• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.1-33
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• 2019

The small and medium sized enterprises (hereinafter SMEs) are already at a competitive disadvantaged when compared to large companies with more abundant resources. Manufacturing SMEs not only need a lot of information needed for new product development for sustainable growth and survival, but also seek networking to overcome the limitations of resources, but they are faced with limitations due to their size limitations. In a new era in which connectivity increases the complexity and uncertainty of the business environment, SMEs are increasingly urged to find information and solve networking problems. In order to solve these problems, the government funded research institutes plays an important role and duty to solve the information asymmetry problem of SMEs. The purpose of this study is to identify the differentiating characteristics of SMEs that utilize the public information support infrastructure provided by SMEs to enhance the innovation capacity of SMEs, and how they contribute to corporate performance. We argue that we need an infrastructure for providing information support to SMEs as part of this effort to strengthen of the role of government funded institutions; in this study, we specifically identify the target of such a policy and furthermore empirically demonstrate the effects of such policy-based efforts. Our goal is to help establish the strategies for building the information supporting infrastructure. To achieve this purpose, we first classified the characteristics of SMEs that have been found to utilize the information supporting infrastructure provided by government funded institutions. This allows us to verify whether selection bias appears in the analyzed group, which helps us clarify the interpretative limits of our study results. Next, we performed mediator and moderator effect analysis for multiple variables to analyze the process through which the use of information supporting infrastructure led to an improvement in external networking capabilities and resulted in enhancing product competitiveness. This analysis helps identify the key factors we should focus on when offering indirect support to SMEs through the information supporting infrastructure, which in turn helps us more efficiently manage research related to SME supporting policies implemented by government funded institutions. The results of this study showed the following. First, SMEs that used the information supporting infrastructure were found to have a significant difference in size in comparison to domestic R&D SMEs, but on the other hand, there was no significant difference in the cluster analysis that considered various variables. Based on these findings, we confirmed that SMEs that use the information supporting infrastructure are superior in size, and had a relatively higher distribution of companies that transact to a greater degree with large companies, when compared to the SMEs composing the general group of SMEs. Also, we found that companies that already receive support from the information infrastructure have a high concentration of companies that need collaboration with government funded institution. Secondly, among the SMEs that use the information supporting infrastructure, we found that increasing external networking capabilities contributed to enhancing product competitiveness, and while this was no the effect of direct assistance, we also found that indirect contributions were made by increasing the open marketing capabilities: in other words, this was the result of an indirect-only mediator effect. Also, the number of times the company received additional support in this process through mentoring related to information utilization was found to have a mediated moderator effect on improving external networking capabilities and in turn strengthening product competitiveness. The results of this study provide several insights that will help establish policies. KISTI's information support infrastructure may lead to the conclusion that marketing is already well underway, but it intentionally supports groups that enable to achieve good performance. As a result, the government should provide clear priorities whether to support the companies in the underdevelopment or to aid better performance. Through our research, we have identified how public information infrastructure contributes to product competitiveness. Here, we can draw some policy implications. First, the public information support infrastructure should have the capability to enhance the ability to interact with or to find the expert that provides required information. Second, if the utilization of public information support (online) infrastructure is effective, it is not necessary to continuously provide informational mentoring, which is a parallel offline support. Rather, offline support such as mentoring should be used as an appropriate device for abnormal symptom monitoring. Third, it is required that SMEs should improve their ability to utilize, because the effect of enhancing networking capacity through public information support infrastructure and enhancing product competitiveness through such infrastructure appears in most types of companies rather than in specific SMEs.

• Water for future
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• v.29 no.4
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• pp.209-221
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• 1996

It may be difficult to make exact estimates of peak discharge or runoff depth of a flood and to establish the proper measurement for the flood protection since water stages or discharges have been rarely measured at small river basins in Korea. Three small catchments in the Su-Young river basin in Pusan were selected for the study areas. Various runoff parameters for the study areas were determined, and runoff analyses were performed using three different runoff models available in literatures; the storage function method, the discrete, linear, input-output model, and the linear reservoir model. The hydrographs calculated by three different methods showed good agreement with the observed flood hydrographs, indicating that the models selected are all capable of sucessfully modeling the flood events for small watersheds. The storage function method gave the best results in spite of its weakness that it could not be applicable to small floods, while the linear reservoir model was found to provide relatively good results with less parameters. The capabilities of simulating flood hydrographs were also evaluated based on the effective rainfall from the storage function parameters, the $\Phi$-index method, and the constant percentage method. For the On-Cheon stream watershed, the storage function parameters provided better estimates of effective rainfall for regenerating flood hydrographs than any others considered in the study. The $\Phi$-index method, however, resulted in better estimates of effective rainfall for the other two study areas.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.39-39
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• 2020

