• The Journal of Bigdata
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• v.5 no.1
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• pp.139-145
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• 2020

In the era of the 4th Industrial Revolution, the use of information based on AI APIs has a great influence on industry and life. In particular, the use of artificial intelligence data in the medical field will have many changes and effects on society. This paper is to study the necessary components to implement the "Cognitive Health Advisor model (CHA model)" and to implement the "CHA model using chatbot" based on this. It uses the open Cognitive chatbot to analyze and analyze the health status of users changing in their daily lives. The user's health information analyzed by the biometric sensor and chatbot consultation delivers the information to the user through the chatbot. And it implements a cognitive health advisor model that provides educational information for users' health promotion. Through this implementation, it intends to confirm the possibility of future use and to suggest research directions.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.746-754
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• 2016

Smart healthcare systems, a convergent industry based on information and communications technologies (ICT), has emerged from personal health management to remote medical treatment as a distinguished industry. The smart healthcare environment provides technology to deliver vital information, such as pulse rate, body temperature, health status, and so on, from wearable devices to the hospital network where the physician is located. However, since it deals with the patient's personal medical information, there is a security issue for personal information management, and the system may be vulnerable to cyber-attacks in wireless networks. Therefore, this study focuses on a key-development and device-management system to generate keys in the smart environment to safely manage devices. The protocol is designed to provide safe communications with the generated key and to manage the devices, as well as the generated key. The security level is analyzed against attack methods that may occur in a healthcare environment, and it was compared with existing key methods and coding capabilities. In the performance evaluation, we analyze the security against attacks occurring in a smart healthcare environment, and the security and efficiency of the existing key encryption method, and we confirmed an improvement of about 15%, compared to the existing cipher systems.

• Information Systems Review
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• v.17 no.1
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• pp.19-47
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• 2015

The purpose of this research is to represent how ICT relatedness and organization environment influence on interactions between healthcare specialist and patients, and how knowledge sharing influence on healthcare innovation, and how service innovation influence on service performance through structured research model. This research also has applied to resource based view, adaptive structuration theory, service innovation, ICT relatedness to find out performance effect on healthcare service innovation and service performance. In other words, organization structure environment and ICT relatedness are important factors to promote interaction between healthcare service providers and customers like patients each other, moreover, to share the tacit knowledge by creating in the interaction. Moreover in order to verify model fitness, this research has surveyed among healthcare specialists, technicians and other staffs. Model verification result, all hypotheses have been found to give a positive effect on the creation and significantly. Structured organizational environment and ICT association is to promote the organization's functions by influencing the behavior of the service organization and patient interaction and knowledge sharing, and suggests that the major factors influencing the innovation performance of hospitals and health care services.

• Convergence Security Journal
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• v.13 no.4
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• pp.101-108
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• 2013

Sensor network configurations are for a specific situation or environment sensors capable of sensing, processing the collected information processors, and as a device is transmitting or receiving data. It is presently serious that sensor networks provide many benefits, but can not solve the wireless network security vulnerabilities, the risk of exposure to a variety of state information. u-Healthcare sensor networks, the smaller the sensor node power consumption, and computing power, memory, etc. restrictions imposing, wireless sensing through the kind of features that deliver value, so it ispossible that eavesdropping, denial of service, attack, routing path. In this paper, with a focus on sensing of the environment u-Healthcare system wireless security vulnerabilities factors u-Healthcare security framework to diagnose and design methods are presented. Sensor network technologies take measures for security vulnerabilities, but without the development of technology, if technology is not being utilized properly it will be an element of threat. Studies suggest that the u-Healthcare System in a variety of security risks measures user protection in the field of health information will be used as an important guide.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.185-191
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• 2022

In this study, we propose a novel super-resolution neural network based on U-Net, residual neural network, and sub-pixel convolution. To prevent the loss of detailed information due to the max pooling of U-Net, we propose down-sampling and connection using sub-pixel convolution. This uses all pixels in the filter, unlike the max pooling that creates a new feature map with only the max value in the filter. As a 2×2 size filter passes, it creates a feature map consisting only of pixels in the upper left, upper right, lower left, and lower right. This makes it half the size and quadruple the number of feature maps. And we propose two methods to reduce the computation. The first uses sub-pixel convolution, which has no computation, and has better performance, instead of up-convolution. The second uses a layer that adds two feature maps instead of the connection layer of the U-Net. Experiments with a banchmark dataset show better PSNR values on all scale and benchmark datasets except for set5 data on scale 2, and well represent local area patterns.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.3
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• pp.605-614
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• 2012

