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Resolving the 'Gray sheep' Problem Using Social Network Analysis (SNA) in Collaborative Filtering (CF) Recommender Systems (소셜 네트워크 분석 기법을 활용한 협업필터링의 특이취향 사용자(Gray Sheep) 문제 해결)

  • Kim, Minsung;Im, Il
    • Journal of Intelligence and Information Systems
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    • v.20 no.2
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    • pp.137-148
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    • 2014
  • 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

    . Past studies to improve CF performance typically used additional information other than users' evaluations such as demographic data. Some studies applied SNA techniques as a new similarity metric. This study is novel in that it used SNA to separate dataset. This study shows that performance of CF can be improved, without any additional information, when SNA techniques are used as proposed. This study has several theoretical and practical implications. This study empirically shows that the characteristics of dataset can affect the performance of CF recommender systems. This helps researchers understand factors affecting performance of CF. This study also opens a door for future studies in the area of applying SNA to CF to analyze characteristics of dataset. In practice, this study provides guidelines to improve performance of CF recommender systems with a simple modification.

  • Analysis of the Time-dependent Relation between TV Ratings and the Content of Microblogs (TV 시청률과 마이크로블로그 내용어와의 시간대별 관계 분석)

    • Choeh, Joon Yeon;Baek, Haedeuk;Choi, Jinho
      • Journal of Intelligence and Information Systems
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      • v.20 no.1
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      • pp.163-176
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      • 2014
    • Social media is becoming the platform for users to communicate their activities, status, emotions, and experiences to other people. In recent years, microblogs, such as Twitter, have gained in popularity because of its ease of use, speed, and reach. Compared to a conventional web blog, a microblog lowers users' efforts and investment for content generation by recommending shorter posts. There has been a lot research into capturing the social phenomena and analyzing the chatter of microblogs. However, measuring television ratings has been given little attention so far. Currently, the most common method to measure TV ratings uses an electronic metering device installed in a small number of sampled households. Microblogs allow users to post short messages, share daily updates, and conveniently keep in touch. In a similar way, microblog users are interacting with each other while watching television or movies, or visiting a new place. In order to measure TV ratings, some features are significant during certain hours of the day, or days of the week, whereas these same features are meaningless during other time periods. Thus, the importance of features can change during the day, and a model capturing the time sensitive relevance is required to estimate TV ratings. Therefore, modeling time-related characteristics of features should be a key when measuring the TV ratings through microblogs. We show that capturing time-dependency of features in measuring TV ratings is vitally necessary for improving their accuracy. To explore the relationship between the content of microblogs and TV ratings, we collected Twitter data using the Get Search component of the Twitter REST API from January 2013 to October 2013. There are about 300 thousand posts in our data set for the experiment. After excluding data such as adverting or promoted tweets, we selected 149 thousand tweets for analysis. The number of tweets reaches its maximum level on the broadcasting day and increases rapidly around the broadcasting time. This result is stems from the characteristics of the public channel, which broadcasts the program at the predetermined time. From our analysis, we find that count-based features such as the number of tweets or retweets have a low correlation with TV ratings. This result implies that a simple tweet rate does not reflect the satisfaction or response to the TV programs. Content-based features extracted from the content of tweets have a relatively high correlation with TV ratings. Further, some emoticons or newly coined words that are not tagged in the morpheme extraction process have a strong relationship with TV ratings. We find that there is a time-dependency in the correlation of features between the before and after broadcasting time. Since the TV program is broadcast at the predetermined time regularly, users post tweets expressing their expectation for the program or disappointment over not being able to watch the program. The highly correlated features before the broadcast are different from the features after broadcasting. This result explains that the relevance of words with TV programs can change according to the time of the tweets. Among the 336 words that fulfill the minimum requirements for candidate features, 145 words have the highest correlation before the broadcasting time, whereas 68 words reach the highest correlation after broadcasting. Interestingly, some words that express the impossibility of watching the program show a high relevance, despite containing a negative meaning. Understanding the time-dependency of features can be helpful in improving the accuracy of TV ratings measurement. This research contributes a basis to estimate the response to or satisfaction with the broadcasted programs using the time dependency of words in Twitter chatter. More research is needed to refine the methodology for predicting or measuring TV ratings.

