재가노인 중에서 일상생활을 정상적으로 유지하려 함에 있어 제3자의 도 움을 필요로 하는 장기요양 인정자의 비중도 증가하고 있다. 돌봄을 필요로 하는 노인의 수는 지속적으로 증가할 것으로 예측되는 반면, 돌봄 제공자인 장기요양 인력의 수는 감소하는 경향이 나타나 향후 인력 부족이 예측되고 있다. 이러한 돌봄 수요와 공급 불균형 대응방안의 일환으로 디지털 돌봄 체 계에 대한 중요성이 부각되고 있으며, 노인의 돌봄권 보장과 노인을 돌보는 가족, 돌봄 제공자(요양보호사 등)의 돌봄 부담 완화 및 삶의 질 제고를 위한 그 역할이 더욱 중요해질 것으로 예상된다. 나아가 재가 노인돌봄 영역에 디 지털 기술을 어떠한 방식으로 활용해야 할 것인지에 대한 면밀한 검토가 필 요한 시점이라 할 수 있다. 이에 본 연구는 AI기술을 활용한 선행연구들을 통하여 노인돌봄 서비스의 범주가 어느 정도까지 연구되어 있는지 살펴보고 현장에서 접근할 수 있는 실질적 개선방안을 도출하고자 한다.

This study analyzes the impact of import country environments on Korean fishery exports. To achieve the research objective, focusing on trade facilitation and import market aspects, the import country environment was modeled and analyzed by panel gravity analysis technique. In the basic export model considering only the trade facilitation aspect, agriculture and institutional factors had a significant impact on Korean fishery exports. However, when considering both trade facilitation and import market aspects, it was found that import market aspect had a greater influence on Korean fishery exports than trade facilitation aspect. Specifically, the import market factor that had the most positive impact on Korean fishery exports was the GDP of the import country. GDP, representing the economic scale of the country, indicates consumer purchasing power through per capita GDP. Hence, a higher GDP level implies a higher consumer purchasing power, suggesting a higher potential consumption of fishery products. The second positive factor influencing Korean fishery exports was food imports in the import country. Therefore, to expand Korean fishery exports, it is essential to target countries with high levels of GDP and food imports. Conversely, factors negatively affecting Korean fishery exports were merchandise imports and population in the import country. Therefore, countries with high levels of these negative factors should be managed as demarketing targets. Additionally, trade facilitation variables, which have relatively smaller influence, such as transparency and institutions, also significantly impact Korean fishery exports. While transparency has a positive effect, institution has a negative effect. Thus, to expand Korean fishery exports, strategies should focus on countries with high transparency and less stringent institutional regulations.

PURPOSES : This study analyzes the accident damage scale of hazardous material transportation vehicles not monitored in real time by the Hazardous Material Transportation Safety (HMTS) management center. METHODS : To simulate hazardous-material transportation vehicle accidents, a preliminary analysis of transportation vehicle registration status was conducted. Simulation analyses were conducted for hazardous substance and flammable gas transportation vehicles with a high proportion of small- and medium-sized vehicles. To perform a spill accident damage-scale simulation of hazardous-substance transportation vehicles, the fluid analysis software ANSYS Fluent was used. Additionally, to analyze explosion accidents in combustible gas transportation vehicles, the risk assessment software Phast and Aloha were utilized. RESULT : Simulation analysis of hazardous material transportation vehicles revealed varying damage scales based on vehicle capacity. Simulation analysis of spillage accidents showed that the first arrival time at the side gutter was similar for various vehicle capacities. However, the results of the cumulative pollution analysis based on vehicle capacity exhibited some differences. In addition, the simulation analysis of the explosion overpressure and radiant heat intensity of the combustible gas transportation vehicle showed that the difference in the danger radius owing to the difference in vehicle capacity was insignificant. CONCLUSIONS : The simulation analysis of hazardous-material transportation vehicles indicated that accidents involving small- and medium-sized transportation vehicles could result in substantial damage to humans and ecosystems. For safety management of these small and medium-sized hazardous material transportation vehicles, it is expected that damage can be minimized with the help of rapid accident response through real-time vehicle control operated by the existing HMTS management center.

