• Particle and aerosol research
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• v.5 no.2
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• pp.53-62
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• 2009

In this study, the continuous monitoring of the concentration of PM-10 atmospheric particulate matter using beta ray attenuation method was compared with gravimetric method from September, 2006 to August, 2007. On the effects of the PM-10 concentration and mass difference by relative humidity and precipitation were considered. The result showed that the measurement error between beta ray method and gravimetric method are within -3~6% in average, which means PM-10 concentration data with beta ray method are relatively comparable. The current study also shows that the high PM-10 concentration events are mainly due to haze, Asian dust, and high relative humidity and the PM-10 mass concentration is closely related with relative humidity and precipitation events. Based on daily mean data, the PM-10 increases as relative humidity increases up to 70~80%, then decreases over 80% due to the precipitation. However, the distinct measurement discrepancy was not shown between beta ray method and gravimetric method based on current results. Consequently, this study shows that the collocated measurement in different instrument is essential in order to quantify the accuracy of PM-10. Furthermore, the more comprehensive and spatially distributed comparison is needed and this is remained for future study.

• Ocean and Polar Research
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• v.31 no.1
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• pp.71-76
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• 2009

Drastic changes in the water quality and phytoplankton community of the new Saemankeum Lakeduring the first decade following the construction of the Saemankeum Sea Wall has been considered to be unavoidable. Input of eutrophicated water through the Mankyeong River and Dongjin River might produce more direct effects on the water quality and phytoplankton community, which lead us to launch a long-term semi-weekly investigation at the "Mankyeong Bridge" monitoring point to resolve its short-term effect as well as long-term stabilization of the ecosystem in the new Saemankeum Lake. During 15 months starting from June 2006, the water temperature varied in accordance with the typical seasonal variations in temperate on the coasts, and no significant daily variations evoked by tidal cycle could be detected. However, there was an inverse relationship between seasonal precipitation and salinity even though the range in annual variation was drastically reduced right after the construction of the Saemankeum Sea Wall. Species richness in the phytoplankton community was also reduced due to the narrowed annual range of salinity, which would eliminate the mid-high salinity species from the Mankyeong Bridge monitoring point. Similarly, species diversity was decreased with increased dominance of the phytoplankton community after the construction. Between the two summer seasons during the present study, species diversity was higher in 2007 than in 2006, which might indicate the early stage of a gradual stabilization in the ecosystem including the phytoplankton community at the monitoring station. The phytoplankton community thus needs to be monitored on a long-term basis to identify indirect signals that can be used to assess the stability of the ecosystem in the young Saemankeum Lake.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.1
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• pp.14-19
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• 2018

Recently, the smart health care industry has been rising rapidly and interest and efforts for public health have been greatly increased. As a result, the public does not visit medical specialists and medical facilities, but the desire to check their health condition in everyday life is increased. Therefore, many domestic and foreign companies continuously research and develop wearable devices that can measure body activity information anytime and anywhere And the market. Especially, it is used for heart activity measurement device using pulse wave sensor and electrocardiogram sensor. However, in this study, a monitoring system that can detect cardiac activity using cardiac sounds, heart sound measurement rather than pulse wave measurement and electrocardiogram measurement, was performed and its performance was evaluated. Experimental results confirmed the predictability of cardiac heart rate and heart valve disease during daily living.

• Healthcare Informatics Research
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• v.24 no.4
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• pp.283-291
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• 2018

Objectives: To identify the current status of smartphone usage and to describe the needs for smartphone-based cardiac telerehabilitation of cardiac patients. Methods: In 2016, a questionnaire survey was conducted in a supervised ambulatory cardiac rehabilitation (CR) program in a university affiliated hospital with the participation of heart failure or heart transplantation patients who were smartphone users. The questionnaire included questions regarding smartphone usage, demands for smartphone-based disease education, and home health monitoring systems. Results were described and analyzed according to principal diagnosis. Results: Ninety-six patients (66% male; mean age, $5{\pm}11$ years), including 56 heart failure and 40 heart transplantation patients, completed the survey (completion rate, 95%). The median daily smartphone usage time was 120 minutes (interquartile range, 60-300), and the most frequently used smartphone function was text messaging (61.5%). Of the patients, 26% stated that they searched for health-related information using their smartphones more than 1 time per week. The major source of health-related information was Internet browsing (50.0%), and the least sought source was the hospital's website (3.1%). Patients with heart failure expressed significantly higher needs for disease education on treatment plan, home health monitoring of blood pressure, and body weight (${\chi}^2=5.79$, 6.27, 4.50, p < 0.05). Heart transplantation patients expressed a significant need for home health monitoring of body temperature (${\chi}^2=5.25$, p < 0.05). Conclusions: Heart failure and heart transplantation patients show high usage of and interest in mobile health technology. A smartphone-based cardiac telerehabilitation program should be developed based on high demand areas and modified to suit to each principal diagnosis.

• Journal of Korean Society of Water and Wastewater
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• v.33 no.2
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• pp.151-158
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• 2019

Objectives of this study were to identify the hotspot for displacement of the on-line water quality sensors, in order to detect illicit discharge of untreated wastewater. A total of twenty-six water quality parameters were measured in sewer networks of the industrial complex located in Daejeon city as a test-bed site of this study. For the water qualities measured on a daily basis by 2-hour interval, the self-organizing maps(SOMs), one of the artificial neural networks(ANNs), were applied to classify the catchments to the clusters in accordance with patterns of water qualities discharged, and to determine the hotspot for priority sensor allocation in the study. The results revealed that the catchments were classified into four clusters in terms of extent of water qualities, in which the grouping were validated by the Euclidean distance and Davies-Bouldin index. Of the on-line sensors, total organic carbon(TOC) sensor, selected to be suitable for organic pollutants monitoring, would be effective to be allocated in D and a part of E catchments. Pb sensor, of heavy metals, would be suitable to be displaced in A and a part of B catchments.

