• Structural Monitoring and Maintenance
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• v.9 no.1
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• pp.59-80
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• 2022

In the present study, the objective is to detect the structural damages using the responses obtained from the sensors at the optimal location under uncertainty conditions. Reducing the error rate in damage detection process due to responses' noise is an important goal in this study. In the proposed algorithm for optimal sensor placement, the noise of responses recorded from the sensors is initially reduced using the principal component analysis. Afterward, the optimal sensor placement is obtained by the damage detection equation based sensitivity analysis. The sensors are placed on degrees of freedom corresponding to the minimum error rate in structural damage detection through this procedure. The efficiency of the proposed method is studied on a truss bridge, a space dome, a double-layer grid as well as a three-story experimental frame structure and the results are compared. Moreover, the performance of the suggested method is compared with three other algorithms of Average Driving Point Residue (ADPR), Effective Independence (EI) method, and a mass weighting version of EI. In the examples, young's modulus, density, and cross-sectional areas of the elements are considered as uncertainty parameters. Ultimately, the results have demonstrated that the presented algorithm under uncertainty conditions represents a high accuracy to obtain the optimal sensor placement in the structures.

• Smart Structures and Systems
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• v.13 no.3
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• pp.389-406
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• 2014

Optimal sensor placement techniques play a significant role in enhancing the quality of modal data during the vibration based health monitoring of civil structures, where many degrees of freedom are available despite a limited number of sensors. The literature has shown a shift in the trends for solving such problems, from expansion or elimination approach to the employment of heuristic algorithms. Although these heuristic algorithms are capable of providing a global optimal solution, their greatest drawback is the requirement of high computational effort. Because a highly efficient optimisation method is crucial for better accuracy and wider use, this paper presents an improved simulated annealing (SA) algorithm to solve the sensor placement problem. The algorithm is developed based on the sensor locations' coordinate system to allow for the searching in additional dimensions and to increase SA's random search performance while minimising the computation efforts. The proposed method is tested on a numerical slab model that consists of two hundred sensor location candidates using three types of objective functions; the determinant of the Fisher information matrix (FIM), modal assurance criterion (MAC), and mean square error (MSE) of mode shapes. Detailed study on the effects of the sensor numbers and cooling factors on the performance of the algorithm are also investigated. The results indicate that the proposed method outperforms conventional SA and Genetic Algorithm (GA) in the search for optimal sensor placement.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.4
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• pp.1931-1938
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• 2012

This study evaluated whether the installed location of air quality monitoring stations is at an optimal level in an effort to improve the health and environmental quality of the surrounding areas of the Pohang Steel Complex. As a result of analyzing the atmospheric flow field, it was found that the location of air quality monitoring stations was acceptable in case of Daesong-myeon(The 1st Division of Local Wind Sector) and Jukdo-dong(The 3rd Division of Local Wind Sector). However, the air quality monitoring stations installed at Daedo-dong and Jukdo-dong is judged to have made an overlapped measurement because the stations existed at the Division of the same Wind Sector. Accordingly, this study suggests that the further air quality monitoring stations should be additionally installed at Buk-gu areas of Pohang where more than 50% of the population of Pohang is living presently. As a result of the analysis of air contaminant concentration distribution, the Jangheung-dong area showed higher concentration distribution than other areas in case of $PM_{10}$ while the Daesong-myeon area showed a comparatively higher concentration distribution in case of $O_3$. Conclusively, this study indicates that it is high time to prepare an aggressive management of $PM_{10}$ and $O_3$ which causes a harmful impact on the life and health of the residents of the target areas.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2005.04a
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• pp.316-319
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• 2005

Contaminated area should be identified for designing polluted groundwater cleanup plan. A methodology was suggested to identify a contaminant plume distribution geostatistically. James & Gorelick (1994) suggested a methodology to evaluate data worth as expected reducing remediation cost. In this study, their methodology was modified to evaluate data worth as expected reducing uncertainty of the contaminant plume distribution. In suggested methodology, the source identification model by Mahar & Datta (2001) using a forward solute transport model is integrated. Suggested methodology was assessed by two simple example problems and its result represented reducing uncertainties of contaminant plume distribution successfully.

• Nuclear Engineering and Technology
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• v.55 no.2
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• pp.493-505
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• 2023

Comprehensive condition monitoring of large industry systems such as nuclear power plants (NPPs) is essential for safety and maintenance. In this study, we developed novel system-scale diagnostic technology based on deep-learning and IR thermography that can efficiently and cost-effectively classify system conditions using compact Raspberry Pi and IR sensors. This diagnostic technology can identify the presence of an abnormality or accident in whole system, and when an accident occurs, the type of accident and the location of the abnormality can be identified in real-time. For technology development, the experiment for the thermal image measurement and performance validation of major components at each accident condition of NPPs was conducted using a thermal-hydraulic integral effect test facility with compact infrared sensor modules. These thermal images were used for training of deep-learning model, convolutional neural networks (CNN), which is effective for image processing. As a result, a proposed novel diagnostic was developed that can perform diagnosis of components, whole system and accident classification using thermal images. The optimal model was derived based on the modern CNN model and performed prompt and accurate condition monitoring of component and whole system diagnosis, and accident classification. This diagnostic technology is expected to be applied to comprehensive condition monitoring of nuclear power plants for safety.