정책효과를 분석하는데 있어 가장 중요한 이슈 중 하나는 선택편의(selection bias)를 통제하는데 있다. 효율적으로 선택편의를 통제하기 위하여 성향점수 매칭을 통한 이 중차분분석(PSM-DID)기법이 널리 사용되어오고 있으나, 이는 수혜집단과 비수혜집단에 포 함된 표본들이 집단에 따라 동질적인 정책효과를 지닌다는 과감한 가정을 필요로 한다. 본 연구는 수혜집단 내에서 이질적으로 나타나는 정책효과를 추정해보고자 성향점수 분위에 따 라 수혜집단과 비수혜집단을 매칭하여 정책수혜여부에 따른 매출성장효과를 분석하였다. 이 를 위하여 2020년 수행된 소재부품장비 R&D지원사업에 참여한 239개 중소기업을 수혜집단 으로 선정하였으며, 이들 기업의 성향점수를 산출한 뒤 8개 분위로 나누어 비수혜집단과 성 향점수 매칭을 수행하였다. 이후 분위별 이중차분분석을 통해 정책지원으로 인한 매출성장 률을 산출하였다. 그 결과 가장 낮은 분위의 집단에서 가장 큰 정책효과가 관찰되었으며, 3개 년 매출 성장률과 특허출원건수가 높은 기업집단들이 탁월한 정책효과를 누린 것으로 나타 났다. 연구의 결과는 성향점수 분위에 따른 이질적 정책효과 분석기법이 산업정책기획을 위 한 수혜기업의 선정기준, 지원범위 등을 조정하는데 효과적으로 사용될 수 있음을 시사한다.

본 연구는 뷰티 분야에서 디지털 기술 적용 및 혁신수용으로 나타나는 변화에 대한 인식개선 및 해결방안으로 뷰티관련 전공 학습자들의 신기술 수용의도를 분석하여 뷰티산업을 이끌어 갈 예비 뷰티 서비스 전문가들에게 필요한 전문적인 디지털 관련 기술 교과목을 개설하여 교육하고, 신기술을 적용할 수 있는 능력을 배양하여 디지털 기술에 대한 인식도가 높은 뷰티 전문가 배출의 가능성을 알아보고자 하였 다. 뷰티전공 학습자의 디지털 신기술 수용의도를 분석한 결과 신기술에 대한 주관적 규범, 자기효능감은 매 개변수인 용이성에 유의미한 영향을 미치는 것으로 나타났으며, 혁신의지와 자기효능감은 매개변수인 유 용성에 유의미한 영향을 미치는 것으로 나타났다. 그러나 혁신의지는 용이성에 유의미한 영향을 미치지 않는 것으로 나타났다. 또한 용이성과 유용성은 수용태도에 유의미한 영향을 미치는 것으로 나타났으며, 수용태도는 신기술 수용의도에 유의미한 영향을 미치는 것으로 나타났다. 이러한 결과를 종합하여 볼 때 뷰티전공 학습자들의 디지털 기술 관련 기초지식 수준을 분석하고, 디지털 신기술과 관련한 기초지식을 습득할 수 있도록 비교적 낮은 수준의 관련 교과목 개발 및 프로그램을 활용하여 뷰티전공 학숩자들이 디지털 신기술을 쉽게 인식할 수 있는 변화의 계기가 마련될 필요가 있다.

By the recent fast growth of e-commerce markets, it has been stimulated to study order picking systems to improve their efficiency in distribution centers. Many companies and researchers have been developed various types of order picking systems and pursued the corresponding optimal operation policies. However, the performances of the systems with the optimal policies often depend on the structures of the centers and the operation environments. Based on a simulation model that mimics a unique zone picking system operated by a real company in the Republic of Korea, this study compares several operation policies and finds the most appropriate order selection rule and worker assignment policy for the system. Under all scenarios considered in this study, simulation results show that it is recommendable to assign more efficient workers to the zones with heavier workload. It also shows that selecting the order with the maximum number of non-repeatedly visited zones from the order list provides the most consistent and stable performances with respect to flow time, makespan, and utilization of the system even under the scenario with the breakdown zones. On the other hand, selecting the order with the minimum ratio of penalty to the number of zones performs the worst in all scenarios considered.

