• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.219-230
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• 2023

Wireless Body Area Networks (WBANs) have made it easier for healthcare workers and patients to monitor patients' status continuously in real time. WBANs have complex and diverse network structures; thus, management and control can be challenging. Therefore, considering emerging Software-defined networks (SDN) with WBANs is a promising technology since SDN implements a new network management and design approach. The SDN concept is used in this study to create more adaptable and dynamic network architectures for WBANs. The study focuses on comparing the performance of two SDN controllers, POX and Ryu, using Mininet, an open-source simulation tool, to construct network topologies. The performance of the controllers is evaluated based on bandwidth, throughput, and round-trip time metrics for networks using an OpenFlow switch with sixteen nodes and a controller for each topology. The study finds that the choice of network controller can significantly impact network performance and suggests that monitoring network performance indicators is crucial for optimizing network performance. The project provides valuable insights into the performance of SDN-based WBANs using POX and Ryu controllers and highlights the importance of selecting the appropriate network controller for a given network architecture.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.11 no.4
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• pp.92-99
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• 1997

This paper proposed a control method to improve the efficiency of monitoring method by applying the nural network for an alarm processing method(APM)in an elevator facility of apartment complex. This APM is based on the cumulative generalized delta rule of backpropagation in neural network.It was used to infer the minimum alarms among multi-fired alarms, and then the inferred alarm can be dis¬played maintenance information of facility by using a pre-defined troubleshoot knowledge base. For validating the proposed monitoring method of this thesis, simulation results are compared with the operation of existing monitoring system and the way of alarm processing. The simulation method used to the three case of virtual scenario. As comparison results, a proposed method in this paper could be proved the applied possibility of an neural network and the performance in fields of facilities maintenance.

• Smart Structures and Systems
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• v.31 no.1
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• pp.45-56
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• 2023

Vibration-based structural health monitoring is used to ensure the safety of structures by installing sensors in structures. The peak picking method, one of the applications of vibration-based structural health monitoring, is a method that analyze the dynamic characteristics of a structure using the peaks of the frequency response function. However, the results may vary depending on the person predicting the peak point; further, the method does not predict the exact peak point in the presence of noise. To overcome the limitations of the existing peak picking methods, this study proposes a new method to automate the modal analysis process by utilizing long short-term memory, a type of recurrent neural network. The method proposed in this study uses the time series data of the frequency response function directly as the input of the LSTM network. In addition, the proposed method improved the accuracy by using the phase as well as amplitude information of the frequency response function. Simulation experiments and lab-scale model experiments are performed to verify the performance of the LSTM network developed in this study. The result reported a modal assurance criterion of 0.8107, and it is expected that the dynamic characteristics of a civil structure can be predicted with high accuracy using data without experts.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.10
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• pp.101-106
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• 2013

This paper proposes the new high precision monitoring sensor for the Marine Installation. Among variety of sensor network systems, wireless information transmission through the marine is one of the enabling technologies for the development of future marine-observation systems and sensor networks. Applications of marine monitoring range from oil industry to aquaculture, and include instrument monitoring, pollution control, climate recording, prediction of natural disturbances. For these marine applications to be available, however, the provision of precise location information using monitoring sensor is essential. In this paper, the dynamic characteristics for obtaining the location information of monitoring sensor is analyzed. The theoretical and experimental studies have been carried out. The presented results from the above investigation show considerably excellent performance for the Monitoring for the Marine Installation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.2
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• pp.191-198
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• 2014

As an NMEA 2000 is a standard for communicate to other electronic equipment, it implemented a Universal gateway based on this ship's network. To implement a NMEA 2000 based Universal gateway, it is porting a NMEA 2000 stack source and CAN device driver source to board, and then it connected a board that equip with various communication protocol(CAN, RS232, USB, Ethernet port). To verify converted ship's data to a developed gateway, it connected pc based simulater program and monitoring program to a developed board. so we can see a ship's data through NEMA 2000 network. We verified a gateway performance and analyzed a generated ship's data from simulator program through a monitoring program that was connected a gateway and NMEA 2000 network. so it was designed, implemented to allow monitoring through utilizing a communication method that user wants.

• Journal of The Korean Association of Information Education
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• v.5 no.3
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• pp.374-379
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• 2001

Recently, R & D about Network Monitoring System is needed to be effective network management and to improve computer education. In this work, we propose a real time network monitoring system named NetCop to improve network management and effective use. This system is designed to show any screen to one or more students in interactive learning environment. The system also provides useful functions such as monitoring students' PCs and chat. In additions, our NetCop can provide more effective learning process to students. Finally, we expect that our system can achieve high network performance and provide high educational quality to managers.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.39 no.2
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• pp.199-206
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• 2015

In this study, a new diagnosis method which can predict the working states of a pipe or its element in realtime is proposed by using an artificial neural network. The displacement data of an inspection element of a piping system are obtained by the use of PIV (particle image velocimetry), and are used for teaching a neural network. The measurement system consists of a camera, a light source and a host computer in which the artificial neural network is installed. In order to validate the constructed monitoring system, performance test was attempted for two kinds of mobile phone of which vibration modes are known. Three values of acceleration (minimum, maximum, mean) were tested for teaching the neural network. It was verified that mean values were appropriate to be used for monitoring data. The constructed diagnosis system could monitor the operation condition of a gas pipe.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.9
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• pp.1250-1256
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• 2018

Recently, wireless networks are becoming an important infrastructure for the critical large-scale applications such as cyber-physical systems and next generation industrial automations. However, the fundamental performance uncertainty of wireless networks may incur the serious instability problem of the overall systems. This paper proposes the proactive network optimizer to guarantee the application demands without any real-time link monitoring information of the networks. In particularly, the proposed proactive optimizer is the cross-layer approach to jointly optimize the routing path and traffic distribution in order to guarantee the performance demand within a maximum k number of link faults. Through the simulations, the proposed proactive network optimizer provides better robustness than the traditional existing reactive networks. Furthermore, the proactive network does not expose to the major weakness of the reactive networks such as the performance degradation due to the erroneous link monitoring information and the network reconfiguration cost.

• Convergence Security Journal
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• v.12 no.3
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• pp.75-83
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• 2012

Recent science technology research network moves to establish logical private network among specific research groups such as high energy physics and climate, requiring to implement private network by group for each purpose. Up to now, national research networks such as KREONET service high capacity logical private networks. Therefore standardized configuration and management scheme is essential for the deployment of logical private network. In this study, we propose the core service element and protocols for the logical networks over Layer 2 networks. We also propose system architecture that make monitoring and management easier. After that we design and implement monitoring map for logical network based on scheme. For this purpose, we also propose the description system for logical research network to provide data such as operation information, formation information, performance information and failure information of network infrastructure resource.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.6
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• pp.486-491
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• 2000

The dicing process cuts a semiconductor wafer to lengthwise and crosswise direction by using a rotating circular diamond blade. But inferior goods are made under the influence of several parameters in dicing such as blade, wafer, cutting water and cutting conditions. This paper describes a monitoring algorithm using neural network in order to find out an instant of vibration signal change when bad dicing appears. The algorithm is composed of two steps: feature extraction and decision. In the feature extraction, five features processed from vibration signal which is acquired by accelerometer attached on blade head are proposed. In the decision, back-propagation neural network is adopted to classify the dicing process into normal and abnormal dicing, and normal and damaged blade. Experiments have been performed for GaAs semiconductor wafer in the case of normal/abnormal dicing and normal/damaged blade. Based upon observation of the experimental results, the proposed scheme shown has a good accuracy of classification performance by which the inferior goods decreased from 35.2% to 6.5%.