• Journal of dental hygiene science
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• v.24 no.1
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• pp.22-28
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• 2024

Background: Particulate matter (PM) has been extensively observed due to its negative association with human health. Previous research revealed the possible negative effect of air pollutant exposure on oral health. However, the predictive model between air pollutant exposure and the prevalence of periodontitis has not been observed yet. Therefore, this study aims to propose a predictive model for the number of patients with periodontitis exposed to PM and atmospheric factors in South Korea using deep learning. Methods: This study is a retrospective cohort study utilizing secondary data from the Korean Statistical Information Service and the Health Insurance Review and Assessment database for air pollution and the number of patients with periodontitis, respectively. Data from 2015 to 2022 were collected and consolidated every month, organized by region. Following data matching and management, the deep neural networks (DNN) model was applied, and the mean absolute percentage error (MAPE) value was calculated to ensure the accuracy of the model. Results: As we evaluated the DNN model with MAPE, the multivariate model of air pollution including exposure to PM_2.5, PM₁₀, and other atmospheric factors predict approximately 85% of the number of patients with periodontitis. The MAPE value ranged from 12.85 to 17.10 (mean±standard deviation=14.12±1.30), indicating a commendable level of accuracy. Conclusion: In this study, the predictive model for the number of patients with periodontitis is developed based on air pollution, including exposure to PM_2.5, PM₁₀, and other atmospheric factors. Additionally, various relevant factors are incorporated into the developed predictive model to elucidate specific causal relationships. It is anticipated that future research will lead to the development of a more accurate model for predicting the number of patients with periodontitis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.7
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• pp.1547-1568
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• 2013

Wireless body area network (WBAN) is an emerging short-range wireless communication network with sensor nodes located on, in or around the human body for healthcare, entertainment and ubiquitous computing. In WBANs, energy is severely constrained which is the prime consideration in the medium access control (MAC) protocol design. In this paper, we propose a novel MAC protocol named Energy-efficient Relay MAC with dynamic Power Control (ERPC-MAC) to save energy consumption. Without relying on the additional devices, ERPC-MAC employs relaying nodes to provide relay service for nodes which consume energy fast. Accordingly the superframe adjustment is performed and then the network topology can be smoothly switched from single-hop to multi-hop. Moreover, for further energy saving and reliability improvement, the dynamic power control is introduced to adjust the power level whenever a node transmits its packets to the coordinator or the relaying node. To the best of the authors' knowledge, this is the first effort to integrate relay, topology adjustment and power control to improve the network performance in a WBAN. Comprehensive simulations are conducted to evaluate the performance. The results show that the ERPC-MAC is more superior to the existing standard and significantly prolongs the network lifetime.

• Annual Conference of KIPS
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• 2021.05a
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• pp.463-465
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• 2021

센서 데이터는 여러가지 원인으로 인해 데이터 결측치가 발생할 수 있으며, 결측치로 인한 데이터의 처리 방식에 따라 데이터 분석 결과가 다르게 해석될 수 있다. 이는 펫 헬스 케어 서비스에서 치명적인 문제로 연결될 수 있다. 따라서 본 논문에서는 펫 웨어러블 디바이스로부터 수집되는 다양한 센서 데이터의 결측치를 처리하기 위해 GATs(Graph Attention neTworks)와 LSTM(Long Short Term Memory)을 결합하여 활용한 데이터 결측치 처리 기법을 제안한다. 펫 웨어러블 디바이스의 센서 데이터가 서로 연관성을 가지고 있다는 점을 바탕으로 인접 노드의 Attention 수치와 Feature map을 도출한다. 이후 Prediction Layer 를 통해 결측치의 Feature 를 예측한다. 예측된 Feature 를 기반으로 Decoding 과정과 함께 결측치 보간이 이루어진다. 제안된 기법은 모델의 변형을 통해 이상치 탐지에도 활용할 수 있을 것으로 기대한다.