Low-flow 하천에서의 최저수위를 나타내는 지표이다. 일반적으로 유황곡선의 갈수량(Q355)를 대표적으로 사용한다. Low-flow는 물 공급 관리 및 계획, 관개용수, 생태계등 다양한 분야에 영향을 미친다. 이러한 Low-flow를 산정하기 위해서는 충분한 기간의 유량자료가 필요하다. 하지만 국토의 70%가 산지지형으로 구성되어 있는 우리나라의 경우 국가하천과 1급하천을 제외한 산지유역은 수위관측소가 부재하거나 결측으로 인해 자료가 충분하지 않아 Low-flow분석에 한계가 있다. 이에 과거에는 미계측지역의 갈수량을 예측하기 위해서 다중회귀분석, ARIMA 모형 등 다양한 기법을 사용하였지만, 최근들어 머신러닝 모형의 수요가 증가하고 있다. 이에 본 연구에서는 새로운 패러다임에 맞는 머신러닝 기법인 DNN기법을 사용하고자 한다. DNN기법은 ANN기법의 단점인 학습과정에서 최적 매개변수값을 찾기 어렵고, 학습시간이 느린 단점을 보완한 방법이다. 따라서 본연구에서는 머신러닝 기법인 DNN기법을 통해 미계측지역에 적용 가능한 지역화 Low-flow indices를 산정하고자 한다. 먼저, Low-flow에 영향을 미치는 인자들을 수집하고 인자들간의 상관분석, 다중공선성 분석을 통해 통계적으로 유의한 변수를 선정하여, 머신러닝 모형에 입력자료를 구축하였다. 또한 기존의 갈수량 예측기법인 다중회귀분석 결과와 비교하여 머신러닝 기법의 효용성을 검토하였다.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.445-456
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• 2021

In this study, we examine the effects of five needs satisfaction on job satisfaction and turnover intention based on Maslow's hierarchy of needs for clinical nurses. Also, this was a convergence study that confirmed the mediating effect of job satisfaction on the relationship between need satisfaction and turnover intention. The participants were 239 clinical nurses at a general hospital located in Seoul. The collected data were analyzed for mediating effects using hierarchical regression analysis and PROCESS Macro (Model 4). Physiological and safety needs did not have a significant effect on job satisfaction while belongingness, esteem, and self-actualizations need had a significant positive effect on job satisfaction. On the other hand, physiological and esteem needs had a significant negative effect on turnover intention. In addition, the mediating effect of job satisfaction was significant in the relationship between need satisfaction (physiological, safety, belongingness, and self-actualization needs) and turnover intention. We confirm that an increase in the satisfaction of the five needs of clinical nurses can reduce their turnover intention. Therefore, we suggest that it is necessary to effectively manage need satisfaction and job satisfaction in the clinical field.

• Proceedings of the Korean DIstribution Association Conference
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• 2006.02a
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• pp.43-78
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• 2006

While trust and commitment, essential ingredients of the relationship quality variables, are core mediating variables for the purpose of maintaining the long-term relationship, in the context of the internal political economy of company and the relational performance of its members, there have been limited studies which explore as to how each of the dimensions have affect differently. The basic purpose of this study is to examine the relationship between an automobile manufacturer and its agencies. The main purpose of this study is to examine how each different dimension of trust and commitment on the automobile manufacturer have different mediating effects in the context of internal political economy variables and relational performance perceived by its agents. Another purpose is to investigate the mechanism by which the relational performance of the agencies is improved. An empirical study surveying 115 sales office managers at a leading automobile manufacturer in Korea was conducted. An analysis of the collected data indicates that while internal political economy variables have a positive influence on the agencies' relational performance through the mediating role of trust and commitment, agencies' benevolence on its headquarter has a different influence on the dimensions of commitment. Currently, an automobile manufacturer is advised to implement the relational management philosophy in dealing with its agencies with an hope of innovative orientation for customers. In this sense, this study is a big stride in providing ample implications for the automobile manufacturer in establishing trust and commitment, which are the prerequisite conditions in developing and maintaining a successful long-term relationship with its agencies, and in improving the agency's relational performance.

