• Journal of Korea Society of Industrial Information Systems
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• v.12 no.3
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• pp.116-123
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• 2007

Despite the number of backlight manufacturer is increased as the market of flat panel display equipments and related development devices is enlarged, the inspection based on the human eye is still used in many backlight production lines. The defects such as particle, spot and scratch on the light emitting surface of the backlight prevent the LCD device from displaying the colors correctly. From that manual inspection it is difficult to maintain the quality of backlight consistently because the accuracy and the speed of the inspection may change with the physical condition of the operater. In this paper we studied on the development of automatic backlight surface defect inspection system. For this, we made up of the computer vision system and we developed the main program with various user interfaces to operate the inspection system effectively. And we developed the image processing module to extract the defect information. Furthermore, we presented the labeling process to reconstruct defect regions using the labeling table and the defect index. From the experimental results, we found that our system can detect all defect regions identified from human eye and it is sufficient to substitute for the conventional surface inspection.

• Korean Journal of Remote Sensing
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• v.35 no.2
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• pp.229-239
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• 2019

All vegetation colonies have layered structure. This layer is called 'forest vertical structure.' Nowadays it is considered as an important indicator to estimate forest's vital condition, diversity and environmental effect of forest. So forest vertical structure should be surveyed. However, vertical structure is a kind of inner structure, so forest surveys are generally conducted through field surveys, a traditional forest inventory method which costs plenty of time and budget. Therefore, in this study, we propose a useful method to classify the vertical structure of forests using remote sensing aerial photographs and machine learning capable of mass data mining in order to reduce time and budget for forest vertical structure investigation. We classified it as SVM (Support Vector Machine) using RGB airborne photos and LiDAR (Light Detection and Ranging) DSM (Digital Surface Model) DTM (Digital Terrain Model). Accuracy based on pixel count is 66.22% when compared to field survey results. It is concluded that classification accuracy of layer classification is relatively high for single-layer and multi-layer classification, but it was concluded that it is difficult in multi-layer classification. The results of this study are expected to further develop the field of machine learning research on vegetation structure by collecting various vegetation data and image data in the future.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.20 no.3
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• pp.93-104
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• 2010

The advent of various mobile devices and mobile services has caused diversification of information stored in a mobile device, e.g., SMS, photos, movies, addresses, e-mails, digital certificates, and so on. Because mobile devices are lost or stolen easily, user authentication is critical to protect the information stored in mobile devices. However, the current user authentication methods using Personal Identification Numbers (PINs) and passwords are vulnerable to Shoulder Surfing Attacks (SSAs), which enables an attacker to obtain user's information. Although there are already several SSA-resistant authentication methods in the literature, most of these methods lack of usability. Moreover, they are not suitable for use in mobile devices. In this paper, we propose a user friendly password input method for mobile devices which is secure against SSA. We also perform user tests and compare the security and usability of the proposed method with those of the existing password input methods.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.212-220
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• 2013

Recently, there has been tremendous increase in human-computer/machine interaction system, where the goal is to provide with an appropriate service to the user at the right time with minimal human inputs for human augmented cognition system. To develop an efficient human augmented cognition system based on human computer/machine interaction, it is important to interpret the user's implicit intention, which is vague, in addition to the explicit intention. According to cognitive visual-motor theory, human eye movements and pupillary responses are rich sources of information about human intention and behavior. In this paper, we propose a novel approach for the identification of human implicit visual search intention based on eye movement pattern and pupillary analysis such as pupil size, gradient of pupil size variation, fixation length/count for the area of interest. The proposed model identifies the human's implicit intention into three types such as navigational intent generation, informational intent generation, and informational intent disappearance. Navigational intent refers to the search to find something interesting in an input scene with no specific instructions, while informational intent refers to the search to find a particular target object at a specific location in the input scene. In the present study, based on the human eye movement pattern and pupillary analysis, we used a hierarchical support vector machine which can detect the transitions between the different implicit intents - navigational intent generation to informational intent generation and informational intent disappearance.