    A Survey of Korean Consumers' Awareness on Animal Welfare of Laying Hens (산란계 동물복지에 대한 국내 소비자의 인지도 조사)

    • Hong, Eui-Chul;Kang, Hwan-Ku;Park, Ki-Tae;Jeon, Jin-Joo;Kim, Hyun-Soo;Kim, Chan-Ho;Kim, Sang-Ho
      • Korean Journal of Poultry Science
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      • v.45 no.3
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      • pp.219-228
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      • 2018
    • This study was conducted twice to investigate egg purchase behavior and perception on animal welfare of Korean consumers. This study included women, who were the main decision makers and caretakers in the household, and men with one-person household. This survey was conducted with by the Computer Assisted Web Interview and Gang Survey methods. On the key considerations factor, the highest response rate was considered to be 'price', and the response rate of considering 'packing date' increased in the second survey. At a reasonable price based on 10 eggs, the response rate was the highest at 53.8% and 42.9% in both the first and second surveys and the appropriate price averages were 2,482 won and 2,132 won, respectively. The highest rate of purchase of egg consumers from 'Large Mart' followed by 'Medium sized supermarket' and 'Chain supermarket'. As for the awareness about animal welfare, the recognition ratio (73.5%) was higher in the result of the second survey than the first. The cognitive period of animal welfare was 59.0% before the insecticide egg crisis and 41.0% thereafter. Regarding whether or not they have ever seen an animal welfare certification mark and an animal welfare animal farm certification mark, 59.6% of respondents said that they saw it for the first time and 37.6% answered that they knew the animal welfare certification mark. On the animal welfare system, the 'free-range' response rate was the highest at 85.8%. The 'free-range' fit response decreased by 34.2%p, while the 'barn' and 'European type' fit response increased by 13.2%p and 24.1%p, respectively. The number of 'I have never seen' and 'I have ever eaten' responses to the recognition and eating experience of animal welfare certified eggs decreased while the number of those who answered 'Have ever seen' and 'Have eaten' increased. The answer of purchasing animal welfare certified eggs at department stores, organic farming cooperatives, and internet shopping malls was higher than that of buying conventional eggs. Of the total respondents, 92.0% were willing to purchase an animal welfare egg before the price was offered, but after offering the prices of animal welfare eggs, the intention to purchase was 62.7%, which was about 30%p lower than before. The reason for purchasing an animal welfare certified egg was the highest score of 71.0% for 'I think it is likely to be high in food safety', and 38.1% for 'I think the price is high' for lack of intention to purchase. In the sensory evaluation of animal welfare eggs, egg color and skin texture of conventional eggs were significantly higher than those of certified welfare eggs (P<0.05), and boiled eggs showed that egg whites of animal welfare certified eggs were more (P<0.05). As a result, the results of this study will contribute to the activation of the animal welfare certification system for laying hens by providing basic data on consumer awareness to animal welfare certified farmers.

    Deriving adoption strategies of deep learning open source framework through case studies (딥러닝 오픈소스 프레임워크의 사례연구를 통한 도입 전략 도출)

