• Journal of the Korean Society of Radiology
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• v.13 no.4
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• pp.605-611
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• 2019

The purpose of this study is to manufacture a multi-function device (MFD) which can be applied to various types of weight-bearing view of the lower leg, and to compare the results with the images from the existing weight-bearing platforms (WBPs), thereby suggesting a clinical utilization. The MFD was manufactured, by considering the minimum adjustable heights of the platform for weight-bearing foot/ankle, platform for hindfoot alignment view, and X-ray tube of the X-ray device. A foot/ankle phantom was used to take the images of weight-bearing lateral foot in MFD and WBPs to compare the resolutions of the X-ray images using a quick modulation transfer function (MTF) program. Between both the images taken from the MFD and WBPs, there was no statistically significant difference found in the mean cycles per pixel (C/P) and the lines per image height (LPH) of the 50%-Contrast Spatial Frequency (MTF50), and 10-90% of Maximum Energy Rise Distance (10-90%), where p>0.05. The MFD is suggested for its clinical trial as a useful positioning device that can secure the patient's safety and manifoldly perform various inspections. Also, the recommendation of the positioning device as a policy can activate dedicated manufacturers, while also improving the quality of medical services.

• The Journal of Bigdata
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• v.5 no.2
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• pp.53-67
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• 2020

This study employees a supervised learning prediction model to detect nonconformity in advance of processed food manufacturing and processing businesses. The study was conducted according to the standard procedure of machine learning, such as definition of objective function, data preprocessing and feature engineering and model selection and evaluation. The dependent variable was set as the number of supervised inspection detections over the past five years from 2014 to 2018, and the objective function was to maximize the probability of detecting the nonconforming companies. The data was preprocessed by reflecting not only basic attributes such as revenues, operating duration, number of employees, but also the inspections track records and extraneous climate data. After applying the feature variable extraction method, the machine learning algorithm was applied to the data by deriving the company's risk, item risk, environmental risk, and past violation history as feature variables that affect the determination of nonconformity. The f1-score of the decision tree, one of ensemble models, was much higher than those of other models. Based on the results of this study, it is expected that the official food control for food safety management will be enhanced and geared into the data-evidence based management as well as scientific administrative system.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.91-98
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• 2023

Recently, according to development of artificial intelligence, a wide range of industry being automatic and optimized. Also we can find out some research of using supervised learning for deteceting defect of railway in domestic rail industry. However, there are structures other than rails on the track, and the fastener is a device that binds the rail to other structures, and periodic inspections are required to prevent safety accidents. In this paper, we present a method of reducing cost for labeling using semi-supervised and transfer model trained on rail fastener data. We use Resnet50 as the backbone network pretrained on ImageNet. At first we randomly take training data from unlabeled data and then labeled that data to train model. After predict unlabeled data by trained model, we adopted a method of adding the data with the highest probability for each class to the training data by a predetermined size. Futhermore, we also conducted some experiments to investigate the influence of the number of initially labeled data. As a result of the experiment, model reaches 92% accuracy which has a performance difference of around 5% compared to supervised learning. This is expected to improve the performance of the classifier by using relatively few labels without additional labeling processes through the proposed method.

• Journal of the Korean Institute of Gas
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• v.27 no.4
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• pp.19-26
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• 2023

Earthquakes are one of the most important disasters affecting underground structures. Urban gas underground pipes may cause safety problems of structures in the event of an earthquake. Since Korea began digital observation, the number of earthquakes has been steadily increasing. The seismic design standard for urban gas pipes was established in 2008, but it is difficult to estimate the impact of pipes in the event of an earthquake based on the installation of pipes. In this study, structural analysis was performed on PE (polyethylene pipe) pipes and PLP (polyethylene coated steel pipe) pipes, which are mainly used as buried pipes in Korea, according to environmental and pipe variables in the event of an earthquake. This study sought to find the variables of the most vulnerable buried pipe by modeling pipes through Computer Aided Engineering (CAE) and generating displacement on the ground. Through this study, it was confirmed that the larger the elastic modulus of the soil, the deeper the buried depth, the smaller the tube diameter, and the higher the pressure, the more PLP pipes are affected by earthquakes than PE. Based on these results, the vulnerable points of buried urban gas pipes are inferred and used for special inspections of buried pipes in the event of an earthquake.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.4
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• pp.55-61
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• 2024

