• Journal of the Korean Society for Nondestructive Testing
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• v.26 no.2
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• pp.69-76
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• 2006

TRISO(tri-isotropic)-coated fuel particle technology is utilized owing to its higher stability at a high temperature and Its efficient retention capability for fission products In the HTGR(high temperature gas-reeled reactor). The typical spherical TRISO fuel panicle with a diameter of about 1mm is composed of a nuclear fuel kernel and outer coating layers. The outer coating layers consist of a buffer PyC(pyrolytic carbon) layer, Inner PyC(1-PyC) layer, SiC layer, and outer PyC(O-PyC) layer Most of the Inspection Items for the TRTSO-coated fuel particle depend on destructive methods. The coating thickness of the TRISO fuel particle can be nondestructively measured by the X-ray radiography without generating radioactive wastel. In this study, the coaling thickness for the simulated TRISO-coated fuel particle with $ZrO_2$ kernel Instead of $%UO_2$ kernel was measured by using micro-focus X-ray radiography with micro-focus X-ray generator and flat panel detector The radiographic image was also enhanced by image processing technique to acquire clear boundary lines between coating layers. The coaling thickness wat effectively measured by applying the micro-focus X-ray radiography The inspection process for the TRISO-coated fuel particles will be improved by the developed micro-focus X-ray radiography and digital image processing technology.

• Journal of Digital Convergence
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• v.12 no.11
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• pp.437-449
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• 2014

In this study, we analyzed an effect of area-environmental factor on breast cancer screening rates using multi-level analysis. It was intended for the KNHANES-IV. Total subjects were 14338. Among them, 4143 subjects met the inclusion criteria. When we applied only empty Model, a variance of breast cancer screening rates was 0.061 in each region. When we applied Model with individual level variables, the variance was 0.034. However, when we applied both Model with individual level variables and Model with area level variables, the variance was 0.023. We drew applied only individual level variables parallel applied 3 regional variances which could explain variance of inspection of breast cancer up to 18.04% compared with applied only individual level variables. Area level variables could reduce a variance of region. This means besides individual level variables. The group can share a same thing and can effect to breast cancer screening rates. We need to discover factors which area level variables and suggest that make a standard for inspection of breast cancer.

• Journal of the Institute of Convergence Signal Processing
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• v.18 no.1
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• pp.13-20
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• 2017

In this paper, we evaluate the basic test results of the 32 Gbps observational equipment introduced as the back-end system for the wideband VLBI (Very Long Baseline Interferometry) observation of KVN (Korean VLBI Network). Radio astronomers want to make a large radio telescope that has excellent performance in order to observe the superfine structure of a celestial body, but a lot of money is needed. Therefore, in order to increase the sensitivity, the performance improvement of the receiving system and the method of observing the wide frequency bandwidth are introduced. To do this, we adopted a wideband sampling method for converting analog signals to digital with ultra-fast speeds and a wideband sampler for performing digital filtering in order to observe a wide observational frequency bandwidth. The wideband sampler (OCTAD-K) supports up to 16 Gsps-2bits sampling and supports a variety of observational bandwidth using digital filtering techniques. In particular, it is designed to support KVN's 4-frequency simultaneous observation system and VERA(VLBI Exploration of Radio Astrometry)'s 2-beam observation system. It can also support polKVN(Korean VLBI Network), KaVA(KVN and VERA Array), 32Gbps Direct Sampler, Digital Filter, Widebandarization observations and supports the standard VDIF(VLBI Data Interchange Format) format of observed data. In this paper, the performance of the system and the problem solving are described in detail after performing the factory inspection and field test before the system is introduced.

• Journal of the Korean Society for Nondestructive Testing
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• v.36 no.3
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• pp.195-201
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• 2016

Eddy current testing (ECT) is commonly applied for the inspection of automated production lines of metallic products, because it has a high inspection speed and a reasonable price. When ECT is applied for the inspection of a metallic object having an uneven target surface, such as the spline gear of a spline shaft, it is difficult to distinguish between the original signal obtained from the sensor and the signal generated by a defect because of the relatively large surface signals having similar frequency distributions. To facilitate the detection of defect signals from the spline gear, implementation of high-order filters is essential, so that the fault signals can be distinguished from the surrounding noise signals, and simultaneously, the pass-band of the filter can be adjusted according to the status of each production line and the object to be inspected. We will examine the infinite impulse filters (IIR filters) available for implementing an advanced filter for ECT, and attempt to detect the flaw signals through optimization of system design parameters for detecting the signals at the system level.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.2
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• pp.1-8
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• 2024

The expansion joint is installed to offset the expansion of the superstructure and must ensure sufficient gap during its service life. In detailed guideline of safety inspection and precise safety diagnosis for bridge, damage due to lack or excessive gap is specified, but there are insufficient standards for determining the abnormal behavior of superstructures. In this study, a data-based maintenance was proposed by continuously monitoring the expansion-gap data of the same expansion joint. A total of 2,756 data were collected from 689 expansion joint, taking into account the effects of season. We have developed a method to evaluate changes in the expansion joint-gap that can analyze the thermal movement through four or more data at the same location, and classified the factors that affect the superstructure behavior and analyze the influence of each factor through deep learning and explainable artificial intelligence(AI). Abnormal behavior of the superstructure was classified into narrowing and functional failure through the expansion joint-gap evaluation graph. The influence factor analysis using deep learning and explainable AI is considered to be reliable because the results can be explained by the existing expansion gap calculation formula and bridge design.

