• Journal of Environmental Impact Assessment
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• v.30 no.2
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• pp.75-88
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• 2021

Six locations in the automated monitoring network at the Geum River Basin were selected forthis study. The water quality characteristics at two of the locations in the water quality monitoring network that were identical, or nearby, were examined, and their correlations were evaluated through statistical analysis. The results of the water quality analysis were converted to the water quality index and expressed in grades for comparison. For the data necessary for the study, public data from four years, from 2016-2019 were used and the evaluation parameters were water temperature, pH, EC, DO, TOC, TN, and TP. Results of the analysis showed that the water quality concentrations measured in the automated monitoring network and the water quality monitoring network differed in some measured values, but they tended to register variation in a specified ratio in most of the locations in the network. The analysis of the correlations of the parameters between the two monitoring networks found that water temperature, EC, and DO showed high correlations between the two monitoring networks. The TOC, TN, and TP showed high correlations, with a 0.7 or higher (correlation coefficient r), with the exception of some of the monitoring networks, although their correlations were lower than those of the basic parameters. The water quality index analysis showed that the water quality index values of the automated monitoring network and the water quality monitoring network were similar. The water quality index decreased and the pollution degree increased in the downstream direction, in both networks.

• Journal of Korean Society for Atmospheric Environment
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• v.23 no.6
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• pp.689-698
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• 2007

Particular attention is paid to the validity of PM-10 measurement using beta attenuation method. In this study, the inter-comparison studies were undertaken for PM-10 sampler with different measuring methods. The three beta attenuation monitoring instruments (BAM1020, FH C-14, and DIGS-150) and filter based gravitational method using High Volume Air Sampler were collocated and mass concentrations were compared from August to November, 2006. The results of the investigation show that beta attenuation monitoring instruments are comparable with gravitational method within 10% of measurement error. For specific conditions under high humidity and high concentrations, the inter-comparison results also showed a relatively good agreement and this can be explained as the effect of inlet heating of beta attenuation instrument. Subsequently, this study shows that beta attenuation monitoring instruments can be equivalently used with reasonable validity when compared gravimetric method.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.1319-1327
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• 2015

As wind power farm (WPF) installations continue to grow, monitoring and controlling large-scale WPFs presents new challenges. In this paper, a hierarchical network architecture is proposed in order to provide remote monitoring and control of large-scale WPFs. The network architecture consists of three levels, including the WPF comprised of wind turbines and meteorological towers, local control center (LCC) responsible for remote monitoring and control of wind turbines, and a central control center (CCC) that offers data collection and aggregation of many WPFs. Different scenarios are considered in order to evaluate the performance of the WPF communications network with its hierarchical architecture. The communications network within the WPF is regarded as the local area network (LAN) while the communication among the LCCs and the CCC happens through a wide area network (WAN). We develop a communications network model based on an OPNET modeler, and the network performance is evaluated with respect to the link bandwidth and the end-to-end delay measured for various applications. As a result, this work contributes to the design of communications networks for large-scale WPFs.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.10a
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• pp.95-98
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• 2002

Monitoring of the cutting trouble is necessarily required to do Factory Automation and Intelligent manufacturing system. Therefore, we constructed a monitoring system using neural network in order to monitor of the cutting trouble. From obtained result, it is shown that the cutting trouble can be monitored effectively by neural network

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.311-315
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• 2000

In thls paper, a remote machine monitoring system for a vimal machine is proposed. The monltonng system is one of the core functmns of a vimd machne that provides a modeling and simulation environment for machining processes and management of the machine life cycle. The proposed system contains the modules for investigating tool wear using neural network and web-based real time process monitoring. An example implementation for tool wear and machining status monitoring is illustrated

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.738-742
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• 1996

This paper presents the automatic monitoring system for the small and medium sized manufacturing system. The monitoring system was composed of main controller, network card and monitoring sub controller for the unit machine. PC was used for the main controller and monitoring controller, which has the same hardware with the network card, was developed using Intel 80196 microprocessor.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.234-237
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• 2014

This paper provides insights into the sFlow monitoring system of OF@KREONET. OF@KREONET is software defined network (SDN) testbed adapted by KREONET (Korea Research Environment Open NETwork). OF@KREONET uses SDN-based network virtualization to slice the network among multiple concurrent experimenter. Flow Monitoring of OF@KREONET using sFlow. sFlow and OpenFlow can be used to provide an integrated flow monitoring system where OpenFlow controller can be used to define flows to be monitored by sFlow. OF@KREONET flow monitoring system supports monitoring of per slice FlowSpace. An Experimental can monitor his/her own FlowSpace while network administrator can monitor all spaces.

• Journal of Ocean Engineering and Technology
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• v.12 no.2 s.28
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• pp.139-146
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• 1998

This paper introduces a network system for monitoring coastal oceanographic data. The network system consists of three parts such as the buoy to observe oceanographic data, the local site to collect data transferred from buoys, and the host site to construct the oceanographic data-base and to share the information for monitoring coastal oceanographic data. The buoy has a one-board microcomputer to manage and to acquire coastal environment data in real-time. A wireless and wire communication technique is employed in order to transfer data measured by buoys and to link local and host sites, respectively. In measuring coastal environment data, this system shows more cost-effective way than the presents conventional. In addition, the realtime monitoring system continuously from various sites with the network systems.

• International Journal of Naval Architecture and Ocean Engineering
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• v.3 no.2
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• pp.136-140
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• 2011

Monitoring of water surfaces through permanent measurement of hydrodynamic and meteorological data is one of the main requirements in safe and sustainable water management. The Caspian Sea, the major surface water body in Iran, significantly affects more than 600 km of urban and industrial coastline. In the present work, an integrated marine monitoring network for the entire southern coastline of the Caspian Sea was developed. The main design concerns centered on the network measuring components and data recording, checking, filtering, gap recognition, and transferring systems. Four coastal monitoring stations were assigned, along with two regional collecting stations and one central data station for gathering, checking and delivering recorded data at different access levels. Applicable guidelines on selection of measuring devices for both shallow and deep water zones are presented herein.

• Communications for Statistical Applications and Methods
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• v.29 no.4
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• pp.487-498
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• 2022

Social network analysis (SNA) techniques have recently been developed to monitor and detect abnormal behaviors in social networks. As a useful tool for process monitoring, control charts are also useful for network monitoring. In this paper, the degree and closeness centrality measures, in which each has global and local perspectives, respectively, are applied to an exponentially weighted moving average (EWMA) chart and a multinomial cumulative sum (CUSUM) chart for monitoring undirected weighted networks. In general, EWMA charts monitor only one variable in a single chart, whereas multinomial CUSUM charts can monitor a categorical variable, in which several variables are transformed through classification rules, in a single chart. To monitor both degree centrality and closeness centrality simultaneously, we categorize them based on the average of each measure and then apply to the multinomial CUSUM chart. In this case, the global and local attributes of the network can be monitored simultaneously with a single chart. We also evaluate the performance of the proposed procedure through a simulation study.