• Korean Journal of Clinical Pharmacy
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• v.33 no.2
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• pp.122-127
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• 2023

Background: This study was aimed to identify the safety signals of metoclopramide in Korea Adverse Event Reporting System (KAERS) database by proportionality analysis methods. Methods: The study was conducted using Korea Institute of Drug Safety and Risk Management-Korea Adverse Event Reporting System Database (KIDS-KD) reported from January 2013 to December 2017 through KAERS. Signals of metoclopramide that satisfied the data-mining indices of proportional reporting ratio (PRR), reporting odds ratio (ROR) and information component (IC) were defined. The detected signals were checked whether they included in drug labels in the Ministry of Food and Drug Safety (MFDS), U.S. Food and Drug Administration (FDA) and Micromedex^®. Results: A total number of drug AE reports associated with all drugs of data in this study was 2,665,429. Among them, the number of AE reports associated with metoclopramide was 22,583. Forty-two meaningful signals of metoclopramide were detected that satisfied with the criteria of data-mining indicies. Especially neurological signals including extrapyramidal reactions, represented in the safety letter of regulatory agencies were identified in this study. Conclusion: Neurological signals of metoclopramide including extrapyramidal reactions were detected. It is believed that this search for signals can contribute to ensuring safety in the use of metoclopramide.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.4
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• pp.707-722
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• 1992

Fracture of a cutting tool is one of the most serious problems in machining systems. Therefore, several methods have been proposed so far to detect cutting tool fracture. However, most of them have some problems from the viewpoint of practical applications. In this study, the feasibility of using acoustic emission and cutting force signals for the detection of massive tool breakages as well as small fracture of cutting tools were investigated. Turning experiments were performed using conventional carbide inset tools under realistic cutting conditions and the SM45C steel and heat treated SM45C steel were used as a workpiece. And the sensitivities of the AE and cutting force signals to the fracture of cutting tools were illustrated. Finally, a detection algortithm for the fracture of cutting tools was developed through the analysis of these dual signals in the several types of tool fracture.

• The Journal of the Acoustical Society of Korea
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• v.40 no.4
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• pp.337-346
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• 2021

Detection of abnormal signal generally can be done by using features of normal signals as main information because of data imbalance. This paper propose an efficient method for abnormal signal detection using parallel AutoEncoder (AE) which can use features of abnormal signals as well. The proposed Parallel AE (PAE) is composed of a normal and an abnormal reconstructors having identical AE structure and train features of normal and abnormal signals, respectively. The PAE can effectively solve the imbalanced data problem by sequentially training normal and abnormal data. For further detection performance improvement, additional binary classifier can be added to the PAE. Through experiments using public acoustic data, we obtain that the proposed PAE shows Area Under Curve (AUC) improvement of minimum 22 % at the expenses of training time increased by 1.31 ~ 1.61 times to the single AE. Furthermore, the PAE shows 93 % AUC improvement in detecting abnormal underwater acoustic signal when pre-trained PAE is transferred to train open underwater acoustic data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.2
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• pp.433-442
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• 2013

This paper presents experimental research work for the evaluation of one-dimensional and two-dimensional acoustic source locations with 50m length of a precast prestressed concrete box girder. Acoustic events are generated by the impacts of Schmidt Hammer and the impact signals are detected by acoustic emission sensors mounted on the concrete web surface of PSC box girder with the average spacing of 9.34m. Based on the amplitude of detected acoustic signals, considering the noises developed in PSC box girder bridges, the arrival times of acoustic signals are estimated by the first arrival times of 0Volt, 0.5Volt, and 1.0Volt amplitude in each signal. Using Least Square Method, the velocities and the source locations of acoustic signals are evaluated. Based on the test results, the spacing of AE sensors and the AE sensor networks are discussed to reduce the source location errors.

• Journal of Mechanical Science and Technology
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• v.17 no.3
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• pp.391-399
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• 2003

The thermo-acoustic emission (AE) technique has been applied for nondestructive characterization of composite laminates subjected to cryogenic cooling. Thermo-AE events during heating and cooling cycles showed a Kaiser effect. An analysis of the thermo-AE behavior obtained during the 1st heating period suggested a method for determining the stress-free temperature of the composite laminates. Three different thermo-AE types classified by a short-time Fourier transform of AE signals enabled to offer a nondestructive estimation of the cryogenic damages of the composites, in that the different thermo-AE types corresponded to secondary microfracturing in the matrix contacting between crack surfaces and some abrasive contact between broken fiber ends during thermal load cycles.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.319-323
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• 2007

Acoustic emission (AE) was originally developed for non-destructive testing of static structure, but over the year its application has been extended to health monitoring of rotating machines and bearings. It offers the advantage of earlier defect detection in comparison with monitoring bearing. This study was diagnosed low-speed machine which had a fault bearing for early detection by AE. And the artificial faults in a experimentation bearing was made for the bearing signals from difference speed and load were compared and analyzed by AE.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.5 s.176
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• pp.1084-1092
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• 2000

Responses of ultrasonic back scattered energy and AE (Acoustic Emission) characteristics related to the progressive damage of $[0/90-{2}]_s$ and $[0/90-{4}]_s$ crossply laminates were studied. It was found that the ultrasonic backscattered energy was sensitive to the matrix cracking but not sensitive to other failure mechanisms. However, AE was proved to be sensitive to matrix cracking as well as other failure mechanisms.AE signals were analyzed by investigating the amplitude and number of counts per event for corresponding applied strain. Loading and unloading tests were conducted separately. AE results showed Kaiser effect in the crossply composite laminates and ultrasonic results supported the AE results.

• Journal of the Korean Society of Safety
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• v.20 no.1 s.69
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• pp.49-54
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• 2005

Recently, many kinds of advanced composite materials have been used in various industry fields. Among them, fabric CFRP composites are being used as primary structural components in many applications because of their superior properties. However, the complexity of the fabric structure makes understanding of their failure behavior very difficult. The mechanical strength and crack propagation of plain woven carbon fiber fabric laminate composites are examined by acoustic emission(AE) method. AE signals are acquired during the tensile test and fracture tests. Thus, the relationship between AE signal and mechanical behavior curves and crack extension length are shown. Also the interlaminar fracture toughness in terms of AE characteristics are discussed in viewpoint of crack propagation behavior.

• Journal of the Korean Society of Safety
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• v.19 no.1
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• pp.31-37
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• 2004

The mechanical strength and crack propagation of plain woven carbon fiber fabric laminate composites are examined by acoustic emission(AE). AE signals are measured during the tensile test and fracture tests. Thus, the relationship between AE signal and load-displacement curves and crack extension length are shown. Also the fracture mechanisms in terms of AE characteristics are discussed in viewpoint of crack propagation behavior.

• Structural Monitoring and Maintenance
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• v.6 no.3
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• pp.173-190
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• 2019

Steel-confined reinforced concrete (SCRC) columns feature highly complex and invisible mechanisms that make damage evaluation and pattern recognition difficult. In the present article, the prevailing acoustic emission (AE) technique was applied to monitor and evaluate the damage process of steel-confined RC columns in a quasi-static test. AE energy-based indicators, such as index of damage and relax ratio, were proposed to trace the damage progress and quantitatively evaluate the damage state. The fuzzy C-means algorithm successfully discriminated the AE data of different patterns, validity analysis guaranteed cluster accuracy, and principal component analysis simplified the datasets. A detailed statistical investigation on typical AE features was conducted to relate the clustered AE signals to micro mechanisms and the observed damage patterns, and differences between steel-confined and unconfined RC columns were compared and illustrated.