• Journal of Fashion Business
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• v.26 no.5
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• pp.91-104
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• 2022

In this study, a cycling smart wear for measuring cycling posture and motion was developed using a three-dimensional motion analysis camera and an IMU inertial sensor. Results were compared according to parts to derive the optimal smart device attachment location, enabling correct posture measurement and cycle motion analysis to design a pattern. Conclusions were as follows: 1) 'S-T8' > 'S-T10' > 'S-L4' was the most significant area for each lumbar spine using a 3D motion analysis system with representative posture change (90°, 60°, 30°) to derive incisions and size specifications; 2) the part with the smallest relative angle change among significant section reference points during pattern design was applied as a reference point for attaching a cycling smart device to secure detachable safety of the device. Optimal locations for attaching the cycling device were the "S-L4" hip bone (Sacrum) and lumbar spine No. 4 (Lumbar 4^th); 3) the most suitable sensor attachment location for monitoring knee induction-abduction was the anatomical location of the rectus femoris; 4) a cycling smart wear pattern was developed without incision in the part where the sensor and electrode passed. The wearing was confirmed with 3D CLO. This study aims to provide basic research on exercise analysis smart wear, to expand the smart cycling area that could only be realized with smart devices and smart watches attached to current cycles, and to provide an opportunity to commercialize it as cycling smart wear.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.9
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• pp.1132-1140
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• 2016

According to global trend, despite the overall scale of agricultural industry has been downsized, agriculture accommodating cutting-edge ICT technologies has been proliferated, and various timely-issued relevant researches have been on progress to deploy the future food cultivation. In this paper, we propose an effective nutrient management system with web-based monitoring with functionality of controlling temperature, humidity, pH (hydrogen ion), EC (Electric Conductivity), LED and cooling fan to maintain the hydroponic nurturing environment being optimal. In this paper, in order the arduino hardware and java software are employed to control the nurturing environment automatically in optimal fashion. In proposed system, due to the usage of WiFi router with the socket communication and DB-assisted Web server with proper interfaces, it allows to facilitate the management to keep monitoring and controling overall hydroponic nurturing environment. Since the proposed Web-based management system provides the superior reliability, the short nurturing period and the robustness to the pest by controlling LED emitting color rather than conventional system, so it can be applied and appropriate for in-house vegetable factory overcoming limitation of time and location.

• Transactions of the Korean Society of Automotive Engineers
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• v.17 no.5
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• pp.74-83
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• 2009

Recently, usage of electric and electronic system for car increases rapidly. Consequently power monitoring supplied to the system is essential for management and controlling. Generally, battery status is monitored through measuring and diagnosing the current measurement method utilizing Hall Effect. Therefore, in this paper, we analysed magnetic field to develop the solution of DC current sensor using Hall Effect which is the core of design and development. By analysing the magnetic field by FEM using Maxwell 3D software, the location of the highest output current and stable part in the Hall IC sensor was shown. Also, the optimal core design of DC current sensor using parametric and Simplex method was presented. A car battery charge and discharge process dependant on time effect on the changing of magnetic field was simulated and compared to the result from the experiment result of actual vehicle.

• Journal of Korea Multimedia Society
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• v.19 no.11
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• pp.1891-1899
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• 2016

Recently food problem and crop disaster have been increased continuously because of the meteorological changes. These cause rising cost for crops continuously and irregularly. Some researchers have studied straight structure of device for hydroponics and plant factory previously to solve a fundamental part of these problems. However, there are several problems such as limited crop cultivation space, providing irregular nutrients for crops, and lack of monitoring interfaces. For them, we propose an optimal growth and development crops management system using light source tracking and recirculation of nutrient solution method to supply nutrient continuously based on IoT. In order to evaluate the performance of our system, we compared and analyzed in terms of two viewpoints, the tracking analysis for natural light source measurement and the growth of crops through artificial light, LED, respectively. We confirmed that the higher the duty ratio of LED, the larger the crop's size, particularly. As well as, for about 1 month, we compared with the existing natural light growing environment and that of our system. It was confirmed that the size of the crops grown through our system is about three times larger than that of natural light natural crops.

• Smart Structures and Systems
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• v.2 no.2
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• pp.189-208
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• 2006

Monitoring large-scale civil engineering structures such as offshore platforms and high-large buildings requires a large number of sensors of different types. Innovative sensor data information technologies are very extremely important for data transmission, storage and retrieval of large volume sensor data generated from large sensor networks. How to obtain the optimal sensor set and placement is more and more concerned by researchers in vibration-based SHM. In this paper, a method of determining the sensor location which aims to extract the dynamic parameter effectively is presented. The method selects the number and place of sensor being installed on or in structure by through the tolerance domain statistical inference algorithm combined with second order sensitivity technology. The method proposal first finds and determines the sub-set sensors from the theoretic measure point derived from analytical model by the statistical tolerance domain procedure under the principle of modal effective independence. The second step is to judge whether the sorted out measured point set has sensitive to the dynamic change of structure by utilizing second order characteristic value sensitivity analysis. A 76-high-building benchmark mode and an offshore platform structure sensor optimal selection are demonstrated and result shows that the method is available and feasible.