• 제목/요약/키워드: Health Platform

검색결과 492건 처리시간 0.024초

Optimization sensor placement of marine platforms using modified ECOMAC approach

  • Vosoughifar, Hamidreza;Yaghoubi, Ali;Khorani, Milad;Biranvand, Pooya;Hosseininejad, Seyedehzeinab
    • Earthquakes and Structures
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    • 제21권6호
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    • pp.587-599
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    • 2021
  • The modified-ECOMAC approach to monitor and investigate health of structure in marine platforms was evaluated in this research. The material properties of structure were defined based on the real platform located in Persian Gulf. The nonlinear time-history analyses were undertaken using the marine natural waves. The modified-ECOMAC approach was designed to act as the solution of the best sensor placement according to structural dynamic behavior of structure. This novel method uses nonlinear time-history analysis results as an exact seismic response despite the common COMAC algorithms utilize the eigenvalue responses. The processes of modified-ECOMAC criteria were designed and developed by author of this paper as a toolbox of Matlab. The Results show that utilizing an efficient ECOMAC method in SHM process leads to detecting the critical weak points of sensitive marine platforms to make better decision about them. The statistical results indicate that considering modified ECOMAC based on seismic waves analysis has an acceptable accuracy on identify the sensor location. The average of statistical comparison of COMAC and ECOMAC via modal and integrated analysis, had a high MAE of 0.052 and RSME of 0.057 and small R2 of 0.504, so there is significant difference between them.

Smartphone-based structural crack detection using pruned fully convolutional networks and edge computing

  • Ye, X.W.;Li, Z.X.;Jin, T.
    • Smart Structures and Systems
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    • 제29권1호
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    • pp.141-151
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    • 2022
  • In recent years, the industry and research communities have focused on developing autonomous crack inspection approaches, which mainly include image acquisition and crack detection. In these approaches, mobile devices such as cameras, drones or smartphones are utilized as sensing platforms to acquire structural images, and the deep learning (DL)-based methods are being developed as important crack detection approaches. However, the process of image acquisition and collection is time-consuming, which delays the inspection. Also, the present mobile devices such as smartphones can be not only a sensing platform but also a computing platform that can be embedded with deep neural networks (DNNs) to conduct on-site crack detection. Due to the limited computing resources of mobile devices, the size of the DNNs should be reduced to improve the computational efficiency. In this study, an architecture called pruned crack recognition network (PCR-Net) was developed for the detection of structural cracks. A dataset containing 11000 images was established based on the raw images from bridge inspections. A pruning method was introduced to reduce the size of the base architecture for the optimization of the model size. Comparative studies were conducted with image processing techniques (IPTs) and other DNNs for the evaluation of the performance of the proposed PCR-Net. Furthermore, a modularly designed framework that integrated the PCR-Net was developed to realize a DL-based crack detection application for smartphones. Finally, on-site crack detection experiments were carried out to validate the performance of the developed system of smartphone-based detection of structural cracks.

Emergence of Online Teaching for Plastic Surgery and the Quest for Best Virtual Conferencing Platform: A Comparative Cohort Study

  • Suvashis Dash;Raja Tiwari;Amiteshwar Singh;Maneesh Singhal
    • Archives of Plastic Surgery
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    • 제50권2호
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    • pp.200-209
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    • 2023
  • Background As the coronavirus disease 2019 virus made its way throughout the world, there was a complete overhaul of our day-to-day personal and professional lives. All aspects of health care were affected including academics. During the pandemic, teaching opportunities for resident training were drastically reduced. Consequently, medical universities in many parts across the globe implemented online learning, in which students are taught remotely and via digital platforms. Given these developments, evaluating the existing mode of teaching via digital platforms as well as incorporation of new models is critical to improve and implement. Methods We reviewed different online learning platforms used to continue regular academic teaching of the plastic surgery residency curriculum. This study compares the four popular Web conferencing platforms used for online learning and evaluated their suitability for providing plastic surgery education. Results In this study with a response rate of 59.9%, we found a 64% agreement rate to online classes being more convenient than normal classroom teaching. Conclusion Zoom was the most user-friendly, with a simple and intuitive interface that was ideal for online instruction. With a better understanding of factors related to online teaching and learning, we will be able to deliver quality education in residency programs in the future.

