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Development of optical dual-sensors for submersion monitoring using zigbee-based wireless sensor networks (지그비 기반 센서 네트워크를 이용한 침수감지용 광 이중센서 개발)

  • Key, Kwang-Hyun;Kim, Hyung-Pyo;Sohn, Kyung-Rak
    • Journal of Sensor Science and Technology
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    • v.19 no.3
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    • pp.184-190
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    • 2010
  • In this paper, a remote submersion warning system based on multi-mode optical fiber(MMF) sensors and a wireless sensor network(WSN) are proposed. To improve the reliability and stability of the sensors, the dual optical fiber sensors combined to the optical coupler are demonstrated. A slave zigbee as a wireless sensor module was used as a platform to monitor and record the signal from the MMF sensors and then transmits these information to a master zigbee wirelessly. The monitoring system running the $LabVIEW^{(R)}$ software was connected to the internet to support the short message service(SMS) through extensible markup language(XML) web service. No matter where the managers are, they can always receive the real-time remote-monitoring data for safety check.

Fault Detection of Synchronous Generator using Wavelet Transform (웨이브릿 변환에 의한 동기발전기의 고장검출)

  • Park, Chul-Won;Shin, Myong-Chul
    • Proceedings of the KIEE Conference
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    • 2007.07a
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    • pp.640-641
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    • 2007
  • In this paper, the discrete wavelet transform (DWT) was applied a fault detection of a synchronous generator being superior to a transient state signal analysis and being easy to real time realization. The fault signals after executing a terminal fault modeling collect using a MATLAB package, and calculate the wavelet coefficients through the process of a multi-level decomposition (MLD). The proposed algorithm of a fault detection of a generator using Daubechies WT (wavelet transform) was executed with a C language for the commend line function and for the real time realization after analyzing MATLAB's graphical interface.

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The Development of the Drawing Information Management Module for the Technical Document Management System (Technical Document Management System을 위한 도면정보 관리시스템 개발)

  • Yoon, Hee-Chul;Kim, Sun-Ho
    • IE interfaces
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    • v.7 no.3
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    • pp.213-225
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    • 1994
  • For the implementation of CE(Concurrent Engineering), the TDMS(Technical Document Management System) which integrates design and manufacuring information, is required. In this paper a drawing information management system, one of the essential modules for the TDMS has been developed. The system is operated in SUN SPARC II workstations. A CAD software called CIMCAD-2D is used for the storage and management of drawings. Relational DBMS ORACLE is used for the development of information data bases concerned with drawings. As an integration tool, the multi-media software called LINKAGE is used. Various functions for drawings and concerned information have been developed with the internal language CIMSHELL and SQL $^*PLUS$.

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Integrating IndoorGML and Indoor POI Data for Navigation Applications in Indoor Space

  • Claridades, Alexis Richard;Park, Inhye;Lee, Jiyeong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.37 no.5
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    • pp.359-366
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    • 2019
  • Indoor spatial data has great importance as the demand for representing the complex urban environment in the context of providing LBS (Location-based Services) is increasing. IndoorGML (Indoor Geographic Markup Language) has been established as the data standard for spatial data in providing indoor navigation, but its definitions and relationships must be expanded to increase its applications and to successfully delivering information to users. In this study, we propose an approach to integrate IndoorGML with Indoor POI (Points of Interest) data by extending the IndoorGML notion of space and topological relationships. We consider two cases of representing Indoor POI, by 3D geometry and by point primitive representation. Using the concepts of the NRS (node-relation structure) and multi-layered space representation of IndoorGML, we define layers to separate features that represent the spaces and the Indoor POI into separate, but related layers. The proposed methodology was implemented with real datasets to evaluate its effectiveness for performing indoor spatial analysis.

A Study on Cognition about Personal Broadcasting

  • Lee, Yong-Whan
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.9
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    • pp.27-34
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    • 2018
  • Personal media centered on blogs, Twitter, and Facebook has opened up a personal broadcasting area while meeting platforms such as YouTube and Africa TV. Due to the many advantages and disadvantages of personal broadcasting, a study on it was necessary and statistical survey was conducted. The study conducted opinion survey of 118 university students on personal broadcasting. As a result, we are getting news using smartphones and mainly watching videos through YouTube, and watching videos type in the order of games, music videos and sports. Satisfaction rate of video was 72.4%, 80.2% of survey did not use paid services, experiences about personal broadcasting was 96.6% and 90.5% of survey the prospect of person broadcasting of the opinion that "it will be expanded". The first thing we want to be improved in personal broadcasting is the prevention of abusive language and hate speech. Second, we were reluctant to sensational content. Third, the survey results are the improvement of excessive advertising.

