• Journal of Yeungnam Medical Science
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• v.8 no.1
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• pp.107-126
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• 1991

The purpose of the study was to assess the morbidity pattern and the medical care utilization behavior of the urban residents in the poor area. The study population included 2,591 family members of 677 households in the poor area of Daemyong 8 Dong, Nam-Gu, Taegu and 2,686 family members of 688 households, near the poor area in the same Dong, were interviewed as a control group. On this study the household interview method was applied. Well-trained interviewers visited every household in the designated area and individually interviewed heads of households or housewives for general information, morbidity condition, and medical care utilization with a structured questionnaire. Individuals were interviewed from 1 to 30 December 1988. The major results were summarized as follows : The proportion of the people below 5 years of age was 4.2% of the total study population and 5.5% were above 65 years of age in the poor area. This was slightly higher than in the control area. The average monthly income of a household in the poor area was 403,000 won versus 529,000 won in the control area. Fifty-eight percent of the residents in the poor area and sixty-one percent in the control area were medical security beneficiaries, but the proportion of medical aid beneficiaries was 7.8% in the poor area and 4.6% in the control area. The 15-day period morbidity rate of acute illnesses was 57.1 per 1,000 in the poor area and 24.2 per 1,000 in the control area. Respiratory disease is the most common acute illness in both areas. The most frequently utilized medical facility was the pharmacy among the patients with acute illnesses in the poor area. Among them 58.1% visited pharmacy initially while 38.4% of the patients in the control area visited a clinic. Among persons with illnesses during the 15 days 8.8% in the poor area and 4.6% in the control area did not seek any medical facility. Mean duration of utilization of medical facilities was 3.5 days in the poor area and 3.3 days in the control area. Initially of the medical facilities in Daemyong 8 Dong, The pharmacy in the poor area and the clinic in the control area were most commonly utilized. The most common reason for visiting the hospital was 'regular customers' in the poor area and 'geographical accessibility' in the control area. The one year period morbidity rate of chronic illness in the poor area was 83.0 per 1,000 population and 28.0 per 1,000 in the control area. Disease of nervous system was the most common chronic illness in the poor area while cardiovascular disease in male and gastrointestinal disease in female were most prevalent in the control area. The most frequently utilized medical facility was the pharmacy among the patients with chronic illnesses in the poor area. Among them 24.2% visited the pharmacy initially while 34.7% of the patients in the control area visited the out-patient department of the hospital within a 15-day period. Among the patients with chronic illnesses 34.9% in the poor area and 16.0% in the control area did not seek any medical facility. Mean duration of utilization of medical facilities was 9.2 days in the poor area and 9.9 days in the control area within a 15-day period. Initially of the medical facilities in Daemyong 8 Dong, the pharmacy in the poor area and the hospital in the control area were most commonly utilized. The most common reason for visiting the hospital, clinic, health center or pharmacy in the poor area was 'geographical accessibility' while the reason for visiting herb clinic was 'good result' and 'reputation' in both areas.

• Journal of Global Scholars of Marketing Science
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• v.17 no.2
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• pp.1-29
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• 2007

