• 한국대기환경학회지
• /
• 제6권1호
• /
• pp.11-21
• /
• 1990

To quantitatively estimate the effect of yellow sand(loess) fromt he Northern China, various soil sources having similar chemical compositions to yellow sands should be separated and identified. After that, mass contribution for yellow sand can be calculated. The study showed that it was impossible to solve this problem by the traditional bulk analyses. However, particle-by-particle analysis by a CCSEM (computer controlled scanning electron microscope) gave enormous potentials to solve it. To perform this study, seven soil source data analyzed by CCSEM were obtained from Texas, U.S.A. Initially, each soil date was classified into two groups, coarse and fine particle groups since the particle number distribution showed a minimum occurring at 5.2$\mu$m of aerodynamic diameter. Particles in each group were then classified into one of the 283 homogeneous particle classes by the universal classification rule which had been built by an expert system in the early study. Further, mass fractions and their uncertainties for each class in each source were calculated by the Jackknife method, and then source profile matrix for the 7 soil sources was created. To use the profile matrix in the study of source contribution, it is necessary to test the degree of collinearity among sources. The profiles were tested by the singular value decomposition method. As a result, each soil source characterized by artificially created variables was totally independent each other and is ready to use in source contribution studies as a receptor model.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
• /
• pp.394-399
• /
• 2002

In this paper, Multisource data classification methods based on Bayesian formula are considered. For this decision fusion scheme, the individual data sources are handled separately by statistical classification algorithms and then Bayesian fusion method is applied to integrate from the available data sources. This method includes the combination of each expert decisions where the weights of the individual experts represent the reliability of the sources. The reliability measure used in the statistical approach is common to all pixels in previous work. In this experiment, the weight factors have been assigned to have different value for all pixels in order to improve the integrated classification accuracies. Although most implementations of Bayesian classification approaches assume fixed a priori probabilities, we have used adaptive a priori probabilities by iteratively calculating the local a priori probabilities so as to maximize the posteriori probabilities. The effectiveness of the proposed method is at first demonstrated on simulations with artificial and evaluated in terms of real-world data sets. As a result, we have shown that Bayesian statistical fusion scheme performs well on multispectral data classification.

• Asia pacific journal of information systems
• /
• 제24권2호
• /
• pp.191-210
• /
• 2014

