• Journal of Korean Society of Rural Planning
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• v.30 no.1
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• pp.57-66
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• 2024

This study aimed to develop a precise vegetation cover classification model for small streams using the combination of drone remote sensing and support vector machine (SVM) techniques. The chosen study area was the Idong stream, nestled within Geosan-gun, Chunbuk, South Korea. The initial stage involved image acquisition through a fixed-wing drone named ebee. This drone carried two sensors: the S.O.D.A visible camera for capturing detailed visuals and the Sequoia+ multispectral sensor for gathering rich spectral data. The survey meticulously captured the stream's features on August 18, 2023. Leveraging the multispectral images, a range of vegetation indices were calculated. These included the widely used normalized difference vegetation index (NDVI), the soil-adjusted vegetation index (SAVI) that factors in soil background, and the normalized difference water index (NDWI) for identifying water bodies. The third stage saw the development of an SVM model based on the calculated vegetation indices. The RBF kernel was chosen as the SVM algorithm, and optimal values for the cost (C) and gamma hyperparameters were determined. The results are as follows: (a) High-Resolution Imaging: The drone-based image acquisition delivered results, providing high-resolution images (1 cm/pixel) of the Idong stream. These detailed visuals effectively captured the stream's morphology, including its width, variations in the streambed, and the intricate vegetation cover patterns adorning the stream banks and bed. (b) Vegetation Insights through Indices: The calculated vegetation indices revealed distinct spatial patterns in vegetation cover and moisture content. NDVI emerged as the strongest indicator of vegetation cover, while SAVI and NDWI provided insights into moisture variations. (c) Accurate Classification with SVM: The SVM model, fueled by the combination of NDVI, SAVI, and NDWI, achieved an outstanding accuracy of 0.903, which was calculated based on the confusion matrix. This performance translated to precise classification of vegetation, soil, and water within the stream area. The study's findings demonstrate the effectiveness of drone remote sensing and SVM techniques in developing accurate vegetation cover classification models for small streams. These models hold immense potential for various applications, including stream monitoring, informed management practices, and effective stream restoration efforts. By incorporating images and additional details about the specific drone and sensors technology, we can gain a deeper understanding of small streams and develop effective strategies for stream protection and management.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.3
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• pp.163-171
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• 2024

Structural health monitoring for ships and offshore structures is important in various aspects. Ships and offshore structures are continuously exposed to various environmental conditions, such as waves, wind, and currents. In the event of an accident, immense economic losses, environmental pollution, and safety problems can occur, so it is necessary to detect structural damage or defects early. In this study, structural response data of multi-linked floating offshore structures under various wave load conditions was calculated by performing fluid-structure coupled analysis. Furthermore, the order reduction method with distortion base mode was applied to the structures for predicting the structural response by using the results of numerical analysis. The distortion base mode order reduction method can predict the structural response of a desired area with high accuracy, but prediction performance is affected by sensor arrangement. Optimization based on a genetic algorithm was performed to search for optimal sensor arrangement and improve the prediction performance of the distortion base mode-based reduced-order model. Consequently, a sensor arrangement that predicted the structural response with an error of about 84.0% less than the initial sensor arrangement was derived based on the root mean squared error, which is a prediction performance evaluation index. The computational cost was reduced by about 8 times compared to evaluating the prediction performance of reduced-order models for a total of 43,758 sensor arrangement combinations. and the expected performance was overturned to approximately 84.0% based on sensor placement, including the largest square root error.

• Journal of the Earthquake Engineering Society of Korea
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• v.10 no.6 s.52
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• pp.1-8
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• 2006

This paper describes the procedures developing the algorithm for analyzing signals acquired from the Bridge Weigh-in-Motion (BWIM) system installed in Seohae Bridge as a part of the bridge monitoring system. Through the analysis procedure, information about heavy traffics such as weight, speed, and number of axles are attempted to be extracted from time domain strain data of the BWIM system. One of numerous pattern recognition techniques, artificial neural network (ANN) is employed since it can effectively include dynamic effects, bridge-vehicle interaction, etc. A number of vehicle running experiments with sufficient load cases are executed to acquire training and/or test set of ANN. Extracted traffic information can be utilized for developing quantitative database of loading effect. Also, it can contribute to estimate fatigue lift or current health condition, and design truck can be revised based on the database reflecting recent trend of traffic.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.8
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• pp.13-18
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• 2016

In Internet of Things (IoT) environment, a variety of smart devices are connected to Internet through various network technologies such as 4G/5G, WiBro, Bluetooth, etc. in order to provide the remote monitoring service such as smart healthcare service, etc. Most standard mobility management protocols based on IETF Mobile IP may not be suitable for Internet of Things (IoT) environments due to constrained power, constrained CPU processing and memory capacity, and large signalling overhead which are inherently accompanied by various devices in IoT environments. In this article, we propose a new mobility management protocol CoMP (CoAP-based Mobility Managemenbt Protocol) for reliable mobility management in IoT environments. The architecture and algorithm to achieve both reliability and simplicity for IoT mobility management are proposed. Finally, performance has been evaluated by both mathematical analysis and simulation.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.11
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• pp.63-70
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• 2008

In this paper, a smart sensor system for the MEMS pressure sensor was developed. A compensation algorithm and programmable calibration circuits were presented to eliminate errors caused by temperature drift of piezoresistive pressure sensors in itself. This system consisted of signal conditioning, calibration, temperature detection, microprocessor, and communication parts and these were integrated into a SOC. A RS-232 interface was employed for monitoring and control of a smart sensor system. The area of fabricated IC is $4.38{\times}3.78\;mm^2$ and a $0.35{\mu}m$ high voltage CMOS process was used. Compensation error for temperature drift of 50 KPa pressure sensors was measured into ${\pm}0.48%$ in the range of $-40^{\circ}C{\sim}150^{\circ}C$. Total power consumption was 30.5 mW.

