Earticle

5G 이동 통신 서비스가 제공됨에 따라 다양한 서비스를 초저지연으로 사용자에게 제공하려는 노력이 진행되고 있다. 이는 네트워크 코어에서 클라우드 컴퓨팅을 제공하는 대신에 사용자 인근에서 고성능 컴퓨팅 서비스를 제공하는 에지 컴퓨팅에 대한 관심을 불러 일으키고 있다. 본 논문은 에지 컴퓨팅의 실현을 위한 필수 장비인 마이크로 데이터센 터의 운영 및 관리 방안을 제시한다. 먼저, 에지 컴퓨팅의 기능 구조와 배치 방안을 제시한다. 다음으로 에지 컴퓨팅을 위한 마이크로 데이터센터의 요구사항과 이에 따른 운영 및 관리 방안을 제시한다. 마지막으로 마이크로 데이터센터의 자원을 효율적으로 관리하기 위해서 수집 및 감시해야 하는 자원 관리 아이템을 제시하고, 에너지 효율을 측정할 수 있는 성능 지표를 제안한다.

As 5G mobile communication services are provided, efforts are being made to provide various services to users with ultra-low latency. This raises interest in edge computing, which can provide high performance computing services near users instead of cloud computing at the network core. This paper presents an efficient operation and management scheme of a micro data center, which is an essential equipment for realizing edge computing. First, we present the functional structure and deployment plan of edge computing. Next, we present the requirements for the micro data centers for edge computing and the operation and management scheme accordingly. Finally, in order to efficiently manage resources in the micro data centers, we present resource management items to be collected and monitored, and propose a performance indicator to measure the energy efficiency.

The development of digitalized rural communities has injected fresh vitality into the modernization process of China's agricultural sector and countryside regions. This integration not only bridges the gap between contemporary information technology and traditional agriculture but also opens up unprecedented entrepreneurial opportunities for rural youth. By leveraging digital tools and platforms, these young individuals can tap into new markets, enhance productivity, and create sustainable livelihoods. However, the question arises as to whether this ambitious construction of digital villages actually enhances the entrepreneurial intentions of rural youth and what specific mechanisms are at play. To address these critical questions, this paper delves deeply into how digital villages influence rural youth entrepreneurship. This study utilizes survey data from Zhejiang Province, one of the pioneering regions in China's digital transformation, to provide a nuanced understanding of the phenomenon. The research employs a range of sophisticated methodologies, including the entropy weight-TOPSIS method for evaluating digital village development, multiple linear regression models to isolate the impact of various factors, ridge regression to handle potential multicollinearity, mediation effect tests to explore underlying mechanisms, and moderating effect tests to identify contextual influences. Additionally, this study explores the differential impacts stemming from digital heterogeneity across various dimensions of digital villages, as well as comparisons between pilot and non-pilot areas. The findings suggest that: (1) the establishment of digital villages significantly promotes the enhancement of entrepreneurial intentions of rural youth, with significant direct influence effects from level of development of the digital economy, level of digital livelihood construction, level of digital governance implementation, and level of digital infrastructure development. (2) The mechanism tests indicate that digital village construction enhances entrepreneurial intentions of rural youth by improving their digital literacy, and native cultural affection, social capital and entrepreneurial environment positively moderates the influence of building digital villages. (3) The effect of digital village initiatives on entrepreneurial aspirations of rural youth is subject to significant heterogeneity in the effect of genders, educational attainment, level of economic development, and whether it is a pilot region for digital village construction. This conclusion offers empirical evidence to support the promotion of building digital villages., offering practical implications for China and other developing nations.

Realizing common prosperity is the ultimate wish of all Chinese people. In recent years, as rural areas have shifted their focus towards digital development, rural industries have embraced e-commerce, effectively harnessing the power of "e-commerce" to propel common prosperity. In China, Zhejiang Province, as a national model area for common prosperity, has provided valuable experience for the whole country by combining digital reform and common prosperity. The development of rural e-commerce has not only significantly increased the income of residents, but also driven the prosperity of the rural economy. However, to promote common prosperity with digital reform, it is not enough to raise residents' material affluence. While pursuing material affluence, we should also pay attention to spiritual affluence. In order to explore the influencing factors and mechanism of rural e-commerce on residents' common prosperity, this paper is based on the micro-sample survey data of 192 Taobao villages in Zhejiang Province, China, and organically combines quantitative research methods, such as multiple regression analysis, heterogeneity test, robustness test, mediation effect model, regulatory effect model, and qualitative methods, such as interview, questionnaire, and empirical generalization, with cross-validation. The results of the study show that: ①rural e-commerce has a significant positive effect on residents' material affluence, spiritual affluence and ecological affluence; ②material affluence and ecological affluence are the main factors that rural e-commerce promotes the transmission path of spiritual affluence; ③entrepreneurship, social capital and financial literacy play a significant positive regulatory role between rural e-commerce and material affluence; ④ career identity plays a positive regulatory role and unequal opportunities plays a negative regulatory role between rural e-commerce and spiritual affluence respectively. This research offers valuable insights for future rural development decisions, serving as a valuable reference for other regions' rural development efforts. Moreover, it offers inspiration and a practical path for achieving comprehensive well-being in the new era.

