• Journal of Korean Tunnelling and Underground Space Association
• /
• v.21 no.3
• /
• pp.397-418
• /
• 2019

It is very important to understand and analyze the interactive behaviour between ground and adjacent structures due to tunneling. With many technological advancement in modern society, numerous methods for analyzing the interactive behaviour are used in a wide range of civil engineering fields. Close range photogrammetry is mainly being used in the field of geotechnical engineering and research on measuring methods associated with GeoPIV has been currently increased. Originally, the close range photogrammetry using target points and aluminum rods for VMS (Vision Measurement System) program has been used. However, applying this has a problem that external errors can be occurred because the target points are artificially installed by hand, and if the grid between points is being wider or narrower, deficient data can be obtained. Therefore, in this study, MATLAB-based No-target program that can analyze displacement without using target was developed. Additionally, this study focused on comparison and verification with existing program through numerical analysis and laboratory model test. Three cases of Greenfield condition, Strip foundation, and Pile foundation were analyzed. From results of VMS program and No-target program, the error rate and reliability of the total displacement and the vertical displacement were analyzed. It was also compared and verified through the finite element numerical program, PLAXIS.

• The Journal of the Korea Contents Association
• /
• v.21 no.5
• /
• pp.668-680
• /
• 2021

Recently, measures for successful settlement and sustainability of social enterprises have become an important topic. Accordingly, researches related to social enterprises are increasing, but studies measuring sustainability are still insufficient. In this study, in order to seek the sustainability and development of social enterprises in the field of literature and arts, a theoretical model for the sustainability of social enterprises in the field of culture and arts was presented. To this end, interviews were conducted with social enterprises in the field of culture and arts, and the results were analyzed to derive the concept and categorization of sustainability of social enterprises in the field of culture and arts. In addition, the integration between the derived categories is illustrated. For a social enterprise in the field of culture and arts to be sustainable, differentiated culture and arts services are important, and each company must constantly strive for its mission and vision, and a differentiated branding strategy unique to companies is required. This research is expected to lay the foundation for empirical research on social enterprises in the culture and arts sector as data for entrepreneurs and prospective entrepreneurs who run social enterprises in the field of culture and arts.

• Journal of Broadcast Engineering
• /
• v.27 no.3
• /
• pp.308-317
• /
• 2022

Researches are underway to efficiently reduce the size of video data transmitted and stored in the image analysis process using deep learning-based machine vision technology. MPEG (Moving Picture Expert Group) has newly established a standardization project called VCM (Video Coding for Machine) and is conducting research on video encoding for machines rather than video encoding for humans. We are researching a multitask that performs various tasks with one image input. The proposed pipeline does not perform all object detection of each task that should precede object detection, but precedes it only once and uses the result as an input for each task. In this paper, we propose a pipeline for efficient multitasking and perform comparative experiments on compression efficiency, execution time, and result accuracy of the input image to check the efficiency. As a result of the experiment, the capacity of the input image decreased by more than 97.5%, while the accuracy of the result decreased slightly, confirming the possibility of efficient multitasking.

• Journal of Intelligence and Information Systems
• /
• v.28 no.2
• /
• pp.263-278
• /
• 2022

With the recent advent of IoT technology, automatic pet feeders are being distributed so that owners can feed their companion animals while they are out. However, due to behaviors of pets, the method of measuring weight, which is important in automatic feeding, can be easily damaged and broken when using the scale. The 3D camera method has disadvantages due to its cost, and the 2D camera method has relatively poor accuracy when compared to 3D camera method. Hence, the purpose of this study is to propose a deep learning approach that can accurately estimate weight while simply using a 2D camera. For this, various convolutional neural networks were used, and among them, the ResNet101-based model showed the best performance: an average absolute error of 3.06 grams and an average absolute ratio error of 3.40%, which could be used commercially in terms of technical and financial viability. The result of this study can be useful for the practitioners to predict the weight of a standardized object such as feed only through an easy 2D image.

• Journal of the Society of Disaster Information
• /
• v.18 no.2
• /
• pp.269-279
• /
• 2022

Purpose: The purpose of this study is to develop a deep learning-based personal protective equipment detection model for disaster prevention at construction sites, and to apply it to actual construction sites and to analyze the results. Method: In the method of conducting this study, the dataset on the real environment was constructed and the developed personal protective equipment(PPE) detection model was applied. The PPE detection model mainly consists of worker detection and PPE classification model.The worker detection model uses a deep learning-based algorithm to build a dataset obtained from the actual field to learn and detect workers, and the PPE classification model applies the PPE detection algorithm learned from the worker detection area extracted from the work detection model. For verification of the proposed model, experimental results were derived from data obtained from three construction sites. Results: The application of the PPE recognition model to construction site brings up the problems related to mis-recognition and non-recognition. Conclusions: The analysis outcomes were produced to apply the object recognition technology to a construction site, and the need for follow-up research was suggested through representative cases of worker recognition and non-recognition, and mis-recognition of personal protective equipment.

• KIPS Transactions on Software and Data Engineering
• /
• v.11 no.1
• /
• pp.51-58
• /
• 2022

Drivable area detection, one of the main functions of advanced driver assistance systems, means detecting an area where a vehicle can safely drive. The drivable area detection is closely related to the safety of the driver and it requires high accuracy with real-time operation. To satisfy these conditions, V-disparity-based method is widely used to detect a drivable area by calculating the road disparity value in each row of an image. However, the V-disparity-based method can falsely detect a non-road area as a road when the disparity value is not accurate or the disparity value of the object is equal to the disparity value of the road. In a road environment including vegetation, such as a highway and a country road, the vegetation area may be falsely detected as the drivable area because the disparity characteristics of the vegetation are similar to those of the road. Therefore, this paper proposes a drivable area detection method and hardware architecture with a high accuracy in road environments including vegetation areas by reducing the number of false detections caused by V-disparity characteristic. When 289 images provided by KITTI road dataset are used to evaluate the road detection performance of the proposed method, it shows an accuracy of 90.12% and a recall of 97.96%. In addition, when the proposed hardware architecture is implemented on the FPGA platform, it uses 8925 slice registers and 7066 slice LUTs.

