본 연구는 한국의 개발모형과 국가적 ‘매력’이 의도한 효과성을 달성하 는 데 필요한 조건을 북한의 지역개발 가능성을 중심으로 설명한다. 한 국이 공적개발원조 수혜국에서 공여국으로 전환되면서 영향력이 커지고 있으나, 동시에 점차 확대되고 있는 재정적 지원과 지식원조의 효과성에 관한 우려도 증대되고 있다. 남·북 관계에 관한 담론에서도 개방 후 북한 의 개발과 성장에 대해 개발협력 방식을 통한 한국식 모형 전수를 당연 시하는 논의들이 존재하지만, 잠재적 개발협력 파트너이자 수혜국인 북 한의 관점에서 한국식 모형이 우선순위 및 선호에 부합하고, 매력적일 것인지는 불투명하다. 본 연구는 한국에서 개발도상국으로의 일(一) 방향 의 원조는 국제개발협력 증진과 효과성에 크게 영향을 줄 수 있으며, 오 히려 북한과 같은 개발도상국에서 인식하는 한국의 ‘매력’ 및 선호와 한 국의 정부와 비영리단체가 제공할 수 있는 정책수단과 맞물려야 좋은 성 과를 보일 수 있다는 점을 주장한다. 이를 위해 최근 지속 가능한 개발 목표(SDGs)와 지방의 발전문제에 관심을 보인 북한에 대한 지역개발 논 의를 중심으로 국제개발 효과성 증진을 위한 방향을 제시한다.
This study aims to develop a comprehensive predictive model for Digital Quality Management (DQM) and to analyze the impact of various quality activities on different levels of DQM. By employing the Classification And Regression Tree (CART) methodology, we are able to present predictive scenarios that elucidate how varying quantitative levels of quality activities influence the five major categories of DQM. The findings reveal that the operation level of quality circles and the promotion level of suggestion systems are pivotal in enhancing DQM levels. Furthermore, the study emphasizes that an effective reward system is crucial to maximizing the effectiveness of these quality activities. Through a quantitative approach, this study demonstrates that for ventures and small-medium enterprises, expanding suggestion systems and implementing robust reward mechanisms can significantly improve DQM levels, particularly when the operation of quality circles is challenging. The research provides valuable insights, indicating that even in the absence of fully operational quality circles, other mechanisms can still drive substantial improvements in DQM. These results are particularly relevant in the context of digital transformation, offering practical guidelines for enterprises to establish and refine their quality management strategies. By focusing on suggestion systems and rewards, businesses can effectively navigate the complexities of digital transformation and achieve higher levels of quality management.
PURPOSES : This study aims to provide quantitative profile values for the objective evaluation of concrete surface profile (CSP) grades in concrete structures. The main aims are to quantify the CSP grade required for concrete surface pretreatment and proposing a more suitable CSP grade for structural maintenance. METHODS : Initially, the challenges in measuring concrete surface profiles were outlined by analyzing pretreatment work and profile samples of concrete pavements. Theoretical foundations for quantifying concrete surface roughness were established, and regression models including linear regression, cubic regression, and log regression were selected. Additionally, the interquartile range anomaly removal technique was employed to preprocess the data for regression modeling. RESULTS : Concrete CSP profiles were measured through indoor tests, and the measured data were quantified. Linear regression, cubic regression, and log regression models were applied to each CSP grade for comparative analysis of the results. Furthermore, comparative studies were conducted through adhesion strength tests based on the CSP grade. CONCLUSIONS : Our results are expected to establish objective standards for the pretreatment stage of concrete repair and reinforcement. The derived reference values can inform standards for the restoration and reinforcement of concrete structures, thereby contributing to performance improvement. Moreover, our results may serve as primary data for the repair and reinforcement of various concrete structures such as airports, bridges, highways, and buildings.
