• Title/Summary/Keyword: multi-source data

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Factors Influencing Multi-cultural Acceptance of Freshmen in Nursing Colleges (간호대학 신입생의 다문화수용성 영향요인)

  • Jung, Sun-Young
    • Journal of Convergence for Information Technology
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    • v.11 no.10
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    • pp.322-331
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    • 2021
  • This study attempted to identify the multi-cultural acceptance level of freshmen in nursing colleges and to analyze the factors influencing it. For the research method, data were collected from 410 first-year nursing students at K University in W City through a questionnaire from March 1 to 28, 2021, and frequency, reliability analysis, t-test, ANOVA, correlation, and multiple regression were conducted using the open-source statistical package R. As a result of the study, the multi-cultural acceptance level of freshman in nursing colleges averaged 77.36 points, indicating that they have a slightly higher multi-cultural acceptance capacity, and as a result of analyzing the influence of multi-cultural acceptance related factors, Korean recognition requirements(𝛽=0.34, p<.001), perceived threat recognition for migrants (𝛽=0.29, p<.001), Experience in multi-cultural education(𝛽=0.14, p<.001), Recognition of the appropriate age for multi-cultural education (𝛽=0.20, p<.001) was statistically significant. According to results, it is necessary to develop and actively utilize regular curriculum and programs related to multi-culturalism for nursing students.

A New Approach for Multi-Source Bio-data Integration and Analysis (멀티 소스 바이오 데이터 통합과 분석을 위한 새로운 접근 방법)

  • 윤혜성;이상호;김주한
    • Proceedings of the Korean Information Science Society Conference
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    • 2004.10b
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    • pp.268-270
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    • 2004
  • 네트워크가 보편화되면서 어떠한 정보의 교환도 시간과 장소에 상관없이 가능하게 되었다. 자체 실험실에서 실험한 값을 포함하여 분산된 다양한 소스로부터 많은 실험 값의 정보를 통합하는 즉, 멀티 소스 데이터에 대한 통합 규칙을 만들 수 있다면 다양하고 유용한 정보를 얻을 수 있을 것이다. 또한 통합된 규칙을 통해서 새로운 안목으로 실험을 진행할 수도 있으며, 미처 생각하지 못했던 관련 지식을 습득할 수도 있을 것이다. 본 논문에서는 이러한 분산된 데이터를 통합하여 멀티 소스 데이터들 간의 통합 규칙을 만들고 이의 분석 기반이 되도록 하는 방법에 대해 소개한다.

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Unsupervised segmentation of Multi -Source Remotely Sensed images using Binary Decision Trees and Canonical Transform

  • Mohammad, Rahmati;Kim, Jung-Ha
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.23.4-23
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    • 2001
  • This paper proposes a new approach to unsupervised classification of remotely sensed images. Fusion of optic images (Landsat TM) and radar data (SAR) has beer used to increase the accuracy of classification. Number of clusters is estimated using generalized Dunns measure. Performance of the proposed method is best observed comparing the classified images with classified aerial images.

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A Study on Implementation of Multi-Function Prototype IED H/W for Generator Protection (발전기 보호용 다기능 IED 시제품 H/W 구현에 관한 연구)

  • Kim, Yoon-Sang;An, Tae-Pung;Park, Chul-Won
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.27 no.12
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    • pp.74-80
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    • 2013
  • Generator faults does not happen more often than the transmission and substation facility faults. However, impacts on the power system by generator faults are very large. In order to minimize the impact of generator faults, generator protection and control system with high reliability is required. Most of the generator relay in generator protection and control system of large power plant of Korea is operated by imports from abroad. Accordingly, in order to accumulate source technology and increase the import substitution effect, localization of multi-function generator protection IED is being developed. This paper deals with the implementation of a multi-function prototype IED H/W, which can be command and data exchange through communication for measuring, monitoring, protection and control. And the IED specification, various relay elements, measurement elements, communication functions, module function, and test system for the prototype IED H/W are described.

Constructing κ-redundant Data Delivery Structure for Multicast in a Military Hybrid Network (군 하이브리드 네트워크에서 생존성 향상을 위한 다중 경로 멀티캐스팅)

  • Bang, June-Ho;Cho, Young-Jong;Kang, Kyungran
    • Journal of the Korea Institute of Military Science and Technology
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    • v.15 no.6
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    • pp.770-778
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    • 2012
  • In this paper, we propose a multi-path construction scheme to improve the survivability of a multicast session in military hybrid networks. A military hybrid network consists of a static backbone network and multiple mobile stub networks where some nodes are frequently susceptible to be disconnected due to link failure and node mobility. To improve the survivability of multicast sessions, we propose a construction scheme of ${\kappa}$ redundant multi-paths to each receiver. In order to take account of different characteristics of static and mobile networks, we propose quite different multi-path setup approaches for the backbone and stub networks, respectively, and combine them at the boundary point called gateway. We prove that our proposed scheme ensures that each receiver of a multicast session has ${\kappa}$ redundant paths to the common source. Through simulations, we evaluate the performance of the proposed schemes from three aspects : network survivability, recovery cost, and end-to-end delay.