• Journal of the Korea Society of Computer and Information
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• v.25 no.3
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• pp.89-96
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• 2020

Solar lamp systems may not operate normally in the event of some system or controller failure due to internal or external factors, in which case secondary problems occur, which may cost the system recovery. Thus, when these errors occur, a technology is needed to recover to the state it was in before the failure occurred and to enable re-execution. This paper designs and implements a system that can recover the state of the system to the state prior to the time of the error by using the Watchdog Timer within the controller if a software error has occurred inside the system, and it also proposes a technology to reset and re-execution the system through a separate reset circuit in the event of hardware failure. The proposed system provides stable operation, maintenance cost reduction and reliability of the solar lamp system by enabling the system to operate semi-permanently without external support by utilizing the automatic recovery and automatic reset function for errors that occur in the operation of the solar lamp system. In addition, it can be applied to maintain the system's constancy by utilizing the self-operation, diagnosis and recovery functions required in various high reliability applications.

• Smart Structures and Systems
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• v.20 no.3
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• pp.385-396
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• 2017

The recent advancements in sensing technologies allow us to record measurements from target structures at multiple locations and with relatively high spatial resolution. Such measurements can be used to develop data-driven methodologies for condition assessment, control, and health monitoring of target structures. One of the state-of-the-art technologies, Fiber Optic Strain Sensors (FOSS), is developed at NASA Armstrong Flight Research Center, and is based on Fiber Bragg Grating (FBG) sensors. These strain sensors are accurate, lightweight, and can provide almost continuous strain-field measurements along the length of the fiber. The strain measurements can then be used for real-time shape-sensing and operational load-estimation of complex structural systems. While several works have demonstrated the successful implementation of FOSS on large-scale real-life aerospace structures (i.e., airplane wings), there is paucity of studies in the literature that have investigated the potential of extending the application of FOSS into civil structures (e.g., tall buildings, bridges, etc.). This work assesses the feasibility of using FOSS to predict operational loads (e.g., wind loads) on chain-like structures. A thorough investigation is performed using analytical, computational, and experimental models of a 4-story steel building test specimen, developed at the University of Southern California. This study provides guidelines on the implementation of the FOSS technology on building-like structures, addresses the associated technical challenges, and suggests potential modifications to a load-estimation algorithm, to achieve a robust methodology for predicting operational loads using strain-field measurements.

• Smart Structures and Systems
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• v.20 no.4
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• pp.427-440
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• 2017

One of the suitable structural damage detection methods using vibrational characteristics are damage-index-based methods. In this study, a damage index for identifying damages in plate structures using frequency response function (FRF) data has been provided. One of the significant challenges of identifying the damages in plate structures is high number of degrees of freedom resulting in decreased damage identifying accuracy. On the other hand, FRF data are of high volume and this dramatically decreases the computing speed and increases the memory necessary to store the data, which makes the use of this method difficult. In this study, FRF data are compressed using two-dimensional principal component analysis (2D-PCA), and then converted into damage index vectors. The damage indices, each of which represents a specific condition of intact or damaged structures are stored in a database. After computing damage index of structure with unknown damage and using algorithm of lookup tables, the structural damage including the severity and location of the damage will be identified. In this study, damage detection accuracy using the proposed damage index in square-shaped structural plates with dimensions of 3, 7 and 10 meters and with boundary conditions of four simply supported edges (4S), three clamped edges (3C), and four clamped edges (4C) under various single and multiple-element damage scenarios have been studied. Furthermore, in order to model uncertainties of measurement, insensitivity of this method to noises in the data measured by applying values of 5, 10, 15 and 20 percent of normal Gaussian noise to FRF values is discussed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.7
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• pp.1283-1289
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• 2016

Electrical energy is the essential resource for modern society. Recently, the demand for power was significantly increased. Increase of power demand has lead to a decrease in the power quality. Power quality in modern society has been an important factor that can cause a major problem throughout the home and general industry. Therefore, we need a system for preventing the power quality problems. To avoid power issues, it is important that the measurement of the power quality and initial response. In this paper, we propose real-time power quality measurement system and harmonics monitoring system. We design the system using DM240001 board include dsPIC33FJ256GP710A of microchip. This system can adapt three-phase three-wire system. And optimized the algorithm, we can measure momentary changes of the power system. In addition, designed system can measure harmonics distortion like to VTHD, ITHD and ITDD for 31th harmonics.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.7
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• pp.1335-1341
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• 2016

For the safety of train operation, monitoring & supervisory systems for train, signal, power, communication and facilities is operating independently in another place, so, its sensors are interdependently connected from each other to transfer gathering datas of sensing to control center. A Goal of Real-time railway safety supervision system is to improve the safety oversight efficiency and to prevent accidents by means of hazard prediction based on big data by integrating all of safety sensing data in wayside of railway, and the System is requested acquisition of all of sensing data of safety. So, we need special method of protocol converting for the purpose of integrating all of detecting data concerning safety without any changing application. In this paper we investigate the existing converting method in communication field, and propose a new progress to converting protocol adding function of transfer using XML file, and implemented this algorithm, and tested with example packets, finally.