• Clinical Psychopharmacology and Neuroscience
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• 제16권4호
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• pp.489-493
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• 2018

Objective: This study was to identify whether working memory (WM) can be clearly subdivided according to auditory and visual modality. To do this, we administered the most recent and universal clinical WM measures in a mixed psychiatric sample. Methods: A total of 115 patients were diagnosed on the basis of DSM-IV diagnostic criteria and with MINI-Plus 5.0, a structured diagnostic interview. WM subtests of Korean version of Wechsler Adult Intelligence Scale-IV and Korean version of Wechsler Memory Scale-IV were administered to assess WM. Confirmatory factor analysis (CFA) was used to observe whether WM measures fit better to a one-factor or two-factor model. Results: CFA results demonstrated that a two factor model fits the data better than one-factor model as expected. Conclusion: Our study supports a modality model of WM, or the existence of modality-specific WM systems, and thus poses a clinical significance of assessing both auditory and visual WM tests.

• Journal of Multimedia Information System
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• 제9권3호
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• pp.191-200
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• 2022

These days, businesses, in both online and offline, have started accepting cryptocurrencies as payment methods. Even in countries like El Salvador, cryptocurrencies are recognized as fiat currencies. Meanwhile, publicly known, but not patched software vulnerabilities are security threats to not only software users but also to our society in general. As the status of cryptocurrencies has gradually increased, the impact of security vulnerabilities related to cryptocurrencies on our society has increased as well. In this paper, we first analyze vulnerabilities from the two major cryptocurrency vendors of Bitcoin and Ethereum in a quantitative manner with the respect to the CVSS, to see how the vulnerabilities are roughly structured in those systems. Then we introduce a modified AML vulnerability discovery model for the vulnerability datasets from the two vendors, after showing the original AML dose not accurately represent the vulnerability discovery trends on the datasets. The analysis shows that the modified model performs better than the original AML model for the vulnerability datasets from the major cryptocurrencies.

• 국제학술발표논문집
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• The 1th International Conference on Construction Engineering and Project Management
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• pp.503-508
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• 2005

In the modern, distributed and dynamic construction environment it is important to exchange information from different sources and in different data formats in order to improve the processes supported by these systems. Previous research has demonstrated that (i) a significant percentage of construction data is stored in semi-structured or unstructured data formats (ii) locating and identifying such data that are needed for the important decision making processes is a very hard and time-consuming task. In this paper, an automated methodology for the classification and retrieval of construction images in AEC/FM model based systems will be presented. Specifically, a combination of techniques from the areas of image processing, computer vision, and content-based image retrieval have been deployed to develop a method that can retrieve related construction site image data from components of a project model.

• The Journal of Asian Finance, Economics and Business
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• 제9권1호
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• pp.153-166
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• 2022

The study estimates the Structured VAR and the Dynamic Stochastic General Equilibrium Model for the Vietnamese economy based on the new Keynesian model for small and open economies, with the output gap, inflation, policy interest rate, the Vietnamese exchange rate, and the inflation and interest rate in the United States. The paper aims to clarify the impulse response of the macro variables through their shocks. It offers to model the SVAR and DSGE processes, as well as describe why and how interest rate policy is important in the impulse response of macro variables like the output gap and inflation process. The study supports the central role of monetary policy by giving empirical evidence for the new Keynesian theory, according to which an interest rate shock causes the output gap to widen and inflation to decrease. Finally, the application of the DSGE model is becoming more and more popular in the State Bank of Viet Nam to improve its policy planning, analyzing, and forecasting policy towards sustainable and stable growth.

• 한국과학교육학회지
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• 제18권3호
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• pp.347-355
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• 1998

학생의 선개념은 일상적 상황의 경험을 바탕으로 형성된 반면, 과학적 개념은 이상화된 상황을 전제로 하여 형성된 것이므로, 개념변화에 필요한 학생의 인지갈등을 유발하려면 이러한 상황의 불일치를 고려할 펼요가 있다. 또한, 학생들은 자신의 생각과 불일치한 현상을 대면하였을 때, 적당한 보조가설을 도입하여 이를 설명하려 함으로 개념변화가 이루어지지 않을 수 있다. 오히려, 과학적 개념이 일상적 상황에서 잘 맞지 않는다고 학생들이 생각할 수 있으므로, 과학적 개념에 따른 보조 가설을 도입하여 일상적 상황의 현상을 설명할 필요가 있다. 본 연구에서는 이러한 점들을 고려한 개념변화 모형을 구안하고, 이에 따라서 보조 가설의 대비를 통한 인지갈등의 명료화, 이상적 상황의 관찰을 통한 과학적 개념의 개념적 지위 상승, 교량적 실험활동을 통한 학생의 선개념의 지위 하강을 통하여 개념변화가 이루어지게 하는 세 단계로 구성된 학습지도 모형인 '구조화된 대비활동'을 제안하였다.

