Journal of the Korean Society of Marine Environment & Safety
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v.27
no.1
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pp.88-96
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2021
When oil tankers, large passenger ships and cargo ships sink under the sea owing to various maritime accidents, the residual cargo oil or fuel oil in the such vessels could pose direct risk to factor for the marine environment and it require safe and rapid removal. Although domestic and foreign salvage companies are adopting various recovery methods and technologies with customizations according to each site during recovery operations studies on reasonable assessment modules for the operation process are relatively insufficient. In this study, the data from trapped-oil recovery operations performed at different site conditions were collected and analyzed in order to designed an operation assessment module, define the operational process steps in terms of preparation, implementation and completion, and derive key factors for each detailed process. Subsequently, the module was designed in such a way as to construct performance indicators to assess these key factors. In order to exclude subjective opinions from the assessment as much as possible, the assessment each item was constructed with indicators based on data that could be evaluated quantitatively and its usefulness was verified by applying the module to the trapped-oil recovery operation cases. We expect this the method and the technology assessment module for the trapped-oil recovery operation on sunken vessels will help to verify the adequacy of the trapped-oil recovery such operation before or after. Furthermore, it is expected that the continuous accumulation of assessment data and feedback from past or future operation cases will contribute toward enhancing the overall safety, efficiency and field applicability of trapped-oil recovery operation.
In this study, the operational characteristics of a cam-type vegetable transplanter which usually used in domestic was analyzed and operating mechanism of a transplanting device was analyzed. The main components and power path of the transplanter were analyzed. The maximum and minimum control cycles according to the moving speed and the plant spacing were analyzed. 3D modeling and simulation were performed to derive the trajectory of the bottom end of the transplanting hopper and the plant spacing at the each operating condition. The simulation results were verified by the field tests. As main findings of this study, the transplanting device has one degree of freedom (DOF) which consist of 13 links, 17 rotating joints and 1 half joint, and each part has composite structure with cam and links. By continuous and repetitive motion of the structures of transplanting device, the transplanting hopper plants the seedling in the ground with a vertical direction, and the seedling was planted stably. The power is transmitted to the driving part and transplanting device from the engine, and the maximum and minimum plant spacing of the transplanting device were about 900 mm and 350 mm, respectively.
The Journal of the Convergence on Culture Technology
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v.7
no.3
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pp.123-134
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2021
This study was conducted for the purpose of convergence exploration of evidence-based practices for the advancement of performance analysis of the extracurricular activities at Duksung Women's University. The research method consisted of an expert meeting procedure along with a procedure for analyzing previous studies dealing with the performance analysis of the university's extracurricular activities in the field of pedagogy. The contents of this study consisted of presenting some facts that should be based on evidence for the advancement of performance analysis of the extracurricular activities after the establishment of the center for extracurricular activities in Duksung Women's University. And in practices, the development and diagnostic analysis of tools for diagnosing extracurricular customized learning capabilities, data-based multidimensional analysis (IR system), continuous monitoring analysis through extracurricular certification, and analysis based on feedback tools were presented in a convergence perspective and context. As a result of the study, the evidence-based practices for the advancement of the performance analysis of the extracurricular activities at Duksung Women's University guarantees the validity and stability of the performance evaluation and feedback system of the extracurricular activities at Duksung Women's University, and has a close influence on the extracurricular education work of other universities analyzed as possible.
The Journal of the Convergence on Culture Technology
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v.7
no.3
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pp.261-268
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2021
After developing literacy education programs using coaching techniques, applying them to literacy learners, in order to see how they have an impact on improving learning achievement, we selected 13 senior literacy learners in U city and chose qualitative research method based on in-depth interviews, observation journals, and learning materials. Literature education programs using coaching techniques are a process-oriented model consisting of four stages of mind-opening, introducing positivity, strengthening learning competence and assistance, confidence and persistence. You can find the results as following. Firstly, communication between teachers and learners was expanded in the first stage, and secondly, self-directed learning ability was strengthened in the second stage by forming a positive mind. Thirdly, the results of utilizing the three-stage balanced literacy teaching method and interaction teaching method resulted in confidence in reading and writing, leading to an increase in self-efficacy. Fourthly, the fourth stage showed the results of improving learning achievement, which overcame the fear of learning with active praise and continuous encouragement and implied hope for higher courses. As a result of the above-mentioned research, I think literacy education programs using coaching techniques can be useful as an educational method for learners in the field of literacy education.
Korean Journal of Agricultural and Forest Meteorology
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v.23
no.4
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pp.340-348
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2021
Continuous monitoring of RGB (Red, Green, Blue) vegetation indices is important to apply remote sensing technology for the estimation of crop growth. In this study, we evaluated the performance of eight vegetation indices derived from soybean RGB images with various agronomic parameters under drought stress condition. Drought stress influenced the behavior of various RGB vegetation indices related soybean canopy architecture and leaf color. In particular, reported vegetation indices such as ExGR (Excessive green index minus excess red index), Ipca (Principal Component Analysis Index), NGRDI (Normalized Green Red Difference Index), VARI (Visible Atmospherically Resistance Index), SAVI (Soil Adjusted Vegetation Index) were effective tools in obtaining canopy coverage and leaf chlorophyll content in soybean field. In addition, the RGB vegetation indices related to leaf color responded more sensitively to drought stress than those related to canopy coverage. The PLS-DA (Partial Squares-Discriminant Analysis) results showed that the separation of RGB vegetation indices was distinct by drought stress. The results, yet preliminary, display the potential of applying vegetation indices based on RGB images as a tool for monitoring crop environmental stress.