    • Choi, Eunjoo;Lee, Junyeong;Han, Ingoo
      • Journal of Intelligence and Information Systems
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      • v.26 no.4
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      • pp.27-65
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      • 2020
    • Many companies on information and communication technology make public their own developed AI technology, for example, Google's TensorFlow, Facebook's PyTorch, Microsoft's CNTK. By releasing deep learning open source software to the public, the relationship with the developer community and the artificial intelligence (AI) ecosystem can be strengthened, and users can perform experiment, implementation and improvement of it. Accordingly, the field of machine learning is growing rapidly, and developers are using and reproducing various learning algorithms in each field. Although various analysis of open source software has been made, there is a lack of studies to help develop or use deep learning open source software in the industry. This study thus attempts to derive a strategy for adopting the framework through case studies of a deep learning open source framework. Based on the technology-organization-environment (TOE) framework and literature review related to the adoption of open source software, we employed the case study framework that includes technological factors as perceived relative advantage, perceived compatibility, perceived complexity, and perceived trialability, organizational factors as management support and knowledge & expertise, and environmental factors as availability of technology skills and services, and platform long term viability. We conducted a case study analysis of three companies' adoption cases (two cases of success and one case of failure) and revealed that seven out of eight TOE factors and several factors regarding company, team and resource are significant for the adoption of deep learning open source framework. By organizing the case study analysis results, we provided five important success factors for adopting deep learning framework: the knowledge and expertise of developers in the team, hardware (GPU) environment, data enterprise cooperation system, deep learning framework platform, deep learning framework work tool service. In order for an organization to successfully adopt a deep learning open source framework, at the stage of using the framework, first, the hardware (GPU) environment for AI R&D group must support the knowledge and expertise of the developers in the team. Second, it is necessary to support the use of deep learning frameworks by research developers through collecting and managing data inside and outside the company with a data enterprise cooperation system. Third, deep learning research expertise must be supplemented through cooperation with researchers from academic institutions such as universities and research institutes. Satisfying three procedures in the stage of using the deep learning framework, companies will increase the number of deep learning research developers, the ability to use the deep learning framework, and the support of GPU resource. In the proliferation stage of the deep learning framework, fourth, a company makes the deep learning framework platform that improves the research efficiency and effectiveness of the developers, for example, the optimization of the hardware (GPU) environment automatically. Fifth, the deep learning framework tool service team complements the developers' expertise through sharing the information of the external deep learning open source framework community to the in-house community and activating developer retraining and seminars. To implement the identified five success factors, a step-by-step enterprise procedure for adoption of the deep learning framework was proposed: defining the project problem, confirming whether the deep learning methodology is the right method, confirming whether the deep learning framework is the right tool, using the deep learning framework by the enterprise, spreading the framework of the enterprise. The first three steps (i.e. defining the project problem, confirming whether the deep learning methodology is the right method, and confirming whether the deep learning framework is the right tool) are pre-considerations to adopt a deep learning open source framework. After the three pre-considerations steps are clear, next two steps (i.e. using the deep learning framework by the enterprise and spreading the framework of the enterprise) can be processed. In the fourth step, the knowledge and expertise of developers in the team are important in addition to hardware (GPU) environment and data enterprise cooperation system. In final step, five important factors are realized for a successful adoption of the deep learning open source framework. This study provides strategic implications for companies adopting or using deep learning framework according to the needs of each industry and business.

    Study on Acknowledge and State of Clinical Experience for 3-years Dental Technology Department (3년제 치기공과 임상실습에 대한 인식 및 실태조사 - 일부 치과기공소 소장을 중심으로 -)

    • Park, Myung-Ja
      • Journal of Technologic Dentistry
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      • v.17 no.1
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      • pp.41-57
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      • 1995
    • This study was conducted to collect and analyze previous information in order to manage efficience, improve experience effect and promote employment rate. The questionnaire interview with 27 chief of dental Laboratory refered clinical experience in technology department about clinical experience in 14 Jumior colleges were also investigated. The results were summarried as follows : The portion of age of 35-39 among chief of dental Laboratory was 40.7% which was the highest, that of male was 96.3%, that of junior college graduate was 97.5%, that of 10years experience was 92.6% and that of ceramic technician was 85.2%, 63.0% dental laboratory for clinical experience was a bore space of 30pyong. Aspect of dental laboratory management, manufacturing all part of prosthetic restoration was 29.6%, othodontic appliance and ceramic restoration was 7.4%, 3.8%, each. The percentage of 40.7 was having connection with 30-3a dental clinics and referring case per day was 10-19 cases(40.7%), manufacturing time of referred prosthetic restoration was 3-4 days(77.8%), places preparing seminar room for education was 29.6%, above a place of 40pyong was 11.1% 30-34 pyong and 35-39 pyong was 7.4% each. During training of 2 years education course student, 18.5% was rack of thorough occupational career. While 44.4% will want the more salary among 3years education course student, 74.1% will expect the more dental techmicians would engaged in their field, 51.9% will hope improve of their theory and practice, 29.6% be expected better skill and 14.8% be expected better theory. Attitude of clinical experience places was distributed by 59.3% of offering only experience chance, 25.9% of wasting time and 29.0% of annoying. The big emphasis of climical experience was thorough occupational career(44.4%). The clinical experience places of our college were selected after direct visiting, so their condition of management was not that bad but most of dental laboratory were poor in management state and working environment. Therefore it is difficult to choose appropriate places and dental Laboratory are also limited manpower and time as suppliers. So that it recommended to induce flexible management of experience period by interval and rotation of experience places among college and to applicate intern-system for employment ant industry-college cooperation aspect.

