• International Journal of Computer Science & Network Security
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• v.23 no.6
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• pp.59-67
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• 2023

The healthcare industry continues to adopt and integrate smart technology in its operations, from medical devices to managing operations. However, the adoption curve has not been smooth, and the historical record of technology adoption in the Kingdom of Saudi Arabia reveals the existence of both known and unknown issues. This review paper is aimed to explain the influences and barriers present in the Saudi healthcare sector affecting IoT technology adoption. A comprehensive discussion of the literature illustrated that Vision 2030, the privatisation trend, transformation in disease patterns and ageing, issues in management and increasing public awareness are the key drivers that may influence the need for the medical Internet of Things (mIoT) in Saudi healthcare. However, based on the past trend, the introduction and adoption of mIoT will likely experience issues such as noncompliance from doctors and nurses due to negative beliefs, lack of knowledge and inadequate perception of effort requirements. Thus, in-depth research of the factors associated with mIoT technology adoption is suggested for a smooth transition.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.6
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• pp.718-723
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• 2018

In a positive Internet of Medical Things (IoMT) environment, by combining the latest computer network technology with IoT technology, remote health care such as health care and monitoring is improved through the provision of quality medical information services. In this paper, we identified and compared the platforms applied with blockchain and presented the results of developing the product distribution de-centralized DApp. In the process, we developed a distribution platform that can use blockchain technology to identify product fraud, manage data, manage customers' information, prevent forgery, track transaction history, and facilitate product transactions.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.551-554
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• 2017

The largest industry in the world is the medical industry, and due to aging and growing demand for well-being, it is necessary to review the competition strategy of the healthcare industry. We will secure competitiveness among medical institutions through the rapid dissemination of ICT convergence, study the intelligence level of digital health care by increasing the capacity of intelligent medical care by combining big data of medical data and artificial intelligence, And to find a countermeasure for constructing a medical optimization model.

• Journal of Internet of Things and Convergence
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• v.10 no.1
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• pp.47-52
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• 2024

The efficiency and quality of healthcare services rely heavily on the secure protection and transparent management of individuals' medical information, which is becoming increasingly important in the digital age. To address this issue, we propose a distributed identity management (DID) and electronic medical record (EMR) integration system based on Hyperledger Indy, which aims to ensure the ownership of medical information to individuals and increase the accessibility and utilization of medical information. The system will allow individuals to manage their own medical information and share it transparently when necessary, which will improve the efficiency of healthcare services. In addition, the system will securely protect and transparently manage medical information, increasing the transparency of medical services and strengthening individuals' control over their medical information. Thus, the system will contribute significantly to improving the quality of medical services, protecting individuals' medical information, and improving the efficiency of medical services.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.258-261
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• 2020

코로나19로 인해 사회적 거리두기가 대두되면서 등산 활동이 인기를 얻고 있다. 본 논문에서는 다양한 등산 용품 중 하나인 등산스틱에 IoT 기술을 접목시키고, 어플리케이션과 연동하여 사용자 맞춤 서비스를 제공하며 대여 시스템을 통해 관리하고자한다. 이를 통해 사용자는 등산스틱의 구매, 관리, 소지에 대한 부담을 해소하고 안정성과 편리함을 얻을 수 있을 것으로 기대된다.

• KIISE Transactions on Computing Practices
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• v.23 no.5
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• pp.284-292
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• 2017

With the development of Internet of Things (IoT) technology, the combination of ICT and medical services has been increasing to improve the quality of medical services. Using the IoTs, we can collect personal health information continuously in a patient's everyday life. We expect that this will improve the quality of medical service through analysis. However, the problem of ensuring the protection of personal information within the personal health information has been hampering the research, development, and application of such services. Other problems include lack of IoT devices and lack of user convenience for collecting health information about a patient's everyday life. Therefore, in this study, we construct a daily health information management service that can collect the health related information at any time and store this data in personal storage. This data is then only provided to the healthcare worker when necessary. We built a test bed for an IoT-based smart home platform and are currently conducting user experiments. Based on the results of this study, we are attempting to provide a high quality medical trial service based on daily health information through linkage with medical device manufacturers, medical clinics, insurance companies, etc. We expect the proposed health information management service will contribute to the revitalization of smart health care services via activating various health related IoT devices and analyzing daily health information.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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• pp.1167-1187
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• 2020

