• Journal of Korean Society of Archives and Records Management
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• v.22 no.1
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• pp.177-200
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• 2022

Administrative information datasets are a kind of record produced based on an organization's work performance. A dataset is evidence of the act of recording and contains a lot of information that can be used for work. Datasets have been neglected in Korea's records management system. However, as the law was revised in 2020, the management of administrative information datasets was legislated. Organizations that require management of administrative information datasets have already gradually begun record management. The core of managing administrative information datasets is the preparation of the Management Reference Table for the dataset. Regardless, there is confusion with the Records Management Reference Table for Dataset in institutions that work on records management, and it is difficult to work because the Management Reference Table for Dataset has a new concept. This study looked into the problems in the records management of datasets that appeared at the beginning of work. It isuggests a method to effectively settle records management for datasets. In that way, the Management Reference Table was selected as the research subject, and the problems discussed so far were summarized. In addition, the items of the current Management Reference Table were analyzed. As a result of the study, we have proposed the simplification of items in the Management Reference Table, the reorganization of areas in the Management Reference Table, the introduction of the concept of retention periods, and the preparation process of the Management Reference Table.

• Journal of Korean Society of Archives and Records Management
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• v.21 no.3
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• pp.227-246
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• 2021

The study seeks to analyze the procedures and methods of preparing the records management reference table of the electronic human resource management system dataset, the roles of participating organizations, and the contents of each management reference table area from the records manager's perspective to help the person in charge of establishing the management reference table. Improvement plans were suggested based on the problems that appeared during the process of preparing the reference table. As a major improvement plan, a separate selecting policy at the level of the national archives should be designed for the national important dataset records in the government information system, which should be operated such that it preserves the entire dataset rather than a part. It is necessary to set the unit function-data table-unstructured data mapping data as mandatory items, and the selection and management criteria for unstructured data that significantly influence system operation should be additionally prepared. Regarding the setting of the disposition delay period, because there is an aspect of increasing complexity, it is deemed desirable to operate it by integrating related unit functions or setting the retention period longer.

• Journal of Korean Society of Archives and Records Management
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• v.22 no.2
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• pp.51-73
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• 2022

Currently, an implementation plan of administrative information dataset record management has been prepared; however, analyzing the specificity of various administrative information systems and preparing a reasonable level of management reference table by applying about 1.3% (EA portal registration system: 16,199, consulting system: 214) has its limitations. This study started by recognizing the importance of the records management environment in administrative information datasets. Based on the described information, the current records management environment was analyzed by dividing the six areas of the management reference table of the picture archiving and communication system (PACS) into three groups. Thus, a systematic environmental improvement model was proposed, enhancing the effectiveness of dataset records management in the field. Although there is a limitation in analyzing one of the dataset records management environments of various institutions, it is intended to help broaden the horizons of records management research.

• Journal of Korean Society of Archives and Records Management
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• v.22 no.2
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• pp.27-49
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• 2022

According to the amendment of the Enforcement Decree of the Public Records Management Act in 2020, an administrative information dataset record management plan will be enacted, and the National Archives of Korea plans to establish an integrated administrative information dataset management system to support it. However, there is no specific service plan that considers the characteristics of the datasets and the Management Reference Table. Therefore, this paper compared and analyzed the current status of dataset services at 14 domestic and foreign public data portals and archives websites, derived implications, and proposed 6 service plans applicable to the integrated administrative information dataset management system. This study's results will lead to utilizing the administrative datasets and the activation of services.

• Journal of Multimedia Information System
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• v.9 no.2
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• pp.75-86
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• 2022

The existing image quality assessment (IQA) datasets have a small number of samples. Some methods based on transfer learning or data augmentation cannot make good use of image quality-related features. A No Reference (NR)-IQA method based on multi-task training and quality awareness is proposed. First, single or multiple distortion types and levels are imposed on the original image, and different strategies are used to augment different types of distortion datasets. With the idea of weak supervision, we use the Full Reference (FR)-IQA methods to obtain the pseudo-score label of the generated image. Then, we combine the classification information of the distortion type, level, and the information of the image quality score. The ResNet50 network is trained in the pre-train stage on the augmented dataset to obtain more quality-aware pre-training weights. Finally, the fine-tuning stage training is performed on the target IQA dataset using the quality-aware weights to predicate the final prediction score. Various experiments designed on the synthetic distortions and authentic distortions datasets (LIVE, CSIQ, TID2013, LIVEC, KonIQ-10K) prove that the proposed method can utilize the image quality-related features better than the method using only single-task training. The extracted quality-aware features improve the accuracy of the model.