As mobile devices that can be connected to the Internet have spread and networking has become possible whenever/wherever, the Internet has become central in the dissemination and consumption of news. Accordingly, the ways news is gathered, disseminated, and consumed have changed greatly. In the traditional news media such as magazines and newspapers, expert editors determined what events were worthy of deploying their staffs or freelancers to cover and what stories from newswires or other sources would be printed. Furthermore, they determined how these stories would be displayed in their publications in terms of page placement, space allocation, type sizes, photographs, and other graphic elements. In turn, readers-news consumers-judged the importance of news not only by its subject and content, but also through subsidiary information such as its location and how it was displayed. Their judgments reflected their acceptance of an assumption that these expert editors had the knowledge and ability not only to serve as gatekeepers in determining what news was valuable and important but also how to rank its value and importance. As such, news assembled, dispensed, and consumed in this manner can be said to be expert-based recommended news. However, in the era of Internet news, the role of expert editors as gatekeepers has been greatly diminished. Many Internet news sites offer a huge volume of news on diverse topics from many media companies, thereby eliminating in many cases the gatekeeper role of expert editors. One result has been to turn news users from passive receptacles into activists who search for news that reflects their interests or tastes. To solve the problem of an overload of information and enhance the efficiency of news users' searches, Internet news sites have introduced numerous recommendation techniques. Recommendations based on popularity constitute one of the most frequently used of these techniques. This popularity-based approach shows a list of those news items that have been read and shared by many people, based on users' behavior such as clicks, evaluations, and sharing. "most-viewed list," "most-replied list," and "real-time issue" found on news sites belong to this system. Given that collective intelligence serves as the premise of these popularity-based recommendations, popularity-based news recommendations would be considered highly important because stories that have been read and shared by many people are presumably more likely to be better than those preferred by only a few people. However, these recommendations may reflect a popularity bias because stories judged likely to be more popular have been placed where they will be most noticeable. As a result, such stories are more likely to be continuously exposed and included in popularity-based recommended news lists. Popular news stories cannot be said to be necessarily those that are most important to readers. Given that many people use popularity-based recommended news and that the popularity-based recommendation approach greatly affects patterns of news use, a review of whether popularity-based news recommendations actually reflect important news can be said to be an indispensable procedure. Therefore, in this study, popularity-based news recommendations of an Internet news portal was compared with top placements of news in printed newspapers, and news users' judgments of which stories were personally and socially important were analyzed. The study was conducted in two stages. In the first stage, content analyses were used to compare the content of the popularity-based news recommendations of an Internet news site with those of the expert-based news recommendations of printed newspapers. Five days of news stories were collected. "most-viewed list" of the Naver portal site were used as the popularity-based recommendations; the expert-based recommendations were represented by the top pieces of news from five major daily newspapers-the Chosun Ilbo, the JoongAng Ilbo, the Dong-A Daily News, the Hankyoreh Shinmun, and the Kyunghyang Shinmun. In the second stage, along with the news stories collected in the first stage, some Internet news stories and some news stories from printed newspapers that the Internet and the newspapers did not have in common were randomly extracted and used in online questionnaire surveys that asked the importance of these selected news stories. According to our analysis, only 10.81% of the popularity-based news recommendations were similar in content with the expert-based news judgments. Therefore, the content of popularity-based news recommendations appears to be quite different from the content of expert-based recommendations. The differences in importance between these two groups of news stories were analyzed, and the results indicated that whereas the two groups did not differ significantly in their recommendations of stories of personal importance, the expert-based recommendations ranked higher in social importance. This study has importance for theory in its examination of popularity-based news recommendations from the two theoretical viewpoints of collective intelligence and popularity bias and by its use of both qualitative (content analysis) and quantitative methods (questionnaires). It also sheds light on the differences in the role of media channels that fulfill an agenda-setting function and Internet news sites that treat news from the viewpoint of markets.

• The Journal of Asian Finance, Economics and Business
• /
• 제5권2호
• /
• pp.139-149
• /
• 2018

In the contemporary era of smart tourism, travelers face more accommodation options than ever before. The rapid expansions of alternative accommodation sector are partially owing to the growth of electronic commerce and the rise of online intermediary platforms. Online travel agencies serve as a critical distribution channel for tourism sectors, and the significance is further increased for small and micro entrepreneurs whose direct communication channels are scarce. Considering the holistic process of customer experience started with a third-party online intermediary, this study explores basic and extended attributes of small and medium-sized alternative accommodation where the comparative value is created. In order to achieve the objective, a research design was developed to synthesize the qualitative evidence. The synthesis encompasses both theoretical and practical perspectives, from a systematic review and opinions of academic professionals to an in-depth interview with an industry expert and the current practices of online travel agencies. This study suggests that the sources of value creation for alternative accommodation are not always consistent with those of the traditional. Accounting for the temporal and spatial dynamics in customer experience, the findings of this study provide insights on the comparative value of alternative accommodation, to both academic and industry audiences.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2002년도 ITC-CSCC -2
• /
• pp.1165-1168
• /
• 2002

Knowledge acquisition is the process that extracts the required knowledge from available sources, such as experts, textbooks and databases, for incorporation into a knowledge-based system. Knowledge acquisition is described as the first step in building expert systems and a major bottleneck in the efficient development and application of effective knowledge based expert systems. One cause of the problem is that the process of human reasoning we need to understand for knowledge-based system development is not available for direct observation. Moreover, the expertise of interest is typically not reportable due to the compilation of knowledge which results from extensive practice in a domain of problem solving activity. This is also a problem of modeling knowledge, which has been described as not a problem of accessing and translating what is known, but the familiar scientific and engineering problem of formalizing models for the first time. And this formalization process is especially difficult for knowledge engineers who are often faced with the difficult task of creating a knowledge model of a domain unfamiliar to them. In this paper, we propose an automated knowledge acquisition tool which is based on an implementation of the Inferential Modeling Technique. The Inferential Modeling Technique is derived from the Inferential Model which is a domain-independent categorization of knowledge types and inferences ［Chan 1992］. The model can serve as a template of the types of knowledge in a knowledge model of any domain.

