• Title/Summary/Keyword: remote laboratory

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Development of Suspended Particulate Matter Algorithms for Ocean Color Remote Sensing

  • Ahn, Yu-Hwan;Moon, Jeong-Eun;Gallegos, Sonia
    • Korean Journal of Remote Sensing
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    • v.17 no.4
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    • pp.285-295
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    • 2001
  • We developed a CASE-II water model that will enable the simulation of remote sensing reflectance($R_{rs}$) at the coastal waters for the retrieval of suspended sediments (SS) concentrations from satellite imagery. The model has six components which are: water, chlorophyll, dissolved organic matter (DOM), non-chlorophyllous particles (NC), heterotrophic microorganisms and an unknown component, possibly represented by bubbles or other particulates unrelated to the five first components. We measured $R_{rs}$, concentration of SS and chlorophyll, and absorption of DOM during our field campaigns in Korea. In addition, we generated $R_{rs}$ from different concentrations of SS and chlorophyll, and various absorptions of DOM by random number functions to create a large database to test the model. We assimilated both the computer generated parameters as well as the in-situ measurements in order to reconstruct the reflectance spectra. We validated the model by comparing model-reconstructed spectra with observed spectra. The estimated $R_{rs}$ spectra were used to (1) evaluate the performance of four wavelengths and wavelengths ratios for accurate retrieval of SS. 2) identify the optimum band for SS retrieval, and 3) assess the influence of the SS on the chlorophyll algorithm. The results indicate that single bands at longer wavelengths in visible better results than commonly used channel ratios. The wavelength of 625nm is suggested as a new and optimal wavelength for SS retrieval. Because this wavelength is not available from SeaWiFS, 555nm is offered as an alternative. The presence of SS in coastal areas can lead to overestimation chlorophyll concentrations greater than 20-500%.

Monitoring the Ecological Drought Condition of Vegetation during Meteorological Drought Using Remote Sensing Data (원격탐사자료를 활용한 기상학적 가뭄 시 식생의 생태학적 가뭄 상태 모니터링)

  • Won, Jeongeun;Jung, Haeun;Kang, Shinuk;Kim, Sangdan
    • Korean Journal of Remote Sensing
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    • v.38 no.5_3
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    • pp.887-899
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    • 2022
  • Drought caused by meteorological factors negatively affects vegetation in terrestrial ecosystems. In this study, the state in which meteorological drought affects vegetation was defined as the ecological drought of vegetation, and the ecological drought condition index of vegetation (EDCI-veg) was proposed to quantitatively monitor the degree of impact. EDCI-veg is derived from a copula-based bi-variate joint probability model between vegetation and meteorological drought information, and can be expressed numerically how affected the current vegetation condition was by the drought when the drought occurred. Comparing past meteorological drought events with their corresponding vegetation condition, the proposed index was examined, and it was confirmed that EDCI-veg could properly monitor the ecological drought of vegetation. In addition, it was possible to spatially identify ecological drought conditions by creating a high-resolution drought map using remote sensing data.

Autonomous Ship's Remote Operation Situation Occurrence Probability Estimation Model based on Navigation Areas (운항 해역별 자율운항선박 원격운항 상황 발생 확률 추산 시뮬레이션 모델)

  • Taewoong Hwang;Taemin Hwang;Dain Lee;Hyeinn Park;Ik-Hyun Youn
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.29 no.7
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    • pp.910-914
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    • 2023
  • With the technological innovation owing to the 4th industrial revolution, the maritime transportation is rapidly being developed with autonomous ships and systems. Particularly, autonomous ships will partially replace the manned ships and navigation among them remotely upon the degree of autonomy suggested by IMO. Accordingly, the remote operator and related research have increased as well. However, the data on the minimum required manpower for remote operators are lacking such as considering engage required situations and their co-occurrence probability. Therefore, this study proposes a simulation model that calculates the number of remote engage required situations by defining restricted water area and remote engage required situation as close-quarter situations based on accumulated trajectory data of actual ships. The findings are expected to be used as background materials to establish the appropriate manpower distribution of remote operators in remote operation centers.