사용자 운동 정보 수집 및 분석 기반의 서비스 플랫폼 (Service Platform Based on User Exercise Information Collection and Analysis)

  • 이현섭;김진덕
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2022년도 춘계학술대회
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    • pp.624-626
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    • 2022
  • 운동 장비에 부착 가능한 스마트폰 어플리케이션 타입의 운동 정보 관리 앱을 이용하여 개인의 운동 정보를 관리하는 것이 가능하고, 블루투스 전송 패킷 기반의 표준 운동 데이터 수집 모듈 구축으로 유사 구동 방식의 헬스 기기의 통합 관리가 가능하며, 운동 데이터 분석을 통한 현재 사용자의 운동량과 운동 강도 방향성 분석 및 제시를 위한 AI 모듈 구축으로 운동자에게 효과적인 운동 기법과 관리 정보 제공하는 서비스 플랫폼을 제안한다. 이를 위해 클라우드 환경 기반의 시스템 구축으로 효과적으로 관리가 가능하며 에어 및 마그네틱 기술을 동시 활용한 하이브리드형 헬스 모델을 구축한다.

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Design of Smart City Considering Carbon Emissions under The Background of Industry 5.0

  • Fengjiao Zhou;Rui Ma;Mohamad Shaharudin bin Samsurijan;Xiaoqin Xie
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제18권4호
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    • pp.903-921
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    • 2024
  • Industry 5.0 puts forward higher requirements for smart cities, including low-carbon, sustainable, and people-oriented, which pose challenges to the design of smart cities. In response to the above challenges, this study introduces the cyber-physical-social system (CPSS) and parallel system theory into the design of smart cities, and constructs a smart city framework based on parallel system theory. On this basis, in order to enhance the security of smart cities, a sustainable patrol subsystem for smart cities has been established. The intelligent patrol system uses a drone platform, and the trajectory planning of the drone is a key problem that needs to be solved. Therefore, a mathematical model was established that considers various objectives, including minimizing carbon emissions, minimizing noise impact, and maximizing coverage area, while also taking into account the flight performance constraints of drones. In addition, an improved metaheuristic algorithm based on ant colony optimization (ACO) algorithm was designed for trajectory planning of patrol drones. Finally, a digital environmental map was established based on real urban scenes and simulation experiments were conducted. The results show that compared with the other three metaheuristic algorithms, the algorithm designed in this study has the best performance.

Implementation of a bio-inspired two-mode structural health monitoring system

  • Lin, Tzu-Kang;Yu, Li-Chen;Ku, Chang-Hung;Chang, Kuo-Chun;Kiremidjian, Anne
    • Smart Structures and Systems
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    • 제8권1호
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    • pp.119-137
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    • 2011
  • A bio-inspired two-mode structural health monitoring (SHM) system based on the Na$\ddot{i}$ve Bayes (NB) classification method is discussed in this paper. To implement the molecular biology based Deoxyribonucleic acid (DNA) array concept in structural health monitoring, which has been demonstrated to be superior in disease detection, two types of array expression data have been proposed for the development of the SHM algorithm. For the micro-vibration mode, a two-tier auto-regression with exogenous (AR-ARX) process is used to extract the expression array from the recorded structural time history while an ARX process is applied for the analysis of the earthquake mode. The health condition of the structure is then determined using the NB classification method. In addition, the union concept in probability is used to improve the accuracy of the system. To verify the performance and reliability of the SHM algorithm, a downscaled eight-storey steel building located at the shaking table of the National Center for Research on Earthquake Engineering (NCREE) was used as the benchmark structure. The structural response from different damage levels and locations was collected and incorporated in the database to aid the structural health monitoring process. Preliminary verification has demonstrated that the structure health condition can be precisely detected by the proposed algorithm. To implement the developed SHM system in a practical application, a SHM prototype consisting of the input sensing module, the transmission module, and the SHM platform was developed. The vibration data were first measured by the deployed sensor, and subsequently the SHM mode corresponding to the desired excitation is chosen automatically to quickly evaluate the health condition of the structure. Test results from the ambient vibration and shaking table test showed that the condition and location of the benchmark structure damage can be successfully detected by the proposed SHM prototype system, and the information is instantaneously transmitted to a remote server to facilitate real-time monitoring. Implementing the bio-inspired two-mode SHM practically has been successfully demonstrated.

