• Tuberculosis and Respiratory Diseases
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• v.86 no.2
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• pp.82-93
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• 2023

Tuberculosis (TB) is a significant public health concern. Globally, TB is among the top 10 and the leading cause of death due to a single infectious agent. Providing standard anti-TB therapy for at least 6 months is recommended as one of the crucial strategies to control the TB epidemic. However, the long duration of TB treatment raised the issue of non-adherence. Non-adherence to TB therapy could negatively affect clinical and public health outcomes. Thus, directly observed therapy (DOT) has been introduced as a standard strategy to improve anti-TB medication adherence. Nonetheless, the DOT approach has been criticized due to inconvenience, stigma, reduced economic productivity, and reduced quality of life, which ultimately could complicate adherence issues. Apart from that, its effectiveness in improving anti-TB adherence is debatable. Therefore, digital technology could be an essential tool to enhance the implementation of DOT. Incorporating the health belief model (HBM) into digital technology can further increase its effectiveness in changing behavior and improving medication adherence. This article aimed to review the latest evidence regarding TB medication non-adherence, its associated factors, DOT's efficacy and its alternatives, and the use of digital technology and HBM in improving medication adherence. This paper used the narrative review methodology to analyze related articles to address the study objectives. Conventional DOT has several disadvantages in TB management. Integrating HBM in digital technology development is potentially effective in improving medication adherence. Digital technology provides an opportunity to improve medication adherence to overcome various issues related to DOT implementation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.728-739
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• 2020

Using webometric big data, this study examines the diversity of online information sources about the novel coronavirus causing the COVID-19 pandemic. Specifically, it focuses on some 28 countries where confirmed coronavirus cases occurred in February 2020. In the results, the online visibility of Australia, Canada, and Italy was the highest, based on their producing the most relevant information. There was a statistically significant correlation between the hit counts per country and the frequency of visiting the domains that act as information channels. Interestingly, Japan, China, and Singapore, which had a large number of confirmed cases at that time, were providing web data related to the novel coronavirus. Online sources were classified using an N-tuple helix model. The results showed that government agencies were the largest supplier of coronavirus information in cyberspace. Furthermore, the two-mode network technique revealed that media companies, university hospitals, and public healthcare centers had taken a positive attitude towards online circulation of coronavirus research and epidemic prevention information. However, semantic network analysis showed that health, school, home, and public had high centrality values. This means that people were concerned not only about personal prevention rules caused by the coronavirus outbreak, but also about response plans caused by life inconveniences and operational obstacles.

• Journal of the Korea Convergence Society
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• v.9 no.6
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• pp.77-88
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• 2018

"Standard Precautions" (SP) is important for nursing students as it will lead to the protection of health professionals from infectious diseases and prevention of the wide spread of epidemic illnesses. Therefore, this study investigated factors influencing nursing students' attitudes toward SP. Data were collected from 291 nursing students from May to June, in 2016. According to the results, perceived benefit (4.26) was the highest among sub factors of the health belief model, test score of SP was 78.8%, and attitude score (4 point scale) was 3.63. Perceived sensitivity, perceived benefits, perceived barriers, self-efficacy, knowledge about SP showed significant correlations with the attitudes towards SP. Among sub-factors of the health beliefs, perceived sensitivity (${\beta}=.152$, p<.05) and perceived barrier (${\beta}=-.125$, p<.05) were found to influence nursing students' attitudes toward SP (F= 5.680, p<.001). Hence, it can be concluded that a convergence education program promoting health belief is needed for improving attitudes toward SP among nursing students.

• Research in Plant Disease
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• v.8 no.4
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• pp.199-206
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• 2002

It was investigated on the relationship of the rice blast epidemics and the real-time meteorological factors, at the experimental paddy field in 1997. Weather factors(temperature, relative humidity, irradiation, precipitation, the direction of wind, wind speed, soil temperature and leaf-wetness, etc) were measured by using the automated weather station. The most influenced weather factor to blast epidemics, was the average max-temp($R^2$= 0.95) during 10 days before leaf blast epidemics, while the least thing was wind speed($R^2$= 0.24). The most potential weather factors correlated with the blast epidemics were T-ave(average temperature), T-max(maximum temperature), RH(Relative Humidity) and RD(Relative Humidity > 90% hrs). A statistics model(the regression equation) of the blast epidemics with the potential weather factors, was established as tallows ; Y = -3410.91 - 23.91 $\times$ T-ave ＋ 28.56 $\times$ T-max ＋ 41.0 $\times$ RH - 3.75 $\times$ RD, ($R^2$= 0.99). (T-ave >= 19$^{\circ}C$, T-max - T-ave >= 5.2$^{\circ}C$ and RH% >= 90.4%). According to the fitness test($\chi$$^2$) of the model, the observed blast disease severity was quite close to those expected.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.6
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• pp.2889-2894
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• 2016