Rural innovation and entrepreneurship serve as crucial driving forces in revitalizing Chinese rural areas. In the context of the national rural revitalization strategy, rural e-commerce has created new ways for agricultural products' entry into cities, rural industry's development, and farmers' employment and entrepreneurship, effectively helping farmers achieve common prosperity. However, despite great progress, rural e-commerce is still facing a large market gap compared with the comprehensive needs of rural economic and social development. Furthermore, rural residents' entrepreneurial motivation to engage in e-commerce activities needs to be strengthened. To address the issues above, this study investigates the impact of two elements, i.e., entrepreneurship and financial literacy, on rural residents' entrepreneurial desire to launch e-commerce, while discussing the mechanisms of influence and adjustment. Based on the rooted theory and literature analysis, this study derives three core research hypotheses on which the questionnaire is designed by strictly following the relevant process. Using the multi-stage sampling method, this study conducted a field questionnaire survey in 192 selected e-commerce specialized villages in 10 cities in Zhejiang Province and collected 1,524 pieces of valid sample data, finding that: ① entrepreneurship can significantly boost rural residents' e-commerce entrepreneurial willingness; ② financial literacy plays a positive moderating role between entrepreneurship and rural residents' e-commerce entrepreneurial willingness; and ③ as shown in heterogeneity study, the lower a rural group's educational level, the greater the positive influence of entrepreneurship on their e-commerce entrepreneurial willingness. While providing an empirical enlightenment for improving rural residents' e-commerce entrepreneurial willingness and cultivating agricultural entrepreneurs from a micro perspective on rural residents, this study expects to ease the pressure in rural growth and boost the rural rehabilitation initiative of China.

본 논문은 기업의 재무, 기본정보, 주가 등을 담고 있는 원자료인 OSIRIS를 이용하여 구축된 67개국의 15,813개 기업에 대한 미시데이터를 이용하여, 배당 관련 조세와 기업특성이 기업의 배당금지급 성향에 어떠한 영향을 미치는가에 대해 실증분석하였다. 실증분석 결과, 배당 관련 조세가 배당금 지급을 저해하는 것이 확인되었으며, 오래되고 규모가 크며 수익률 변동성이 낮으며 재단과 연금에 의해 소유된 기업에서 그리고 수입의 안정성이 높거나 현금 수입비중이 높은 산업에서 배당 성향이 높은 것으로 나타났다. 이러한 실증분석 결과는 배당성향에 있어서 조세유인, 대리인 비용, 시그널 효과, 고객효과 등이 작용하고 있음으로 해석될 수 있다.

The purpose of this article is to investigate empirically the effect of taxes and firm characteristics on dividend payout. We used the OSIRIS database which has information on 15,813 firms in 67 countries from 1986 to 2003 to provide evidence that taxes and firm characteristics affect corporate dividend policy. The empirical results suggest that dividends increase with firm size, years in operation, and the tax advantage of dividends. Dividends decrease with variability of profit. In our analysis, one standard error increase in the tax advantage is estimated to increase dividend payout ratio by 6.5%p in OLS, and by 14.5%p in Tobit. And in the case of firm size, if there is one standard error change, the ratio increases by 5.1%p in OLS, and 15.9%p in Tobit. Also a one year increase in operation increases the payout ratio by 0.15%p in OLS, and 0.28%p in Tobit. When the profit fluctuation increases by one standard error, the corporation tends to decrease the dividend payout ratio by -0.7~-2.0%p. In addition, we find that the dividend payout varies systematically across industries. Firms in the utility industry pay 17.5%p more dividends than those in technology industries. Firms in the financial industry pay 12.7%p more than technology industry. Ultimate ownership is also found to affect the dividend payout. The ultimate ownership by foundations is associated with 17.5%p larger dividends than firms with not concentrated or unknown. Next are Mutual & Pension funds, trust or nominees whose corporation pay 7%p more dividends than the reference group.Our empirical results suggest that tax incentive, agency cost (positive effect of firm size and industry with stable cash income on dividends), signaling effect (negative effect of variability of profit on dividends), and clientele effect (positive effect of foundations and fund), affect the dividend payout ratios.

