This study investigates the impact of perpetual swaps on structural complexity and market efficiency within cryptocurrency markets. Utilizing 15-minute interval price data from 35 cryptocurrencies, we employ multifractal detrended fluctuation analysis (MF-DFA), Multifractal-based measure of the degree of market efficiency (MED), and Market deficiency measure (MDM) to comparatively evaluate market characteristics before and after the introduction of perpetual swaps. Our empirical analysis reveals a substantial decrease in multifractality and structural complexity across most cryptocurrencies post-introduction, particularly pronounced over longer horizons (4–6 months). This reduction indicates enhanced information dissemination and more efficient price formation mechanisms. Notably, Bitcoin (BTC), benefiting from superior liquidity and efficient information flow, exhibited relatively stable multifractal characteristics, although significant volatility driven by fat-tail distributions remained persistent. Statistically significant improvements in market efficiency were consistently demonstrated via paired t-tests, one-sided t-tests, and Wilcoxon non-parametric tests. These improvements were particularly salient during extended observation periods, providing robust empirical evidence that perpetual swaps markedly enhance market efficiency. Consequently, our findings highlight that the introduction of perpetual swaps contributes meaningfully to cryptocurrency market efficiency beyond mere liquidity enhancement, promoting more accurate price discovery and reducing informational asymmetries.

This study aimed to enhance the operational efficiency and safety of offshore eel trap fisheries by developing six types of automated fishing equipment: a bait crusher, bait cutter, main line arranging device, trap cleaning device, eel sorting device, and fish pump system. Sea trials demonstrated that the bait crusher and bait cutter significantly reduced manual labor and processing time while maintaining bait quality. The main line arranging device improved productivity and safety by automating the sorting of looped cords. The trap cleaning device effectively removed fouling organisms using high-pressure water and rotating brushes. The eel sorting device enabled automatic size-based selection, improving resource management and operational efficiency. The fish pump system transferred eels rapidly with minimal physical damage, reducing unloading time by over 80% and decreasing labor requirements. A satisfaction survey of fishery participants confirmed that all developed devices were highly effective in reducing workload, enhancing safety, and improving operational performance. The automated equipment developed in this study is expected to contribute to the sustainable management of offshore eel trap fisheries and to offer potential applicability to other coastal and offshore fisheries.

This study examined impact of agricultural cooperative membership on technical efficiency, income, and costs of coffee farmers in Southern Shan State, Myanmar. Using stochastic frontier analysis (SFA) and propensity score matching (PSM) methods, this study estimated average treatment effect on the treated of agricultural cooperative participation. Results showed that technical efficiency, total income, and total variable costs were significantly higher for cooperative members than for comparable non-members. However, net income of members is not significantly different from that of comparable non-members.

The Safe Korea Training is a national-level training program that has been conducted since 2005 to create a safe Korea by preventing various disasters and minimizing the damage in the event of a disaster, and it has contributed a lot to the safety of Korea. However, there are still some problems that need to be solved, and one of the most urgent problems is that the Safe Korea Training is focused on efficient response measures in the event of a disaster, and the evaluation of the Training is limited to the evaluation of the training organization, which does not meet the main purpose of the Safe Korea drill to prevent various disasters. Therefore, in order to achieve the purpose of preventing various disasters, it is necessary to share the results and evaluations of the drill with other relevant public institutions other than the Ministry of the Interior and Safety in order to prevent various risk factors recognized during the drill in advance, and to establish a network that can lead to legislation so that the problems recognized during the drill are not repeated. By doing so, it is hoped that the Safe Korea Training will fulfill its purpose and lead to a truly safe Korea.

