• Journal of Digital Convergence
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• v.16 no.2
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• pp.19-26
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• 2018

We proposed a numerical calculation of the proportion of necrotic cells in pulmonary segmentation, pulmonary vessel segmentation lung disease site for diagnosis of lung disease from chest CT images. The first step is to separate the lungs and bronchi by applying a three-dimensional labeling technique from a chest CT image and a three-dimensional region growing method. The second step is to divide the pulmonary vessels by applying the rate of change using the first order polynomial regression, perform noise reduction, and divide the final pulmonary vessels. The third step is to find a disease prediction factor in a two-step image and calculate the proportion of necrotic cells.

• Journal of Digital Convergence
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• v.16 no.2
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• pp.251-259
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• 2018

This study aimed to identify the risk factors for cardiovascular disease (CVD) among age groups using the Framingham risk score (FRS). The research design used was a cross sectional descriptive study using the Sixth Korean National Health and Nutrition Examination Survey from 2013-2015. Data from 5211 men, between the ages of 30-74 was analyzed. After adjusting for age, the result of logistic regression analysis showed that obesity (OR=2.51 95% CI=2.05-3.07), physical inactivity (OR=1.71, 95% CI=1.39-2.10), heavy alcohol drinking (OR=1.33, 95% CI=1.09-1.62), and dietary fiber intake (OR=0.99, 95% CI=0.98-0.99) were presented as predictors of CVD. Obesity was considered to be a particularly important predictor of CVD for young and middle-aged men. This result will be used for developing intervention relating to lifestyle modification for young and middle-aged men.

• Journal of Digital Convergence
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• v.14 no.2
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• pp.501-507
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• 2016

We obtained medical test data of 150 male from National Health Insurance Corporation, that included physique, blood chemistry, and lifestyle. ${\chi}^2-test$ and logistic regression, and multiple regression were done to verify how CAD risks and/or lifestyle are different between obese and non-obese person. SPSS(version 18) was used for statistical procedures and p-value of .05 was regarded as good through. ${\chi}^2-test$ showed the frequency of hypertension, htperglycemia, hyperlipidemia were higher in obese person than in non-obese This result told us that lifestyle modification could be a key to prevent cardiovascular disease by controlling and managing body composition, especially abdominal obesity.

• Journal of Digital Convergence
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• v.15 no.9
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• pp.311-319
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• 2017

The purpose of this study was to examine the relationship between hours of sleep and periodontal diseases among adolescents based on the raw materials of the 5th third-year(2012) national health and nutrition examination survey. The subjects in this study were 593 selected teens who were at the western ages of 12 to 18. SPSS 18.0 for Windows was used to analyze general characteristics, health behavior, oral health care, mental health, and relationship of sleep duration to periodontal disease. As a result, the groups of adolescents who were older and whose household income was larger slept for less hours, and higher toothbrushing frequencies led to more hours of sleep. There were 2.28-fold more periodontal diseases in the group that got five or less hours of sleep than in the group that got eight or more hours of sleep. The above-mentioned findings of the study illustrated that insufficient sleep is linked to periodontal health in adolescence.

• Journal of Digital Convergence
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• v.14 no.12
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• pp.217-224
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• 2016

As livestock diseases such as foot-and-mouth disease are highly infectious and likely to inflict nationwide damage, it is important to detect such diseases in advance. Infection of foot-and-mouth disease is determined in the field through examination of external symptoms such as rise in body temperature. However, as the disease is carried around initially by travelling veterinarians in some cases, it is critical to measure the body temperature of livestock to detect abnormal temperature pattern early on and transmit temperature reading data remotely to a veterinarian remotely to expedite decision. In this study, we have developed a telemedicine system designed to connect veterinarians and livestock farmers and measure the body temperature of Korean beef cattle with IR sensor module linked to ubiquitous ICT platform as a solution for controlling health conditions of Korean beef cattle and improving the efficiency of livestock farming operations at individual farm, regional, and national level by converging ubiquitous ICT platform and livestock farming practices. Successfully employing the state-of-the-art IT technologies of Korea, the system proposed herein is expected to make Korea's livestock farming industry more sustainable and help the nation to secure technological preeminence in the global livestock products market.

