Since the globalization, many changes are occurring in our society. Multicultural phenonmenon in the society is becoming one of our major concern in the Korean society. Thus, this study is focusing on the multicultural phenomenon that we are facing since the globalization in Korea. No doubt that immigration is a growing force influencing the demographics of Korea. Since the mid-1990s, immigrant children and children from mixed marriage have become the fastest growing and the most extraordinarily diverse segment of Korea's child population. Until the recent past, Korea's major social attention has focused on adult immigrants to the neglect of their offspring, creating a profound gap between the strategic importance of the new second generation and the knowledge about its socioeconomic circumstances. In other words, there is a significant lack of studies on children of migrant, particularly from the Muslim background living in Korea. International marriage has grown rapidly in Korea since the late 1990s, and this phenomenon is especially common in rural farming communities. Most brides come from China, followed by Vietnam and other southeast Asian countries. However, there are certain number of Muslim bride coming to Korea. There are about 100 thousand muslim peoples living in Korean society. Among them 2.92% are Muslim immigrants' intermarriage with the Koreans. As a result, there are growing number of muslim brides and bridegroom settling in Korea, which would eventually create muslim families in growing korean multicultural societies. This study specify its research on the muslim mixed family by focusing on the offsprings of the muslim background. Our research team has created the new term on such research subject by using Koslim. Koslim is a 1.5 and 2nd generation from the Muslim back ground family living in Korea. Thus, the objective of this study is to examine the awareness and the perception of Koslim by the Korean mainstream people. By doing so, it can analyze the general attitude of Koreans towards the Koslim people. In this sense this study intends to play a groundwork to promote successful coexistence between Korean and Koslim. It is anticipated that this research can lay the basis for Koreans to have more open and tolerant attitude towards our new members of society that is increasing everyday.
Purpose: Soft tissue reconstruction of a defect around the foot and ankle is a particularly challenging procedure due to the anatomical and functional characteristics of this area. Hence, only a limited number of treatment options are available. Moreover, if patients wish to avoid additional scars on the ipsilateral lower leg for cosmetic reasons, even fewer options are available for treatment. The authors used an anterolateral thigh perforator flap for soft tissue defects in this area, when other surgical options were inadequate. The aim of this study was to report the clinical results and the efficacy of this procedure. Materials and Methods: Sixteen cases of soft tissue defects around the foot and ankle were included. Participants included 12 male and 4 female subjects, and the mean age was 34 years. The most common cause of defect was acute trauma, and the average follow-up period was 33 months. Flap survival time, surgical complications, and ambulation status at the final follow-up stage were evaluated. Results: All 16 flaps successfully survived, except for one case with partial flap necrosis that was thought to be due to weight bearing earlier than scheduled. All patients were able to walk independently without any aid at the final follow-up stage. No patients showed other significant surgical complications. Conclusion: The anterolateral thigh perforator flap is a good alternative for soft tissue defects of the foot and ankle, when other options are not applicable. This study also demonstrated that surgery using an anterolateral thigh perforator flap is safe and highly reliable.
Developed nations are increasingly seeking to secure competitiveness in the international market through the development of human resources of workers in high value-added industries. And what is especially important in this process is the fact that workers, employers, and concerned government agencies are participating together in building and improving workers' skills through partnerships. This is based on the perception that workers training programs conducted according to the interest of one side are difficult to bring desired results. For the past decades, Korea has focused mostly on labor-management-government partnerships and strategies for developing the human resources of workers in developed nations in Europe. Related case studies show labor-management-government partnerships in European countries established through powerful trade unions, and interested parties actively cooperate and participate in employment and training programs that benefit both workers and employers. In contrast, studies on human resource development participated by workers and employers are relatively rare in the US, the reason being the lack of a mechanism for establishing labor-management-government partnership due to the country's strong tradition of decentralization and the emphasis on market principles. However, while it is difficult to find such channels for dialogue between workers, employers, and the government in th US on the federal level, there are many regional-level or industry-level programs that tackle common problems through partnerships between interested parties. This study analyzes how the regional labor-management-government partnerships in the US work and examines the types of programs operated by investigating the One-Stop Center based on the Workforce Investment Act and the Wisconsin Regional Training Partnership. While the One-Stop Center is a regional labor-management-government partnership model that is institutionally executed in each state according to the Workforce Investment Act, the WRTP is a regional labor-management -government partnership model led by the private sector. The two examples are introduced in the OECD as best practice examples of regional partnerships, and are key references to Korea's current human resource development policy.
