• 한국컴퓨터정보학회논문지
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• 제28권11호
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• pp.209-226
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• 2023

국경 간 전자상거래는 중국의 대외무역을 안정시키고, 중국 대외무역의 전환과 업그레이드를 추동하며, 글로벌 경제 발전과 안정에 기여하는 결정적인 힘으로 부상했다. 이에 따라 국경 간 전자상거래의 고품질 발전을 추동하는 것은 중국 업계 내에서 공동의 난제로 되었습니다. 그러나 국경 간 전자상거래가 빠르게 성장하면서 품질 혼재, 치열한 경쟁, 가격 경쟁 등 새로운 현상과 도전에 직면해 있다. 브랜드는 주체를 식별하는 구별표지 역할을 하며 브랜드 구축은 국경 간 전자상거래에서 고품질 발전을 이룩하는 신중한 선택이다. 이 글은 정성적 접근법과 정량적 접근법이 결합된 브랜드 이론을 활용하며, 국경 간 전자상거래 기업 운영 내의 주요 요소에 구체적으로 초점을 맞춘다. 중국 국경 간 전자상거래 기업의 내부 운영 내에서 브랜드의 형성과 발전에 영향을 미치는 핵심 요소들에 대한 분석을 통해 그들의 내부 형성 메커니즘을 조사하고 브랜드 형성에 영향을 미치는 이들 중요요소들의 중요성을 평가한다. 연구과정은 해외 소비자의 데이터를 바탕으로 실증분석을 실시하여 궁극적으로 국경 간 전자상거래 기업의 브랜드 개발을 위한 일정한 지침을 제공하고 있다.

• Structural Engineering and Mechanics
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• 제89권1호
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• pp.33-46
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• 2024

The present research delves into the analysis of nonlinear free and forced vibrations of porous functionally graded (FG) shallow shells reinforced with oblique stiffeners, which are embedded in a nonlinear elastic foundation (NEF) subjected to external excitation. Two distinct types of PFG shallow shells, characterized by even and uneven porosity distribution along the thickness direction, are considered in the research. In order to model the stiffeners, Lekhnitskii's smeared stiffeners technique is implemented. With the stress function and first-order shear deformation theory (FSDT), the nonlinear model of the oblique stiffened shallow shells is established. The strain-displacement relationships for the system are derived via the FSDT and utilization of the von-Kármán's geometric assumptions. To discretize the nonlinear governing equations, the Galerkin method is employed. The model such developed allows analysis of the effects of the stiffeners with various angles as desired, in addition to the quantitative investigation on the influence of the surrounding nonlinear elastic foundations. To numerically solve the problem of vibrations, the 4th-order P-T method is used, as this method, known for its enhanced accuracy and reliability, proves to be an effective choice. The validation of the present research findings includes a comprehensive comparison with outcomes documented in existing literature. Additionally, a comparative analysis of the numerical results against those obtained using the 4th Runge-Kutta method is performed. The impact of stiffeners with varying angles and material parameters on the vibration characteristics of the present system is also explored. The researchers and engineers working in this field may use the results of this study as benchmarks in their design and research for the considered shell systems.

• 대한토목학회논문집
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• 제35권1호
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• pp.153-164
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• 2015

전면기초의 설계 방법은 사용되는 가정에 따라 강성법과 연성법으로 구분된다. 강성법에서는 전면기초가 무한 강체이며 기초저면의 접지압 분포를 평면형으로 가정한다. 그러나 실제 기초는 강체가 아니므로 접지압이 평면형이 아닌 곡면형인 경우가 대부분으로, 강성법를 적용하는 것은 정밀한 해석이 될 수 없으며 발생되는 오차를 감수해야 한다. 한편, 연성법에서는 전면기초를 탄성지반 위에 놓인 판으로 생각하는데, 이 탄성판이론은 탄성지반 위에 무한 폭을 가진 평판에 집중하중이 작용하는 경우에 해당한다. 그런데 연성법에 의해 구하려는 모멘트, 전단력, 처짐 함수식은 매우 복잡하여 설계자가 이용하는데 많은 어려움이 있다. 또한 구조물 기초설계기준에서 복잡한 수식대신 설계를 위해 제공되는 그래프는 최대모멘트나 최대전단력을 나타내는 위험단면에서 그 함수값을 포함하고 있지 않아 이를 활용할 수 없다. 따라서, 본 연구에서는 연성법을 설계자가 보다 쉽게 이용하기 위해 회귀분석을 통하여 모멘트와 전단력, 처짐의 단순화된 함수식을 제안하였으며, 제안된 함수식들은 매우 단순화되어 활용하기 쉽고 매우 정확한 값을 제공하고 있다.

