• Journal of the Korean earth science society
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• v.26 no.2
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• pp.129-136
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• 2005

Continued observation of ARGO floats for years(about 4 years) makes the conductivity sensor more vulnerable to fouling by marine life and associated drift in salinity measurements. In this paper, we address this issue by making use of floats deployed in different years. Floats deployed in the East Sea and the Indian Ocean are examined to find out float-to-float match-ups in such a way that an older float pops up simultaneously with a newer deployment (with tolerable space-time difference). A time difference of less than five days and space difference of less than 100km are considered for the match-up data sets. For analysis of the salinity drift under the stable water mass, observations of the floats from deepest water masses have been used. From the cross-check of ARGO floats in the East Sea and the Indian Ocean, it is found that there is a systematic drift in the older float compared to later deployments. All drift results, consistently show negative bias indicating the typical nature of drift from fouled sensors. However, the drift is much less than 0.01, the specified accuracy of ARGO program.

• Journal of Information Technology Services
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• v.19 no.3
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• pp.139-149
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• 2020

There are now many different commercial weather sensors suitable for smart farms, and various smart farm devices are being developed and distributed by companies participating in the government-led smart farm expansion project. However, most do not comply with standard specifications and are therefore limited to use in smart farms. This paper proposed the connecting structure of operating non-standard node devices in smart farms following standard specifications supporting smart greenhouse. This connecting structure was proposed as both a virtual node module method and a virtual node wrapper method. In addition, the SoftFarm2.0 system was experimentally operated to analyze the performance of the implementation of the two methods. SoftFarm2.0 system complies with the standard specifications and supports non-standard smart farm devices. According to the analysis results, both methods do not significantly affect performance in the operation of the smart farm. Therefore, it would be good to select and implement the method suitable for each non-standard smart farm device considering environmental constraints such as power, space, distance of communication between the gateway and the node of the smart farm, and software openness. This will greatly contribute to the spread of smart farms by maximizing deployment cost savings.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.1
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• pp.3-6
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• 2015

Recently, the collection of the sensor data and its analysis become important as the smart buildings equipped with the various sensors appear as a usual scene. The interconnection through the wire cable among the sensors is indispensible because of the information collections such as the temperature, the humidity, and the luminance in the rooms and the hallways for the effective management of the in-building energies. However, these interconnections through the cabling will be very costly, time-consuming, and a difficult task since they will cause some damages to the buildings. Therefore, the interconnections through the unwired connections are required in terms of the deployment effectiveness such as time and cost In this paper, the design and the operation appropriateness are confirmed through the simulation of the signal measurement system for in-building propagation characteristics based on signature sequence.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.2
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• pp.480-497
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• 2012

As a new business concept, machine-to-machine (M2M) communications are born from original telemetry technology with the intrinsic features of automatic data transmissions and measurement from remote sources typically by cable or radio. M2M includes a number of technologies that need to be combined in a compatible manner to enable its deployment over a broad market of consumer electronics. In order to provide better understanding for this emerging concept, the correlations among M2M, wireless sensor networks, cyber-physical systems (CPS), and internet of things are first analyzed in this paper. Then, the basic M2M architecture is introduced and the key elements of the architecture are presented. Furthermore, the progress of global M2M standardization is reviewed, and some representative applications (i.e., smart home, smart grid and health care) are given to show that the M2M technologies are gradually utilized to benefit people's life. Finally, a novel M2M system integrating intelligent road with unmanned vehicle is proposed in the form of CPS, and an example of cyber-transportation systems for improving road safety and efficiency are introduced.

• Smart Structures and Systems
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• v.5 no.4
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• pp.317-328
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• 2009

Current maintenance operations and integrity checks on a wide array of structures require personnel entry into normally-inaccessible or hazardous areas to perform necessary nondestructive inspections. To gain access for these inspections, structure must be disassembled and removed or personnel must be transported to remote locations. The use of in-situ sensors, coupled with remote interrogation, can be employed to overcome a myriad of inspection impediments stemming from accessibility limitations, complex geometries, the location and depth of hidden damage, and the isolated location of the structure. Furthermore, prevention of unexpected flaw growth and structural failure could be improved if on-board health monitoring systems were used to more regularly assess structural integrity. A research program has been completed to develop and validate Comparative Vacuum Monitoring (CVM) Sensors for surface crack detection. Statistical methods using one-sided tolerance intervals were employed to derive Probability of Detection (POD) levels for a wide array of application scenarios. Multi-year field tests were also conducted to study the deployment and long-term operation of CVM sensors on aircraft. This paper presents the quantitative crack detection capabilities of the CVM sensor, its performance in actual flight environments, and the prospects for structural health monitoring applications on aircraft and other civil structures.