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    Assessment of Inorganic Nutrients Contents of Seasonal Foods in Seoul (계절별 다소비식품 중 무기영양원소 함량 평가)

    • Lee, Kyeong-Ah;Jang, Mi-Ra;Kim, Ouk-Hee;Park, Young-Ae;Choi, Bu-Chuhl;Han, Sung-Hee;Kim, Li-La;Kim, Jin-Kyeong;Lee, Jib-Ho;Hwang, In-Sook;Oh, Young-Hee;Jung, Kweon
      • Journal of Food Hygiene and Safety
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      • v.32 no.2
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      • pp.123-128
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      • 2017
    • The purpose of this study was to determine the sodium (Na) and potassium (K) content of seasonal foods Four hundred food samples classified into 8 different kinds of seasonal foods were collected from 150 restaurants located in Seoul. The Na and K content in seasonal foods were the analyzed by ICP-OES. The Average content of Na and K in spicy seafood noodle soup were highest as $391.4{\pm}72.7mg$/100 g and $88.6{\pm}21.4mg$/100 g, respectly, while average content of Na was lowest in spicy buckwheat noodles as $255.3{\pm}67.0mg$/ 100 g and the average content of K was lowest in Udon as $36.3{\pm}17.8mg$/ 100 g, respectively. The Na/K ratio of spicy buckwheat noodles was $3.2{\pm}1.0$, while those of cold buckwheat noodles, fish cake, Udon were very high as measured more than 8. Among the seasonal foods, the average content of Na was highest in Winter group as $366.9{\pm}81.8mg$/ 100 g and the average content of K was highest in Autumn group as $84.8{\pm}24.1mg$/ 100 g. The ratio of Na/K was lowest in Summer group as $5.9{\pm}3.3$.

    Philosophical Stances for Future Nursing Education (미래를 향한 간호교육이념)