최근 자율주행 기술의 급속한 발전으로 자율주행 기술이 탑재된 차량이 눈에 띄고 있다. 자율주행 기술로 인해 교통사 고 감소와 효율적인 교통운영을 유도할 수 있는데, 주행 환경뿐만 아니라 주차 환경에서도 큰 이점을 보이고 있다. 이러 한 자율주행 기술을 기반으로 한 로봇 파킹 시스템은 주차 소요 시간을 단축하고 주차 공간을 더욱 효율적으로 활용할 수 있는데, 이는 특히 교통약자들의 이동 편의성을 크게 향상시킬 수 있다. 따라서 본 연구에서는 차량의 진출입이 빈번 하고 보행자의 이동이 많은 고속도로 휴게시설을 대상으로 교통약자를 고려한 로봇 파킹 시스템을 도입하여 안정성과 효율성을 평가하고자 한다. 이를 위해 2010년부터 2022년까지의 고속도로 휴게시설 사고 데이터를 분석하여, 사고 빈도 와 사고 심각도를 고려한 EPDO(Equivalent Property Damage Only) 값이 높은 중부내륙선 충주휴게소(창원방향)를 분석 대상지로 선정하였다. 미시교통 시뮬레이션 VISSIM을 활용하여 대상 휴게소의 도로 및 주차장 네트워크를 구축하고 시 뮬레이션하였다. 안전성 평가를 위해 DRAC(Deceleration Rate to Avoid Crash) 및 PET(Post Encroachment Time) 지 표 등을 활용하였으며, 효율성 평가로는 주차 회전율(Parking Turning Rate) 및 정지횟수(Number of Stops) 지표 등을 사용하여 비교하였다. 본 연구는 기존 연구들과 달리 교통약자의 관점에서 로봇 파킹 시스템의 효과를 분석했다는 점에 서 차별성을 가진다.

이 연구에서는 환노출이 기업의 투자비효율성과 갖는 관계를 확인한다. 표본 기간은 2007년부터 2022년까지 16년 동안이며, 분석 대상 기업은 한국의 유가증권시장과 코스닥시장에 상장된 비금융업종 기업이다. 분석결과, 환노출이 존재하는 기업에서 과대투자와 과소투자를 포함한 비효율적인 투자가 감소하여 투자효율성 이 향상된다. 이러한 결과는 환노출이 존재하는 것으로 확인되는 경우 경영자는 기회주의적 행동을 하기보다는, 위 험을 인지하고 기업 성과를 극대화할 수 있는 투자 결정을 내리기 때문인 것으로 판단된다. 환노출이 외부 감시 메커니즘으로 작용하여 투자비효율성을 감소시킨다는 분석결과는 환노출 추정 모형과 환노출과 투자비효율성 간 의 관계 추정모형 선택과 무관하게 일관성 있게 나타나는 결과이다. 그러나 글로벌 금융위기 동안에는 환노출과 투 자비효율성 간에 유의적인 관계를 확인할 수 없다. 이는 글로벌 금융위기가 초래한 환노출의 직접적인 영향인 환 위험의 증가로 인한 불확실성의 확대와 경영자와 외부이해관계자 간의 정보비대칭 확대로 인한 경영자의 비효율적 인 투자 선택 가능성 증가 효과가, 환노출의 간접적인 영향인 시장의 규율효과에 의한 비효율적 투자 감소효과를 상쇄시키기 때문인 것으로 판단된다. 이 연구는 환노출이 기업 투자비효율성에 미치는 영향을 경영자와 외부 감시 메커니즘의 관계 관점에서 분석함 으로써 환노출이 기업에 미치는 영향에 대한 연구 영역을 확장시키고 있다는 측면에서 학술적 의의를 갖는다.

전국 태양광 발전시설의 효율적인 보급을 위해 9개 도 지역별 기상 데이터를 활용한 DEA(Data Envelopment Analysis) 효율성 분석 결과를 도출하고자 한다. 국내 태양광 중심으로 설비보급과 발전 비중이 빠른 속도로 증가 중이며 재생에너지 전력 생산의 효율적 개편을 위해 기후변화에 따른 기상 예측 정보를 활용하고 있다. 본 연구는 신재생 에너지 정책의 시사점이 높았던 2020∼2022년의 기상청 데이터와 과거 30년 평균(1981년 ∼2012년) 데이터를 기준으로 일사량 변화에 의한 발전량 예측 모델을 시뮬레이션했다. 특히 기상 데이터와 실제 발전량 사이 관계를 분석하여 투입 산출 변수와 관련 있는 연구모형의 효율성을 파악하였다. 태양광 발전시설의 안정적인 운영과 관리를 통해 최상의 발전시설 상태를 유지하고, 전력량을 끌어올리기 위해 전문적이고 차별화된 운영관리 (O&M) 서비스 제공이 필요하다.

