• Journal of Korea Port Economic Association
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• v.37 no.4
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• pp.51-70
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• 2021

This study measured the environmental efficiency of 21 international airports based on sustainability reports issued by each airport for 2018. As many sectors in the industry paid attention to social and environmental responsibilities, airport operators comprise one of the leading sectors that streamlined their facilities to become increasingly sustainable and environmental. Nevertheless, studies on the environmental operations of airports are insufficient compared with studies on economic or operational efficiency. Therefore, the current study aims to determine any possible improvement in the environmental inefficiency of airports with the utilization of directional distance function (DDF) and to examine operational efficiency with the application of the data envelopment analysis (DEA). The majority of airports have operated their facilities efficiently, but not all have effectively managed pollutants generated by airports. Furthermore, many airports can still potentially reduce CO₂ and water consumption. This study suggests several implementable environmental improvements to the aviation sector. Moreover, other industrial sectors may use the research as a benchmark for enhancing environmental efficiency.

• Journal of Korea Port Economic Association
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• v.38 no.2
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• pp.123-138
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• 2022

Korea has been huge investments in its port system, annually upgrading its infrastructure to turn the ports into Asian hub port. However, while Busan port is ranked fifth globally for container throughput, Other Korean ports are ranked much lower. This article applies Data Envelopment Analysis (DEA) and Malmquist Productivity Index (MPI) to evaluate selected major Korean seaports' operational efficiency and productivity from 2010 to 2018. It further integrates Principal Component Analysis (PCA) into DEA, with the PCA-DEA combined model strengthening the basic DEA results, as the discriminatory power weakens when the variable number exceeds the number of Decision Making Units(DMU). Meanwhile, MPI is applied to measure the seaports' productivity over the years. The analyses generate efficiency and productivity rankings for Korean seaports. The results show that except for Gwangyang and Ulsan port, none of the selected seaports is currently efficient enough in their operations. The study also indicates that technological progress has led to impactful changes in the productivity of Korean seaports.

• Journal of Technology Innovation
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• v.31 no.1
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• pp.175-213
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• 2023

As the importance of industry-university cooperation continues to increase in a knowledge-based society, the government is implementing various projects related to industry-university cooperation. However, despite the government's support, it has not achieved satisfactory results, and the need for empirical performance analysis to diffuse the results of industry-university cooperation is increasing. In this study, DEA was used to analyze the Industry-University cooperation performance of universities participating in LINC+ program. Efficiency analysis was performed using the CCR model and the BCC model, and the return to scale and causes of inefficiency were analyzed through the scale efficiency analysis. As a result of the analysis, it was found that there were differences in LINC+ performance depending on the region where the university is located and that each university had different goals for inefficiency improvement. The results of this study will contribute to improving the university's operational efficiency and strengthening competitiveness, and are expected to be utilized in the establishment of follow-up program plans for LINC+.

• Journal of the Korea Society of Computer and Information
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• v.28 no.9
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• pp.159-165
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• 2023

This study aims to analyze the changes in the management efficiency of public institutions in time series, and to examine the relationship with financial performance based on the results of time series changes. Specifically, we classified into upper and lower groups of financial performance based on the government's management evaluation results, and analyze how the management efficiency of each group changed in the period before the evaluation year. Based on public institutions published in public business information system, DEA(Data Envelopment Analysis) was performed for estimating management efficiency. The results are summarized as follows; First, we find that DEA of the upper group changed in the direction of increasing, but DEA of the lower group changed in the direction of decreasing. Second, we find that there is a significant positive relation between DEA and financial performance. This result means that the higher financial performance, the higher management efficiency. These findings imply that management efficiency can be a factor that improve financial performance in public institutions. The results also suggest that government's innovation strategies to improve financial stability by enhancing management efficiency were effective.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.5
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• pp.315-321
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• 2023

Long-span bridges are flexible structures with low natural frequencies and damping ratios, making them susceptible to vibrational serviceability problems. However, the current design guideline of South Korea assumes a uniform threshold of wind speed or vibrational amplitude to assess the occurrence of harmful vibrations, potentially overlooking the complex vibrational patterns observed in long-span bridges. In this study, we propose a pointwise vortex-induced vibration (VIV) detection method using a deep-learning-based signalsegmentation model. Departing from conventional supervised methods of data acquisition and manual labeling, we synthesize training data by generating sinusoidal waves with an envelope to accurately represent VIV. A Fourier synchrosqueezed transform is leveraged to extract time-frequency features, which serve as input data for training a bidirectional long short-term memory model. The effectiveness of the model trained on synthetic VIV data is demonstrated through a comparison with its counterpart trained on manually labeled real datasets from an actual cable-supported bridge.