현재의 ICT 인프라(인터넷과 서버/Client 연동)는 다양한 장치, 서비스, 비즈니스 및 기술 진화에 따른 신속한 대응 에 어려움을 겪고 있다. 클라우드 컴퓨팅(Cloud Computing)은 구름 같은 네트워크 환경에서 원하는 작업을 요청하여 실행한다는 데서 기원하였으며, 인터넷 기술을 활용하여 IT 자원을 서비스로 제공하는 컴퓨팅을 뜻하고 오늘날 IT 트 렌드의 하나로 가장 주목 받고 있다. 이러한 분산클라우드 환경에서는 네트워크 및 컴퓨팅 자원에 대한 통합 관리 체계 를 통하여 관리 비용 증가 문제를 원천적으로 해결하고 분산된 마이크로 데이터센터(Micro DC(Data Center))를 통하여 코어 네트워크 트래픽 폭증 문제를 해결하여 비용 절감 효과를 높일 수 있다. 그러나 기존의 Flooding 방식은 인접한 모든 DC들에게 전송하기 때문에 많은 트래픽을 유발 할 수 있다. 이를 위해 Restricted Path Flooding 알고리즘이 제안 되었으나 대규모 네트워크에서는 여전히 트래픽을 발생할 수 있는 단점이 있어서 본 논문에서는 홉수 제한을 통하여 이를 개선한 Lightweight Path Flooding 알고리즘을 제안하였다.

Current ICT(Information & Communication Technology) infrastructures (Internet and server/client communicatio n) are struggling for a wide variety of devices, services, and business and technology evolution. Cloud computing or iginated simply to request and execute the desired operation from the network of clouds. It means that an IT resour ce that provides a service using the Internet technology. It is getting the most attention in today's IT trends. In the distributed cloud environments, management costs for the network and computing resources are solved fundamentall y through the integrated management system. It can increase the cost savings to solve the traffic explosion problem of core network via a distributed Micro DC. However, traditional flooding methods may cause a lot of traffic due to transfer to all the neighbor DCs. Restricted Path Flooding algorithms have been proposed for this purpose. In large networks, there is still the disadvantage that may occur traffic. In this paper, we developed Lightweight Path Floodi ng algorithm to improve existing flooding algorithm using hop count restriction..

최근 마이크로 모빌리티는 비대면 사회에서 라스트 마일을 이용하는데 유용한 교통수단으로 정의되고 있지만, 현재 주차방식을 비고정형으로 채택하고 있어 교통수단이 가지는 장점보다는 단점이 더 부각되고 있다. 본 연구는 마이크로 모빌리티의 주차방식을 비고정형에서 고정형으로 전환하면서 필요한 주차장 입지를 공학적 분석을 통해 마이크로 모빌리티의 주차문제 해결에 목적이 있다. 마이크로 모빌리티 주차장의 최적 개수 및 위치를 도출하기 위해서 입지선정모형인 MCLP 모형을 사용하였다. MCLP 모형 적용의 대상지는 분당 1기 신도시로 현실적인 공유 전동킥보드의 수요에 대응하는 최적입지 도출을 위해 실제 이용 데이터를 수집하여 반영하였으며, 최적입지에 시간대별 이용 수요를 반영하기 위해 커버 범위, 수요, 시간대별로 모형을 적용 및 분류하였다. 분석 결과, 커버 범위를 400 m로 적용하였을 때 최적 주차시설의 개수는 146개로 현재 마이크로 모빌리티의 수요가 99.83 % 커버되어 주차문제 해결에 적절한 커버 범위로 나타났다. 또한, 공유 전동킥보드의 이용 수요를 4개의 수준, 시간대를 3개의 수준으로 분류하고 교차하여 도출된 마이크로 모빌리티의 주차장을 총 12개의 유형으로 분류하였다. 이러한 주차장 유형의 분류는 향후 마이크로 모빌리티 주차시설의 설치 및 운영에 있어 전략적인 정책 제안이 가능할 것이다.

Most of the Micro-mobility parking in Korea use Dockless system. However, Dockless can result in cluttering, infrastructure deficiencies, and safety challenges as has been observed in cities. It is necessary to introduce a Station Parking system in order to solve the drawbacks of the dockless, but the introduction without engineering has low accessibility and induces side effects. In this study, to decide optimal location about number of the Micro-mobility Station, we has been applied the MCLP model about the coverage range, usage demand, usage time in order to classify the type of Micro-mobility Station. For the MCLP, User Date input to reflect realistic demand in Bundang new town, Korea. The result show that the optimal number of facilities in 400 m was 146, and the coverage ratio was 99.83 %, which was most suitable coverage for solving the parking problem. We also classified the demand into 4 levels and the usage time into 3 levels, and by crossing them, we were able to classify the Parking lot types into 12 types. It is possible to propose strategic policies in the installation and operation of Micro-mobility Parking System.

