• Journal of Biomedical Engineering Research
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• v.18 no.4
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• pp.373-380
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• 1997

In this paper, we describe the intrabed network in a patient monitoring system we developed The intrabed network handles data communication between the main unit of a bedside patient monitor and parameter modules plugged in it. We designed the intrabed network based on RS-485 and HDLC protocol with 1 Mbps data rate. Message exchanges are implemented based on three data structures of packet frame. and stream. We present the specification and the performance of the data communication network for the developed patient monitor.

• Smart Structures and Systems
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• v.29 no.1
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• pp.53-62
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• 2022

The deployment of advanced structural health monitoring (SHM) systems in large-scale civil structures collects large amounts of data. Note that these data may contain multiple types of anomalies (e.g., missing, minor, outlier, etc.) caused by harsh environment, sensor faults, transfer omission and other factors. These anomalies seriously affect the evaluation of structural performance. Therefore, the effective analysis and mining of SHM data is an extremely important task. Inspired by the deep learning paradigm, this study develops a novel generative adversarial network (GAN) and convolutional neural network (CNN)-based data anomaly detection approach for SHM. The framework of the proposed approach includes three modules : (a) A three-channel input is established based on fast Fourier transform (FFT) and Gramian angular field (GAF) method; (b) A GANomaly is introduced and trained to extract features from normal samples alone for class-imbalanced problems; (c) Based on the output of GANomaly, a CNN is employed to distinguish the types of anomalies. In addition, a dataset-oriented method (i.e., multistage sampling) is adopted to obtain the optimal sampling ratios between all different samples. The proposed approach is tested with acceleration data from an SHM system of a long-span bridge. The results show that the proposed approach has a higher accuracy in detecting the multi-pattern anomalies of SHM data.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.6
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• pp.44-50
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• 1997

This paper describes the design and test of an on-line non-invasive network performance monitor (hardware portion) for the SPAX parallel computer. The SPAX parallel computer supports up to 256 intel P6 processors with 4 P6 processors constituting a processign node. The nodes are interconnected with a dual two-level crossbar network calle dXcent-net. Since the performance of the SPAX parallel computer is highly dependent on the proper and efficient operation of the network, an on-line non-invasive network performance monitor (with hardware components) has been developed to aid in the monitoring and tunign of the Xcent-net. Successful testing of a prototype node monitor board and PC interface system shows that our monitor design provides a low-cost practical solution to this problem.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.1012-1015
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• 2008

The packet capturing becomes a bottleneck in the network intrusion detection and monitoring system as the network performance developing. Many approaches, zero copy, interrupt coalescing and NAPI which attempt to improve packet capturing performance of Linux, are inefficient. PF_RING is a new type of network socket that dramatically improves the packet capture speed, but not perfect. This paper proposes some solutions which can improve the memory utilization and save some data copy time based on the commodity network adapters rather than on the commercial network adapters.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.6 s.171
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• pp.135-143
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• 2005

The shoes process management monitoring system for supporting SCM is developed in this study. This system consists of a monitoring program, a conveyer system, a pneumatic unit, a controller, an USB camera, and a server and a client computer. To operate the developed system easily, the monitoring program using LabVIEW in the Windows environment is developed. This program consists of 5 modules: production management, inventory control, media management, defective management, and communication management. The developed system has several advantages: reduced time for managing process work, decreased labor costs, effective operation, and continuous work without an operator. Nowadays advanced manufacturing companies are trying to find a way to check the performance of their production equipments and plants from remote sites. Thus, to manage the developed system from remote sites, communication network is constructed. In order to evaluate the performance of the monitoring system, experiments were performed. The experimental results showed that the developed system provided a reliable performance and a stable communication.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.1
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• pp.38-55
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• 2013

Wireless network systems provide fast data transmission rates and various services to users of mobile devices such as smartphones and smart pads. Because many people use high-performance mobile devices, the use of real-time multimedia services is increasing rapidly. However, the preoccupation of resources by real-time traffic users is causing harm to other services-for example, frequent call interference, lowered service quality, and poor network performance. This paper suggests a resource allocation algorithm for effective traffic service support in a hybrid network. The main objective is to obtain an optimum value of data rates by comparing user requirements with the amount of resources that can be allocated. A new mechanism based on Adaptive-Quality of Service (QoS) and a monitoring system based on Queue-Aware are proposed. Adaptive-QoS supports effective resource control according to the type of traffic service, and the monitoring system based on Queue-Aware measures the amount of resources in order to calculate the maximum that can be allocated. We apply our algorithm to a test system and use Qualnet 4.5.1 to evaluate its performance.

