• 가정∙방문간호학회지
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• 제11권1호
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• pp.5-13
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• 2004

The home health care industry has grown rapidly and can be expected to continue to grow in the foreseeable future. Home health care refers to the practice of nursing applied to clients with a health condition in the clients place of residence. clients and their designated care givers are the focus at home health nursing practice. The goal of care is to initiate. manage and evaluate the resources needed to promote the clients optimal level of well-being and function. Nursing activities necessary to achieve this goal may warrant preventive maintenance and restorative emphases to prevent potential problems from developing. Many project program were suggested home health care model for Korea's health care system and policy direction for expansion and establishment of home health care .But the aim of this paper is to provide on overview for theoretical frame work in home health care. Theories and conceptual frameworks or models are important nursing because they define and guide the boundaries of professional practice and identify key nurse-patient-caregiver relationships that emerge with caring. Following is the research with an investigation of the literature review in the University of Arizona international medline database, In conclusion, are as followers: First, many nursing theorists have had a tremendous impact on nursing practice. the following highlights those nursing theorists that are particularly helpful in understanding home health care. 1. Florence Nightingale : Our earliest theoretical legacy. Nightingale's believes are reflected in basic infection control practice such as hand washing and infectious waste disposal and are key nursing interventions in home care. 2. Martha Roger's :Science of unitary human beings theory. Rorger's believed that the focus of shared. non invasive healing modelities is the human environmental field rather than direct physical care. These modelities continue to evolve as our awareness (reflecting greater diversity, faster rhythms, motions, and ways of knowing) transcends time and space, allowing individuals to get in touch with their integral nature of unbroken wholeness. On people as ever changing energy fields have special relevance in home care especially with hospice and palliative care applications. 3. Madeline Leininger's; Transcultural nursing theory. Home care nurses move through a variety of communities and often care for patients from different cultural back grounds. Therefore Leininger's work has a good that with home care because home care nursing practice is very culturally focused. 4. Dorothea Orem's : Self care deficit theory. Orem's theory views care as something to be performed by both nurses and patients. The role of the nurse is to provide education and support that help patients acquire the necessary activities to perform self-care. Orem's theory is foundational to have care because it begins to truly acknowledge the role of the patient in managing his or her own health. which is referred to as self-care. 5. Margaret Neuman's; Health as expending consciousness theory. Neuman believes that health compasses disease and reflects an underlying pattern of person-environment interaction. A key application of 'Neuman's work to home care is for nurses to understand that health and illness do not necessarily exist at opposite ends of a continuum. 6. Jean Watson's: Theory of human caring. Watson's theory of human caring in nursing proposes human caring as the moral ideal of nursing. Nurses participate human caring to protect, enhance and preserve humanity by assisting individuals to fing meaning in illness. pain and existence and to help others gain self knowledge. self control. and self healing such thinking lends richness to theory development. as well as clinical practice in home care. Second, Robin Rice : Dynamic self determination for self care. (A theoretical framework for home care) Dynamical self determination for self care can be useful to home care nurses in a variety of ways. As research tool it can be reflected in the interview process when the home visit. The home care nurse's role is that of facilitator of patient self-determination for self care through numerous strategies. including patient education and case management.

• 지능정보연구
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• 제18권1호
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• pp.125-141
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• 2012

본 연구는 최근 그 중요성이 한층 높아지고 있는 침입탐지시스템(IDS, Intrusion Detection System)의 침입탐지모형을 개선하기 위한 방안으로 유전자 알고리즘에 기반한 새로운 통합모형을 제시한다. 본 연구의 제안모형은 서로 상호보완적 관계에 있는 이분류 모형인 로지스틱 회귀분석(LOGIT, Logistic Regression), 의사결정나무(DT, Decision Tree), 인공신경망 (ANN, Artificial Neural Network), 그리고 SVM(Support Vector Machine)의 예측결과에 적절한 가중치를 부여해 최종 예측결과를 산출하도록 하였는데, 이 때 최적 가중치의 탐색을 위한 방법으로는 유전자 알고리즘을 사용한다. 아울러, 본 연구에서는 1차적으로 오탐지율을 최소화하는 최적의 모형을 산출한 뒤, 이어 비대칭 오류비용 개념을 반영해 오탐지로 인해 발생할 수 있는 전체 비용을 최소화할 수 있는 최적 임계치를 탐색, 최종적으로 가장 비용 효율적인 침입탐지모형을 도출하고자 하였다. 본 연구에서는 제안모형의 우수성을 확인하기 위해, 국내 한 공공기관의 보안센서로부터 수집된 로그 데이터를 바탕으로 실증 분석을 수행하였다. 그 결과, 본 연구에서 제안한 유전자 알고리즘 기반 통합모형이 인공신경망이나 SVM만으로 구성된 단일모형에 비해 학습용과 검증용 데이터셋 모두에서 더 우수한 탐지율을 보임을 확인할 수 있었다. 비대칭 오류비용을 고려한 전체 비용의 관점에서도 단일모형으로 된 비교모형에 비해 본 연구의 제안모형이 더 낮은 비용을 나타냄을 확인할 수 있었다. 이렇게 실증적으로 그 효과가 검증된 본 연구의 제안 모형은 앞으로 보다 지능화된 침입탐지시스템을 개발하는데 유용하게 활용될 수 있을 것으로 기대된다.

