• Title/Summary/Keyword: R&D classification

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A Study on the Process Improvement of ICT Technological Innovation System : with the Focus on Classification and Assessment of R&D Projects (ICT 기술혁신체계 프로세스 개선방안 연구 : 과제구분 및 선정평가를 중심으로)

  • Rim, Myung Hwan;Koh, Soon Ju;Lee, Jung Mann
    • Korean Management Science Review
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    • v.33 no.3
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    • pp.53-64
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    • 2016
  • The government is mapping out R&D innovation measures aimed at improving the qualitative level of the performance of national R&D projects that are supported by grants or public funds. This paper proposes ways of making improvements in technology planning, project assessment, performance management, and results evaluation in order to boost the efficiency of the country's promotion of ICT R&D projects, as well as to upgrade the processes involved with its technological innovation system at each of the commercialization stages of its R&D projects. According to our experts' in-depth survey and interview, it has been found that technology planning is the most important phase in the full cycle-based technological innovation system and that the promotion of a combination of top-down and bottom-up approaches is the most reasonable. This paper also suggests it is necessary to secure a process for exploring technological opportunities as the preparatory phase for technology planning, and that it is desirable to reflect the technology demand map associated with the technology road map. Currently, R&D projects are divided into policy designation, designation contest, and free contest. To minimize the inefficiency associated with indiscriminate competition, this paper proposes the introduction of a general contest system in order to change the project assessment system into one based on the results of the competition in each category(e.g. firms, universities, research institutions, etc.).

A Study on the Building of Integrated Service for Science and Technology Knowledge Infrastructure Supporting the Entire R&D Cycle (R&D 전주기 지원형 과학기술 지식인프라 통합서비스 구축에 관한 연구)

  • Lee, Seok Hyoung
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.31 no.3
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    • pp.235-256
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    • 2020
  • The purpose of this study is to define a method of building an integrated service to provide various science and technology knowledge infrastructures that are helpful in R&D activities, and to show the cases that are adapted the methodologies. Knowledge infrastructures scattered throughout the entire R&D cycle, such as generating/development of ideas, finding the R&D project, performing the project, and spreading results, are segmented in terms of services, functions, information, and data, and links and converges to provide the knowledge infrastructure that desired by users in one place. We define the integrated service classification, integration level model, integrated architecture, and integrated user authentication system in consideration of logical linkage and integration rather than physical integration of individual knowledge infrastructures. Also, we considered the extensibility as the reference model for building of similar integrated service.

Performance analysis in automatic modulation classification based on deep learning (딥러닝 기반 자동 변조 인식 성능 분석)

  • Kang, Jong-Jin;Kim, Jae-Hyun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.3
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    • pp.427-432
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    • 2021
  • In this paper, we conduct performance analysis in automatic modulation classification of unknown communication signal to identify its modulation types based on deep neural network. The modulation classification performance was verified using time domain digital sample data of the modulated signal, frequency domain data to which FFT was applied, and time and frequency domain mixed data as neural network input data. For 11 types of analog and digitally modulated signals, the modulation classification performance was verified in various SNR environments ranging from -20 to 18 dB and reason for false classification was analyzed. In addition, by checking the learning speed according to the type of input data for neural network, proposed method is effective for constructing an practical automatic modulation recognition system that require a lot of time to learn.

A New Object Region Detection and Classification Method using Multiple Sensors on the Driving Environment (다중 센서를 사용한 주행 환경에서의 객체 검출 및 분류 방법)

  • Kim, Jung-Un;Kang, Hang-Bong
    • Journal of Korea Multimedia Society
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    • v.20 no.8
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    • pp.1271-1281
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    • 2017
  • It is essential to collect and analyze target information around the vehicle for autonomous driving of the vehicle. Based on the analysis, environmental information such as location and direction should be analyzed in real time to control the vehicle. In particular, obstruction or cutting of objects in the image must be handled to provide accurate information about the vehicle environment and to facilitate safe operation. In this paper, we propose a method to simultaneously generate 2D and 3D bounding box proposals using LiDAR Edge generated by filtering LiDAR sensor information. We classify the classes of each proposal by connecting them with Region-based Fully-Covolutional Networks (R-FCN), which is an object classifier based on Deep Learning, which uses two-dimensional images as inputs. Each 3D box is rearranged by using the class label and the subcategory information of each class to finally complete the 3D bounding box corresponding to the object. Because 3D bounding boxes are created in 3D space, object information such as space coordinates and object size can be obtained at once, and 2D bounding boxes associated with 3D boxes do not have problems such as occlusion.

A Service Framework for Supporting XML-based National Research and Development Report Contents (XML 기반 국가연구개발보고서 콘텐츠 서비스의 프레임워크 설계)

  • Shon, Ho-Sun;Lee, Jong-Yun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.12 no.1
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    • pp.427-435
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    • 2011
  • The information management system for the national R&D reports on the level of each government department have been operated in order to have special affiliated organizations collect detailed information, construct databases for R&D reports, and operate their information system; thus, the current classification system for the R&D reports on the governmental level is insufficient. Also, each department requires to prepare a standardized electronic original text service system since mutually different electronic original text services have been provided. therefore, this paper sets up the following research goals and detailed research contents. The goals of this study are to establish methods to standardize the forms of national R&D reports and suggest the framework for XML-based national R&D reports services by analyzing the problems in the forms of previous national R&D reports services. As detailed research contents, first, Identify the current R&D electronic original reports services by each government department. Second, this paper analyzed primary overseas science technology information service systems related with national research and development reports and related database schemata. this paper proposed the XML-based national R&D reports service framework through analyzing the problems in the framework of the existing national R&D reports service system and also established and suggested the methods to provide database schema design and report portal services. Lastly, it is expected that this paper will have academic contribution to enhancing R&D investment efficiency by utilizing collaboratively the information and resources related with national R&D through establishing the general information management system for national-dimension R&D reports and also managing science technology information efficiently and developing a user-centered integrated information system.

