• 한국정보통신학회논문지
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• 제16권9호
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• pp.1970-1976
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• 2012

현재 홈 헬스케어시스템은 의료기기와의 통합을 위한 표준화 기술이 미비한 상황이며 특히, 다양한 개인의료기기들의 호환성 제공과 시스템 간 상호 운용성 확보를 위한 보다 구체적인 솔루션이 필요하다. 본 논문에서는 핵심기술 요소인 ISO/IEEE 11073, HL7 표준 적용을 통하여 스마트 게이트웨이 기반 모바일 헬스케어시스템을 설계 및 구현하고자 한다. 이를 위해, 심박측정계, 산소포화도 측정계, 심전도 측정계 등을 헬스케어 의료기기로 구성하였다. 아울러, 본 논문에서는 Android 4.x Bluetooth HDP(Health Device Profile)를 기반으로 continua health alliance 표준의 의료기기 연결성을 제공하며, 스마트폰 환경에서 의료기기를 통해 얻어진 데이터를 HL7 표준을 기반으로 사용자와 의료인에게 제공하여 사용자의 건강 평가/관리를 위한 진단지원시스템을 가능하게 하는 헬스케어시스템을 구현하고자한다.

• Smart Structures and Systems
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• 제16권4호
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• pp.607-621
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• 2015

Wireless sensor technology has been opened up numerous opportunities to advanced health and maintenance monitoring of civil infrastructure. Compare to the traditional tactics, it offers a better way of providing relevant information regarding the condition of building structure health at a lower price. Numerous domestic buildings, especially longer-span buildings have a low frequency response and challenging to measure using deployed numbers of sensors. The way the sensor nodes are connected plays an important role in providing the signals with required strengths. Out of many topologies, the dense and sparse topologies wireless sensor network were extensively used in sensor network applications for collecting health information. However, it is still unclear which topology is better for obtaining health information in terms of greatest components, node's size and degree. Theoretical and computational issues arising in the selection of the optimum topology sensor network for estimating coverage area with sensor placement in building structural monitoring are addressed. This work is an attempt to fill this gap in high-rise building structural health monitoring application. The result shows that, the sparse topology sensor network provides better performance compared with the dense topology network and would be a good choice for monitoring high-rise building structural health damage.

• 지역사회간호학회지
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• 제27권4호
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• pp.410-422
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• 2016

Purpose: This study evaluated the effects of a cultural competence training program for public health nurses (PHNs) using intervention mapping. Methods: An embedded mixed method design was used. Forty-one PHNs (experimental: 21, control: 20) and forty marriage migrant women (MMW) (20, in each group) who were provided nursing care by PHN participated in the study. The experimental group was provided with a four-week cultural competence program consisting of an eight hour offline and online course, e-mail newsletters and social networking services (BAND). Transcultural Self-efficacy (TSE) of the PHNs, client-nurse trust, and satisfaction with nursing care of MMW were measured. Ten PHNs in the experimental group were interviewed after the experimental study. Results: The experimental group showed a significantly greater improvement in TSE, client-nurse trust, and satisfaction with nursing care than did the control group. Six themes emerged from qualitative data: (a) Recognizing cultural differences, (b) Being interested in the multicultural policy, (c) Trying to communicate in MMW's own language, (d) Providing medical information using internet and smart phone, (e) Embracing culturally diverse people into society, and (f) Requiring ongoing cultural competence training. Conclusion: Cultural competence training enabled PHNs to provide culturally competent care and contribute to MMW's health outcomes.

• Smart Structures and Systems
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• 제5권1호
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• pp.43-54
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• 2009

This study introduces a novel approach for locating damage in a structure using wireless sensor system with local level computational capability to alleviate data traffic load on the centralized computation. Smart wireless sensor systems, capable of iterative damage-searching, mimic an optimization process in a decentralized way. The proposed algorithm tries to detect damage in a structure by monitoring abnormal increases in strain measurements from a group of wireless sensors. Initially, this clustering technique provides a reasonably effective sensor placement within a structure. Sensor clustering also assigns a certain number of master sensors in each cluster so that they can constantly monitor the structural health of a structure. By adopting a voting system, a group of wireless sensors iteratively forages for a damage location as they can be activated as needed. Since all of the damage searching process occurs within a small group of wireless sensors, no global control or data traffic to a central system is required. Numerical simulation demonstrates that the newly developed searching algorithm implemented on wireless sensors successfully localizes stiffness damage in a plate through the local level reconfigurable function of smart sensors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권6호
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• pp.2910-2925
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• 2017

Inadequate and inappropriate intake of food is known to cause various health issues and diseases. Due to lack of concise information about healthy diet, people have to rely on medicines instead of taking preventive measures in food intake. Due to diversity in food components and large number of dietary sources, it is challenging to perform real-time selection of diet patterns that must fulfill one's nutrition needs. Particularly, selection of proper diet is critical for patients suffering from various diseases. In this article, we highlight the issue of selection of proper diet that must fulfill patients' nutrition requirements. To address this issue, we present a cloud based food recommendation system, called Diet-Right, for dietary recommendations based on users' pathological reports. The model uses ant colony algorithm to generate optimal food list and recommends suitable foods according to the values of pathological reports. Diet-Right can play a vital role in controlling various diseases. The experimental results show that compared to single node execution, the convergence time of parallel execution on cloud is approximately 12 times lower. Moreover, adequate accuracy is attainable by increasing the number of ants.

