• KIPS Transactions on Software and Data Engineering
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• v.11 no.5
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• pp.211-220
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• 2022

Recently, research on smart factories triggered by the 4th industrial revolution is being actively conducted. Accordingly, the manufacturing industry is conducting various studies to improve productivity and quality based on deep learning technology with robust performance. This paper is a study on the method of detecting tire surface defects in the visual inspection stage of the tire manufacturing process, and introduces a tire surface defect detection method using a depth image acquired through a 3D camera. The tire surface depth image dealt with in this study has the problem of low contrast caused by the shallow depth of the tire surface and the difference in the reference depth value due to the data acquisition environment. And due to the nature of the manufacturing industry, algorithms with performance that can be processed in real time along with detection performance is required. Therefore, in this paper, we studied a method to normalize the depth image through relatively simple methods so that the tire surface defect detection algorithm does not consist of a complex algorithm pipeline. and conducted a comparative experiment between the general normalization method and the normalization method suggested in this paper using YOLO V3, which could satisfy both detection performance and speed. As a result of the experiment, it is confirmed that the normalization method proposed in this paper improved performance by about 7% based on mAP 0.5, and the method proposed in this paper is effective.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.711-719
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• 2021

EBS has been producing numerous educational contents with traditional virtual studio production systems since the early 2000s and applied AR video production system in October 2020, twenty-years after. Although the basic concept of synthesizing graphic elements and actual image in real time by tracking camera movement and lens information is similar to the previous one but the newly applied AR video production system contains some of advanced technologies that are improved over the previous ones. Marker tracking technology that enables camera movement free and position tracking has been applied that can track the location stably, and the operating software has been applied with Unreal Engine, one of the representative graphic engines used in computer game production, therefore the system's rendering burden has been reduced, enabling high-quality and real-time graphic effects. This system is installed on a crane camera that is mainly used in a crane shot at the live broadcasting studio and applied for live broadcasting programs for children and some of the videos such as program introductions and quiz events that used to be expressed in 2D graphics were converted to 3D AR videos which has been enhanced. This paper covers the effect of introduction and application of the AR video production system on EBS content production and the future development direction and possibility.

• Tunnel and Underground Space
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• v.32 no.5
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• pp.298-311
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• 2022

Some problems, such as aging workers, a decreased population due to a low birth rate, and shortage of skilled workers, are rising in construction sites. Therefore research for smart construction technology that can be improved for productivity, safety, and quality has been recently developed with government support by replacing traditional construction technology with advanced digital technology. In particular, the motor grader that mainly performs road surface flattening is a construction machine that requires the application of automation technology for repetitive construction. It is predicted that the construction period will be shortened if the construction automation technology such as trajectory tracking, automation work, and remote control technology is applied. In this study, we introduce the hardware and software architecture of the smart motor grader to apply unmanned and automation technology and then analyze the traditional earthwork method of the motor grader. We suggested the application plans for the path pattern and blade control method of the smart motor grader based on this. In addition, we verified the performance of waypoint-based path-following depending on scenarios and the blade control's performance through tests.

• Geophysics and Geophysical Exploration
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• v.25 no.3
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• pp.109-119
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• 2022

The computational efficiency of reverse time migration (RTM) based on numerical modeling is not secured due to the high-frequency band of several hundred Hz or higher for data acquired through a three-dimensional (3D) ultra-high-resolution (UHR) seismic survey. Therefore, this study develops an RTM program to derive high-quality 3D geological structures using UHR seismic data. In the traditional 3D RTM program, an excitation amplitude technique that stores only the maximum amplitude of the source wavefield and a domain-limiting technique that minimizes the modeling area where the source and receivers are located were used to significantly reduce memory usage and calculation time. The program developed through this study successfully derived a 3D migration image with a horizontal grid size of 1 m for the 3D UHR seismic survey data obtained from the Korea Institute of Geoscience and Mineral Resources in 2019, and geological analysis was conducted.

• Journal of Korean Home Economics Education Association
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• v.34 no.4
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• pp.93-111
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• 2022

This study started with the question of 'What innovative task should elementary and secondary school clothing life education perform in accordance with the changes in the future educational environment?' It is time to prepare for a major shift in the educational paradigm that improves the quality of life for all everyone, based on social innovations such as the 4th industrial revolution and the transition to the post-corona era. This study examined the literature for the characteristics of changes in the future educational environment from an educational perspective, and examined the curriculum focusing on the clothing life with the porpose of presenting the direction for the clothing life education. In order to carry out this study, various literature including previous studies related to clothing life education and the national curriculum from the first curriculum to the 2015 revision were analyzed. In conclusion, the direction of the clothing life education curriculum according to the changes in the future educational environment is proposed as follows: First, nurturing convergence education experts that can combine human emotion, environment, and clothing life culture to artificial intelligence(AI); second, developing a clothing life education curriculum that links software competency and practical problem-solving competency; and lastly, implementing fashion maker education using artificial intelligence(AI) and value-oriented clothing life education. In the future, it is expected that the direction of teaching/learning methods and evaluation in clothing life education curriculum is proposed, and that this educational discussion process will help establish the identity of clothing life education in school education.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.149-158
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• 2023