• Journal of Digital Convergence
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• v.18 no.8
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• pp.281-291
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• 2020

This study identifies the factors influencing Quality of Life (QoL) in both male and female workers with diabetes mellitus and examines the differences between them. Using data from the Korea National Health and Nutrition Examination Survey (KNHANES) for 2010-2017, 1693 workers (1082 males; 611 females), aged 19 or over, with diabetes mellitus were enrolled in the study. Data were analyzed by complex sample linear regression using SPSS/WIN 23.0. The factors influencing QoL differed between males and females. The common factors included household income, education, job, stress, disease duration, and disease complications. The additional factors in males included working style, and, in females included age, marital status, drinking habits, and the treatment and control of the disease. Males had a higher QoL than females in all the sub-factors. Patients with diabetes mellitus require gender-specific intervention and governmental and social policies that can support it must be developed.

• Journal of Digital Convergence
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• v.11 no.10
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• pp.571-576
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• 2013

The purpose of this study is to investigate work related diseases in Korean firefighters and to prepare the preventive measure for health management for the firefighters. Structured self-reported questionnaire was distributed to the firefighters. The result revealed that 37.7% of fire fighters had chronic diseases and 12.3% had chronic low back pains. The affected parts included lumbar region(41.5%), shoulder(33.0%), and neck(23.6%). The affected parts caused physical pain and work discomfort for more than a month. A total of 54.1% firefighters visited to the hospital within a year. This results suggest that it is necessary to develop the health promotion program for the prevention of musculoskeletal disease and regular health checkup for the acute disorders caused by workload.

• Journal of Digital Convergence
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• v.17 no.2
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• pp.313-318
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• 2019

The purpose of this study is to investigate whether there is a difference in the incidence of the black circle border of iris(skin disease) according to the iris constitution. Iris was taken for 100 adults living in Seoul. Iris was photographed using the iris camera DV-2H, a blue focus development product. Statistical significance was tested by correlation analysis, and the occurrence of black circle border of iris was low negative correlation(p<0.01). As mentioned above, we know that the occurrence of black circle border of iris differs according to the iris constitution, and by using it actively, it will help health promotion about skin. There is a need to study the changes of iris in the cause of skin disease by using a blood test to analyze the cause of the skin disease in the future.

• Journal of Korean Society for Quality Management
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• v.48 no.4
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• pp.581-596
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• 2020

Purpose: purpose of this study was to propose the web application platform which can be to detect and discriminate various diseases and pest of tomato plant based on the large amount of disease image data observed in the facility or the open field. Methods: The deep learning algorithms uesed at the web applivation platform are consisted as the combining form of Faster R-CNN with the pre-trained convolution neural network (CNN) models such as SSD_mobilenet v1, Inception v2, Resnet50 and Resnet101 models. To evaluate the superiority of the newly proposed web application platform, we collected 850 images of four diseases such as Bacterial cankers, Late blight, Leaf miners, and Powdery mildew that occur the most frequent in tomato plants. Of these, 750 were used to learn the algorithm, and the remaining 100 images were used to evaluate the algorithm. Results: From the experiments, the deep learning algorithm combining Faster R-CNN with SSD_mobilnet v1, Inception v2, Resnet50, and Restnet101 showed detection accuracy of 31.0%, 87.7%, 84.4%, and 90.8% respectively. Finally, we constructed a web application platform that can detect and discriminate various tomato deseases using best deep learning algorithm. If farmers uploaded image captured by their digital cameras such as smart phone camera or DSLR (Digital Single Lens Reflex) camera, then they can receive an information for detection, identification and disease control about captured tomato disease through the proposed web application platform. Conclusion: Incheon Port needs to act actively paying.

• The Journal of the Convergence on Culture Technology
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• v.8 no.2
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• pp.1-6
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• 2022

Lifelog is a digital record of an individual collected from various digital sensors, and includes activity amount, sleep information, weight change, body mass, muscle mass, fat mass, etc. Recently, as wearable devices have become common, a lot of high-quality lifelog data is being produced. Lifelog data shows the state of an individual's body, and can be used not only for individual health care, but also for causes and treatment of diseases. However, at present, AI/ML-based correlation analysis and personalization are not reflected. It is only at the level of presenting simple records or fragmentary statistics. Therefore, in this paper, the correlation/relationship between lifelog data and disease, and AI/ML technology inside lifelog data are examined, and furthermore, a lifelog data analysis process based on AI/ML is proposed. The analysis process is demonstrated with the data collected in the actual Galaxy Watch. Finally, we propose a future convergence service roadmap including lifelog data, diet, health information, and disease information.