Low female labor force participation has been an important issue in Asian countries like Korea and Japan. China’s female labor force participation rate has been relatively high, but is beginning to decline. The previous literature on determinants of female labor participation reached a consensus that age, education, marital status, and children are the main factors. However, the previous research does not address the role of parents, or only the effect of cohabitation with parents due to the lack of data. This is problematic since the presence of parents in vicinity may also have a similar effect to cohabitation with parents. This paper analyzes the effect of parents on the labor market participation of married women in China by taking into account the residence type of parents. A 5-year panel dataset of China Health and Nutrition Survey (CHNS), covering the period between 2000 and 2011, was utilized for the analysis. The analysis is carried out in three steps. First, all different types of residence are regressed as dummy variables to determine the threshold of “vicinity to parents.” Then, using the new indicator variable and instrument variables, a 2SLS method is applied to address endogeneity issues. Finally, sub-sample regressions are implemented to investigate the mechanism of parents’ impact. There are four main findings in this paper. First, the participation rate of women increases when they live with their parents and reside with or next to their parents-in-law. Second, living in close proximity to parents’ generation has a positive effect on women’s labor participation before and after controlling for the confounding factors. Third, this paper analyzes the property of the endogeneity between living close to parents and female labor participation, proving the existence of negative correlation between them. Last but not least, it is found that parents' influence is greater in the sub-sample of women with children less than 3-years old than in other groups, confirming that living near to parents improves female labor supply because parents help raise children.

자율주행 관련 기술의 고도화와 함께 자율차와 비자율차가 혼재된 교통 환경이 예측됨에 따라서 미시구간의 차량 속도정보 예측은 안전한 교통 환경 구축에 가장 중요한 정보 중 하나 로 판단되고 있다. 하지만, 현재 제공되는 링크 기준 미시구간 주행 속도는 속도 변화 구간을 정확하게 반영하지 못하는 한계가 있다. 본 연구에서는 미시구간 속도정보 서비스를 위한 개 별 차량 빅데이터 기반의 공간 분할 방안을 제시한다. 본 연구에서는 차량 빅데이터를 이용한 동질속도구간 도출과 지오해시 기반의 단계적 구간 분할을 통하여 미시적 속도 정보 변화 지 점을 분류하였다. 경부고속도로 경기지역에 대하여 제안된 방법을 적용한 결과 해당 구간 도 로는 130 및 170개의 동질속도구간으로 세분되었다. 본 연구에서는 결과 분석을 통하여 제안 된 방법은 기존 링크 기반 정보에 비하여 정밀하고 정확한 속도 정보 제공이 가능함을 제시하 였으며, 개별 차량 빅데이터를 이용한 미시적 속도 정보 제공을 위한 구간 세분화가 필요함을 검증하였다.

Vehicle average speed information which measured at a point or a short section has a problem in that it cannot accurately provide the speed changes on an actual highway. In this study, segment separation method based on vehicle big data for accurate micro-speed estimation is proposed. In this study, to find the point where the speed deviation occurs using location-based individual vehicle big data, time and space mean speed functions were used. Next, points being changed micro-scale speed are classified through gradual segment separation based on geohash. By the comparative evaluation for the results, this study presents that the link-based speed is could not represent accurate speed for micro-scale segments.

본 연구에서는 미시적 접근법을 통해 최근 국내 가계부채 증가추세와 부채증가 결정요인에 대해 분석하였다. 분석 결과, 국내 가계는 외환위기를 겪은 1999년 이래 카드사태가 발생한 2003년 직전인 2002년까지 부채규모가 지나치게 높았던 것으로 나타났다. 특히 이 기간 동안 부채가구가 지닌 부채의 비중이 소득뿐 아니라 상대적으로 현금화내지 유동화가 수월한 금융자산에 대비해서도 지나치게 높았다. 이는 그만큼 우리나라 가계들이 자신들이 감당할 수 있는 수준이상의 부채를 지속적으로 늘려왔다는 심각성을 보여주고 있다. 다행히 카드 사태를 겪었던 2003년 이래로 2007년 글로벌 금융위기를 겪기 전 2006년까지 부채의 규모가 수용 가능한 안정적인 수준을 보였다. 그러나 2007년 다시 국내 가계의 금융자산대비 부채규모뿐 아니라, 국내 가계가 가구소득대비 감당할 수 있는 채무부담 역시 다시 높아지고 있음을 확인할 수 있어, 이에 대해서는 우려되는 부분이다. 다음으로 한국노동패널조사 2차～11차 연도의 패널자료를 이용하여 국내가계의 부채유무 및 부채규모의 결정요인을 분석한 결과, 가구주가 남성이고 연령이 높을수록, 가구원수가 많고 자가 주택보유 가구일수록, 그리고 가구 소득과 부동산 자산이 많을수록 부채를 보유할 가능성이 높은 것으로 나타났다.