• Journal of Information Processing Systems
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• 제16권6호
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• pp.1238-1249
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• 2020

Throughout the world, aging populations and doctor shortages have helped drive the increasing demand for smart healthcare systems. Recently, these systems have benefited from the evolution of the Internet of Things (IoT), big data, and machine learning. However, these advances result in the generation of large amounts of data, making healthcare data analysis a major issue. These data have a number of complex properties such as high-dimensionality, irregularity, and sparsity, which makes efficient processing difficult to implement. These challenges are met by big data analytics. In this paper, we propose an innovative analytic framework for big healthcare data that are collected either from IoT wearable devices or from archived patient medical images. The proposed method would efficiently address the data heterogeneity problem using middleware between heterogeneous data sources and MapReduce Hadoop clusters. Furthermore, the proposed framework enables the use of both fog computing and cloud platforms to handle the problems faced through online and offline data processing, data storage, and data classification. Additionally, it guarantees robust and secure knowledge of patient medical data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권1호
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• pp.173-187
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• 2022

Recent studies have focused on self-management of hypertension using smart devices (cellular phones, tablets, watches). It has proven to be an effective tool for early detection and control of high Blood Pressure (BP) without affecting patients' daily routines. This systematic review surveys the existing self-monitoring systems, evaluate their effectiveness and compares the different approaches. We investigated the current systems in terms of various attributes, including methods used, sample size, type of investigation, inputs/ outputs, rate of success in controlling BP, group of users with higher response rate and beneficiaries, acceptability, and adherence to the system. We identified some limitations, shortcomings, and gaps in the research conducted recently studying the impact of mobile technology on managing hypertension. These shortcomings can generate future research opportunities and enable it to become more realistic and adaptive. We recommended including more observable factors and human behaviors that affect BP. Furthermore, we suggested that vital monitoring/logging and medication tuning are insufficient to improve hypertension control. There is also a need to observe and alter patient behavior and lifestyles.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권2호
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• pp.480-497
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• 2012

As a new business concept, machine-to-machine (M2M) communications are born from original telemetry technology with the intrinsic features of automatic data transmissions and measurement from remote sources typically by cable or radio. M2M includes a number of technologies that need to be combined in a compatible manner to enable its deployment over a broad market of consumer electronics. In order to provide better understanding for this emerging concept, the correlations among M2M, wireless sensor networks, cyber-physical systems (CPS), and internet of things are first analyzed in this paper. Then, the basic M2M architecture is introduced and the key elements of the architecture are presented. Furthermore, the progress of global M2M standardization is reviewed, and some representative applications (i.e., smart home, smart grid and health care) are given to show that the M2M technologies are gradually utilized to benefit people's life. Finally, a novel M2M system integrating intelligent road with unmanned vehicle is proposed in the form of CPS, and an example of cyber-transportation systems for improving road safety and efficiency are introduced.

• 대한지역사회영양학회지
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• 제21권4호
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• pp.332-343
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• 2016

Objectives: Study purpose was to investigate perception on diet, diet problems and related factors among young adult women using focus group interviews (FGI) based on the Social Cognitive Theory (SCT). Methods: Eight groups of FGI were conducted with 47 female undergraduate or graduate students. Guide for FGI included questions regarding perception on optimal diet, diet problems and cognitive, behavioral, and environmental factors of SCT. FGI were video, audio-taped, transcribed and analyzed by themes and sub-themes. Results: Subjects showed irregular eating habits (skipping breakfast, irregular meal time) and selection of unhealthy foods as the main diet problems. Regarding cognitive factors related to optimal diet, subjects mentioned positive outcome expectations (e.g., health promotion, skin health, improvement in eating habits, etc.) and negative outcome expectations (e.g., annoying, hungry, expensive, taste). Factors that promoted optimal diet were mainly received from information from mobile or internet and access to menu or recipes. Factors that prevented optimal diet included influence from friends, lack of time and cooking skills. Behavioral factors for optimal diet included behavioral capability regarding snacks, healthy eating and smart food selection. Subjects mentioned mass media (mobile, internet, TV) as the influential physical environment, and significant others (parents, friends, grandparents) as the influential social environment in optimal diet. For education topics, subjects wanted to learn about healthy meals, basic nutrition, disease and nutrition, and weight control. They wanted to learn those aspects by using mobile or internet, lectures (cooking classes), campaign and events. Conclusions: Study results might be used for planning education regarding optimal diet for young adult women. Education programs need to focus on increasing positive outcome expectations (e.g., health) and behavioral capability for healthy eating and food selection, reducing negative outcome expectations (e.g., cost, taste) and barriers, making supportive environments for optimal diet, and incorporating topics and methods found in this study.

• 전자공학회논문지CI
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• 제45권5호
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• pp.155-161
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• 2008

자동화된 건강관리 모니터링은 많은 시간이 소요되고, 많은 문제들이 발생할 수 있다. 왜냐하면 정시에 환자들의 건강 상태에 대한 모니터링 정보를 제공받기 어렵기 때문이다 이 논문에서는 임베디드된 건강 관리 서비스가 iSCSI 프로토콜에 의해 제안된다. 이 프로토콜은 자동화된 멀티에이전트와 제한된 자원의 디바이스들(예. PD4 스마트폰, 테블릿PC)의 협력체계에 기반을 두고 있다. 이 둘의 협력체계는 쌍방향 iSCSI 프로토콜에 의해 유지된다. 자동화된 건강관리 제어는 반복되는 방식에서 매우 유용할 수 있다. 완전 집중화된 제어에서는 이 방법이 적용될 수 없다.