• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2414-2433
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• 2021

This article focuses on providing remedial solutions for COVID disease through the data collection process. Recently, In India, sudden human losses are happening due to the spread of infectious viruses. All people are not able to differentiate the number of affected people and their locations. Therefore, the proposed method integrates robotic technology for monitoring the health condition of different people. If any individual is affected by infectious disease, then data will be collected and within a short span of time, it will be reported to the control center. Once, the information is collected, then all individuals can access the same using an application platform. The application platform will be developed based on certain parametric values, where the location of each individual will be retained. For precise application development, the parametric values related to the identification process such as sub-interval points and intensity of detection should be established. Therefore, to check the effectiveness of the proposed robotic technology, an online monitoring system is employed where the output is realized using MATLAB. From simulated values, it is observed that the proposed method outperforms the existing method in terms of data quality with an observed percentage of 82.

• Earthquakes and Structures
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• v.21 no.6
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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.

• Smart Structures and Systems
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• v.29 no.1
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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.

• Archives of Plastic Surgery
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• v.50 no.2
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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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.624-626
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• 2022

It is possible to manage individual exercise information using a smartphone application that may be attached to exercise equipment. We propose a service platform that provides effective exercise techniques and management information to athletes by establishing an AI module to analyze and present the current user's exercise volume and exercise intensity direction through analysis of exercise data. To this end, it can be effectively managed by establishing a system based on a cloud environment and builds a hybrid health model that utilizes air and magnetic technologies at the same time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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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.

• Smart Structures and Systems
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• v.8 no.1
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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.

• Journal of the Korea Society of Computer and Information
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• v.17 no.7
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• pp.97-106
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• 2012

Management of biosignal data in mobile devices causes many problems in real-time transmission of large volume of multimedia data or storage devices. Therefore, this research paper intends to suggest an m-Health system, a clinical data processing system using mobile in order to provide quick medical service. This system deployed health system on IP network, compounded outputs from many bio sensing in remote sites and performed integrated data processing electronically on various bio sensors. The m-health system measures and monitors various biosignals and sends them to data servers of remote hospitals. It is an Android-based mobile application which patients and their family and medical staff can use anywhere anytime. Medical staff access patient data from hospital data servers and provide feedback on medical diagnosis and prescription to patients or users. Video stream for patient monitoring uses a scalable transcoding technique to decides data size appropriate for network traffic and sends video stream, remarkably reducing loads of mobile systems and networks.

• The Journal of Korean Physical Therapy
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• v.33 no.6
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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.

• Journal of The Korean Society of Integrative Medicine
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• v.9 no.3
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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.