• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.23 no.1
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• pp.31-38
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• 2005

Importance of road that is country base equipment is occupying fair part. Therefore, establishment of road and maintenance expense for road management are increasing continuously. These problem can manage efficiently through data model construction that take advantage of framework data. But, because of difference of method of study in research institution, framework data research was constructed being overlapped until current. This is because framework data research was no access of application side. Therefore, National Geographic Information Institute presented subject framework data model guide through framework data model standardization business. This research constructed road management data model that take advantage of traffic framework data. Therefore, we can check equal data construction and reduce expense accordingly. Also, because there are not data model development instances by framework data model, it is difficult that judge whether is suitable to apply framework data model guide. Hence, in this study, the extended road management data medel and the suitability of framework data is presented.

• Journal of Korean Academy of Nursing Administration
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• v.18 no.2
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• pp.222-233
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• 2012

Purpose: This study was conducted to develop an evaluation framework for QI activity in medical institutions and to analyze QI activity cases by applying the developed evaluation framework. Method: A four-phase process was employed to develop the evaluation framework, and a descriptive survey was used for the QI case study. Data were collected in April, 2010 by examining 157 QI activity cases presented at conferences and published in Journal of Korean Society of Quality Assurance in Health Care over the past three years. Developed QI activity evaluation instruments were used for data collection. Data were analyzed using the SPSS 18.0 for Windows program. Result: A QI Activity Evaluation Framework was developed. This framework consisted of 45 items. The department with the highest level of QI participation was the nursing department. The most frequent QI activity theme was patient safety. QI activity levels in Korean medical institutions are relatively equalized without significant differences according to institution characteristics. Conclusions: From the quality aspect of QI activity, more systematic and scientific approaches are required to upgrade QI activity. This study could provide methodological guidelines for QI activity and be useful in setting goals and directions for QI activity in medical institutions in Korea.

• Journal of Animal Science and Technology
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• v.66 no.1
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• pp.167-177
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• 2024

Iris segmentation is an initial step for identifying the biometrics of animals when establishing a traceability system for livestock. In this study, we propose a deep learning framework for pixel-wise segmentation of bovine iris with a minimized use of annotation labels utilizing the BovineAAEyes80 public dataset. The proposed image segmentation framework encompasses data collection, data preparation, data augmentation selection, training of 15 deep neural network (DNN) models with varying encoder backbones and segmentation decoder DNNs, and evaluation of the models using multiple metrics and graphical segmentation results. This framework aims to provide comprehensive and in-depth information on each model's training and testing outcomes to optimize bovine iris segmentation performance. In the experiment, U-Net with a VGG16 backbone was identified as the optimal combination of encoder and decoder models for the dataset, achieving an accuracy and dice coefficient score of 99.50% and 98.35%, respectively. Notably, the selected model accurately segmented even corrupted images without proper annotation data. This study contributes to the advancement of iris segmentation and the establishment of a reliable DNN training framework.

• ETRI Journal
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• v.43 no.1
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• pp.53-63
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• 2021

Cloud computing has drastically reduced the price of computing resources through the use of virtualized resources that are shared among users. However, the established large cloud data centers have a large carbon footprint owing to their excessive power consumption. Inefficiency in resource utilization and power consumption results in the low fiscal gain of service providers. Therefore, data centers should adopt an effective resource-management approach. In this paper, we present a novel load-balancing framework with the objective of minimizing the operational cost of data centers through improved resource utilization. The framework utilizes a modified genetic algorithm for realizing the optimal allocation of virtual machines (VMs) over physical machines. The experimental results demonstrate that the proposed framework improves the resource utilization by up to 45.21%, 84.49%, 119.93%, and 113.96% over a recent and three other standard heuristics-based VM placement approaches.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.23 no.2
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• pp.157-163
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• 2005

In the 21th century as knowledge-based society and according as GIS is embossed, demand of map is increasing rapidly for GIS's basic. Ministry of Construction & Transportation Republic of Korea National Geographic Information Institute who supervise basis geography information run the studies of basis geography information construction, therefore choice of each subject extent and standardization of data model for basis geography information is attained. In this study, framework data has been established in three steps according to Framework data Product Specification in Facility Area. Also the evaluation of usability was implemented as combining Framework data.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.3
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• pp.293-301
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• 2002

