• The Journal of the Acoustical Society of Korea
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• v.40 no.6
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• pp.555-565
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• 2021

The goal of this study is to improve flow and noise performances of existing backward-curved blade centrifugal fan system used for circulating cold air in a refrigerator freezer by optimally designing airfoil shape. The unique characteristics of the system is to drive cold airflow with two volute tongues in combination with duct system in a back side of a refrigerator without scroll housing generally used in a typical centrifugal fan system. First, flow and noise performances of existing fan system were evaluated experimentally. A P-Q curve was obtained using a fan performance tester in the flow experiment, and noise spectrum was measured in an anechoic chamber in the noise experiment. Then, flow characteristics were numerically analyzed by solving the three-dimensional unsteady Navier-Stokes equations and noise analysis was performed by solving the Ffowcs Williams and Hawkins equation with input from the flow simulation results. The validity of numerical results was confirmed by comparing them with the measured ones. Based on the verified numerical method, blade inlet and outlet angles were optimized for maximum flow rate using the two-factor central composite design of the response surface method. Finally, the flow and noise performances of a prototype manufactured with the optimum design were experimentally evaluated, which showed the improvement in flow and noise performance.

• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.87-95
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• 2022

Recently, with the development of smart technology, in medical information platform, patient's biometric data is measured in real time and accumulated into database, and it is possible to determine the patient's emergency situations. Medical staff can easily access patient information after simple authentication using a mobile terminal. However, in accessing medical information using the mobile terminal, it is necessary to study authentication in consideration of the patient situations and mobile terminal. In this paper, we studied on medical information platforms based on big data processing and edge computing for supporting automatic authentication in emergency situations. The automatic authentication system that we had studied is an authentication system that simultaneously performs user authentication and mobile terminal authentication in emergency situations, and grants upper-level access rights to certified medical staff and mobile terminal. Big data processing and analysis techniques were applied to the proposed platform in order to determine emergency situations in consideration of patient conditions such as high blood pressure and diabetes. To quickly determine the patient's emergency situations, edge computing was placed in front of the medical information server so that the edge computing determine patient's situations instead of the medical information server. The medical information server derived emergency situation decision values using the input patient's information and accumulated biometric data, and transmit them to the edge computing to determine patient-customized emergency situation. In conclusion, the proposed medical information platform considers the patient's conditions and determine quick emergency situations through big data processing and edge computing, and enables rapid authentication in emergency situations through automatic authentication, and protects patient's information by granting access rights according to the patient situations and the role of the medical staff.

• Journal of Internet Computing and Services
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• v.22 no.6
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• pp.141-150
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• 2021

Based on Artificial Intelligence technology, AI-enabled warfare is expected to become the main issue in the future warfare. Natural language processing technology is a core technology of AI technology, and it can significantly contribute to reducing the information burden of underrstanidng reports, information objects and intelligences written in natural language by commanders and staff. In this paper, we propose a Language model-based Multi-source Information Integration (LAMII) framework to reduce the information overload of commanders and support rapid decision-making. The proposed LAMII framework consists of the key steps of representation learning based on language models in self-supervsied way and document integration using autoencoders. In the first step, representation learning that can identify the similar relationship between two heterogeneous sentences is performed using the self-supervised learning technique. In the second step, using the learned model, documents that implies similar contents or topics from multiple sources are found and integrated. At this time, the autoencoder is used to measure the information redundancy of the sentences in order to remove the duplicate sentences. In order to prove the superiority of this paper, we conducted comparison experiments using the language models and the benchmark sets used to evaluate their performance. As a result of the experiment, it was demonstrated that the proposed LAMII framework can effectively predict the similar relationship between heterogeneous sentence compared to other language models.

• Korean Journal of Construction Engineering and Management
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• v.23 no.3
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• pp.74-82
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• 2022

With the introduction of proptech, this study aims to find out the changes and necessity of introducing blockchain technology, one of the most popular technologies, in real estate electronic transactions. In addition, it is intended to develop evaluation indicators that classify newly created values within real estate electronic transactions and calculate the relative importance of each value area through technology application. To this end, the value that can be created when applying blockchain technology to real estate electronic transactions was classified according to the hierarchy, and considering that the evaluation criteria are complex and the importance can be measured differently depending on various factors, an analysis was conducted according to the AHP method for experts in practical and academic fields. As a result of the analysis, general value showed the highest importance in the first dimension, and digitalization of real estate information showed the highest importance in the second dimension.

• Journal of Korean Society of Forest Science
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• v.111 no.3
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• pp.435-449
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• 2022

Forest canopy height is an indispensable vertical structure parameter that can be used for understanding forest biomass and carbon storage as well as for managing a sustainable forest ecosystem. Plot-based field surveys, such as the national forest inventory, have been conducted to provide estimates of the forest canopy height. However, the comprehensive nationwide field monitoring of forest canopy height has been limited by its cost, lack of spatial coverage, and the inaccessibility of some forested areas. These issues can be addressed by remote sensing technology, which has gained popularity as a means to obtain detailed 2- and 3-dimensional measurements of the structure of the canopy at multiple scales. Here, we reviewed both international and domestic studies that have used remote sensing technology approaches to estimate the forest canopy height. We categorized and examined previous approaches as: 1) LiDAR approach, 2) Stereo or SAR image-based point clouds approach, and 3) combination approach of remote sensing data. We also reviewed upscaling approaches of utilizing remote sensing data to generate a continuous map of canopy height across large areas. Finally, we provided suggestions for further advancement of the Korean forest canopy height estimation system through the use of various remote sensing technologies.

