• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.11
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• pp.1015-1026
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• 2019

The purpose of this study is to develop evaluation indexes for improving the quality of long-term care institutions (facility salary) evaluation in the sense that the applicability and effectiveness of previous studies related to the development of evaluation indexes for long-term care facilities for elderly are insufficient. There was this. To this end, an analytical review of the 2018 long-term care institution (accommodation benefit) evaluation index, an analysis of Japan's elderly long-term care home evaluation index, and the elderly long-term care facility workers in Korea and the special care home for the elderly in Japan FGI on evaluation indicators and evaluation system was conducted. Based on the results of the research, evaluation indicators were developed in terms of supporting users to receive high quality services. The characteristics of the elderly, that is, the characteristics of elderly diseases that are difficult to maintain and improve, the direction and transparency of institutional operation, and the need for terminal care were reflected. Forty-three evaluation indicators were presented, covering institutional operations, environment and safety, beneficiary rights protection, payroll process, and payroll results. In addition, we proposed a four-step multi-level evaluation system that can improve the efficiency of the evaluation process by improving the redundant and unnecessary evaluation process.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.6
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• pp.129-134
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• 2021

Recently, the demand for electricity is gradually increasing due to the rapid industrial development and the improvement of living standards. In the case of Korea, which is highly dependent on fossil fuels due to such a surge in electricity demand, reduction and freezing of greenhouse gas emissions due to international environmental regulations will immediately lead to a contraction in industrial activities. Accordingly, there are many difficulties in competition with advanced countries that want to link the environment with the country's industrial production activities, and the development of alternative energy as a countermeasure is of great interest around the world. Among these new power generation methods, small-scale power generation facilities with relatively small capacity include photovoltaic generation, wind power generation, and fuel cell generation. Among them, the fuel cell attracts the most attention in consideration of continuous operation, high power generation efficiency, and long-term durability, which are important factors for practical use. Therefore, in this paper, the fuel cell power generation system was researched and constructed by designing the power conversion circuit necessary to finally obtain the AC power used in our daily life by using the DC power generated from the fuel cell as an input.

• Journal of Navigation and Port Research
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• v.42 no.6
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• pp.437-445
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• 2018

IMO (International Maritime Organization) has been strengthening the regulations of ship emission gas such as sulfur oxides (SOX), nitrogen oxides (NOX) and carbon dioxides (CO2) to protect the marine environment. Especially, ECA (Emission Control Area) has been set and operated in the USA and US. As a countermeasure against these environmental regulations, the demand for environmentally, friendly and highly efficient vessels has led to a growing interest in technology related research with respect to electric propulsion systems capable of reducing exhaust gas. Container ships were excluded from the application coverage of the electric propulsion systems for reasons of operation at economical speed. However, in the future, the need for electric propulsion system is expected to rise, because it is easy to monitor and control so that it can be an applicate to smart ship which are represented by fourth industrial revolution technology. In this study, research was carried out to design a generator and battery capacity through the load analysis of the 6,800TEU container ship to apply the electric propulsion system of the container ship. A capacity design based on the load analysis has an advantage that the generator can be operated in a high efficiency section through the load distribution control using the battery.

• The Journal of Bigdata
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• v.5 no.2
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• pp.17-27
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• 2020

District heating system supplies heat from low-cost high-efficiency heat production facilities to heat demand areas through a heat pipe network. For efficient heat supply system operation, it is important to accurately predict the heat demand within the region and optimize the heat production plan accordingly. In this study, a heat demand forecasting model is proposed considering real-time calorimeter information from local heat demands. Previous models considered ambient temperature and heat demand history data to predict future heat demands. To improve forecast accuracy, the proposed heat demand forecast model added big data from real-time calorimeters installed in the heat demands within the target region. By employing calorimeter information directly in the model, it is expected that the proposed forecast model is to reflect heat use pattern of each demand. Computational experiemtns based on the actual heat demand data shows that the forecast accuracy of the proposed model improved when the calorimeter big data is reflected.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.3
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• pp.203-214
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• 2022