• Journal of Nutrition and Health
• /
• v.55 no.2
• /
• pp.201-210
• /
• 2022

Vitamin A (Vit A) is a lipid-soluble vitamin required for diverse normal body functions, including good vision, reproduction, growth, development, and cellular differentiation. The therapeutic effects of Vit A have been demonstrated for the treatments of inflammation, low immunity, and cancer. The present review discusses the scientific evidence for establishing the 2020 Dietary Reference Intakes for Koreans (KDRI) for Vit A, issues caused by unit change of Vit A, and suggestions for the 2025 KDRI revision. Due to the changes in the standard bodyweight observed in several age groups, the 2020 KDRI had minor revisions as compared to the 2015 KDRI. In the 2015 KDRI, the Vit A unit has changed from retinol equivalent (RE) to retinol activity equivalent (RAE) and the activity of carotenoids became half with RAE compared to RE due to this unit change. Since the Vit A intake of Koreans relies heavily on plant-based carotenoids, the dietary intake of Vit A in Koreans as determined by considering the RAE was much lower than values obtained with RE. The analysis for Vit A intake by the Korean National Health and Nutrition Survey only reflects intakes of retinol and beta-carotene. Thus, it would be necessary to include the consumption of other provitamin A, such as alpha-carotene and beta-cryptoxanthin. Moreover, assessing the amounts of Vit A in foods should be customized to Korean diets since there are seasonal variations in the carotenoid concentration of plants. Moreover, other factors such as age- and sex-specific intake data and considerations of baseline micronutrient status, body mass index, and dietary patterns should be considered for developing more precise KDRI. In particular, the Vit A requirement needs to be met by consuming diverse foods, including animal foods.

• KIPS Transactions on Software and Data Engineering
• /
• v.11 no.10
• /
• pp.409-418
• /
• 2022

In this paper, we propose SAAnnot-C3Pap, a semi-automatic annotation method for obtaining ground truth of a player's posture. In order to obtain ground truth about the two-dimensional joint position in the existing music domain, openpose, a two-dimensional posture estimation method, was used or manually labeled. However, automatic annotation methods such as the existing openpose have the disadvantages of showing inaccurate results even though they are fast. Therefore, this paper proposes SAAnnot-C3Pap, a semi-automated annotation method that is a compromise between the two. The proposed approach consists of three main steps: extracting postures using openpose, correcting the parts with errors among the extracted parts using supervisely, and then analyzing the results of openpose and supervisely. Perform the synchronization process. Through the proposed method, it was possible to correct the incorrect 2D joint position detection result that occurred in the openpose, solve the problem of detecting two or more people, and obtain the ground truth in the playing posture. In the experiment, we compare and analyze the results of the semi-automated annotation method openpose and the SAAnnot-C3Pap proposed in this paper. As a result of comparison, the proposed method showed improvement of posture information incorrectly collected through openpose.

• Journal of Appropriate Technology
• /
• v.7 no.2
• /
• pp.196-205
• /
• 2021

As industrial safety increases, various industrial accident prevention technologies using smart factory technology are being studied. However, small and medium enterprises (SMEs), which account for the majority of industrial accidents, are having difficulties in preventing industrial accidents by applying these smart factory technologies due to practical problems. In this study, customized monitoring and warning systems for each type of industrial accident were developed and applied to the actual field. Through this, we demonstrated industrial accident prevention technology through appropriate smart factory technology used by SMEs. A customized monitoring system using vision, current, temperature, and gas sensors was established for the four major disaster types: worker body access, short circuit and overcurrent, fire and burns due to high temperature, and emission of hazardous gas. In addition, a notification method suitable for each work environment was applied so that the monitored risk factors could be recognized quickly, and real-time data transmission and display enabled workers and managers to understand the disaster risk effectively. Through the application and demonstration of these appropriate smart factory technologies, the spread of these industrial safety technologies is to be discussed.

• Korean small business review
• /
• v.43 no.1
• /
• pp.147-164
• /
• 2021

This study focuses on succession in a family business which is the crucial factor affecting future and survival of a family business. Especially, the study concentrate a successor's view which is regarded as a key-player during the succession. In this study, we used AHP (Analytic Hierarchy Process) methodology to identify priorities of factors influencing succession. We divided into two-tier level. The first-tier is defined as 1) the relationship with an incumbent CEO, 2) a successor 's management ability, 3) a successor' s self-efficacy and 4) succession plan. For the second-tier of each first-tier have 3 sub-factors ; 1) the relationship with an incumbent CEO is set as level of mutual trust, sharing the vision of a company, and level of communication each other. 2) A successor 's management ability is based on business competence, education and training and interpersonal management ability, 3) a successor 's self-efficacy was set as successor' s willingness of succession, confidence of overcoming crisis and confidence of achieving objectives. Lastly, 4) a succession plan is set as finance plan, leadership transformation plan and human-organization management plan. A total of 93 questionnaires is distributed and retrieved, and 88 questionnaires are used for the study, excluding those with missing data. As a result of this study, successors selected 1) the relationship with an incumbent C.E.O. as the most important priority in the first-tier. The second is 2) a successor 's management ability, the third is 3) a successor' s self-efficacy, and the last priority is 4) a succession plan. In particular, 3 sub-factors that make up the relationship with an incumbent are the most important factors. These factors rank the first to the third in the final result.