Development of High Current Shunt Regulator for Beam Based Alignment in PLS 2GeV Storage Ring (포항방사광가속기 빔위치 정렬 용 정밀전원장치 개발)

  • Nam, S.H.;Suh, J.H.;Ha, K.M.;Huang, J.Y.;Ko, I.S.
    • Proceedings of the KIEE Conference
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    • 1997.07f
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    • pp.2249-2251
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    • 1997
  • Total 144 quadrupole magnets are installed in PLS. The magnets are connected in series with groups of two or 24. Each group is powered by a high-precision constant-current DC power supply. For the purpose of the beam based alignment of beam position monitors in the PLS, it is necessary to adjust the current of each quadrupole independently. To achieve this, a high current shunt regulator is designed. It can shunt a maximum 50 A of the quadrupole magnet current. The shunt regulator is programmable and the current amplitude can be varied linearly with a 12-bit resolution. Power transistors are used in the current shunt regulator. The operation of transistors is in linear region. The RS232C protocol is used for remote control and status report of the shunt regulator to the main control centre of the PLS. Preliminary result indicates that the calibration accuracy of the beam position monitor can be achievable in less than $10{\mu}m$.

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PROJECTION OF TRAJECTORY FOR SUPPORTING UNCERTAINTY FUTURE TIME OF MOVING OBJECT

  • Won Ho-Gyeong;Jung Young Jin;Lee Yang Koo;Park Mi;Kim Hak-cheol;Ryu Keun Ho
    • Proceedings of the KSRS Conference
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    • 2005.10a
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    • pp.72-75
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    • 2005
  • Uncertainty of objects in Moving Object Database is a coherent property. It has been discussed in a lot of researches on modelling and query processing. The previous studies assume that uncertain future time is determined through utilizing recent speed and direction of vehicles. This method is simple and useful for estimating the time of the near future location. However, it is not appropriate when we estimate the time of the far future location. Therefore, in this paper, we propose a concept of planned route. It is used to estimate uncertain future time, which has to be located at a given point. If the route of an object is planned beforehand its locations are uncertainly distributed near that route. By a simple projection operation, the probability that a location lies in the planned route is increased. Moreover, we identify the future time of an object based on the speed for passing the route, which is offered via a website.

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TIME SERIES PREDICTION USING INCREMENTAL REGRESSION

  • Kim, Sung-Hyun;Lee, Yong-Mi;Jin, Long;Chai, Duck-Jin;Ryu, Keun-Ho
    • Proceedings of the KSRS Conference
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    • v.2
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    • pp.635-638
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    • 2006
  • Regression of conventional prediction techniques in data mining uses the model which is generated from the training step. This model is applied to new input data without any change. If this model is applied directly to time series, the rate of prediction accuracy will be decreased. This paper proposes an incremental regression for time series prediction like typhoon track prediction. This technique considers the characteristic of time series which may be changed over time. It is composed of two steps. The first step executes a fractional process for applying input data to the regression model. The second step updates the model by using its information as new data. Additionally, the model is maintained by only recent data in a queue. This approach has the following two advantages. It maintains the minimum information of the model by using a matrix, so space complexity is reduced. Moreover, it prevents the increment of error rate by updating the model over time. Accuracy rate of the proposed method is measured by RME(Relative Mean Error) and RMSE(Root Mean Square Error). The results of typhoon track prediction experiment are performed by the proposed technique IMLR(Incremental Multiple Linear Regression) is more efficient than those of MLR(Multiple Linear Regression) and SVR(Support Vector Regression).