• Korean Journal of Remote Sensing
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• v.34 no.4
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• pp.601-610
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• 2018

The national accuracy of global land cover (GLC) products is of great importance to ecological and environmental research. However, GLC products that are derived from different satellite sensors, with differing spatial resolutions, classification methods, and classification schemes are certain to show some discrepancies. The goal of this study is to assess the accuracy of four commonly used GLC datasets in South Korea, GLC2000, GlobCover2009, MCD12Q1, and GlobeLand30. First, we compared the area of seven classes between four GLC datasets and a reference dataset. Then, we calculated the accuracy of the four GLC datasets based on an aggregated classification scheme containing seven classes, using overall, producer's and user's accuracies, and kappa coefficient. GlobeLand30 had the highest overall accuracy (77.59%). The overall accuracies of MCD12Q1, GLC2000, and GlobCover2009 were 75.51%, 68.38%, and 57.99%, respectively. These results indicate that GlobeLand30 is the most suitable dataset to support a variety of national scientific endeavors in South Korea.

• ETRI Journal
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• v.33 no.5
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• pp.741-751
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• 2011

This paper focuses on online speaker tracking for telephone conversations and broadcast news. Since the online applicability imposes some limitations on the tracking strategy, such as data insufficiency, a reliable approach should be applied to compensate for this shortage. In this framework, a set of reference speaker models are used as side information to facilitate online tracking. To improve the indexing accuracy, adaptation approaches in eigenvoice decomposition space are proposed in this paper. We believe that the eigenvoice adaptation techniques would help to embed the speaker space in the models and hence enrich the generality of the selected speaker models. Also, an index structure of the reference models is proposed to speed up the search in the model space. The proposed framework is evaluated on 2002 Rich Transcription Broadcast News and Conversational Telephone Speech corpus as well as a synthetic dataset. The indexing errors of the proposed framework on telephone conversations, broadcast news, and synthetic dataset are 8.77%, 9.36%, and 12.4%, respectively. Using the index tree structure approach, the run time of the proposed framework is improved by 22%.

• New & Renewable Energy
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• v.20 no.1
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• pp.102-109
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• 2024

The Typical Meteorological Year (TMY) dataset compiles 12 months of data that best represent long-term climate patterns, focusing on global horizontal irradiance and other weather-related variables. However, the irradiance measured on the plane of the array (POA) shows certain distinct distribution characteristics compared with the irradiance in the TMY dataset, and this may introduce some biases. Our research recalculated POA irradiance using both the Isotropic and DIRINT models, generating an updated dataset that was tailored to POA characteristics. Our analysis showed a 28% change in the selection of typical meteorological months, an 8% increase in average irradiance, and a 40% reduction in the range of irradiance values, thus indicating a significant shift in irradiance distribution patterns. This research aims to inform stakeholders about accurate use of TMY datasets in potential decision-making. These findings underscore the necessity of creating a typical dataset by using the time series of POA irradiance, which represents the orientation in which PV panels will be deployed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.5
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• pp.186-201
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• 2021

As autonomous driving technology advances, the accuracy of the vehicle position is important for recognizing the environments around driving. Map-matching localization techniques based on high definition (HD) maps have been studied to improve localization accuracy. Because conventional map-matching techniques estimate the vehicle position based on an HD map reference dataset representing the center of the lane, the estimated position does not reflect the deviation of the lateral distance within the lane. Therefore, this paper proposes a localization system based on the reference lateral position dataset extracted using image processing and HD maps. Image processing extracts the driving lane number using inverse perspective mapping, multi-lane detection, and yellow central lane detection. The lane departure method estimates the lateral distance within the lane. To collect the lateral position reference dataset, this approach involves two processes: (i) the link and lane node is extracted based on the lane number obtained from image processing and position from GNSS/INS, and (ii) the lateral position is matched with the extracted link and lane node. Finally, the vehicle position is estimated by matching the GNSS/INS local trajectory and the reference lateral position dataset. The performance of the proposed method was evaluated by experiments carried out on a highway environment. It was confirmed that the proposed method improves accuracy by about 1.0m compared to GNSS / INS, and improves accuracy by about 0.04m~0.21m (7~30%) for each section when compared with the existing lane-level map matching method.

• Journal of Korean Society of Archives and Records Management
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• v.21 no.1
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• pp.75-95
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• 2021

In this study, we focused on creating plans to manage the administrative information dataset of public records in closed universities. In particular, according to various reference materials and internal materials of the institution, we studied the theoretical discussion about the dataset and figured out the management status of the closed university's dataset. Therefore, as a measure for the data management of the Comprehensive Information Management System, recording targets are selected, retention periods are determined, administrative information dataset management standards are prepared, administrative information dataset evaluation and deletion are implemented, and comprehensive management systems of closed universities are established.