• Proceedings of the Korean Geotechical Society Conference
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• 2009.09a
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• pp.815-826
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• 2009

The paper presents a case study addressing the design and construction aspects for DCM(Deep Cement Mixing) method employed as the foundation of a caisson type breakwater with heavy weight(10,700 ton/EA) and a high design wave height($H_{1/3}$=8.7m). The DCM was designed for the project(Ulsan New Port North Breakwater Phase 1) by optimizing the pattern of DCM columns with a combination of short and long columns (i.e., block type(upper 3m)+wall type(lower)) and considering overlapped section between columns as a critical section against shear force where the coefficient of effective width of treated column($\alpha$) was estimated with caution. It was shown that the value can be 0.9 under the condition with the overlapped width of 30cm. In addition to that, a field trial test was performed after improving conventional DCM equipment (e.g., mixing blades, cement paste supplying pipes, multi auger motor, etc.) to establish a standardized DCM construction cycle (withdrawal rate of mixing blades) which can provide the prescribed strength. The result of the field strength test for cored DCM specimens shows that the averaged strength is larger than the target strength and the distribution of the strength(with a defect rate of 7%) also satisfies with the quality control normal distribution curve which allows defect rate of 15.9%.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.363-366
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• 2001

The present process of grading leather quality by the rare eyes is not reliable. Because inconsistency of grading due to eyes strain for long time can cause incorrect result of grading. Therefore it is necessary to automate the process of grading quality of leather based on objective standard for it. In this paper, leather automatic classification system consists of the process obtaining the information of leather and the process grading the quality of leather from the information. Leather is graded by its information such as texture density, types and distribution of defects. This paper proposes the algorithm which sorts out leather information like texture density and defects from the gray-level images obtained by digital camera. The density information is sorted out by the distribution value of Fourier spectrum which comes out after original image is converted to the image in frequency domain. And the defect information is obtained by the statistics of pixels which is relevant to Window using searching Window after sort out boundary lines from preprocessed images. The information for entire leather is used as standard of grading leather quality, and the proposed algorithm is practically applied to machine vision system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.367-370
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• 2016

QFN(Quad Flat No-leads package) is one of the SMD(Surface Mount Device). Since there is no lead in QFN, there are many defects on solder. Therefore, we propose an efficient mechanism for QFN solder defect detection at this paper. For this, we employ Convolutional Neural Network(CNN) of the Machine Learning algorithm. QFN solder's color multi-layer images are used to train CNN. Since these images are 3-channel color images, they have a problem with applying to CNN. To solve this problem, we used each 1-channel grayscale image(Red, Blue, Green) that was separated from 3-channel color images. We were able to detect QFN solder defects by using this CNN. Later, further research is needed to detect other QFN.

• Journal of Sensor Science and Technology
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• v.5 no.3
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• pp.25-31
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• 1996

Steel wires are made by elongating hot billets. If the billets have internal or surface defects, the wire can be broken during elongation process. After testing surface defect, we are testing internal defect by ultrasonic transducers. POSCO is producing two kinds of billets, hot rolled billet and cast billet. Hot rolled one is denser than cast billet. Because of the low density and rough surface, ultrasonic testing is difficult for the cast billet. Size of the transducer was related with the size and density of the billet. A transducer having 21mm long, 8.5mm wide and 0.95mm thick piezoelectric ceramic plate was best for $160mm\;{\times}\;160mm$ cast billet. Center frequency of the transducer was 2.25MHz and the focus distance was 70mm.

• Journal of the Korean Society for Nondestructive Testing
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• v.22 no.1
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• pp.53-58
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• 2002

New nondestructive inspection (NDI) technique to detect the defect in metal was developed in which an electromagnetic field is induced in a metal by AC current flowing in the magnetic coil and the leak magnetic-flux disturbed by defects is measured using a tape-recorder head with air gap. This technique can be applied in evaluating the location and sizing of surface defects in components of the ferromagnetic body by means of the non-contacting measurement. In this paper, we have applied this technique to the evaluation of two-dimensional surface cracks in ferromagnetic metal, and also investigated the influence of the various frequencies and lift-off. Defects were detected with maximum values in the distribution of voltage and it was found that the maximum values tend to increase with the defect depth. Although the maximum values for defects are affected by the frequency and lift-off, the depth of small defects can be estimated from the linear relationship between the depth and voltage rate$(V_0/V_{ave})$.

