• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.41-43
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• 2022

In order to prevent and block infectious diseases caused by the recent COVID-19 pandemic, non-contact biometric information acquisition and analysis technology is attracting attention. The invasive and attached biometric information acquisition method accurately has the advantage of measuring biometric information, but has a risk of increasing contagious diseases due to the close contact. To solve these problems, the non-contact method of extracting biometric information such as human fingerprints, faces, iris, veins, voice, and signatures with automated devices is increasing in various industries as data processing speed increases and recognition accuracy increases. However, although the accuracy of the non-contact biometric data acquisition technology is improved, the non-contact method is greatly influenced by the surrounding environment of the object to be measured, which is resulting in distortion of measurement information and poor accuracy. In this paper, we propose a context-based bio-signal modeling technique for the interpretation of personalized information (image, signal, etc.) for bio-information analysis. Context-based biometric information modeling techniques present a model that considers contextual and user information in biometric information measurement in order to improve performance. The proposed model analyzes signal information based on the feature probability distribution through context-based signal analysis that can maximize the predicted value probability.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.1
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• pp.58-71
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• 2019

This paper proposes architecture of a cognitive radio engine platform and the allowable frequency channel reasoning method that enables acquisition of the allowable channels for the military tactical network environment. The current military tactical wireless communication system is increasing need to secure a supplementary radio frequency to ensure that multiple wireless networks for different military wireless devices coexist, so that tactical wireless communication between the same or different systems can be operated effectively. This paper presents the allowable frequency channel reasoning method based on cognitive radio engine for realizing DSA(Dynamic Spectrum Access) as an optimal available frequency channel. To this end, a case-based allowable frequency channel reasoning method for cognitive radio devices is proposed through modeling of primary user's traffic status and calculation of channel occupancy probability. Also through the simulation of the performance analysis, changing rate of collision probability between the primary users' occupancy channel and the available channel acquisition information that can be used by the cognitive radio device was analysed.

• Journal of radiological science and technology
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• v.46 no.5
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• pp.417-425
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• 2023

The glomerular filtration rate (GFR) has been the subject of much research as a key indicator for diagnosing, treating, and monitoring kidney function. The gamma camera method (Gates method) is simple and allows simultaneous acquisition of GFR and renal scintigraphy for each kidney, however its accuracy is inferior. This study aimed to investigate changes in GFR depending on how region of interest (ROI) are set up, which is one of many factors influencing accuracy. GFR was calculated by setting the ROI for each phase of the image acquisition time (Gates-1: 0~1 minutes, Gates-2: 1~3 minutes, Gates-3: 3~27 minutes), and statistical significance was verified based on probability value 0.05 through ANOVA analysis. While there was no statistically significant difference among results from Gates-1, 2, 3 (p=0.481>0.05), overall results from the Gates method tended to overestimate compared to those from the multiple blood sampling-dual exponential (MBSDE) method. When comparing averages between phases, results from Gates-2 were most similar to those from the MBSDE method. Moreover, paired t-test p-values between MBSDE method and phases were as follows Gates-1: 0.021 (p<0.05), Gates-2: 0.280 (p>0.05), and Gates-3: 0.164 (p>0.05) indicating that only Gates-1 had statistically significant differences compared with MBSDE method. Thus, setting ROI around 2~3 minutes is calculated can aid in accurately determining GFR when Gates Method.

• Smart Structures and Systems
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• v.15 no.1
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• pp.151-167
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• 2015

