• The Journal of the Korea Contents Association
• /
• v.21 no.1
• /
• pp.552-560
• /
• 2021

Currently, the domestic aquaculture industry is pursuing smartization, but it is still proceeding with human subjective judgment in many processes in the aquaculture stage. The prerequisite for the smart aquaculture industry is to effectively grasp the condition of fish in the farm. If real-time monitoring is possible by identifying the number of fish populations, size, pathways, and speed of movement, various forms of automation such as automatic feed supply and disease determination can be carried out. In this study, we proposed an algorithm to identify the state of fish in real time using underwater video data. The fish detection performance was compared and evaluated by applying the latest deep learning-based object detection models, and an algorithm was proposed to measure fish object identification, path tracking, and moving speed in continuous image frames in the video using the fish detection results. The proposed algorithm showed 92% object detection performance (based on F1-score), and it was confirmed that it effectively tracks a large number of fish objects in real time on the actual test video. It is expected that the algorithm proposed in this paper can be effectively used in various smart farming technologies such as automatic feed feeding and fish disease prediction in the future.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.20 no.6
• /
• pp.55-65
• /
• 2021

In January 2020, the first COVID-19 confirmed patient occurred in Korea, and the pandemic continues to this day. In unprecedented situations, COVID-19 also affected the transportation sector, and there were no appropriate measures against changes in traffic volume and use of public transportation due to changes in citizens' lifestyles. Currently, each local government has not established separate measures for pandemic disease measures. In order to establish future disease countermeasures in the transportation sector, a predictive model was developed by analyzing the traffic volume and the number of public transportation uses, and conducting correlation analysis with the current status of COVID-19. As a result of the analysis, the traffic volume decreased, but the traffic volume decreased due to the increase in personal transportation, but it did not reach the number of public transportation uses. In addition, it was analyzed that the use of public transportation was initially affected by the number of confirmed cases, but over time, it was more sensitive to death and mortality than to the number of confirmed cases.

• Journal of the Korean Society of Radiology
• /
• v.16 no.4
• /
• pp.453-462
• /
• 2022

In this paper, the artificial intelligence (AI) technology used in the medical image analysis field was analyzed through a literature review. Literature searches were conducted on PubMed, ResearchGate, Google and Cochrane Review using the key word. Through literature search, 114 abstracts were searched, and 98 abstracts were reviewed, excluding 16 duplicates. In the reviewed literature, AI is applied in classification, localization, disease detection, disease segmentation, and fit degree of registration images. In machine learning (ML), prior feature extraction and inputting the extracted feature values into the neural network have disappeared. Instead, it appears that the neural network is changing to a deep learning (DL) method with multiple hidden layers. The reason is thought to be that feature extraction is processed in the DL process due to the increase in the amount of memory of the computer, the improvement of the calculation speed, and the construction of big data. In order to apply the analysis of medical images using AI to medical care, the role of physicians is important. Physicians must be able to interpret and analyze the predictions of AI algorithms. Additional medical education and professional development for existing physicians is needed to understand AI. Also, it seems that a revised curriculum for learners in medical school is needed.

• Journal of agricultural medicine and community health
• /
• v.25 no.2
• /
• pp.231-244
• /
• 2000

Classification and research trends were studied to analyze a total of 240 original articles that have been published in 34 volumes of The Korean Journal of Rural Medicine from 1976 to 1999. The results were as follows: 1. A total of 337 articles were published. Among them, 240(71.2%) articles were classified as original articles. This number has been increasing significantly over the years as the number of the articles was 13 in the 1970s, 73 in the 1980s, and 154 in the 1990s. 2. There were 10 authors in the original articles and 55(22.9%) of them were written by 3 of them. There were five research institutions involved in the articles, and 106(44.2%) of the articles were done by one research group. 3. In the original articles. 24(10.0%) were noted to be done using research funds, and only 6(2.5%) were written in English. 4. In the view of the research styles of the original articles, 115(47.9%) used analytical study, 92(38.3%) used technical study, 21(9.2%) used experimental study, and 6(2.5%) used case reports. In the 1970s, 13(100.0%) articles used technical study, and in the 1980s, 47(64.4%) used technical studies and 19(26.0%) used analytical studies. However, in the 1990s, 96(62.8%) articles used analytical studies and 32(20.9%) used technical studies. The statistical methods most commonly used in the articles were technical statistics, the ${\chi}^2$-test, and the t-test respectively. 5. On the classification into three different research fields, 105(43.8%) articles were classified as health management, 96(40.0%) as disease epidemiology, and 39(16.3%) as rural environment and rural occupational disorders. In the 1970s, 12 (92.3 %) of the articles were on disease epidemiology and 1(7.7%) on health management were published. In the 1980s, 33(45.2%) articles on disease epidemiology, 29(39.7%) on health control, and 11(15.1%) on rural environment and rural occupational disorders were recorded. In the 1990s, however, 75(48.7%) articles were on health control, 51(33.1%) on disease control, and 28(18.2%) on the rural environment and rural occupational disorders. 6. According to the research subjects in each research field, the 39 articles in rural environment and rural occupational disorders were composed of 8(20.5%) articles on pesticide intoxication, 7(17,9%) on farmer's diseases, 7(17.9%) on vinyl-house diseases, and 6(15.4%) on accidents. From a total of 96 articles in disease epidemiology 56(58.3%) articles were on parasites, 16(16.7%) on non-infectious diseases, 12(12.5) on infectious diseases. From 105 articles in health control 25(23.8%) articles were on medical care utilization patterns, 18(17.1%) on the health care delivery system, and 13(12.4%) on maternal and child health. In the analysis of the 10 most prevalent subjects dealt in the above articles, 6(46.2%) articles were on parasites and 4(30.8%) on non-infectious diseases were recorded in the 1970s. In the 1980s, 28(38.4%) were on parasites. 9(12.3%) on the health care system, 7(9.6%) on medical care utilization patterns, 5(6.8%) on maternal and child health, and 4(5.5%) were on pesticide intoxication. In the 1990s, 22(14.3%) articles were on parasites. 18(11.7%) on medical care utilization patterns, 16(10.4%) on senile health, 14(9.1%) on the health care system, 10(6.5%) on infectious diseases, arid 10(6.5%) were on non-infectious diseases. In conclusion, the research activity on rural health has been strengthened in this country because the original articles in The Korean Journal of Rural Medicine have significantly increased in the past 24 years. In the 1970s and 1980s, research on disease epidemiology was most prevalent, but in the 1990s papers on health care were most popular. In addition, the articles on parasites were most frequently published in the 1970s, 1980s, and 1990s, showing that parasitic problem was the main theme in those eras. However, in the 1990s, it was evident that the articles on parasites were decreasing and articles on the subject of medical care utilization patterns and senile health increased. Hereafter it was expected that research on health care would be more common in rural health in Korea.