Although the rapid development of technology has led to a swift increase in the number of companies using social networking services (SNS), it will not be accurate to say that they have fully "utilized" the functionality of SNS simply by "using" these services. Therefore, this study aims to increase the convenience of using digital technology and help SNS users in extending the functionality of these services beyond their regular use and thus, revitalize the field by increasing the service providers' efficiency. In this study, the Facebook usage status of a graduate school newspaper from an undisclosed university in Seoul was analyzed from February to December, 2021 using the participant observation method. The results of the study revealed the following: First, it is necessary to diversify the subject and type of content to ensure a continuous supply of quality content; Second, there is a need to examine the user categories and characteristics by utilizing SNS functionalities such as, the target reports and insights, and based on this, supply content that meets the needs of the users; Third, to resolve the problem of low levels of user participation and an inactive Facebook account, it is necessary to mobilize new marketing tools like online events. The significance of this study is that it confronts the real problems faced by some companies that cannot keep pace with market changes in a digital environment, identifies failure factors, and proposes solutions to them.
With the advent of cryptocurrencies such as Bitcoin in 2009, the paradigm of money, a means of payment, has been changing significantly. And it has a great impact on our daily lives. Thus central banks have attempted various analyzes on the issuance and impact of digital currencies including electronic payments but a study on which issuance method is suitable is insufficient. In this study, the issuance of digital currency was analyzed compared to the electronic payments which are currently used. As a result, the account-based model did not show any significant differences from the current RTGS(real-time gross settlement systems) and retail payment systems. But the token-based model is expected that it can improve the efficiency of finance and induce technological innovation in the financial field. However, it was analyzed that this model would weaken the intermediary function of financial institutions such as loans due to the characteristics of digital signature technology. In addition, in order to protect consumers against security attacks such as hacking and phishing of CBDCs, legal and institutional supports similar to the current electronic payment method are required, and continuous technology development efforts are also required for the CBDC issuance model to maintain convenience and anonymity equivalent to cash.
This study aims to understand the characteristics of Korean language learners and propose appropriate teaching plans for them through a focus group interview with Korean language instructors who had experience in teaching Korean at university-attached institutions in Hong Kong. For this purpose, the investigator interviewed ten instructors who taught Korean for at least five years. Korean language learners in Hong Kong who were in their twenties, but there were diverse age groups, including those in their fifties or older. Their motivations for learning Korean included the Korean Wave and the influence of support from the Continuing Education Fund by the Hong Kong government. Korean language learners in Hong Kong were characterized by active learning desire and effort, continuous learning intention, passive performance in speaking, and sensitivity to the disclosure of private information. Based on these findings, the study proposes to devise teaching and learning methods based on various age groups in a class and teaching methods for speaking that reflect the characteristics of Korean language learners in Hong Kong to teach Korean more effectively. The study is significant as a field study that examines the learning motivations, learning attitudes, and difficulties with Korean study of Korean language learners based on an unprecedented survey of the characteristics of common local Korean learners in Hong Kong.
Journal of the Korea institute for structural maintenance and inspection
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v.26
no.4
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pp.20-29
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2022
The operational modal analysis (OMA) technique, which extracts the modal parameters of a structural system using ambient vibrations, has been actively developed as a field of structural health monitoring of cable-supported bridges. In this paper, the short and long-term modal parameters of a cable-stayed bridge were evaluated using the acceleration data obtained from the two ambient vibration tests (AVTs) and three years of continuous measurements. A total of 27 vertical modes and 1 lateral mode in the range 0.1 ~ 2.5 Hz were extracted from the high-resolution AVTs which were conducted in the 6th and 19th years after its completion. Existing OMA methods such as Peak-Picking (PP), Eigensystem Realization Algorithm with Data Correlation (ERADC), Frequency Domain Decomposition (FDD) and Time Domain Decomposition (TDD) were applied for modal parameters extraction, and it was confirmed that there was no significant difference between the applied methods. From the correlation analysis between long-term natural frequencies and environmental factors, it was confirmed that temperature change is the dominant factor influencing natural frequency fluctuations. It was revealed that the decreased natural frequencies of the bridge were not due to changes in structural performance and integrity, but to the environmental effects caused by the temperature difference between the two AVTs. In addition, when the TDD technique is applied, the accuracy of extracted mode shapes is improved by adding a proposed algorithm that normalizes the sequence so that the autocorrelations at zero lag equal 1.
With the recent development of deep convolutional neural network learning, deep learning techniques applied to single image super-resolution are showing good results. One of the existing deep learning-based super-resolution techniques is RDN(Residual Dense Network), in which the initial feature information is transmitted to the last layer using residual dense blocks, and subsequent layers are restored using input information of previous layers. However, if all hierarchical features are connected and learned and a large number of residual dense blocks are stacked, despite good performance, a large number of parameters and huge computational load are needed, so it takes a lot of time to learn a network and a slow processing speed, and it is not applicable to a mobile system. In this paper, we use the residual dense structure, which is a continuous memory structure that reuses previous information, and the residual dense channel attention block using the channel attention method that determines the importance according to the feature map of the image. We propose a method that can increase the depth to obtain a large receptive field and maintain a concise model at the same time. As a result of the experiment, the proposed network obtained PSNR as low as 0.205dB on average at 4× magnification compared to RDN, but about 1.8 times faster processing speed, about 10 times less number of parameters and about 1.74 times less computation.
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