This study analyzes increasing recent domestic debt and determinant of debt increase through microscopic panel data collected by KLIPS through 2nd to 11th surveys. Upon the findings, the scale of domestic economy is excessively big since Asian financial crisis in 1999, up to 2002 right before the card crisis occurred in 2003. Particularly, the debt is extraordinary high compared not only to income but also monetary assets with relatively high encashment, fluidization during the period. It is a telltale sign of how seriously domestic households have spent more money than they actually could deal with. Fortunately, since the outbreak of the card crisis, the debt amount shows the stable level which can be acceptable until 2007, a year before global financial crisis in 2007. However, debt scale compared to monetary assets and the burden of debt that household can deal with are observed in increasing trend again since 2007, which is very concerned. According to the study of determinants of debt scale and whether to have debt or not through KLIPS through 2nd to 11th surveys, the high debt tendency appears if the householder is male, old and if the family has more members, household income and real estate assets, and has ones own house.

자율주행 차량의 도입 및 확산에 따라 일반차량과 자율주행 차량이 혼재하는 과도기적 교통환경에 있으며, 이질적인 주행 특성 간 상호작용은 상충(conflict) 상황을 야기할 가능성이 높다. 특히 차로변경이 빈번한 교차로 및 합류부 등에서 상충 상황이 집중적으로 발생하고 있다. 차량간 차로변경은 대표적인 상충 유발 행태로, 일반차량과 자율주행 차량 간 대응성의 한계로 교차로 또는 엇갈림(weaving) 구간에서 충돌 위험이 급격하게 증가한다. 이에 교통류의 엇갈림은 자율주행 혼재 환경에서 반드시 고려해야 할 핵심적인 고위험 상황으로 인식하고 체계적으로 계량화할 필요가 있다. 본 연구는 개별차량의 궤적 데이터를 활용하여 연속된 교차로 간의 진출입 특성을 반영한 교통류 간 엇갈림 비율을 산정하고, 이를 토대로 상충 위험이 높은 구간을 식별하였다. 교통류 엇갈림 지표와 교통사고율 간의 상관관계 분석 결과 두 지표간 양의 상관관계가 존재하는 것으로 분석되었다. 본 지표는 연속류 도로 뿐만 아니라 도로망 전체의 사고위험에 대한 일관성 있는 평가 및 우선순위 산정 등 모니터링에 활용 가능할 것으로 기대된다.

The introduction and proliferation of Autonomous Vehicles (AVs) have created a transitional mixed traffic environment, where the interaction between vehicles with heterogeneous driving characteristics is highly likely to generate conflict situations. Specifically, conflicts are concentrated in sections with frequent lane changes, such as intersections and merging segments. Lane changing is a representative conflict-inducing behavior, and the collision risk sharply increases in intersections and weaving zones due to limitations in the responsiveness between Conventional Vehicles(CVs) and AVs to abrupt maneuvers. Consequently, traffic weaving is recognized as a critical high-risk scenario in mixed traffic environments and requires systematic quantification. This study utilizes individual vehicle trajectory data to calculate a Traffic Weaving Index (TWI) that reflects entry and exit characteristics between consecutive intersections. Based on this index, segments with a high risk of conflict were identified. The correlation analysis between the proposed TWI and the crash rate confirmed a significant positive correlation. The developed index is expected to be useful for traffic safety monitoring, particularly for the consistent evaluation and prioritization of crash risks across the entire road network, extending beyond uninterrupted flow highways.

