m^3$, B; When it is between 0.05 and $0.10mg/m^3$, and C; When it is above $0.10mg/m^3$. The results obtained were as follows: 1. The means of blood lead concentration (PBB), ZPP concentration and hemoglobin(HB) in all male workers exposed to lead less than 1 year in storage battery industries were $29.5{\pm}12.4{\mu}g/100ml,\;52.9{\pm}30.0{\mu}g/100ml\;and\;15.2{\pm}1.1\;gm/100ml$. 2. The means of blood lead concentration (PBB), ZPP concentration and hemoglobin(HB) in control group were $5.8{\pm}1.6{\mu}g/100ml,\;30.8{\pm}12.7{\mu}g/100ml\;and\;15.7{\pm}1.6{\mu}g/100ml$, being much lower than that of study group exposed to lead. 3. The means of blood lead concentration and ZPP concentration among group A were $21.9{\pm}7.6{\mu}g/100,\;41.4{\pm}12.6{\mu}g/100ml$ ; those of group B were $29.8{\pm}11.6{\mu}g/100,\;52.6{\pm}27.9{\mu}g/100ml$ ; those of group C were $37.2{\pm}13.5{\mu}g/100,\;66.3{\pm}40.7{\mu}g/100ml$. Significant differences were found among three factory group(P<0.01) that was classified by the geometric mean of lead concentration in the air, group A being the lowest. 4. The mean of blood lead concentration of workers who have different work duration (month) was as follows ; When the work duration was $1\sim2$ month, it was $24.1{\pm}12.4{\mu}g/100ml$, ; When the work duration was $3\sim4$ month, it was $29.2{\pm}13.4{\mu}g/100ml$ ; and it was $28.9\sim34.5{\mu}g/100ml$ for the workers who had longer work duration than other. Significant differences were found among work duration group(P<0.05). 5. The mean of ZPP concentration of workers who have different work duration (month) was as follows ; When the work duration was $1\sim2$ month, it was $40.6{\pm}18.0{\mu}g/100ml$, ; When the work duration was $3\sim4$ month, it was $53.4{\pm}38.4{\mu}g/100ml$ ; and it was $51.5\sim60.4{\mu}g/100ml$ for the workers who had longer work duration than other. Significant differences were found among work duration group(P<0.05). 6. Among total workers(433 person), 18.2% had PBB concentration higher than $40{\mu}g/100ml$ and 7.1% had ZPP concentration higher than $100{\mu}g/100ml$ ; In workers of factory group A, those were 0.9% and 0.0% ; In workers of factory group B, those were 17.1% and 6.9% ; In workers of factory group C, those were 39.4% and 15.4%. 7. The proportions of total workers(433 person) with blood lead concentration lower than $25{\mu}g/100ml$ and ZPP concentration lower than $50{\mu}g/100ml$ were 39.7% and 61.9%, respectively ; In workers of factory group A, those were 65.5% and 82.3% : In workers of factory group B, those were 36.1% and 60.2% ; In workers of factory group C, those were 19.2% and 43.3%. 8. Blood lead concentration (r=0.177, P<0.01), ZPP concentration (r=0.135, P<0.01), log ZPP (r=0.170, P<0.01) and hemoglobin (r=0.096, P<0.05) showed statistically significant correlation with work duration (month). ZPP concentration (r=0.612, P<0.01) and log ZPP (r=0.614, P<0.01) showed statistically significant correlation with blood lead concentration 9. The slopes of simple linear regression between work duration(month, independent variable) and blood lead concentration (dependent variable) in workplace with low air concentration of lead was less steeper than that of poor working condition with high geometric mean air concentration of lead. The study result indicates that new employees should be provided with biological monitoring including blood lead concentration test and education about personal hygiene and work place management within $3\sim4$ month.