The flow theory becomes one of the most important frameworks in the internet research arena. Hoffman and Novak proposed a hierarchical flow model showing the antecedents and outcomes of flow and the relationship among these variables in the hyper-media computer circumstances (Hoffman and Novak 1996). This model was further tested after their initial research (Novak, Hoffman, and Yung 2000). At their paper, Hoffman and Novak explained that the balance of challenge and skill leads to flow which means the positive optimal state of mind (Hoffman and Novak 1996). An imbalance between challenge and skill, leads to negative states of mind like anxiety, boredom, apathy (Csikszentmihalyi and Csikszentmihalyi 1988). Almost all research on the flow 4-channel model have been focusingon flow, the positive state of mind (Ellis, Voelkl, and Morris 1994 Mathwick and Rigdon 2004). However, it also needs to examine the formation of the negative states of minds and their outcomes. Flow researchers explain play or playfulness as antecedents or the early state of flow. However, play has been regarded as a distinct concept from flow in the flow literatures (Hoffman and Novak 1996; Novak, Hoffman, and Yung 2000). Mathwick and Rigdon discovered the influences of challenge and skill on play; they also observed the influence of play on web-loyalty and brand loyalty (Mathwick and Rigdon 2004). Unfortunately, they did not go so far as to test the influences of play on state of mind. This study focuses on the relationships between state of mind in the flow 4-channel model and play. Early research has attempted to hypothetically explain state of mind in flow theory, but has not been tested except flow until now. Also the importance of play has been emphasized in the flow theory, but has not been tested in the flow 4-channel model context. This researcher attempts to analyze the relationships among state of mind, skill of play, challenge, state of mind and web loyalty. For this objective, I developed a measure for state of mind and defined the concept of play as a trait. Then, the influences of challenge and skill on the state of mind and play under on-line shopping conditions were tested. Also the influences of play on state of mind were tested and those of flow and play on web loyalty were highlighted. 294 undergraduate students participated in this research survey. They were asked to respond about their perceptions of challenge, skill, state of mind, play, and web-loyalty to on-line shopping mall. Respondents were restricted to students who bought products on-line in a month. In case of buying products at two or more on-line shopping malls, they asked to respond about the shopping mall where they bought the most important one. Construct validity, discriminant validity, and convergent validity were used to check the measurement validations. Also, Cronbach's alpha was used to check scale reliability. A series of exploratory factor analyses was conducted. This researcher conducted confirmatory factor analyses to assess the validity of measurements. All items loaded significantly on their respective constructs. Also, all reliabilities were greater than.70. Chi-square difference tests and goodness of fit tests supported discriminant and convergent validity. The results of clustering and ANOVA showed that high challenge and high skill leaded to flow, low challenge and high skill leaded to boredom, and low challenge and low skill leaded to apathy. But, it was different from my expectation that high challenge and low skill didnot lead to anxiety but leaded to apathy. The results also showed that high challenge and high skill, and high challenge and low skill leaded to the highest play. Low challenge leaded to low play. 4 Structural Equation Models were built by flow, anxiety, boredom, apathy for analyzing not only the impact of play on state of mind and web-loyalty, but also that of state of mind on web-loyalty. According the analyses results of these models, play impacted flow and web-loyalty positively, but impacted anxiety, boredom, and apathy negatively. Results also showed that flow impacted web-loyalty positively, but anxiety, boredom, and apathy impacted web-loyalty negatively. The interpretations and implications of the test results of the hypotheses are as follows. First, respondents belonging to different clusters based on challenge and skill level experienced different states of mind such as flow, anxiety, boredom, apathy. The low challenge and low skill group felt the highest anxiety and apathy. It could be interpreted that this group feeling high anxiety or fear, then avoided attempts to shop on-line. Second, it was found that higher challenge leads to higher levels of play. Test results show that the play level of the high challenge and low skill group (anxiety group) was higher than that of the high challenge and high skill group (flow group). However, this was not significant. Third, play positively impacted flow and negatively impacted boredom. The negative impacts on anxiety and apathy were not significant. This means that the combination of challenge and skill creates different results. Forth, play and flow positively impacted web-loyalty, but anxiety, boredom, apathy had negative impacts. The effect of play on web-loyalty was stronger in case of anxiety, boredom, apathy group than fl ow group. These results show that challenge and skill influences state of mind and play. Results also demonstrate how play and flow influence web-loyalty. It implies that state of mind and play should be the core marketing variables in internet marketing. The flow theory has been focusing on flow and on the positive outcomes of flow experiences. But, this research shows that lots of consumers experience the negative state of mind rather than flow state in the internet shopping circumstance. Results show that the negative state of mind leads to low or negative web-loyalty. Play can have an important role with the web-loyalty when consumers have the negative state of mind. Results of structural equation model analyses show that play influences web-loyalty positively, even though consumers may be in the negative state of mind. This research found the impacts of challenge and skill on state of mind in the flow 4-channel model, not only flow but also anxiety, boredom, apathy. Also, it highlighted the role of play in the flow 4-channel model context and impacts on web-loyalty. However, tests show a few different results from hypothetical expectations such as the highest anxiety level of apathy group and insignificant impacts of play on anxiety and apathy. Further research needs to replicate this research and/or to compare 3-channel model with 4-channel model.