본 연구에서는 대학 교수학습센터에서 제공하는 학습지원 프로그램의 성과를 종합적으로 평가하기 위한 BSC(Balanced Score Card) 기반의 성과평가 모형을 개발하고 적용하는 데 있다. 문헌 연구를 통해 성과평 가의 이론적 배경을 조사하고, BSC 모형을 교육 분야에 맞게 수정하여 학습지원 프로그램에 적용 가능한 평가 체계를 설계하였다. 재무, 수요 자, 운영, 프로그램의 네 가지 관점에서 성과평가 지표를 설정하고, 이를 기반으로 대학의 다양한 학습지원 프로그램의 성과를 분석하였다. 분석 결과, 특정 프로그램들이 높은 성과를 보임을 확인하였으며, 동시에 개선 이 필요한 영역을 확인하였다. 개발된 BSC 기반 성과평가 모형은 대학 학습지원 프로그램의 다각도에서의 성과를 평가하는 데 유용하였으며, 프로그램의 강점과 개선점을 명확하게 확인할 수 있었다. 이 연구를 통 하여 대학 교수학습센터가 학습지원 프로그램의 질을 개선하고, 대학 교 육의 질적 향상에 기여하길 기대한다.
This study explores ways to enhance pre-service English teachers’ curriculum development competency through collaboration with in-service teachers. To this end, a course was designed to incorporate three key competencies of curriculum development (curriculum literacy, curriculum development competency, and curriculum evaluation competency) while adopting task-based language teaching and collaboration with inservice teachers as teaching methods. The designed course was implemented in a university for validation and revision. Ten pre-service English teachers participated in the course, where they developed English curricula in response to requests from three in-service middle school English teachers. A questionnaire survey conducted at the end of the semester with both pre-service and in-service teachers revealed that the proposed course model adequately worked to improve the three key competencies of English curriculum development among pre-service teachers. Further, collaboration with inservice teachers was found to enhance pre-service teachers’ responsibility and active engagement in curriculum development, while also providing practical assistance and creative teaching ideas to in-service teachers.
기후변화는 연안지역에 심각한 영향을 미치고 있으며 그 영향이 점점 증가할 것이라고 예상되는 바, 최근 기후변화 적응 및 리스크 평가에 있어 많은 연구들이 취약성과 함께 회복탄력성 개념을 이용하고 있다. 본 연구의 목적은 기후변화 적응을 위한 연안재해 회복탄력성 측정 모형을 개발하는 것이다. 측정 모형 개발에 앞서 연안재해 회복탄력성에 대한 광범위한 문헌검토를 통해 취약성과 회복 탄력성에 대한 조작적 정의와 함께 여러 피드백 메커니즘이 포함된 개념적 프레임워크를 작성하였다. 연안재해 회복탄력성 측정 모형은 네 가지 측정값(MRV, LRV, RTSPV, ND)과 연안재해 회복탄력성 복합 지수(CRI)를 포함하고 있으며, 개발된 지수는 국내 연안침식 사례에 적용되었다. 또한 지수 등급에 따른 지역적 분석이 수행되었다. 연구 결과, 네 가지 회복탄력성 측정값을 통해 각 지점이 가지는 연안침식 회복탄력성의 다양한 특성을 파악할 수 있음을 확인하였다. 연안 회복탄력성 복합 지수의 매핑 결과 서해안 및 남해안 지역에 비해 동해 안 지역들은 연안침식 회복탄력성이 상대적으로 떨어지는 것으로 나타났다. 본 연구의 회복탄력성 측정 모형은 적응 이후의 이행전략에 대한 논의를 제공하는 도구로 활용될 수 있으며, 서로 다른 취약 지역 그룹 간 정책지원에 대한 우선순위를 결정하는 데 이용 가능하다.
Approximately 40,000 elevators are installed every year in Korea, and they are used as a convenient means of transportation in daily life. However, the continuous increase in elevators has a social problem of increased safety accidents behind the functional aspect of convenience. There is an emerging need to induce preemptive and active elevator safety management by elevator management entities by strengthening the management of poorly managed elevators. Therefore, this study examines domestic research cases related to the evaluation items of the elevator safety quality rating system conducted in previous studies, and develops a statistical model that can examine the effect of elevator maintenance quality as a result of the safety management of the elevator management entity. We review two types: odds ratio analysis and logistic regression analysis models.