• 산업진흥연구
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• 제5권3호
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• pp.53-60
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• 2020

본 연구는 하인즈 코헛의 자기(Self)이론을 기반으로, 자기대상(Selfobject) 기능을 상실한 내담자의 치료적 활성화를 위해 상담자의 전이대상 역할을 기술하였다. 본 연구에서 인간은 평생을 통해서 자기대상이 필요함을 확인하는 계기가 되었다고 할 수 있다. 다음으로는 변형적 내재화 과정을 언급하면 유아는 자기대상을 통한 최적의 좌절로 인하여 부모의 한계를 체험하면서 환상의 세계에서 현실로 돌아오게 된다. 전이대상으로 상담자 역할은 내담자가 응집적 자기를 확립하여, 적절한 자기대상을 선용하도록 하여야 한다. 그리고 내담자의 과대주의와 과시주의를 공감하고 상담자는 이상화 대상이 되어서 내담자가 인정받고 동일시할 수 있는 기회를 주어야 한다. 상담자는 상담 과정에서 내담자에게 최적의 좌절을 제공할 수 있다. 이때 상담자는 자신의 실수를 인정할 때 내담자는 상담자를 현실적으로 바라보게 되고 건강한 자기를 구축하여 변형적 내면화를 이룩하게 된다. 상담을 통해서 내담자에게 응집적 자기가 형성되면 타인을 공감하고 건강한 인간관계를 형성할 수 있다. 그러면 자신의 감정을 통제할 수 있고 비전을 가지게 된다. 그리고 내담자는 삶을 살아가면서 일생동안 적절한 대상과 관계를 맺으면서 살아갈 수밖에 없다고 인식하게 된다.

• 한국데이타베이스학회:학술대회논문집
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• 한국데이타베이스학회 1999년도 춘계공동학술대회: 지식경영과 지식공학
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• pp.175-186
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• 1999

Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support fer multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To date, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques' results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 1999년도 춘계공동학술대회-지식경영과 지식공학
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• pp.175-186
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• 1999

Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support for multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To data, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

• 대한간호학회지
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• 제26권1호
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• pp.73-93
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• 1996

