• Composites Research
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• v.13 no.1
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• pp.89-97
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• 2000

Fatigue damage detection and vibration sensing for a laminated composites and impact location detection for a steel beam have been carried out using optical fiber sensor. Intensity based optical fiber sensor is constructed by placing two cleaved fiber end in a hollow glass tube, and multiple reflection within the cavity is considered. Fatigue signals are measured by embedded optical fiber, surface mounted optical fiber sensor and strain gage simultaneously. For vibration sensing, optical fiber sensor is mounted on the carbon fiber composite beam and its response to free vibration and forced vibration is investigated. In impact location detection, two optical fiber sensors are used and the information obtained from two sensors is arrival time delay of vibration caused by impact. Impact location can be calculated from this time delay. The obtained results show that the intensity based optical fiber sensor provide reliable data during long-term fatigue loading, unlike strain gage which deteriorate during the early part of the fatigue test. Optical fiber sensor signals coincide with gap sensor in vibration sensing. The precise locations of impact can be detected within 4.1% error limit.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.1
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• pp.51-57
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• 2013

Leak detection, the system is controlled by humanity's precious water resources, prepare for natural disasters and prevent damage to buildings and various industrial facilities. Especially because it causes serious environmental pollution, chemicals or oil spills, leak detection of various liquid(oil, water), the point at which the liquid leak is detected early on, and minimize environmental pollution, prevent damage of the equipment due to the leak, and the country's precious water resources to be used safely. In this paper, we solve these problems by using specialized film sensor, any person who is not a skilled technician, equipment or walls anywhere can be easily installed. also reduce unnecessary circuit, If film sensor is connected to operate, have a big competitive price, the detection of liquid and the surrounding environment according to, the sensor film that can set the sensitivity control, and monitoring system was implemented.

• ETRI Journal
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• v.45 no.6
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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.

• Spatial Information Research
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• v.19 no.5
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• pp.1-11
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• 2011

This study mainly focused on the method of accurately extracting damage information in the im agery change detection process using the constructed high resolution aerial im agery. Bongwha-gun in Gyungsangbuk-do which had been severely damaged from a localized torrential downpour at the end of July, 2008 was selected as study area. This study utilized aerial im agery having photographing scale of 30cm gray image of pre-disaster and 40cm color image of post-disaster. In order to correct errors from the differences of the image resolution of pre-/post-disaster and time series, the prelim inary phase of image processing techniques such as normalizing, contrast enhancement and equalizing were applied to reduce errors. The extent of the damage was calculated using one to one comparison of the intensity of each pixel of pre-/post-disaster im aged. In this step, threshold values which facilitate to extract the extent that damage investigator wants were applied by setting difference values of the intensity of pixel of pre-/post-disaster. The accuracy of optimal image processing and the result of threshold values were verified using the error matrix. The results of the study enabled the early exaction of the extents of the damages using the aerial imagery with identical characteristics. It was also possible to apply to various damage items for imagery change detection in case of utilizing multi-band im agery. Furthermore, more quantitative estimation of the dam ages would be possible with the use of numerous GIS layers such as land cover and cadastral maps.

• The Transactions of the Korean Institute of Power Electronics
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• v.24 no.5
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• pp.356-364
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• 2019

In this study, major problems, such as licensing problems due to civil complaints, deterioration of facility period, and damage of modules, are exposed to many problems in domestic businesses. Particularly, the photovoltaic (PV) modules applied to early PV systems have been repaired and replaced over the past two decades, and a new module-based aging detection method is needed to expand the maintenance market and stabilize and repair power supplies. PV modules in a PV system use a string that is configured in series to generate high voltage. However, even if only one module of the solar modules connected in series ages, the power generation efficiency of the aged string is reduced. Therefore, we propose a topology that can measure the instantaneous PV characteristic curve to determine the aging module in the solar string and the aging judgment algorithm using the measured PV characteristic curve.