Buddhist dance (seungmu) is a crux and highlight of Korean traditional dance; its aesthetics and technique are extraordinary, and Korean dance's unique style is well expressed. The Buddhist dance, which has been descended, is divided into Han Yeong Suk style, which is designated as Important Intangible Asset Number 27, and Lee Mae Bang style. While the two dances are same one, area is difference and they have unique style because of genealogical difference. However, studies on Buddhist dance so far have focused on single style's dance, or comparison of regional aspects (Han Yeong Suk dance is from Gyeonggi and Lee Mae Bang dance is from Honam area). But, Lee Byeong Ok suggested traditional artist dance is differed by male dance genealogy and female dance (gibang) genealogy dance, and while folk dance has storng tie with region, but artist dance has weak regional tie. Therefore, the purpose of this thesis is to study genealogical character of Buddhist dance's dancing style, clarifying Han Yeong Suk dance is male dance genealogy and Lee Mae Bang dance is gibang dance genealogy. In other words, among three theses that compared Lee Mae Bang and Han Yeong Suk dances, one analyzing movement, one comparing dance of invocation and one comparing traditional ballad, are re-analyzed from genealogical perspective and characteristics are comparatively analzyed. The overall summary of the genealogical attitude of the Han Yeong Suk and Lee Mae Ban dances is; First, Han's dance has masculinity, upwardness, progressiveness, activeness, outgoing character, boldness and grace, which are character of male dance lineage, while Lee's dance shows feminity, downwardness, backwardness, aesthecity, inwardness, delicacy and coquette. Second, the most expressed parts of the attitude of two dances are genealogical character, and then are original and regional characters. Third, two dances have strong genealogical attitude, but also has anti-genealogical attitude since the gender of descendent was changed, in other words Lee Mae Bang was man, and Han Yeong Suk was woman. Fourth, even though the two Buddhist dances have different genealogy and region, they share similarities as traditional dance descended in the same time period, so there are many common features. In other words, the two dances are Korean nation's dance and from same time period, but they should not be mixed, either. Even though they have small differences, they must keep each genealogy and descend to the next generation.
Data on reported cancer mortality in the Gyeongsangbuk- do province from 1991 to 1998 were collected and analyzed using the existing mortality reporting system as well as the public health network to furnish accurate data on reported cancer death and to collect data to establish a high quality district health plan. The overall crude death rate in Gyeongsangbuk province in 1991 was 74.56 deaths per 100,000-person but this rate increased to 79.22 in 1998. Among the deaths, the overall death rate of cancer was 16.7% in 1991, which increased to 19.3% in 1998; specifically the death rate of men increased from 19.4% in 1991 to 22.3% in 1998 while that of women increased from 12.4% in 1991 to 15.5% in 1998, showing a more increase among women. The types of cancer and associated death rates in 1991 were gastric cancer(41.5%), followed by liver cancer (28.8%), and lung and bronchogenic carcinoma(8.7%) and in 1998, gastric cancer (24.7%), followed by liver cancer(22.7%), lung and bronchogenic carcinoma(19.3%), showing the same order. For men and women, gastric cancer(40.2% and 44.7%, respectively) was the most common cancer death, followed by liver cancer(33.7% and 16.7%, respectively), and lung and bronchogenic carcinoma(10.2% and 5.0%, respectively) in 1991. However, in 1998, gastric cancer(27.8%) was still the most common type among both men and women, followed by liver cancer (18.5%) and lung and bronchogenic carcinoma(12.7%), showing the most decrease in gastric cancer but most increase in lung and bronchogenic carcinoma. The age- adjusted mortality rates by gastric cancer, hepatoma, laryngeal carcinoma were decreased in both male and female, and also uterine cancer was decreased in female. The age- adjusted mortality rates by lung and bronchogenic carcinoma, pancreatic cancer, rectal cancer were