• Smart Structures and Systems
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• 제3권2호
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• pp.201-217
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• 2007

An active damage detection technique is introduced to locate damage in an isotropic plate using Lamb waves. This technique uses a time-domain energy model of Lamb waves in plates that the wave amplitude inversely decays with the propagation distance along a ray direction. Accordingly the damage localization is formulated as a least-squares problem to minimize an error function between the model and the measured data. An active sensing system with integrated actuators/sensors is controlled to excite/receive $A_0$ mode of Lamb waves in the plate. Scattered wave signals from the damage can be obtained by subtracting the baseline signal of the undamaged plate from the recorded signal of the damaged plate. In the experimental study, after collecting the scattered wave signals, a discrete wavelet transform (DWT) is employed to extract the first scattered wave pack from the damage, then an iterative method is derived to solve the least-squares problem for locating the damage. Since this method does not rely on time-of-flight but wave energy measurement, it is more robust, reliable, and noise-tolerant. Both numerical and experimental examples are performed to verify the efficiency and accuracy of the method, and the results demonstrate that the estimated damage position stably converges to the targeted damage.

• Smart Structures and Systems
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• 제15권4호
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• pp.1121-1137
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• 2015

This study presents probabilistic-based damage identification technique for highlighting damage in metallic structures. This technique utilizes distributed piezoelectric transducers to generate and monitor the ultrasonic Lamb wave with narrowband frequency. Diagnostic signals were used to define the scatter signals of different paths. The energy of scatter signals till different times were calculated by taking root mean square of the scatter signals. For each pair of parallel paths an error function based on the energy of scatter signals is introduced. The resultant error function then is used to estimate the probability of the presence of damage in the monitoring area. The presented method with an autofocusing feature is applied to aluminum plates for method verification. The results identified using both simulation and experimental Lamb wave signals at different central frequencies agreed well with the actual situations, demonstrating the potential of the presented algorithm for identification of damage in metallic structures. An obvious merit of the presented technique is that in addition to damages located inside the region between transducers; those who are outside this region can also be monitored without any interpretation of signals. This novelty qualifies this method for online structural health monitoring.

• Smart Structures and Systems
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• 제6권9호
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• pp.1057-1077
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• 2010

An early detection of structural damages is critical for the decision making of repair and replacement maintenance in order to guarantee a specified structural reliability. Consequently, the structural damage detection, based on vibration data measured from the structural health monitoring (SHM) system, has received considerable attention recently. The traditional time-domain analysis techniques, such as the least square estimation (LSE) method and the extended Kalman filter (EKF) approach, require that all the external excitations (inputs) be available, which may not be the case for some SHM systems. Recently, these two approaches have been extended to cover the general case where some of the external excitations (inputs) are not measured, referred to as the adaptive LSE with unknown inputs (ALSE-UI) and the adaptive EKF with unknown inputs (AEKF-UI). Also, new analysis methods, referred to as the adaptive sequential non-linear least-square estimation with unknown inputs and unknown outputs (ASNLSE-UI-UO) and the adaptive quadratic sum-squares error with unknown inputs (AQSSE-UI), have been proposed for the damage tracking of structures when some of the acceleration responses are not measured and the external excitations are not available. In this paper, these newly proposed analysis methods will be compared in terms of accuracy, convergence and efficiency, for damage identification of structures based on experimental data obtained through a series of laboratory tests using a scaled 3-story building model with white noise excitations. The capability of the ALSE-UI, AEKF-UI, ASNLSE-UI-UO and AQSSE-UI approaches in tracking the structural damages will be demonstrated and compared.

• ETRI Journal
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• 제45권6호
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• pp.1007-1021
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• 2023

Stroke is the leading cause of permanent disability in adults, and it can cause permanent brain damage. According to the World Health Organization, 795 000 Americans experience a new or recurrent stroke each year. Early detection of medical disorders, for example, strokes, can minimize the disabling effects. Thus, in this paper, we consider various risk factors that contribute to the occurrence of stoke and machine learning algorithms, for example, the decision tree, random forest, and naive Bayes algorithms, on patient characteristics survey data to achieve high prediction accuracy. We also consider the semisupervised self-training technique to predict the risk of stroke. We then consider the near-miss undersampling technique, which can select only instances in larger classes with the smaller class instances. Experimental results demonstrate that the proposed method obtains an accuracy of approximately 98.83% at low cost, which is significantly higher and more reliable compared with the compared techniques.