• Smart Media Journal
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• v.13 no.6
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• pp.90-97
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• 2024

This paper focuses on detecting Alzheimer's Disease (AD). The most usual form of dementia is Alzheimer's disease, which causes permanent cause memory cell damage. Alzheimer's disease, a neurodegenerative disease, increases slowly over time. For this matter, early detection of Alzheimer's disease is important. The purpose of this work is using Magnetic Resonance Imaging (MRI) to diagnose AD. A Convolution Neural Network (CNN) model, Reset, and VGG the pre-trained learning models are used. Performing analysis and validation of layers affects the effectiveness of the model. T1-weighted MRI images are taken for preprocessing from ADNI. The Dataset images are taken from the Alzheimer's Disease Neuroimaging Initiative (ADNI). 3D MRI scans into 2D image slices shows the optimization method in the training process while achieving 96% and 94% accuracy in VGG 16 and ResNet 18 respectively. This study aims to classify AD from brain 3D MRI images and obtain better results.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.1401-1409
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• 2007

This paper presents a detecting technique for the improvement in quality by appling the various vibrational characteristics theory. The object of this study is to objectively point out faulty gear by developing the program which can be used to analyze and predict the vibrational characteristics caused by gear wear, deformation and nick of auto-transmission. The fault detection methods by vibrational signal analysis of gear have been progressed in the various fields of industry. These methods have the advantage of being easy to attach the accelerometer without discontinuance of the structure. But not all the methods are efficient for finding early faults. So in the thesis, we completed development of the inspection system of vibration by appling the most efficient detecting methods and verified the system's reliability through experiments.

• Fisheries and Aquatic Sciences
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• v.16 no.4
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• pp.273-277
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• 2013

Vibriosis caused by Vibrio anguillarum and edwardsiellosis caused by Edwardsiella tarda are septicemic diseases of many commercially important freshwater and marine fishes, and threaten the aquaculture industry in Korea. Early diagnosis and accurate identification of these two bacterial species could help to prevent these diseases and minimize the damage to cultured marine species. This study designed a duplex polymerase chain reaction (PCR) method for the simultaneous detection of two major fish pathogens: V. anguillarum and E. tarda. Each pair of oligonucleotide primers exclusively amplified the target groEL gene of the specific microorganism. Twenty-two Vibrio and ten non-Vibrio enteric species were used to check the specificity of the primers, which were found to be highly specific for the target species, even among closely related species. The detection limit was 400 pg for V. anguillarum and 4 ng for E. tarda when mixed purified DNA was used as the template. This assay showed high specificity and sensitivity in the simultaneous detection of V. anguillarum and E. tarda from artificially inoculated seawater and fish.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.1
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• pp.47-56
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• 2008

This paper presents a detecting technique for the improvement in quality by appling the various vibrational characteristics theory. The object of this study is to objectively point out faulty gear by developing the program which can be used to analyze and predict the vibrational characteristics caused by gear wear, deformation and nick of auto-transmission. The fault detection methods by vibrational signal analysis of gear have been progressed in the various fields of industry. These methods have the advantage of being easy to attach the accelerometer without discontinuance of the structure. But not all the methods are efficient for finding early faults. So in the thesis, we completed development of the inspection system of vibration by appling the most efficient detecting methods and verified the system's reliability through experiments.

• Journal of the Korean institute of surface engineering
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• v.55 no.6
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• pp.398-402
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• 2022

Vacuum Insulation Panel (VIP) is an high energy efficient insulation system that facilitate slim but high insulation performance, based on based on a porous core material evacuated and encapsulated in a multi-barrier envelope. Although VIP has been on the market for decades now, it wasn't until recently that efforts have been initiated to propose a standard on aging testing. One of the issues regarding VIP is its durability and aging due to pressure and moisture dependent increase of the initial low thermal conductivity with time. It is hard to visually determine at an early stage. Recently, a method of analyzing the damage on the a material surface by applying image processing technology has been widely used. These techniques provide fast and accurate data with a non-destructive way. In this study, the surface VIP images were analyzed using the Harris corner detection algorithm. As a result, 171,333 corner points in the normal packaging were detected, whereas 32,895 of the defective packaging, which were less than the normal packaging. were detected. These results are considered to provide meaningful information for the determination of VIP condition.