increased in both male and female, and also breast cancer was increased in female. The calculated overall age-adjusted death rate based on the 1995 population was 84.25 in 1991, which decreased to 77.67 in 1998. Male death rate decreased significantly from 119.81 in 1991 to 101.82 in 1998 while the female death rate increased from 48.64 in 1991 to 53.80 in 1998. A census of cancer death rate using accurate death records is important for the establishment of proper and high-quality district health and medical plan and policy. The effort to improve the accuracy of death reports using the health facility network, as had been attempted by this study, can be continued. Furthermore, there must be a way for the Health and Welfare Department to use the death reports to improve the present reporting system. Lastly, additional studies need to be conducted to investigate how much the accuracy was improved by the supplemented death reports in this study.
Recommender system has become one of the most important technologies in e-commerce in these days. The ultimate reason to shop online, for many consumers, is to reduce the efforts for information search and purchase. Recommender system is a key technology to serve these needs. Many of the past studies about recommender systems have been devoted to developing and improving recommendation algorithms and collaborative filtering (CF) is known to be the most successful one. Despite its success, however, CF has several shortcomings such as cold-start, sparsity, gray sheep problems. In order to be able to generate recommendations, ordinary CF algorithms require evaluations or preference information directly from users. For new users who do not have any evaluations or preference information, therefore, CF cannot come up with recommendations (Cold-star problem). As the numbers of products and customers increase, the scale of the data increases exponentially and most of the data cells are empty. This sparse dataset makes computation for recommendation extremely hard (Sparsity problem). Since CF is based on the assumption that there are groups of users sharing common preferences or tastes, CF becomes inaccurate if there are many users with rare and unique tastes (Gray sheep problem). This study proposes a new algorithm that utilizes Social Network Analysis (SNA) techniques to resolve the gray sheep problem. We utilize 'degree centrality' in SNA to identify users with unique preferences (gray sheep). Degree centrality in SNA refers to the number of direct links to and from a node. In a network of users who are connected through common preferences or tastes, those with unique tastes have fewer links to other users (nodes) and they are isolated from other users. Therefore, gray sheep can be identified by calculating degree centrality of each node. We divide the dataset into two, gray sheep and others, based on the degree centrality of the users. Then, different similarity measures and recommendation methods are applied to these two datasets. More detail algorithm is as follows: Step 1: Convert the initial data which is a two-mode network (user to item) into an one-mode network (user to user). Step 2: Calculate degree centrality of each node and separate those nodes having degree centrality values lower than the pre-set threshold. The threshold value is determined by simulations such that the accuracy of CF for the remaining dataset is maximized. Step 3: Ordinary CF algorithm is applied to the remaining dataset. Step 4: Since the separated dataset consist of users with unique tastes, an ordinary CF algorithm cannot generate recommendations for them. A 'popular item' method is used to generate recommendations for these users. The F measures of the two datasets are weighted by the numbers of nodes and summed to be used as the final performance metric. In order to test performance improvement by this new algorithm, an empirical study was conducted using a publically available dataset - the MovieLens data by GroupLens research team. We used 100,000 evaluations by 943 users on 1,682 movies. The proposed algorithm was compared with an ordinary CF algorithm utilizing 'Best-N-neighbors' and 'Cosine' similarity method. The empirical results show that F measure was improved about 11% on average when the proposed algorithm was used