Recently, the number of aging concrete structures is steadily increasing. This is because many of these structures are reaching their expected lifespan. Such structures require accurate inspections and persistent maintenance. Otherwise, their original functions and performance may degrade, potentially leading to safety accidents. Therefore, research on objective inspection technologies using deep learning and computer vision is actively being conducted. High-resolution images can accurately observe not only micro cracks but also spalling and exposed rebar, and deep learning enables automated detection. High detection performance in deep learning is only guaranteed with diverse and numerous training datasets. However, surface damage to concrete is not commonly captured in images, resulting in a lack of training data. To overcome this limitation, this study proposed a method for generating concrete surface damage images, including cracks, spalling, and exposed rebar, using stable diffusion. This method synthesizes new damage images by paired text and image data. For this purpose, a training dataset of 678 images was secured, and fine-tuning was performed through low-rank adaptation. The quality of the generated images was compared according to three base models of stable diffusion. As a result, a method to synthesize the most diverse and high-quality concrete damage images was developed. This research is expected to address the issue of data scarcity and contribute to improving the accuracy of deep learning-based damage detection algorithms in the future.

• Journal of the Korean Institute of Landscape Architecture
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• v.48 no.4
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• pp.29-40
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• 2020

This study quantitatively and qualitatively analyzes the physical environment for health promotion in urban parks by indicators that were selected in consideration of overseas cases and previous studies. To evenly distribute the areas to be evaluated by region, Seodaemun Independence Park, Hongneung Park, Gocheok Park, Sillim Park, Cheongdam Park, Gaepo Park, and Sungin Park were selected among the old neighborhood parks already established in Seoul. The evaluation indicators consist of quantitative indicators (12 factors classified into the three categories of the surrounding environment, the park characteristics, and the park facilities) and qualitative indicators (14 factors classified according to the five categories of accessibility, safety, convenience, activities, and amenities). These indicators were selected after conducting advisory meetings with experts in the field. The physical environment perception factors were evaluated by experts and investigators by field inspections and were rated on a three-point scale (high, medium, low). According to the results of the analysis, first, not only were exercise facilities and trails, but also various factors which support health activities, such as rest areas, leisure spots, and cultural facilities, as well as accessibility, cleanliness, and drinking water facilities are important indicators for health promotion. Second, even if the requirements are met for quantitative factors, several inconveniences hinder the actual implementation or use in the qualitative evaluation. Thus, both quantitative and qualitative evaluations must be simultaneously performed for the proper judging of the physical environment of a park. Third, upon conducting a qualitative evaluation of the physical environmental factors, score differences depended on the evaluated categories in each park. These differences show that indirect indicators, such as accessibility, safety, and facility convenience are insufficiently equipped compared to direct indicators, such as activity, which includes exercise facilities and fitness centers for health promotion. As the utilization rate of parks is increasing due to COVID-19, more efforts should be made to improve park services in the post-corona era. To promote such services, it is necessary to regularly evaluate parks based on both quantitative and qualitative indicators and to contemplate services not only through direct factors but also indirect factors and security measures.

• The Korean Journal of Nuclear Medicine Technology
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• v.22 no.2
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• pp.84-87
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• 2018

Purpose The radiopharmaceutical used in the nuclear medicine department is used only for the specific patient according to the prescription or instruction of the doctor without selling, so it is dispensed and it is distributed and used for the examination. Radiopharmaceuticals administered to patients should be managed appropriately as well as radiation safety management during dispensation. The purpose of this study is to investigate microbial contamination during dispensation of radiopharmaceuticals Materials and Methods This study distinguished between general workbench and clean workbench and performed three tests. First, microbial cultivation test of radiopharmaceutical prepared and dispensed in general workbenches and sterile workbenches were carried out five times, respectively. The second test was performed settle plate method three times before and after the use of the exhaust filter. Finally, Adenosine Triphosphate (ATP) measurement was performed in each workbench to measure bacterial counts. In addition, ATP measurement were carried out by designating locations and items that may be contaminated during dispensation. Results In the microbial culture test, no microorganisms were detected in both samples. In the settle plate method, it was detected without using of the exhaust filter in a general workbench once. In the ATP measurement test, it was measured at the level of 400 RLU or less, which is the standard value of contamination, in both workbenches surface. In additional ATP measurement test, the refrigerator handle in the distribution room was measured above the reference value of 1217 RLU, the vacuum vial shield of the Tech Generator at 435 RLU, and the syringe holder at 1357 RLU. After environmental disinfection, the results were reduced to 311 RLU, 136 RLU, and 291 RLU. Conclusion No contamination by bacteria was found in both workbenches. However, microbial contamination may occur if the use of an exhaust filter or proper hand hygiene is not achieved. Regular inspections and management for aseptic processing themselves will be necessary.