• Journal of the Korean Society of Radiology
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• v.15 no.2
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• pp.159-164
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• 2021

The examination using diagnostic x-ray equipment is one of the most useful diagnostic equipment for identifying information in the human body in diagnostic radiology. For this reason, the number of examinations has recently increased a lot. Increasing the number of examinations will accelerate the aging of the device. In addition, this makes them aware of the importance of quality control for the diagnostic x-ray device. Particularly, in a diagnostic x-ray device, quality control refers to an act of always maintaining a certain level of image quality by identifying and correcting all problems that may lead to reduction of the diagnosis area in advance. Therefore, this study summarizes and reports general information about quality control in examinations using diagnostic x-ray equipment.

• Endocrinology and Metabolism
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• v.33 no.4
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• pp.435-444
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• 2018

The prevalence of chronic diseases including osteoporosis and sarcopenia increases as the population ages. Osteoporosis and sarcopenia are commonly associated with genetics, mechanical factors, and hormonal factors and primarily associated with aging. Many older populations, particularly those with frailty, are likely to have concurrent osteoporosis and sarcopenia, further increasing their risk of disease-related complications. Because bones and muscles are closely interconnected by anatomy, metabolic profile, and chemical components, a diagnosis should be considered for both sarcopenia and osteoporosis, which may be treated with optimal therapeutic interventions eliciting pleiotropic effects on both bones and muscles. Exercise training has been recommended as a promising therapeutic strategy to encounter the loss of bone and muscle mass due to osteosarcopenia. To stimulate the osteogenic effects for bone mass accretion, bone tissues must be exposed to mechanical load exceeding those experienced during daily living activities. Of the several exercise training programs, resistance exercise (RE) is known to be highly beneficial for the preservation of bone and muscle mass. This review summarizes the mechanisms of RE for the preservation of bone and muscle mass and supports the clinical evidences for the use of RE as a therapeutic option in osteosarcopenia.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.355-357
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• 2019

Now that we are entering an aging society, the user interface for new devices and IoT technology is very inconvenient for senior generation. To improve this, we propose an AI technology-based intelligent senior assistant voice recognition system. This system implements Cloud platform based API to accumulate data for machine learning processing, provides content for diagnosis and prevention of dementia, and provide chat-bot content for senior generation. We hope that senior generations will increase the accessibility and convenience of IoT devices and new technology devices with our system.

• Journal of Korea Multimedia Society
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• v.23 no.12
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• pp.1486-1495
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• 2020

The analysis of digital microscopy images plays a vital role in computer-aided diagnosis (CAD) and prognosis. The main purpose of this paper is to develop a machine learning technique to predict the histological grades in prostate biopsy. To perform a multiclass classification, an AI-based deep learning algorithm, a multichannel convolutional neural network (MCCNN) was developed by connecting layers with artificial neurons inspired by the human brain system. The histological grades that were used for the analysis are benign, grade 3, grade 4, and grade 5. The proposed approach aims to classify multiple patterns of images extracted from the whole slide image (WSI) of a prostate biopsy based on the Gleason grading system. The Multichannel Convolution Neural Network (MCCNN) model takes three input channels (Red, Green, and Blue) to extract the computational features from each channel and concatenate them for multiclass classification. Stain normalization was carried out for each histological grade to standardize the intensity and contrast level in the image. The proposed model has been trained, validated, and tested with the histopathological images and has achieved an average accuracy of 96.4%, 94.6%, and 95.1%, respectively.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.12-14
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• 2022

One of the most negative social changes of the last decade is population aging which leads to 19 times more patients with Mild Cognitive Disorder(MCI). It is well established that MCI is the most important state that can prevent dementia with early diagnosis and intervention. However, the social security system for patients with dementia is not working properly due to the coronavirus pandemic and the limited human power. This article proposes design principles for dementia training programs of extended reality devices. and The findings in this study provide a guide for considering the cognitive and physical and social functions of patients.

