• International Journal of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.250-260
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• 2023

In this paper, we designed a IoT(Internet of Things) sensor block embedded lightweight house deck structures that can be implemented using Carbon Fiber Reinforced Polymer(CFRP). Deck-Sensor interconnection interface block via IoT connectivity Hub that can mount external environmental sensors such as fire sensors on the Deck body itself was also proposed. Additionally we described the configuration of devices for data acquisition and analysis based on IoT environmental detection sensors that can be commonly installed and used on these deck bodies. On the other hand, received sensing data based monitoring user interface(UI) also developed and used for sensing data analysis for remote monitoring center. Through the implementation of such IoT-based sensor data transmission and collection analysis devices and UI software, this paper confirmed the availability of CFRP based lightweight House deck structure and possibility of CFRP deck-based IoT sensor data networking and analysis functions.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.1
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• pp.9-15
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• 2024

In this study, the mechanical properties of friction stir welded A6061-T6 were evaluated. This material is used as a battery pack case material for electric vehicles. The Vickers hardness, tensile strength, and yield stress of the friction stir welding (FSW) specimen were all smaller than those of the base metal specimen. As the heat input increased, the nugget zone widened, and there were differences in hardness according to the base metal zone, heat affected zone, thermal-mechanical affected zone, and nugget zone. Mechanical properties were not proportional to heat input, and the thermal-mechanical affected zone on the advancing side was the smallest in all conditions. This is because the material flow speed increased on the advancing side, where the welding direction and the tool rotation direction were the same, forming a distinct boundary with mechanical deformation.

• Design & Manufacturing
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• v.18 no.2
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• pp.51-56
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• 2024

In this study, a tool was developed for analyzing production lead time in turning operations. It is expected to help to reduce machining time and to identify, for example, tool change intervals. The tool was developed using Visual Basic.Net and features a user-friendly graphical user interface (GUI) that allows users to easily input cutting conditions and calculate the usage time and feeding distance for each cutting tool based on a G-code program. Object-oriented programming techniques were also used to encapsulate and classify complex logic, thereby efficiently organizing and managing the functions and data structures of this analysis tool. The analysis tool provides various outputs. It calculates the use time of each detailed process of the turning operation, the use time of each tool, the use time of each type of feeding, and also generates the data needed for cutting time analysis, which can be visualized in charts. The analysis tool developed in this study is expected to significantly contribute to improving the efficiency of manufacturing processes and increasing productivity, particularly, in the manufacturing of components requiring massive material removal, such as aircraft parts.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.5
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• pp.325-330
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• 2023

This paper proposes to apply machine learning to the process of predicting the slab thickness based on the structural analysis results or experience and subjectivity of engineers in the design of bridge data construction to enable digital-based decision-making. This study aims to build a reliable design environment by utilizing machine learning techniques to provide guide values to engineers in addition to structural analysis for slab thickness selection. Based on girder bridges, which account for the largest proportion of bridge data, a prediction model process for predicting slab thickness among superstructures was defined. Various machine learning models (Linear Regress, Decision Tree, Random Forest, and Muliti-layer Perceptron) were competed for each process to produce the prediction value for each process, and the optimal model was derived. Through this study, the applicability of machine learning techniques was confirmed in areas where slab thickness was predicted only through existing structural analysis, and an accuracy of 95.4% was also obtained. models can be utilized in a more reliable construction environment if the accuracy of the prediction model is improved by expanding the process

• Korea Journal of Hospital Management
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• v.22 no.4
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• pp.113-122
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• 2017

The purpose of the study was to investigate the patient, disease and hospital characteristics which affect treatment result and early complication for inpatients with psychiatric comorbidity. We analyzed data on 19,806 patients of the Korea Centers for Disease Control and Prevention from 2012 to 2014, Korea National Hospital discharge in-depth data. Frequency, chi-square and logistic regression analysis was performed, using STATA 12.0. According to logistic regression analysis, gender(Odds ratio(OR)=0.776, 95% confidence interval(CI)=0.686-0.878), insurance type(OR=0.853, CI=0.731-0.995), operation(OR=0.424, CI=0.350-0.513), disposition(OR= 39.307, CI=34.394-44.923), beds(300-499, OR=0.470, CI=0.377-0.585; 500-999, OR=0.462, CI=0.395-0.541; 1000 over, OR=0.598, CI=0.480-0.745) were significant predictors of treatment result. And insurance type(OR=1.527, CI=1.241-1.879), CCI(3 over, OR=1.865, CI=1.534-2.266), operation(OR=5.399, CI=4.562-6.389), disposition(OR=1.279, CI=1.013-1.614), district(Metropolitan city, OR=0.519, CI=0.407-0.661; Non-metropolitan OR=0.469, CI=0.383-0.574), beds(500-999, OR=2.799, CI=1.986-3.944; 1000 over, OR=2.109, CI=1.429-3.113) were significant predictors of early complication. This research would be used as a basic data of high quality of medical care and efficient resource utilization in order to detect and minimize the negative medical treatment results of inpatients with psychiatric comorbidity.