안드로이드 플랫폼 기반의 임상 바이오신호 처리를 위한 모바일 헬스 시스템 (m-Health System for Processing of Clinical Biosignals based Android Platform)

  • 서정희;박흥복
    • 한국컴퓨터정보학회논문지
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    • 제17권7호
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    • pp.97-106
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    • 2012
  • 모바일 장치에서의바이오신호데이터의 관리는 용량이많은 실시간멀티미디어 데이터의전송이나 저장 장치에서 많은 문제점을야기시킨다. 따라서 본 논문은신속한 의료 서비스를 제공하기 위해서 모바일을 이용한 임상 데이터 처리 시스템인 m-Health 시스템을 제안한다. 이 시스템은 지역의 IP 네트워크 상의 헬스 시스템을 구축하여 원격의 여러 바이오 센싱으로 부터 출력을 조합하고, 다양한 바이오 센서에서의 전자적인 데이터 통합 처리를 수행하였다. m-Health 시스템은 다양한 바이오신호들을 측정 및 모니터링하고 원거리에 위치한 병원의 데이터 서버로 전송한다. 환자 및 가족, 의료진 모두가 언제 어디서나 사용할 수 있는 안드로이드 기반의 모바일 애플리케이션으로 의료 관련자는 병원의 데이터 서버에서 환자 데이터를 접근하여 환자 또는 사용자에게 의료 진단 및 처방을 피드백 한다. 그리고 환자 관찰을 위한 비디오 스트림은 스케일러블 트랜스코딩 기법을 이용하여 네트워크 트래픽에 알맞은 데이터 크기를 결정하고 비디오 스트림을 전송함으로서 모바일 시스템과 네트워크의 부하를 줄일 수 있다.

Effects of Open Kinetic Chain Exercise for the Gastrocnemius and Tibialis Anterior Muscles on Balance

  • Yi, Song Yeon;Kim, Young Ju;Lee, Dong Yeop;Yu, Jae Ho;Kim, Jin Seop;Kim, Soung Gil;Hong, Ji heon
    • The Journal of Korean Physical Therapy
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    • 제33권6호
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    • pp.278-285
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    • 2021
  • Purpose: This study investigated the effects of open kinetic chain (OKC) exercise for the gastrocnemius (GCM) and tibialis anterior (TA) muscles on static and dynamic balance and muscle strength. Methods: We recruited 21 healthy participants, dividing them into 3 groups (GCM, TA, and non-exercise). Each group contains 7 participants. Two exercise groups (GCM and TA) performed OKC exercise with elastic bands twice per week for 4 weeks, while non-exercise group did nothing. We obtained the data for static and dynamic balance and muscle strength before and after the intervention. We used the Kruskal-Wallis test to compare and analyze the pre-post-intervention differences among the groups. Results: For static balance, the stability index of the TA group was the lowest for the dynamic platform (p<0.05). The dynamic balance of the TA group increased for the anterior and posteromedial directions (p<0.05). The peak torque increased in the TA group for dorsiflexion (D/F) movement and in the GCM group for plantar flexion movement compared with the other groups, except for the left direction during D/F (p<0.05). Conclusion: OKC exercises with elastic bands were effective for selectively increasing muscle strength. It is clinically thought that strength training for TA muscles will be effective among the muscles of the ankle.

