• The Journal of the Korea Contents Association
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• v.20 no.12
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• pp.671-680
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• 2020

Today, if you don't reflect trends in developing new content crafts, you can't succeed in marketing. This is because the trend is the driving force that leads to the needs of consumers that come and go temporarily. The current market is changing and wants new lifestyle trends. As a trend of such latent desire, the purpose is to develop high-value-added interior vases using rice cake patterns and ceramic complexes. In the manufacturing method, the first rice cake patterns writing tool is stamped at a different angle from the top of the toremi board (a new term created above) written in the process of the pot work. A cylinder is made of a second potter's wheel, and after the outer wall is double-flavored, the cylinder is quickly rotated to be extended by pushing it from inside to outside by hand. The purpose of this vase is to develop a decorative vase with high added value by experimenting with various geometric patterns that are dismantled vertically and horizontally at a high speed with the static rice cake pattern stamped on the third, and then utilizing the various rice cake patterns developed in this way as the shape of a jar.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.3
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• pp.60-67
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• 2021

Recently, research attention has been focused on vibration-free vehicles to transport small numbers of expensive electronic products. Vibration-free vehicles can be used to transport expensive test equipment or semiconductors, mainly produced in the domestic IT industry, and can serve as a readily available transportation system for short driving distances due to the increased efficiency on narrow national highways. This study was aimed at developing a Z-Spring to minimize the vibration by installing an air spring instead of the plate spring applied to conventional freight cars and to prevent the damage of the loaded cargo from the shock occurring during movement. The mechanical properties (elastic modulus, tensile strength, and shear strength) of carbon fiber (CF) and glass fiber (GF) prepreg were derived, and ANSYS ACP PrepPost analyses were performed. It was observed that in the case of hybrid composites, the total deformation and equivalent stress are higher than that of CFRP; however, in terms of the unit cost, the hybrid Z-Spring is more inexpensive and durable compared to the GF.

• Journal of Advanced Navigation Technology
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• v.24 no.6
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• pp.521-526
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• 2020

In this paper, we propose a design method and process for hybrid V2X communication platform that combines WAVE communication and LTE-V2X communication which are C-ITS communication protocols for vehicle environments and Legacy LTE communication which is a commercial mobile communication for evaluating the autonomous platooning platform of commercial vehicles. For a safe and efficient autonomous platooning platform, an low-latency communication function based on C-ITS communication is required, and to control it, commercial communication functions such as Legacy LTE, which can be connected at all times, are required. In order to evaluate such a system, the evaluation equipment must have the same level of communication performance or higher. The main design contents presented in this paper will be applied to the implementation of hybrid V2X terminals for functional evaluation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.4
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• pp.95-105
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• 2021

Road surface damage detection is essential for a comfortable driving environment and the prevention of safety accidents. Road management institutes are using automated technology-based inspection equipment and systems. As one of these automation technologies, a sensor to detect road surface damage plays an important role. For this purpose, several studies on sensors using deep learning have been conducted in recent years. Road images and label images are needed to develop such deep learning algorithms. On the other hand, considerable time and labor will be needed to secure label images. In this paper, the adversarial learning method, one of the semi-supervised learning techniques, was proposed to solve this problem. For its implementation, a lightweight deep neural network model was trained using 5,327 road images and 1,327 label images. After experimenting with 400 road images, a model with a mean intersection over a union of 80.54% and an F1 score of 77.85% was developed. Through this, a technology that can improve recognition performance by adding only road images was developed to learning without label images and is expected to be used as a technology for road surface management in the future.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.47-54
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• 2021

The number of freeway traffic accidents in Korea is about 4,000 as of 2020, and deaths per traffic accident is about 3.7 times higher than other roads due to non-recurring congestion and high driving speed. Most of the accident types on freeways are side and rear-end collisions, and one of the main factors is hazard traffic flow caused by merge, diverge and accidents. Therefore, the hazard traffic flow, which appears in a continuous flow such as a freeway, can be said to be important information for the driver to prevent accidents. This study tried to classify hazard traffic flows, such as the speed change point and the section where the speed difference by lane, using individual vehicle information. The homogeneous segment of speed was classified using spatial separation based on geohash and space mean speed that can indicate the speed difference of individual vehicles within the same section and the speed deviation between vehicles. As a result, I could extract the diverging influence segment and the hazard traffic flow segment that can provide dangerous segments information of freeways.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.2_1
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• pp.149-159
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• 2022