• International journal of advanced smart convergence
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• v.4 no.2
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• pp.109-119
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• 2015

The interaction between wireless sensors such as Internet of Things (IoT) and Cloud is a new paradigm of communication virtualization to overcome resource and efficiency restriction. Cloud computing provides unlimited platform, resources, services and also covers almost every area of computing. On the other hand, Wireless Sensor Networks (WSN) has gained attention for their potential supports and attractive solutions such as IoT, environment monitoring, healthcare, military, critical infrastructure monitoring, home and industrial automation, transportation, business, etc. Besides, our virtual groups and social networks are in main role of information sharing. However, this sensor network lacks resource, storage capacity and computational power along with extensibility, fault-tolerance, reliability and openness. These data are not available to community groups or cloud environment for general purpose research or utilization yet. If we reduce the gap between real and virtual world by adding this WSN driven data to cloud environment and virtual communities, then it can gain a remarkable attention from all over, along with giving us the benefit in various sectors. We have proposed a Pub/Sub-based sensor virtualization framework Cloud environment. This integration provides resource, service, and storage with sensor driven data to the community. We have virtualized physical sensors as virtual sensors on cloud computing, while this middleware and virtual sensors are provisioned automatically to end users whenever they required. Our architecture provides service to end users without being concerned about its implementation details. Furthermore, we have proposed an efficient content-based event matching algorithm to analyze subscriptions and to publish proper contents in a cost-effective manner. We have evaluated our algorithm which shows better performance while comparing to that of previously proposed algorithms.

• Journal of agricultural medicine and community health
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• v.48 no.4
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• pp.262-274
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• 2023

Objectives: This study examined the evaluation and potential improvements of 'Integrated Healthcare and Social Welfare service model' based on the experiences of practitioners from institutions participating in the 'Dalgubeol Health Doctor Services' and the service recipients. Methods: Qualitative research was conducted from September to November 2022 in this study, focusing on 4 providers from the dedicated Dalgubeol Health Doctor Services Team, 5 contact partners from affiliated organizations, and 6 service beneficiaries. The data gathered underwent thematic analysis. Results: The evaluation indicated that Dalgubeol Health Doctor Services has proven to be effective in addressing the complex needs of vulnerable populations. By providing integrated services through quick and simple beneficiary selection and resource linkage, it has contributed to the resolution of complex demands, recovery of positive attitudes towards life, and improvement in quality of life for users who have fear the use of medical and welfare services. Dalgubeol Health Doctor Services has established an integrated health care system involving not only public but also private organizations, from the referral agency to the service provider. Centered around Daegu Medical Center and involving five tertiary hospitals, it has established a model that supports treatment appropriate to the severity of the patient, from mild to severe. Conclusions: These findings indicate an enhancement in health equity, achieved through the active identification and subsequent health and welfare issue resolution of individuals marginalized from medical benefits.

• Journal of Digital Convergence
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• v.12 no.11
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• pp.225-232
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• 2014

Supply of a smart device has been made with the development of communication networks and growing desire of people to improve the quality of life, the service industry about it have been made with smart devices. Among them, there are various services that can help people change their behavior to healthy life. But it does not have a large impact on the behavior change of performer because its been developed as a general process. Therefore in this study examine development situation about current behavior change applications through application markets. Development current situation can be separated by process to two patterns. As a result we propose behavioral change model that includes integrated change model that one of the behavior theory model, accomplish the goal process of goal setting theory and habit formation phase for automate the changes. Also, we provide appropriate service according to the model that leads motivation, sustainability of the action and positive behavior change to performer. We can expect in many aspects such as ability and motivation than existing service.