MGF(Marine Geographical Framework) data are the essential data sets concerning graphical and attribute information on coast and ocean among various marine-related data, which consist of framework data of the National Spatial Data Infrastructure(NSDI). This study did research and analyzed the development of current data, the situation of its usage, related technical environment and case study of foreign countries through the survey on the users and experts. Then the item of marine geographical framework data was selected in accordance with the measures for usage and management of possible MGF data. A map was pilot producted based on selected items and MGF data was presented through making up some problems shown ill the process. The importance of GIS will be growing continuously which can develop, deal with and provide the various data to efficiently manage coast and ocean. Accordingly, the MGF data will be applied to various areas such as Internet or raw data for marine information system.

• Journal of Korean Library and Information Science Society
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• v.51 no.2
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• pp.103-131
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• 2020

This study was started with the aim of grasping the current status of research data management of forestry engineering researchers. In order to achieve the research purpose, the survey was conducted using a tool called DAF (Data Asset Framework). DAF is an investigative tool that provides a means to identify, position, describe and evaluate how the agency manages research data. Using this DAF, the research data management status was analyzed for researchers in the field of forestry engineering at the National Institute of Forest Science. As a result of analysis, the current status and problems of the five categories such as the method and type of research data creation, sharing, storage, preservation, and reuse were identified, and solutions were presented in relation to the problems. This study is a basic investigation using a systematic tool such as DAF, and can be used as a reference for analyzing the current status and problems of research data when designing RDM system in a specific field.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2292-2313
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• 2023

With improving computing performance, various digital platforms are being developed to enable easily utilization of high-performance computing environments. EDISON 1.0 is an online simulation platform widely used in computational science and engineering education. As the research paradigm changes, the demand for developing the EDISON 1.0 platform centered on simulation into the EDISON 2.0 platform centered on data and artificial intelligence is growing. Herein, a data framework, a core module for data-centric research on EDISON 2.0 digital platform, is proposed. The proposed data framework provides the following three functions. First, it provides a data repository suitable for the data lifecycle to increase research reproducibility. Second, it provides a new data model that can integrate, manage, search, and utilize heterogeneous data to support a data-driven interdisciplinary convergence research environment. Finally, it provides an exploratory data analysis (EDA) service and data enrichment using an AI model, both developed to strengthen data reliability and maximize the efficiency and effectiveness of research endeavors. Using the EDISON 2.0 data framework, researchers can conduct interdisciplinary convergence research using heterogeneous data and easily perform data pre-processing through the web-based UI. Further, it presents the opportunity to leverage the derived data obtained through AI technology to gain insights and create new research topics.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.6
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• pp.305-312
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• 2018

Software has been used to develop many functions of the modern weapon systems which has a high mission criticality. Weapon system software must consider multi-threaded processing to satisfy growing performance requirement. However, developing multi-threaded programs are difficult because of concurrency faults, such as unintended data races. Especially, it is important to prepare analysis for debugging the data races, because the weapon system software may cause personal injury. In this paper, we present an efficient framework of analysis, called ConDeWS, which is designed to determine the scope of dynamic analysis through using the result of static analysis and fault analysis. As a result of applying the implemented framework to the target software, we have detected unintended data races that were not detected in the static analysis.

• Journal of the Korean Data and Information Science Society
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• v.18 no.4
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• pp.1157-1170
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• 2007

LBS must manage various context data and make the best use of this data for application service in ubiquitous environment. Conventional mobile object data management architecture did not consider process of context data. Therefore a new mobile data management framework is needed to process location context data. In this paper, we design a new context management framework for a location based application service. A suggestion framework is consisted of context collector, context manager, rule base, inference engine, and mobile object context database. It describes a form of rule base and a movement process of inference engine that are based on location based application scenario. It also presents an embodiment instance of interface which suggested framework is applied to location context interference of mobile object.