Biomass is material that is comprehensive of carbonaceous materials from plants, crops, animals, and algae. It has been used as one of heating fuel since the beginning the emergence of human beings. Since biomass is regarded as carbon-neutral energy source, it has recently been attracting attention as an energy source that can replace fossil fuels. The most widely applied field is distributed power generation, and a method of generating electric power by driving an internal combustion engine with syngas produced by gasifier is chosen. While the composition of the syngas produced in gasifiers changes depending on the air flowing into the reactor, commercialized gasifiers so far do not control the air flowing into the reactor. When the inner pressure in reactor increases, the air sucked into the reactor is reduced. That change of amount of air makes the composition of syngas varied. Those variations of composition of syngas cause the incomplete combustion hence the power output of engine drops, which is a critical weakness of the gasification technology. In this paper, to produce the uniformly composed syngas, PID control is applied. The result was shown when the amount of air into the reactor is supplied with the constant amount using PID control, the standard deviation of caloric values of syngas is around 2[%] of its average value. Meanwhile the gasifier without PID control has the standard deviation of caloric values is around 7[%]. Therefore, Adopting PID control to supply constant air to the gasifier is highly desirable.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.813-826
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• 2022

AI-based image processing technologies in various fields have been widely studied. However, the lighter the board, the more difficult it is to reduce the weight of image processing algorithm due to a lot of computation. In this paper, we propose a method using deep learning for object recognition algorithm in lightweight embedded boards. We can determine the area using a deep neural network architecture algorithm that processes semantic segmentation with a relatively small amount of computation. After masking the area, by using more accurate deep learning algorithm we could operate object detection with improved accuracy for efficient neural network (ENet) and You Only Look Once (YOLO) toward executing object recognition in real time for lightweighted embedded boards. This research is expected to be used for autonomous driving applications, which have to be much lighter and cheaper than the existing approaches used for object recognition.

• Journal of Korean Society of Archives and Records Management
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• v.22 no.1
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• pp.1-25
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• 2022

This study aims to identify the current situation and core competencies of records managers and archivists through an in-depth interpretation of the perception and its meaning behind their experiences and, based on them, to seek the educational service directions of professional organizations. As a result of qualitative data analysis using interpretive phenomenological research method, this study identified three categories of field needs, core competencies, and educational service directions, as well as 10 super-topics, 30 sub-topics, and 82 semantic units. Based on this, this study has suggested the educational service directions of professional organizations, such as the provision of opportunities to secure external driving forces for work innovation, the provision of learning opportunities for communication and public discussion among institutions, and the provision of new partnerships and practical learning opportunities. This study is meaningful in having derived the main educational service directions that professional organizations should focus on and support by identifying the current situation and core competencies of records managers and archivists.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.2
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• pp.74-84
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• 2022

Vehicle average speed information which measured at a point or a short section has a problem in that it cannot accurately provide the speed changes on an actual highway. In this study, segment separation method based on vehicle big data for accurate micro-speed estimation is proposed. In this study, to find the point where the speed deviation occurs using location-based individual vehicle big data, time and space mean speed functions were used. Next, points being changed micro-scale speed are classified through gradual segment separation based on geohash. By the comparative evaluation for the results, this study presents that the link-based speed is could not represent accurate speed for micro-scale segments.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.3
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• pp.110-115
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• 2021

With the era of the 4th Industrial Revolution, education on artificial intelligence is one of the important topics. However, since existing education is aimed at knowledge, it is not suitable for developing the active problem-solving ability and AI utilization ability required by artificial intelligence education. To solve this problem, we proposes PBL-based education method in which learners learn in the process of solving the presented problem. The problem presented to the learner is a completed project. This project consists of three types: a classification model, the training data of the classification model, and the block code to be executed according to the classified result. The project works, but each component is designed to perform a low level of operation. In order to solve this problem, the learners can expect to improve their computational thinking skills by finding problems in the project through testing, finding solutions through discussion, and improving to a higher level of operation.