This study was conducted to develop a model for predicting the growth of kimchi cabbage using image data and environmental data. Kimchi cabbages of the ‘Cheongmyeong Gaual’ variety were planted three times on July 11th, July 19th, and July 27th at a test field located at Pyeongchang-gun, Gangwon-do (37°37′ N 128°32′ E, 510 elevation), and data on growth, images, and environmental conditions were collected until September 12th. To select key factors for the kimchi cabbage growth prediction model, a correlation analysis was conducted using the collected growth data and meteorological data. The correlation coefficient between fresh weight and growth degree days (GDD) and between fresh weight and integrated solar radiation showed a high correlation coefficient of 0.88. Additionally, fresh weight had significant correlations with height and leaf area of kimchi cabbages, with correlation coefficients of 0.78 and 0.79, respectively. Canopy coverage was selected from the image data and GDD was selected from the environmental data based on references from previous researches. A prediction model for kimchi cabbage of biomass, leaf count, and leaf area was developed by combining GDD, canopy coverage and growth data. Single-factor models, including quadratic, sigmoid, and logistic models, were created and the sigmoid prediction model showed the best explanatory power according to the evaluation results. Developing a multi-factor growth prediction model by combining GDD and canopy coverage resulted in improved determination coefficients of 0.9, 0.95, and 0.89 for biomass, leaf count, and leaf area, respectively, compared to single-factor prediction models. To validate the developed model, validation was conducted and the determination coefficient between measured and predicted fresh weight was 0.91, with an RMSE of 134.2 g, indicating high prediction accuracy. In the past, kimchi cabbage growth prediction was often based on meteorological or image data, which resulted in low predictive accuracy due to the inability to reflect on-site conditions or the heading up of kimchi cabbage. Combining these two prediction methods is expected to enhance the accuracy of crop yield predictions by compensating for the weaknesses of each observation method.
PURPOSES : In this study, a model was developed to estimate the concentrations of particulate matter (PM2.5 and PM10) in expressway tunnel sections. METHODS : A statistical model was constructed by collecting data on particulate matter (PM2.5 and PM10), weather, environment, and traffic volume in the tunnel section. The model was developed after accurately analyzing the factors influencing the PM concentration. RESULTS : A machine learning-based PM concentration estimation model was developed. Three models, namely linear regression, convolutional neural network, and random forest models, were compared, and the random forest model was proposed as the best model. CONCLUSIONS : The evaluation revealed that the random forest model displayed the least error in the concentration estimation model for (PM2.5 and PM10) in all tunnel section cases. In addition, a practical application plan for the model developed in this study is proposed.
본 연구는 K연구원의 상향식 R&D과제기획 차원의 신규 연구기획과제 선정 평가를 위한 평가도구 개발에 목적을 두고 진행하였다. 이를 위해 CIPP모형과 연구기획평가를 위한 선정평가 및 평가지표에 관한 선행연구를 중심으로 R&D과제기획 선정평가 항목과 문항을 개발 한 후, 2회에 걸친 델파이 조사를 실시하였다. 개발된 평가도구는 13명의 전문가를 대상으로 설문조사를 실시하여 내용타당도, 합의도 및 수렴도를 검증하였다. 최종 선정된 R&D과제기획 선정평가 도구는 8개 항목에 총 21개 문항으로, 상황평가 5 문항, 투입평가 2문항, 과정평가 8문항, 산출평가 6문항으로 구성되었다. 개발된 평가 도구는 상향식 기획 과정상의 문제점을 해소하고 연구자들의 기획역량을 제고하는 데 기여할 것이다. 또한, 선정 평가 시 평가에 대한 일관성과 효율성 제고에 기여할 것이다.
PURPOSES : This study aims to analyze the impact of demand risk on two public-private partnership (PPP) projects, namely BTO and BTO-a. The main aspects covered in this study are: i) identification of key risk issues considering the structure of PPP projects, and ii) game theory-oriented scenario building and simulation of demand risk allocation from participants’ perspectives.