• Nuclear Engineering and Technology
• /
• 제46권5호
• /
• pp.619-632
• /
• 2014

The Best Estimate Plus Uncertainty (BEPU) method has been widely used to evaluate the uncertainty of a best-estimate thermal hydraulic system code against a figure of merit. This uncertainty is typically evaluated based on the physical model's uncertainties determined by expert judgment. This paper introduces the application of data assimilation methodology to determine the uncertainty bands of the physical models, e.g., the mean value and standard deviation of the parameters, based upon the statistical approach rather than expert judgment. Data assimilation suggests a mathematical methodology for the best estimate bias and the uncertainties of the physical models which optimize the system response following the calibration of model parameters and responses. The mathematical approaches include deterministic and probabilistic methods of data assimilation to solve both linear and nonlinear problems with the a posteriori distribution of parameters derived based on Bayes' theorem. The inverse problem was solved analytically to obtain the mean value and standard deviation of the parameters assuming Gaussian distributions for the parameters and responses, and a sampling method was utilized to illustrate the non-Gaussian a posteriori distributions of parameters. SPACE is used to demonstrate the data assimilation method by determining the bias and the uncertainty bands of the physical models employing Bennett's heated tube test data and Becker's post critical heat flux experimental data. Based on the results of the data assimilation process, the major sources of the modeling uncertainties were identified for further model development.

• 한국정보통신학회논문지
• /
• 제15권3호
• /
• pp.691-699
• /
• 2011

최근 사회망 기반의 검색 서비스들을 중심으로 다양한 방법들이 제시되고 있다. 기존의 추천시스템들은 특정 영역의 전문가를 검색할 수 있지만 검색하고자 하는 전문가에 대한 프로파일과 전문가를 평가하는 항목이 한 시스템에 있어야만 한다. 본 논문에서는 지식베이스와 XMDR을 이용하여 서로 다른 시스템에 존재하는 전문가 프로파일과 전문가를 평가하는 항목 수집을 자동화할 수 있다. 또한 다양한 리소스들을 이용하여 사회망을 동적으로 구축하여 여러 전문가를 추천할 수 있는 시스템을 구성하고자한다. 그러나 다양한 리소스들은 지역적으로 분산되어 있고 이종의 데이터 소스들로 구성되어있기 때문에 사용자 의사결정을 위한 정보를 얻는 것은 어렵다. 이러한 문제를 효율적으로 해결하기 위해서 사용자에게 단일 인터페이스를 제공하고 이종시스템들 간에 구축된 리소스들에는 각각 독립성과 투명성을 제공할 필요성이 있다. 따라서 본 논문에서는 분산되어있는 전문가 프로파일 추출을 위해 XMDR과 지식베이스를 이용하고 이러한 지식베이스를 사회망과 연계한 전문가 추천 시스템을 설계한다.