• Smart Structures and Systems
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• v.12 no.2
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• pp.209-233
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• 2013

With an annual growth rate of about 30%, wind energy systems, such as wind turbines, represent one of the fastest growing renewable energy technologies. Continuous structural health monitoring of wind turbines can help improving structural reliability and facilitating optimal decisions with respect to maintenance and operation at minimum associated life-cycle costs. This paper presents an integrated monitoring system that is designed to support structural assessment and life-cycle management of wind turbines. The monitoring system systematically integrates a wide variety of hardware and software modules, including sensors and computer systems for automated data acquisition, data analysis and data archival, a multiagent-based system for self-diagnosis of sensor malfunctions, a model updating and damage detection framework for structural assessment, and a management module for monitoring the structural condition and the operational efficiency of the wind turbine. The monitoring system has been installed on a 500 kW wind turbine located in Germany. Since its initial deployment in 2009, the system automatically collects and processes structural, environmental, and operational wind turbine data. The results demonstrate the potential of the proposed approach not only to ensure continuous safety of the structures, but also to enable cost-efficient maintenance and operation of wind turbines.

• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.1-10
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• 2018

Wide-area monitoring of tree-related high impedance fault (THIF) efficiently contributes to increase reliability of large-scaled network, since the failure to early location of them may results in critical lines tripping and consequently large blackouts. In the first place, this wide-area monitoring of THIF requires managing the placement of sensors across large power grid network according to THIF detection objective. For this purpose, current paper presents a framework in which sensors are distributed according to a predetermined risk map. The proposed risk map determines the possibility of THIF occurrence on every branch in a power network, based on electrical conductivity of trees and their positions to power lines which extracted from spectral data. The obtained possibility value can be considered as a weight coefficient assigned to each branch in sensor placement problem. The next step after sensors deployment is to on-line monitor based on moving data window. In this on-line process, the received data window is evaluated for obtaining a correlation between low frequency and high frequency components of signal. If obtained correlation follows a specified pattern, received signal is considered as a THIF. Thereafter, if several faulted section candidates are found by deployed sensors, the most likely location is chosen from the list of candidates based on predetermined THIF risk map.

• Journal of Advanced Navigation Technology
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• v.24 no.4
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• pp.267-272
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• 2020

In order to monitor in large area of a ship without any concerns of spacial environments, there can be the use of many sensors that support wireless network technologies. Through the deployment of the wireless sensors and their autonomous network formations, the status of a ship can be easily monitored in real time. Moreover, if all the sensors are timely synchronized with each other, the locations and the moving directions of certain events can be estimated. Thus, the time synchronization amongst wireless sensors are crucial. In this paper, we propose an algorithm which supports reduced message transmissions between the sensors for synchronization.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1459-1478
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• 2020

In the last few years, quantum communication technology and services have been developing in various advanced applications to secure the sharing of information from one device to another. It is a classical commercial medium, where several Internet of Things (IoT) devices are connected to information communication technology (ICT) and can communicate the information through quantum systems. Digital communications for future networks face various challenges, including data traffic, low latency, deployment of high-broadband, security, and privacy. Quantum communication, quantum sensors, quantum computing are the solutions to address these issues, as mentioned above. The secure transaction of data is the foremost essential needs for smart advanced applications in the future. In this paper, we proposed a quantum communication model system for future ICT and methodological flow. We show how to use blockchain in quantum computing and quantum cryptography to provide security and privacy in recent information sharing. We also discuss the latest global research trends for quantum communication technology in several countries, including the United States, Canada, the United Kingdom, Korea, and others. Finally, we discuss some open research challenges for quantum communication technology in various areas, including quantum internet and quantum computing.

• 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.