• 인지과학
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• 제10권4호
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• pp.71-83
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• 1999

기존의 기호주의 적 추론 시스템은 경직성 문제로 인하여 유연성을 결여하고 있다. 이는 기호주의 적 지식표현 체계가 지식의 유연한 의미구조를 충분히 반영하고 있지 못할 뿐 아니라 추론 방법도 논리를 바탕으로 하기 때문이다. 이러한 문제를 해결하기 위하여, 우리는 최근 인공 신경 망에 기반 한 유연한 지식표현과 추론을 위한 연결주의 적 의미 망(CSN)을 제안한 바 있다. CSN은 인간의 유사성과 연관성에 기반 하여 근사 추론과 상식추론을 수행할 수 있다. 그러나 CSN 모델에서는 상위개념간의 관계를 표현하는 데 있어서 단순한 전향 신경 망을 이용함으로써 상위개념간의 일반적이고 구조화된 관계를 표현하거나 변수의 표현 및 바인딩의 어려움과 같은 문제점이 있었다. CSN모델의 이런 문제점을 해결하기 위해 본 논문에서는 상위개념간의 일반적이고 구조화된 지식표현을 가능하게 하고 추론이 용이한 기호주의 표현 체계와 이 표현 체계 안에서 의미구조를 표현하고 학습할 수 있는 연결주의 학습 모델인 CSN을 결합한 기호-연결주의 통합 시스템 SymCSN(Symbolic CSN)을 제안하고, 실험을 통하여 제안한 시스템이 인간과 유사한 유연한 지식표현과 추론을 위한 모델임을 보인다.

• 산업공학
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• 제16권3호
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• pp.362-374
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• 2003

The major objective of this paper is to empirically examine the effect of process maturity on the performance of industrial R&D projects. Process maturity, a fundamental concept of the Capability Maturity Model developed by Software Engineering Institute, represents the essential of Total Quality Management (TQM). Based on literature, our research model constructs process maturity in terms of structured process, goal setting and controlling, metrics, and process learning; and links it to the R&D performance that consists of technical, commercial and managerial successes. The model also includes firm size as a moderator of different effects that process maturity may have across firms. Measures for process maturity are based on the best practices identified in literature. Data are obtained from 77 successful R&D projects carried out by Korean manufacturing firms. Multiple regression and t-test are used to test proposed hypotheses. Findings are as follows. (1) In the R&D process, process maturity partially contributes to the performance of R&D projects. More specifically, goal setting and controlling-related practices drive both technical and commercial successes, while process learning-related practices drive commercial success. In contrast, traditionally emphasized elements such as structured process or metrics are found not to be significant. (2) The degree of process maturity is significantly higher in large firms. (3) Process maturity impacts on commercial success in the case of large firms, whereas it does on technical success in the case of small firms. The results imply that the TQM principles are partially associated with R&D performance, and the nature of benefit from high maturity could vary according to firm size.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2006년도 춘계종합학술대회
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• pp.81-90
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• 2006