• Journal of agricultural medicine and community health
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• v.30 no.1
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• pp.1-14
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• 2005

Objectives: This study attempts to analyze the length of hospital stay and expenses of frequent disease admitted in a Vaterans Hospital. Methods: Data was collected from January 1, 2001 to December 31, 2003 from the Claim records of 9,640 patients in a Vaterans Hospital. Results: The results were as follows: 1. In age & sex distribution, there was male 70.9%, female 29.1%, and 35.8% of them is 70 age group. Frequency by insurance program was Health insurance 78.1%, Medical aid 14.2%, no insurance 4.1%, others 3.6%. Distribution of each department was internal medicine 28.3%, orthopedic surgery 21.3%, surgery 16.6%, neurosurgey 7.1%, pediatrics 5.9%. Also, in the veterans group, male to female patient ratio was 99.3% male to 0.7% female, them over 70 years old was 51.6%, and them which live in daejeon was 43.5%. 2. In frequency of disease, there was gastroenteritis 4.8%, pneumonia 3.8%, cartaract 3.7%, cerebral infarct 3.2%, hyperplasia of prostate 3.0%. In frequency of korean standard classification of diseases, there was injury and poisoning and certain other consequences of external causes 17.1%, diseases of digestive system 16.1%, diseases of musculoskeletal system and connective tissue 13.9%, diseases of respiratory system 9.4%, diseases of genitourinary system 8.6%. Also, in veterans group, frequency of them was diseases of musculoskeletal system and connective tissue 19.4%, diseases of digestive system 16.8%, injury and poisoning and certain other consequences of external causes 15.7%, diseases of genitourinary system 9.7%, diseases of circuatory system 8.2%. 3. Average length of hospital stay was 29.0 days for total patients, 51.8 days for the veterans group, 15.7 days for the non-veterans one. Average total expenses was 3,669,579 won, the veterans group 7,263,877 won, the non-veterans one 1,560,333 won. The ratio of insurer to insuree was 55.2 : 44.8, the ratio of amount paid by patient in the veterans group 61.7%, in the non-veterans one 33.0%. 4. In items of medical expenses, fee for hospital accommodation was 34.7%, fee for medication 13.2%(injection 7.8%, drug 5.4%), fee for service 48.6%(physical therapy 26.3%, operation 9.7%, laboratory examination 5.2%, radiological examination 3.1%, etc), others 3.4%. In them for the veterans group, fee for physical therapy was 35.3%, fee for hospital accommodation 35.2%, fee for injection 6.2%, fee for operation 5.9%, for the non-veterans one, fee for hospital accommodation 35.7%, fee for operation 16.4%, fee for injection 11.4%, fee for laboratory examination 8.3%. 5. In the comparison of the frequency by Korean standard classification of diseases and distance between the hospital and home, the region under 21.5Km was more frequent in symptoms, signs an abnormal clinical and laboratory findings 56.0%, injury and poisoning and certain other consequences of external causes 55.6%, diseases of the eye and adnexa 52.9%, the one over 21.5Km was more frequent in neoplasms 57.4%, diseases of musculoskeletal system and connective tissue 55.9%, diseases of genitourinary system 53.5%.

• Journal of the Korean Society of Food Science and Nutrition
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• v.38 no.6
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• pp.709-720
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• 2009

This study was conducted to identify daily caffeine intakes in beverages for elementary school children and to evaluate its effectiveness after nutrition education. The caffeine contents of 140 commercial beverages were analysed by high performance liquid chromatography-ultraviolet detector (HPLC-UV) and information about their consumption were obtained by surveying 267 children. Researchers gave nutrition education to the children, who were 6 to 11 years old and attended 9 classes of 3 elementary schools, by lecture, Powerpoint file and moving picture. Their preference and intake amount on beverages were investigated by questionnaire before and after nutrition education. The order on caffeine contents was coffee ($33.8{\pm}2.4{\sim}49.1{\pm}5.6\;mg/100\;mL$)> coffee milk ($10.6{\pm}3.3\;mg/100\;mL$)> cola ($6.0{\pm}2.4\;mg/100\;mL$)> green black oolong tea drink ($6.0{\pm}2.4\;mg/100\;mL$)> chocolate milk and chocolate drink ($1.6{\pm}0.7{\sim}1.7\;mg/100\;mL$)> black ice tea mix ($1.3{\pm}1.7\;mg/100\;mL$). The order on children's preference was carbonated drink and fruit and vegetable drink (27%)> sports drink (26%)> processed cocoa mix (7%)> milk (6%)> vitamin & functional drink (3%)> green tea drink (2%)> black tea drink and coffee (1%). The average daily caffeine intakes except tea drink was $5.9{\pm}11.2$ mg/person/day ($0.17{\pm}0.32$ mg/kg bw/day), ranged from $0.0{\sim}80.5$ mg/person/day for children. The sources of caffeine were coffee 57% (3.4 mg/person/day), coffee milk 20% (1.2 mg/person/day), carbonated drink 15% (0.9 mg/person/day), chocolate milk and chocolate drink 6% (0.4 mg/person/day), and vitamin & functional drink 2% (0.1 mg/person/day). After nutrition education, the preference of carbonated drink, coffee, vitamin drinks & functional drink was decreased significantly (p<0.05, p<0.05, p<0.01) and the intakes of carbonated drink, chocolate milk & chocolate drink, and vitamin & functional drink were also decreased significantly (p<0.01, p<0.05, p<0.01). This study has shown that nutrition education influences the preference and the intake behavior of caffeinated beverages.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.1-23
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• 2013