The purpose of this study is to develop an empirical foundation for designing a micro-degree-based beauty convergence curriculum by analyzing industry trend keywords using big data. To achieve this, beauty-related text data collected from major online platforms between 2021 and 2025 were analyzed using a four-stage analytical framework, including TF-IDF-based text mining, semantic network and centrality analysis, CONCOR clustering, and QAP correlation analysis. The results revealed that “K-Beauty,” “Global Beauty Market,” and “Beauty Consumer Trends” serve as core hubs in the industry network, while emerging keywords such as “Skin Microbiome,” “AI Skin Diagnosis,” “Beauty-Tech Convergence,” and “Sustainable Packaging” highlight rapid growth in the technology-driven and ESG-oriented sectors. The CONCOR analysis classified the keywords into five structural groups: industry structure, technology convergence, ESG and sustainability, marketing and distribution, and education and workforce, suggesting a modular curriculum framework with foundational, core, and advanced levels. Additionally, QAP analysis confirmed high structural stability (average correlation = .957) across years, alongside gradual evolution driven by technological and sustainability trends. These findings provide data-driven evidence for designing flexible and industry-aligned micro-degree programs and contribute to advancing curriculum development in beauty convergence education.

本研究旨在利用大数据分析产业趋势关键词为构建基于微学位的美容融合课程体系 提供实证基础资料为此以2021‑2025年主流网络平台采集的美容类文本数据为研究对象 采用由TF‑IDF文本挖掘语义网络与中心性分析CONCOR聚类分析QAP相关分析构成的 四阶段分析框架开展研究分析结果显示,“K‑美容”“全球美容市场”“美容消费趋势”是产业网络当中的核心枢纽节点此 外“皮肤微生物组”“AI皮肤诊断”“美容技术融合”“可持续包装”等新兴关键词反映出技术驱 动领域与ESG导向领域正在快速发展CONCOR聚类分析将关键词划分为五大结构集群产 业结构技术融合ESG与可持续发展营销与流通教育与人才该结果为搭建包含基础‑ 核心‑深化层级的模块化课程体系提供参考同时QAP分析得出各年度网络间平均相关系数 高达0.957证实产业网络具备结构稳定性并且行业正围绕技术可持续发展两大主题逐步 发生演变本研究结果为设计兼顾灵活性贴合产业需求的微学位课程提供数据依据有助 于推动美容融合教育领域课程开发的精细化发展.

본 연구는 소상공인을 대상으로 금융지원을 제공하고 있는 전국 16개 지역신용보증재단의 소상공인 신용정보와 신용평가등급 등의 자료를 활용하여 정보특성별 차이가 소상공인의 신용위험과 어떠한 관련성(예측력)을 가지는지를 검증하였다. 먼저 개인CB등급(외부등급정보)와 지역신보 내부정보인 가점미적용등급, 가점적용등급 등의 세 그룹으로 구분하여 각 정보를 기초로 평가한 신용등급의 차이가 이들의 신용보증의 실제 대위변제 발생과 유의한 관련성이 존재하는지를 살펴본 결과, 현재 지역신보가 획득/보유하고 있는 현 수준의 비재무적 정보는 외부등급 이상으로 소상공인 신용위험관리에 큰 도움이 되지 못하고 있는 것으로 나타났다. 즉, 세 가지 정보특성 분류 중 외부등급정보인 개인CB등급을 활용한 신용위험관리가 가장 예측력이 높았고, 내부정보 중 소상공인 비재무적 정보라 할 수 있는 가점을 포함한 가점적용 모형등급이 가점미적용 모형등급보다 상대적으로 더 낮은 부도예측력을 가지고 있는 것으로 나타났기 때문이다. 이는 향후 금융기관들이 관계형 금융의 필요성과 편익/비용에 관한 논의 뿐 아니라 관계형 금융의 효율성 확보를 위해 어떠한 특성의 비재무적 정보가 획득되어야하는지에 관한 고민도 중요함을 시사하는 것으로, 결국 소상공인을 포함한 중소기업 신용평가방식의 진화 방향이 새롭게 그리고 구체적으로 모색되어야 할 시점임을 의미하고 있다.

Recently, in Korea, Kakao Corp. and KT Corp. have won preliminary licenses to run Internet-only banks. The two consortiums are expected to focus primarily on providing medium-cost loans to people with low credit standings. To serve these people, the two banks should be able to analyze their creditworthiness. Therefore, It is expected that the necessity of collecting and using non-financial data as well as traditional credit data for credit scoring would be increased. In fact, until now, underwriting credit risk of consumer has relied heavily on financial data inputs. But for micro-enterprises we focus on in this study, the traditional financial data inputs are generally unavailable in the financial market, so it has served as an obstacle to evaluate consumer credit risk. Under this circumstance, this paper examined, using micro-enterprises data of credit-guarantee foundations, the efficiency of adding non-financial data to a traditional credit scoring model (CB) on micro-enterprise consumers, and could not find the improvement in scoring model performance with inclusion of non-financial data in CB credit-rating information.