• Industry Promotion Research
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• v.8 no.4
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• pp.257-266
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• 2023

The research focuses on the provincial universities in the western region of China and investigates the research level of 12 provincial universities from 2017 to 2021, considering both static efficiency and dynamic efficiency. The static efficiency is examined using Data Envelopment Analysis (DEA), while the dynamic efficiency is analyzed using the Malmquist model. The analysis results are as follows: the scientific research efficiency of universities in the 12 western provinces is generally not high. Against the background of the "Double First-Class" construction, the overall efficiency of scientific research in universities is showing an increasing trend. The main reason for the increase in scientific research efficiency is the increase in scale efficiency in recent years. The total factor productivity (TFP) of research activities is influenced by the technology progress index and exhibits a pattern of initial increase, followed by a decline, and then an increase again. Research conclusion: Western colleges and universities should reasonably allocate resources for scientific research activities, perfect scientific research mechanisms, improve management standards, promote scientific innovation and corresponding achievements, and ultimately raise the scientific and technological level in western China.

• Korea Trade Review
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• v.48 no.4
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• pp.121-148
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• 2023

The rapid melting of Arctic sea ice has increased interest in the Northern Sea Route (NSR) as a viable alternative trade route between Europe and Asia. While extensive research has examined its competitiveness in terms of technical feasibility, safety, profitability, and environmental impact, the topic of the NSR ports remains relatively underrepresented in the literature. Hence, this study aims to contribute to the existing research by assessing the efficiency of 17 NSR ports to gain insights into their operations and identify areas for improvement using models of Data Envelopment Analysis(DEA). The obtained results show that efficient ports mainly belong to the western NSR region, with ports like Murmansk and Varandei consistently demonstrating high efficiency and constant returns to scale. Several ports, such as Onega, Arkhangelsk, Naryan-Mar, and Khatanga, showed inefficiencies in the utilization of berths and quay lengths. The findings not only contribute to academic knowledge but also offer practical implications for NSR port authorities, assisting them in making well-informed decisions regarding infrastructure development plans.

• Journal of Korean Society of Forest Science
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• v.113 no.2
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• pp.153-163
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• 2024

Since the onset of the COVID-19 pandemic, there has been a significant shift in the lifestyle patterns of the populace across various domains. Concerns surrounding COVID-19 have emerged as pivotal catalysts of change in recreational habits with people giving a particular preference for environments with low population density and increased openness. This trend has resulted in an uptick in excursions to natural reserves, coastlines, and parks. However, during the peak of infectious outbreaks, widespread adherence to social distancing measures has precipitated a steep decline in tourist footfall across natural recreation forests, exacerbating financial deficits to a considerable extent. Thus, this research sought to compare and analyze the operational efficacy and productivity of national, public, and private natural recreation forests pre- and post-COVID-19 pandemic by utilizing non-parametric methodologies, such as data envelopment analysis and the Malmquist productivity index analysis. The objective was to identify the factors contributing to the decreases in efficiency and productivity and ultimately offer nuanced recommendations tailored to respective administrative bodies. This study's distinctive focus on the analysis of management efficiency and productivity in natural recreation forests nationwide offers significant academic and practical relevance.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.97-109
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• 2024

This research aims to investigate how major cities in Korea utilize smart city-related technologies, develop key performance indicators (KPIs) to measure the smartness and efficiency of cities, and propose a methodology for assessing and suggesting smart city policy directions based on Data Envelopment Analysis (DEA). Referring to the CITYkeys Smart City Performance Measurement Framework, 10 key performance indicators (KPIs) were derived. For each KPI, city statistical data were allocated to input and output variables, and 15 cities were assigned as Decision Making Units (DMUs). The DEA methodology was employed to evaluate the operational efficiency and scale profitability of cities, providing insights into the operational efficiency of each city. Finally, the operational efficiency among DMUs was ranked to propose smart city policy directions for each city.

• The Journal of the Acoustical Society of Korea
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• v.28 no.1
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• pp.32-43
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• 2009

In this paper, we improve the performance of cardiac disorder classification by continuous heart sound signals using automatic segmentation and extreme learning machine (ELM). The accuracy of the conventional cardiac disorder classification systems degrades because murmurs and click sounds contained in the abnormal heart sound signals cause incorrect or missing starting points of the first (S1) and the second heart pulses (S2) in the automatic segmentation stage, In order to reduce the performance degradation due to segmentation errors, we find the positions of the S1 and S2 pulses, modify them using the time difference of S1 or S2, and extract a single period of heart sound signals. We then obtain a feature vector consisting of the mel-scaled filter bank energy coefficients and the envelope of uniform-sized sub-segments from the single-period heart sound signals. To classify the heart disorders, we use ELM with a single hidden layer. In cardiac disorder classification experiments with 9 cardiac disorder categories, the proposed method shows the classification accuracy of 81.6% and achieves the highest classification accuracy among ELM, multi-layer perceptron (MLP), support vector machine (SVM), and hidden Markov model (HMM).