Proceedings of the Korean Institute of Navigation and Port Research Conference
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2022.06a
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pp.108-109
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2022
In this study analyzed experimental data on noise interference caused by engine operating apply surface wave communication in the engine room. For the experiment, 7 areas of the engine room on 256 ton tug boat and measured noise during engine on off using signal analyzer for effect surface wave communication. In order to construct and actual communication network based on the analysis of the noise and confirm the characteristics of surface wave communication in the area made metal bulkheads the actual communication network installed communication equipment between three metal bulkheads and conducted a comparative experiment with wireless communication. The difference was confirmed. As a result, in the case of surface wave communication, there was no significant difference in the transmission and reception rates before and after engine operation in an environment with three bulkheads, but in the case of Wi-Fi using wireless, the performance deteriorated significantly during operation. was confirmed. As a result of analyzing the experimental data, it was confirmed that noise caused by engine operation affects wireless communication but does not affect surface wave communication. Therefore, even in the area with a lot of electromagnetic wave noise in the ship, when the surface wave communication system is configured using the ship's metal structure, it is possible to replace the wireless communication and furthermore, it is possible to apply the surface wave communication in the enclosed space and the engine room in the ship.
Kim, Jaeyoung;Jung, Dooyup;Jin, Young-Hyun;Kang, Byung-Goo
Informatization Policy
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v.30
no.4
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pp.40-61
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2023
The adoption of smart factories and smart manufacturing as strategies to enhance competitiveness and stimulate growth in the manufacturing sector is vital for a country's future competitiveness and industrial transformation. The government has consistently pursued smart manufacturing innovation policies starting with the Manufacturing Innovation 3.0 strategy in the Ministry of Industry. This study aims to identify policy areas for smart factories and smart manufacturing based on technical standards. Analyzing policy areas at the current stage where the establishment and support of domestic standards aligning with international technical standards are required is crucial. By prioritizing smart manufacturing process areas within the industry, policymakers can make well-informed decisions to advance smart manufacturing without blindly following international standardization in already well-established areas. To achieve this, the study utilizes a hierarchical analysis method including expert interviews and importance-performance analysis for the five major process areas. The findings underscore the importance of proactive participation in standardization for emerging technologies, such as data and security, instead of solely focusing on areas with extensive international standardization. Additionally, policymakers need to consider carbon emissions, energy costs, and global environmental challenges to address international trends in export and digital trade effectively.
As the development of drones and sensors accelerates, new services and values are created by fusing data acquired from various sensors mounted on drone. However, the construction of spatial information through data fusion is mainly constructed depending on the image, and the quality of data is determined according to the specification and performance of the hardware. In addition, it is difficult to utilize it in the actual field because expensive equipment is required to construct spatial information of high-quality. In this study, super-resolution was performed by applying deep learning to low-resolution images acquired through RGB and THM cameras mounted on a drone, and quantitative evaluation and feature point extraction were performed on the generated high-resolution images. As a result of the experiment, the high-resolution image generated by super-resolution was maintained the characteristics of the original image, and as the resolution was improved, more features could be extracted compared to the original image. Therefore, when generating a high-resolution image by applying a low-resolution image to an super-resolution deep learning model, it is judged to be a new method to construct spatial information of high-quality without being restricted by hardware.
The frequency response of a microphone, which indicates the frequency range that a microphone can output within the approved level, is one of the most significant standards used to measure the characteristics of a microphone. At present, conventional methods of measuring the frequency response are complicated and involve the use of expensive equipment. To complement the disadvantages, this paper suggests a new algorithm that can measure the frequency response of a microphone in a simple manner. The algorithm suggested in this paper generates the Optimized Aoshima's Time Stretched Pulse(OATSP) signal from a computer via a standard speaker and measures the impulse response of a microphone by convolution the inverse OATSP signal and the received by the microphone to be measured. Then, the frequency response of the microphone to be measured is calculated using the signals. The performance test for the algorithm suggested in the study was conducted through a comparative analysis of the frequency response data and the measures of frequency response of the microphone measured by the algorithm. It proved that the algorithm is suitable for measuring the frequency response of a microphone, and that despite a few errors they are all within the error tolerance.