• Journal of Digital Convergence
• /
• v.13 no.8
• /
• pp.419-429
• /
• 2015

We investigate how the regional prevalence of hyperlipidemia is affected by health-related and socioeconomic factors with a special emphasis on geographic variations. We focus on the likelihood of hyperlipidemia as function of various region-specific attributes. We analysis a data set at the level of 249 small administrative districts collected from 2012 Korean Community Health Survey by Korea Centers for Disease Control and Prevention. To estimate, we use several methods including correlation analysis, multiple regression and decision tree model. We find that the average prevalence of hyperlipidemia in 249 small districts is 9.6% and its coefficient of variation is 28.3%. Prevalence of hyperlipidemia in continental and capital regions is higher than in southeast coastal regions. Further findings using decision tree model suggest that variations of hyperlipidemia prevalence between regions is more likely to be associated with rate of employee, level of stress, prevalence of hypertension, angina pectoris, and osteoarthritis in their regions.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.22 no.4
• /
• pp.386-392
• /
• 2002

Ultrasonic has been proposed as an attractive means of detecting bone loss. There have been several commercial ultrasound devices developed for measuring the heel to predict fracture at other bones. However, these devices select only single point of heel bone as measurement site. It causes poor assessment of bone quality due to the error of transducer positioning. In an effort to improve current ultrasound systems, we evaluated the linear scanning method which provides better prediction of bone quality and an accurate image of bone shape. The system used in this study biaxially scans a heel bone using automated linear scanning technique. The results demonstrated that the values of ultrasound parameters varied with different positions within bone specimen. It has been also found that the linear scanning method could better pre야ct bone quality, eliminating the error of transducer positioning.

• The Journal of the Korea Contents Association
• /
• v.17 no.2
• /
• pp.198-206
• /
• 2017

This study was conducted to identify the relationship between personal competence of health care(PCHC) and quality of life among middle-aged adults. Data were collected using questionnaires from 412 middle-aged parents of university student. There were significant differences in PCHC and quality of life according to educational level, family support, monthly income, exercise over 3times a week, subjective health status. However, religion and drinking made a differece only in PCHC on the other hand, sex and disease affected quality of life. All subdomains of PCHC had significant positive correlations with quality of life. Factors predicting quality of life among subdomains of PCHC were health perception, sociocultural relationship and socioeconomical involvement, which explained about 50.3%. These results indicate a need to develop programs to improve health perception, sociocultural and socioeconomical competence for middle-aged adults.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.20 no.4
• /
• pp.683-690
• /
• 2016

In modern society, disasters frequently occur, and the effect is getting more massive. Also, unpredictable future increases anxiety about social security. Accordingly, in order to prevent national-scale emergency from happening, it is highly required governments' role as ICT power nation and transition to disaster management system using big data applied service. Thus, e-gov necessarily acquires disaster response system in order to predict and manage disasters. Disasters are linked with some attributes of modern society in diversity, complexity and unpredictability, so various approach and remedies of them will appease the nation's anxiety upon them. For this reason, this manuscript suggests epidemics preactive warning algorithm model as a mean of reduce national anxiety on disaster using big data for social security. Also, by recognizing the importance of e-gov and analyzing problems in weak disaster management system, it suggests political implication for disaster response.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.20 no.12
• /
• pp.2348-2354
• /
• 2016

In recent days, IoT (Internet of Things) technology has been widely used in the field of agriculture, which enables the collection of environmental data and biometric data into the database. The availability of big data on agriculture results in the increase of the machine learning based analysis. Through the analysis, it is possible to forecast agricultural production and the diseases of livestock, thus helping the efficient decision making in the management of smart farm. Herein, we use the environmental and biometric data of Smart Pig farm to derive the accurate relationship model between the environmental information and the daily weight increase of swine and verify the accuracy of the derived model. To this end, we applied the M5P tree algorithm of machine learning which reveals that the wind speed is the major factor which affects the daily weight increase of swine.

• Journal of Digital Convergence
• /
• v.11 no.6
• /
• pp.289-298
• /
• 2013

The objective of this study was to predict the changes in the duration of hospital stay, hospital admission fee, costs of drugs, changes in laboratory cost, material cost, total medical cost, adjusted amount of treatment and the efficacy of obstetrics and gynecology DRG system. The cost of drugs showed the greatest change and was followed by materials for medical examinations and the change in methods of medical examinations. In the analysis of the quantity of medical service the profit of medical examinations were influenced mostly by the duration of hospital stay. The results and data in this study could be used as a basis of future DRG system protocols and will be utilized so that hospitals can build a efficient medical system.