• Title/Summary/Keyword: colocation

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Time Delay Control of Noncolocated Flexible System in z-Domain (비병치 유연계의 시간지연 이산제어)

  • 강민식
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.16 no.6
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    • pp.1089-1098
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    • 1992
  • This paper concerns a discrete time control of noncolocated flexible mechanical systems by using time delay relation. A stability criterion of closed-loop system is derived in discrete time domain and a graphic method is developed for designing controllers. Based on this method, a derivative controller is designed for a simply supported uniform beam in the cases of colocation without time delay and of noncolocation with time delay. Some simulation results show the effectiveness of the suggested control.

Lessons from constructing and operating the national ecological observatory network

  • Christopher McKay
    • Journal of Ecology and Environment
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    • v.47 no.4
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    • pp.187-192
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    • 2023
  • The United States (US) National Science Foundation's (NSF's) National Ecological Observatory Network (NEON) is a continental-scale observation facility, constructed and operated by Battelle, that collects long-term ecological data to better understand and forecast how US ecosystems are changing. All data and samples are collected using standardized methods at 81 field sites across the US and are freely and openly available through the NEON data portal, application programming interface (API), and the NEON Biorepository. NSF led a decade-long design process with the research community, including numerous workshops to inform the key features of NEON, culminating in a formal final design review with an expert panel in 2009. The NEON construction phase began in 2012 and was completed in May 2019, when the observatory began the full operations phase. Full operations are defined as all 81 NEON sites completely built and fully operational, with data being collected using instrumented and observational methods. The intent of the NSF is for NEON operations to continue over a 30-year period. Each challenge encountered, problem solved, and risk realized on NEON offers up lessons learned for constructing and operating distributed ecological data collection infrastructure and data networks. NEON's construction phase included offices, labs, towers, aquatic instrumentation, terrestrial sampling plots, permits, development and testing of the instrumentation and associated cyberinfrastructure, and the development of community-supported collection plans. Although colocation of some sites with existing research sites and use of mostly "off the shelf" instrumentation was part of the design, successful completion of the construction phase required the development of new technologies and software for collecting and processing the hundreds of samples and 5.6 billion data records a day produced across NEON. Continued operation of NEON involves reexamining the decisions made in the past and using the input of the scientific community to evolve, upgrade, and improve data collection and resiliency at the field sites. Successes to date include improvements in flexibility and resilience for aquatic infrastructure designs, improved engagement with the scientific community that uses NEON data, and enhanced methods to deal with obsolescence of the instrumentation and infrastructure across the observatory.

A Study on the Natural Mapping between Burner and Switch of Gas Range by Color coding (가스레인지에 있어서 칼라코딩을 통한 버너와 스위치의 자연적 대응에 관한 연구)

  • 오해춘;홍지영
    • Archives of design research
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    • v.16 no.2
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    • pp.415-424
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    • 2003
  • People store information not only in their Drain but also material things. Norman called it knowledge in the world. The general way to store the information is to paste labels. 4 burner gas range force user to make conceptual model between burner and switch to see labels. but those are cognitive stress. Norman suggested spatial analogies for natural mapping between display and control. However the way of his methods in spatial analogies was not compatible with kitchen atmosphere. To solve those problems 1 suggested color coding . This study hypothesized that the mapping between burner and switch is realized by color coding. To testy the hypothesis 1 compared A group using general gas range with B group using color coded gas range. The result showed difference between A and B in accuracy ( F (1, 38) = 17.892, p < 0.01) and response time ( F (1, 38) = 6.726 p < 0.05). The result of this test is to certify that color coding affect peoples by presenting the difference accuracy and response time. As result this study presents that color coding can be compatible the product having importance to certify in the design process.

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An Estimation of the Composite Sea Surface Temperature using COMS and Polar Orbit Satellites Data in Northwest Pacific Ocean (천리안 위성과 극궤도 위성 자료를 이용한 북서태평양 해역의 합성 해수면온도 산출)

  • Kim, Tae-Myung;Chung, Sung-Rae;Chung, Chu-Yong;Baek, Seonkyun
    • Korean Journal of Remote Sensing
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    • v.33 no.3
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    • pp.275-285
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    • 2017
  • National Meteorological Satellite Center(NMSC) has produced Sea Surface Temperature (SST) using Communication, Ocean, and Meteorological Satellite(COMS) data since April 2011. In this study, we have developed a new regional COMS SST algorithm optimized within the North-West Pacific Ocean area based on the Multi-Channel SST(MCSST) method and made a composite SST using polar orbit satellites as well as the COMS data. In order to retrieve the optimized SST at Northwest Pacific, we carried out a colocation process of COMS and in-situ buoy data to make coefficients of the MCSST algorithm through the new cloud masking including contaminant pixels and quality control processes of buoy data. And then, we have estimated the composite SST through the optimal interpolation method developed by National Institute of Meteorological Science(NIMS). We used four satellites SST data including COMS, NOAA-18/19(National Oceanic and Atmospheric Administration-18/19), and GCOM-W1(Global Change Observation Mission-Water 1). As a result, the root mean square error ofthe composite SST for the period of July 2012 to June 2013 was $0.95^{\circ}C$ in comparison with in-situ buoy data.