• Journal of Preventive Medicine and Public Health
• /
• v.29 no.4 s.55
• /
• pp.785-799
• /
• 1996

We investigated the 1,004 workers who worked in a automobile factory to study the epidemiologic characterists of dermatoses due to cutting oils. Among the workers, 667(66.4%) answered the questionaire. They are belong to 5 departments of the factory-the Engine-Work(258 workers), Gasoline engine Assembly(210), Diesel engine Assembly(96), Power train Work(86), Power train Assembly(17). We measured the oil mist concentration in air of the departments and examined the workers who had dermatologic symptoms. The results were follows; 1) Oil mist concentration ; Of all measured points(52),9 points(17.2%) exeeded $5mg/m^3$- the time-weighed PEL-and one department had a upper confidence limit(95%) higher than $5mg/m^3$. 2) Dermatologists examined 213 workers. 172 of them complained any skin symptoms at that time - itching(32.5%), papule(21.6%), scale(15.7%), vesicle(12.5%) in order. The abnormal skin site found by dermatologist were palm(29.3%), finger & nail(24.6%), forearm(16.2%), back of hand(8.4%) in order. 3) As the result of physical examination, we found that 160 workers had skin diseases. Contact dermatitis was the most common; 69 workers had contact dermatitis alone(43.1%), 11 had contact dermatitis with acne(6.9%), 10 had contact dermatitis with folliculitis(6.3%), 1 had contact dermatitis with acne & folliculitis, and 1 had contact dermatitis with abnormal pigmentation. Others were folliculitis(9 workers, 5.6%), acne(8, 5.0%), folliculitis & acne (2, 1.2%), keratosis(1, 0.6%), abnormal pigmentation (1, 0.6%), and non-specific hand eczema (47, 29.3%). 4) The prevalence of any skin diseases was 34.0 pet 100 in cutting oil users, and 13.3 per 100 in non- users. Especially, the prevalence of contact dermatitis was 23.0 per 100 in cutting oil users and 23.0 per 100 in non-users. 5) We tried patch test(standard serise, oil serise, organic solvents) on 49 patients to differentiate allergic contact dermatitis from irritant contact dermatitis and found 20 were positive. 6) In a multivariate analysis(independant=age, tenure, kinds of cutting oil), the risk of skin diseases was higher in the water-based cutting oil user and both oil user than non-user or neat oil user(odds ratio were 2.16 and 2.78, respectively). And the risk of contact dermatitis was much higher at the same groups(odds ratio were 5.16 and 6.82, respectively).

• Journal of the Society of Cosmetic Scientists of Korea
• /
• v.41 no.4
• /
• pp.361-373
• /
• 2015

This study was carried out to evaluate the antioxidant and antibacterial activities of Glycyrriza uralensis Fisher (Jecheon, Korea) extracts obtained by various extraction conditions (85% ethanol, heating temperatures and times), and to establish the optimal extraction condition of G. uralensis for the application as cosmetic ingredients. The extracts obtained under different conditions were concentrated and made in the powdered (sample-1) and were the crude extract solutions without concentration (sample-2). The antioxidant effects were determined by free radical scavenging activity ($FSC_{50}$), ROS scavenging activity ($OSC_{50}$), and cellular protective effects. Antibacterial activity was determined by minimum inhibitory concentration (MIC) on human skin flora. DPPH free radical scavenging activity of sample-1 ($100{\mu}g/mL$) was 10% higher in group extracted for 6 h than 12 h, but sample-2 didn't show any significant differences. The extraction yield extracted with same temperature for 12 h was 2.6 times higher than 6 h, but total flavonoid content was 1.1 times higher. These results indicated that total flavonoid content hardly increased with increasing extraction time. Free radical scavenging activity, ROS scavenging activity and cellular protective effects were not dependent on the yield of extraction, but total flavonoid content of extraction. Antibacterial activity on three skin flora (S. aureus, B. subtilis, P. acnes)of sample-1 in different extraction conditions were evaluated on same concentration, and the group extracted at 25 and $40^{\circ}C$ showed 16 times higher than methyl paraben ($2,500{\mu}g/mL$). In conclusion, 85% ethanol extracts of G. uralensis extracted at $40^{\circ}C$ for 6 h showed the highest antioxidant and antibacterial activity. These results indicate that the extraction condition is important to be optimized by comprehensive evaluation of extraction yield with various conditions, yield of active component, and activity test with concentrations, and activity of 100% extract, for manufacturing process of products.