    • Hong Yeo Shin
      • The Korean Nurse
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      • v.20 no.4 s.112
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      • pp.27-38
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      • 1981
    • 오늘 저희에게 주어진 주제, 내일에 타당한 간호사업 및 간호교육의 향방을 어떻게 정하여야 하는가의 논의는 오늘날 간호계 주변에 일어나고 있는 변화의 실상을 이해하는 데서 비롯되어져야 한다고 생각하는 입장에서 먼저 세계적으로 건강관리사업이 당면한 딜레마가 어떠한 것이며 이러한 문제해결을 위해 어떠한 새로운 제안들이 나오고 있는가를 개관 하므로서 그 교육적 의미를 정의해 보고 장래 간호교육이 지향해야할 바를 생각해 보려 합니다. 오늘의 사회의 하나의 특징은 세계 모든 나라들이 각기 어떻게 전체 국민에게 고루 미칠 수 있는 건강관리체계를 이룩할 수 있느냐에 관심을 모으고 있는 사실이라고 봅니다. 부강한 나라에 있어서나 가장 빈궁한 나라에 있어서나 그 관심은 마찬가지로 나타나고 있읍니다. 보건진료 문제의 제기는 발달된 현대의학의 지식과 기술이 지닌 건강관리의 방대한 가능성과 건강 관리의 요구를 지닌 사람들에게 미치는 실질적인 혜택간에 점점 더 크게 벌어지는 격차에서 발생한다고 봅니다. David Rogers는 1960년대 초반까지 갖고 있던 의료지식의 축적과 민간인의 구매력 향상이 자동적으로 국민 건강의 향상을 초래할 것이라고 믿었던 순진한 꿈은 이루어지지 않았고 오히려 의료사업의 위기는 의료지식과 의료봉사간에 벌어지는 격차와 의료에 대한 막대한 투자와 그에서 얻는 건강의 혜택간의 격차에서 온다고 말하고 있읍니다. 균등 분배의 견지에서 보면 의료지식과 기술의 향상은 그 단위 투자에 대한 생산성을 낮춤으로서 오히려 장애적 요인으로 작용해온 것도 사실이고 의료의 발달에 따른 일반인의 기대 상승과 더불어 의료를 태성의 권리로 규명하는 의료보호사업의 확대로 야기되는 의료수요의 급증은 모두 기존 시설 자원에 압박을 초래하여 전래적 의료공급체제에 도전을 가해 왔으며 의료의 발달에 건 기대와는 달리 인류의 건강 문제 해결은 더욱 요원한 과제로 남게 되었읍니다. 현시점에서 세계인구의 건강문제는 기아, 영양실조, 안전한 식수 공급 및 위생적 생활환경조성의 문제에서부터 가장 정밀한 의료기술발달에 수반되는 의료사회문제에 이르는 다양한 문제를 지니고 있으며 주로 각개 국가의 경제 사회적 여건이 이 문제의 성격을 결정짓고 있다고 볼수 있읍니다. 그러나 건강 관리에 대한 요구는 영구히, 완전히 충족될 수 없는 요구에 속한다는 의미에서 경제 사회적 발달 수준에 상관없이 모든 국가가 공히 요구에 미치지 못하는 제한된 자원문제로 고심하고 있는 실정입니다. 또 하나의 공통된 관점은 각기 문제의 상황은 달라도 오늘날의 건강 문제는 주로 의료권 밖의 유전적 소인, 사회경제적, 정치문화적인 환경여건과 각기 선택하는 삶의 스타일에 깊이 관련되어 있다는 사실입니다. 따라서 오늘과 내일의 건강관리 문제는 의학적 견지에서 뿐 아니라 널리 경제, 사회, 정치, 문화적 관점에서 포괄적인 접근이 시도되어야 한다는 점과 의료의 고급화, 전문화, 일변도의 과정에서 소외되었던 기본건강관리체계 강화에 역점을 둔 다양하고 탄력성 있는 사업전개가 요구되고 있다는 점입니다. 다양한 건강관리요구에 적절히 대처할 수 있기 위한 그간 세계 각처에서 시도된 새로운 건강관리 접근과 그 제안을 살펴보면 대체로 4가지의 뚜렷한 성격들로 집약할 수 있을 것 같습니다. 그 첫째는 건강관리사업계획 및 그 수행에 있어 지역 사회의 적극적 참여를 유도하는 일, 둘째는 지역단위의 일차보건의료에서 부터 도심지 신예 종합병원, 시설 의료에 이르기까지 건강관리사업을 합리적으로 체계화하는 일. 셋째로 의료인력이용의 효율화 및 비의료인의 훈련과 협조 유발을 포함하는 효과적인 인력관리에 대한 제안과 넷째로 의료보험 및 각양 집단 의료유형을 포함하는 대체 의료재정 운영관리에 관련된 제안들을 들 수 있읍니다. 건강관리사업에 있어 지역사회 참여의 의의는 첫째로 사회 경제적인 제약이 모든 사람에게 가능한 최대한의 의료를 모두 고루 공급하기 어렵게 하고 있다는 점에서 제한된 정부재정과 지역사회가용자원을 보다 효율적으로 이용할 수 있게 하는 자조적이고 자율적인 지역사회건강관리체제의 구현에 있다고 볼 수 있으며 둘때로는 개인과 가족 및 지역민의 건강에 영향하는 많은 요인들은 실질적으로 의료권 외적 요인들로서 위생적인 생활양식, 식사습관, 의료시설이용 등 깊이 지역사회특성과 관련되어 국민보건의 실질적 향상을 위하여는 지역 주민의 자발적인 참여가 필수여건이 된다는 점 입니다. 지역 단위별 체계적인 의료사업의 전개는 제한된 의료자원의 보다 합리적이고 효율적인 이용을 가능하게 하며 요구가 있을때 언제나 가까운 거리에서 경제 사회적 제약을 받지 않고 이용할 수 있는 일차건강관리망을 통하여 건강에 관련된 정보를 얻으며 질병예방, 건강증진 및 기초적인 진료의 도움을 얻을 수 있고 의뢰에 대한 제2차, 제3차 진료에의 길은 건강관리사업의 질과 폭을 동시에 높고 넓게 해 줄 수 있는 길이 된다는 것입니다. 