• Structural Engineering and Mechanics
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• v.78 no.5
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• pp.599-610
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• 2021

Early detection of small concrete crack or reinforcement corrosion is necessary for Structural Health Monitoring (SHM). Global vibration based methods are advantageous over local methods because of simple equipment installation and cost efficiency. Among vibration based techniques, FRF based methods are preferred over modal based methods. In this study, a new coupled method using frequency response function (FRF) and proper orthogonal modes (POM) is proposed by using the dynamic characteristic of a damaged beam. For the numerical simulation, wave finite element (WFE), coupled with traditional finite element (FE) method is used for effectively incorporating the damage related information and faster computation. As reported in literature, hybrid combination of wave function based wave finite element method and shape function based finite element method can addresses the mid frequency modelling difficulty as it utilises the advantages of both the methods. It also reduces the dynamic matrix dimension. The algorithms are implemented on a three-dimensional reinforced concrete beam. Damage is modelled and studied for two scenarios, i.e., crack in concrete and rebar corrosion. Single and multiple damage locations with different damage length are also considered. The proposed methodology is found to be very sensitive to both single- and multiple- damage while being computationally efficient at the same time. It is observed that the detection of damage due to corrosion is more challenging than that of concrete crack. The similarity index obtained from the damage parameters shows that it can be a very effective indicator for appropriately indicating initiation of damage in concrete structure in the form of spread corrosion or invisible crack.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.145-153
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• 2023

This study emphasizes the essential need in the military for effective measurement and monitoring of soldiers' physical fitness, health, and exercise capabilities to enhance both their overall fitness and combat effectiveness. The effective assessment of physical fitness is considered a core element of management, aligning with principles of modern management. Particularly, preparing soldiers with robust physical fitness is deemed crucial for adapting to dynamic changes on the battlefield. In this research, the RFM (Recency, Frequency, Monetary) customer analysis and clustering methods, validated in e-commerce, are introduced as a basis for applying an AI-driven customer analysis approach to assess military personnel fitness. To achieve this, the study explores the incorporation of the RSC (Reveal, Sustainable, Control) analysis model. This model aims to effectively categorize and monitor military personnel fitness. The application of the RFM technique in the RSC analysis model quantifies and models military fitness, fostering continuous improvement and seeking strategies to enhance the effectiveness of fitness management. Through these methods, the study develops an AI customer analysis technique applied to the RSC clustering analysis method for improving and sustaining military personnel fitness.

• Structural Engineering and Mechanics
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• v.89 no.6
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• pp.589-599
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• 2024

This study presents the usability of the high-rate single-frequency Precise Point Positioning (SF-PPP) technique based on 20 Hz Global Positioning Systems (GPS)-only observations in detecting dynamic motions. SF-PPP solutions were obtained from post-mission and real-time GNSS corrections. These include the International GNSS Service (IGS)-Final, IGS real-time (RT), real-time MADOCA (Multi-GNSS Advanced Demonstration tool for Orbit and Clock Analysis), and real-time products from the Australian/New Zealand satellite-based augmentation systems (SBAS, known as SouthPAN). SF-PPP results were compared with LVDT (Linear Variable Differential Transformer) sensor and single-frequency relative positioning (SF-RP) solutions. The findings show that the SF-PPP technique successfully detects the harmonic motions, and the real-time products-based PPP solutions were as accurate as the final post-mission products. In the frequency domain, all GNSS-based methods evaluated in this contribution correctly detect the dominant frequency of short-term harmonic oscillations, while the differences in the amplitude values corresponding to the peak frequency do not exceed 1.1 mm. However, evaluations in the time domain show that SF-PPP needs high-pass filtering to detect accurate displacement since SF-PPP solutions include trends and low-frequency fluctuations, mainly due to atmospheric effects. Findings obtained in the time domain indicate that final, real-time, and MADOCA-based PPP results capture short-term dynamic behaviors with an accuracy ranging from 3.4 mm to 8.5 mm, and SBAS-based PPP solutions have several times higher RMSE values compared to other methods. However, after high-pass filtering, the accuracies obtained from PPP methods decreased to a few mm. The outcomes demonstrate the potential of the high-rate SF-PPP method to reliably monitor structural and earthquake-induced ground motions and vibration frequencies of structures.