This study aimed to modify behavior regarding liver fluke and cholangiocarcinoma prevention in Chumphuang district, Nakhon Ratchasima province, Thailand through integrated learning. A total of 180 participants were included through purposive selection of high-risk scores on verbal screening. Participants attended the health education program which applied the health belief model included family based, knowledge station based, academic merit based and community based learning. Data were collected using a questionnaire composed of 4 parts: 1) personal information, 2) knowledge, 3) perceived susceptibility, severity, benefits, and barriers, 4) practice regarding liver fluke and cholangiocarcinoma prevention. The result revealed that the majority were female (79.9%), age ${\geq}60$ years old (33.2%), primary school educational level (76.1%), and agricultural occupation (70.1%). The mean scores of knowledge, perception, and practice to liver fluke and cholangiocarcinoma prevention, before participated the integrative learning were low, moderate, and low, respectively. Meanwhile, the mean score of knowledge, perceived susceptibility, severity, benefits, and barriers, and practice regarding liver fluke and cholangiocarcinoma prevention, were higher with statistical significance after participation in the integrated learning. This finding indicates that health education programs may successfully modify health behavior in the rural communities. Therefore they may useful for further work behavior modification in other epidemic areas.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2018.10a
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• pp.73-73
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• 2018

Bacterial leaf blight(BLB), caused by X. oryzae pv. oryzae(Xoo), is one of the most destructive diseases of rice due to its high epidemic potential. Understanding BLB resistance at a genetic level is important to further improve the rice breeding that provides one of the best approaches to control BLB disease. In the present investigation, a collection of 192 accessions was used in the genome-wide association study (GWAS) for BLB resistance loci against four Korean races of Xoo that were represented by the prevailing BLB isolates under Xoo differential system. A total of 192 accessions of rice germplasm were selected on the basis of the bioassay using four isolated races of Xoo such as K1, K2, K3 and K3a. The selected accessions was used to prepare 384-plex genotyping by sequencing (GBS) libraries and Illumina HiSeq 2000 paired- end read was used for GBS sequencing. GWAS was conducted using T ASSEL 5.0. The T ASSEL program uses a mixed linear model (MLM). T he results of the bioassay using a selected set of 192 accessions showed that a large number of accessions (93.75%) were resistant to K1 race, while the least number of accessions (34.37%) resisted K3a race. For races K2 and K3, the resistant germplasm proportion remained between 66.67 to 70.83%. T he genotypic data produced SNP matrix for a total of 293,379 SNPs. After imputation the missing data was removed, which exhibited 34,724 SNPs for association analysis. GWAS results showed strong signals of association at a threshold of [-log10(P-value)] more than5 (K1 and K2) and more than4 (K3 and K3a) for nine of the 39 SNPs, which are plausible candidate loci of resistance genes. T hese SNP loci were positioned on rice chromosome 2, 9, and 11 for K1 and K2 races, whereas on chromosome 4, 6, 11, and 12 for K3 and K3a races. The significant loci detected have also been illustrated, NBS-LRR type disease resistance protein, SNARE domain containing protein, Histone deacetylase 19, NADP-dependent oxidoreductase, and other expressed and unknown proteins. Our results provide a better understanding of the distribution of genetic variation of BLB resistance to Korean pathogen races and breeding of resistant rice.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.3
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• pp.1111-1114
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• 2016

Opisthorchiasis is a major problem in Thailand particularly in northeast region which also has a high incidence of cholangiocarcinomas. Since health modification is needed, this quasi-experimental study aimed to assess the effectiveness of a health education program based on self-efficacy and social support in Tha Tum district, Surin province, Thailand. A total of 70 participants were purposive selected with a history of opisthorchiasis. Participants were divided into experimental and control groups, each with 35 subjects. The experimental group received a health education program composed of: (1) knowledge improvement, lectured with multimedia, demonstration, brochure, and handbook; (2) group discussion about their health beliefs, sharing their ideas and experience; and (3) social support from village health volunteers (VHV), heads of villages (HV), friends, and members of families, and public health officer (PHO). Follow-up was by PHO/VHV/HV, with provision of certificates and flasg for household that did not eat raw fish. Data were collected by predesigned questionnaires after implementation of the program for 3 months. Comparative data was analyzed by paired simple t-test and independent t-test. The results revealed that the experimental group had mean score of knowledge higher more than before the experiment (mean difference=3.1, t=3.915, 95%CI-3.3, -1.8 p-value=0.001), and the control group (mean difference=2.5, t=4.196, 95%CI=1.4, 3.6, p-value=0.001) with statistical significance. The mean scores of practice were higher than before the experiment (mean difference=4.6, t=4.331, 95%CI-5.3, -3.1, p-value=0.001), and control group (mean difference=4.4, t=6.142, 95%CI=4.2, 7.9, p-value=0.001). The mean scores of perceived susceptibility and perceived severity of opisthorchiasis, al well as perceived benefits and perceived barriers to prevention of opisthorchiasis, were also higher than before the experiment and in the control group (p-value <0.001). In conclusion, this was a successful health education program for liver fluke avoidance. Therefore, it may useful for further behavior modification in the other epidemic areas.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2019.04a
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• pp.62-62
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• 2019