GNUnet은 파일의 익명성 지원을 위해 파일을 1KByte 블록코기로 분리하는 인코딩 방법, 인코딩된 블록을 비구조적 분산기법을 통해 피어들에게 분산시키는 방법, 분산된 블록을 검색하여 원본 데이터로 복구하는 방법을 제안하였다. 하지만 인코딩 및 블록 분산 방안은 약 $600\sim700MB$의 대용량 멀티미디어 파일을 처리할 경우 첫째, 추가적으로 R블럭과 I블럭을 과도하게 요구하게 되어 약 4%의 저장공간을 낭비하는 문제를 지니게 되었다. 둘째, 비구조적 브로드캐스팅 분산방에 의하여 네트워크 부하가 과도한 단점을 내포하였다. 셋째, 이용자의 데이터 검색방법에 있어 파일명을 키워드로 생성하는 방법을 제안했기 때문에 키워드 검색의 한계점이 들어났다. 본 논문에서는 이러한 문제점 해결을 위하여 인코딩 블록의 크기를 가변적으로 결정하는 방법과 구조적 위상을 통해 블록을 분산시키는 방안 그리고 데이터 컨텐츠를 이용한 키워드 생성방안을 제안하였다. 따라서 제안 인코딩 방법은 기존 4%에 해당되는 추가 블록생성을 1% 이내로 최소화하였고, 다면체의 구조적 위상에 인코딩된 블록을 전송하기 때문에 네트워크 부하를 감소시켰다. 그리고, 데이터의 컨텐츠를 키워드로 작성한 컨텐츠 기반 키워드 추출방법을 제안하였다.

• Journal of Acupuncture Research
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• 제38권3호
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• pp.219-226
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• 2021

Background: The objective structured clinical examination (OSCE) is a widely used method to assess the clinical performance of students in clinical practice. Although OSCE has been used for undergraduate students of Korean medicine, this has not been widely reported. Methods: In 2020, the practical course for acupuncture and moxibustion medicine (acupuncture, electroacupuncture, pharmacopuncture, auricular acupuncture, and burning acupuncture) was taught using flipped learning, according to clinical practice guidelines, and assessed by the OSCE. The appropriateness of this model of education and its evaluation using OSCE were evaluated using a 5-point Likert scale, and the results were analyzed. Results: Of the respondents, 67% reported that the OSCE accurately reflected their competency, and 82% reported that online video lectures helped them to improve their clinical skills. The average adequacy score of the model was > 3.7/5, and the average adequacy score of the checklist used in the OSCE was > 4.1/5 for all 5 clinical application skills. The difference in the mean self-efficacy score between students who had taken the OSCE and those students who had not taken the OSCE, was highest in the burning acupuncture group (0.923). Conclusion: This study showed that students' satisfaction with the OSCE was high and flipped learning was an effective education model. In the future, models representing the human body or simulated patients should be used to evaluate students' skills and attitude.

• 유통과학연구
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• 제15권2호
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• pp.79-90
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• 2017

Purpose - Cargo Distribution O2O Business Model is the form of business that connects the cargo and empty cargo-truck based on mobile online platform. In Korean cargo distribution market, FIN(Freight Information Network) is the only model that represents O2O Business Model. The purpose of this paper is investigating the recognition of driver who is the only source of income toward cargo distribution O2O Business Model, and based on the investigated recognition of trucker, suggesting strategic implication. Research design, data, and methodology - PESTLE methodology which is massive environment analysis, and 5 Forces Model when analyze the present and future of cargo distribution O2O business market of industrial structure analysis were used as investigation methodology. Also structured questionnaire was used for trucker's recognition investigation. Based on collected 196 structured effective questionnaires organized with 26 questions were analyzed using statistics package. Results - 51.3% of responded driver is non-differentiated, deprofessionalize form that transport all types of cargo. 95.4% recognize cargo distribution O2O Business Model, FIN is needed, especially during back-hall(94.7%). As a payment method, monthly due is preferred(73%), but it is also needed to pay annual due and pay whenever cargo and cargo-truck are connected(24.5%). Trucker prefer FIN operation corporation which has rich supply(85.2%), and is liberal in supply in any domestic area(75.5%). Conclusions - First, 91% was the member of FIN, and 95% of non-member recognized FIN is needed. 83% of them has the intent to be the member of FIN. Second, besides of monthly due as payment method of FIN, 25% has positive recognition toward new payment method. The new payment method means paying annual due and pay whenever cargo and cargo-truck are connected. Third, because of information imbalance about the cargo and cargo-truck among, operators whose business goal is FIN, it was investigated that transportation fee is low and commission charge of broker is high. The core of Korean Cargo Distribution O2O Business Model, FIN, is online platform that matches cargo and cargo-truck. Therefore, FIN operator should minimize the amount of single transportation of trucker. This study suggests the development of shipper using FIN, diversify distribution channel, suggesting backhaul toward trucker as solution to FIN operator.