• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.701-710
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• 2024

This study conducted a survey of companies in the aviation, drone, and Urban Air Mobility (UAM) sectors to analyze the educational and workforce needs, identifying essential competencies and technical training required. The study also proposed potential areas for collaboration between universities and industry regarding educational methods. Key findings and implications of the survey were derived. The results indicated that the most critical consideration for hiring was job-specific skills in the respective field. The most essential quality for workforce training was identified as enhancing the ability to use various equipment and software related to the major field. In the UAM sector, there was a high demand for personnel and education related to aircraft and components, with the highest demand being for lightweight manufacturing technology for aircraft. This study can serve as foundational data for addressing the educational needs in this field.

• Korean Journal of Agricultural Science
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• v.43 no.4
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• pp.650-655
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• 2016

Gears are components of transmission which transmit the power of an engine to a machine and offer numerous speed ratios, a compact structure, and high efficiency of power transmission. Gear train design in the automotive industry uses simulation software. However, PTO (Power Take-Off) gear design for agricultural applications uses the empirical method because of the wide range of load fluctuations in agricultural fields. The PTO is an important part of agricultural tractors which transmits the power to various tractor implements. Therefore, a simulation was essential to the optimal design of the PTO. When the PTO gear is optimally designed, there are many advantages such as low cost, reduced size, and light weight. In this study, we conducted the bending and contact safety factor simulation for the PTO gear of an agricultural tractor. The bending and contact safety factors were calculated on ISO 6336 : 2006 by decreasing the face widths of the PTO pinion and wheel gear from 18 mm at an interval of 1 mm. The safety factor of the PTO gear decreased as the face width decreased. The contact safety factors of the pinion and wheel gear were 1.45 and 1.53, respectively, when the face width was 18 mm. The simulation results showed that the face width of the PTO gear should be greater than 9 mm to maintain the bending and contact safety factors higher than 1. It would be possible to reduce the weight of the PTO gear for different uses and working conditions. This study suggests that the possibility of designing an optimal PTO gear decreases as its face width decreases.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.6
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• pp.611-618
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• 2020

In this paper, we propose a design and implementation method of speed quiz content that can be driven by a social robot capable of interacting with humans, and a method of developing an intelligent module necessary for implementation. In addition, we propose a method of implementing speed quiz content through the process of constructing a map by arranging and connecting intelligent module blocks. Recently, software education has become mandatory and interest in programming is increasing. However, programming is difficult for students without basic knowledge of programming languages to directly access, and interest in block-type programming platforms suitable for beginners is growing. The block-type programming platform used in this paper is a platform that supports immediate and intuitive programming by supporting interactions between humans and robots. In this paper, the intelligent module implemented for the speed quiz content was used by blocking it within a block-type programming platform. In order to implement the scenario of the speed quiz content proposed in this paper, we implement a total of three image-based artificial intelligence modules. In addition to the intelligent module, various functional blocks were placed to implement the speed quiz content. In this paper, we propose a method of designing a speed quiz content scenario and a method of implementing an intelligent module for speed quiz content.

• Journal of Korean Society for Atmospheric Environment
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• v.22 no.5
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• pp.661-678
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• 2006

Products developed in this research is a software which can transfer the type of shape(.shp) into the type of ascii using the land cover data and the topography data in the metropolitan area of Seoul. In addition, it can calculate the $CO_2$ flux according to distribution of plants within the land cover data. The $CO_2$ flux is calculated by the experimental equation which is compose of the meteorological parameters such as the solar radiation and the air temperature. The net flux was shown in about $-19ton/km^2$ by removing $CO_2$ through the photosynthesis during daytime, and in 2 ton/km2 by producing it through the respiration during nighttime on 10 August 2004, the maximum day of air temperature during the period of 3yr(2001 to 2004), in the metropolitan area of Seoul. Spatial distribution of the air temperature and the wind field is simulated by substituting the middle classification of the land cover map data, upgraded by the Korean Ministry of Environment(KME), for the land-use data of the United States Geological Survey(USGS) within the Meteorological Mesoscale Model Version 5(MM5) on 10 August 2006 in the metropolitan area of Seoul. Difference of the air temperature between both data was shown in the maximum range of $-2^{\circ}C\;to\;2.9^{\circ}C$, and the air temperature due to the land use data of KME was higher than that of USGS in average $0.4^{\circ}C$. Also, those of wind vectors were meanly lower than that of USGS in daytime and nighttime. Furthermore, the hourly time series of Volatile Organic Components(VOCs) is calculated by using the Biosphere Emission and Interaction System Version 2(BEIS2) including the new land cover data and the meteorological parameters such as the air temperature and so]ar insolation. It is possible to calculate the concentration of ozone due to the biogenic emission of VOCs.

• Korean Journal of Remote Sensing
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• v.21 no.2
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• pp.121-133
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• 2005

Texture imaging, which means texture image creation by co-occurrence relation, has been known as one of the useful image analysis methodologies. For this purpose, most commercial remote sensing software provides texture analysis function named GLCM (Grey Level Co-occurrence Matrix). In this study, texture-imaging program based on GLCM algorithm is newly implemented. As well, texture imaging modules for GLDV (Grey Level Difference Vector) are contained in this program. As for GLCM/GLDV Texture imaging parameters, it composed of six types of second order texture functions such as Homogeneity, Dissimilarity, Energy, Entropy, Angular Second Moment, and Contrast. As for co-occurrence directionality in GLCM/GLDV, two direction modes such as Omni-mode and Circular mode newly implemented in this program are provided with basic eight-direction mode. Omni-mode is to compute all direction to avoid directionality complexity in the practical level, and circular direction is to compute texture parameters by circular direction surrounding a target pixel in a kernel. At the second phase of this study, some case studies with artificial image and actual satellite imagery are carried out to analyze texture images in different parameters and modes by correlation matrix analysis. It is concluded that selection of texture parameters and modes is the critical issues in an application based on texture image fusion.