• 한국의학물리학회:학술대회논문집
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• 한국의학물리학회 2002년도 Proceedings
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• pp.356-358
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• 2002

MRI, particularly diffusion weighted imaging (DWI), plays vital roles in detection of the acute brain infarction$\^$1-4/ and others metabolic changes of biological tissues. In general, every molecule in biological tissues may diffuse and move randomly in three-dimensional space. However, in clinical diagnosis, only 2D-DWI is used. The authors have developed a new method for rapid three-dimensional DWI (3D-DWI). In this method, by refocusing of the magnetized spin with the applied gradient field, direction of which is opposite to phase encoding field. Magnetized spin of $^1$H is kept under the SSFP (steady state free precession)$\^$5-6/. Under SSFP, in addition of FID, spin echo and stimulated echo are also generated, so the acquired signal is increased. The signal intensity is increased depending on flip angle (FA) of magnetized spin. This phenomenon is confirmed by human brain and phantom studies. The performance of this method is quantitatively analyzed by using both of conventional spin echo DWI and 3D-DWI. From experimental results, three dimensional diffusion weighted images are obtained correctly for liquid phantoms (water, acetone and oil), diffusion coefficient is enhanced in each image. Therefore, this method will provide useful information for clinical diagnosis.

• 센서학회지
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• 제19권1호
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• pp.8-16
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• 2010

This research proposes measuring of BCG(ballistocardiogram) to monitor heart activities in a non-constrained environment, at home or work. Unlike with ECG, measuring BCG does not require the attachment of leads on the subject's body and allows signal measuring in a non-constrained state. It enables effective long-term monitoring of cardiac conditions. In this study a chair type BCG measurement system to continuous monitor the activity of the heart is implemented. The instrument consists of upper petal and ready for press of chair load cell sensor is attached to measure the change of the object's weight. In order to extract the output ballistic signal from the weight and force sensor signals. Beside the signal processing circuit for the digital conversion, the ballistic signal is detected using DAQ equipment. Signal processing algorithm including wavelet transforms for noise cancellation, template matching for normalization and peak detection in BCG is developed. ECG and BCG were concurrently measured to evaluate the performance of the system, and comparing the characteristics of the two signals verified the possibility of the system in non-constrained and nonconscious health monitoring.

• Journal of Community Nutrition
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• 제4권3호
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• pp.180-186
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• 2002

The food attitudes of 285 Korean female students attending a secondary school in Seoul were examined with respect to the 5 food groups of the Korean Food Tower : grain products, vegetables and fruits, meat, milk, and fats and sweets. An instrument with 22 items was utilized to measure food attitudes toward the five food groups. The items were categorized into five factors through factor analysis to obtain a description of the participants' food attitudes. The five factors are conscious choice of food, health concerns, economics and time influence, interest in foods, and foods that energize. Several facts emerged from examining the food attitudes. The most evident was their response to the items concerning the influence of economics and time on food choice, which the majority consider not limiting their food consumption. Most participants gave favorable responses for vegetables and fruits on all the five factors, but gave unfavorable responses for meat group and fats and sweets in health concerns. They also gave favorable responses for“foods that energize”for all except fats and sweets. Four of the total 25 relationships among food intake (five groups) and food attitudes (five factors) were found to have significant positive correlations (p < .01). (J Community Nutrition 4(3) : 180∼186, 2002)

• International Journal of Contents
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• 제16권1호
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• pp.75-86
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• 2020

As the elderly population is becoming an aging society, the elderly are experiencing many problems. Social security costs for the elderly are increasing and the un-linked social phenomenon is emerging. Thus, the social infrastructure and welfare system established in the past economic growth period are in danger of not functioning properly. People socially isolated or with chronic diseases among the elderly are exposed to various accidents. Thus, an active healthcare management service is imperative. Additionally, in the event of a dangerous situation, the system must have ways to notify guardians (family or medical personnel) regarding appropriate action. Thus, in this paper, we propose the smartphone-based healthcare and emergency response service platform. The proposed service platform aggregates movement of relevant data in real-time using a smartphone. Based on aggregated data, it will always recognize the user's movements and current state using the human motion recognition mechanism. Thus, the proposed service platform provides real-time status monitoring, activity reports, a health calendar, location-based hospital information, emergency situation detection, and cloud messaging server-based efficient notification to several subscribers such as family, guardians, and medical personnel. Through this service, users or guardians can augment the level of care for the elderly through the reports. Also, if an emergency situation is detected, the system immediately informs guardians so as to minimize the risk through immediate response.