This study aimed to analyse the test contents of the national examination for the registered nurses (NERN) over 3 years from 1991 to 1993 in Korea. In recent years in Korea, the MCQ(multiple choice question) has been showing to be a highly recognized method for assessing the qualification of registered nurses. Unfortunately, nursing faculties have found NERN had some bad MCQs through having evaluation workshop for Some MCQs often provide so many unwriting clues which become a bias of the results, and some items fell into the category of the lower level of educational taxonomy such as isolated recall a fact or data. Frequently the stems of the questions are ambigous, unclear, disputable, esoterical or trivial. Considering those fallacies of the national examination, it is very critical to review the test items to see whether it is of high quality, is more fair, reliable and objective in depth. Therefore, this study was done to provide data for the improvement of the test contents as well as the teachers's assessment skill. For this study, the ad hoc committee was composed of 16 members, including 5 education board members of Korean Academic Nurses Association and 11 nursing faculty members. This committee had one day panel discussion and filled the checklist for this study. The process of analysing data was held over 10 times during 1992-1994. The analysis focussed on educational taxonomy such as cognitive domain(knowledge), psychmotor domain (skill), affective domain(attitude) and the level of learning such as recall, understanding, problems solving, and learning area of theory and practice, and the learning content categorised by nursing process and disease process. The test analysed using difficulty index and the structure of the test items was analysed. The conclusions and suggestion as follows : 1. In learning area, the average ratio of the theory and practice was 1 : 1.1 which was less than 1 : 2 suggested by Korean National Health Institute, and the ratio was different by the 8 leaning subjects of nursing. 2. In category of the educational taxonomy, the knowledge domain was emphasized mostly（79. 7％）, the skill domain was 14.9％, and the attitude domain was 5.4％ only. 3. In the level of learning, generally, the test items of the level of recall（45.5％） and the understanding（46.3％） were covered almost and the problem solving was 8.1％. 4. In the learning contents, generally, the test items related to nursing process was 67.2％ and that of disease process was 32.8％. However, this proportion was different by the 8 leaning subjects. Even though the nursing diagnosis has been emphasized in nursing curricula recently, the test items of this was identified very few. 5. In the structure of the test item, some were not clear, incorrect grammar, unclear description and some have clues to answer. 6. In the item analysis, the non-acceptable level of the difficulty index (means too easy) was 65.7％, and the acceptable level was 33.9％. Considering the results we would like to suggest the followings, 1. Since the test items of knowledge domain was dominant, the test items of the practice domain and attitude domain should be emphasized more. 2. The regular review and analysis of NERN should be arranged in order to improve the quality of the test items which will give influence to the nursing education positively.

• 한국지구과학회지
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• 제26권6호
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• pp.511-523
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• 2005

본 연구에서는 한국 지구과학 올림피아드 문항의 질 향상 방안을 모색하고자 1회와 2회 예선 및 본선 문항을 다양한 측면에서 분석하였다. 문항 분석을 위해 내적 및 외적 문항 분류틀을 구안하여 적용하였다. 고전 검사이론을 적용하여 문항의 난이도와 변별도, 상관계수, 그리고 신뢰도를, 일반화가능도 이론을 적용하여 일반화가능 도를 각각 추정하였다. 문항 분류틀 적용 결과는 다음과 같다: (1) 내용 차원에서는 지질 영역과 천문 영역에, 지식 및 탐구과정 차원에서는 자료 분석 및 해석에 집중되는 경향을 보였다. 또한 맥락 차원에서는 거의 대부분의 문항이 교과서적인 상황을 토대로 한 것이었다. (2) 요구 사고 수준에서 예선과 본선간의 차이를 발견할 수 없었다. (3) 문항 표현 범주에서는 그림의 사용 비율이 가장 높았고, 문항 유형 범주에서는 예선은 선다형과 단답형의 비율이, 본선은 서술형의 비율이 높았다. 또한 문항 형식 범주에서는 중학부와 예선은 단독형의 비율이 높고, 고교부와 본선은 복합형의 비율이 높았다. 문항을 분석한 결과는 다음과 같다: (1) 중학부는 대체로 난이도가 낮고, 변별도는 적절하였다. 그러나 고교부는 일반고와 과학고간에 상당한 차이가 있었다. (2) 중학부는 대기 영역과 총점과의 상관이, 고교부는 천문 영역과 총점과의 상관이 가장 높았다. (3) 양호한 문항이 가장 많은 일반고부의 문항 내적 일관성신뢰도와 일반화가능도가 가장 높았다. (4) 일반 고는 출제된 문항 수로 적정 수준의 일반화가능 도에 도달되나, 중학부나 과학고는 출제된 문항보다 2배 이상 많은 문항수가 필요한 것으로 나타났다.