• Journal of Service Research and Studies
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• v.14 no.1
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• pp.1-12
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• 2024

As the service robot market grows among the food technology industry, the quality of robot service that affects consumer behavioral intentions in the restaurant industry has become important. Serving robots, which are common in restaurants, reduce employee work through order and delivery, but because they do not respond to service failures, they increase customer dissatisfaction as well as increase employee work. In order to improve the quality of service beyond the simple function of receiving and serving orders, functions of recovery effort, fairness, empathy, responsiveness, and certainty of the process after service failure, such as serving employees, are also required. Accordingly, we assumed the type of failure of restaurant serving service as two internal and external factors, and developed a serving robot with a vocational ethics module to respond with a professional ethical attitude when the restaurant serving service fails. At this time, the expression and action of the serving robot were developed by adding a failure mode reflecting failure recovery efforts and empathy to the normal service mode. And by recruiting college students, we tested whether the service robot's response to two types of service failures had a significant effect on evaluating the robot. Participants responded that they were more uncomfortable with service failures caused by other customers' mistakes than robot mistakes, and that the serving robot's professional ethical empathy and response were appropriate. In addition, unlike the robot's favorability, the evaluation of the safety of the robot had a significant difference depending on whether or not a professional ethical empathy module was installed. A professional ethical empathy response module for natural service failure recovery using generative artificial intelligence should be developed and mounted, and the domestic serving robot industry and market are expected to grow more rapidly if the Korean serving robot certification system is introduced.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.1-9
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• 2020

In highly complex EPC(engineering, procurement, construction)-based manufacturing processes such as shipbuilding and marine plants, it is essential to prepare a way to enable organic working at the site referring to each other's detailed working data for collaboration between partner companies. However, companies cannot share the progress of the sites including working information in real-time due to the use of SW unique to each company and the complex site management system. As a result, the construction process is delayed, and resources are used inefficiently. This study developed a neutral data generation algorithm that can apply the working information in various file formats to a collaborative manufacturing process. In addition, this study verified the accuracy of the algorithm by applying the developed algorithm to the manufacturing process of piping in shipbuilding and marine plants, developing the SW for visualization of working information using the generated neutral data, and comparing the coordinate, shape & dimension and the kind, number, and spec. of BOM. The result confirmed that the accuracy of the coordinate of the neutral data was 99%, and that of the shape & dimension of the neutral data and BOM Spec. was both 100%. It is thought that this study can be used for overcoming the restrictions in information sharing due to the development of informatization at companies and maximizing the share of working file information in a complex manufacturing process.

• Fire Science and Engineering
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• v.34 no.3
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• pp.67-75
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• 2020

In this study, the risk of heat generation due to normal and overload currents that vary with the abnormal loosening angle of wire-connecting bolts were identified. The risks were analyzed based on the thermal characteristics to minimize the carbonization accidents of terminal blocks inside distribution panels typically used in industrial sites. We applied a method for measuring the heating temperature and temperature variations in the terminal blocks in real-time by installing a resistance temperature detector sensor board in the terminal block. The experimental results showed that the terminal block model with a low-rated current exhibited a higher heating temperature, thus, confirming the need to select the terminal block capacity based on load currents. Additionally, the higher the rated current of the terminal block with a high-rated current and the higher the degree of loosening, the faster the carbonization point. Such heating temperature monitoring enabled real-time thermal temperature measurement and a step-by-step risk level setting through thermal analysis. The results of the measurement and analysis of carbonization risks can provide a theoretical basis for further research regarding the risk of fire due to carbonization. Furthermore, the deterioration measurement method using the temperature sensor board developed in this study is widely applicable to prevent fires caused by poor electrical contact as well as risk-level management.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.25-40
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• 2019

Many companies are executing big data analysis and utilization projects to legitimize the development of new business areas or conversion of management or technical strategies. In Korea and abroad, however, such projects are failing because they are not completed within specified deadlines, which is not unrelated to the current situation in which the knowledge base for big data project risk management from an engineering perspective is grossly lacking. As such, the current study analyzes the risk factors of big data implementation and utilization projects, in addition to finding risk factors that are highly important. To achieve this end, the study extracts project risk factors via literature review, after which they are grouped using affinity methodology and sifted through expert surveys. The deduced risk factors are structuralize using factor analysis to develop a table that categorizes various types of big data project risk factors. The current study is significant that in it provides a basis for developing basic control indicators related to risk identification, risk assessment, and risk analysis. The findings from the study contribute greatly to the success of big data projects, by providing theoretical basis regarding efficient big data project risk management.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.45-55
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• 2021

This paper has proposed an algorithm that detecting for dense small vehicle in large image efficiently. It is consisted of two Ensemble Deep-Learning Network algorithms based on Coarse to Fine method. The system can detect vehicle exactly on selected sub image. In the Coarse step, it can make Voting Space using the result of various Deep-Learning Network individually. To select sub-region, it makes Voting Map by to combine each Voting Space. In the Fine step, the sub-region selected in the Coarse step is transferred to final Deep-Learning Network. The sub-region can be defined by using dynamic windows. In this paper, pre-defined mapping table has used to define dynamic windows for perspective road image. Identity judgment of vehicle moving on each sub-region is determined by closest center point of bottom of the detected vehicle's box information. And it is tracked by vehicle's box information on the continuous images. The proposed algorithm has evaluated for performance of detection and cost in real time using day and night images captured by CCTV on the road.