• Proceedings of the KOR-KST Conference
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• 1998.10b
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• pp.261-261
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• 1998

교통계획의 목적은 교통체계를 분석하여 교통과 활동간의 상호작용을 효율화시켜 도시 및 지역사회의 목표를 달성하는데 있으며, 합리적인 교통계획을 수립하여 한정된 투자재원을 효율적으로 배분하기 위해서는 교통수요에 대한 합리적 접근이 필요하다. 교통수요예측의 접근방법은 미시적인 개별적 접근방법과 거시적인 집단적 접근방법으로 구분되며, 다시 모형화 기법이 결정적인가 확률적인가에 따라 개별결정적, 개별활률적, 그리고 집단결정적, 집단확률적 모형의 4가지로 구분될 수 있다. 이 중에서 일반적으로 관심의 대상이 되는 2가지 형태는 집단결정적, 개발확률적 모형이다. 집단결정적모형은 전통적 교통수요예측모형에 해당되며, 개별확률적모형은 1970년대 Mc Fadden을 시작으로 Ben-Akiva, Manheim을 중심으로 한 소비자 행동선택 이론에 근거한 개별행태모형이 이에 해당된다. 개별행태모형은 개개인의 통행행태를 다른 모든 조건이 동일할 때 개개인은 비용의 최소화를 추구하고, 비용과 관련한 통행행태는 거시적 수준에서의 주어진 제약 조건과 관계가 있으며, 의사결정은 확률분포에 의해서 결정되는 효용원칙(Efficiency Principle)에 입각하여 해석한다. 도시내와 도시간, 취업자와 비취업자, 출퇴근 시, 목적별 등의 여러 가지 통행에 있어서 다양한 변수들을 사용하여 교통수단 선택모형의 파라메카 값을 추정하고 통행패턴을 분석해 왔다. 본 논문에서는 개별행태모형인 로짓모형 중에서 집단다항로짓모형을 이용하여 여러 통행 중 공항시설의 접근에 필요한 교통수단 효용함수의 파라메타 값 추정 시, 일반적으로 사용되는 통행시간, 통행비용이라는 변수를 공통으로 두고, 대중교통의 경우에만 해당하는 환승이라는 특정대안변수(Specific alternative variable)를 첨가하여 그것이 수단선택에 미치는 영향을 분석한다. 또한, 대중교통의 속성을 가지고 있는 지하철과 버스를 하나의 대안으로 묶어서 효용함수를 구한 다음 다시 승용차, 택시, 대중교통을 독립된 대안으로 두고 모형을 정립하는 NESTED LOGIT모형으로 파라메타를 추정하여 대중교통의 효용에 관해 분석·비교하였다. 본 논문에 이용된 자료는 공항을 이용하는 이용객들을 대상으로 직접 설문·면접조사한 자료이며 대상 교통수단은 승용차, 택시, 지하철, 버스로 설정하였다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.19 no.2
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• pp.173-181
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• 2001

It is very important to assess spatial data quality of a digital map produced through digital map generalization. In this study, as a aspect of spatial data quality maintenance, we examined the tolerate range of theoretical expectation accuracy and established the quality assessment standard in spatial data for the transformed digital map data do not act contrary to the digital map specifications and the digital map accuracy of the relational scale. And, transforming large scale digital map to small scale, if we reduce complexity through processes as simplification, smoothing, refinement and so on., the spatial position change may be always happened. thus, because it is very difficult to analyse the spatial accuracy of the transformed position, we used the buffering as assessment method of spatial accuracy in digital map generalization procedure. Although the tolerated range of generic positioning error for l/l, 000 and l/5, 000 scale is determined based on related law, because the algorithms adapted to each processing elements have different property each other, if we don't determine the suitable parameter and tolerance, we will not satisfy the result after generalization procedure with tolerated range of positioning error. The results of this study test which is about the parameters of each algorithm based on tolerated range showed that the parameter of the simplification algorithm and the positional accuracy are 0.2617 m, 0.4617 m respectively.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.371-371
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• 2011