• 지능정보연구
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• 제19권2호
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• pp.73-85
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• 2013

정보기술의 비약적 발전에 힘입어, 오늘날 기업들은 지금까지 축적한 고객 데이터를 기반으로 맞춤형 서비스를 제공하는 것에 많은 관심을 가지고 있다. 고객에게 소구하는 맞춤형 서비스를 효과적으로 제공하기 위해서는 우선 그 고객이 처한 상태나 상황을 정확하게 인지하는 것이 중요하다. 특히, 고객에게 서비스가 전달되는 이른바 진실의 순간에 해당 고객의 감정 상태를 정확히 인지할 수 있다면, 기업은 더 양질의 맞춤형 서비스를 제공할 수 있을 것이다. 이와 관련하여 사람의 얼굴과 행동을 이용하여 사람의 감정을 판단하고 개인화 서비스를 제공하기 위한 연구가 활발하게 이루어지고 있다. 얼굴 표정을 통해 사람의 감정을 판단하는 연구는 좀 더 미세하고 확실한 변화를 통해 정확하게 감정을 판단할 수 있지만, 장비와 환경의 제약으로 실제 환경에서 다수의 관객을 대상으로 사용하기에는 다소 어려움이 있다. 이에 본 연구에서는 Plutchik의 감정 분류 체계를 기반으로 사람들의 행동을 통해 감정을 추론해내는 모형을 개발하는 것을 목표로 한다. 본 연구는 콘텐츠에 의해 유발된 사람들의 감정적인 변화를 사람들의 행동 변화를 통해 판단하고 예측하는 모형을 개발하고, 4가지 감정 별 행동 특징을 추출하여 각 감정에 따라 최적화된 예측 모형을 구축하는 것을 목표로 한다. 모형 구축을 위해 사람들에게 적절한 감정 자극영상을 제공하고 그 신체 반응을 수집하였으며, 사람들의 신체 영역을 나누었다. 특히, 모션캡쳐 분야에서 널리 쓰이는 차영상 기법을 적용하여 사람들의 제스쳐를 추출 및 보정하였다. 이후 전처리 과정을 통해 데이터의 타임프레임 셋을 20, 30, 40 프레임의 3가지로 설정하고, 데이터를 학습용, 테스트용, 검증용으로 구분하여 인공신경망 모형을 통해 학습시키고 성과를 평가하였다. 다수의 일반인들을 대상으로 수집된 데이터를 이용하여 제안 모형을 구축하고 평가한 결과, 프레임셋에 따라 예측 성과가 변화함을 알 수 있었다. 감정 별 최적 예측 성과를 보이는 프레임을 확인할 수 있었는데, 이는 감정에 따라 감정의 표출 시간이 다르기 때문인 것으로 판단된다. 이는 행동에 기반한 제안된 감정예측모형이 감정에 따라 효과적으로 감정을 예측할 수 있으며, 실제 서비스 환경에서 사용할 수 있는 효과적인 알고리즘이 될 수 있을 것으로 기대할 수 있다.

• Asia pacific journal of information systems
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• 제24권4호
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• pp.443-472
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• 2014