Vertical takeoff and landing (VTOL) is a core feature of unmanned aerial vehicles (UAVs), which are commonly referred to as drones. In emerging smart logistics, drones are expected to play an increasingly important role as mobile platforms. Therefore, research on last-mile delivery using drones is on the rise. There is a growing trend toward providing drone delivery services, particularly among retailers that handle small and lightweight items. However, there is still a lack of research on a structural definition of the VTOL drone flight model for multi-point delivery service. This paper describes a VTOL drone flight route structure for a multi-drone delivery service using rotary-wing type VTOL drones. First, we briefly explore the factors to be considered when providing drone delivery services. Second, a VTOL drone flight route model is introduced using the idea of the nested graph. Based on the proposed model, we describe various time-related attributes for delivery services using drones and present corresponding calculation methods. Additionally, as an application of the drone route model and the time attributes, we comprehensively describe a simple example of the multi-drone delivery for first-come-first-served (FCFS) services.

This study emphasizes R&D as a management strategy for small and medium-sized manufacturing enterprises (SMEs) to achieve competitive advantage and aims to analyze the impact of innovation resistance, prior knowledge, and technological capability on the intention to adopt R&D. The research targeted 403 decision-makers from SMEs that have not adopted R&D. The analysis revealed the following key findings: As a result, both technical capabilities and prior knowledge had a negative effect on innovation resistance. In addition, technological capabilities and prior knowledge had a positive effect on adoption intention, and innovation resistance had a negative effect on acceptance intention. The indirect effects of technical capabilities and prior knowledge both had a positive impact. In addition, we tested whether dependency on partners and trading organizations that accepted R&D had a moderating effect, but it was not significant. The academic implications of this study provide a detailed analysis of how prior knowledge and technological capability affect innovation resistance in SMEs and verify the intention to adopt R&D. The practical implications suggest a direction for small and medium-sized enterprises to reduce innovation resistance in accepting R&D, and companies need to recognize the suitability of R&D and recognize the importance of technological capabilities and prior knowledge in order to reduce innovation resistance.

As part of the KOPIA Paraguay Center rice pilot villages project, conducted from July 1, 2021, to the end of June 2024, this study examined the average yield and value of paddy rice harvested between January and April 2023 in five local rice pilot villages in Paraguay: Santa Rosa, Eusebio Ayala, Coronel Bogado, Santa Maria, and Yaguaron. The CEA-5K-PUNTA variety was planted in late August 2022 and subsequently harvested from January to April 2023. The farmers in the pilot villages received information on common pests, diseases, and weeds, including instructions on timing and the number of applications required for their control. They also received technical guidance on water management and weeding methods. The study found that the average yield per hectare in the pilot villages for the CEA-5K PUNTA variety in the 2022/2023 growing season was 794.50 kg/10a, compared to 477.17 kg/10a for the conventional variety IRGA 424 in the 2019/2020 season, which preceded the project. This indicates a 66.5% increase in yield per hectare for the pilot village farmers compared to the pre-project period (2020/2021). The analysis of paddy rice production value in the pilot villages, using the Difference in Differences method, revealed a 65.1% increase. Moreover, a financial analysis was conducted based on the addition of agricultural inputs to the paddy fields during the period from the end of August 2022 to January-April 2023. The analysis showed that the total cost was US$597.25 per hectare, while the gross income was US$1,685.3 per hectare. As a result, the net profit per hectare amounted to US$1,088.05.

As the complexity and uncertainty of international construction projects increase, the importance of risk management capabilities in the construction industry has become more pronounced. Accordingly, Enterprise Risk Management (ERM) has become a widely adopted approach among organizations as a new way for more effective risk management. Despite its growing application, research related to ERM is still in its infancy, and most of the existing studies have been limited to financial industries. Therefore, this study aims to empirically examine the influence of ERM’s core elements on project risk management (PRM) and project performance within construction firms. Our findings indicate that the key ERM components—organization, policy, and culture—significantly enhance PRM processes, underscoring their critical role and importance. Additionally, effective PRM positively affects project outcomes, highlighting its significance for construction companies engaged in international projects. While ERM does not directly impact project performance, it indirectly improves outcomes through enhanced PRM capabilities. It suggests that ERM will contribute to the firm’s performance by improving the firm’s PRM capability through policies and a risk-focused culture corresponding to the adopted ERM organization and system..

