• Information Systems Review
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• v.26 no.2
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• pp.137-153
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• 2024

This study aimed to propose early diagnosis and management of dementia, which is increasing in aging societies, and suggest commercial utilization strategies by leveraging digital healthcare technologies, particularly lifelog data collected from wearable devices. By introducing new approaches to dementia prevention and management, this study sought to contribute to the field of dementia prediction and prevention. The research utilized 12,184 pieces of lifelog information (sleep and activity data) and dementia diagnosis data collected from 174 individuals aged between 60 and 80, based on medical pathological diagnoses. During the research process, a multidimensional dataset including sleep and activity data was standardized, and various machine learning algorithms were analyzed, with the random forest model showing the highest ROC-AUC score, indicating superior performance. Furthermore, an ablation test was conducted to evaluate the impact of excluding variables related to sleep and activity on the model's predictive power, confirming that regular sleep and activity have a significant influence on dementia prevention. Lastly, by exploring the potential for commercial utilization strategies of the developed model, the study proposed new directions for the commercial spread of dementia prevention systems.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.10
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• pp.323-328
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• 2014

ZigBee based on the most vulnerable part of u-Healthcare system that uses the ZigBee communication is the wireless section. ZigBee communication sectors to identify vulnerabilities in this paper, we propose to compensate. ZigBee has been raised from the existing vulnerabilities organize and ZigBee also uses the 64bit address that uniquely identifies a vulnerability that was defined as exposure. And to prevent the exposure of a unique identifying address was used to address a temporary identification. ZigBee security services, the proposed system during the Network Key for encryption only use one mechanism of Residential Mode is used. Residential Mode on all nodes of the entire network because they use a common key, the key is stolen, your network's security system at a time are at risk of collapse. Therefore, in order to guard against these risks to the security policy Network Key updated periodically depending on the method used to. The proposed evaluation and comparative analysis of the system were exposed in the existing system can hide the address that uniquely identifies a public key Network Key also updated periodically, so that leaks can occur due to reduced risk.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.32 no.3
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• pp.231-241
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• 2022

Objectives: The purpose of this study is to evaluate the input status of exposure-related information in the working environment monitoring database (WEMD) and special health examination database (SHED) for the construction of a national exposure surveillance system. Methods: The industrial and process code input status of WEMD and SHED for 21 carcinogens from 2014 to 2016 was compared. Data from workers who performed both work environment monitoring and special health examinations in 2019 and 2020 were extracted and the actual status of input of industrial and process codes was analyzed. We also investigated the cause of input errors through a focus group interview with 12 data input specialists. Results: As a result of analyzing WMED and SHED for 21 carcinogens, the five-digit industrial code matching rate was low at 53.5% and the process code matching rate was 19% or less. Among the data that simultaneously conducted work environment monitoring and special health examination in 2019 and 2020, the process code matching rate was very low at 18.1% and 5.2%, respectively. The main causes of exposure-related data input errors were the difference between the WEMD and SHED process code input systems from 2020, the number of standard process and job codes being too large, and the inefficiency of the standard code search system. Conclusions: In order to use WEMD and SHED as a national surveillance system, it is necessary to simplify the number of standard code input codes and improve the search system efficiency.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.7
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• pp.1547-1568
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• 2013

Wireless body area network (WBAN) is an emerging short-range wireless communication network with sensor nodes located on, in or around the human body for healthcare, entertainment and ubiquitous computing. In WBANs, energy is severely constrained which is the prime consideration in the medium access control (MAC) protocol design. In this paper, we propose a novel MAC protocol named Energy-efficient Relay MAC with dynamic Power Control (ERPC-MAC) to save energy consumption. Without relying on the additional devices, ERPC-MAC employs relaying nodes to provide relay service for nodes which consume energy fast. Accordingly the superframe adjustment is performed and then the network topology can be smoothly switched from single-hop to multi-hop. Moreover, for further energy saving and reliability improvement, the dynamic power control is introduced to adjust the power level whenever a node transmits its packets to the coordinator or the relaying node. To the best of the authors' knowledge, this is the first effort to integrate relay, topology adjustment and power control to improve the network performance in a WBAN. Comprehensive simulations are conducted to evaluate the performance. The results show that the ERPC-MAC is more superior to the existing standard and significantly prolongs the network lifetime.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.21
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• pp.9529-9534
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• 2014

Background: Cancer staging enables planning for the best treatments, evaluation of prognosis, and predictions for survival. The Collaborative Stage (CS) system makes it possible to significantly reduce the proportion of patients labeled at an "unknown" stage as well as discrepancies among different staging systems. This study aims to analyze the factors that influence the accuracy and validity of CS data. Materials and Methods: Data were randomly selected (233 cases) from stomach cancer cases enrolled for CS survey at the Korea Central Cancer Registry. Two questionnaires were used to assess CS values for each case and to review the cancer registration environment for each hospital. Data were analyzed in terms of the relationships between the time spent for acquisition and registration of CS information, environments relating to cancer registration in the hospitals, and document sources of CS information for each item. Results: The time for extracting and registering data was found to be shorter when the hospitals had prior experience gained from participating in a CS pilot study and when they were equipped with full-time cancer registrars. Evaluation of the CS information according to medical record sources found that the percentage of items missing for Site Specific Factor (SSF) was 30% higher than for other CS variables. Errors in CS coding were found in variables such as "CS Extension," "CS Lymph Nodes," "CS Metastasis at Diagnosis," and "SSF25 Involvement of Cardia and Distance from Esophagogastric Junction (EGJ)." Conclusions: To build CS system data that are reliable for cancer registration and clinical research, the following components are required: 1) training programs for medical records administrators; 2) supporting materials to promote active participation; and 3) format development to improve registration validity.