To survive in the global competitive environment, enterprise should be able to solve various problems and find the optimal solution effectively. The big-data is being perceived as a tool for solving enterprise problems effectively and improve competitiveness with its' various problem solving and advanced predictive capabilities. Due to its remarkable performance, the implementation of big data systems has been increased through many enterprises around the world. Currently the big-data is called the 'crude oil' of the 21st century and is expected to provide competitive superiority. The reason why the big data is in the limelight is because while the conventional IT technology has been falling behind much in its possibility level, the big data has gone beyond the technological possibility and has the advantage of being utilized to create new values such as business optimization and new business creation through analysis of big data. Since the big data has been introduced too hastily without considering the strategic value deduction and achievement obtained through the big data, however, there are difficulties in the strategic value deduction and data utilization that can be gained through big data. According to the survey result of 1,800 IT professionals from 18 countries world wide, the percentage of the corporation where the big data is being utilized well was only 28%, and many of them responded that they are having difficulties in strategic value deduction and operation through big data. The strategic value should be deducted and environment phases like corporate internal and external related regulations and systems should be considered in order to introduce big data, but these factors were not well being reflected. The cause of the failure turned out to be that the big data was introduced by way of the IT trend and surrounding environment, but it was introduced hastily in the situation where the introduction condition was not well arranged. The strategic value which can be obtained through big data should be clearly comprehended and systematic environment analysis is very important about applicability in order to introduce successful big data, but since the corporations are considering only partial achievements and technological phases that can be obtained through big data, the successful introduction is not being made. Previous study shows that most of big data researches are focused on big data concept, cases, and practical suggestions without empirical study. The purpose of this study is provide the theoretically and practically useful implementation framework and strategies of big data systems with conducting comprehensive literature review, finding influencing factors for successful big data systems implementation, and analysing empirical models. To do this, the elements which can affect the introduction intention of big data were deducted by reviewing the information system's successful factors, strategic value perception factors, considering factors for the information system introduction environment and big data related literature in order to comprehend the effect factors when the corporations introduce big data and structured questionnaire was developed. After that, the questionnaire and the statistical analysis were performed with the people in charge of the big data inside the corporations as objects. According to the statistical analysis, it was shown that the strategic value perception factor and the inside-industry environmental factors affected positively the introduction intention of big data. The theoretical, practical and political implications deducted from the study result is as follows. The frist theoretical implication is that this study has proposed theoretically effect factors which affect the introduction intention of big data by reviewing the strategic value perception and environmental factors and big data related precedent studies and proposed the variables and measurement items which were analyzed empirically and verified. This study has meaning in that it has measured the influence of each variable on the introduction intention by verifying the relationship between the independent variables and the dependent variables through structural equation model. Second, this study has defined the independent variable(strategic value perception, environment), dependent variable(introduction intention) and regulatory variable(type of business and corporate size) about big data introduction intention and has arranged theoretical base in studying big data related field empirically afterwards by developing measurement items which has obtained credibility and validity. Third, by verifying the strategic value perception factors and the significance about environmental factors proposed in the conventional precedent studies, this study will be able to give aid to the afterwards empirical study about effect factors on big data introduction. The operational implications are as follows. First, this study has arranged the empirical study base about big data field by investigating the cause and effect relationship about the influence of the strategic value perception factor and environmental factor on the introduction intention and proposing the measurement items which has obtained the justice, credibility and validity etc. Second, this study has proposed the study result that the strategic value perception factor affects positively the big data introduction intention and it has meaning in that the importance of the strategic value perception has been presented. Third, the study has proposed that the corporation which introduces big data should consider the big data introduction through precise analysis about industry's internal environment. Fourth, this study has proposed the point that the size and type of business of the corresponding corporation should be considered in introducing the big data by presenting the difference of the effect factors of big data introduction depending on the size and type of business of the corporation. The political implications are as follows. First, variety of utilization of big data is needed. The strategic value that big data has can be accessed in various ways in the product, service field, productivity field, decision making field etc and can be utilized in all the business fields based on that, but the parts that main domestic corporations are considering are limited to some parts of the products and service fields. Accordingly, in introducing big data, reviewing the phase about utilization in detail and design the big data system in a form which can maximize the utilization rate will be necessary. Second, the study is proposing the burden of the cost of the system introduction, difficulty in utilization in the system and lack of credibility in the supply corporations etc in the big data introduction phase by corporations. Since the world IT corporations are predominating the big data market, the big data introduction of domestic corporations can not but to be dependent on the foreign corporations. When considering that fact, that our country does not have global IT corporations even though it is world powerful IT country, the big data can be thought to be the chance to rear world level corporations. Accordingly, the government shall need to rear star corporations through active political support. Third, the corporations' internal and external professional manpower for the big data introduction and operation lacks. Big data is a system where how valuable data can be deducted utilizing data is more important than the system construction itself. For this, talent who are equipped with academic knowledge and experience in various fields like IT, statistics, strategy and management etc and manpower training should be implemented through systematic education for these talents. This study has arranged theoretical base for empirical studies about big data related fields by comprehending the main variables which affect the big data introduction intention and verifying them and is expected to be able to propose useful guidelines for the corporations and policy developers who are considering big data implementationby analyzing empirically that theoretical base.