• Journal of Information Technology Applications and Management
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• v.12 no.4
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• pp.93-104
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• 2005

Recently, RFID/USN is one of fundamental technologies in information and communications networks. Low-Rate WPAN, IEEE802.15.4 is a low-cost communication network that allows wireless connectivity in applications with limited Power and relaxed throughput requirements. Its applications are building automation, personal healthcare, industrial control, consumer electronics, and so on. Some applications require location information. Of course location awareness is useful to improve usability of data Low-Rate WPAN Is regarded as a key specification of the sensor network with the characteristics of wireless communication, computing, energy scavenging, self-networking, and etc. Unfortunately ZigBee alliance propose a lot of applications based on location aware technologies, but the specification and low-rate WPAN devices don't support anything about location-based services. RSSI ( Received Signal Strength indication) is for energy detection to associate, channel selection, and etc. RSSI is used to find the location of a potable device in WLAN. In this paper we studied indoor location awareness using vector matching of RSSI in low-Rate wireless PAN. We analyzed the characteristics of RSSI according to distance and experimented location awareness. We implemented sensor nodes with different shapes and configured the sensor network for the location awareness with 4 fixed nodes and a mobile node. We try to contribute developing location awareness method using RSSI in 3-dimension space.

• Korea Journal of Hospital Management
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• v.8 no.1
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• pp.81-94
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• 2003

This paper aims at developing a prediction model and analyzing a sensitivity for the outpatient's overall satisfaction on utilizing hospital services by using data mining techniques within the context of customer satisfaction. From a total of 900 outpatient cases, 80 percent were randomly selected as the training group and the other 20 percent as the validation group. Cases in the training group were used in the development of the CHAID and Neural Networks. The validation group was used to test the performance of these models. The major findings may be summarized as follows: the CHAID provided six useful predictors - satisfaction with treatment level, satisfaction with healthcare facilities and equipments, satisfaction with registration service, awareness of hospital reputation, satisfaction with staffs courtesy and responsiveness, and satisfaction with nurses kindness. The prediction accuracy rates based on MLP (77.90%) is superior to RBF (76.80%).

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.2
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• pp.79-85
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• 2020

IIoT stands for Industrial Internet of Things used in manufacturing, healthcare, and transportation in networked smart factories. Recently, IIoT's environment requires an automated control system through intelligent cognition to improve efficiency. In particular, IIoT can be applied to automatic calibration of production equipment for improved management in industrial environments. Such automation systems require a wireless network for transmitting industrial data. Self-calibration systems in laser transmission paths using wireless networks can save resources and improve production quality by real-time monitoring and remote control of laser transmission path. In this paper, we propose a wireless networked system for self-calibration of laser equipment that requires a laser transmission path, and we show the results of the prototype evaluation. The self-calibration system of laser equipment measures the coordinates of the laser points with sensors and sends them to the host using the proposed application protocol. We propose a wireless network service for the wired motor controller to align the laser coordinates. Using this wireless network, the host controls the motor by sending a control command of the motor controller in an HTTP message based on the received coordinate values. Finally, we build a prototype system of the proposed design to verify the detection performance and analyze the network performance.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.6
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• pp.151-158
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• 2010

In line with the requirement of appropriate protocol support for such mission-critical wireless sensor network (WSN) applications as patient monitoring, we investigate the framework for designing medium access control (MAC) schemes. The data traffic in medical systems comes with inherent traffic heterogeneity as well as strict requirement of reliability according to the varied extents of devise-wise criticality in separate cases. This implies that the quality-of-Service (QoS) issues are very distinctly delicate requiring specialized consideration. Besides, there are features in such systems that can be exploited during the design of a MAC scheme. In a monitoring or routine surveillance application, there are degrees of regularity or predictability in traffic as coordinated from a node of central control. The coordinator thus takes on the role of marshaling the resources in a neighborhood of nodes deployed mostly for upstream traffic; in a collision-free scheme, it schedules the time slots for each superframe based on the QoS specifications. In this preliminary study, we identify the key artifacts of such a MAC scheme. We also present basic performance issues like the impact of superframe length on delay incurred, energy efficiency achieved in the network operation as obtained in a typical simulation setup based on this framework.