• Journal of the Korean Society of Industry Convergence
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• v.24 no.6_2
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• pp.899-908
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• 2021

It is expected that the global market for vessel repair and remodeling will grow up to the scale of about 25 billion dollars by 2023. Korea's shipbuilding industry is leading the world with its international competitiveness in design and production technology. The actual status of vessel repair industry, however, is poor as there are only two or three companies for vessel repair that can deal with large vessels in the area of Gyeongnam. The reason is that civil complaints are filed severely about environmental problems and environment-related regulations are so strict that it is fairly hard to get governmental approval for the operation of a vessel repair workplace. Domestic vessel repair companies mainly target small- and medium-sized vessels. There are only few workplaces that can carry out regular examination or repair work on large vessels such as LNG vessels, and due to the high price of vessel repair, most of the domestic repair work on large vessels including LNG vessels tends to be snatched by markets in Southeast Asia or China. Despite the tremendous domestic demand of Korea that has established the world's first shipbuilding industry and world's sixth biggest harbor infrastructure, its vessel repair industry can be said to be in very poor condition. In order to vitalize vessel repair industry, this study is aimed to analyze the environmental influence of vessel repair workplaces in Gyeongnam where vessel repair companies are concentrated and suggest standard processes by analyzing vessel repair processes precisely.

• Journal of Ocean Engineering and Technology
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• v.35 no.6
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• pp.446-456
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• 2021

To build an environment facility of a large-scale ocean basin, various detailed reviews are required, but it is difficult to find data that introduces the related research or construction processes on the environment facility. The current generator facility for offshore structure safety evaluation tests should be implemented by rotating the water of the basin. However, when the water in the large basin rotates, relatively large flow irregularities may occur and the uniformity may not be adequate. In this paper, design and review were conducted to satisfy the performance goals of the DOEB through computational numerical analysis on the shape of the waterway and the flow straightening devices to form the current in the large tank. Based on this, the head loss, which decreases the flow rate when the large tank water rotates through the water channel, was estimated and used as the pump capacity (impeller) design data. The impeller of the DOEB current generator was designed through computational numerical analysis (CFD) based on the lift surface theory from the axial-type impeller shape for satisfying the head loss of the waterway and maximum current velocity. In order to confirm the performance of the designed impeller system, the flow rate and flow velocity performance were checked through factory test operation. And, after installing DOEB, the current flow rate and velocity performance were reviewed compare with the original design target values. Finally, by measuring the current velocity of the test area in DOEB formed through the current generator, the spatial current distribution characteristics in the test area were analyzed. Through the analysis of the current distribution characteristics of the DOEB test area, it was confirmed that the realization of the maximum current velocity and the average flow velocity distribution, the main performance goals in the waterway design process, were satisfied.

• Journal of Biomedical Engineering Research
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• v.43 no.5
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• pp.361-368
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• 2022

The purpose of this study was to develop a hand rehabilitation training system for hemiplegic patients. We also tried to find out five hand postures (WF: Wrist Flexion, WE: Wrist Extension, BG: Ball Grip, HG: Hook Grip, RE: Rest) in real-time using multi-channel EMG-based deep learning. We performed a pre-processing method that converts to Spider Chart image data for the classification of hand movement from five test subjects (total 1,500 data sets) using Convolution Neural Networks (CNN) deep learning with an 8-channel armband. As a result of this study, the recognition accuracy was 92% for WF, 94% for WE, 76% for BG, 82% for HG, and 88% for RE. Also, ten physical therapists participated for the usability evaluation. The questionnaire consisted of 7 items of acceptance, interest, and satisfaction, and the mean and standard deviation were calculated by dividing each into a 5-point scale. As a result, high scores were obtained in immersion and interest in game (4.6±0.43), convenience of the device (4.9±0.30), and satisfaction after treatment (4.1±0.48). On the other hand, Conformity of intention for treatment (3.90±0.49) was relatively low. This is thought to be because the game play may be difficult depending on the degree of spasticity of the hemiplegic patient, and compensation may occur in patient with weakened target muscles. Therefore, it is necessary to develop a rehabilitation program suitable for the degree of disability of the patient.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.35 no.5
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• pp.431-438
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• 2022

In functional materials, in situ experimental techniques as a function of external stimulus (e.g., electric field, magnetic field, light, etc.) or changes in ambient environments (e.g., temperature, humidity, pressure, etc.) are highly essential for analyzing how the physical properties of target materials are activated/evolved by the given stimulation. In particular, in situ electric-field-dependent X-ray diffraction (XRD) measurements have been extensively utilized for understanding the underlying mechanisms of the emerging electromechanical responses to external electric field in various ferroelectric, piezoelectric, and electrostrictive materials. This tutorial article briefly introduces basic principles/key concepts of in situ electric-field-dependent XRD analysis using a lab-scale XRD machine. We anticipate that the in situ XRD method provides a practical tool to systematically identify/monitor a structural modification of various electromechanical materials driven by applying an external electric field.