• Journal of the Korean Society of Radiology
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• v.17 no.6
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• pp.977-983
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• 2023

Due to the development of the domestic economy and science, the people's standard of living has increased. Accordingly, we want to improve the quality of life. In other words, we guarantee human rights and pursue dignity and value as human beings. Therefore, the medical field extends human life and helps maintain a healthy life. The social medicine that protects human rights is forensic medicine. Forensic medicine identifies deaths and analyzes the cause using forensic radiology images. Forensic radiology is the acquisition and provision of medical images by the radiographer. Therefore, the radiographer must have expertise by completing forensic science-related courses. Recently, medical and nursing schools have opened and operated various subjects such as forensic medicine and forensic nursing. However, the Department of Radiology science is the only school that offers courses related to forensic science. For the future development and exploration of the radiographer and department of radiology science, forensic education should be considered. For this purpose, we investigated the necessity and demand for forensic education in the department of radiology science undergraduate and graduate schools. The department of radiology science students' awareness of forensic science was found to be 2.977 points, but the need for forensic science education for the radiographer was high at 3.759 points. In addition, current students' demand for forensic science courses was high at 84.1%, with the majority responding that it was necessary to open and operate the course. This study was able to determine the demand for forensic science-related subjects among the department of radiology science undergraduate and graduate students, and there is a need to explore diversity and expertise in education. We hope that it will be used as basic data for the development of forensic medicine and radiology science.

• Journal of the Korean Society of Radiology
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• v.18 no.3
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• pp.187-201
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• 2024

Osteoporosis is a major health issue globally, often remaining undetected until a fracture occurs. To facilitate early detection, deep learning (DL) models were developed to classify osteoporosis using abdominal computed tomography (CT) scans. This study was conducted using retrospectively collected data from 3,012 contrast-enhanced abdominal CT scans. The DL models developed in this study were constructed for using image data, demographic/clinical information, and multi-modality data, respectively. Patients were categorized into the normal, osteopenia, and osteoporosis groups based on their T-scores, obtained from dual-energy X-ray absorptiometry, into normal, osteopenia, and osteoporosis groups. The models showed high accuracy and effectiveness, with the combined data model performing the best, achieving an area under the receiver operating characteristic curve of 0.94 and an accuracy of 0.80. The image-based model also performed well, while the demographic data model had lower accuracy and effectiveness. In addition, the DL model was interpreted by gradient-weighted class activation mapping (Grad-CAM) to highlight clinically relevant features in the images, revealing the femoral neck as a common site for fractures. The study shows that DL can accurately identify osteoporosis stages from clinical data, indicating the potential of abdominal CT scans in early osteoporosis detection and reducing fracture risks with prompt treatment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.5
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• pp.557-564
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• 2017

The purpose of the thermal imaging observation device mounted on the K's tank in the Republic of Korea military is to convert infrared rays into visual information to provide information about the environment under conditions of restricted visibility. Among the various performance indicators of thermal observation devices, such as the view, magnification, resolution, MTF, NETD, and Minimum Resolvable Temperature Difference (MRTD), the MRTD is the most important, because it can indicate both the spatial frequency and temperature resolvable. However, the standard method of measuring the MRTD in NATO contains many subjective factors. As the measurement result can vary depending on subjective factors such as the human eye, metal condition and measurement conditions, the MRTD obtained is not stable. In this study, these qualitative MRTD measurement systems are converted into quantitative indicators based on a gray scale using imaging processing. By converting the average of the gray scale differences of the black and white images into the MRTD, the mean values can be used to determine whether the performance requirements required by the defense specification are met. The (mean) value can also be used to discriminate between detection, recognition and identification and the detectable distance of the thermal equipment can be analyzed under various environmental conditions, such as altostratus, heavy rain and fog.

• Convergence Security Journal
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• v.11 no.5
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• pp.99-108
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• 2011

The purpose of this study is to profile actual conditions of personal information protection systems operated in overseas countries and examine major considerations of personal information that security service providers must know in the capacity of privacy information processor, so that it may contribute to preventing potential occurrence of any legal disputes in advance. Particularly, this study further seeks to describe fundamental idea and principle of said Personal Information Protection Act; enhancement of various safety measures (e.g. collection / use of privacy data, processing of sensitive information / personal ID information, and encryption of privacy information); restrictions on installation / operation of video data processing devices; and penal regulations as a means of countermeasure against leakage of personal information, while proposing possible solutions to cope with these matters. Using cases among foreign countries for this study. Possible solutions proposed by this study can be summed up as follows: By changing minds with sufficient legal reviews, it is required for security service providers to 1) clearly and further specify any purposes of collecting and using privacy information, if possible, 2) obtain any privacy information by legitimate means as it is necessary to collect such information, 3) stop providing any personal information for the 3rd parties or for any other purposes except fundamental purposes of using privacy information, and 4) have full knowledge about duty of safety measure in accordance with safe maintenance of privacy information and protect any personal information from unwanted or intentional leakage to others.