COVID-19 팬데믹이 대학생의 신체적 활동과 정신적 건강에 미치는 영향 (Effects of the COVID-19 Pandemic on the Physical Activity and Mental Health of University Students)

  • 김보혜;이보영;이예영;황수진
    • 대한통합의학회지
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    • 제9권3호
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    • pp.59-68
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    • 2021
  • Purpose : The purpose of this study was to investigate the lecture method and physical activity level of Korean university students during the COVID-19 pandemic to determine their effect on the students' mental health, self-efficacy, and learning motivation. Methods : A total of 203 participants (53 male, 150 female) completed the study. An online survey was distributed through a social media platform between March 24 and April 7, 2021. Participants completed the international physical activity questionnaire-short form (IPAQ-SF), COVID-19 stress scale for Korean people (CSSK), the Korean version of the general health questionnaire (KGHQ-30), and self-efficacy and learning motivation scales. Results : Among the general characteristics of the study subjects, there were statistically significant differences in the IPAQ-SF, CSSK, KGHQ, self-efficacy, and learning motivation measures by sex. There were no significant differences in the degree of IPAQ-SF, CSSK, KGHQ, self-efficacy, and learning motivation among any of the lecture method and university area groups. The level of physical activity corresponded with significant differences in KGHQ, self-efficacy, and learning motivation, excluding CSSK. There was a statistically significant positive correlation between IPAQ and self-efficacy (r=.273, p<.001), IPAQ-SF and learning motivation (r=.201, p<.01), CSSK and KGHQ (r=.271, p<.001), self-efficacy and learning motivation measures (r=.506, p<.001). There was a statistically significant negative correlation between IPAQ-SF and KGHQ (r=-.203, p<.01) and between KGHQ and self-efficacy (r=-.558, p<.001). Conclusion : CSSK and KGHQ measures were significantly higher in female students than in male students. Therefore, it is important to consider sex as a protective factor in the mental health management of university students in the context of an infectious disease pandemic. The results of this study suggest that university students should continue to engage in physical activities, even during a pandemic, and that it is necessary to prepare health management to improve mental health in such situations.

사물인터넷 헬스케어 서비스를 위한 oneM2M기반 ISO/IEEE 11073 DIM 전송 구조 설계 및 구현 (Design and Implementation of ISO/IEEE 11073 DIM Transmission Structure Based on oneM2M for IoT Healthcare Service)

  • 김현수;천승만;정윤석;박종태
    • 전자공학회논문지
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    • 제53권4호
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    • pp.3-11
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    • 2016
  • 사물 인터넷 (Internet of Things : IoT) 환경에서 IoT 디바이스들은 전원이나 메모리 등의 물리적 구성요소들에 의해 제한되며 대역폭, 무선 채널, 처리율, 페이로드 등의 네트워크 성능 또한 제한적임에도 불구하고 타 IoT 디바이스들과 리소스를 공유한다. 특히 IoT 헬스케어 서비스에 있어서 원격 디바이스 정보 관리 뿐만 아니라 원격 환자 정보관리가 매우 중요하며, 더욱이, 사물인터넷 헬스케어 디바이스와 헬스케어 플랫폼간 상호연동성 지원이 매우 중요하다. 이를 위해서는 헬스케어 디바이스와 헬스케어 플랫폼간 데이터 정보 표현, 데이터 전송 표현, 메시지 규격 등이 사물인터넷 환경에 적합한 국제표준 준수가 매우 필요하다. 하지만, 기존의 국제의료정보 전송표준인 ISO/IEEE 11073 PHD (Personal Healthcare Device) 표준에서는 사물인터넷 환경 (네트워크 프로토콜)을 고려하지 않아 사물인터넷 헬스케어 서비스에 적용하기 어렵다. 이를 위해 본 논문에서는 사물인터넷 표준인 oneM2M과 의료정보 전송표준인 ISO/IEEE 11073 DIM(Domain Information Model)을 적용한 사물인터넷 헬스케어 시스템을 설계 및 구현하였다. 구현을 위해 oneM2M 기반인 OM2M 플랫폼을 활용하였고, 헬스케어 디바이스와 OM2M 플랫폼간 효율적인 전송 구문에 대한 평가를 위해 HTTP와 CoAP간, XML과 JSON간 단일 처리과정의 패킷 사이즈와 전송 패킷 수 등을 성능 분석하였다.