To discover significant social issues such as unemployment, economy crisis, social welfare etc. that are urgent issues to be solved in a modern society, in the existing approach, researchers usually collect opinions from professional experts and scholars through either online or offline surveys. However, such a method does not seem to be effective from time to time. As usual, due to the problem of expense, a large number of survey replies are seldom gathered. In some cases, it is also hard to find out professional persons dealing with specific social issues. Thus, the sample set is often small and may have some bias. Furthermore, regarding a social issue, several experts may make totally different conclusions because each expert has his subjective point of view and different background. In this case, it is considerably hard to figure out what current social issues are and which social issues are really important. To surmount the shortcomings of the current approach, in this paper, we develop a prototype system that semi-automatically detects social issue keywords representing social issues and problems from about 1.3 million news articles issued by about 10 major domestic presses in Korea from June 2009 until July 2012. Our proposed system consists of (1) collecting and extracting texts from the collected news articles, (2) identifying only news articles related to social issues, (3) analyzing the lexical items of Korean sentences, (4) finding a set of topics regarding social keywords over time based on probabilistic topic modeling, (5) matching relevant paragraphs to a given topic, and (6) visualizing social keywords for easy understanding. In particular, we propose a novel matching algorithm relying on generative models. The goal of our proposed matching algorithm is to best match paragraphs to each topic. Technically, using a topic model such as Latent Dirichlet Allocation (LDA), we can obtain a set of topics, each of which has relevant terms and their probability values. In our problem, given a set of text documents (e.g., news articles), LDA shows a set of topic clusters, and then each topic cluster is labeled by human annotators, where each topic label stands for a social keyword. For example, suppose there is a topic (e.g., Topic1 = {(unemployment, 0.4), (layoff, 0.3), (business, 0.3)}) and then a human annotator labels "Unemployment Problem" on Topic1. In this example, it is non-trivial to understand what happened to the unemployment problem in our society. In other words, taking a look at only social keywords, we have no idea of the detailed events occurring in our society. To tackle this matter, we develop the matching algorithm that computes the probability value of a paragraph given a topic, relying on (i) topic terms and (ii) their probability values. For instance, given a set of text documents, we segment each text document to paragraphs. In the meantime, using LDA, we can extract a set of topics from the text documents. Based on our matching process, each paragraph is assigned to a topic, indicating that the paragraph best matches the topic. Finally, each topic has several best matched paragraphs. Furthermore, assuming there are a topic (e.g., Unemployment Problem) and the best matched paragraph (e.g., Up to 300 workers lost their jobs in XXX company at Seoul). In this case, we can grasp the detailed information of the social keyword such as "300 workers", "unemployment", "XXX company", and "Seoul". In addition, our system visualizes social keywords over time. Therefore, through our matching process and keyword visualization, most researchers will be able to detect social issues easily and quickly. Through this prototype system, we have detected various social issues appearing in our society and also showed effectiveness of our proposed methods according to our experimental results. Note that you can also use our proof-of-concept system in http://dslab.snu.ac.kr/demo.html.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.1-20
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• 2013