• Korean Journal of Childcare and Education
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• v.17 no.3
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• pp.65-87
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• 2021

Objective: This study aimed to examine the effects of maternal monitoring, shared activities with children, maternal education-oriented behavior, and allowing children to own smart-phones on smart media usage patterns based on smart-phone usage time and purposes among elementary school children. Methods: The participants were 1,315 second-grade elementary school children from the 9th wave of PSKC. Latent profile analysis and the three-step estimation approach were used to examine the determinants of the latent profile and the effects of maternal parenting on the profile. Results: Four latent profiles were identified: 'High-level usage & Entertaining oriented,' 'Moderate-level usage & Social/entertaining oriented,' 'Moderate-level usage & Learning oriented,' and 'Low-level usage.' Additionally, results showed that each profile can be predicted by maternal monitoring, education-oriented behavior, and permitting children to own smart-phones. Conclusion/Implications: Our outcomes suggested that it would be necessary to understand the smart media usage patterns of elementary school children, considering both the amount of time spent with smart media and purposes of uses. Further, it is helpful for mothers to monitor children's daily activities, support their educational activities, and take the role of gatekeeper for smart media as a way of appropriate guidance for their children's use of smart media.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.12-18
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• 2021

This paper proposes a framework for the development of the health recommender system, designed to cater COVID-19 symptoms' self-assessment and monitoring as well as to provide recommendations for self-care and medical treatments. The aim is to provide an online platform for Patient Under Investigation (PUI) and close contacts with positive COVID-19 cases in Malaysia who are under home quarantine to perform daily self-assessment in order to monitor their own symptoms' development. To achieve this, three main phases of research methods have been conducted where interviews have been done to thirty former COVID-19 patients in order to investigate the symptoms and practices conducted by the Malaysia Ministry of Health (MOH) in assessing and monitoring COVID-19 patients who were under home quarantine. From the interviews, an algorithm using user-based collaborative filtering technique with Pearson correlation coefficient similarity measure is designed to cater the self-assessment and symptoms monitoring as well as providing recommendations for self-care treatments as well as medical interventions if the symptoms worsen during the 14-days quarantine. The proposed framework will involve the development of the health recommender system for COVID-19 self-assessment and treatments using the progressive web application method with cloud database and PHP codes.

• Health Policy and Management
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• v.33 no.1
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• pp.29-39
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• 2023

Background: Breaking the chain of disease transmission from overseas is necessary to control new infectious diseases such as coronavirus disease 2019 effectively. In this study, we developed a mobile app called Self-Symptom Checker (SSC) to monitor the health of inbound travelers. Methods: SSC was developed for general users and administrators. The functions of SSC include non-repudiation using QR (quick response) codes, monitoring fever and respiratory symptoms, and requiring persons showing symptoms to undergo polymerase chain reaction tests at nearby screening stations following a review of reported symptoms by the Korea Disease Control and Prevention Agency, as well as making phone calls, via artificial intelligence or public health personnel, to individuals who have not entered symptoms to provide the necessary information. Results: From February 12 to March 27, 2020, 165,000 people who were subjected to the special entry procedure installed SSC. The expected number of public health officers and related resources needed per day would be 800 if only the phone was used to perform symptom monitoring during the above period. Conclusion: By applying SSC, more effective symptom monitoring was possible. The daily average number of health officers decreased to 100, or 13% of the initial estimate. SSC reduces the work burden on public healthcare personnel. SSC is an electronic solution conceived in response to health questionnaires completed by inbound travelers specified in the World Health Organization International Health Regulations as a requirement in the event of a pandemic.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.2
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• pp.62-69
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• 2022

An electrocardiogram (ECG) is one of the most important biosignals, and in particular, continuous ECG monitoring is very important in patients with arrhythmia. There are many different types of arrhythmia (sinus node, sinus tachycardia, atrial premature beat (APB), and ventricular fibrillation) depending on the cause, and continuous ECG monitoring during daily life is very important for early diagnosis of arrhythmias and setting treatment directions. The ECG signal of arrhythmia patients is very unstable, and it is difficult to detect the R-peak point, which is a key feature for automatic arrhythmias detection. In this study, we develped a continuous measuring Holter ECG monitoring device and software for analysis and confirmed the utility of R-peak of the ECG signal with MIT-BIH arrhythmia database. In future studies, it needs the validation of algorithms and clinical data for morphological classification and prediction of arrhythmias due to various etiologies.

• Journal of the Korea Convergence Society
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• v.13 no.1
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• pp.387-398
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• 2022

This paper presents a system that remotely monitors lone seniors at home and promptly alarms caregivers to recommend appropriate medical care services upon detecting abnormal behavior and critical conditions such as collapsing, excessive coughing, degradation of sleep quality, fever, and unusual indoor moving lines. Our system offers contactless monitoring techniques based on heterogeneous IoT sensors and deep learning to minimize the disruption to lone senior's daily life. In addition to the design and implementation of the sensor data collection and analysis system, we share our experience in installation, deployment, configuration, maintenance of the system through the case study conducted on the actual lone seniors living in Seoul Metropolitan. Based on our research, we recommend further development directions to prepare for the nationwide expansion of our system.