Instrumentation on structural health monitoring system imposes critical issues for applying the structural monitoring system to real world structures, for which not only on the configuration and geometry, but also aesthetics on the system to be monitored should be considered. To illustrate this point, two real world structural health monitoring systems, the structural health monitoring system of Shenzhen Vanke Center and the structural health monitoring system of Shenzhen Bay Stadium in China, are presented in the paper. The instrumentation on structural health monitoring systems of real world structures is addressed by providing the description of the structure, the purpose of the structural health monitoring system implementation, as well as details of the system integration including the installations on the sensors and acquisition equipment and so on. In addition, an intelligent algorithm on stress identification using measurements from multi-region is presented in the paper. The stress identification method is deployed using the fuzzy pattern recognition and Dempster-Shafer evidence theory, where the measurements of limited strain sensors arranged on structure are the input data of the method. As results, at the critical parts of the structure, the stress distribution evaluated from the measurements has shown close correlation to the numerical simulation results on the steel roof of the Beijing National Aquatics Center in China. The research work in this paper can provide a reference for the design and implementation of both real world structural health monitoring systems and intelligent algorithm to identify stress distribution effectively.

• The Korean Journal of Nuclear Medicine Technology
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• v.18 no.2
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• pp.8-16
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• 2014

Purpose The quantitative analysis of gallbladder emptying is very important in diagnosis of motility disorder of gallbladder and in biliary physiology. The GBEF obtain the statics aquisition method or the dynamic acquisition method in two ways. The purpose of this study is to compare the GBEF value of statics acquisition method and the dynamic acquisition method. And we find the best way for calculate GBEF. Materials and Methods The quantitative hepatobiliary scan with $^{99m}Tc$-mebrofenin was performed of 27 patients. Initial images were acquired statically, for 60 min after injection of the radioactive tracer. And if the gallbladder is visualized to 60 min, performed stimulation of gallbladder (1egg, 200 mL milk). After that, started acquisition of dynamic image for 30 min. After that, image of after fatty meal of the statics method were acquired on equal terms with 60 min image. The statics GBEF was calculated using the images of before fatty meal and post fatty meal by the statics method. The dynamic GBEF was calculated using the images of time of maximum bile juice uptake ($T_{max}$) and time of minimum bile juice uptake ($T_{min}$) images from the gallbladder time-activity curve. A bile juice is secreted from gallbladder while eating a fatty meal. that is named early GBEF and that was calculated using before fatty meal image of the statics method and 1 min image of the dynamic method. Results The result saw very big difference between two according to $T_{max}$. The result, were as follows. 1) In case of less than 1 min, the dynamic mean GBEF was $40.1{\pm}21.7%$, the statics mean GBEF was $51.5{\pm}23.6%$ in 16 cases. The early mean GBEF was $14.0{\pm}29.1%$. The GBEF of statics method was higher because that include secreted bile juice while performed stimulation of gallbladder. A difference of GB counts according to acquisition method and the early bile juice counts was $17.6{\pm}14.8%$ and $13.5{\pm}15.3%$. 2) In case of exceed than 1 min, the dynamic mean GBEF was $31.0{\pm}19.7%$, the statics mean GBEF was $21.3{\pm}19.4%$ in 7 cases. The early GBEF was $-6.9{\pm}4.9%$. The GBEF of dynamic method was higher because that include concentrated bile juice to $T_{max}$. A difference of GB counts according to acquisition method and the early bile juice counts was $14.3{\pm}7.3%$ and $5.9{\pm}3.9%$. Conclusion The statics method is very easy and simple, but in case of $T_{max}$ delay, the GBEF can be lower. The dynamic method is able to calculate accurately in case of $T_{max}$ delay, but in case of $T_{max}$ is less than 1 min, the GBEF can be lower because dynamic GBEF exclude secreted bile juice while performed stimulation of gallbladder. The best way to calculate GBEF is to scan with dynamic method preferentially and to choose suitable method between the two way after conform $T_{max}$ on the T-A curve of the dynamic method.