Nowadays, social network is a huge communication platform for providing people to connect with one another and to bring users together to share common interests, experiences, and their daily activities. Users spend hours per day in maintaining personal information and interacting with other people via posting, commenting, messaging, games, social events, and applications. Due to the growth of user's distributed information in social network, there is a great potential to utilize the social data to enhance the quality of recommender system. There are some researches focusing on social network analysis that investigate how social network can be used in recommendation domain. Among these researches, we are interested in taking advantages of the interaction between a user and others in social network that can be determined and known as social relationship. Furthermore, mostly user's decisions before purchasing some products depend on suggestion of people who have either the same preferences or closer relationship. For this reason, we believe that user's relationship in social network can provide an effective way to increase the quality in prediction user's interests of recommender system. Therefore, social relationship between users encountered from social network is a common factor to improve the way of predicting user's preferences in the conventional approach. Recommender system is dramatically increasing in popularity and currently being used by many e-commerce sites such as Amazon.com, Last.fm, eBay.com, etc. Collaborative filtering (CF) method is one of the essential and powerful techniques in recommender system for suggesting the appropriate items to user by learning user's preferences. CF method focuses on user data and generates automatic prediction about user's interests by gathering information from users who share similar background and preferences. Specifically, the intension of CF method is to find users who have similar preferences and to suggest target user items that were mostly preferred by those nearest neighbor users. There are two basic units that need to be considered by CF method, the user and the item. Each user needs to provide his rating value on items i.e. movies, products, books, etc to indicate their interests on those items. In addition, CF uses the user-rating matrix to find a group of users who have similar rating with target user. Then, it predicts unknown rating value for items that target user has not rated. Currently, CF has been successfully implemented in both information filtering and e-commerce applications. However, it remains some important challenges such as cold start, data sparsity, and scalability reflected on quality and accuracy of prediction. In order to overcome these challenges, many researchers have proposed various kinds of CF method such as hybrid CF, trust-based CF, social network-based CF, etc. In the purpose of improving the recommendation performance and prediction accuracy of standard CF, in this paper we propose a method which integrates traditional CF technique with social relationship between users discovered from user's behavior in social network i.e. Facebook. We identify user's relationship from behavior of user such as posts and comments interacted with friends in Facebook. We believe that social relationship implicitly inferred from user's behavior can be likely applied to compensate the limitation of conventional approach. Therefore, we extract posts and comments of each user by using Facebook Graph API and calculate feature score among each term to obtain feature vector for computing similarity of user. Then, we combine the result with similarity value computed using traditional CF technique. Finally, our system provides a list of recommended items according to neighbor users who have the biggest total similarity value to the target user. In order to verify and evaluate our proposed method we have performed an experiment on data collected from our Movies Rating System. Prediction accuracy evaluation is conducted to demonstrate how much our algorithm gives the correctness of recommendation to user in terms of MAE. Then, the evaluation of performance is made to show the effectiveness of our method in terms of precision, recall, and F1-measure. Evaluation on coverage is also included in our experiment to see the ability of generating recommendation. The experimental results show that our proposed method outperform and more accurate in suggesting items to users with better performance. The effectiveness of user's behavior in social network particularly shows the significant improvement by up to 6% on recommendation accuracy. Moreover, experiment of recommendation performance shows that incorporating social relationship observed from user's behavior into CF is beneficial and useful to generate recommendation with 7% improvement of performance compared with benchmark methods. Finally, we confirm that interaction between users in social network is able to enhance the accuracy and give better recommendation in conventional approach.

• Korean Journal of Poultry Science
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• v.16 no.2
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• pp.61-71
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• 1989

