• Proceedings of the Korea Concrete Institute Conference
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• 2008.04a
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• pp.1009-1012
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• 2008

The fiber dispersion performance in fiber-reinforced cementitious composites is a crucial factor with respect to achieving desired mechanical performance. However, evaluation of the fiber dispersion performance in the composite PVA-ECC(Polyvinyl alcohol-Engineered Cementitious Composite) is extremely challenging because of the low contrast of PVA fibers with the cement-based matrix. In the present work, an enhanced fiber detection technique is developed and demonstrated. Using a fluorescence technique on the PVA-ECC, PVA fibers are observed as green dots in the cross-section of the composite. After capturing the fluorescence image with a Charged Couple Device(CCD) camera through a microscope. The fibers are more accurately detected by employing a series of process based on a categorization, watershed segmentation, and morphological reconstruction.

• Structural Monitoring and Maintenance
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• v.2 no.4
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• pp.319-338
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• 2015

The electro-mechanical impedance (EMI) technique makes use of surface-bonded lead zirconate titanate (PZT) patches as impedance transducers measuring impedance variations monitored on host structural components. The present experimental work further evaluate an alternative to the conventional EMI technique which performs measurements of the variations in the output voltage of PZT transducers rather than computing electromechanical impedance (or admittance) itself. This paper further evaluates a variant of the EMI approach presented in a previous work of the present authors, suitable, for low-cost concrete structures monitoring applications making use of a credit card-sized Raspberry Pi single board computer as core hardware unit. This monitoring approach is also deployed by introducing a new damage identification index based on the ratio between the area of the 2-D error ellipse of specific probability of EMI-based measurements containment over that of the 2-D error circle of equivalent probability. Experimental results of damages occurring in concrete cubic and beam specimens are investigated under increasing loading conditions. Results illustrate that the proposed technique is an efficient approach for identification and early detection of damage in concrete structures.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.52 no.12
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• pp.562-567
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• 2003

Lightning arresters are deteriorated by repetition of protective operation against overvoltages or impulse currents in environments of its use. If a deteriorated arrester is left in power lines, it can lead to an accident such as a line to ground fault even in a normal system. Therefore, it is necessary to eliminate the deteriorated arrester in advance by checking the soundness of arresters on a regular basis, and to ensure the reliability of power systems by preventing accidents. Various deterioration diagnostic techniques and devices are suggested, and most of which measure leakage current components as an indicator of arrester ageing. However, the techniques based on the magnitude of leakage current measure simply RMS or peak value of leakage current components and do not provide detailed information needed in the diagnosis. In this study, we found that the wave height distributions of the total leakage currents are remarkably changed or a new wave height are produced with the progress of arrester deterioration. To propose a new technique for the diagnosis, we designed a leakage current detection unit and an analysis program which can measure leakage current magnitudes and analyze wave height distributions. From the experimental results, we confirmed that the proposed technique by analyzing the wave height distribution can simply diagnose the mode of defects such as a partial damage and an existence of punctures in arresters as well as deterioration of arresters.

• Journal of Korean Society of Environmental Engineers
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• v.31 no.1
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• pp.64-69
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• 2009

Musty and earth odors caused by geosmin and 2-MIB are the major complaints from the drinking water consumers. Therefore, early detection of geosmin and 2-MIB is the key to prevent off-flavor occurrence. In this study, a rapid method using stir bar sorptive extraction (SBSE) in combination with the GC/MS was investigated to analyze geosmin and 2-MIB in water. The SBSE method, a solventless extraction technique, was optimized and then applied to the analysis of geosmin and 2-MIB in water. The SBSE technique was found to be a simple and fast procedure that allows many samples to be extracted simultaneously using very small volume (10~20 mL). In addition, the SBSE method offered high recovery and good linear regression coefficient for the geosmin and 2-MIB. The good repeatability of this method can be deduced from the low RSD (7.2~7.6%) at 10 ng/L for geosmin and 2-MIB. The limit of detection was determined 1~2 ng/L and the limit of quantitation was 3~6 ng/L. Above all, the SBSE method proved to be a very practical technique for the analysis of geosmin and 2-MIB in water.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.2
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• pp.202-207
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• 2021

One of the most important tasks in image processing is noise filtering. Noise removal in image is a difficult task due to many reasons such as nonstationary sequences and corrupted by various types of noise. Human's visual perception is heavily based on the edge information. Thus, noise filtering must preserve edges. To remove the noise, we usually use the square-shaped median filter. They possess mathematical simplicity but have the disadvantages that blur the edges. In this paper we consider a new technique for image restoration using a weighted octagonal median filter. The technique consists of simple hypothesis test for edge detection, and we use the weighted octagonal-shaped moving window. The new technique is applied to noise corrupted image and experimental results are compared to the results of the square-shaped median filter and the cross-shaped median filter.