• Korean Journal of Digital Imaging in Medicine
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• v.9 no.2
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• pp.23-30
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• 2007

This study attempts to propose an appropriate method of using digital medical imaging equipments, by studying the effects of automatic exposure control(AEC), grid ratio and the change of radiography distance on the patient dose and detertor acquisition dose during the procedure of acquiring image through a digital medical imaging detector. The change of dose following the change of grid ratio's exposure and radiography distance was measured, by using an abdominal phantom organized with tissue equivalent materials in an amorphous silicon thin film transistor detecter installed with AWC. The case to use grid ratio 12 : 1, focal distance 180cm to radiography distance 110cm in AEC, the patient dose increased rather when we used grid ration 10 : 1, focal distance 110cm. When AEC was not used,the dose necessary for image acquisition decreased as the grid ratio became higher and the distance became further. but detector acquisition dose was not reduced when in applied AEC. When purchasing digiral medical imaging equipments, optional items such as AEC and grid shall be accurately selected to satisfy the use of the equipments. Radiography error made by radiation technologist and unnenessary patient dose can be reduced by selecting equipments with a radiography distance marker equipment when it did not apply AEC. These equipments can also be helpful in maintaining high imaging quality, one of the merits of digital detectors.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.6
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• pp.108-115
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• 2013

A developed skill of an intelligent CCTV is also advancing by using its Image Acquisition Device. In this field, area for technique can be divided into Foreground Subtraction which detects individuals and objects in a potential observing area and a tracing technology which figures out moving route of individuals and objects. In this thesis, an improved algorism for a settled engine development, which is stable to change in both noise and illumination for detecting moving objects is suggested. The proposed algorism from this thesis is focused on designing a stable and real time processing method which is perfect model in detecting individuals, animals, and also low-speeding transports and catching a change in an illumination and noise.

• Nuclear Engineering and Technology
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• v.50 no.5
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• pp.690-697
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• 2018

Criticality alarm systems (CASs) are mandatory in nuclear plants for prompt alarm in the event of any criticality incident. False criticality alarms are not desirable as they create a panic environment for radiation workers. The present article describes the design enhancement of the CAS at each stage and provides maximum availability, preventing false criticality alarms. The failure mode and effect analysis are carried out on each element of a CAS. Based on the analysis, additional hardware circuits are developed for early fault detection. Two different methods are developed, one method for channel loop functionality test and another method for dose alarm test using electronic transient pulse. The design enhancement made for the external systems that are integrated with a CAS includes the power supply, criticality evacuation hooter circuit, radiation data acquisition system along with selection of different soft alarm set points, and centralized electronic test facility. The CAS incorporating all improvements are assembled, installed, tested, and validated along with rigorous surveillance procedures in a nuclear plant for a period of 18,000 h.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.1
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• pp.87-95
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• 2020

Delivering the weapons system requirements of the military to the acquirer is an essential activity for the development of the defense industry as well as the successful acquisition of a weapons system. In order to ensure successful delivery of requirements, the creation of a weapons system Operational Requirements Document(ORD) has been mandated since 7. 2013. However, according to the results of a study which analyzes recently-created ORD, a number of problems are occurring. For one, some items in created ORDs differ from what the ORD template requires. In addition, the overall mission area of the weapons system to be acquired and the core parts(operation performance, system performance, and core performance) of ORD are being poorly recorded. In response, this study presented a framework(focused on a creating method of overall contents and core parts) for the creation of ORDs which can solve the problems that arose during ORD creation in the past.

• Electronics and Telecommunications Trends
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• v.33 no.5
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• pp.103-110
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• 2018

Studies on artificial intelligence have been developed for the past couple of decades. After a few periods of prosperity and recession, a new machine learning method, so-called Deep Learning, has been introduced. This is the result of high-quality big- data, an increase in computing power, and the development of new algorithms. The main targets for deep learning are 1D audio and 2D images. The application domain is being extended from a discriminative model, such as classification/segmentation, to a generative model. Currently, deep learning is used for processing 3D data. However, unlike 2D, it is not easy to acquire 3D learning data. Although low-cost 3D data acquisition sensors have become more popular owing to advances in 3D vision technology, the generation/acquisition of 3D data remains a very difficult problem. Moreover, it is not easy to directly apply an existing network model, such as a convolution network, owing to the variety of 3D data representations. In this paper, we summarize the 3D deep learning technology that have started to be developed within the last 2 years.