• Journal of The Korean Association of Information Education
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• v.17 no.4
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• pp.475-486
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• 2013

Recent healthcare studies evaluate the effective impacts of a patient educational information intervention in hospitals on adherence to communicating knowledge, life quality, and therapeutic response in patients treated with highly active therapy in medical organizations. Therefore, the aim of this study is to design and implement the effective and systematic frameworks by providing clinical patient-oriented education system(CPES), which enhances health promotion and medical cures. CPES initiatives accelerate positive financial returns with network-driven educational system. To validate the CPES, the author analyzes the efficiency and effectiveness using statistical survey works. With this outcome, it is compared with previous system. One of the findings is that the system can improve compliance with treatment right dietetics and give patients self-manage their conditions in S hospital. Patients' acknowledge of their condition and its treatment process can be improved through the educational systems.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.4
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• pp.145-152
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• 2019

Unlike a single value from a sensor device, a massive data set has characteristics for various processing aspects; input data may be formed in a different format, the size of input data varies, and the processing time of analyzing input data is not predictable. Therefore, context aware systems may contain complex modules, and these modules can be implemented and used in different ways. In order to solve these problems, we propose a method to handle context information from the result of analyzing massive data. The proposed method considers analysis work as a different type of abstracting context and suggests the way of representing context information. In experiment, we demonstrate how the context processing engine works properly in a couple of steps with healthcare services.

• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.97-110
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• 2022

Federated learning is a learning method capable of performing model learning without transmitting learning data. The IoT or healthcare field is sensitive to information leakage as it deals with users' personal information, so a lot of attention should be paid to system design, but when using federated-learning, data does not move from devices where data is collected. Accordingly, many federated-learning implementations have been developed, but detailed research on system design for the development and operation of systems using federated learning is insufficient. This study shows that measures for the life cycle, code version management, model serving, and device monitoring of federated learning are needed to be applied to actual projects and distributed to IoT devices, and we propose a design for a development environment that complements these points. The system proposed in this paper considered uninterrupted model-serving and includes source code and model version management, device state monitoring, and server-client learning schedule management.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.5
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• pp.1273-1300
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• 2024

In the complex virtual environment of cyberspace, comprised of digital and communication networks, ensuring the security of information is being recognized as an ongoing challenge. The importance of 'Cyber Situation Awareness (CSA)' is being emphasized in response to this. CSA is understood as a vital capability to identify, understand, and respond to various cyber threats and is positioned at the heart of cyber security strategies from a defensive perspective. Critical industries such as finance, healthcare, manufacturing, telecommunications, transportation, and energy can be subjected to not just economic and societal losses from cyber threats but, in severe cases, national losses. Consequently, the importance of CSA is being accentuated and research activities are being vigorously undertaken. A systematic five-step approach to CSA is introduced against this backdrop, and a deep analysis of recent research trends, techniques, challenges, and future directions since 2019 is provided. The approach encompasses current situation and identification awareness, the impact of attacks and vulnerability assessment, the evolution of situations and tracking of actor behaviors, root cause and forensic analysis, and future scenarios and threat predictions. Through this survey, readers will be deepened in their understanding of the fundamental importance and practical applications of CSA, and their insights into research and applications in this field will be enhanced. This survey is expected to serve as a useful guide and reference for researchers and experts particularly interested in CSA research and applications.

• Journal of Information Technology Services
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• v.15 no.4
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• pp.25-39
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• 2016

The drone is an unmanned aerial vehicle which has no human pilot. Drones can be classified into military drones, commercial drones, and personal drones by usage. Also, drones can be classified from large-sized to nano-sized drone by size and autonomous, remote controlled drone by control type. Especially, military drones can be classified into low-altitude drones, medium-altitude, and high-altitude drones by altitude. Recently, the drone industry is one of the fast growing industries in the world. As drone technologies have become more advanced and cost-effective, Korean government has set its goal to become a top-level country in drone business. However, the government's strict regulation for drone operations is one of the biggest hurdles for the development of the related technologies in Korea and other countries. For example, critical problems for drone delivery can be classified into technical issues and institutional issues. Technical issues include durability, conditional awareness, grasp and release mechanisms, collision avoidance systems, drone operating system. Institutional issues include pilot and operator licensing, privacy rules, noise guidelines, security rules, education for drone police. This study analyzes the trends of the drone industry from the viewpoint of technology and regulation. Also, we define the business areas of drone utilization. Especially, the drone business types or models for public sector are proposed. Drone services or functions promoting public interests need to be aligned with the business reference model of Korean government. To define ten types of drone uses for public sector, we combine the business types of government with the future uses of drones that are proposed by futurists and business analysts. Future uses of drones can be divided into three sectors or services. First, drone services for public or military sectors include early warning systems, emergency services, news reporting, police drones, library drones, healthcare drones, travel drones. Second, drone services for commercial or industrial services include parcel delivery drones, gaming drones, sporting drones, farming and agriculture drones, ranching drones, robotic arm drones. Third, drone services for household sector include smart home drones.