As data utilization is becoming more important recently, the importance of data centers is also increasing. However, the data center is a problem in terms of environment and economy because it is a massive power-consuming facility that runs 24 hours a day. Recently, studies using deep learning techniques to reduce power used in data centers or servers or predict traffic have been conducted from various perspectives. However, the amount of traffic data processed by the server is anomalous, which makes it difficult to manage the server. In addition, many studies on dynamic server management techniques are still required. Therefore, in this paper, we propose a dynamic server management technique based on Long-Term Short Memory (LSTM), which is robust to time series data prediction. The proposed model allows servers to be managed more reliably and efficiently in the field environment than before, and reduces power used by servers more effectively. For verification of the proposed model, we collect transmission and reception traffic data from six of Wikipedia's data centers, and then analyze and experiment with statistical-based analysis on the relationship of each traffic data. Experimental results show that the proposed model is helpful for reliably and efficiently running servers.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.189-198
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• 2023

As crimes frequently occur on the street, the spread of CCTV is increasing. However, due to the shortcomings of passively operated CCTV, the need for intelligent CCTV is attracting attention. Due to the heavy system of such intelligent CCTV, high-performance devices are required, which has a problem in that it is expensive to replace the general CCTV. To solve this problem, an intelligent CCTV system that recognizes low-quality images and operates even on devices with low performance is required. Therefore, this paper proposes a Saying CCTV system that can detect threats in real time by using the AWS cloud platform to lighten the system and convert images into text. Based on the data extracted using YOLO v4 and OpenPose, it is implemented to determine the risk object, threat behavior, and threat situation, and calculate the risk using machine learning. Through this, the system can be operated anytime and anywhere as long as the network is connected, and the system can be used even with devices with minimal performance for video shooting and image upload. Furthermore, it is possible to quickly prevent crime by automating meaningful statistics on crime by analyzing the video and using the data stored as text.

• Therapeutic Science for Rehabilitation
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• v.12 no.2
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• pp.55-68
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• 2023

Objective : This study aims to analyze the effects of visual perception intervention by systematically reviewing the studies that applied visual perception intervention to children with cerebral palsy. Methods : The databases used were PubMed, EMbase, Science Direct, ProQuest, Koreanstudies Information Service System (KISS), Research Information Sharing Service (RISS), and the National Assembly Library. The keywords used were cerebral palsy, CP, and visual perception. According to the PRISMA flowchart, 10 studies were selected from among studies published from January 1, 2012 to March 30, 2022. The quality level of the selected studies, the demographic characteristics of study participants, the effectiveness of interventions, area and strategies of intervention, assessment tools to measure the effectiveness of interventions, and risk of bias were analyzed. Results : All selected studies confirmed that visual perception intervention was effective in improving visual perception function. In addition, positive results were shown in upper extremity function, activities of daily living, posture control, goal achievement, and psychosocial areas as well as visual perception function. The eye-hand coordination area was intervened in all studies. Conclusion : In visual perception intervention, It is necessary to evaluate the visual perception function by area, and apply systematically graded customized interventions for each individual.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.12
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• pp.489-498
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• 2022

Recently, the textile industry, which is labor-intensive, is attempting to reduce process costs and optimize quality through artificial intelligence. However, the fiber spinning process has a high cost for data collection and lacks a systematic data collection and processing system, so the amount of accumulated data is small. In addition, data imbalance occurs by preferentially collecting only data with changes in specific variables according to the purpose of fiber spinning, and there is an error even between samples collected under the same fiber spinning conditions due to difference in the measurement environment of physical properties. If these data characteristics are not taken into account and used for AI models, problems such as overfitting and performance degradation may occur. Therefore, in this paper, we propose an outlier handling technique and data augmentation technique considering the characteristics of the spinning process data. And, by comparing it with the existing outlier handling technique and data augmentation technique, it is shown that the proposed technique is more suitable for spinning process data. In addition, by comparing the original data and the data processed with the proposed method to various models, it is shown that the performance of the tensile tenacity and elongation prediction model is improved in the models using the proposed methods compared to the models not using the proposed methods.

• Journal of Broadcast Engineering
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• v.27 no.1
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• pp.104-123
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• 2022

Style transfer based on neural network provides very high quality results by reflecting the high level structural characteristics of images, and thereby has recently attracted great attention. This paper deals with the problem of resolution limitation due to GPU memory in performing such neural style transfer. We can expect that the gradient operation for style transfer based on partial image, with the aid of the fixed size of receptive field, can produce the same result as the gradient operation using the entire image. Based on this idea, each component of the style transfer loss function is analyzed in this paper to obtain the necessary conditions for partitioning and padding, and to identify, among the information required for gradient calculation, the one that depends on the entire input. By structuring such information for using it as auxiliary constant input for partition-based gradient calculation, this paper develops a recursive algorithm for super high-resolution image style transfer. Since the proposed method performs style transfer by partitioning input image into the size that a GPU can handle, it can perform style transfer without the limit of the input image resolution accompanied by the GPU memory size. With the aid of such super high-resolution support, the proposed method can provide a unique style characteristics of detailed area which can only be appreciated in super high-resolution style transfer.