• Journal of Practical Engineering Education
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• v.14 no.2
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• pp.267-277
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• 2022

Achievement at university is recognized in a comprehensive sense as the level of qualitative change and development that students have embodied as a result of their experience in university education. Therefore, the academic achievement of university students will be given meaning in cooperation with the historical and social demands for diverse human resources such as creativity, leadership, and global ability, but it is practically an indicator of the outcome of university education. Measurement of academic achievement by such credits involves many problems, but in particular, standardization of academic achievement by credits based on evaluation methods, contents, and university rankings is a very difficult problem. In this study, we present a model that uses machine learning techniques to predict whether or not academic achievement is excellent for D-University graduates. The variables used were analyzed using up to 96 personal information and bachelor's information such as graduation year, department number, department name, etc., but when establishing a future education course, only the data after enrollment works effectively. Therefore, the items to be analyzed are limited to the recommended ability to improve the academic achievement of the department/student. In this research, we implemented an academic achievement prediction model through analysis of core abilities that reflect the philosophy, goals, human resources image, and utilized machine learning to affect the impact of the introduction of the prediction model on academic achievement. We plan to apply the results of future research to the establishment of curriculum and student guidance conducted in the department to establish a basis for improving academic achievement.

• The Journal of the Acoustical Society of Korea
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• v.42 no.1
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• pp.7-15
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• 2023

Recently, as interest in air quality in vehicles increases, the use of fine dust detection sensors for air quality measurement is becoming common. An axial-flow fan is inserted in the fine dust sensor installed in the air conditioning system in the vehicle to prevent dust from sinking directly on the sensor. When the sensor operates, the flow noise caused by the rotation of the axial-flow fan acts as a major noise source of the fine dust sensor. flow noise is recognized as one of the product competitiveness of fine dust sensors. In this study, the noise was gradually reduced at the same flow rate by improving the flow performance of the small axial flow fan. First, a virtual fan performance tester consisting of about 20 million grids was developed to analyze the aerodynamic performance of the target small axial-flow fan. In addition, the flow field was simulated by using compressible Large Eddy Simulation for direct computation of flow noise as well as high-accurate prediction of flow rate. The validity of numerical method are confirmed through the comparison of predicted results with experimental ones. After the effects of pitch angle on flow performance were analyzed using the verified numerical method, the pitch angle was determined to maximize the flow rate. It was found that the flow rate was increased by 8.1 % and noise was reduced by 0.8 dBA when the axial-flow fan with the optimum pitch angle was used.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.4
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• pp.274-284
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• 2022

To use kenaf (Hibiscus cannabinus L.) as a fiber and livestock feed, a high-yielding variety needs to be identified. For this, accurate phenotyping of plant height is required for this breeding purpose due to the strong relationship between plant height and yield. Plant height can be estimated using RGB images from unmanned aerial vehicles (UAV-RGB) and photogrammetry based on Structure from Motion (SfM) algorithms. In kenaf, accurate measurement of height is limited because kenaf stems have high flexibility and its height is easily affected by wind, growing up to 3 ~ 4 m. Therefore, we aimed to identify a method suitable for the accurate estimation of plant height of kenaf and investigate the feasibility of using the UAV-RGB-derived plant height map. Height estimation derived from UAV-RGB was improved using multi-point calibration against the five different wooden structures with known heights (30, 60, 90, 120, and 150 cm). Using the proposed method, we analyzed the variation in temporal height of 23 kenaf cultivars. Our results demontrated that the actual and estimated heights were reliably comparable with the coefficient of determination (R²) of 0.80 and a slope of 0.94. This method enabled the effective identification of cultivars with significantly different heights at each growth stages.

• 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 Korean Society of Forest Science
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• v.112 no.3
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• pp.382-392
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• 2023

Recent reports have indicated a rapid increase in the frequency of sediment disasters due to climate change and other changes in the geological environment. Given this alarming situation and the recent increase in the frequency of land creep in Korea, systematic and efficient recovery and management of land creep areas is essential. The purpose of this study is to identify disaster vulnerability by conducting a physical exploration of land creep in San 4-1, Jayeon-ri, Gaegun-myeon, Yangpyeong-gun, Gyeonggi-do, and examine stability by identifying the overall geological structure of the affected ground. In addition, drilling surveys are conducted to verify the reliability of the measured data. The results of the study reveal that low specific resistance abnormalities are distributed in the upper part of the soil layer and weathering zone and that this section is a 50-120 m exploration line. It is also confirmed to be a low-hardness ground area where tensile cracks are observed. Therefore, there is a need for research focused on developing measures to reduce economic and social damage within the domestic context by continuously monitoring indicators of land creep and identifying land creep risks.