• 한국게임학회 논문지
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• 제8권3호
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• pp.43-50
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• 2008

UI(User Interface)디자인은 하드웨어의 발달과 다양하게 만들어지는 콘텐츠들로 인해 자체의 의미와 형태를 발전시켜왔다. 특히 입력장치와 그래픽기술의 발달로 인해 이용자와 콘텐츠와의 풍부해진 교감을 통해 이용자는 신체와 정신의 확장으로써 UI를 받아들이게 되었다. 본 연구에서는 디지털스토리텔링의 입장에서 UI를 재해석하여, 콘텐츠와 이용자 간의 역할을 관찰하고, 특히 그래픽 기반 게임에서 나타는 스토리 요소들의 구분과 이유 분석을 통한 스토리텔링UI의 이론적기반성립과 활용을 위한 요소탐구를 실시하였다. 이를 위해 그래픽 요소 및 입력장치의 활용의 입장과 논문 내에서 밝힌 분절형 스토리텔링의 적용체로써 게임이 적합함에 입각하여 요소연구대상으로 디아블로, 하프라이프, 홈월드를 선정, 분석하였다. 본 분석을 통해 게임의 UI와 콘텐츠의 결합형태에서 인터페이스가 부분적으로, 또는 특화된 형태로의 콘텐츠정보를 지님으로 디지털스토리텔링의 스토리분절과 선택의 역할을 하고 있음을 밝혔다. 또한 개발자가 내재시킨 스토리와 이용자가 인터페이스를 통해 재구성하는 스토리가 공존하는 공간으로써 작동하며 이는 인터페이스에 스토리요소의 대입과 활용이 가능함을 유추하였다. 스토리텔링UI는 각각의 분절된 스토리를 사용한 능동적 즐거움의 복합체로써 끊임없는 흥미를 발생시킬 수 있는 좋은 수단이 될 것이다. 게임UI를 통한 스토리 중심의 UI제작은 콘텐츠의 내면적 맥락을 살리는 동시에 인터페이스의 감성형 인터페이스의 구체적인 구성 방법에 대한 대안이 될 것이다.

• Asia pacific journal of information systems
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• 제22권1호
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• pp.53-77
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• 2012

Financial firms, especially large scaled firms such as KB bank, NH bank, Samsung Card, Hana SK Card, Hyundai Capital, Shinhan Card, etc. should be securely dealing with the personal financial information. Indeed, people have tended to believe that those big financial companies are relatively safer in terms of information security than typical small and medium sized firms in other industries. However, the recent incidents of personal information privacy invasion showed that this may not be true. Financial firms have increased the investment of information protection and security, and they are trying to prevent the information privacy invasion accidents by doing all the necessary efforts. This paper studies how effectively a financial firm will be able to avoid personal financial information privacy invasion that may be deliberately caused by internal staffs. Although there are several literatures relating to information security, to our knowledge, this is the first study to focus on the behavior of internal staffs. The big financial firms are doing variety of information security activities to protect personal information. This study is to confirm what types of such activities actually work well. The primary research model of this paper is based on Theory of Planned Behavior (TPB) that describes the rational choice of human behavior. Also, a variety of activities to protect the personal information of financial firms, especially credit card companies with the most customer information, were modeled by the four-step process Security Action Cycle (SAC) that Straub and Welke (1998) claimed. Through this proposed conceptual research model, we study whether information security activities of each step could suppress personal information abuse. Also, by measuring the morality of internal staffs, we checked whether the act of information privacy invasion caused by internal staff is in fact a serious criminal behavior or just a kind of unethical behavior. In addition, we also checked whether there was the cognition difference of the moral level between internal staffs and the customers. Research subjects were customer call center operators in one of the big credit card company. We have used multiple regression analysis. Our results showed that the punishment of the remedy activities, among the firm's information security activities, had the most obvious effects of preventing the information abuse (or privacy invasion) by internal staff. Somewhat effective tools were the prevention activities that limited the physical accessibility of non-authorities to the system of customers' personal information database. Some examples of the prevention activities are to make the procedure of access rights complex and to enhance security instrument. We also found that 'the unnecessary information searches out of work' as the behavior of information abuse occurred frequently by internal staffs. They perceived these behaviors somewhat minor criminal or just unethical action rather than a serious criminal behavior. Also, there existed the big cognition difference of the moral level between internal staffs and the public (customers). Based on the findings of our research, we should expect that this paper help practically to prevent privacy invasion and to protect personal information properly by raising the effectiveness of information security activities of finance firms. Also, we expect that our suggestions can be utilized to effectively improve personnel management and to cope with internal security threats in the overall information security management system.