• Journal of Global Scholars of Marketing Science
• /
• v.18 no.3
• /
• pp.59-88
• /
• 2008

Digital Convergence means integration between industry, technology, and contents, and in marketing, it usually comes with creation of new types of product and service under the base of digital technology as digitalization progress in electro-communication industries including telecommunication, home appliance, and computer industries. One can see digital convergence not only in instruments such as PC, AV appliances, cellular phone, but also in contents, network, service that are required in production, modification, distribution, re-production of information. Convergence in contents started around 1990. Convergence in network and service begins as broadcasting and telecommunication integrates and DMB(digital multimedia broadcasting), born in May, 2005 is the symbolic icon in this trend. There are some positive and negative expectations about DMB. The reason why two opposite expectations exist is that DMB does not come out from customer's need but from technology development. Therefore, customers might have hard time to interpret the real meaning of DMB. Time is quite critical to a high tech product, like DMB because another product with same function from different technology can replace the existing product within short period of time. If DMB does not positioning well to customer's mind quickly, another products like Wibro, IPTV, or HSPDA could replace it before it even spreads out. Therefore, positioning strategy is critical for success of DMB product. To make correct positioning strategy, one needs to understand how consumer interprets DMB and how consumer's interpretation can be changed via communication strategy. In this study, we try to investigate how consumer perceives a new product, like DMB and how AD strategy change consumer's perception. More specifically, the paper segment consumers into sub-groups based on their DMB perceptions and compare their characteristics in order to understand how they perceive DMB. And, expose them different printed ADs that have messages guiding consumer think DMB in specific ways, either cellular phone or personal TV. Research Question 1: Segment consumers according to perceptions about DMB and compare characteristics of segmentations. Research Question 2: Compare perceptions about DMB after AD that induces categorization of DMB in direction for each segment. If one understand and predict a direction in which consumer perceive a new product, firm can select target customers easily. We segment consumers according to their perception and analyze characteristics in order to find some variables that can influence perceptions, like prior experience, usage, or habit. And then, marketing people can use this variables to identify target customers and predict their perceptions. If one knows how customer's perception is changed via AD message, communication strategy could be constructed properly. Specially, information from segmented customers helps to develop efficient AD strategy for segment who has prior perception. Research framework consists of two measurements and one treatment, O1 X O2. First observation is for collecting information about consumer's perception and their characteristics. Based on first observation, the paper segment consumers into two groups, one group perceives DMB similar to Cellular phone and the other group perceives DMB similar to TV. And compare characteristics of two segments in order to find reason why they perceive DMB differently. Next, we expose two kinds of AD to subjects. One AD describes DMB as Cellular phone and the other Ad describes DMB as personal TV. When two ADs are exposed to subjects, consumers don't know their prior perception of DMB, in other words, which subject belongs 'similar-to-Cellular phone' segment or 'similar-to-TV' segment? However, we analyze the AD's effect differently for each segment. In research design, final observation is for investigating AD effect. Perception before AD is compared with perception after AD. Comparisons are made for each segment and for each AD. For the segment who perceives DMB similar to TV, AD that describes DMB as cellular phone could change the prior perception. And AD that describes DMB as personal TV, could enforce the prior perception. For data collection, subjects are selected from undergraduate students because they have basic knowledge about most digital equipments and have open attitude about a new product and media. Total number of subjects is 240. In order to measure perception about DMB, we use indirect measurement, comparison with other similar digital products. To select similar digital products, we pre-survey students and then finally select PDA, Car-TV, Cellular Phone, MP3 player, TV, and PSP. Quasi experiment is done at several classes under instructor's allowance. After brief introduction, prior knowledge, awareness, and usage about DMB as well as other digital instruments is asked and their similarities and perceived characteristics are measured. And then, two kinds of manipulated color-printed AD are distributed and similarities and perceived characteristics for DMB are re-measured. Finally purchase intension, AD attitude, manipulation check, and demographic variables are asked. Subjects are given small gift for participation. Stimuli are color-printed advertising. Their actual size is A4 and made after several pre-test from AD professionals and students. As results, consumers are segmented into two subgroups based on their perceptions of DMB. Similarity measure between DMB and cellular phone and similarity measure between DMB and TV are used to classify consumers. If subject whose first measure is less than the second measure, she is classified into segment A and segment A is characterized as they perceive DMB like TV. Otherwise, they are classified as segment B, who perceives DMB like cellular phone. Discriminant analysis on these groups with their characteristics of usage and attitude shows that Segment A knows much about DMB and uses a lot of digital instrument. Segment B, who thinks DMB as cellular phone doesn't know well about DMB and not familiar with other digital instruments. So, consumers with higher knowledge perceive DMB similar to TV because launching DMB advertising lead consumer think DMB as TV. Consumers with less interest on digital products don't know well about DMB AD and then think DMB as cellular phone. In order to investigate perceptions of DMB as well as other digital instruments, we apply Proxscal analysis, Multidimensional Scaling technique at SPSS statistical package. At first step, subjects are presented 21 pairs of 7 digital instruments and evaluate similarity judgments on 7 point scale. And for each segment, their similarity judgments are averaged and similarity matrix is made. Secondly, Proxscal analysis of segment A and B are done. At third stage, get similarity judgment between DMB and other digital instruments after AD exposure. Lastly, similarity judgments of group A-1, A-2, B-1, and B-2 are named as 'after DMB' and put them into matrix made at the first stage. Then apply Proxscal analysis on these matrixes and check the positional difference of DMB and after DMB. The results show that map of segment A, who perceives DMB similar as TV, shows that DMB position closer to TV than to Cellular phone as expected. Map of segment B, who perceive DMB similar as cellular phone shows that DMB position closer to Cellular phone than to TV as expected. Stress value and R-square is acceptable. And, change results after stimuli, manipulated Advertising show that AD makes DMB perception bent toward Cellular phone when Cellular phone-like AD is exposed, and that DMB positioning move towards Car-TV which is more personalized one when TV-like AD is exposed. It is true for both segment, A and B, consistently. Furthermore, the paper apply correspondence analysis to the same data and find almost the same results. The paper answers two main research questions. The first one is that perception about a new product is made mainly from prior experience. And the second one is that AD is effective in changing and enforcing perception. In addition to above, we extend perception change to purchase intention. Purchase intention is high when AD enforces original perception. AD that shows DMB like TV makes worst intention. This paper has limitations and issues to be pursed in near future. Methodologically, current methodology can't provide statistical test on the perceptual change, since classical MDS models, like Proxscal and correspondence analysis are not probability models. So, a new probability MDS model for testing hypothesis about configuration needs to be developed. Next, advertising message needs to be developed more rigorously from theoretical and managerial perspective. Also experimental procedure could be improved for more realistic data collection. For example, web-based experiment and real product stimuli and multimedia presentation could be employed. Or, one can display products together in simulated shop. In addition, demand and social desirability threats of internal validity could influence on the results. In order to handle the threats, results of the model-intended advertising and other "pseudo" advertising could be compared. Furthermore, one can try various level of innovativeness in order to check whether it make any different results (cf. Moon 2006). In addition, if one can create hypothetical product that is really innovative and new for research, it helps to make a vacant impression status and then to study how to form impression in more rigorous way.