Bacterial leaf blight(BLB), caused by X. oryzae pv. oryzae(Xoo), is one of the most destructive diseases of rice due to its high epidemic potential. Understanding BLB resistance at a genetic level is important to further improve the rice breeding that provides one of the best approaches to control BLB disease. In the present investigation, a collection of 192 accessions was used in the genome-wide association study (GWAS) for BLB resistance loci against four Korean races of Xoo that were represented by the prevailing BLB isolates under Xoo differential system. A total of 192 accessions of rice germplasm were selected on the basis of the bioassay using four isolated races of Xoo such as K1 and K2. The selected accessions was used to prepare 384-plex genotyping by sequencing (GBS) libraries and Illumina HiSeq 2000 pairedend read was used for GBS sequencing. GWAS was conducted using TASSEL 5.0. The TASSEL program uses a mixed linear model (MLM). The results of the bioassay using a selected set of 192 accessions showed that a large number of accessions (93.75%) were resistant to K1 race and K2 resistant germplasm proportion remained between 66.67. The genotypic data produced SNP matrix for a total of 293,379 SNPs. After imputation the missing data was removed, which exhibited 34,724 SNPs for association analysis. GWAS results showed strong signals of association at a threshold of [-log10(P-value)] more than 5 (K1 and K2) for nine of the 39 SNPs, which are plausible candidate loci of resistance genes. These SNP loci were positioned on rice chromosome 2, 9, and 11 for K1 and K2 races. The significant loci detected have also been illustrated and make the CPAS markers for NBS-LRR type disease resistance protein, SNARE domain containing protein, Histone deacetylase 19, NADP-dependent oxidoreductase, and other expressed and unknown proteins. Our results provide a better understanding of the distribution of genetic variation of BLB resistance to Korean pathogen races and breeding of resistant rice.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.5
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• pp.157-166
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• 2022

Exercise is necessary for a healthy life, but it is recommended that it be conducted in a non-face-to-face environment in the context of an epidemic such as COVID-19. However, in the existing non-face-to-face exercise content, it is possible to recognize exercise movements, but the process of interpreting and providing feedback information is not automated. Therefore, in this paper, to solve this problem, we propose a method of creating a formalized rule to track the contents of exercise and the motions that constitute it. To make such a rule, first make a rule for the overall exercise content, and then create a tracking rule for the motions that make up the exercise. A motion tracking rule can be created by dividing the motion into steps and defining a key frame pose that divides the steps, and creating a transition rule between states and states represented by the key frame poses. The rules created in this way are premised on the use of posture and motion recognition technology using motion capture equipment, and are used for logical development for automation of application of these technologies. By using the rules proposed in this paper, not only recognizing the motions appearing in the exercise process, but also automating the interpretation of the entire motion process, making it possible to produce more advanced contents such as an artificial intelligence training system. Accordingly, the quality of feedback on the exercise process can be improved.

• Journal of Internet Computing and Services
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• v.21 no.5
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• pp.139-148
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• 2020

Infectious diseases have long plagued mankind, and predicting and preventing them has been a big challenge for mankind. For this reasen, various studies have been conducted so far to predict infectious diseases. Most of the early studies relied on epidemiological data from the Centers for Disease Control and Prevention (CDC), and the problem was that the data provided by the CDC was updated only once a week, making it difficult to predict the number of real-time disease outbreaks. However, with the emergence of various Internet media due to the recent development of IT technology, studies have been conducted to predict the occurrence of infectious diseases through web data, and most of the studies we have researched have been using single Web data to predict diseases. However, disease forecasting through a single Web data has the disadvantage of having difficulty collecting large amounts of learning data and making accurate predictions through models for recent outbreaks such as "COVID-19". Thus, we would like to demonstrate through experiments that models that use multiple Web data to predict the occurrence of infectious diseases through LSTM models are more accurate than those that use single Web data and suggest models suitable for predicting infectious diseases. In this experiment, we predicted the occurrence of "Malaria" and "Epidemic-parotitis" using a single web data model and the model we propose. A total of 104 weeks of NEWS, SNS, and search query data were collected, of which 75 weeks were used as learning data and 29 weeks were used as verification data. In the experiment we predicted verification data using our proposed model and single web data, Pearson correlation coefficient for the predicted results of our proposed model showed the highest similarity at 0.94, 0.86, and RMSE was also the lowest at 0.19, 0.07.