The purposes of this study were to investigate the genetic variations by backcrossing in commercial chickens. Backcrossing was carried out successively back to parent stock (P.S). Heritabilities and genetic correlation coefficients were estimated to verify the genetic variations. The data obtained from a breeding programme with commercial chickens (I strain) were collected from 1955 to 1987 at Poultry Breeding Farm, Seoul National University. Data came from a total of 1230 female offspring. The results obtained are summarized as follows： 1. The general performance ($Mean\pmStandard deviation$) of each trait was $663.94\pm87.11$g for 8 weeks body weight, $1579.1\pm155.43$g for 20 weeks body weight, $2124.1\pm215.3$g for 40 weeks body weight, $2269.1\pm242.94$g for 60 weeks body weight, $168.43\pm12.94$ day for a9e at sexual maturity (SM), $214.52\pm29.82$ eggs , for total egg number to 60 weeks of age (TEN), $61.45\pm3.48$ g for average weight (AEW), $13180.7\pm1823.22$ g for total egg mass to 60 weeks of age(TEM). All traits, except 10 weeks body weight and AEW, were significant for the degrees of backcross (p＜0.01). 2. The pooled estimates of heritabilities derived from the sire, dam and combined variance components were 0.47~0.52 for age at sexual maturity (SM), 0.07~0.37 for total egg number (TEN), 0.40~0.54 for average egg weight (AEW), 0.18~0.27 for total egg mass (TEM). High heritability estimates were found for SM and AEW. TEN and TEM were estimated to be a lowly heritable traits. Heritability estimates from dam components were higher than those from sire components. These differences might be due to non-additive genetic effect and maternal effect. 3. The estimates of heritabilities and standard errors derived from combined variance components for different degrees of backcross were $0.47\pm0.11$ (BCO), $0.42\pm0.16$ (BC1), $0.51\pm0.29$ (BC2) for TEN, $0.59\pm0.20$ (BCO), $0.43\pm0.17$ (BC1), $0.35\pm0.18$ (BC2) for AEW, $0.28\pm0.12$(BC0), $0.20\pm0.11$(BC1), $0.18\pm0.14$ (BC2) for TEM. Heritability estimates for AEW and TEM were decreased by backcrossing while those for SM and TEN remained constant. Since backcrossing contributes to increased homozygosity, the genetic variation of the traits (AEW and TEM) decreased . 4. The pooled estimates of genetic correlation coefficients were -0.55 between SM and TEN, 0.20 between SM and AEW, -0.29 between TEN and AEW, 0.82 between TEM and TEN, 0.31 between TEM and AEW, -0.42 between TEM and SM. The genetic correlation between TEM and TEN was higher than that between TEM and AEW, and it was suggested that egg mass was strongly affected by egg number. Also, age at sexual maturity(SM) contributes to egg mass(TEM). 5. When backcrossing was carried out successively, the genetic correlation between TEM and TEN increased (BC0：0.79, BC1：0.82, BC2：0.91) but those between TEM and SM decreased (BC0：-0.54, BC1：-0.36, BC2：-0.09) with successive backcrosses.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.57-77
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• 2013

Social media has become one of the most popular media in web and mobile application. In 2011, social networks and blogs are still the top destination of online users, according to a study from Nielsen Company. In their studies, nearly 4 in 5active users visit social network and blog. Social Networks and Blogs sites rule Americans' Internet time, accounting to 23 percent of time spent online. Facebook is the main social network that the U.S internet users spend time more than the other social network services such as Yahoo, Google, AOL Media Network, Twitter, Linked In and so on. In recent trend, most of the companies promote their products in the Facebook by creating the "Facebook Page" that refers to specific product. The "Like" option allows user to subscribed and received updates their interested on from the page. The film makers which produce a lot of films around the world also take part to market and promote their films by exploiting the advantages of using the "Facebook Page". In addition, a great number of streaming service providers allows users to subscribe their service to watch and enjoy movies and TV program. They can instantly watch movies and TV program over the internet to PCs, Macs and TVs. Netflix alone as the world's leading subscription service have more than 30 million streaming members in the United States, Latin America, the United Kingdom and the Nordics. As the matter of facts, a million of movies and TV program with different of genres are offered to the subscriber. In contrast, users need spend a lot time to find the right movies which are related to their interest genre. Recent years there are many researchers who have been propose a method to improve prediction the rating or preference that would give the most related items such as books, music or movies to the garget user or the group of users that have the same interest in the particular items. One of the most popular methods to build recommendation system is traditional Collaborative Filtering (CF). The method compute the similarity of the target user and other users, which then are cluster in the same interest on items according which items that users have been rated. The method then predicts other items from the same group of users to recommend to a group of users. Moreover, There are many items that need to study for suggesting to users such as books, music, movies, news, videos and so on. However, in this paper we only focus on movie as item to recommend to users. In addition, there are many challenges for CF task. Firstly, the "sparsity problem"; it occurs when user information preference is not enough. The recommendation accuracies result is lower compared to the neighbor who composed with a large amount of ratings. The second problem is "cold-start problem"; it occurs whenever new users or items are added into the system, which each has norating or a few rating. For instance, no personalized predictions can be made for a new user without any ratings on the record. In this research we propose a clustering method according to the users' genre interest extracted from social network service (SNS) and user's movies rating information system to solve the "cold-start problem." Our proposed method will clusters the target user together with the other users by combining the user genre interest and the rating information. It is important to realize a huge amount of interesting and useful user's information from Facebook Graph, we can extract information from the "Facebook Page" which "Like" by them. Moreover, we use the Internet Movie Database(IMDb) as the main dataset. The IMDbis online databases that consist of a large amount of information related to movies, TV programs and including actors. This dataset not only used to provide movie information in our Movie Rating Systems, but also as resources to provide movie genre information which extracted from the "Facebook Page". Formerly, the user must login with their Facebook account to login to the Movie Rating System, at the same time our system will collect the genre interest from the "Facebook Page". We conduct many experiments with other methods to see how our method performs and we also compare to the other methods. First, we compared our proposed method in the case of the normal recommendation to see how our system improves the recommendation result. Then we experiment method in case of cold-start problem. Our experiment show that our method is outperform than the other methods. In these two cases of our experimentation, we see that our proposed method produces better result in case both cases.