• Journal of Korean Society of Steel Construction
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• v.17 no.6 s.79
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• pp.681-688
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• 2005

This study investigates an existing steel plate girder railroad bridge after superstructure rehabilitation to monitor static and dynamic responses using Fiber Bragg Grating (FBG) sensors. This paper also presents an experimental technique to estimate the vertical deflection of the bridge using FBG sensors. Seven FBG sensors are multiplexed in a single optical fiber and installed in parallel pairs along the length of the bridge, with one set at the top flange and the other at the bottom flange. In addition to FBG sensors, a conventional electric strain gauge and anLVDT are installed at the mid-span of the bridge for comparison. A test train consisting of one locomotive is placed at the center of the bridge to produce the maximum static effect. The train is also made to pass over the bridge at different speeds ranging from 10 km/h to 90 km/h to monitor the dynamic response of the bridge. This study demonstrates that the measured strains using the FBG sensor compared well with the readings from the electric strain gauge. The results show that the proposed instrumentation technique is capable of estimating the vertical deflection of the bridge for various loading conditions, which is crucial in structural health monitoring. Several dynamic characteristics of the bridge were also identified.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.5
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• pp.785-796
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• 2023

In this study, a methodology for real-time classification and prediction of defects that may appear in PVDF(Polyvinylidene fluoride) sensors, which are widely used for structural integrity monitoring, is proposed. The types of sensor defects appearing according to the sensor attachment environment were classified, and an impact test using an impact hammer was performed to obtain an output signal according to the defect type. In order to cleary identify the difference between the output signal according to the defect types, the time domain statistical features were extracted and a data set was constructed. Among the machine learning based classification algorithms, the learning of the acquired data set and the result were analyzed to select the most suitable algorithm for detecting sensor defect types, and among them, it was confirmed that the highest optimization was performed to show SVM(Support Vector Machine). As a result, sensor defect types were classified with an accuracy of 92.5%, which was up to 13.95% higher than other classification algorithms. It is believed that the sensor defect prediction technique proposed in this study can be used as a base technology to secure the reliability of not only PVDF sensors but also various sensors for real time structural health monitoring.

• The Korean Journal of Nuclear Medicine Technology
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• v.12 no.1
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• pp.33-38
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• 2008

Purpose: The Gated cardiac blood pool scan is non-invasive method that a quantitative evaluation of left ventricular function. Also this scan have shown the value of radionuclide ejection fraction measurements during the course of chemotherapy as a predictor of cardiac toxicity. Therefore a reliable method of monitoring its cardiotoxic effects is necessary. the purpose of this study is to minimize the overestimate of left ventricular ejection fraction (LVEF) by modified body position to reduce the influence of scattered rays from surrounding organs of the heart in the background region of interest. Materials and Methods: Gated cardiac blood pool scan using in vivo $^{99m}Tc$-red blood cell (RBC) was carried out in 20 patients (mean $44.8{\pm}8.6$ yr) with chemotherapy for a breast carcinoma. Data acquisition requires about 600 seconds and 24 frames of one heart cycle by the multigated acquisition mode, Synchronization deteriorates toward the end of the cycle and with the distance from the trigger signal (R-wave) by ECG gating. Gated cardiac blood pool scan was studied with conventional method (supine position and the detector head in $30-45^{\circ}$ left anterior oblique position and caudal $10-20^{\circ}$ tilt) and compared with modified method (left lateral flexion position with 360 mL of drinking water). LVEF analysis was performed by using the automatically computer mode. Results: The ROI counts of modified scan method were lower than LV conventional method ($1429{\pm}251$ versus $1853{\pm}243$, <0.01). And LVEF of modified method was also decrease compared with conventional method ($58.3{\pm}5.6%$ versus $65.3{\pm}6.1%$, <0.01). Imaging analysis indicated that stomach was expanded because of water and spleen position was changed to lateral inferior compared with conventional method. Conclusion: This study shows that the modified method in MUGA reduce the influence of scattered rays from surrounding organs. Because after change the body position to left lateral flexion and drinking water, the location of spleen, left lobe of liver and stomach had changed and they could escaped from background ROI. Therefore, modified method could help to minimize the overestimate LVEF (%).