• Journal of KIISE
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• v.44 no.7
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• pp.733-741
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• 2017

LPWAN(Low Power Wide Area Network) technology is M2M (Machine to Machine) networking technology for the Internet of Things. The technology is designed to support low-power, long-distance and low-speed communications that are typical of LoRaWAN(Long Range Wide Area Network). To exchange inter-object information using a LoRaWAN, the link performances for various environments must be known. however, active performance analysis research that is based on an empirical environment is nonexistent. Therefore, this paper empirically evaluates the performance of the LoRa (Long Range) link, a physical communication technology of the LoRaWAN for various variables that may affect the link quality in indoor and outdoor environments. To achieve this, a physical performance monitoring system was designed and implemented. A communication experiment environment was subsequently constructed based on the indoor and outdoor conditions. The SNR(Signal to Noise Ratio), RSSI(Received Signal Strength Indication), and the PDR(Packet Delivery Ratio) were evaluated.

• Smart Structures and Systems
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• v.14 no.2
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• pp.145-158
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• 2014

The objective of this study is to improve the survivability and reliability of the FBG sensor network in the structural health monitoring (SHM) system. Therefore, a model reconstruction soft computing recognition algorithm based on support vector regression (SVR) is proposed to achieve the high reliability of the FBG sensor network, and the grid search algorithm is used to optimize the parameters of SVR model. Furthermore, in order to demonstrate the effectiveness of the proposed model reconstruction algorithm, a SHM system based on an eight-point fiber Bragg grating (FBG) sensor network is designed to monitor the foreign-object low velocity impact of a CFRP composite plate. Simultaneously, some sensors data are neglected to simulate different kinds of FBG sensor network failure modes, the predicting results are compared with non-reconstruction for the same failure mode. The comparative results indicate that the performance of the model reconstruction recognition algorithm based on SVR has more excellence than that of non-reconstruction, and the model reconstruction algorithm almost keeps the consistent predicting accuracy when no sensor, one sensor and two sensors are invalid in the FBG sensor network, thus the reliability is improved when there are FBG sensors are invalid in the structural health monitoring system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.1
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• pp.233-239
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• 2015

The demand of remote control and monitoring for efficiency and applications of LED streetlight is increasing continuously because the demand of LED streetlight was increase last few years. Existing street light remote control system is wired using a power line network. The wireless connection exists, but due to its low data transmission rate, it cannot support specialized applications. It can only support simple control and monitoring. In this paper, we propose a system that uses a IEEE 802.11s wireless mesh network based on WLAN, as a backbone network for remote control and monitoring of the LED street lights along with other specialized applications. Using the wireless mesh network for remote control and monitoring the LED street lights, the same can be used to act like a public Wi-Fi access point. We have designed Wi-Fi integrated LED streetlight controller and implemented our system. We evaluated the performance of our system on a real test bed. Our proposed system is expected to perform the role of a U-city infrastructure by utilizing the wireless mesh network.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.31 no.6
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• pp.359-366
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• 2018

Social infrastructure facilities that have been under construction since the country's high-growth period are undergoing rapid aging, and safety assessments of large structures such as bridge tunnels, which can be directly linked to large-scale casualties in the event of an accident, are necessary. Wireless smart sensor networks that improve SHM(Structural Health Monitoring) based on existing wire sensors are difficult to construct economical and efficient system due to short signal reach. The LPWAN, Low Power Wide Area Network, is becoming popular with the Internet of Things and it is possible to construct economical and efficient SHM by applying it to structural health monitoring. This study examines the applicability of LoRa LPWAN to structural health monitoring and proposes a channel usage pre-planning based LoRa network operation method that can efficiently utilize bandwidth while resolving conflicts between channels caused by using license - exempt communication band.