• Journal of Radiation Industry
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• v.17 no.4
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• pp.359-367
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• 2023

In this study, the function and purpose of the disposal cover, which is an engineering barrier installed to isolate the disposal vault of the near-surface disposal facility for radioactive waste from natural/man-made intrusion, and the design details of the demonstration facility for performance verification were described. The Demonstration facility was designed in a partially divided form to secure the efficiency of measurement while being the same as the actual size of the surface disposal facility to be built in the Intermediate & low-level radioactive waste disposal site of the Korea Radioactive Waste Agency (KORAD). The instruments used for measurement consist of a multi-point thermometer, FDR (Frequency Domain Reflectometry) sensor, inclinometer, acoustic sensor, flow meter, and meteorological observer. It is used as input data for the monitoring system. The 3D monitoring system was composed of 5 layers using the e-government standard framework, and was developed based on 4 components: screen, control module, service module, and DBIO(DataBase Input Output) module, and connected them to system operation. The monitoring system can provide real-time information on physical changes in the demonstration facility through the collection, analysis, storage, and visualization processes.

• Smart Media Journal
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• v.10 no.2
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• pp.84-91
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• 2021

In the EU GDPR, when collecting personal information, the right of the information subject(user) to consent or refuse is given the highest priority. Therefore, the information subject must be able to withdraw consent and be forgotten and claim the right at any time. Especially, restricted IoT devices(Constrained Node) implement the function of consent of the data subject regarding the collection and processing of privacy data, and it is very difficult to post the utilization content of the collected information. In this paper, we designed and implemented a management system that allows data subjects to monitor data collected and processed from IoT devices, recognize information leakage problems, connect, and control devices. Taking into account the common information of the standard OCF(Open Connectivity Foundation) of IoT devices and AllJoyn, a device connection framework, 10 meta-data for information protection were defined, and this was named DPD (Data Protection Descriptor). we developed DPM (Data Protection Manager), a software that allows information subjects to manage information based on DPD.

• International Journal of Computer Science & Network Security
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• v.24 no.8
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• pp.32-42
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• 2024

The Internet of Things (IoT) is set to transform patient care by enhancing data collection, analysis, and management through medical sensors and wearable devices. However, the convergence of IoT device vulnerabilities and the sensitivity of healthcare data raises significant data integrity and privacy concerns. In response, this research introduces the Smart-Coord system, a practical and affordable solution for securing healthcare IoT. Smart-Coord leverages blockchain technology and coordinate-based access management to fortify healthcare IoT. It employs IPFS for immutable data storage and intelligent Solidity Ethereum contracts for data integrity and confidentiality, creating a hierarchical, AES-CBC-secured data transmission protocol from IoT devices to blockchain repositories. Our technique uses a unique coordinate system to embed confidentiality and integrity regulations into a single access control model, dictating data access and transfer based on subject-object pairings in a coordinate plane. This dual enforcement technique governs and secures the flow of healthcare IoT information. With its implementation on the Matic network, the Smart-Coord system's computational efficiency and cost-effectiveness are unparalleled. Smart-Coord boasts significantly lower transaction costs and data operation processing times than other blockchain networks, making it a practical and affordable solution. Smart-Coord holds the promise of enhancing IoT-based healthcare system security by managing sensitive health data in a scalable, efficient, and secure manner. The Smart-Coord framework heralds a new era in healthcare IoT adoption, expertly managing data integrity, confidentiality, and accessibility to ensure a secure, reliable digital environment for patient data management.

• Smart Structures and Systems
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• v.29 no.1
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• pp.181-193
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• 2022

Data-driven structural health monitoring (SHM) of civil infrastructure can be used to continuously assess the state of a structure, allowing preemptive safety measures to be carried out. Long-term monitoring of large-scale civil infrastructure often involves data-collection using a network of numerous sensors of various types. Malfunctioning sensors in the network are common, which can disrupt the condition assessment and even lead to false-negative indications of damage. The overwhelming size of the data collected renders manual approaches to ensure data quality intractable. The task of detecting and classifying an anomaly in the raw data is non-trivial. We propose an approach to automate this task, improving upon the previously developed technique of image-based pre-processing on one-dimensional (1D) data by enriching the features of the neural network input data with multiple channels. In particular, feature engineering is employed to convert the measured time histories into a 3-channel image comprised of (i) the time history, (ii) the spectrogram, and (iii) the probability density function representation of the signal. To demonstrate this approach, a CNN model is designed and trained on a dataset consisting of acceleration records of sensors installed on a long-span bridge, with the goal of fault detection and classification. The effect of imbalance in anomaly patterns observed is studied to better account for unseen test cases. The proposed framework achieves high overall accuracy and recall even when tested on an unseen dataset that is much larger than the samples used for training, offering a viable solution for implementation on full-scale structures where limited labeled-training data is available.

• Journal of Korean Academy of Nursing
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• v.42 no.2
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• pp.302-309
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• 2012

Purpose: This study aimed to identify contents and trends of Korean nursing doctoral dissertations in terms of research methodology and theoretical characteristics. Methods: The design of the study was descriptive study and a total of 1,089 quantitative studies completed between 1982 and 2010 were reviewed using the analytical framework developed by the researchers. Results: The majority of studies utilized the experimental design (51.5%) and the others were survey design (38.8%) and methodological design (5.0%). Study subjects were shown as patients (45%), care givers (11.2%), ordinary persons (40.6%) and others (3.2%). There were growing trends in experimental design and patients as subjects. The prevailing data collection settings were hospitals (45.8%) and community (27.8%). The theoretical frameworks that studies were based on were the existing theories (37%) and a newly developed theoretical framework by a researcher (25.2%). a framework derived from other studies by the researcher (25.2%). Majority of studies (78.5%) employed a single theory as a theoretical framework. However, 31.8% of studies had no theoretical framework based on. Conclusion: Findings of this study provided the opportunities to shed new light on the current status of Korean doctoral dissertation and to deliberate on the future direction of nursing studies in Korea.