• The Korean Journal of Mycology
• /
• v.7 no.2
• /
• pp.91-116
• /
• 1979

This paper is to investigate the standing crops and microfungal flora in soil in Phyllostachys reticulata forests in both the Yesan area (A) and the Kwangsan area (B). The stand density of the bamboo revealed 17,250 shoots per ha in area A, and in area B 14,780 shoots which were 16.1% less in number than area A. In respect to the environmental factors between the two areas, the mean temperature during the growth period was $1.5{\sim}2^{\circ}C$ higher in area B than in area A, soil tempeature also was $1{\sim}2^{\circ}C$ higher in area B, and the total quantities of nitrogen, phosphoric acid and organic compounds contained in the soil of area B were also slightly higher than those of area A. In area B the quantities of dried leaf matter, humus, and vegetation in the bamboo forest were also larger than in area A. In addition, five more species of microfungi which playa role in the decomposition of the various organic materials in the bamboo forests were identified in area B: Mortierella elongata, Mucor circinelloides, Aspergillus japonicus, Penicillium waksmani and Trichoderma lignorum. The atmospheric temperature in the inner portions of the bamboo forests was lower than the outside temperature, but the humidity was higher. The rates of relative illuminance were measured in area A at 4.19%, and in area B at 2.7%. These values revealed that the photosynthetic acitivity in the lower part of the bamboo was lost but it was considered that lower illuminance increased the microfungal activities in the vicinity of the surface soil. Since the productive structure of the bamboo showed that the maximum amount of photosynthesis was located in the upper portion of the bamboo in area B, it was considered to be an effective structure in maintaining the high productivity of the bamboo. The allometric relation between $D^2H$ and dry weight of stems(Ws), branches(Wb) and leaves(Wl) of the bamboo in area A were appoximated by log Ws=0.5262 log $D^2H$+1.9546; log Wb=0.6288 log $D^2H$+1.5723; log Wl=0.5181 log $D^2H$+1.8732, and those of the bamboo in area B were approximated by log Ws=0.5433 log $D^2H$+1.8610; log Wb=0.1630 log $D^2H$+2.3475; log Wl=0.4509 log $D^2H$+2.0041. From the above, the standing crops in area A were measured thus: Ws was 1,128. 83kg; Wb, 689.05kg; Wl, 926.69kg and Wl, 2,744.57kg per 10a. In area B, Ws was 1,206. 66kg; Wb, 679.92kg; Wl, 1,112.51kg and Wt, 2.999kg per l0a. Significant differences from the result of t-test were for $D^2H$ Ws, Wl and Wt between areas A and B. But no significant difference was found for Wb. In order to record as completely as possible the microfungal flora of the areas, every possible means was tried, and 158 strains of fungi were isolated, and of these, the microfungi of 55 species were identified. The dominant species were Trichoderma viride, Penicillium janthinellum, P. commune, Aspergillus oryzae, A. niger, A. gigantus, A. fumigatus, Mortierella ramaniana, var. anguliFPora, Mucor hiemalis and Zygorhynchus moelleri. According to the above results, it was revealed that optimum soil, the increases of soil materials, more species of soil microfungi, and the atmospheric temperature during the growth period have made the bamboo flourish and bring more species and larger quantities of vegetation in the bamboo forests. The correlation between the standing crops and environmental factors in the bamboo forest is considered to be a complicated relationship of all the factors, but the stand density is thought to be the most important factor involved.