By actively adopting technologies from the Fourth Industrial Revolution, the port industry is trending toward new types of ports, such as automated and smart ports. However, behind the development of these ports, there is an increasing risk of cyber security incidents and threats within ports and container terminals, including information leakage through cargo handling equipment and ransomware attacks leading to disruptions in terminal operations. Despite the necessity of research to enhance cyber security within ports, there is a lack of such studies in the domestic context. This study focuses on Busan Port, a representative port in South Korea that actively incorporates technology from the Fourth Industrial Revolution, in order to discover variables for improving cyber security in container terminals. The research results categorized factors for enhancing cyber security in Busan Port's container terminals into network construction and policy support, standardization of education and personnel training, and legal and regulatory factors. Subsequently, multiple regression analysis was conducted based on these factors, leading to the identification of detailed factors for securing and enhancing safety, reliability, performance, and satisfaction in Busan Port's container terminals. The significance of this study lies in providing direction for enhancing cyber security in Busan Port's container terminals and addressing the increasing incidents of cyber security attacks within ports and container terminals.
Nam, Hyeon-bin;Choi, Yo-seok;Kim, In-su;Kim, Gyung-jun;Park, Seong-su;Lee, Ja Hyun
Industry Promotion Research
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v.9
no.1
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pp.21-29
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2024
In the rapidly advancing information society, electronic devices, including smartphones and tablets, are increasingly digitized and equipped with high-performance features such as flexible displays. This study focused on optimizing the manufacturing process for Transparent Conductive Films (TCF) by using the cost-effective conductive polymer PEDOT and transparent substrate PET as alternatives to expensive materials in flexible display technology. The variables considered are production speed (m/min), coating maximum temperature (℃), and PEDOT supply speed (rpm), with surface resistivity (Ω/□) as the response parameter, using Response Surface Methodology (RSM). Optimization results indicate the ideal conditions for production: a speed of 22.16 m/min, coating temperature of 125.28℃, and PEDOT supply at 522.79 rpm. Statistical analysis validates the reliability of the results (F value: 18.37, P-value: < 0.0001, R2: 0.9430). Under optimal conditions, the predicted surface resistivity is 145.75 Ω/□, closely aligned with the experimental value of 142.97 Ω/□. Applying these findings to mass production processes is expected to enhance production yields and decrease defect rates compared to current practices. This research provides valuable insights for the advancement of flexible display manufacturing.
Jae-young Park;Jung Hwan Lee;Mo-Yeol Kang;Tae-Won Jang;Hyoung-Ryoul Kim;Se-Yeong Kim;Jongin Lee
Annals of Occupational and Environmental Medicine
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v.35
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pp.24.1-24.15
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2023
Background: The construction workers are vulnerable to fatigue due to high physical workload. This study aimed to investigate the relationship between overwork and heart rate in construction workers and propose a scheme to prevent overwork in advance. Methods: We measured the heart rates of construction workers at a construction site of a residential and commercial complex in Seoul from August to October 2021 and develop an index that monitors overwork in real-time. A total of 66 Korean workers participated in the study, wearing real-time heart rate monitoring equipment. The relative heart rate (RHR) was calculated using the minimum and maximum heart rates, and the maximum acceptable working time (MAWT) was estimated using RHR to calculate the workload. The overwork index (OI) was defined as the cumulative workload evaluated with the MAWT. An appropriate scenario line (PSL) was set as an index that can be compared to the OI to evaluate the degree of overwork in real-time. The excess overwork index (EOI) was evaluated in real-time during work performance using the difference between the OI and the PSL. The EOI value was used to perform receiver operating characteristic (ROC) curve analysis to find the optimal cut-off value for classification of overwork state. Results: Of the 60 participants analyzed, 28 (46.7%) were classified as the overwork group based on their RHR. ROC curve analysis showed that the EOI was a good predictor of overwork, with an area under the curve of 0.824. The optimal cut-off values ranged from 21.8% to 24.0% depending on the method used to determine the cut-off point. Conclusion: The EOI showed promising results as a predictive tool to assess overwork in real-time using heart rate monitoring and calculation through MAWT. Further research is needed to assess physical workload accurately and determine cut-off values across industries.