인력 관리에 관련된 두가지 기본 방향으로서는 첫째로 기존보건의료인력의 적정배치 유도이고 둘째는 기존인력의 역할확대, 조정 및 비의료인의 교육훈련과 부분적 업무대체를 들수 있으며 이러한 인력관리의 기본 방향은 부족되는 의료인력의 생산성을 높이고 주민들의 자조적 능력을 강화시킨다는 데에 두고 있음니다. 대체적 의료재정운영안은 대체로 의료공급과 재정관리를 이원화하여 주민의 경제능력이 의료수혜의 장애요소로 작용함을 막고 의료인의 경제적 동기에 의한 과잉치료처치에 의한 낭비를 줄임으로써 의료재정의 투자의 효과를 증대하는 데(cost-effectiveness) 그 기본방향을 두고 있다고 봅니다. 이러한 주변의료 사회적인 동향이 간호교육의 미래상에 끼치는 영향은 지대한 것이라 봅니다. 첫째로 장래 세계인구의 건강문제는 정치, 사회, 경제, 환경적인 의료권 밖의 요인들에 의해 더욱 크게 영향 받는다고 전제한다면 건강문제해결에 있어서도 전통적인 의료사업의 접근에서 더나아가 문제발생의 근원이 되는 생활개선이라는 차원에서 포괄적 접근을 생각하여야 하고 이를 위해선 정치, 경제, 사회전반에 걸친 깊이있는 이해과 주민의 생활환경에 직접 영향하는 교통수단, 통신망 mass media, 전력문제, 농업경영방법 및 조직적 사회활동 등 폭넓은 이해가 요구된다고 봅니다. 둘째로, 지역사회참여의 의의를 인정한다면 지역민의 자발적 참여를 효과적으로 유발시킬수 있고 의료집단과 각종 주민조직과 일반주민들 사이에서 협조적으로 일할수 있는 역량을 기르기위한 교육적 준비가 요구된다고 봅니다. 셋째로, 지역주민의 건강관리 자조능력 강화를 하나의 목표로 삼는다면 치료자에서 교육자로, 지도자에서 촉진자로, 제공자에서 지원자료의 역할의 변화 내지 다양화를 요구하게 될 것이므로 그에 대처할 수 있는 준비가 필요하다고 봅니다. 넷째로, 생각되어야 할 점은 지역중심건강관리사업을 지향하는 보건의료의 이념적 방향과 그에 상응하는 구체적 접근방법을 효율적으로 적용하기 위해서는 종횡으로 연결되는 의사소통체계의 정립과 민활한 정보교환이 이루어질 수 있어야 한다는 점에서 의사소통의 구심체로서 역할할 수 있는 역량을 함양해야 할 교육적 과제가 있다고 봅니다. 마지막으로 생각되어야 할 점은 지역중심으로 전개될 건강관리사업은 건강증진 및 질병예방적 측면과 질병진료 및 회복과 재활에 이르는 종합적이고 포괄적인 사업이어야 한다는 점에서 종래 공공 의료부문과 사설의료기관 사이에 나누어져 있던 예방의학과 치료의학의 통합 뿐 아니라 정부주축으로 이루어 지고 있는 지역사회개발사업 및 농촌지도사업과 종교 및 각종 민간인 집단이 벌이고있는 사업들과의 전체적인 통합적 접근이 이루어져야 한다고 생각하는 입장에서 종래 간호교육이 강조하지 않던 진료의 의무와 대외적 조직활동에 대한 보완적인 교육조치가 요구된다고 봅니다. 간호의 학문체계로서의 입장은 오랜 역사를 두고 논의의 대상이 되어왔으나 아직까지 뚜렷이 어떤 것이 간호 특유의 지식체계이며 건강문제에 관련하여 무엇이 간호특유의 결정영역이며 이 결정과 그 결과를 어떠한 방법으로 치료적 행위로 옮길 수 있는가에 대한 확실한 답을 얻지 못하고 있는 실정이라고 봅니다. 다만 근래에 제시된 여러 간호이론들 속에서 공통적으로 이야기되어지고 있는 개념들로선 우선 간호학문을 건강과 질병에 관련된 인간의 전인적이고 전체적인 상황을 다루는 학제적 과학으로서보는 입장이 있고 따라서 생물신체적인 면 외에 정신심리적, 사회경제적, 정치문화적 환경과의 상호작용 속에서 인간의 건강과 질병문제를 생각한다는 지향을 갖고 있다고 말할 수 있겠읍니다. 간호교육은 간호계 내적인 학문적, 이론적 체계화의 요구에 못지않게 대민봉사하는 전문직으로서의 사회적 책임을 감당해야하는 중요과제를 안고있어 변화하는 사회요구에 효과적으로 대처해 나가야 할 당면문제를 안고 있읍니다. 간효역할 확대, 보건진료원훈련 등 이러한 사회적 요구에 대응하려는 조치가 되겠읍니다. 이러한 시점에서 간호계가 분명히 짚고 넘어가야 할 사실은 이러한 움직임들이 종래의 의사들의 외업무공급을 연장 확대하는 입장에 서서 간호의 특수전문직 명목을 흐리게 할수있는 위험을 감수할 것인지 아니면 가능한 대체방안을 갖고 간호전문직의 독자적인 진로를 개척하면서 다각적인 도전을 받아들일 준비를 갖추든지 그 방향을 뚜렷이 해야할 일이라 생각합니다. 저로서는 이미 잘 훈련된 간호원들과 조산원들의 교육적, 경험적 배경을 기반으로 지역사회 최일선 건강관리요원으로 사회적 효능을 다 할수 있는 일차건강관리간호조직의 구현을 대체방안으로 제시하고 싶습니다. 간호원과 조산원들의 훈련된 역량과 건강관리체제의 구조적 변화를 효과적으로 조화시킨다면 대부분의 세계인구의 건강문제는 해결가능하다고 보는 입장입니다. 물론 정책과 의료와 행정적지원이 활성화되어지는 환경속에서만 그 기대하는 결과가 확대되리라는 점 부언하는 바입니다. 마지막으로 언급하고 싶은 점은 바로 오늘의 주제 ''교육의 동역자-선생과 학생''이라는 개념입니다. 특히 상회정의적 입장에서 보는 의료사업전개에 지역민 내지 의료소비자의 참여를 강조하는 현시점에 있어 교육자와 학생이 교육의 현장에서 서로 동역자로서 학습의 책임을 나누는 경험은 아주 시기적으로 적합하여 교육적으로 지대한 의미를 갖는 것이라고 생각합니다. 이에 수반되어져야 할 역할의 변화에 수용적인 자세를 갖고 적극 실제적용하려 노력하는 선생앞에서 자주적 결정을 행사해본 학생이야말로 건강관리대상자로 하여금 같은 결정권을 행사할수 있도록 촉구하여 주민의 자조적 역량을 기르고 의료사업의 민주화, 인간화를 이룩할 수 있는 길잡이가 될 수 있으리라 믿는 바입니다.