• Tuberculosis and Respiratory Diseases
• /
• v.46 no.5
• /
• pp.674-684
• /
• 1999

Background : It has been generally known that the incidence of lung cancer is higher in the patients with idopathic pumonary fibrosis (IPF) than those in general population. The reported incidence was variable from 4.8 to 43.2%. There were controversies on the most frequent cell type (squamous cell carcinoma vs. adenocarcinoma) and no study was done about the real concordance of cancer and the fibrotic lesion. And the pulmonary fibrosis may influence not only the development of cancer but also the treatment and prognosis of the cancer, but there was no report on that point. Method : Total 63 patients ($66.8{\pm}7.8$ year, M : F=61 : 2) were diagnosed as IPF combined with lung cancer (IFF-CA) at Asan Medical Center. A retrospective analysis was done about the risk factors of the lung cancer, pulmonary function test, the site of cancer(especially the relationship of the cancer with the fibrotic lesion), the histologic types, and the stage of cancer. The histologic types were compared with those of 2,660 patients with lung cancer who were diagnosed at the same institute for the same period. The effect of IPF on the treatment of the cancer was evaluated with the survival time after the detection of lung cancer. Results : The lung cancer was found in 63(22.9%) out of 281 patients with IPF. But in most of them(45 patients), lung cancer was detected at the same time with IPF and only in 18 patients, the cancer was diagnosed during the follow-up($25.2{\pm}17.7$ months) of IPF. So in our study, 6.7% of patients with IPF developed lung cancer during the course of the disease. The age ($66.8{\pm}7.84$ vs. $63.4{\pm}11.1$ years), percentage of smoker (88.9 vs. 67.2%), and the male gender (96.8 vs. 67.6%) were significantly higher in IPF-CA compared with lone IPF (p<0.05). The odds ratio of smoking was 4.7 compared with non smoking IPF controls. The lung cancer was located more frequently in the upper lobe and 55.5% was in the periphery of lung. The cancer was developed in the fibrotic lesion in 23 patients (35.9%), and in the majority of the patients, the cancer was separated from the fibrosis. The cell type of the lung cancer in IPF-CA was squamous cell carcinoma 34.9%, adenocarcinoma 30.2%, small cell carcinoma 19.0%, large cell undifferenciated carcinoma 6.3%, and others 9.5%. No significant difference in the distribution of histologic type of the lung cancer was found between IPF-CA and lone lung cancer. There was no significant difference in demographic features, cell types, location and the stage of the cancer between the group with concurrent IPF-CA and the group with cancer diagnosed during the follow up of IPF. There was a tendency (but statistically not significant : p=0.081) of higher incidence of adenocarcinoma among the cancers developed in the fibrotic area(43.5%) (F-CA) than in the cancers in non-fibrotic area (22.5%) (NF-CA). The prognosis of the patients with F-CA was poor (median survival : 4 months) compared with the patients with NF-CA (7 months, p=0.013), partly because the prevalence of severe IPF (the extent of fibrosis in HRCT 50%) was higher in F-CA group. Conclusion : These data suggest that the lung cancer in the patients with IPF has similar features to the ordinary lung cancer.