Korea Pathfinder Lunar Orbiter (KPLO), launched in August 2022, is successfully carrying out its mission. Korea's lunar lander and rover programs are expected to proceed in the future. To successfully carry out the mission after the lunar lander has landed on the surface, the performance of the equipment to be mounted should be checked in a laboratory environment similar to the Moon. Scientists and engineers of several countries, including the United States and China, use lunar soil simulant which is developed to resemble lunar soil for simulating the surface of the lunar landing site. Several lunar probe landing sites are being discussed in Korea, and lunar soil simulants such as Korea Hanyang Lunar Simulant-1 (KOHLS-1), Korea Aerospace University Mechanical Lunar Simulants (KAUMLS), and Korea Lunar Simulant-1 (KLS-1), which are similar to the characteristics of lunar mare soil, have been developed. However, those simulants are not useful if the landing site is chosen as a highland area. In this study, we introduce the process of developing KIGAM-L1, a lunar highland soil simulant similar to the chemical composition of the Apollo 16 lunar soil sample and the particle size distribution of lunar soil sample 60500-1, in case the lunar lander lands at highland area.
The purpose of this study is to explore the experiences of Science Chief Teachers in schools, focusing on the specific activities in which they engage during the school year as a part of the science curriculum in the school. To do so, five research participants were selected who were in charge of the activities of the Science Chief Teacher in elementary schools. After the interviews, their activities and roles were categorized into "planning and implementation" and "management and supplementation." In addition, the research participants were asked to bring documents they had drafted and provide information about accomplishments related to science contests, lists of materials and equipment used in science labs, and other materials to be used as reference data for the research. As prompted by the research, the category of "planning and implementation," which represented the activities conducted by the Science Chief Teachers, was further classified into "operation of the intramural events for the Month of Science at the beginning of the school year," "participation in contests sponsored by the Office of Education in accordance with the results of the intramural events," " the operation of the science club in school," and "preparation for the end of the year evaluation of the science education performance." As for the category of "management and supplementation," it was further classified into "constant management and improvement of the science lab," "maintenance of the relationship with the public service officials present at science lab," and "management of other matters related to the science education." Through this study, it was possible to look into the activities of the Science Chief Teachers who supported the smooth progress of science education in schools. This study will provide implications for improving the work efficiency of the Chief Science Teachers and indicate the difficulties expected in the future.
In this study, AHP-based production management job training was developed for MPE companies in the aviation logistics industry. The AHP model was designed with upper and lower classes. Purchase management competency, material management competency, process management competency, and SCM competency were selected as factors of the upper class of production management job training. Lower class evaluation factors were selected for each upper class. As a result of AHP analysis, the relative importance of the upper class evaluation factors was found in the order of SCM competency (0.322), process management competency (0.314), material management competency (0.201), and purchase management competency (0.163). Among the upper classes, it was analyzed that the importance of SCM competency and process management competency was high. The final priority of evaluation factors for the development of the production management curriculum of MPE companies in the aviation logistics industry was analyzed as follows. First, supply chain performance management, which is the lower layer of SCM competency, was analyzed as the top priority factor, and the priorities of evaluation factors were derived such as facility preservation management, which is the lower layer of SCM competency, supply chain production operation, which is the lower layer of SCM competency, process quality management, which is the lower layer of SCM competency, supply chain transportation management, and supply chain supply plan, which are the lower layers of SCM competency
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