• Title/Summary/Keyword: Research Data Sharing

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Object Detection on the Road Environment Using Attention Module-based Lightweight Mask R-CNN (주의 모듈 기반 Mask R-CNN 경량화 모델을 이용한 도로 환경 내 객체 검출 방법)

  • Song, Minsoo;Kim, Wonjun;Jang, Rae-Young;Lee, Ryong;Park, Min-Woo;Lee, Sang-Hwan;Choi, Myung-seok
    • Journal of Broadcast Engineering
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    • v.25 no.6
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    • pp.944-953
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    • 2020
  • Object detection plays a crucial role in a self-driving system. With the advances of image recognition based on deep convolutional neural networks, researches on object detection have been actively explored. In this paper, we proposed a lightweight model of the mask R-CNN, which has been most widely used for object detection, to efficiently predict location and shape of various objects on the road environment. Furthermore, feature maps are adaptively re-calibrated to improve the detection performance by applying an attention module to the neural network layer that plays different roles within the mask R-CNN. Various experimental results for real driving scenes demonstrate that the proposed method is able to maintain the high detection performance with significantly reduced network parameters.

A Study on Use Case of Research Data Sharing in Biotechnology (생명공학분야의 연구데이터 공유 사례에 관한 연구)

  • Park, Miyoung;Ahn, Inja;Kim, Junmo
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.29 no.1
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    • pp.393-416
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    • 2018
  • In this study, major steps of the research data management plan were derived through the research data management guidelines of major countries (NISO DMP in the US, UK DMP in UK archives, etc.). The results obtained are support for research data policy & planning, research data technical support, research data sharing support, research data legal mechanism support, and research data education support. In this study, we analyzed seven cases of data sharing among 7 domestic and foreign biotechnology. Shared use case countries are limited to the United Kingdom and the United States, which play a leading role in the management of research data. In Korea, shared cases were analyzed for the Korean Bio Information Center and related systems, which is a research and performance management and distribution agency designated by the Ministry of Science and Technology.

An Unified Spatial Index and Visualization Method for the Trajectory and Grid Queries in Internet of Things

  • Han, Jinju;Na, Chul-Won;Lee, Dahee;Lee, Do-Hoon;On, Byung-Won;Lee, Ryong;Park, Min-Woo;Lee, Sang-Hwan
    • Journal of the Korea Society of Computer and Information
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    • v.24 no.9
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    • pp.83-95
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    • 2019
  • Recently, a variety of IoT data is collected by attaching geosensors to many vehicles that are on the road. IoT data basically has time and space information and is composed of various data such as temperature, humidity, fine dust, Co2, etc. Although a certain sensor data can be retrieved using time, latitude and longitude, which are keys to the IoT data, advanced search engines for IoT data to handle high-level user queries are still limited. There is also a problem with searching large amounts of IoT data without generating indexes, which wastes a great deal of time through sequential scans. In this paper, we propose a unified spatial index model that handles both grid and trajectory queries using a cell-based space-filling curve method. also it presents a visualization method that helps user grasp intuitively. The Trajectory query is to aggregate the traffic of the trajectory cells passed by taxi on the road searched by the user. The grid query is to find the cells on the road searched by the user and to aggregate the fine dust. Based on the generated spatial index, the user interface quickly summarizes the trajectory and grid queries for specific road and all roads, and proposes a Web-based prototype system that can be analyzed intuitively through road and heat map visualization.

Adaptive Counting Line Detection for Traffic Analysis in CCTV Videos (CCTV영상 내 교통량 분석을 위한 적응적 계수선 검출 방법)

  • Jung, Hyeonseok;Lim, Seokjae;Lee, Ryong;Park, Minwoo;Lee, Sang-Hwan;Kim, Wonjun
    • Journal of Broadcast Engineering
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    • v.25 no.1
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    • pp.48-57
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    • 2020
  • Recently, with the rapid development of image recognition technology, the demand for object analysis in road CCTV videos is increasing. In this paper, we propose a method that can adaptively find the counting line for traffic analysis in road CCTV videos. First, vehicles on the road are detected, and the corresponding positions of the detected vehicles are modeled as the two-dimensional pointwise Gaussian map. The paths of vehicles are estimated by accumulating pointwise Gaussian maps on successive video frames. Then, we apply clustering and linear regression to the accumulated Gaussian map to find the principal direction of the road, which is highly relevant to the counting line. Experimental results show that the proposed method for detecting the counting line is effective in various situations.

A Novel Vehicle Counting Method using Accumulated Movement Analysis (누적 이동량 분석을 통한 영상 기반 차량 통행량 측정 방법)

  • Lim, Seokjae;Jung, Hyeonseok;Kim, Wonjun;Lee, Ryong;Park, Minwoo;Lee, Sang-Hwan
    • Journal of Broadcast Engineering
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    • v.25 no.1
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    • pp.83-93
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    • 2020
  • With the rapid increase of vehicles, various traffic problems, e.g., car crashes, traffic congestions, etc, frequently occur in the road environment of the urban area. To overcome such traffic problems, intelligent transportation systems have been developed with a traffic flow analysis. The traffic flow, which can be estimated by the vehicle counting scheme, plays an important role to manage and control the urban traffic. In this paper, we propose a novel vehicle counting method based on predicted centers of each lane. Specifically, the centers of each lane are detected by using the accumulated movement of vehicles and its filtered responses. The number of vehicles, which pass through extracted centers, is counted by checking the closest trajectories of the corresponding vehicles. Various experimental results on road CCTV videos demonstrate that the proposed method is effective for vehicle counting.