본 연구에서는 자료포락분석(DEA) 기법을 이용하여 해양환경 요인의 영향을 받는 남해 주요 해역의 어업생산활동 효율성을 비교하고, 해양환경 재해요인이 효율성 변동에 어떠한 영향을 미치는지 분석하였다. 분석에는 남해 서부 여자만부터 동부 진해만 해역까 지 18개 해역을 업무구역으로 하는 12개 지구별 수협의 10년간(2013-2022년) 계통출하 생산자료를 사용하였다. 분석기간 동안 여수와 고흥 수협이 상대적으로 적은 생산자수와 어업비용을 투입하여 높은 생산량과 생산금액을 산출함으로써 높은 기술적 효율성을 달성하였으며, 멸치 생산금액과 김 생산량이 각각 높은 효율성의 기반으로 추정되었다. 평균 기술적 효율성은 2013년 49.3%에서 2022년 40.7%으로 감소 하였으며, 통영 수협이 96.4%에서 34.5%로 가장 크게 감소하였다. 삼천포 수협은 기술적 효율성 대비 규모 효율성이 가장 높아 생산기술 의 순수기술적인 비효율을 해결해야 하는 것으로 나타났다. 정태적 분석에서 기술적 효율성을 달성했던 여수와 고흥 수협의 경우, 5년 단 위의 Window-DEA 분석 결과 동태적인 비효율성이 존재하는 것을 확인하였다. 해양환경 재해요인의 경우, 진해만 해역의 수협과 여수 수 협의 어업생산 효율성이 연도별로 빈산소수괴 발생횟수와 유의한 부(-)의 상관관계를 나타내었다.

본 논문에서는 소성 설계를 기반으로 한 프레임 구조 설계 시, 기둥의 종류에 따른 구조 제작 비용과 거동의 차이를 연구하였다. 축 력과 횡력을 모두 받는 구조물에 적합한 기둥 부재를 선택하는 것이 중요하며, 플라스틱 설계 방법을 채택할 경우 기둥의 역할이 더욱 강조된다다. 특히, 횡력은 기둥의 연성을 요구하며, CFT(콘크리트 충전 강관)형 기둥은 RC(철근 콘크리트) 기둥보다 높은 강철 비율 로 연성을 확보하게 된다. 이 논문에서는 CFT 기둥이 RC 기둥보다 더 나은 성능을 보이는지 확인하기 위해 다양한 구조 유형에서 기 둥을 설계하고 분석하였다. CFT 기둥을 소성 설계에 채택함으로써 얻을 수 있는 이점은 다양한 구조 유형에 따른 하중 유형의 분석을 통해 제시한다.

The purpose of this study is to identify bias-adjusted efficiency estimates and the determinants of efficiency in the Marine-Bio industry. Efficiency was estimated using the Bootstrap-DEA model, and efficiency determinants were analyzed by utilizing the dependent variables such as company age, number of employees, location within Marine-Bio clusters, R&D performance, and debt ratio. The efficiency analysis revealed that most of the DMUs belonged to the inefficient group with efficiency values below 0.7. The primary cause of inefficiency was identified as pure technical efficiency, which reflects the effectiveness of input combinations. In the analysis of efficiency determinants, it was found that the number of employees and the debt ratio had a positive (+) effect on efficiency. Conversely, engaging in R&D activities was found to have a negative (-) effect on efficiency.

The purpose of this study is to estimate the production function of the oliver flounder (Paralichthys olivaceus) aquaculture industry, analyze its efficiency, and provide implications for sustainable aquaculture. For this purpose, the SFA model was utilized. The results of this study are as follows. First, the coefficient values of labor wages and farm area are higher than other inputs. This suggests that the Korean oliver flounder aquaculture industry is labor-intensive. Second, disease management is highly influenced by management efficiency. The more frequently farms are disinfected and culled, the higher the management efficiency with culling having a greater impact on management efficiency. Finally, the cost inputs of high and low-efficiency fish farms were analyzed, and it is recommended that wages, electricity, drugs, and oxygen should be kept at a reasonable level rather than excessive. However, the higher the inputs for mortality removal and disease management, the higher the management efficiency. In other words, improving the farm environment is the most important to achieve sustainability and management efficiency of Korean oliver flounder farming.