As the global demand for small satellites weighing less than 500 kg increases, the development and operation of dedicated small launch vehicles increase significantly. The responsiveness of a launch vehicle that puts a small satellite into a target orbit at the desired time is attracting attention. As a result, interest in the air launch is increasing in the rapid establishment of a constellation. As the demand for small satellites in south Korea increases, this study performed analyses on the applicability of an air launch vehicle using a large civil aircraft considering the geographical environment. In terms of responsiveness, mission response times were compared and analyzed for air launch vehicles and ground small and large vehicles. In addition, an air vehicle and a small ground vehicle were quantitatively compared and analyzed for the orbital insertion performance. As a result of the analysis, the air launch vehicle has limited responsiveness in Korea regarding rapid satellite constellation establishment. However, it can be an effective alternative for low inclination angle orbit insertion with the benefit of a fast turnaround time. Furthermore, the performance of the orbital injection is close to that of the ground small launch vehicle, and the high efficiency in terms of the required propellant mass is possible, so air launch can be an effective launch means for putting small satellites into orbit in Korea.

• Smart Structures and Systems
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• v.29 no.4
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• pp.625-640
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• 2022

Maglev rail joints are vital components serving as connections between the adjacent F-type rail sections in maglev guideway. Damage to maglev rail joints such as bolt looseness may result in rough suspension gap fluctuation, failure of suspension control, and even sudden clash between the electromagnets and F-type rail. The condition monitoring of maglev rail joints is therefore highly desirable to maintain safe operation of maglev. In this connection, an online damage detection approach based on three-dimensional (3D) convolutional neural network (CNN) and time-frequency characterization is developed for simultaneous detection of multiple damage of maglev rail joints in this paper. The training and testing data used for condition evaluation of maglev rail joints consist of two months of acceleration recordings, which were acquired in-situ from different rail joints by an integrated online monitoring system during a maglev train running on a test line. Short-time Fourier transform (STFT) method is applied to transform the raw monitoring data into time-frequency spectrograms (TFS). Three CNN architectures, i.e., small-sized CNN (S-CNN), middle-sized CNN (M-CNN), and large-sized CNN (L-CNN), are configured for trial calculation and the M-CNN model with excellent prediction accuracy and high computational efficiency is finally optioned for multiple damage detection of maglev rail joints. Results show that the rail joints in three different conditions (bolt-looseness-caused rail step, misalignment-caused lateral dislocation, and normal condition) are successfully identified by the proposed approach, even when using data collected from rail joints from which no data were used in the CNN training. The capability of the proposed method is further examined by using the data collected after the loosed bolts have been replaced. In addition, by comparison with the results of CNN using frequency spectrum and traditional neural network using TFS, the proposed TFS-CNN framework is proven more accurate and robust for multiple damage detection of maglev rail joints.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.29 no.2
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• pp.95-102
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• 2023

Despite the easing of social distancing, demand for non-face-to-face services continues to rise. Recently, the EU is pursuing a comprehensive plastic use reduction by expanding the scope of plastic use regulations for packaging plastics according to the New Cyclical Economy Action Plan(NCEAP). In response to this trend, the packaging industry is moving away from conventional non-degradable/petroleum-based plastics and conducting research on packaging materials using biodegradable plastics such as PLA(Poly Lactic Acid), PBAT(Poly Butylene Adipate-co-butylene Terephthalate). On the other hand, ginkgo leaves occur in large quantities in Korea and act as a cause of slip accidents and flooding. In this study, a method to utilize ginkgo biloba leaf as a new alternative biomass resource was proposed by producing lactic acid through pretreatment, enzymatic saccharification, and fermentation processes. For the efficiency of lactic acid production, a comparative analysis of lignin content from before and after browning was performed. In addition, the degree of glucan extraction was evaluated by applying a pretreatment method using three catalysts: hot water, sulfuric acid, and sodium hydroxide. It is difficult to expect high production of lactic acid with single process. Therefore, an integrated process operation using both the pretreated hydrolyzate and the residual solid enzymatic saccharification solution must necessarily be applied.

