• Title/Summary/Keyword: Public Dataset

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Construction and Effectiveness Evaluation of Multi Camera Dataset Specialized for Autonomous Driving in Domestic Road Environment (국내 도로 환경에 특화된 자율주행을 위한 멀티카메라 데이터 셋 구축 및 유효성 검증)

  • Lee, Jin-Hee;Lee, Jae-Keun;Park, Jaehyeong;Kim, Je-Seok;Kwon, Soon
    • IEMEK Journal of Embedded Systems and Applications
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    • v.17 no.5
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    • pp.273-280
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    • 2022
  • Along with the advancement of deep learning technology, securing high-quality dataset for verification of developed technology is emerging as an important issue, and developing robust deep learning models to the domestic road environment is focused by many research groups. Especially, unlike expressways and automobile-only roads, in the complex city driving environment, various dynamic objects such as motorbikes, electric kickboards, large buses/truck, freight cars, pedestrians, and traffic lights are mixed in city road. In this paper, we built our dataset through multi camera-based processing (collection, refinement, and annotation) including the various objects in the city road and estimated quality and validity of our dataset by using YOLO-based model in object detection. Then, quantitative evaluation of our dataset is performed by comparing with the public dataset and qualitative evaluation of it is performed by comparing with experiment results using open platform. We generated our 2D dataset based on annotation rules of KITTI/COCO dataset, and compared the performance with the public dataset using the evaluation rules of KITTI/COCO dataset. As a result of comparison with public dataset, our dataset shows about 3 to 53% higher performance and thus the effectiveness of our dataset was validated.

A Study on Data Quality Evaluation of Administrative Information Dataset (행정정보데이터세트의 데이터 품질평가 연구)

  • Song, Chiho;Yim, Jinhee
    • The Korean Journal of Archival Studies
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    • no.71
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    • pp.237-272
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    • 2022
  • In 2019, the pilot project to establish a record management system for administrative information datasets started in earnest under the leadership of the National Archives. Based on the results of the three-year project by 2021, the improved administrative information dataset management plan will be reflected in public records-related laws and guidelines. Through this, the administrative information dataset becomes the target of full-scale public record management. Although public records have been converted to electronic documents and even the datasets of administrative information systems have been included in full-scale public records management, research on the quality requirements of data itself as raw data constituting records is still lacking. If data quality is not guaranteed, all four properties of records will be threatened in the dataset, which is a structure of data and an aggregate of records. Moreover, if the reliability of the quality of the data of the administrative information system built by reflecting the various needs of the working departments of the institution without considering the standards of the standard records management system is insufficient, the reliability of the public records itself can not be secured. This study is based on the administrative information dataset management plan presented in the "Administrative Information Dataset Recorded Information Service and Utilization Model Study" conducted by the National Archives of Korea in 2021. A study was conducted. By referring to various data, especially public data-related policies and guides, which are being promoted across the government, we would like to derive quality evaluation requirements in terms of records management and present specific indicators. Through this, it is expected that it will be helpful for record management of administrative information dataset which will be in full swing in the future.

A Study on the Role of Records Center for Dataset Records Management: Focused on Case Study of KR Project Management System (데이터세트 기록관리를 위한 기록관의 역할 연구: KR 사업관리시스템 사례를 중심으로)

  • Lee, Kyungnam;Choi, Kwanghoon;Yim, Jinhee
    • Journal of the Korean Society for information Management
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    • v.38 no.3
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    • pp.263-285
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    • 2021
  • It is necessary to recognize the urgency and importance of administrative information dataset management and study effective management measures and specific procedures applicable in practice. Particularly, identify dataset records and developing records schedule for records management needs to be presented in detail and specific. This study designed and verified an identification method and appraisal procedure of dataset records in public administrative information systems dataset operating in public institutions. In addition, this study presented the role of the participants including the records center in the appraisal process. Through this, useful implications are derived for the development of specific and practical processes and tools for dataset management in the records center.

STAR-24K: A Public Dataset for Space Common Target Detection

  • Zhang, Chaoyan;Guo, Baolong;Liao, Nannan;Zhong, Qiuyun;Liu, Hengyan;Li, Cheng;Gong, Jianglei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.2
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    • pp.365-380
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    • 2022
  • The target detection algorithm based on supervised learning is the current mainstream algorithm for target detection. A high-quality dataset is the prerequisite for the target detection algorithm to obtain good detection performance. The larger the number and quality of the dataset, the stronger the generalization ability of the model, that is, the dataset determines the upper limit of the model learning. The convolutional neural network optimizes the network parameters in a strong supervision method. The error is calculated by comparing the predicted frame with the manually labeled real frame, and then the error is passed into the network for continuous optimization. Strongly supervised learning mainly relies on a large number of images as models for continuous learning, so the number and quality of images directly affect the results of learning. This paper proposes a dataset STAR-24K (meaning a dataset for Space TArget Recognition with more than 24,000 images) for detecting common targets in space. Since there is currently no publicly available dataset for space target detection, we extracted some pictures from a series of channels such as pictures and videos released by the official websites of NASA (National Aeronautics and Space Administration) and ESA (The European Space Agency) and expanded them to 24,451 pictures. We evaluate popular object detection algorithms to build a benchmark. Our STAR-24K dataset is publicly available at https://github.com/Zzz-zcy/STAR-24K.