목적: 본 연구는 4가지 다른 프리즘 종류와 크기에 따른 측정 시 발생하는 오차를 수치화하고, 특히 낱개 프리즘을 사용할 때 발생하는 기울임에 의한 오차를 비교하고자 한다. 방법 : 각 4가지 유형의 프리즘 렌즈 수평 프리즘 바(H), 수직 프리즘 바(V), 낱개 프리즘(I), 프레넬 프리즘(F) 에 대해 4개씩 제품을 준비하여 실험을 진행했다. 1 m 거리에서 총 4번 같은 방향으로 측정했으며, H, V, I는 7가 지 프리즘(Δ), 프레넬 프리즘은 3가지 프리즘 크기를 측정하여 발생하는 오차를 비교하였다. 또한 낱개 프리즘의 경우 방향 오차로 인한 오차를 비교하기 위해 1, 3 및 5도를 측정하였고, 수평 방향으로 8가지 프리즘, 수직 방향 으로 6가지 프리즘 크기에 따른 오차를 비교했다. 결과 : 수평 방향에서 프리즘 렌즈를 측정한 결과, H와 I가 가장 오차가 적었으며 두 렌즈 간 차이는 크지 않았 다. F는 12 Δ에서 유의한 오차가 나타났으며(p<0.010), 20 Δ에서 V의 오차가 높아져 F와의 차이가 없었다. 수직 방향에서는 프리즘 크기가 작을수록 H와 V 사이에 차이가 없었으나, 16 및 20 Δ부터 H와 V에서 유의한 오차가 나타났다(p<0.010). I를 수평 및 수직 방향으로 3가지 각도로 기울였을 때, 2 Δ에서는 수평 및 수직 방향 모두에서 차이가 없었다. 그러나 4~20 Δ까지 프리즘 크기가 커질수록 수평 및 수직 방향 모두에서 기울기가 증가함에 따라 유의한 차이가 나타났다(p<0.010). 결론 : 본 연구의 결과에 따르면, 프레넬 프리즘에서 가장 많은 오차가 발생한 반면, 낱개 프리즘에서 가장 적은 오차가 나타났다. 프리즘 바는 수평 및 수직 방향으로 나누어져 있어 사용 목적에 맞게 정확히 사용해야 한다. 프 리즘 크기가 커질수록 측정 각도를 주의해야 하며, 임상에서는 오차가 적은 낱개 프리즘을 사용하는 것을 권장 한다.

The use of big data needs to be emphasized in policy formulation by public officials in order to improve the transparency of government policies and increase efficiency and reliability of government policies. ‘Hye-Ahn’, a government-wide big data platform was built with this goal, and the subscribers of ‘Hye-Ahn’ has grown significantly from 2,000 at the end of 2016 to 100,000 at August 2018. Additionally, the central and local governments are expanding their big data related budgets. In this study, we derived the costs and benefits of ‘Hye-Ahn’ and used them to conduct an economic feasibility analysis. As a result, even if only some quantitative benefits are considered without qualitative benefits, the net present value, the benefit/ cost, and internal rate of return turned out to be 22,662 million won, 2.3213, and 41.8%, respectively. Since this is larger than the respective comparison criteria of 0 won, 1.0, and 5.0%, it can be seen that ‘Hye-Ahn’ has had economic feasibility. As noticed earlier, the number of analysis using ‘Hye-Ahn’ is increasing, so it is expected that the benefits will increase as time passes. Finally, the socioeconomic value gained when the results of analysis using ‘Hye-Ahn’ are used in policy is expected to be significant.

Fueled by international efforts towards AI standardization, including those by the European Commission, the United States, and international organizations, this study introduces a AI-driven framework for analyzing advancements in drone technology. Utilizing project data retrieved from the NTIS DB via the “drone” keyword, the framework employs a diverse toolkit of supervised learning methods (Keras MLP, XGboost, LightGBM, and CatBoost) enhanced by BERTopic (natural language analysis tool). This multifaceted approach ensures both comprehensive data quality evaluation and in-depth structural analysis of documents. Furthermore, a 6T-based classification method refines non-applicable data for year-on-year AI analysis, demonstrably improving accuracy as measured by accuracy metric. Utilizing AI’s power, including GPT-4, this research unveils year-on-year trends in emerging keywords and employs them to generate detailed summaries, enabling efficient processing of large text datasets and offering an AI analysis system applicable to policy domains. Notably, this study not only advances methodologies aligned with AI Act standards but also lays the groundwork for responsible AI implementation through analysis of government research and development investments.