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    A Study to Evaluate the Efficacy of CBCT and EXACTRAC on Spine Stereotactic Body Radiation Therapy (CBCT와 EXACTRAC을 이용한 Spine SBRT의 유용성 평가)

    • Choi, Woo Keun;Park, Su Yeon;Park, Do Keun;Song, Ki Won
      • The Journal of Korean Society for Radiation Therapy
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      • v.25 no.2
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      • pp.167-173
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      • 2013
    • Purpose: This study is to evaluate the efficacy of the CBCT and EXACTRAC the image on the spine stereotactic body radiation treatment. Materials and Methods: The study compared the accuracy of the dose distribution for changes in the real QA phantom for The shape of the body of the phantom was performed. Novalis treatment artificially set up at the center and to the right, on the Plan 1 mm, 2 mm, 3 mm in front 1 mm, 2 mm, 3 mm and upwards 1 mm, 2 mm, 3 mm and $0.5^{\circ}$ by moving side to side Exactrac error correction and error values of CBCT and plan changes on the dose distribution were recorded and analyzed. Results: Cubic Phantom of the experimental error, the error correction Exactrac X-ray 6D Translation in the direction of the 0.18 mm, Rotation direction was $0.07^{\circ}$. Translation in the direction of the 3D CBCT 0.15 mm Rotation direction was $0.04^{\circ}$. DVH dose distribution using the results of the AP evaluate the change in the direction of change was greatest when moving. Conclusion: ExacTrac image-guided radiation therapy with a common easy and fast to get pictures from all angles, from the advantage of CBCT showed a potential alternative. But every accurate information compared with CT treatment planning and treatment of patients with more accurate than the CBCT ExacTrac the location provided. Changes in the dose distribution in the experiment results show that the treatment of spinal SBRT set up some image correction due to errors at the target and enter the spinal cord dose showed that significant differences appear.