Architecture_Speaking in Colors

  • Kim, Tae-Eun
    • International journal of advanced smart convergence
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    • v.8 no.3
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    • pp.167-176
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    • 2019
  • Building skins are expanding even beyond theirfunctions as a simple boundary between the exterior and interior and into the realm of linguistic functions thanks to the development of media art. LED has been used as material on outer walls following the advancement of building materials, so the outerskins of large buildings are evolving into a messenger of language capable of communication. In big cities, buildings send out video images to enable communication between people and architecture, which plays a huge role in determining the identity of a building beyond simple advertising. Such media fa?ade technologies can be understood based on the concept of outerskin change, which refers to the idea that animals change the colors or textures of their skins to show their various states. In addition, various message delivery functions in human clothes should be included in such a discussion. We need to research on the possibilities of seeing media facades for their information delivery function and expanding them into information delivery between buildings as well as just between buildings and people.

EFMDR-Fast: An Application of Empirical Fuzzy Multifactor Dimensionality Reduction for Fast Execution

  • Leem, Sangseob;Park, Taesung
    • Genomics & Informatics
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    • v.16 no.4
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    • pp.37.1-37.3
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    • 2018
  • Gene-gene interaction is a key factor for explaining missing heritability. Many methods have been proposed to identify gene-gene interactions. Multifactor dimensionality reduction (MDR) is a well-known method for the detection of gene-gene interactions by reduction from genotypes of single-nucleotide polymorphism combinations to a binary variable with a value of high risk or low risk. This method has been widely expanded to own a specific objective. Among those expansions, fuzzy-MDR uses the fuzzy set theory for the membership of high risk or low risk and increases the detection rates of gene-gene interactions. Fuzzy-MDR is expanded by a maximum likelihood estimator as a new membership function in empirical fuzzy MDR (EFMDR). However, EFMDR is relatively slow, because it is implemented by R script language. Therefore, in this study, we implemented EFMDR using RCPP ($c^{{+}{+}}$ package) for faster executions. Our implementation for faster EFMDR, called EMMDR-Fast, is about 800 times faster than EFMDR written by R script only.

Learning Algorithms in AI System and Services

  • Jeong, Young-Sik;Park, Jong Hyuk
    • Journal of Information Processing Systems
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    • v.15 no.5
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    • pp.1029-1035
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    • 2019
  • In recent years, artificial intelligence (AI) services have become one of the most essential parts to extend human capabilities in various fields such as face recognition for security, weather prediction, and so on. Various learning algorithms for existing AI services are utilized, such as classification, regression, and deep learning, to increase accuracy and efficiency for humans. Nonetheless, these services face many challenges such as fake news spread on social media, stock selection, and volatility delay in stock prediction systems and inaccurate movie-based recommendation systems. In this paper, various algorithms are presented to mitigate these issues in different systems and services. Convolutional neural network algorithms are used for detecting fake news in Korean language with a Word-Embedded model. It is based on k-clique and data mining and increased accuracy in personalized recommendation-based services stock selection and volatility delay in stock prediction. Other algorithms like multi-level fusion processing address problems of lack of real-time database.

Design of control software for GMACS (Giant Magellan Telescope Multi-Object Astronomical and Cosmological Spectrograph)

  • Lee, Hye-In;Ji, Tae-Geun;Pak, Soojong;Cook, Erika;Froning, Cynthia;Schmidt, Luke M.;Marshall, Jennifer L.;DePoy, Darren L.
    • The Bulletin of The Korean Astronomical Society
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    • v.44 no.2
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    • pp.79.3-79.3
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    • 2019
  • GMACS is one of the first light instruments for the Giant Magellan Telescope (GMT). The development of GMACS control software follows Agile software development process, and the design of the software is based on the Unified Model Language (UML). In this poster, we present the architecture of the GMACS software and the development processes. As an example of the software development, we show the software of the Slit Mask Exchange Mechanism Prototype (SMEM-P) which is part of the GMACS Device Control Package (DCP).

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SG-MLP: Switch Gated Multi-Layer Perceptron Model for Natural Language Understanding (자연어 처리를 위한 조건부 게이트 다층 퍼셉트론 모델 개발 및 구현)

  • Son, Guijin;Kim, Seungone;Joo, Se June;Cho, Woojin;Nah, JeongEun
    • Proceedings of the Korea Information Processing Society Conference
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    • 2021.11a
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    • pp.1116-1119
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    • 2021
  • 2018 년 Google 사의 사전 학습된 언어 인공지능 BERT 를 기점으로, 자연어 처리 학계는 주요 구조를 유지한 채 경쟁적으로 모델을 대형화하는 방향으로 발전했다. 그 결과, 오늘날 자연어 인공지능은 거대 사기업과 그에 준하는 컴퓨팅 자원을 소유한 연구 단체만의 전유물이 되었다. 본 논문에서는 다층 퍼셉트론을 병렬적으로 배열해 자연어 인공지능을 제작하는 기법의 모델을 제안하고, 이를 적용한'조건부 게이트 다층 퍼셉트론 모델(SG-MLP)'을 구현하고 그 결과를 비교 관찰하였다. SG-MLP 는 BERT 의 20%에 해당하는 사전 학습량만으로 다수의 지표에서 그것과 준하는 성능을 보였고, 동일한 과제에 대해 더 적은 연산 비용을 소요한다.