• Nutrition Research and Practice
• /
• 제15권2호
• /
• pp.137-159
• /
• 2021

Long-chain (LC) n-3 polyunsaturated fatty acids (n-3 PUFAs), in particular docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA), are nutrients involved in many metabolic and physiological processes, and are referred to as n-3 LCPUFA. They have been extensively studied for their effects in human nutrition and health. This paper provides an overview on metabolism, sources, dietary intake, and status of n-3 LCPUFA. A summary of the dietary recommendations for n-3 LCPUFAs for different age groups as well as specific physiological conditions is provided. Evidence for n-3 LCPUFA in cardiovascular diseases, including new studies, is reviewed. Expert recommendations generally support a beneficial effect of n-3 LCPUFA on cardiovascular health and recommend a daily intake of 500 mg as DHA and EPA, or 1-2 servings of fish per week. The role of n-3 LCPUFA on brain health, in particular neurodegenerative disorders and depression, is reviewed. The evidence for beneficial effects of n-3 LCPUFA on neurodegenerative disorders is non-conclusive despite mechanistic support and observational data. Hence, no definite n-3 LCPUFA expert recommendations are made. Data for the beneficial effect of n-3 LCPUFA on depression are generally compelling. Expert recommendations have been established: 200-300 mg/day for depression; up to 1-2 g/day for major depressive disorder. Recent studies support a beneficial role of n-3 LCPUFAs in reducing the risk for premature birth, with a daily intake of 600-800 mg of DHA during pregnancy. Finally, international experts recently reviewed the scientific evidence on DHA and arachidonic acid (ARA) in infant nutrition and concluded that the totality of data support that infant and follow-on formulas should provide both DHA and ARA at levels similar to those in breast milk. In conclusion, the available scientific data support that dietary recommendations for n-3 LCPUFA should be established for the general population and for subjects with specific physiological conditions.

• 디지털산업정보학회논문지
• /
• 제8권1호
• /
• pp.191-205
• /
• 2012

A book review is one of the most important sources of information which provide the descriptive and evaluative contents about books. Reviews have great influence on consumer behavior because they are believed to be more reliable than information provided by sellers. Readers who read a book review includes information about book decide whether they will buy or not. This study examines customer attitude change by book reviews with regarding to different type of information sources(experts and prior customers) and different directions of messages. We address the following research questions: (1) Can positive book reviews with credibility have a positive impact on acceptance of books? (2) Can negative book reviews with credibility have a negative impact on acceptance of books? The results shows that a credibility is an essential factor for affecting customers' mind. When positive book reviews were written, both expert and customer opinions have a positive impact on acceptance of customers. Given negative book reviews of experts, trustworthiness is more important than expertise. However, a objectivity of customer's reviews is more important.

• 경영정보학연구
• /
• 제8권2호
• /
• pp.51-72
• /
• 2006

본 연구에서는 인터넷에서 운영되는 비즈니스 모델 분류와 함께 각 모델 별로 주요 수익요인을 알아보았다. 선행 연구 결과들과 문헌 자료들을 참고하여 인터넷 비즈니스 모델을 판매모델, 중개모델, 광고료모델, 이용료모델로 분류하였으며, 이 들 각 모델들의 수익요인들을 문헌자료와 전문가인터뷰를 통해 선정하였다. 인터넷 비즈니스 모델별 주요수익요인의 차이여부를 파악하기 위하여, 2단계의 조사가 이루어졌다. 첫 단계는 전문가 조사로, 인터넷 비즈니스의 수익성에 영향을 미치는 항목전정 및 각 수익모델별 가중치를 파악하기 위해 이루어졌다. 인터넷 비즈니스 모델에 대한 이해와 경험이 풍부한 전문가들을 대상으로 인터뷰 조사 및 AHP 질문지에 대한 답변을 얻었다. 두 번째 단계의 조사로서, 위의 전문가 조사 단계에서 얻어진 평가 항목들을 사용하여, 직접 운영중인 인터넷 비즈니스 모델들에 있어서 각 요소들이 실로 중요하게 운영되고 관리되고 있는지를 설문 조사 하였다. 유효 설문 답변으로 파악된 각 평가항목별 획득점수에(1단계에서 파악된) 가중치를 곱하여 최종 평가값을 얻었으며, 그 차이를 수익모델 별로 분석하였다. 분석결과, 판매모델, 중개모델, 이용료모델은 사업전략이 가장 중요하였으며, 광고료모델은 운영효율이 가장 중요하였다. 사업전략 중, 판매모델은 수익률 증가 전략, 중개모델은 수익 고객 확보 전략, 이용료모델은 고객정의가 가장 중요한 활동으로 파악되었다.