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    Diagnostic Efficacy of Anorectal Manometry for the Diagnosis of Hirschsprung's Disease (Hirschsprung병에서 항문직장 내압검사의 진단적 유용성)

    • Chang, Soo-Hee;Min, Uoo-Gyung;Choi, Ok-Ja;Kim, Dae-Yeon;Kim, Seong-Chul;Yu, Chang-Sik;Kim, Jin-Cheon;Kim, In-Koo;Yoon, Jong-Hyun;Kim, Kyung-Mo
      • Pediatric Gastroenterology, Hepatology & Nutrition
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      • v.6 no.1
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      • pp.24-31
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      • 2003
    • Purpose: As diagnostic tools for Hirschsprung's disease (HD), barium enema and rectal biopsy have radiation exposure and invasiveness respectively; however anorectal manometry does not have these disadvantages. We therefore performed this study to evaluate the diagnostic efficacy of anorectal manometry. Methods: We reviewed medical records of infants with one or two symptoms of vomiting, abdominal distension, chronic diarrhea or constipation who had a anorectal manometry followed by barium enema and/or biopsy from July 1995 to May 2002. We evaluated the sensitivity, specificity and predictive value of anorectal manometry and barium enema for diagnosis of HD. We also measured sphincter length, median value of balloon volume at which rectoanal inhibitory reflex (RAIR) occurred. Results: All 61 patients received anorectal manometry, 33 of 61 received barium enema. 18 of 61 were diagnosed as HD according to histology and 43 of 61 were evaluated as a control. The sensitivity, specificity, positive predictive value, negative predictive value of anorectal manometry and barium enema for diagnosis of HD were 1.00, 0.91, 0.82, 1.00 and 0.93, 0.67, 0.70, 0.92 respectively. The mean value of sphincter length in control was $1.68{\pm}0.67$ cm and correlated with age, weight and significantly longitudinal length. The median value of balloon volume at which RAIR occurred was 10 mL and did not correlated with age, weight and longitudinal length. Conclusion: This study suggests that anorectal manometry is an excellent initial screening test for Hirschsprung's disease because of its safety and accuracy.

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    Finite Element Method Modeling for Individual Malocclusions: Development and Application of the Basic Algorithm (유한요소법을 이용한 환자별 교정시스템 구축의 기초 알고리즘 개발과 적용)

    • Shin, Jung-Woog;Nahm, Dong-Seok;Kim, Tae-Woo;Lee, Sung Jae
      • The korean journal of orthodontics
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      • v.27 no.5 s.64
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      • pp.815-824
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      • 1997
    • The purpose of this study is to develop the basic algorithm for the finite element method modeling of individual malocclusions. Usually, a great deal of time is spent in preprocessing. To reduce the time required, we developed a standardized procedure for measuring the position of each tooth and a program to automatically preprocess. The following procedures were carried to complete this study. 1. Twenty-eight teeth morphologies were constructed three-dimensionally for the finite element analysis and saved as separate files. 2. Standard brackets were attached so that the FA points coincide with the center of the brackets. 3. The study model of a patient was made. 4. Using the study model, the crown inclination, angulation, and the vertical distance from the tip of a tooth was measured by using specially designed tools. 5. The arch form was determined from a picture of the model with an image processing technique. 6. The measured data were input as a rotational matrix. 7. The program provides an output file containing the necessary information about the three-dimensional position of teeth, which is applicable to several finite element programs commonly used. The program for a basic algorithm was made with Turbo-C and the subsequent outfile was applied to ANSYS. This standardized model measuring procedure and the program reduce the time required, especially for preprocessing and can be applied to other malocclusions easily.

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