• Journal of Periodontal and Implant Science
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• v.48 no.6
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• pp.383-394
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• 2018

Purpose: The purpose of this study was to evaluate the optimal diabetes duration for bone regeneration experiments in an alloxan monohydrate (ALX)-induced diabetic rabbit calvarial defect model by evaluating the association between diabetes duration and bone healing capacity. Methods: Twenty-four New Zealand white rabbits were used. Twenty-two rabbits were injected with 100 mg/kg of ALX to induce experimental diabetes. These rabbits were divided into 4 groups, including a control group and groups with diabetes durations of 1 week (group 1), 2 weeks (group 2), and 4 weeks (group 3). Calvarial defects were created at 1, 2, and 4 weeks after ALX injection and in the control rabbits. Cone-beam computed tomography (CBCT) scanning was performed on the day of surgery and at 2 and 4 weeks after surgery. The rabbits were sacrificed 4 weeks after surgery, followed by histological and immunofluorescence analysis. Results: The diabetic state of all diabetic rabbits was well-maintained throughout the experiment. Reconstructed 3-dimensional CBCT imaging showed more rapid and prominent bone regeneration in the control group than in the experimental groups. Histological staining showed notable bone regeneration in the control group, in contrast to scarce bone formation in the experimental groups. The appearance and immunoreactivity of receptor activator of nuclear factor-kappa B and osteoprotegerin did not show notable differences among the groups. Conclusion: ALX administration at 100 mg/kg successfully induced experimental diabetes in rabbits. The effect of diabetes on bone healing was evident when the interval between diabetes induction and the intervention was ${\geq}1$ week.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.316-319
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• 2014

People's interests in coffee are increasing with the expansion of coffee market. In this trend, people's taste becomes more luxurious and coffee bean's quality is considered to be very important. Currently, bean defects are mainly detected by experienced specialists. In this paper, a detection system of bean defects using machine learning is presented. This system concentrates on detecting two main defect types : bean's shape and insect damage. Convolutional Neural Networks are used for machine learning. The neural networks are comprised of two neural networks. The first neural network detects defects in the bean's shape, and the second one detects the bean's insect damage. The development of this system could be a starting point for automated coffee bean defects detection. Later, further research is needed to detect other bean defect types.

• Industry Promotion Research
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• v.7 no.4
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• pp.9-15
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• 2022

This study evaluated the automated system of the roll bending process, which is one of the difficult processes. In the past, 20 cartridges were produced per hour. but Automation changed it to a process that produces 50 pieces per hour. The average value of production was 57.6 pieces per hour, error of repeatability was 0.03 mm, average roll diameter error value was 0.49 mm, average alignment error value was 0.09 mm and average process lead time was 43.21 seconds. This paper presented specific evaluation methods such as productivity, repeatability, defect rate, alignment defect rate, and process lead time. It is thought that the contents performed in this study will be helpful in the verification of other automation systems in the future.

• Journal of Veterinary Clinics
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• v.40 no.2
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• pp.85-92
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• 2023

Fractures in the horse industry are challenging and a common cause of death in racehorses. To accelerate fracture healing, tissue engineering (TE) provides promising ways to regenerate bone tissues. This study aimed to evaluate the osteogenic effects of biphasic calcium phosphate collagen (BCPC) graft, bone morphogenetic protein 2 (BMP2), mesenchymal stem cell (MSC), and platelet-rich plasma (PRP) treatments in horses. Four thoroughbred horses were included in the study, and, in each horse, three cortical defects with a diameter of 5 mm and depth of 10 mm were formed in the third metacarpal bones (MC) and metatarsal bones (MT). The defects were randomly assigned to one of six treatment groups (saline, BCPC, BMP2, MSC, PRP, and control). Injections of saline, BMP2, PRP, or MSCs were made at 1, 3, and 5 weeks after defect surgery. Bone regeneration effects were assessed by radiography, quantitative computed tomography (QCT), micro-computed tomography (μCT), histopathological, and histomorphometric evaluation. The new bone ratio (%) in the histomorphometric evaluation was higher in the BMP2 group than in the control and saline groups. Radiographic and QCT values were significantly higher in the BCPC groups than in the other groups. QCT values of the BMP2 group were significantly higher than in the control and saline groups. The present study demonstrated that BCPC grafts were biologically safe and showed osteoconductivity in horses and the repeated injections of BMP2 without a carrier can be simple and promising TE factors for treating horses with bone fractures.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.5A
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• pp.421-431
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• 2009

This paper is the study on the verification of structural health monitoring (SHM) algorithm based on the ultrasonic guided wave. An active inspection system using Lamb wave (LW) for SHM was considered. The basic study about the application of this algorithm was performed for detecting the circular notch defect in steel plate. LW testing technique, pitch-catch method, was used for interpretation of circular notch defect with depth of 50% of plate thickness and 7 mm width. Damage characterization takes place by comparing $S_0$ mode sensor signals collected before and after the damage event. By subtracting the signals of both conditions from each other, a scatter signal is produced which can be used for damage localization. The continuous Gabor wavelet transform is used to attain the time between the arrivals of the scatter and sensor signals. A new practical damage monitoring algorithm, based on damage monitoring polygon and pitch-catch method, has been proposed and verified with good accuracy. The possible damage location can be estimated by the average on calculated location points and the damage extent by the standard deviation.