• Journal of the Korean Society for information Management
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• v.35 no.3
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• pp.165-187
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• 2018

Despite repeated efforts to develop a methodological foundation for assembling collaborative authority data in South Korea, issues such as the establishment of a standard authority model and standard authority construction as well as the reconfiguration of existing entities in authority building have prevented such research from generating a cooperative push for nation-wide authority data and progressing toward concrete implementation. The formulation of a collaborative and well-utilized collection of national authority data accordingly calls for 1) a practical approach to supporting both established authority data contributors and newly organized avenues of mutual participation in authority building, 2) committed involvement on the part of national institutions capable of providing the project with sustained assistance, and 3) a standard identification system which allows multiple organizations to merge their data. This study addresses the challenges of the current environment by taking stock of the key components necessary for the creation of collaborative authority data and using a Semantic Web-based interoperable VIVO ontology model to propose a viable national authority data framework.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.521-524
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• 2003

Recently various construction management systems are applied for more efficient project management, and through them as-built construction information is collected. However, the accuracy of the collected information shows big differences among projects, since tile collection of tile as-built information is not based on objective manner or criteria and also each management personnel uses difference criteria on this based on individual experiences. This initiates the need for a development of methods and information frameworks for efficient collection and management of as-built information with assurance of data accuracy. Therefor the objective of this study is to suggest a method to determine the task performance measurement unit depending on the characteristics of work types. A prototype system was developed for generating task performance measurement units by utilizing MS ACCESS. The information framework and the system developed in this research is expected to help standardized performance measurements across projects by improving the objectivity and the accuracy of the collected information.

• The Journal of Information Technology
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• v.4 no.1
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• pp.125-139
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• 2001

EDI(Electronic Data Interchange) works by providing a collection of standard message formats and element dictionary in a simple way for businesses to exchange data via any electronic messaging service. Open-edi is electronic data interchange among autonomous parties using public standards and aiming towards interoperability over time, business sectors, information technology and data types. The number of Internet services using XML/EDI has grown rapidly since it is easily expansible and exchangeable. To use this service, the client does not have to install EDI S/W but only needs internet browser. Consequently, it became much easier and faster to handle the trading process in an office. eBusiness SML (extensible markup language) electronic data interchange. eXedi is the service that realizes B2B of XML/EDI. eXedi can be used easily in small and medium sized companies. Companies in any place can access to eXedi using the existing Internet connection. XML/EDI provides a standard framework to exchange different types of data -- for example, an invoice, healthcare claim, project status -- so that the information be it in a transaction, exchanged via an Application Program Interface (API), web automation, database portal, catalog, a workflow document or message can be searched, decoded, manipulated, and displayed consistently and correctly by first implementing EDI dictionaries and extending our vocabulary via on-line repositories to include our business language, rules and objects.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.510-519
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• 2020

Within an intelligent automated cyber-physical system, the realization of the autonomous mechanism for data collection, data integration, and data analysis plays a critical role in the design, development, operation, and maintenance of such a system. This construct is particularly vital for fault-tolerant route-finding systems that rely on the imprecise GPS location of the vehicles to properly operate, timely plan, and continuously produce informative feedback to the user. More essentially, the integration of digital twins with cyber-physical route-finding systems has been overlooked in intelligent transportation services with the capacity to construct the network routes solely from the locations of the operating vehicles. To address this limitation, the present study proposes a conceptual architecture that employs digital twin to autonomously maintain, update, and manage intelligent transportation systems. This virtual management simulation can improve the accuracy of time-of-arrival prediction based on auto-generated routes on which the vehicle's real-time location is mapped. To that end, first, an intelligent transportation system was developed based on two primary mechanisms: 1) an automated route finding process in which predictive data-driven models (i.e., regularized least-squares regression) can elicit the geometry and direction of the routes of the transportation network from the cloud of geotagged data points of the operating vehicles and 2) an intelligent mapping process capable of accurately locating the vehicles on the map whereby their arrival times to any point on the route can be estimated. Afterward, the digital representations of the physical entities (i.e., vehicles and routes) were simulated based on the auto-generated routes and the vehicles' locations in near-real-time. Finally, the feasibility and usability of the presented conceptual framework were evaluated through the comparison between the primary characteristics of the physical entities with their digital representations. The proposed architecture can be used by the vehicle-tracking applications dependent on geotagged data for digital mapping and location tracking of vehicles under a systematic comparison and simulation cyber-physical system.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.119-131
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• 2024

Understanding accurate traffic performance is crucial for ensuring efficient highway operation and providing a sustainable mobility environment. On the other hand, an immediate and precise estimation of highway traffic performance faces challenges because of infrastructure and technological constraints, data processing complexities, and limitations in using integrated big data. This paper introduces a framework for estimating traffic performance by analyzing real-time data sourced from toll collection systems and dedicated short-range communications used on highways. In particular, this study addresses the data errors arising from segmented information in data, influencing the individual travel trajectories of vehicles and establishing a more reliable Origin-Destination (OD) framework. The study revealed the necessity of trip linkage for accurate estimations when consecutive segments of individual vehicle travel within the OD occur within a 20-minute window. By linking these trip ODs, the daily average highway traffic performance for South Korea was estimated to be248,624 thousand vehicle kilometers per day. This value shows an increase of approximately 458 thousand vehicle kilometers per day compared to the 248,166 thousand vehicle kilometers per day reported in the highway operations manual. This outcome highlights the potential for supplementing previously omitted traffic performance data through the methodology proposed in this study.