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Design of Markov Decision Process Based Dialogue Manager (마르코프 의사결정 과정에 기반한 대화 관리자 설계)

  • Choi, Joon-Ki;Eun, Ji-Hyun;Chang, Du-Seong;Kim, Hyun-Jeong;Koo, Myong-Wan
    • Proceedings of the KSPS conference
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    • 2006.11a
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    • pp.14-18
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    • 2006
  • The role of dialogue manager is to select proper actions based on observed environment and inferred user intention. This paper presents stochastic model for dialogue manager based on Markov decision process. To build a mixed initiative dialogue manager, we used accumulated user utterance, previous act of dialogue manager, and domain dependent knowledge as the input to the MDP. We also used dialogue corpus to train the automatically optimized policy of MDP with reinforcement learning algorithm. The states which have unique and intuitive actions were removed from the design of MDP by using the domain knowledge. The design of dialogue manager included the usage of natural language understanding and response generator to build short message based remote control of home networked appliances.

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Genome Scale Protein Secondary Structure Prediction Using a Data Distribution on a Grid Computing

  • Cho, Min-Kyu;Lee, Soojin;Jung, Jin-Won;Kim, Jai-Hoon;Lee, Weontae
    • Proceedings of the Korean Biophysical Society Conference
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    • 2003.06a
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    • pp.65-65
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    • 2003
  • After many genome projects, algorithms and software to process explosively growing biological information have been developed. To process huge amount of biological information, high performance computing equipments are essential. If we use the remote resources such as computing power, storages etc., through a Grid to share the resources in the Internet environment, we will be able to obtain great efficiency to process data at a low cost. Here we present the performance improvement of the protein secondary structure prediction (PSIPred) by using the Grid platform, distributing protein sequence data on the Grid where each computer node analyzes its own part of protein sequence data to speed up the structure prediction. On the Grid, genome scale secondary structure prediction for Mycoplasma genitalium, Escherichia coli, Helicobacter pylori, Saccharomyces cerevisiae and Caenorhabditis slogans were performed and analyzed by a statistical way to show the protein structural deviation and comparison between the genomes. Experimental results show that the Grid is a viable platform to speed up the protein structure prediction and from the predicted structures.

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Laboratory Environment Monitoring: Implementation Experience and Field Study in a Tertiary General Hospital

  • Kang, Seungjin;Baek, Hyunyoung;Jun, Sunhee;Choi, Soonhee;Hwang, Hee;Yoo, Sooyoung
    • Healthcare Informatics Research
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    • v.24 no.4
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    • pp.371-375
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    • 2018
  • Objectives: To successfully introduce an Internet of Things (IoT) system in the hospital environment, this study aimed to identify issues that should be considered while implementing an IoT based on a user demand survey and practical experiences in implementing IoT environment monitoring systems. Methods: In a field test, two types of IoT monitoring systems (on-premises and cloud) were used in Department of Laboratory Medicine and tested for approximately 10 months from June 16, 2016 to April 30, 2017. Information was collected regarding the issues that arose during the implementation process. Results: A total of five issues were identified: sensing and measuring, transmission method, power supply, sensor module shape, and accessibility. Conclusions: It is expected that, with sufficient consideration of the various issues derived from this study, IoT monitoring systems can be applied to other areas, such as device interconnection, remote patient monitoring, and equipment/environmental monitoring.

Diagnosis and Control System of Wastewater Treatment Processes Using Intelligent Approaches (지능형 기법을 이용한 축산폐수처리장의 진단ㆍ제어 시스템)

  • Bae, Hyeon;Seo, Hyun-Yong;Jun, Byong-Hee;Kim, Sung-Shin;Kim, Ye-Jin
    • Proceedings of the IEEK Conference
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    • 2003.07d
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    • pp.1315-1318
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    • 2003
  • Wastewater treatment processes are usually located in the outskirts of cities. But these processes should be dealt with continuous maintenance by expert operators. Therefore, in this paper, unmaned and automated control system is designed for the SBR(Sequencing Batch Reactor) plant. This plant is constructed in Gimhae city. Networks and wireless modules are employed for the data transmission. A local controller is in the SBR plant as a client and a monitoring system is located in the other place as a server. Remote control and monitoring system are constructed at the laboratory of ours. Measured data from plant sensors are translated to the remote site using communication modules, and then the data could be displayed and analyzed by means of remote monitoring and control systems.

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