• Journal of Korea Port Economic Association
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• v.38 no.4
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• pp.65-85
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• 2022

In this study, in order to derive the priority of indicators and sustainability areas of smart ports, which means ports in the digital era, previous studies and ESG, which have recently been indispensably introduced in all industries worldwide, were studied together. A hierarchical structure was established with upper evaluation items and 20 lower evaluation items in four areas (operational, environmental, social, and governance), and a relative evaluation method of weighting items among the AHP techniques was applied. The pairwise comparison questionnaire consisted of a 9-point scale proposed by Satty (1980). A survey was conducted targeting working-level workers who perform sustainability or ESG(Environmental, Social, Governance)-related work at four representative port authorities in Korea (Busan, Incheon, Ulsan, Yeosu Gwangyang). In order to increase the accuracy of the analysis results, AHP analysis was conducted on 17 questionnaires with a consistency ratio of 0.1 or less. As a result of the analysis, it was confirmed that among the four areas representing the sustainability of domestic smart ports, the operation area had the highest priority, followed by the environment area. In addition, looking at the overall priorities for the 20 detailed indicators, indicators such as operational efficiency, operational planning, energy management, and pollution measurement and management system were found to have high priority. On the other hand, it was confirmed that the social and the governance areas had relatively low importance compared to other areas.

• Journal of Internet of Things and Convergence
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• v.10 no.1
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• pp.39-45
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• 2024

Container volume is a very important factor in accurate evaluation of port performance, and accurate prediction of effective port development and operation strategies is essential. However, it is difficult to improve the accuracy of container volume prediction due to rapid changes in the marine industry. To solve this problem, it is necessary to analyze the impact on port performance using the Internet of Things (IoT) and apply it to improve the competitiveness and efficiency of Busan Port. Therefore, this study aims to develop a prediction model for predicting the future container volume of Busan Port, and through this, focuses on improving port productivity and making improved decision-making by port management agencies. In order to predict port container volume, this study introduced the Extreme Gradient Boosting (XGBoost) technique of a machine learning model. XGBoost stands out of its higher accuracy, faster learning and prediction than other algorithms, preventing overfitting, along with providing Feature Importance. Especially, XGBoost can be used directly for regression predictive modelling, which helps improve the accuracy of the volume prediction model presented in previous studies. Through this, this study can accurately and reliably predict container volume by the proposed method with a 4.3% MAPE (Mean absolute percentage error) value, highlighting its high forecasting accuracy. It is believed that the accuracy of Busan container volume can be increased through the methodology presented in this study.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.1
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• pp.31-37
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• 2024

In this study, we propose a machine vision-based pedestrian signal detection algorithm that operates efficiently even in computing resource-constrained environments. This algorithm demonstrates high efficiency within limited resources and is designed to minimize the impact of ambient lighting by sequentially applying HSV color space-based image processing, binarization, morphological operations, labeling, and other steps to address issues such as light glare. Particularly, this algorithm is structured in a relatively simple form to ensure smooth operation within embedded system environments, considering the limitations of computing resources. Consequently, it possesses a structure that operates reliably even in environments with low computing resources. Moreover, the proposed pedestrian signal system not only includes pedestrian signal detection capabilities but also incorporates IoT functionality, allowing wireless integration with a web server. This integration enables users to conveniently monitor and control the status of the signal system through the web server. Additionally, successful implementation has been achieved for effectively controlling 50W LED pedestrian signals. This proposed system aims to provide a rapid and efficient pedestrian signal detection and control system within resource-constrained environments, contemplating its potential applicability in real-world road scenarios. Anticipated contributions include fostering the establishment of safer and more intelligent traffic systems.