With the development of medical imaging technology, image registration has been widely used in the field of disease diagnosis. The registration between different modal images of brain magnetic resonance (MR) is particularly important for the diagnosis of brain diseases. However, previous registration methods don't take advantage of the prior knowledge of bilateral brain symmetry. Moreover, the difference in gray scale information of different modal images increases the difficulty of registration. In this paper, a multimodal medical image registration method based on image segmentation and symmetric self-similarity is proposed. This method uses modal independent self-similar information and modal consistency information to register images. More particularly, we propose two novel symmetric self-similarity constraint operators to constrain the segmented medical images and convert each modal medical image into a unified modal for multimodal image registration. The experimental results show that the proposed method can effectively reduce the error rate of brain MR multimodal medical image registration with rotation and translation transformations (average 0.43mm and 0.60mm) respectively, whose accuracy is better compared to state-of-the-art image registration methods.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.1-12
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• 2022

The current progression in the Internet of Things (IoT) and Machine Learning (ML) based technologies converted the traditional healthcare system into a smart healthcare system. The incorporation of IoT and ML has changed the way of treating patients and offers lots of opportunities in the healthcare domain. In this view, this research article presents a new IoT and ML-based disease diagnosis model for the diagnosis of different diseases. In the proposed model, vital signs are collected via IoT-based smart medical devices, and the analysis is done by using different data mining techniques for detecting the possibility of risk in people's health status. Recommendations are made based on the results generated by different data mining techniques, for high-risk patients, an emergency alert will be generated to healthcare service providers and family members. Implementation of this model is done on Anaconda Jupyter notebook by using different Python libraries in it. The result states that among all data mining techniques, SVM achieved the highest accuracy of 0.897 on the same dataset for classification of Parkinson's disease.

• Structural Engineering and Mechanics
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• v.85 no.1
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• pp.15-27
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• 2023

Using artificial intelligence and internet of things methods in engineering and industrial problems has become a widespread method in recent years. The low computational costs and high accuracy without the need to engage human resources in comparison to engineering demands are the main advantages of artificial intelligence. In the present paper, a deep neural network (DNN) with a specific method of optimization is utilize to predict fundamental natural frequency of a cylindrical structure. To provide data for training the DNN, a detailed numerical analysis is presented with the aid of functionally modified couple stress theory (FMCS) and first-order shear deformation theory (FSDT). The governing equations obtained using Hamilton's principle, are further solved engaging generalized differential quadrature method. The results of the numerical solution are utilized to train and test the DNN model. The results are validated at the first step and a comprehensive parametric results are presented thereafter. The results show the high accuracy of the DNN results and effects of different geometrical, modeling and material parameters in the natural frequencies of the structure.

• Journal of Internet of Things and Convergence
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• v.9 no.3
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• pp.75-80
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• 2023

In medically vulnerable areas in Korea, public health doctors play a significant role in providing not only general medical care but also emergency medical services to the local residents. However, it has been observed that public health doctors generally lack field experience, resulting in insufficient ability to handle emergency patients and to effectively use medical equipment. This study confirmed the effectiveness of education after conducting remote education using smart glasses on how to use medical equipment necessary for public health doctors. Specifically, real wear was used for smart glasses for medical equipment utilization education, and 10 public health officials in 10 islands in Shinan-gun were targeted. After the training, both the effect of using the equipment and the level of satisfaction were 3 or higher. Therefore, it was confirmed that remote education using smart glasses can be usefully used for public health doctors in medically vulnerable areas.