• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.569-570
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• 2018

Recently, Although particulate matter monitoring has been attracting attention as a result of social attention to the human impact of particulate matter, data suitable for the residential environment can not be obtained due to imbalances in the installation of monitoring stations and differences in topography. In this paper, we propose LoRa LPWA-based particulate matter measurement system which can make long distance wireless communication to measure particulate matter in residential environment. In the proposed system, it is possible to collect the data of the external environment which is difficult to construct the internet by utilizing LPWA which is a long distance wireless communication technology. When the proposed system is applied to the residential environment, it is expected to provide particulate matter monitoring information suitable for the residential environment.

• Journal of the Korean Home Economics Association
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• v.41 no.7
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• pp.121-143
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• 2003

The purpose of this study was to show general trends in the psychological environment of family and problem behaviors perceived by adolescents and examine possible changes in such trends in accordance with the individual variables of adolescent, and then find out the effect of these variables on adolescents' problem behavior. The subject were 1374 adolescents of middle school in Busan(male 698, female 676). The main results were as follows : (1) General trends in the degree of parental monitoring showed that girls had more high than boys, and in the degree of family discord, boys showed more high than girls. In the degree of openness of parent-adolescent communication perceived by adolescents showed that girls had more open communication with mother than boys. Such trends in problem behaviors indicated that adolescents had the attention problem most. According to gender, girls had more problems in withdrawal, somatic complain, anxiety/depression, thought problems, attention problems, destructivity/identity, internalizing problems, total behavior problems in comparison to boys. Boys did delinquent behaviors more than girls. (2) For boys, the monthly income of their family, family discord, and the mother-adolescent communication have a significant direct effect on internalizing problems, externalizing problems and total behavior problems. Besides mother's employment and the type of family have a significant indirect effect on behavior problem. For girls, mother's employment, parental monitoring, family discord, and father-adolescent communication have a significant direct effect on internalizing problems. Mother's employment, family discord, mother-adolescent communication have a significant indirect effect on externalizing problems and total behavior problems. Bisides mother's employment, grade, the type of family, dating have a significant indirect effect on behavior problem. (3) The variables to have a significant influence on the parental monitoring showed as the monthly income of their family, dating, mother's employment, the type of family, the family discord showed as mother's employment on the parent-adolescent communication showed as the type of family. (4) Family discord was the most powerful predicator of problem behaviors of middle school students.

• Smart Structures and Systems
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• v.30 no.6
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• pp.687-701
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• 2022

Inevitable response loss under complex operational conditions significantly affects the integrity and quality of measured data, leading the structural health monitoring (SHM) ineffective. To remedy the impact of data loss, a common way is to transfer the recorded response of available measure point to where the data loss occurred by establishing the response mapping from measured data. However, the current research has yet addressed the structural condition changes afterward and response mapping learning from a small sample. So, this paper proposes a novel data driven structural response reconstruction method based on a sophisticated designed generating adversarial network (UAGAN). Advanced deep learning techniques including U-shaped dense blocks, self-attention and a customized loss function are specialized and embedded in UAGAN to improve the universal and representative features extraction and generalized responses mapping establishment. In numerical validation, UAGAN efficiently and accurately captures the distinguished features of structural response from only 40 training samples of the intact structure. Besides, the established response mapping is universal, which effectively reconstructs responses of the structure suffered up to 10% random stiffness reduction or structural damage. In the experimental validation, UAGAN is trained with ambient response and applied to reconstruct response measured under earthquake. The reconstruction losses of response in the time and frequency domains reached 16% and 17%, that is better than the previous research, demonstrating the leading performance of the sophisticated designed network. In addition, the identified modal parameters from reconstructed and the corresponding true responses are highly consistent indicates that the proposed UAGAN is very potential to be applied to practical civil engineering.

• Smart Structures and Systems
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• v.34 no.3
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• pp.157-169
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• 2024

Accidents involving inland waterway vessels have raised concerns regarding monitoring their navigation tracks. The economical and convenient deployment of video surveillance equipment and computer vision techniques offer an effective solution for tracking vessel trajectories in narrow inland waterways. However, field applications of video surveillance systems face challenges of small object detection and the limited field of view of cameras. This paper investigates the feasibility of using multiple monocular cameras to monitor long-distance inland vessel trajectories. The one-stage CNN model, YOLOv5, is enhanced for small object detection by incorporating generalized intersection over union loss and a multi-scale fusion attention mechanism. The Bytetrack algorithm is employed to track each detected vessel, ensuring clear distinction in multiple-vessel scenarios. An inverse projection formula is derived and applied to the tracking results from monocular camera videos to estimate vessel world coordinates under potential water level changes in long-term monitoring. Experimental results demonstrate the effectiveness of the improved detection and tracking methods, with consistent trajectory matching for the same vessel across multiple cameras. Utilizing the Savitzky-Golay filter mitigates jitter in the entire final trajectory after timing-alignment merging, leading to a better fit of the dispersed trajectory points.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.2
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• pp.369-376
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• 2018

This paper presents an android-based implementation of real-time remote monitoring system for industrial gas turbines. The use of remote monitoring techniques can be beneficial in terms of not only the reduction of monitoring cost but also the earlier detection of abnormal status. In order to achieve the ability of protecting sensitive information from unauthorized persons, the proposed system supports secure transmissions using the RSA(Rivest Shamir Adleman) algorithm. In the event of abnormal situation on the gas turbine, the remote monitoring system generates an alarm to attract the user's attention by exploiting a push-message technique. The proposed system has been verified through a series of experiments with an experimental setup including a virtual data generator.