• Journal of Digital Convergence
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• v.12 no.8
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• pp.113-127
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• 2014

The use of mobile devices offers a variety of services to the individuals and companies. On the other hand, security threats and new mobile security threats that exist in IT infrastructure to build the environment for mobile services are present at the same time. Services such as mobile and vaccine management services, such as MDM (Mobile Device Management) has attracted a great deal of interest in order to minimize the threat of security in mobile environment. These solutions can not protect an application that was developed for the mobile service from the threat of vulnerability of mobile application itself. Under these circumstances, in this paper, we proposed mobile application security checklists based on application security review items in order to prevent security accidents that can occur in a mobile service environment. We collected and analyzed Android applications, we performed a total inspection of the applications for verification of the effectiveness of the check items. And we checked that the check items through a survey of experts suitability was verified.

• Journal of Digital Convergence
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• v.10 no.6
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• pp.71-82
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• 2012

The interest in SLA in accordance with the development of IT outsourcing has increased due to the rapid development of information systems. Moreover, an awareness and necessity for the Information System Operating Audit has increased while an effective IT service management operations for information systems is needed desperately. However, information system operations and maintenance instructions of the National Information Society Agency operates due to the current information system operation, but the experience and the interpretation of the auditor determine the decision in the field. This paper introduces an operating audit model for the efficient management. This model is derived from the Korea Information Society Agency's operating instructions of the Information Systems Audit and their inspection services. The audit checklists were derived from the areas of service planning, service delivery, service support, and service management. Consequently, the operating audit model was proposed, and the suitability of this model was verified by experts' opinions on the survey.

• The Korean Journal of Physiology and Pharmacology
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• v.24 no.1
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• pp.89-99
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• 2020

Although microscopic analysis of tissue slides has been the basis for disease diagnosis for decades, intra- and inter-observer variabilities remain issues to be resolved. The recent introduction of digital scanners has allowed for using deep learning in the analysis of tissue images because many whole slide images (WSIs) are accessible to researchers. In the present study, we investigated the possibility of a deep learning-based, fully automated, computer-aided diagnosis system with WSIs from a stomach adenocarcinoma dataset. Three different convolutional neural network architectures were tested to determine the better architecture for tissue classifier. Each network was trained to classify small tissue patches into normal or tumor. Based on the patch-level classification, tumor probability heatmaps can be overlaid on tissue images. We observed three different tissue patterns, including clear normal, clear tumor and ambiguous cases. We suggest that longer inspection time can be assigned to ambiguous cases compared to clear normal cases, increasing the accuracy and efficiency of histopathologic diagnosis by pre-evaluating the status of the WSIs. When the classifier was tested with completely different WSI dataset, the performance was not optimal because of the different tissue preparation quality. By including a small amount of data from the new dataset for training, the performance for the new dataset was much enhanced. These results indicated that WSI dataset should include tissues prepared from many different preparation conditions to construct a generalized tissue classifier. Thus, multi-national/multi-center dataset should be built for the application of deep learning in the real world medical practice.

• Journal of Digital Convergence
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• v.13 no.12
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• pp.285-290
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• 2015

The purpose of this study is to compare the status of eyesight according to the change of astigmatism axis in myopic astigmatism and to minimize errors in making astigmatic glasses based on accurate optometry and prescription. The subjects were 93 males and females(186 eyes) who have myopic astigmatism without any ocular disease or systemic disease. We performed comparative analysis on the status of visual acuity according to the change of astigmatism axis to 5, 10 and 15 degree in corrected eyesight 1.0. The direct astigmatism was the most common astigmatism type among the 186 eyes. After all subjects were perfectly corrected into 1.0, the change of astigmatism axis affected eyesight; The results suggested that the more change was made in astigmatism axis, the worse their eyesight would become. The main astigmatism type was changed from direct astigmatism to inverse astigmatism as age increased. The change of the astigmatism axis resulted in failing of corrected eyesight. Therefore, the convergence of examination and correction for astigmatism strength and axis is necessary when conducting refraction inspection for astigmatism.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.2
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• pp.159-164
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• 2013

It is well known that a single moving camera video is capable of extracting the 3-dimensional position of an object. With this in mind, current research performed image-based monitoring to establish a floating structure model using a camcorder system. Following this, the present study extracted frame images from digital camcorder video clips and matched the interest points to obtain relative 3D coordinates for both regular and irregular wave conditions. Then, the researchers evaluated the transformation accuracy of the modified SURF-based matching and image-based displacement estimation of the floating structure model in regular wave condition. For the regular wave condition, the wave generator's setting value was 3.0 sec and the cycle of the image-based displacement result was 2.993 sec. Taking into account mechanical error, these values can be considered as very similar. In terms of visual inspection, the researchers observed the shape of a regular wave in the 3-dimensional and 1-dimensional figures through the projection on X Y Z axis. In conclusion, it was possible to calculate the displacement of a floating structure module in near real-time using an average digital camcorder with 30fps video.