교육부에서 2022 개정 교육과정에 본격적으로 AI교육을 도입하면서 AI교육과 더불어 데이터 관련 교육의 필 요성에 대한 공감도가 높아지고 있다. 인공지능을 제대로 이해하고 활용하는 역량을 기르기 위해서는 데이터에 대한 이해와 활용 역량이 기반되어야 한다. 본 연구에서는 요구분석, 선행연구분석 결과를 종합하여 마이크로비 트를 활용한 데이터 기반 문제해결 SW교육 프로그램을 개발하였다. 데이터 기반 문제해결 교육 프로그램은 데 이터 과학의 내용 중 초등학생을 대상으로 적용할 수 있는 교육 요소들로 구성하여 개발되었다. 본 연구에서 개 발한 프로그램을 통해 실생활 데이터를 바탕으로 다양한 주제와 교과를 융합한 교육을 연계할 수 있다. 더 나아 가 데이터에 대한 이해를 바탕으로 보다 내실 있는 AI교육 프로그램의 기반을 갖추게 될 것이다.

As the Ministry of Education has introduced AI education in earnest in the 2022 revised curriculum, there is growing sympathy for the need for data-related education along with AI education. In order to develop the competence to understand and utilize artificial intelligence properly, the understanding and utilization competence of data must be based on it. In this study, a data-driven problem solving SW education program using microbit was developed by synthesizing the results of demand analysis and previous research analysis. The data-driven problem solving education program was developed with educational elements that can be applied to elementary school students among the contents of data science. Through the program developed in this study, education that combines various topics and subjects can be linked based on real-life data. Furthermore, based on an understanding of data, it will lay the foundation for a more substantial AI education program.

사회 각종 분야에서 데이터 과학이 활용되는 비율이 높아지고 있음에도 불구하고 데이터 과학 교육 프로그램 에 대한 연구는 비교적 미비한 실정이다. 본 연구에서는 초등학생을 대상으로하는 데이터 과학 교육 프로그램을 개발하여 그 효과를 검증하였다. 피지컬 컴퓨팅 도구 중에 하나인 마이크로비트를 활용하여 데이터를 수집하는 프로그램을 제작해 보고, 수집된 데이터를 분석하여 결과를 도출하는 데이터 과학의 단계를 수행하는 교육 프로 그램을 개발하였다. 00대학교 정보영재과정을 수강하고 있는 초등학생 6학년 10명을 대상으로 연구를 진행하였 으며, 효과를 검증하기 위하여 컴퓨팅 사고력 사전·사후 검사를 실시하였다. 그 결과 본 연구를 통해 개발된 데 이터 과학 교육 프로그램이 초등학생의 컴퓨팅 사고력을 향상시키는 데 유의미한 효과가 있음을 알 수 있었다.

Despite the increasing rate of use of data science in various fields of society, research on data science education programs is relatively inadequate. In this study, a data science education program for elementary school students was developed and its effectiveness was verified. We created a program that collects data using microbit, one of the physical computing tools, and developed an education program that performs the data science stage of analyzing the collected data to derive results. A study was conducted on 10 students enrolled in the Information Gifted Program at 00 University, and pre- and post-tests of computing thinking skills were conducted to verify the effectiveness. As a result, it was found that the data science education program developed through this study has a significant effect on improving the computational thinking of elementary school students.

Privacy is the word which can listen everywhere in the data mining for data preserving. It should be provided the security to the data in many ways. Privacy should be provided to the sensitive data and micro data. Hence more number of existing techniques has been introduced to provide sensitive data. Many third party service providers are showing interest to release the data which is collected for research purpose. Existing systems like k-anonymity, l-diversity and t-closeness are already existed but they can’t provide better privacy measures. Each existing method carries different types of problems. The t-closeness is the more flexible privacy model called (n,t)-closeness will provide the better privacy and usage. Proposed Closeness measures require Probability distribution that is assessed using Earth Mover’s Distance (EMD) measurement. In this paper, the graph based algorithm graph-EMD. Compare with tree-EMD, graph EMD performs more flexible. The number of unknown variables is reduced to O (N) from O (N2) of the original EMD. In this paper, with Graph-EMD is implemented and show the performance and efficiency.