• Journal of Korean Society of Forest Science
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• v.25 no.1
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• pp.13-47
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• 1975

Among the many species of bamboo, it is well known that the dwarf-type is widely distributed in the tropical regions, and the slender type in temperated zone. In the temperated zone the trees have extensively differentiated into one hundred species in 50 genera. In many oriental countries, the bamboo wood is being used as a material for construction and for the manufacture of technical instruments. The bamboo shoot is also regarded as a good and delicious edible resource. Moreover, recent medical investigation verifies that the sap of certain species of the bamboo is an antibiotic effect against cancer. Fortunately, it is very easy to propagate the bamboo trees by using cutting from southeastern Asian countries. This important resource can further be used as a significant source of pulp, which is becoming increasingly important. The classification system of this significant resource has not been completely established to date, even though its importance has been emphasized. Initiated by Canlevon Linne in the 18th century, a classification method concerning the morphological characteristics of flowers was the first step in developing a classification. But it was not an easy task to accomplish, because this type of classification system is based on the sexual organs in bamboo trees. Because the bamboo has a long life cycle of 60-120 years and classification according to this method was very difficult as the materials for the classification are not abundant and some species have changed, even though many references related to the morphological classification of bamboo trees are available nowadays. So, the certification of bamboo trees according to the morphological classification system is not reasonable for us. Consequently, the classification system of bamboo trees on the basis of endomorphological characteristics was initiated by Chinese-born Liese. And classification method based on the morphological characteristics of the vascular bundle was developed by Grosser. These classification methods are fundamentally related to Holltum's classification method, which stressed the morphology of the ovary. The author investigated to re-establish a new classification method based on the vascular sheath. Twenty-six species in 11 genera which originated from Formosa where used in the study. The results obtained from the investigation were somewhat coordinated with those of Crosser. Many difficulties were found in distinguishing the species of Bambusa and Dendrocalamus. These two species were critically differentiated under the new classification system, which is based on the existence of a separated vascular bundle sheath in the bamboo. According to these results, it is recommended that Babusa divided into two groups by placing it into either subspecies or the lower categories. This recommendation is supported by the observation that the evolutional pattern of the bamboo thunk which is from outward to inward. It is also supported by the viewpoint that the fundamental hypothesis in evolution is from simple to complex. There remained many problems to be solved through more critical examination by comparing the results to those of the classification based on the sexual organs method. The author observed the figure of the cross-sectional area of vascular trunk of bamboo tree and compared the results with those of Grosser and Liese, i.e. A, $B_1$, $B_2$, C, and D groups in classification. Group A and $B_2$ were in accordance with the results of those scholars, while group D showed many differences, Grosser and Liese divided bamboo into "g" type and "h" type according to the vascular bundle type; and they included Dendrocalamus and Bambusa in Group D without considering the type of vascular bundle sheath. However, the results obtained by the author showed that Dendrocalamus and Bambusa are differentiated from each other. By considering another group, "i" identified according to the existence of separated vascular bundle sheath. Bambusa showed to have a separated vascular bundle sheath while Dendrocalamus does not have a separated vascular bundle sheath. Moreover, Bambusa showed peculiar characteristics in the figure of vascular development, i.e., one with an inward vascular bundle sheath and the other with a bivascular bundle sheath (inward and outward). In conclusion, the bamboo species used in this experiment were classified in group D, without any separated vascular bundle sheath, and in group E, with a vascular bundle sheath. Group E was divided into two groups, i.e., and group $E_1$, with bivascular sheath, and group $E_2$, with only an inward vascular sheath. Therefore, the Bambusa in group D as described by Grosser and Liese was included in group E. Dendrocalamus seemed to be the middle group between group $E_l$ and group $E_2$ under this classification system which is summarized as follows: Phyllostachys-type: Group A - Phyllostachys, Chymonobambus, Arundinaria, Pseudosasa, Pleioblastus, Yashania Pome-type: Group $B_2$ - Schizostachyum, Melocanna Hemp-type: Group D - Dendrocalamu Bambu-type: Group $E_1$ - Bambusa ghi.