• Journal of Technology Innovation
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• v.30 no.3
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• pp.35-64
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• 2022

Currently, The budget expenditure for national R&D has been on the rise, and the quantitative performance in national R&D programs has been increasing accordingly. However, a growth of qualitative performance can not reach to an upward trend of quantitative performance. For a poor qualitative performance such as patent grades and technologies with low efficiency of technology transfer, the performance evaluation centered on "number of cases" is necessary to improve and start to introduce various "qualitative performance indicators". This paper focuses on "Triadic Patent Families" being measurable the overseas competitiveness of patent applied in major countries(the US, Europe and Japan). It analyzes the influencing factors to evaluate the quality of qualitative performance of R&D program. The result of this analysis shows a significant effect on the creating of triadic patent families within factors of R&D scale and project characteristics. This paper is significantly meaningful to expand insufficient triadic patent families to the target of interest rather than early study relatively, and to analyze the influencing factors of the creation of triadic patent families.

• Journal of the Korea Convergence Society
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• v.12 no.7
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• pp.169-179
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• 2021

This study shows that the two-stage k-means clustering method can improve prediction performance by predicting the stock price, To this end, this study introduces the two-stage k-means clustering algorithm and tests the prediction performance through comparison with various machine learning techniques. It selects the cluster close to the prediction target obtained from the k-means clustering, and reapplies the k-means clustering method to the cluster to search for a cluster closer to the actual value. As a result, the predicted value of this method is shown to be closer to the actual stock price than the predicted values of other machine learning techniques. Furthermore, it shows a relatively stable predicted value despite the use of a relatively small cluster. Accordingly, this method can simultaneously improve the accuracy and stability of prediction, and it can be considered as the new clustering method useful for small data. In the future, developing the two-stage k-means clustering is required for the large-scale data application.

• The Journal of the Korea Contents Association
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• v.21 no.11
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• pp.361-374
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• 2021

The purpose of this study is to analyze the efficiency and productivity of technological innovation activities of companies certified as innovative pharmaceutical companies by the government to diagnose their competitiveness and derive measures to strengthen them. This study collected pharmaceutical input (R&D expenditures and number of employees) and output (sale, operating profit and patent) data between 2017 and 2019 for 38 innovative pharmaceutical companies. This study analyzed them using the data envelopment analysis (DEA) method, Tobit model and the Malmquist Productivity Index (MPI). First, the DEA result of the innovative pharmaceutical companies show that between the value of the CCR model of the scale efficiency and the value of the BCC model to diagnose the internal operation efficiency is differences. Second, efficiency does not differ between corporate characteristics. Third, Tobit model shows that number of patents held have positive effects on efficiency. Forth, overall MPI is 0.89. This can be interpreted as the rate of TECI decreased 3%p and TCI has increased 4%p. The results of this study can be used as decision-making data for response strategies to improve efficiency by identifying the cause of inefficiency and presenting target values.

• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.6
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• pp.177-184
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• 2021

In recent years, large-scale earthquake activity has occurred in Korea, and thus public interest in earthquakes is increasing. Accordingly, the importance of seismic performance management of structures is emerging. In particular, the collapse of a bridge, one of main road facilities, directly leads to many casualties. Therefore, engineers need to evaluate the seismic fragility of the bridge and prepare for the earthquake event. The service life of these bridges has been over 30 years, which requires a study on the aging effect on bridges. In this study, seismic analysis of the target RC slab bridge was performed considering the aging effects of each component of the bridge. Components of the bridge included pier and bearing, which dominate the seismic response of the bridge. The seismic performance of the bridge was evaluated using nonlinear static and dynamic analyses. In addition, the limit state and dynamic response of each component were used to evaluate the seismic fragility according to the aging of each component.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.4065-4083
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• 2021

Super-resolution can improve the clarity of low-resolution (LR) images, which can increase the accuracy of high-level compute vision tasks. Portable devices have low computing power and storage performance. Large-scale neural network super-resolution methods are not suitable for portable devices. In order to save the computational cost and the number of parameters, Lightweight image processing method can improve the processing speed of portable devices. Therefore, we propose the Enhanced Information Multiple Distillation Network (EIMDN) to adapt lower delay and cost. The EIMDN takes feedback mechanism as the framework and obtains low level features through high level features. Further, we replace the feature extraction convolution operation in Information Multiple Distillation Block (IMDB), with Ghost module, and propose the Enhanced Information Multiple Distillation Block (EIMDB) to reduce the amount of calculation and the number of parameters. Finally, coordinate attention (CA) is used at the end of IMDB and EIMDB to enhance the important information extraction from Spaces and channels. Experimental results show that our proposed can achieve convergence faster with fewer parameters and computation, compared with other lightweight super-resolution methods. Under the condition of higher peak signal-to-noise ratio (PSNR) and higher structural similarity (SSIM), the performance of network reconstruction image texture and target contour is significantly improved.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.55-63
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• 2023

In this paper, we propose a function and service of the Disaster Crisis Alert Management System that automatically analyzes the situation judgment criteria to issue a disaster crisis alert and a plan to operate in the National Disaster Management System(NDMS). In the event of a disaster, a crisis alert(interest-caution-alert-serious) is issued according to the crisis alert level. In order to automatically analyze and determine the crisis alert level, first, data collection, crisis alert level analysis, crisis alert level judgment, and disaster crisis alert management system that expresses the crisis alert level by spatial scale(province, city, district) were implemented. The crisis alert level was analyzed and expressed in two ways by applying the intelligent crisis alert level(determination of regional sensitivity, risk level, and crisis alert level) and the crisis alert standard of the crisis management manual(province-level standard setting). Second, standard metadata, linkage of situation information of target) and API standards for data provision are presented to jointly utilize data linkage and crisis alert data of the disaster and safety data sharing platform so that it can be operated within the NDMS.