Rapid 3D Mapping Using LIDAR System (LIDAR 시스템을 이용한 근 실시간 3D 매핑)

  • Sohn, Hong-Gyoo;Yun, Kong-Hyun;Kim, Kee-Tae;Kim, Gi-Hong
    • Journal of the Korean Society of Hazard Mitigation
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    • v.4 no.4 s.15
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    • pp.55-61
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    • 2004
  • Rapid developments in sensor technologies now allow the generation of multi-source topographical data. For many applications, however, the geospatial information provided by individual sensors is not complete, precise, and consistent. To solve these inherent problems, additional diverse sources of complementary data can be used and fused. In this paper, the experiment was done for generation of 3D orthoimage data using LIDAR data and digital camera image. And the results show that 3D orthoimage can be used for the flood monitoring.

Regional Scale Rice Yield Estimation by Using a Time-series of RADARSAT ScanSAR Images

  • Li, Yan;Liao, Qifang;Liao, Shengdong;Chi, Guobin;Peng, Shaolin
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.917-919
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    • 2003
  • This paper demonstrates that RADARSAT ScanSAR data can be an important data source of radar remote sensing for monitoring crop systems and estimation of rice yield for large areas in tropic and sub-tropical regions. Experiments were carried out to show the effectiveness of RADARSAT ScanSAR data for rice yield estimation in whole province of Guangdong, South China. A methodology was developed to deal with a series of issues in extracting rice information from the ScanSAR data, such as topographic influences, levels of agro-management, irregular distribution of paddy fields and different rice cropping systems. A model was provided for rice yield estimation based on the relationship between the backscatter coefficient of multi-temporal SAR data and the biomass of rice.

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Implementation of Git's Commit Message Classification Model Using GPT-Linked Source Change Data

  • Ji-Hoon Choi;Jae-Woong Kim;Seong-Hyun Park
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.10
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    • pp.123-132
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    • 2023
  • Git's commit messages manage the history of source changes during project progress or operation. By utilizing this historical data, project risks and project status can be identified, thereby reducing costs and improving time efficiency. A lot of research related to this is in progress, and among these research areas, there is research that classifies commit messages as a type of software maintenance. Among published studies, the maximum classification accuracy is reported to be 95%. In this paper, we began research with the purpose of utilizing solutions using the commit classification model, and conducted research to remove the limitation that the model with the highest accuracy among existing studies can only be applied to programs written in the JAVA language. To this end, we designed and implemented an additional step to standardize source change data into natural language using GPT. This text explains the process of extracting commit messages and source change data from Git, standardizing the source change data with GPT, and the learning process using the DistilBERT model. As a result of verification, an accuracy of 91% was measured. The proposed model was implemented and verified to ensure accuracy and to be able to classify without being dependent on a specific program. In the future, we plan to study a classification model using Bard and a management tool model helpful to the project using the proposed classification model.

MPMTP-AR: Multipath Message Transport Protocol Based on Application-Level Relay

  • Liu, Shaowei;Lei, Weimin;Zhang, Wei;Song, Xiaoshi
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.3
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    • pp.1406-1424
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    • 2017
  • Recent advancements in network infrastructures provide increased opportunities to support data delivery over multiple paths. Compared with multi-homing scenario, overlay network is regarded as an effective way to construct multiple paths between end devices without any change on the underlying network. Exploiting multipath characteristics has been explored for TCP with multi-homing device, but the corresponding exploration with overlay network has not been studied in detail yet. Motivated by improving quality of experience (QoE) for reliable data delivery, we propose a multipath message transport protocol based on application level relay (MPMTP-AR). MPMTP-AR proposes mechanisms and algorithms to support basic operations of multipath transmission. Dynamic feedback provides a foundation to distribute reasonable load to each path. Common source decrease (CSD) takes the load weight of the path with congestion into consideration to adjust congestion window. MPMTP-AR uses two-level sending buffer to ensure independence between paths and utilizes two-level receiving buffer to improve queuing performance. Finally, the MPMTP-AR is implemented on the Linux platform and evaluated by comprehensive experiments.

Exploring the temporal and spatial variability with DEEP-South observations: reduction pipeline and application of multi-aperture photometry

  • Shin, Min-Su;Chang, Seo-Won;Byun, Yong-Ik;Yi, Hahn;Kim, Myung-Jin;Moon, Hong-Kyu;Choi, Young-Jun;Cha, Sang-Mok;Lee, Yongseok
    • The Bulletin of The Korean Astronomical Society
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    • v.43 no.1
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    • pp.70.1-70.1
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    • 2018
  • The DEEP-South photometric census of small Solar System bodies is producing massive time-series data of variable, transient or moving objects as a by-product. To fully investigate unexplored variable phenomena, we present an application of multi-aperture photometry and FastBit indexing techniques to a portion of the DEEP-South year-one data. Our new pipeline is designed to do automated point source detection, robust high-precision photometry and calibration of non-crowded fields overlapped with area previously surveyed. We also adopt an efficient data indexing algorithm for faster access to the DEEP-South database. In this paper, we show some application examples of catalog-based variability searches to find new variable stars and to recover targeted asteroids. We discovered 21 new periodic variables including two eclipsing binary systems and one white dwarf/M dwarf pair candidate. We also successfully recovered astrometry and photometry of two near-earth asteroids, 2006 DZ169 and 1996 SK, along with the updated properties of their rotational signals (e.g., period and amplitude).

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