• ETRI Journal
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• v.40 no.5
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• pp.664-676
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• 2018

Given the rapidly increasing market penetration of photovoltaic (PV) systems in many fields, including construction and housing, the effective maintenance of PV systems through remote monitoring at the panel level has attracted attention to quickly detect faults that cause reductions in yearly PV energy production, and which can reduce the whole-life cost. A key point of PV monitoring at the panel level is cost-effectiveness, as the installation of the massive PV panels that comprise PV systems is showing rapid growth in the market. This paper proposes an implementation method that involves the use of a panel-level wireless PV monitoring module (WPMM), and which assesses the cost-effectiveness of this approach. To maximize the cost-effectiveness, the designed WPMM uses a voltage-divider scheme for voltage metering and a shunt-resistor scheme for current metering. In addition, the proposed method offsets the effect of element errors by extracting calibration parameters. Furthermore, a design method is presented for portable and user-friendly PV monitoring, and demonstration results using a commercial 30-kW PV system are described.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1480-1493
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• 2018

Recently, computational intelligence has received a lot of attention from researchers due to its potential applications to artificial intelligence. In computer science, computational intelligence refers to a machine's ability to learn how to compete various tasks, such as making observations or carrying out experiments. We adopted a computational intelligence solution to monitoring residual resources in cloud computing environments. The proposed residual resource monitoring scheme periodically monitors the cloud-based host machines, so that the post migration performance of a virtual machine is as consistent with the pre-migration performance as possible. To this end, we use a novel similarity measure to find the best target host to migrate a virtual machine to. The design of the proposed residual resource monitoring scheme helps maintain the quality of service and service level agreement during the migration. We carried out a number of experimental evaluations to demonstrate the effectiveness of the proposed residual resource monitoring scheme. Our results show that the proposed scheme intelligently measures the similarities between virtual machines in cloud computing environments without causing performance degradation, whilst preserving the quality of service and service level agreement.

• Smart Structures and Systems
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• v.12 no.3_4
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• pp.415-426
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• 2013

Condition assessment and monitoring of bridges is critical for safe passenger travel, public transportation, and efficient freight. In monitoring, displacement measurement capability is important to keep track of performance of bridge, in part or as whole. One of the most important parts of a bridge is the expansion joint, which accommodates continuous cyclic thermal expansion of the whole bridge. Though expansion joint is critical for bridge performance, its inspection and monitoring has not been considered significantly because the monitoring requires long-term data using cost intensive equipment. Recently, a wireless smart sensor network (WSSN) has drawn significant attention for transportation infrastructure monitoring because of its merits in low cost, easy installation, and versatile on-board computation capability. In this paper, a rapid wireless displacement monitoring system, wireless hybrid sensor (WHS), has been developed to monitor displacement of expansion joints of bridges. The WHS has been calibrated for both static and dynamic displacement measurement in laboratory environment, and deployed on an in-service highway bridge to demonstrate rapid expansion joint monitoring. The test-bed is a continuous steel girder bridge, the Founders Bridge, in East Hartford, Connecticut. Using the WHS system, the static and dynamic displacement of the expansion joint has been measured. The short-term displacement trend in terms of temperature is calculated. With the WHS system, approximately 6% of the time has been spent for installation, and 94% of time for the measurement showing strong potential of the developed system for rapid displacement monitoring.

• Smart Structures and Systems
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• v.11 no.5
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• pp.477-496
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• 2013

Due to their cost-effectiveness and ease of installation, wireless smart sensors (WSS) have received considerable recent attention for structural health monitoring of civil infrastructure. Though various wireless smart sensor networks (WSSN) have been successfully implemented for full-scale structural health monitoring (SHM) applications, monitoring of low-level ambient strain still remains a challenging problem for WSS due to A/D converter (ADC) resolution, inherent circuit noise, and the need for automatic operation. In this paper, the design and validation of high-precision strain sensor board for the Imote2 WSS platform and its application to SHM of a cable-stayed bridge are presented. By accurate and automated balancing of the Wheatstone bridge, signal amplification of up to 2507-times can be obtained, while keeping signal mean close to the center of the ADC span, which allows utilization of the full span of the ADC. For better applicability to SHM for real-world structures, temperature compensation and shunt calibration are also implemented. Moreover, the sensor board has been designed to accommodate a friction-type magnet strain sensor, in addition to traditional foil-type strain gages, facilitating fast and easy deployment. The wireless strain sensor board performance is verified through both laboratory-scale tests and deployment on a full-scale cable-stayed bridge.

• Spatial Information Research
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• v.14 no.4 s.39
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• pp.421-431
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• 2006

Nowadays, the importance of safety monitoring for facilities is increasing. Therefore, the introduction of ubiquitous technology to replace the existing manually-operated methods is required. In this study, a web-based GIS system that provides monitoring information of bridges in real-time for the application of a bridge management system through the use of ubiquitous technology is constructed. Particular attention is given to the effective interconnection of bridge monitoring information and bridge management system and, through a ubiquitous environment, how to connect this with the UFID and the GIS-based bridge management system (BMS) operated by the Ministry of Construction and Transportation. In addition, data expression methods are also suggested that state the detailed locations and attributes of structures in bridge management by using GIS.