• Safety and Health at Work
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• 제11권2호
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• pp.207-214
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• 2020

Background: Prolonged sitting at work can lead to adverse health outcomes. The health risk of office workers is an increasing concern for the society and industry, with prolonged sitting work becoming more prevalent. Objective: This study aimed to explore the variation in muscle activities during prolonged sitting work and found out when and how to take a break to mitigate the risk of muscle symptoms. Methods: A preliminary survey was conducted to find out the prevalence of muscle discomfort in sedentary work. Firstly, a 2-h sedentary computer work was designed based on the preliminary study to investigate the variation in muscle activities. Twenty-four participants took part in the electromyography (EMG) measurement study. The EMG variations in the trapezius muscle and latissimus dorsi were investigated. Then the intervention time was determined based on the EMG measurement study. Secondly, 48 participants were divided into six groups to compare the effectiveness of every break type (passive break, active break of changing their posture, and stand and stretch their body with 5 or 10 mins). Finally, data consisting of EMG amplitudes and spectra and subjective assessment of discomfort were analyzed. Results: In the EMG experiment, results from the joint analysis of the spectral and amplitude method showed muscle fatigue after about 40 mins of sedentary work. In the intervention experiment, the results showed that standing and stretching for 5 mins was the most effective break type, and this type of break could keep the muscles' state at a recovery level for about 30-45 mins. Conclusions: This study offers the possibility of being applied to office workers and provides preliminary data support and theoretical exploration for a follow-up early muscle fatigue detection system.

• 한국산업보건학회지
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• 제10권1호
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• pp.208-222
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• 2000

This study was conducted to supplement limit of previous study, The objectives of this study were to select optimal conditions of high performance liquid chromatography(HPLC) operation for detecting urinary 2-thiothiazolicline-4-carboxylic acid(TTCA) and thiocarbamide simultaneously, and to evaluate recovery rates for various liquid-liquid extration method of these metabolites, The results are as follows : 1. The urinary TTCA and thiocarbamide were separate sharply when flow rate is $0.7m{\ell}/min$, using a series $C_8$ and $C_{18}$ column, 50 mM $KH_2PO_4$ : acetonitrile (93.5 : 6.5) and pH 3.5 as a mobile phase. The retention time was TTCA, $12.07{\pm}0.11$(mean${\pm}$SD, n=06), thiocarbamide, $7.85{\pm}0.01$ (mean${\pm}$SD, n=6), respectively. The calibration curve for TTCA and thiocarbamide was linear within the range 0.05 to $30{\mu}g/m{\ell}$. 2. By the liquid-liquid extration, butanol extration with $(NH_4)_2$ as a salting-out reagent was used as a simultaneous extration method for these metabolites in acid state, and recovery rates of this method are urinary TTCA, $49.6{\pm}17.7$ (mean${\pm}$SD, n=16), thiocarbamide, $43,9{\pm}5.50$ (mean${\pm}$SD, n=16), respectively 3. The precision(pooled coefficients of variation for 4 concentration) of the urinary thiocarbamide analysis was 0.03754 by butanol liquid-liquid extraction with $(NH_4)_2$ as a salting-out reagent, and TTCA was 0.04082 by ethyl acetate liquid-liquid extration with $(NH_4)_2$ as a salting out reagent The above results show that the butanol liquid-liquid extraction with $(NH_4)_2$ as a salting-out reagent in acid state, and using a series $C_8$ and $C_{18}$ column, 50 mM $KH_2PO_4$ : acetonitrile (93.5 : 6.5) and pH 3.5 as a mobile phase are suitable for the analysis of urinary TTCA and thiocarbamide simultaneously. The detection limit of TTCA and thiocarbamide was about $0.17{\mu}g/m{\ell}$, $0.07{\mu}g/m{\ell}$.