• International Journal of Computer Science & Network Security
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• v.23 no.12
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• pp.151-160
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• 2023

Breast cancer is the most dangerous and deadly form of cancer. Initial detection of breast cancer can significantly improve treatment effectiveness. The second most common cancer among Indian women in rural areas. Early detection of symptoms and signs is the most important technique to effectively treat breast cancer, as it enhances the odds of receiving an earlier, more specialist care. As a result, it has the possible to significantly improve survival odds by delaying or entirely eliminating cancer. Mammography is a high-resolution radiography technique that is an important factor in avoiding and diagnosing cancer at an early stage. Automatic segmentation of the breast part using Mammography pictures can help reduce the area available for cancer search while also saving time and effort compared to manual segmentation. Autoencoder-like convolutional and deconvolutional neural networks (CN-DCNN) were utilised in previous studies to automatically segment the breast area in Mammography pictures. We present Automatic SegmenAN, a unique end-to-end adversarial neural network for the job of medical image segmentation, in this paper. Because image segmentation necessitates extensive, pixel-level labelling, a standard GAN's discriminator's single scalar real/fake output may be inefficient in providing steady and appropriate gradient feedback to the networks. Instead of utilising a fully convolutional neural network as the segmentor, we suggested a new adversarial critic network with a multi-scale L1 loss function to force the critic and segmentor to learn both global and local attributes that collect long- and short-range spatial relations among pixels. We demonstrate that an Automatic SegmenAN perspective is more up to date and reliable for segmentation tasks than the state-of-the-art U-net segmentation technique.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.265-271
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• 2018

This paper presents a method for detecting damage to a structure at low cost using its impedance. The impedance technique is a typical method to detect local damage for structural health monitoring. This is a common technique for estimating damage by monitoring the electro-mechanical admittance signal of the structure. To apply this technique, an expensive impedance analyzer is generally used. On the other hand, it is necessary to develop a low-cost variant to effectively disseminate the technique. In this study, a method based on the transfer impedance using a function generator and digital multimeter, which are generally used in the laboratory instead of an impedance analyzer, was developed. That is, this technique estimates the damage by comparing the damage index using the amplitude ratio of the output voltage measured in the healthy and damaged state. A transfer impedance test was carried out on a steel specimen. By comparing the damage index, the presence of damage could be assessed reasonably. This study is a basic investigation of an impedance-based low-cost damage detection method that can be used effectively for structural health monitoring if supplemented with future research to estimate the damage location and severity.

• Journal of the Korean Society for Nondestructive Testing
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• v.36 no.1
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• pp.53-59
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• 2016

Ultrasonic nonlinear evaluation is generally utilized for detection of not only defects but also microdamage such as corrosion and plastic deformation. Nonlinearity is determined by the amplitude ratio of primary wave second harmonic wave, and the results of its comparison are used for evaluation. Owing to the experimental features, the experimental nonlinearity result contains system nonlinearity and material nonlinearity. System nonlinearity is that which is unwanted by the user; hence, it acts as an error and interrupts analysis. In this study, a bulk wave mixing technique is implemented in order to minimize the system nonlinearity and obtain the reliable analysis results. The biggest advantage of this technique is that experimental nonlinearity contains less system nonlinearity than that for the conventional nonlinear ultrasonic technique. Theoretical and experimental verifications are performed in this study. By comparing the results of the bulk wave mixing technique with those of the conventional technique, the strengths, weaknesses, and application validity of the bulk wave mixing technique are determined.

• Investigative and Clinical Urology
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• v.59 no.6
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• pp.363-370
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• 2018

Purpose: The aim of this study is to describe the technique and to report early results of transperineal magnetic resonance imaging and ultrasonography (MRI-US) fusion biopsy. Materials and Methods: A total of 75 patients underwent MRI-US fusion transperineal biopsy. Targeted biopsy via MRI-US fusion imaging was carried out for cancer-suspicious lesions with additional systematic biopsy. Detection rates for overall and clinically significant prostate cancer (csPCa) were evaluated and compared between systematic and targeted biopsy. In addition, further investigation into the detection rate according to prostate imaging reporting and data system (PI-RADS) score was done. Results of repeat biopsies were also evaluated. Results: Overall cancer detection rate was 61.3% (46 patients) and the detection rate for csPCa was 42.7% (32 patients). Overall detection rates for systematic and targeted biopsy were 41.3% and 57.3% (p<0.05), respectively. Detection rates for csPCa were 26.7% and 41.3%, respectively (p<0.05). The cancer detection rates via MRI fusion target biopsy were 30.8% in PI-RADS 3, 62.1% in PI-RADS 4 and 89.4% in PI-RADS 5. Rates of csPCa missed by targeted biopsy and systematic biopsy were 0.0% and 25.0%, respectively. The cancer detection rate in repeat biopsies was 61.1% (11 among 18 patients) in which 55.5% of cancer suspected lesions were located in the anterior portion. Conclusions: Transperineal MRI-US fusion biopsy is useful for improving overall cancer detection rate and especially detection of csPCa. Transperineal MRI-US targeted biopsy show potential benefits to improve cancer detection rate in patients with high PIRADS score, tumor located at the anterior portion and in repeat biopsies.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.2
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• pp.29-38
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• 2012

The data quality and measurements along consecutive detector stations can vary much even in the same traffic conditions due to variety in detector types, calibration and maintenance effort, field operation periods, minor geometric changes of roads and so on. These faulty situations often create 10% or more of inherent difference in important traffic measurements between two stations even under stable low flow condition. Low detection rates(DR) and high false alarm rates(FAR) therefore sets in among many popular Automatic Incident Detection Algorithms(AIDA). This research is two-folded and aims mainly to develop a new AIDA for uninterrupted flow. For this purpose, a technique which utilizes a Simple Arithmetic Operation(SAO) of traffic variables is introduced. This SAO technique is designed to address the inherent discrepancy of detector data observed successive stations, and to overcome the degradation of AIDA performance. It was found that this new algorithm improves DR as much as 95 percent and above. And mean time to detection(MTTD) is found to be 1 minutes or less. When it comes to FAR, this new approach compared to existing AIDAs reduces FAR up to 31.0 percent. And capability in persistency check of on-going incidents was found excellent as well.