본 연구에서는 마이크로 데이터 센터의 환경 모니터링 시스템(EMS)을 설계하고 개발하는 방법을 나타낸다. 설계하는 환경 모니터링 시스템은 IoT 센서 및 싱글보드 컴퓨터를 이용하여 데이터센터 운영환경을 실시간으로 감지 하여 데이터를 해석하고 운영환경을 모니터한다. 먼저, EMS 하드웨어 플랫폼 및 IoT 센싱 패키지 설계 방법에 대하 여 나타낸다. 또한 서로 다른 프로토콜을 갖는 IoT 센서에 대한 데이터 수집 SW을 설계하고 원격에서 모니터링이 가능한 EMS 모니터링 SW를 개발한다. 데이터 수집 SW는 센서 수집 모듈과 수집 메니저 모듈로 구성된다. EMS 소프트웨어는 마이크로 서비스 아키텍츠(MSA) 개념을 적용하여 설계하며 각각의 서비스는 독립적인 비즈니스 로직 을 포함한다.

In this paper, we present design and developing method for EMS(environment monitoring system) of micro data center. This developing EMS monitors operating environment of micro data center and analyze sensing data through IoT(Internet of things) sensors in real time. Firstly we present configuration method of IoT sensing package and design method EMS hardware platform. Secondly we design data collector software for data collection of IoT sensor with different protocol and develop monitoring software of EMS. The data collector software consists of sensor collector module and collector manager module. Also we design EMS software which has micro service architecture structural style and component based business logic.

The purpose of this paper is to analyze the relationship between localization and performance of Korean corporations in Latin America. The empirical findings show that localization has a positive coefficient but statistical insignificance. Among the factors affecting corporate sales, only two variables such as introduction of new products and setting price have positive effects on corporate performances. And among variables affecting corporate net profits, only a variable of introduction of new products has a positive impact on corporate performances. JEL Classification: FO, F2, M1.

본 연구는 국가 경제적으로 매우 중요한 의미를 지니는 기술혁신적인 제품인 디지털 TV의 보급에 영향을 미치는 요인들에 대해 정보통신수용도를 중심으로 실증적으로 분석하였다. 이를 위해 1,000개의 가구 설문조사를 토대로 구축된 미시 데이터(micro data)를 이용하여 가구의 DTV 구매선택에 어떤 요인들이 영향을 미쳤는지를 실증적으로 분석하였으며, 이로부터 디지털 TV보급관련 정책에 함의를 찾고자 하였다. 분석 결과, 다른 설명변수의 조건이 일정할 때 가구 세대주의 학력이 높은 가구가, 소득이 높은 가구가, 통신 및 방송, 인터넷 등 정보통신 여러 부문에 대한 수용도가 높은 가구가 각각 DTV의 구매의향이 높은 것으로 나타났다. 아울러 2010년에 아날로그 방송이 중단되며 디지털방송으로 전환이 이루어진다는 정책방향을 아는 가구가 이를 알지 못하는 가구에 비해 훨씬 구매의향이 높은 것으로 나타나, 정부의 디지털전환 정책 홍보가 디지털 TV의 보급에 매우 큰 영향을 미친다는 점을 시사하고 있다. 또한 TV를 구입한지 오래될수록 디지털 TV를 구매할 확률이 높은 것으로 나타나 TV의 대체수요에 대한 인센티브를 줄 경우 더 많은 가구들이 구매할 것임을 보여 주었다. 끝으로, 디지털위성방송 시청가구가 그렇지 않은 가구에 비해 디지털 TV구매 확률이 월등히 높은 것으로 나타나 DTV 확산을 위하여는 위성방송에 대한 정책과의 연계가 효과적이라는 점을 시사하고 있다.

This paper empirically analyzes determinants of DTV (Digital Television) adoption in household survey data with IT-related household demand characteristics. To this purpose, we conducted a survey for the adoption of DTV to 1,000 households nationwide. In the questionnaire, various questions asking socio-economics characteristics such as age, education, income were included. Also, status of adoption and usage of IT services such as paid broadcasting, internet, and DVD were asked. To analyze the determinants of intention of purchasing, decision of purchasing, and the timing of purchasing DTV, we adopted the ordered logit, binary logit and multinomial legit models. When there is an order among groups, ordered logit was employed and when there is no orders among groups, multinomial logit was emplyed for the estimation. It is found that when conditions of other explanatory variable are constant, the more educated household heads are, the more probable they become early adopters of DTV. It is also found that other conditions being constant, the income level of households and IT-related household demand characteristics are very important factors affecting DTV adoption. Since the likelihood of purchasing DTV is much higher for those who know the government policy of analog broadcasting termination schedule than others who do not know, dissemination of the Korean government's digital broadcasting policy will affect significantly the adoption of DTV. And policy with various incentives ought to be employed to accelerate DTV adoption, because households with the older TV sets are more likely to purchase DTV. It is suggested that the Korean government should develop policy to connect both DBS (Direct Broadcast Satellite) and DTV since DBS subscribers are more likely to be an early adopter than non-subscribers.