• Journal of Advanced Navigation Technology
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• v.25 no.1
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• pp.60-67
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• 2021

Countries around the world, including the U.S. are actively researching to commercialize the logistics services using drones. In Korea, telecommunications companies as well as logistics companies are researching and developing the logistics services using drones. However, there's an environmental difference for last-mile delivery between the U.S. and Korea. In Korea, more than 77% of the population lives in apartments and the population density is the 4th highest in the world. Accordingly, in terms of the logistics services using drones, it is necessary to research it with the Korean suitable environment. In this paper, a precision positioning method of drone last-mile delivery in urban areas using short-range wireless communication and barometer is proposed. The experiment results show that the proposed method can detect a window within 2.5 meters. It is expected that the proposed method will help improve the logistics services using drones in urban areas.

• Journal of the Economic Geographical Society of Korea
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• v.25 no.1
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• pp.171-181
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• 2022

The real estate price index plays key roles as quantitative data in real estate market analysis. International organizations including OECD publish the real estate price indexes by country, and the Korea Real Estate Board announces metropolitan-level and municipal-level indexes. However, when the index is set on the smaller spatial unit level than metropolitan and municipal-level, problems occur: missing values. As the spatial scope is narrowed down, there are cases where there are few or no transactions depending on the unit period, which lead index calculation difficult or even impossible. This study suggests a supervised learning-based machine learning model to compensate for missing values that may occur due to no transaction in a specific range and period. The models proposed in our research verify the accuracy of predicting the existing values and missing values.

• Journal of Welding and Joining
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• v.32 no.4
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• pp.39-45
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• 2014

Today, the development of digitized information media and info-communications are bringing many changes. Due to the development of IT thechnology, we can learn wherever, whenever, regardless of time and place. Machine drawing subject is a very important in mechanical engineering course, but it's studyed only basic theory in a short period, average 1~2weeks. So that, students think that the mechanical drawing is of minor importance. Such ideas make them difficult to impove sense of space in isometric drawing and drawing skill. Therefore, in this paper, augmented reality-based contents through the system, Mechanical Drawing of education to meet the effectiveness and satisfaction, student learning can be spontaneously it was construct self-system. And, Theoretical part of the Mechanical Drawing is proposed ensure more efficient and easier training. In this paper, we were test operation for user effectualness of proposed service at Korea Polytechnics Colleges a industrial facilities management in Daegu. Target user are 66 students, and The students were divided into experimental group and comparison group. Experimental results, experimental group was able to do systematically experience many Projection Drawing and Pictorial Drawing in short schooltime. And, The test operation results showed that have the possibility to meet education effectiveness and user satisfaction in this augmented reality-based contents system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.11
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• pp.5416-5426
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• 2012

This study uses the algorithm which estimates the magnetic flux using different models in the low speed driving area and the high speed driving area by the voltage-current model synthesis magnetic flux Estimator and, from this result, estimates the magnetic flux angle to achieve the stable speed control through all the areas from the low speed to the high speed drive. In particular, the current change and the magnetic flux change under variable load were estimated in real time in the low speed area and this made the control characteristic improved in the low speed area. According to this, even under variable load, the more stable simulation and experiment could have been completed using PI current controller and PI flux controller in all the areas. As a result, the outstanding speed control characteristic has been achieved.

• Journal of Internet of Things and Convergence
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• v.3 no.2
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• pp.33-39
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• 2017

The purpose of this study is to analyze the characteristics of talents required in electronic companies in the 4th industrial revolution. we conducted a network analysis on the key talent of the companies presented in over 100 job announcements to companies in the electronics industry. The results of the study are as follows. First, electronic companies showed the most favored creative talents, preferring collaborative talent and challenging talent. Second, looking at the core definitions of talent, change, response, problem solving, performance creation, communication, challenge, professionalism, enthusiasm, development, aggressiveness and spontaneity were used. In other words, key keywords emerging from the 4^th industrial revolution were being used continuously. Third, in the Centrality analysis, talented people who emphasize humanity also appeared. Based on the study, it suggested that manpower training of the 4^th Industrial Revolution.