This study proposes a mathematical model to optimize the fighter aircraft-weapon combinations for the ROKAF(Republic Of Korea Air Force). With the recent emergence of the population declining issue in Republic of Korea, there is an urgent need for efficient weapon system operations in light of decreasing military personnel. In order to solve these issues, we consider to reduce the workload of pilots and maintenance personnel by operating an optimal number of weapons instead of deploying all possible armaments for each aircraft type. To achieve this, various factors for optimizing the fighter-weapon combinations were identified and quantified. A model was then constructed using goal programming, with the objective functions based on the compatibility, CEP(Circular Error Probable), and fire range of the weapons, along with the planned wartime mission-specific weapon ratios for each aircraft type. The experimental result's analysis of the proposed model indicate a significant increase in mission performance efficiency compared to the existing system in both operational and maintenance aspects. We hope that our model will be reflected to help improve the operational capabilities of Republic of Korea Air Force.

This study focuses on the effectiveness of regional business support programs funded by South Korea's Balanced National Development Special Account, one of the policies designed to address regional imbalances and promote local autonomy. Using the analytical approach including DEA (Data Envelopment Analysis) methodology, This study analyzed the efficiency of 76 star companies in the Jeonbuk region based on their performance from 2018 to 2023. This study was designed to improve previous studies limitations, which only analyzed simple input-output efficiency in the short term, by using six years of mid-term data to comprehensively evaluate input variables in both R&D and Non-R&D sectors. The main purpose of this study is to analyze the effectiveness of the expiring Star Company Development Program by evaluating efficiency of supported company groups using DEA and to propose support models and policy suggestions for upcoming regional specialized industries support program by identifying the features of both optimal and inefficiency models. For this, employments along with financial indicators such as sales revenue, operating profit, and total assets were set as output variables, with R&D and non-R&D support amounts were set as input variables for analysis. According to the results, the optimal efficiency model group has strong intellectual property acquisition capabilities, and continuous R&D investment. It shows that continuous innovation activities are a key factor for improving the effectiveness of support. This study found that, from a mid․long term perspective, policy support programs should be customized by unique characteristics of each industry field, Based on this, it was suggested that upcoming regional specialized industry support programs in the Jeonbuk region should include policy planning and support program design to complement the weaknesses of each industry field.

As the Fourth Industrial Revolution advances, smart factories have become a new manufacturing paradigm, integrating technologies such as Information and Communication Technology (ICT), the Internet of Things (IoT), Artificial Intelligence (AI), and big data analytics to overcome traditional manufacturing limitations and enhance global competitiveness. This study offers a comprehensive approach by evaluating both technological and economic performance of smart factory Research and Development (R&D) projects, addressing gaps in previous studies that focused narrowly on either aspect. The research combines Latent Dirichlet Allocation (LDA) topic modeling and Data Envelopment Analysis (DEA) to quantitatively compare the efficiency of various topics. This integrated approach not only identifies key research themes but also evaluates how effectively resources are utilized within each theme, supporting strategic decision-making for optimal resource allocation. Additionally, non-parametric statistical tests are applied to detect performance differences between topics, providing insights into areas of comparative advantage. Unlike traditional DEA methods, which face limitations in generalizing results, this study offers a more nuanced analysis by benchmarking efficiency across thematic areas. The findings highlight the superior performance of projects incorporating AI, IoT, and big data, as well as those led by the Ministry of Trade, Industry, and Energy (MOTIE) and small and medium-sized enterprises (SMEs). The regional analysis reveals significant contributions from non-metropolitan areas, emphasizing the need for balanced development. This research provides policymakers and industry leaders with strategic insights, guiding the efficient allocation of R&D resources and fostering the development of smart factories aligned with global trends and national goals.

This study proposes a mathematical model to optimize the fighter aircraft-weapon combinations for the Republic of Korea Air Force. With the recent emergence of the population cliff issue due to declining birth rates in Korea, there is an urgent need for efficient weapon system operations in light of decreasing military personnel. This study aims to enhance operational environments and mission efficiency within the military. The objective is to reduce the workload of pilots and maintenance personnel by operating an optimal number of weapons instead of deploying all possible armaments for each aircraft type. To achieve this, various factors for optimizing the fighter-weapon combinations were identified and quantified. A model was then constructed using goal programming, with the objective functions based on the compatibility, Circular Error Probable (CEP), and fire range of the weapons, along with the planned wartime mission-specific weapon ratios for each aircraft type. Experimental analysis of the proposed model indicated a significant increase in mission performance efficiency compared to the existing system in both operational and maintenance aspects. It is hoped that this model will be applied in military settings.