A Study on the Factors Affecting Sharing of Research Data of Science and Technology Researchers (과학기술분야 연구자의 연구데이터 공유의 영향요인에 대한 연구)

  • Kim, Moonjeong;Kim, Seonghee
    • Journal of the Korean Society for Library and Information Science
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    • v.49 no.2
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    • pp.313-334
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    • 2015
  • The purpose of this study was to investigate factors affecting the sharing of research data of science and technology researchers. Data was collected through a survey of 198 science and technology researchers. Independent variables in this study included perception, openness in communication, collaboration, and trust. Latent variable was selected as reward system and dependent variable was research data sharing. The results of analysis of structural equation modeling showed that perception were found to have a positive impact on reward system for data sharing for research. Other factors such as trust, openness in communication and collaboration were not statistically significant in their affect on reward system for data sharing. Finally, reward system was identified as the influential factor on research data sharing.

A Study on the analysis of Research Data Management and Sharing of Science & Technology Government-funded Research Institutes (과학기술분야 출연연구기관 연구데이터 관리 및 공유 사례 분석 연구)

  • Park, Miyoung;Ahn, Inja;Nam, Seungjoo
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.29 no.4
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    • pp.319-344
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    • 2018
  • As a part of the open science policy, this study compared the perception of research data sharing and utilization by academic field. Based on this, in - depth interviews were conducted with semistructured questions to the data task managers of 27 government - funded research institutes in science and technology. Among them, nine excellent organizations were selected from the viewpoint of data management and cases of research data collection and management were specifically presented. The State of the collection and management of research data by the participating research institutes is generally a pilot project stage, and the level of collection and establishment of data also differs by institution. In terms of institutions, they are divided into three levels: the level of collection and establishment of data(KIOM), the advanced level of it (KIST), And level of steps to start sharing (KRIBB, KRICT).

Study about Research Data Citation Based on DCI (Data Citation Index) (Data Citation Index를 기반으로 한 연구데이터 인용에 관한 연구)

  • Cho, Jane
    • Journal of the Korean Society for Library and Information Science
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    • v.50 no.1
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    • pp.189-207
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    • 2016
  • Sharing and reutilizing of research data could not only enhance efficiency and transparency of research process, but also create new science through data integrating and reinterpretationing. Diverse policies about research data sharing and reutilizing have been developing, along with extending of research evaluating spectrum that across research data citation rate to social impact of research output. This study analyzed the scale and citation number of research data which has not been analyzed before in korea through data citation index using Kruskal-Wallis H analysis. As result, genetics and biotechnology are identified as subject areas which have most huge number of research data, however the subject areas that have been highly cited are identified as economics and social study such as, demographic and employment. And Uk Data Archive, Inter-university Consortium for Political and Social Research are analyzed as data repositories which have most highly cited research data. And the data study which describes methodology of data survey, type and so on shows high citation rate than other data type. In the result of altmetrics of research data, data study of social science shows relatively high impact than other areas.

A Study on Analysis of Research Data Repository in Humanities and Social Sciences (re3data를 기반으로 한 인문사회 RDR 연구)

  • Cho, Jane;Park, Jong-Do
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.30 no.2
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    • pp.69-87
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    • 2019
  • As the discussions on sharing research data prevail by the chance of the inauguration of the International Open Data Charter, research support organizations in the United States, the United Kingdom, and Japan are encouraging researchers to deposit their findings in a credible repository. Humanities and social sciences field, in which research data sharing culture and storage infrastructure are immature compared to life science and natural science, also needs to establish and operate a reliable storage infrastructure to guarantee the continuous access and utilization of data. This study analyzed the overall operational status of 305 subject repositories registered in re3data for the humanities and social sciences and clustered them according to the operational level using 5 indicators. As a result, 70% of the population were identified as universal clusters, and 20% of the excellent cluster was found to have the largest number of linguistic fields and the German-operated. In addition, this study confirmed through correspondence analysis that there is a relation between the sub-theme fields of humanities and social sciences and the types of data to be archived. The history and art domians are related to images, and social studies are related to statistical data. Linguistics has also been analyzed to be related to audio, plain text, and code.

Strategies for Improving the Collection and Use of Research Data in the Humanities (인문학 분야 연구데이터의 수집 및 활용성 증진을 위한 전략 연구 - 기초학문자료센터를 중심으로 -)

  • Shim, Wonsik;Ahn, Hye-yeon;Byun, Jeayeon
    • Journal of the Korean Society for Library and Information Science
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    • v.49 no.3
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    • pp.155-183
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    • 2015
  • The rapid growth of information technologies and data networks has increased the volume of data generated from scholarly research and the possibilities of re-using and sharing such data. However, there is a serious problem of management and sharing of research data due to the lack of facilitating policies and supporting infrastructure. In particular, few data repositories exist that support systematic collection and sharing of research data in the humanities. In this regard, the Korea Research Memory (KRM) established by the Korea Research Foundation is a rare exception. The purpose of this research is to present specific processes and strategies that can facilitate the data collection, reuse and preservation through the KRM using task analysis and source document gathering as main focal points. In addition, in order for the effective collection and sharing of research data, the following recommendations are proposed: 1) the need for the adoption of data management plan related policies that govern the collection and sharing of research data generated from publicly funded research projects, 2) the need for training and support services for individual researchers and research institutes, 3) the need for training data specialists, and 4) the citation scheme and structure designed for research data.