• Korean Journal of Heritage: History & Science
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• v.37
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• pp.285-307
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• 2004

Synthesize and examine petrological characteristic and geochemical characteristic by weathering formation of rock and progress of weathering laying stress on stone cultural properties of Unjusa temple of Chonnam Hwasun county site in this research. Examine closely weathering element that influence mechanical, chemical, mineralogical and physical weathering of rocks that accomplish stone cultural properties and these do quantification, wish to utilize by a basic knowledge for conservation scientific research of stone cultural properties by these result. Enforced component analysis of rock and mineralogical survey about 18 samples (pyroclastic tuff; 7, ash tuff; 4, granite ; 4, granitic gneiss; 3) all to search petrological characteristic and geochemical characteristic by weathering of Unjusa temple precinct stone cultural properties and recorded deterioration degree about each stone cultural properties observing naked eye. Major rock that constitution Unjusa temple one great geological features has strike of N30-40W and dip of 10-20NE being pyroclastic tuff. This pyroclastic tuff is ranging very extensively laying center on Unjusa temple and stone cultural properties of precinct is modeled by this pyroclastic tuff. Stone cultural propertieses of present Unjusa temple precinct are accomplishing structural imbalance with serious crack, and because weathering of rock with serious biological pollution is gone fairly, rubble break away and weathering and deterioration phenomenon such as fall off of a particle of mineral are appearing extremely. Also, a piece of iron and cement mortar of stone cultural properties everywhere are forming precipitate of reddish brown and light gray being oxidized. About these stone cultural properties, most stone cultural propertieses show SD(severe damage) to MD(moderate damage) as result that record Deterioration degree. X-ray diffraction analysis result samples of each rock are consisted of mineral of quartz, orthoclase,plagioclase, calcite, magnetite etc. Quartz and feldspar alterated extremely in a microscopic analysis, and biotite that show crystalline form of anhedral shows state that become chloritization that is secondary weathering mineral being weathered. Also, see that show iron precipitate of reddish brown to crack zone of tuff everywhere preview rock that weathering is gone deep. Tuffs that accomplish stone cultural properties of study area is illustrated to field of Subalkaline and Peraluminous, $SiO_2$(wt.%) extent of samples pyroclastic tuff 70.08-73.69, ash tuff extent of 70.26-78.42 show. In calculate Chemical Index of Alteration(CIA) and Weathering Potential Index(WPI) about major elements extent of CIA pyroclastic tuff 55.05-60.75, ash tuff 52.10-58.70, granite 49.49-51.06 granitic gneiss shows value of 53.25-67.14 and these have high value gneiss and tuffs. WPI previews that is see as thing which is illustrated being approximated in 0 lines and 0 lines low samples of tuffs and gneiss is receiving esaily weathering process as appear in CIA. As clay mineral of smectite, zeolite that is secondary weathering produce of rock as result that pick powdering of rock and clothing material of stone cultural properties observed by scanning electron micrographs (SEM). And roots of lichen and spore of hyphae that is weathering element are observed together. This rock deep organism being coating to add mechanical weathering process of stone cultural properties do, and is assumed that change the clay mineral is gone fairly in stone cultural properties with these. As the weathering of rocks is under a serious condition, the damage by the natural environment such as rain, wind, trees and the ground is accelerated. As a counter-measure, the first necessary thing is to build the ground environment about protecting water invasion by making the drainage and checking the surrounding environment. The second thing are building hardening and extirpation process that strengthens the rock, dealing biologically by reducing lichens, and sticking crevice part restoration using synthetic resin. Moreover, it is assumed to be desirable to build the protection facility that can block wind, sunlight, and rain which are the cause of the weathering, and that goes well with the surrounding environment.