본 연구에서는 한강유역 내 관측기간이 충분한 기상청 지상관측소 10개소를 선정하고 CCCma(Canadian Century for Climate modeling and analysis)에서 제공하는 자료에 대한 인공신경망기법 상세화 적용을 실시하였다. 인공신경망의 학습을 위해 CGCM3.1/T63 20C3M시나리오(reference scenario)의 22개 2D변수 중 물리적으로 민감도가 높다고 판단되는 GCM_Prec, huss, ps를 입력변수로 선정하였으며 인공신경망 학습기간은 1991년~1995년, 검증기간은 1996년~2000년, 예측기간은 2011년~2100년으로 A1B, A2 B1 시나리오 등 다양한 기후변화 시나리오를 통해 예측band를 제시하고자 하였다. 하지만 공간상관을 고려하기 위하여 각 관측소에 대하여 인공신경망 학습을 하는 경우 관측소간 spatial correlation 및 spatial cluster구현이 어렵기 때문에 Spatial Rectangular Pulse모형을 이용하고자 하였으나, 강수면적에 대한 scale의 결정이 어렵다는 단점을 확인 하고 본 연구에서는 Random Cascade 모형을 이용하여 ${\beta}$를 통한 강수면적 scale(rainy area fraction)을 결정하고자 하였다. Random Cascade모형의 기법은 격자단위의 downscaling기법으로 강수대의 공간적 형상을 재현하며 스케일에 비종속적인(scale-invariant)프랙탈 특성을 이용하여 매개변수를 최소화 할 수 있는 장점을 가진 기법으로 한강유역 1Km내외 강우장을 만들어 topographic effect를 첨가하고자 한다.

• Proceedings of the Korean DIstribution Association Conference
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• 2006.05a
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• pp.103-115
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• 2006

중국은 세계 무역기구에 가입하면서 세계경제에서 차지하는 위치가 강화되고 디지털 경제체제에 편입되면서 산업구조를 고부가가치 산업으로 개편하고 있다. 동안 상대적으로 외국기업에 대해 폐쇄적이었던 중국의 유통시장은 2006년부터 전면개방이 시작될 것으로 전망되고 있다. 그러나 중국전자상거래 시장에서 정보 기초화와 물류배송 금융체계의 문제는 나날이 안정화되어 온라인 구매환경은 나아지고 있으나, 오히려 해마다 인터넷쇼핑물 구매율의 하락은 온라인 쇼핑몰 상거래에 대한 불신 문제가 그대로 남아있음을 알 수 있다. 따라서 본 연구에서는 중국의 소비자수준에서의 온라인 구매가 활성화되지 못하는 주요 장애요인으로써 불신(distrust)을 제기하고자 하며 신뢰를 신뢰와 불신의 2차원으로 파악하여 각각의 차원(신뢰와 불신)이 마케팅 성과에 차별적으로 공헌하고 있음을 밝히고자 한다. 본 연구에서 선행변수로 상호작용, 지각된 평판, 정보유용성, 지각된 보안위험, 지각된 거래위험을 설정했으며 매개변수로는 신뢰와 불신을, 결과 변수로는 관계몰입과 구매의도로 구성하였다. 결과에서는 온라인 맥락에서는 신뢰와 불신의 선행요인이 온라인 쇼핑몰에 대한 관계몰입과 구매의도에 서로 차별적으로 공헌한다는 것을 밝혔다. 이는 기존의 신뢰를 2차원으로 구분하여 신뢰와 불신으로 분리하여 관리하는 것이 필요하다는 것을 시사한다고 할 수 있다.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.392-395
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• 2017

본 연구에서는 일 증발접시 증발량 산정을 위한 딥러닝 (deep learning) 모형의 적용성을 평가하였다. 본 연구에서 적용된 딥러닝 모형은 deep belief network (DBN) 기반 deep neural network (DNN) (DBN-DNN) 모형이다. 모형 적용성 평가를 위하여 부산 관측소에서 측정된 기상자료를 활용하였으며, 증발량과의 상관성이 높은 기상변수들 (일사량, 일조시간, 평균지상온도, 최대기온)의 조합을 고려하여 입력변수집합 (Set 1, Set 2, Set 3)별 모형을 구축하였다. DBN-DNN 모형의 성능은 통계학적 모형성능 평가지표 (coefficient of efficiency, CE; coefficient of determination, $r^2$; root mean square error, RMSE; mean absolute error, MAE)를 이용하여 평가되었으며, 기존의 두가지 형태의 ANN (artificial neural network), 즉 모형학습 시 SGD (stochastic gradient descent) 및 GD (gradient descent)를 각각 적용한 ANN-SGD 및 ANN-GD 모형과 비교하였다. 효과적인 모형학습을 위하여 각 모형의 초매개변수들은 GA (genetic algorithm)를 이용하여 최적화하였다. 그 결과, Set 1에 대하여 ANN-GD1 모형, Set 2에 대하여 DBN-DNN2 모형, Set 3에 대하여 DBN-DNN3 모형이 가장 우수한 모형 성능을 나타내는 것으로 분석되었다. 비록 비교 모형들 사이의 모형성능이 큰 차이를 보이지는 않았으나, 모든 입력집합에 대하여 DBN-DNN3, DBN-DNN2, ANN-SGD3 순으로 모형 효율성이 우수한 것으로 나타났다.