Nowadays u-healthcare which is very sensitive to the character of user's information among other ubiquitous computing field is popular in medical field. u-healthcare deals extremely personal information including personal health/medical information so it is exposed to various weaknees and threats in the part of security and privacy. In this paper, RFID based patient's information protecting protocol that prevents to damage the information using his or her mobile unit illegally by others is proposed. The protocol separates the authority of hospital(doctor, nurse, pharmacy) to access to patient's information by level of access authority of hospital which is registered to management server and makes the hospital do the minimum task. Specially, the management server which plays the role of gateway makes access permission key periodically not to be accessed by others about unauthorized information except authorized information and improves patient's certification and management.

• Journal of the Korea Society of Computer and Information
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• v.25 no.6
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• pp.65-72
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• 2020

Today, the Internet of Things is used in many places, including homes, industrial sites, and hospitals, to give us convenience. Many services generate new value through real-time data collection, storage and analysis as devices are connected to the network. Many of these fields are creating services and applications that utilize sensors and communication functions within IoT devices. However, since everything can be hacked, it causes a huge privacy threat to users who provide data. For example, a variety of sensitive information, such as personal information, lifestyle patters and the existence of diseases, will be leaked if data generated by smarwatches are abused. Development of IoT must be accompanied by the development of security. Recently, Differential Privacy(DP) was adopted to privacy-preserving data processing. So we propose the method that can aggregate health data safely on smartwatch platform, based on DP.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.279-282
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• 2022

Acute lymphoblastic leukemia is an acute leukemia caused by suppression of bone marrow function due to overgrowth of immature lymphocytes in the bone marrow. It accounts for 30% of acute leukemia in adults, and children show a cure rate of over 80% with chemotherapy, while adults show a low survival rate of 20% to 50%. However, research on a machine learning algorithm based on medical image data for the diagnosis of acute lymphoblastic leukemia is in the initial stage. In this paper, we compare and analyze CNN algorithm models for quick and accurate diagnosis. Using four models, an experimental environment for comparative analysis of acute lymphoblastic leukemia diagnostic models was established, and the algorithm with the best accuracy was selected for the given medical image data. According to the experimental results, among the four CNN models, the InceptionV3 model showed the best performance with an accuracy of 98.9%.

• Journal of Internet Computing and Services
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• v.17 no.2
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• pp.59-65
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• 2016

The result of analyzing the cognitive reaction due to the color environment has been applied to various filed especially in medical field. Moreover, the study about the identification of patient's condition and examination the brain activity by collecting the bio-signal based on the color environment is being actively conducted. Even though, there were a variety of experiments by convention the color environment using a light or LED color, it still has a problem that affects the psychological information. Therefore, our proposed system using a HMD (Head Mounting display) to provide a completed color environment condition. This system uses the BMS(Biomedical System) to collect the biometric information which responds to the specific color condition and the human body response information can be measured by the development the Memory and Attention test on Mobile phone. The collection of Biometric information includes electro cardiogram(ECG), respiration, oxygen saturation (Sp02), Bio-impedance, blood pressure will store in the database. In addition, we can verify the result of the human body reaction in the color environment by Memory and Attention application. By utilizing the reaction of the human body information that is collected thought the proposed system, we can analyze the correlation between the physiological information and the color environment. And we also expect that this system can apply to the medical diagnosis and treatment. For future work, we will expand the system for prediction and treatment of Alzheimer disease by analyzing the visualization data through the proposed system. We will also do evaluation on the effectiveness of the system for using in the rehabilitation program.

• The Journal of the Korea Contents Association
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• v.22 no.9
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• pp.46-63
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• 2022

With the rapid development of digital technology and the growing trend to integrate it into the medical field, recent studies suggest language rehabilitation for people with aphasia using virtual reality (VR), augmented reality (AR) and mobile applications. This study conducted a scoping review to summarize the features of digital technology-based language rehabilitation for aphasia in the last four years (2018-2021) and draw implications for future research. A total of 20 papers met the selection criteria among the documents retrieved from the Web of Science, CINAHL, and RISS. This review demonstrates that digital technology could offer unique treatment content by gamification, individualization, and creating a realistic communication environment, and by utilizing them in various ways. Therefore, we expect digital technology-based language rehabilitation for aphasia could supplement the limitations of conventional language rehabilitation and provide a novel perspective on development of treatment content.