• Nuclear Engineering and Technology
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• v.55 no.4
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• pp.1528-1539
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• 2023

Since the leakage of sodium in an SFR (sodium-cooled fast reactor) causes an explosion upon reaction with air and water, sodium leakages represent an important safety issue. In this study, a novel technique for improving the reliability of sodium leakage detection applying DDVR (dynamic data validation and reconciliation) is proposed and verified to resolve this technical issue. DDVR is an approach that aims to improve the accuracy of a target system in a dynamic state by minimizing random errors, such as from the uncertainty of instruments and the surrounding environment, and by eliminating gross errors, such as instrument failure, miscalibration, or aging, using the spatial redundancy of measurements in a physical model and the reliability information of the instruments. DDVR also makes it possible to estimate the state of unmeasured points. To validate this approach for supporting sodium leakage detection, this study applies experimental data from a sodium leakage detection experiment performed by the Korea Atomic Energy Research Institute. The validation results show that the reliability of sodium leakage detection is improved by cooperation between DDVR and hardware measurements. Based on these findings, technology integrating software and hardware approaches is suggested to improve the reliability of sodium leakage detection by presenting the expected true state of the system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.8
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• pp.2333-2345
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• 2024

Facial wrinkles are widely used to evaluate skin condition or aging for various fields such as skin diagnosis, plastic surgery consultations, and cosmetic recommendations. In order to effectively process facial wrinkles in facial image analysis, accurate wrinkle segmentation is required to identify wrinkled regions. Existing deep learning-based methods have difficulty segmenting fine wrinkles due to insufficient wrinkle data and the imbalance between wrinkle and non-wrinkle data. Therefore, in this paper, we propose a new facial wrinkle segmentation method based on a UNet++ model. Specifically, we construct a new facial wrinkle dataset by manually annotating fine wrinkles across the entire face. We then extract only the skin region from the facial image using a facial landmark point extractor. Lastly, we train the UNet++ model using both dice loss and focal loss to alleviate the class imbalance problem. To validate the effectiveness of the proposed method, we conduct comprehensive experiments using our facial wrinkle dataset. The experimental results showed that the proposed method was superior to the latest wrinkle segmentation method by 9.77%p and 10.04%p in IoU and F1 score, respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.2C
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• pp.184-191
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• 2008

Oriental base diagnosis method is not going to hospital different from Oriental medicine and because of the possible disease diagnosis through the network and many communication equipment. Especially diagnosis development using ocular inspection method aspect of Oriental medicine among an aging society advance into cut the medical cost for contribution. Ocular inspection method the most important look at disease color that is Observing a Person's Shape and Color which is implementation the development of methodology and important the build of application ability system. So in this paper study observing a person's shape and color implementation of ocular inspection. Specially body's the five viscera presentate the five colors disease color in face that is important the color coordinate system thesis so that proceed the experiment for the color coordinate system analysis. Finally five color extract need the observing a person's shape and color through experiment select the digital color system and so real skin color analysis and comparison about the experiment which suggest the something to color coordinate system the best case of digital color system for observing a person's shape and color implementation.

• Journal of the Korean Regional Science Association
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• v.37 no.4
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• pp.33-47
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• 2021

In urban declining areas, the population is decreasing, and drying environments such as buildings and facilities are aging. Therefore, it is vulnerable in the event of disaster, and recovery takes a lot of time and money. The purpose of this study is to develop an evaluation technique for comprehensively diagnosing disasters in declining areas and to present implications through case analysis. Evaluation indicators were selected to calculate the comprehensive diagnosis index of disasters, and weights were calculated for each class, including disaster types, components, and evaluation indicators, through Analytic Hierarchy Process analysis. The comprehensive diagnoses index for each type of disaster was calculated with the calculated weight, and the risk according to the level of urban decline was analyzed. As a result of analyzing Seoul as a case area, it was analyzed that the overall risk of disasters was high in southern regions such as Seocho-gu, Dongjak-gu, Geumcheon-gu, and Gangseo-gu, and relatively low in downtown and northern Seoul, parks and green areas. The results of this study are of academic significance in that they presented a comprehensive diagnostic index evaluation system and technique for each type of disaster, including natural and social disasters.

• The Journal of Bigdata
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• v.6 no.1
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• pp.37-49
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• 2021

The number of dementia patients in Korea is estimated to be over 800,000, and the severity of dementia is becoming a social problem. However, no treatment or drug has yet been developed to cure dementia worldwide. The number of dementia patients is expected to increase further due to the rapid aging of the population. Currently, early detection of dementia and delaying the course of dementia symptoms is the best alternative. This study presented a methodology for early diagnosis of dementia by measuring and analyzing amyloid plaques. This vital protein can most clearly and early diagnose dementia in the retina through AI-based image analysis. We performed binary classification and multi-classification learning based on CNN on retina data. We also developed a deep learning algorithm that can diagnose dementia early based on pre-processed retinal data. Accuracy and recall of the deep learning model were verified, and as a result of the verification, and derived results that satisfy both recall and accuracy. In the future, we plan to continue the study based on clinical data of actual dementia patients, and the results of this study are expected to solve the dementia problem.