METHODS : Using the institutional analysis and development (hereafter IAD) framework, a hypothetical structure is formulated to examine the interactions of demand risk. It develops a series of demand risk allocation models for PPP projects (i.e., BTO and BTO-a). The risk structures from the IAD step are the demand risk allocation issues. Using game theory-oriented simulation, this study evaluates demand risk based on scenario building.
RESULTS : First, this study highlights the imbalanced rate problems of returns between the BTO and BTO-a projects proposed by the market. This may lead to improvement measures geared towards problematic methods for determining the rate of return among domestic PPP projects. Second, compared with the BTO type, this study expects that the BTO-a type may exhibit more effectiveness, which can increase the probability of project success in both the public and private sectors. Third, judging from game-theory-oriented approaches, this study confirms the function of the BTO-a as a method to adjust moral hazard in the private sector.
CONCLUSIONS : Government management standards for BTO-a projects were derived based on the simulation results. It is necessary to select an appropriate project method based on rationality by balancing the IRR for each project method. Legal regulations should be applied separately to each part of the government guarantee. In addition, this study emphasizes that the introduction of ex-post value-for-money (VFM) analysis is essential for the efficient management of government expenses.
PURPOSES : The main purpose of this study is to identify directions for improvement of triangular islands installation warrants through analysis of the characteristics of crashes and severity with and without triangular islands on intersections.
METHODS : The data was collected by referring to the literature and analyzed using statistical analysis tools. First, an independence test analyzed whether statistically significant differences existed between crashes depending on the installation of triangular islands. As a result of the analysis, individual prediction models were developed for cases with significant differences. In addition, each crash factor was derived by comparison with each model.
RESULTS : Significant differences appeared in the "crash frequency of serious or fatal" and "crash severity" owing to the installation of triangular islands. As a result of comparing crash factors through the individual models, it was derived that the differences were dependent on the installation of the triangular islands.
CONCLUSIONS : As a result of reviewing previous studies, it is found that improving the installation warrants of triangular islands is reasonable. Through this study, the need to consider the volume and composition ratio of right-turn vehicles when installing a triangular island was also derived; these results also need to be referred to when improving the triangular island installation warrants.
본 연구는 교수자가 학습자를 위해 긍정적 가치탐색을 효과적으로 적용할 수 있도록 4D 프로세스 기반 학습모형을 개발하고 학습유형을 분류하여 연구하는 것을 목적으로 하였다. 긍정적 가치탐색 교육 방법은 학습자의 사고방식과 행동 변화에 효과적이다. 또한, 의미와 가치발견에 중점을 둔 강점 기반 접근을 통해 학습 참여를 증진하고 지속 가능한 학습 환경과 배움을 실현할 수 있다. 이러한 교육적 효과는 긍정적 가 치 탐색의 4D 프로세스를 토대로 한 활동으로 이루어진다. 교육 현장에서 긍정적 가치탐색 4D 프로세스 를 보다 유용하게 활용하기 위해서는 교육목표와 지향하는 역량개발에 따라 4D 프로세스에 적합한 학습 유형 분류와 체계적이고 구조화된 학습모형 개발이 필요하다. 본 연구는 4D 프로세스 기반 4가지 학습유 형을 구조화하여 학습모형을 개발하고 모형타당화를 진행하였다. 4D 프로세스 기반 학습모형 구성요소 도 출은 선행 문헌의 검토와 분석을 통해 이루어졌고, 구성요소의 구조화는 사례연구를 통해 진행하였다. 그 리고 해당 분야 전문가 검토를 통한 타당성 평가를 3차에 걸쳐 실시하였다. Discover, Dream, Design, Destiny 4D 프로세스는 탐색과 발견, 사고와 상상, 공유와 구성, 발표와 실천으로 개선되어 적용되었다. 학습에 적합하도록 보완된 4D 프로세스는 도달할 학습 목표와 개발할 학습자의 역량에 따라 탐구형, 창의 형, 과제해결형, 실천형으로 세분화하여 개발되었다. 개발된 학습모형에서의 학습유형은 다양한 교육 환경 에 맞게 긍정적 가치탐색 활동이 선택적으로 운영될 수 있다는 이점이 있다.