Classification of Terrestrial LiDAR Data Using Factor and Cluster Analysis (요인 및 군집분석을 이용한 지상 라이다 자료의 분류)

  • Choi, Seung-Pil;Cho, Ji-Hyun;Kim, Yeol;Kim, Jun-Seong
    • Journal of Korean Society for Geospatial Information Science
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    • v.19 no.4
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    • pp.139-144
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    • 2011
  • This study proposed a classification method of LIDAR data by using simultaneously the color information (R, G, B) and reflection intensity information (I) obtained from terrestrial LIDAR and by analyzing the association between these data through the use of statistical classification methods. To this end, first, the factors that maximize variance were calculated using the variables, R, G, B, and I, whereby the factor matrix between the principal factor and each variable was calculated. However, although the factor matrix shows basic data by reducing them, it is difficult to know clearly which variables become highly associated by which factors; therefore, Varimax method from orthogonal rotation was used to obtain the factor matrix and then the factor scores were calculated. And, by using a non-hierarchical clustering method, K-mean method, a cluster analysis was performed on the factor scores obtained via K-mean method as factor analysis, and afterwards the classification accuracy of the terrestrial LiDAR data was evaluated.

Radiomics-based Biomarker Validation Study for Region Classification in 2D Prostate Cross-sectional Images (2D 전립선 단면 영상에서 영역 분류를 위한 라디오믹스 기반 바이오마커 검증 연구)

  • Jun Young, Park;Young Jae, Kim;Jisup, Kim;Kwang Gi, Kim
    • Journal of Biomedical Engineering Research
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    • v.44 no.1
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    • pp.25-32
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    • 2023
  • Recognizing the size and location of prostate cancer is critical for prostate cancer diagnosis, treatment, and predicting prognosis. This paper proposes a model to classify the tumor region and normal tissue with cross-sectional visual images of prostatectomy tissue. We used specimen images of 44 prostate cancer patients who received prostatectomy at Gachon University Gil Hospital. A total of 289 prostate slice images consist of 200 slices including tumor region and 89 slices not including tumor region. Images were divided based on the presence or absence of tumor, and a total of 93 features from each slice image were extracted using Radiomics: 18 first order, 24 GLCM, 16 GLRLM, 16 GLSZM, 5 NGTDM, and 14 GLDM. We compared feature selection techniques such as LASSO, ANOVA, SFS, Ridge and RF, LR, SVM classifiers for the model's high performances. We evaluated the model's performance with AUC of the ROC curve. The results showed that the combination of feature selection techniques LASSO, Ridge, and classifier RF could be best with an AUC of 0.99±0.005.

A Study on the Development of Technology Roadmap for Construction Automation (건설기계 자동화를 위한 기술 로드맵 개발에 관한 연구)

  • Kim, Young-Suk;Seo, Jong-Won;Lee, Junbok;Kim, Sung-Keun
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.4D
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    • pp.493-504
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    • 2008
  • Considerable effort has been made to improve construction processes through mechanization and robotization of current work. In this paper, the trend of research and development related to the construction machinery automation to improve the construction productivity has been reviewed. A classification system is proposed for automation of architectural and civil works. Then, the priority among the classified construction tasks for automation has been identified through the questionnaire study. Based on the priority for automation a comprehensive technology road map was also developed. The technology road map suggests the time frame to complete R&D work for the selected construction tasks and the core technology required for automation of the selected tasks. Such automation R&D road map for construction machinery can be utilized as a milestone in setting up the R&D strategy in the construction industry.

Application Traffic Classification using PSS Signature

  • Ham, Jae-Hyun;An, Hyun-Min;Kim, Myung-Sup
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.7
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    • pp.2261-2280
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    • 2014
  • Recently, network traffic has become more complex and diverse due to the emergence of new applications and services. Therefore, the importance of application-level traffic classification is increasing rapidly, and it has become a very popular research area. Although a lot of methods for traffic classification have been introduced in literature, they have some limitations to achieve an acceptable level of performance in real-time application-level traffic classification. In this paper, we propose a novel application-level traffic classification method using payload size sequence (PSS) signature. The proposed method generates unique PSS signatures for each application using packet order, direction and payload size of the first N packets in a flow, and uses them to classify application traffic. The evaluation shows that this method can classify application traffic easily and quickly with high accuracy rates, over 99.97%. Furthermore, the method can also classify application traffic that uses the same application protocol or is encrypted.

3D VISION SYSTEM FOR THE RECOGNITION OF FREE PARKING SITE LOCATION

  • Jung, H.G.;Kim, D.S.;Yoon, P.J.;Kim, J.H.
    • International Journal of Automotive Technology
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    • v.7 no.3
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    • pp.361-367
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    • 2006
  • This paper describes a novel stereo vision based localization of free parking site, which recognizes the target position of automatic parking system. Pixel structure classification and feature based stereo matching extract the 3D information of parking site in real time. The pixel structure represents intensity configuration around a pixel and the feature based stereo matching uses step-by-step investigation strategy to reduce computational load. This paper considers only parking site divided by marking, which is generally drawn according to relevant standards. Parking site marking is separated by plane surface constraint and is transformed into bird's eye view, on which template matching is performed to determine the location of parking site. Obstacle depth map, which is generated from the disparity of adjacent vehicles, can be used as the guideline of template matching by limiting search range and orientation. Proposed method using both the obstacle depth map and the bird's eye view of parking site marking increases operation speed and robustness to visual noise by effectively limiting search range.