A Study on Data Adjustment and Quality Enhancement Method for Public Administrative Dataset Records in the Transfer Process-Based on the Experiences of Datawarehouses' ETT (행정정보 데이터세트 기록 이관 시 데이터 보정 및 품질 개선 방법 연구 - 데이터웨어하우스 ETT 경험을 기반으로)

  • Yim, Jin-Hee;Cho, Eun-Hee
    • The Korean Journal of Archival Studies
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    • no.25
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    • pp.91-129
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    • 2010
  • As it grows more heavily reliant on information system, researchers seek for various ways to manage and utilize of dataset records which is accumulated in public information system. It might be needed to adjust date and enhance the quality of public administrative dataset records during transferring to archive system or sharing server. The purpose of this paper is presenting data adjustment and quality enhancement methods for public administrative dataset records, and it refers to ETT procedure and method of construction of datawarehouses. It suggests seven typical examples and processing method of data adjustment and quality enhancement, which are (1) verification of quantity and data domain (2) code conversion for a consistent code value (3) making component with combinded information (4) making a decision of precision of date data (5) standardization of data (6) comment information about code value (7) capturing of metadata. It should be reviewed during dataset record transfer. This paper made Data adjustment and quality enhancement requirements for dataset record transfer, and it could be used as data quality requirement of administrative information system which produces dataset.

Building-up and Feasibility Study of Image Dataset of Field Construction Equipments for AI Training (인공지능 학습용 토공 건설장비 영상 데이터셋 구축 및 타당성 검토)

  • Na, Jong Ho;Shin, Hyu Soun;Lee, Jae Kang;Yun, Il Dong
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.43 no.1
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    • pp.99-107
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    • 2023
  • Recently, the rate of death and safety accidents at construction sites is the highest among all kinds of industries. In order to apply artificial intelligence technology to construction sites, it is essential to secure a dataset which can be used as a basic training data. In this paper, a number of image data were collected through actual construction site, for which major construction equipment objects mainly operated in civil engineering sites were defined. The optimal training dataset construction was completed by annotation process of about 90,000 image dataset. Reliability of the dataset was verified with the mAP of over 90 % in use of YOLO, a representative model in the field of object detection. The construction equipment training dataset built in this study has been released which is currently available on the public data portal of the Ministry of Public Administration and Security. This dataset is expected to be freely used for any application of object detection technology on construction sites especially in the field of construction safety in the future.

A Study on Managing Dataset in the Administration Information System of Closed Private Universities (폐교 사립대학 행정정보 데이터세트의 기록관리 방안 연구)

  • Lee, Jae-Young;Chung, Yeon-Kyoung
    • 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.

A Study on the Service of the Integrated Administrative Information Dataset Management System (행정정보 데이터세트 종합관리시스템의 서비스 방안 연구)

  • Kim, Ji-Hye;Yoon, Sung-Ho;Yang, Dongmin
    • 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.

Current Status Analysis of Business Units and Retention Period Estimation related to Administrative Information Systems of Public Institutions (공공기관 행정정보시스템 관련 단위과제 및 보존기간 책정 현황분석)

  • Yoon, Sung-Ho;Yu, Sin Seong;Choi, Kippeum;Oh, Hyo-Jung
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.31 no.2
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    • pp.139-160
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    • 2020
  • Since the Public Records Management Act was enacted in 2007, the administrative information system has already been included in the electronic records production system, and dataset has been subject to record management as a type of electronic records. With the recent revision of the enforcement decree, dataset records management has been enacted. This study analyzes business units related to administrative information systems of public institutions and examines the current status of retention periods estimation. For this purpose, we collected 36 records classification systems from 49 public institutions among the direct management agencies of the National Archives and disaster management agencies. And we discriminated 824 business units related to administrative information system and divided into large and small groups according to types. We also compared the retention period estimation of records. The problems and improvement plans of this study are expected to be used as basic data in preparing the standard of administrative dataset management in the future.

A Study on Managing Dataset Records in Government Information Systems (행정정보 데이터세트 기록의 관리방안)

  • Wang, Ho-sung;Seol, Moon-won
    • Journal of Korean Society of Archives and Records Management
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    • v.17 no.3
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    • pp.23-47
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    • 2017
  • According to a recent survey, over 18,000 government information systems have numerous different functions and characteristics. Although every dataset that is created and maintained in government information systems is declared as a collection of records according to the Public Records Management Act, current electronic records management policies cannot cover dataset records management. This study suggests the policy directions for dataset records management at the national level. It emphasizes the necessity to preserve the appearance and behavior (function) of database systems to ensure the authenticity of dataset records. In addition, this study investigates "emulation" as a representation and long-term preservation methodology for dataset-type records. It also suggests a dataset records model.