• Journal of the Korean Society for Nondestructive Testing
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• v.31 no.4
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• pp.360-366
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• 2011

The Elasto-magnetic sensor is applied to detect the local cross-sectional loss of steel cables in this study while it was originally developed for measuring the tensile force in the previous works. To verify the feasibility of the proposed damage detection technique, steel bars which have 4-different diameters were fabricated and the output voltage value was measured at each diameter by the E/M sensor. Optimal input voltage and working point are chosen so that the linearity and resolution of results can ensure through repeated experiments, and then the E/M sensor was measured the output voltage values at the damage points of steel bar specimen that was applied the 4 types of damage condition based on the selected optimal experimental condition. This proposed approach can be an effective tool for steel cable health monitoring.

• Journal of the Korea institute for structural maintenance and inspection
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• v.15 no.4
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• pp.165-174
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• 2011

This research aims at the optimal constitution of sensors required to identify the structural shortcoming of roller-coaster. In this research we analyzed the dynamic characteristics of roller-coaster by three dimensional FE modelling, decided on the appropriate location and number of sensors through optimal transducer theory, abstracted the mathematical value of modal features before and after damage on the basis of optimally placed and numbered sensors. and then presented it as a primary information about the basic structure which would be applied to damage estimation. As a target structure, the roller-coater at Seoul Children's Grand Park was chosen and built as a model reduced by one twentieth in size. In order to consider the Kinetics features particular to the roller-coaster structure, we made an exact three-dimensional FE modelling for the model structure by means of Spline function. As for the proper location and number of sensors, it was done by applying EIM and EOT. We also estimated the damage from the combination of strength, flexibility, and model corelation after abstracting the value of modal features. Finally the optimal transducer theory presented here in this research was proved to be valid, and the structural damage was well identified through changes in strength and flexibility. As a result, we were able to present the optimal constitution of sensors needed for the analysis of dynamic characteristics and the development of techniques in dynamic characteristics, which would ultimately contribute to the development of health monitoring for roller-coaster.

• Genomics & Informatics
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• v.15 no.1
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• pp.2-10
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• 2017

Early detection and proper management of kidney rejection are crucial for the long-term health of a transplant recipient. Recipients are normally monitored by serum creatinine measurement and sometimes with graft biopsies. Donor-derived cell-free deoxyribonucleic acid (cfDNA) in the recipient's plasma and/or urine may be a better indicator of acute rejection. We evaluated digital PCR (dPCR) as a system for monitoring graft status using single nucleotide polymorphism (SNP)-based detection of donor DNA in plasma or urine. We compared the detection abilities of the QX200, RainDrop, and QuantStudio 3D dPCR systems. The QX200 was the most accurate and sensitive. Plasma and/or urine samples were isolated from 34 kidney recipients at multiple time points after transplantation, and analyzed by dPCR using the QX200. We found that donor DNA was almost undetectable in plasma DNA samples, whereas a high percentage of donor DNA was measured in urine DNA samples, indicating that urine is a good source of cfDNA for patient monitoring. We found that at least 24% of the highly polymorphic SNPs used to identify individuals could also identify donor cfDNA in transplant patient samples. Our results further showed that autosomal, sex-specific, and mitochondrial SNPs were suitable markers for identifying donor cfDNA. Finally, we found that donor-derived cfDNA measurement by dPCR was not sufficient to predict a patient's clinical condition. Our results indicate that donor-derived cfDNA is not an accurate predictor of kidney status in kidney transplant patients.

• Journal of the Korea institute for structural maintenance and inspection
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• v.17 no.2
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• pp.10-20
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• 2013

To evaluate the safety of a beam structure, strains are measured as an indicator of structural states. However, unless strain sensors are installed exactly on where maximum or other representative strains occur, the techniques by which rational assessment through measured strains is accomplished are required. Thus, this study suggests a process to estimate strain distribution on the steel beam from discrete strains measured by sensors. In the presented technique, the targeted beam is regarded to be subjected to unknown loads so that applicability is enhanced. Final strain distribution is given as form of a function after regression analysis. To verify the performance of estimation, a bending test for steel beam on which distributed and concentrated loads simultaneously act is conducted. From the comparison between estimated and directly measured strains in the test, the curve of strain distribution and the strain at arbitrary location could be predicted within maximum relative error 3.32% and maximum absolute error of $2.32{\mu}{\varepsilon}$, respectively. Thus reliable and practical monitoring is expected to apply effectively for the steel beam structure.