• Ocean and Polar Research
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• 제23권3호
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• pp.223-242
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• 2001

This paper presents the depth-mean monthly variation in the circulation of the Yellow Sea and the East China Sea computed using a robust diagnostic model. The mixed three-dimensional finite-difference Galerkin function model developed by Lee et at. (2000, 2001) has been extended to take into account baroclinic effects and then used to calculate the depth-mean flow fields as part of the results. In addition to M2 tide and oceanic flows previously considered, the model has been driven by the monthly mean wind stresses from Na and Seo (1998), the density gradient calculated based on by GDEM data set released by US Navy. Model results are very encouraging in that many of observed features including Jeju Cyclonic Gyre and frontal eddies along the shelfside of the Kuroshio main stream and west of Kyushu, are satisfactorily reproduced and are expected to be of value in interpreting observations in various oceanograhic disciplines.

• 대한의용생체공학회:의공학회지
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• 제27권5호
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• pp.229-236
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• 2006

The acoustic field analysis method is the superior calibration method for rectifying the ultrasonic probe sensitivity. This method also can be applied to evaluate the probe performance in clinical fields without numerical analysis and precise measurements. In this paper, we propose the method of acoustic field pattern analysis with probe channel division for the evaluation of diagnostic ultrasound probe characterization. In order to verify our purpose, we performed a set of experiments. We measured the acoustic-field pattern of the three inferiority probes by channel division to evaluate an acoustic field distribution and impulse response characteristics. By comparing the results of acoustic field measurement method with that of conventional method such as impulse response and live image test for linear array probes, it is demonstrated that the ultrasound field measurement method is more effective then conventional method in detection of defective elements.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 26-27 Oct. 1990
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• pp.1399-1404
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• 1990

There is an increasing need to apply artificial intelligence to the real application fields of industry. These include an intelligent process control, an expert machine and a diagnostic and/or maintenance machine. These applications are implemented in AI Languages. It is commonly recognized that AI Languages, such as Common Lisp or Prolog, require a workstation. This is mainly due to the fact that both languages need a large amount of memory space and disk storage space. Workstations are appropriate for a laboratory or office environment. However, they are too bulky to use in the real application fields of industry or business. Also users who apply artificial intelligence to these fields wish to have their own operating systems. We propose a new design method of an intelligent controller which is embedded within equipment and provides easy-to-use tools for artificial intelligence applications. In this paper we describe the new design method of a VMEbus based intelligent controller for artificial intelligence applications and a small operating system which supports Common Lisp and Prolog.

• 전기학회논문지
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• 제59권8호
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• pp.1456-1463
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• 2010

The safety critical systems in nuclear power plants should be designed to have a high level of fault tolerant capability because those systems are used for protection or mitigation of the postulated accidents of nuclear reactor. Due to increasing of the system complexity of the digital based system in nuclear fields, the reliability of the digital based systems without an auto-test or a self-diagnostic feature is generally lower than those of analog system. To overcome this problem, additional redundant architectures in each redundant channel and self-diagnostic features are commonly integrated into the digital safety systems. The self diagnostic function is a key factor for increasing fault tolerant capabilities in the digital based safety system. This paper presents an availability and safety evaluation model to analyze the effect to the system's fault tolerant capabilities depending on self-diagnostic features when the loss or erroneous behaviors of self-diagnostic function are expected to occur. The analysis result of the proposed model on the several modules of a safety platform shows that the improvement effect on unavailability of each module has generally become smaller than the result of usage of conventional models and the unavailability itself has changed significantly depending on the characteristics of failures or errors of self-diagnostic function.

• 한국환경과학회지
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• 제19권1호
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• pp.27-37
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• 2010

A system coupled the prognostic WRF mesoscale model and CALMET diagnostic model has been employed for predicting high-resolution wind field over complex coastal area. WRF has three nested grids down to from during two days from 24 August 2007 to 26 August 2007. CALMET simulation is performed using both initial meteorological field from WRF coarsest results and surface boundary condition that is Shuttle Radar Topography Mission (SRTM) 90m topography and Environmental Geographic Information System (EGIS) 30m landuse during same periods above. Four Automatic Weather System (AWS) and a Sonic Detection And Ranging (SODAR) are used to verify modeled wind fields. Horizontal wind fields in CM_100m is not only more complex but better simulated than WRF_1km results at Backwoon and Geumho in which there are shown stagnation, blocking effects and orographically driven winds. Being increased in horizontal grid spacing, CM_100m is well matched with vertically wind profile compared SODAR. This also mentions the importance of high-resolution surface boundary conditions when horizontal grid spacing is increased to produce detailed wind fields over complex terrain features.

• 대한방사성의약품학회지
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• 제5권2호
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• pp.120-128
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• 2019

Radiopharmaceuticals include therapeutic radiopharmaceuticals and diagnostic radiopharmaceuticals. Therapeutic radiopharmaceuticals are administered to the body and ingested at specific organs to detect radiation emitted from the site and to construct an image to diagnose the disease. Diagnostic radiopharmaceuticals are used to treat diseases by killing cells with radiation emitted from radiopharmaceuticals, such as cancer cells, vascular endothelial cells, arthritis, and Alzheimer's disease. The application possibilities of terahertz imaging technology for the combination of radiopharmaceuticals and molecular imaging medicine are discussed and experimental methods are presented. Terahertz imaging is expected to be a powerful technique because of the effective piercing feasibility, which enables to perform safe and high resolutive imaging. To investigate the response of cell to the terahertz wave, both the pulsed and CW THz wave systems are employed. THz imaging of a rat's paraffin-embedded epithelial cell with tumor is studied in advance.

• Asian Pacific Journal of Cancer Prevention
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• 제17권2호
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• pp.473-478
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• 2016

Hepatocellular cancer is a very common cause of cancer related deaths worldwide. Only 30-40% of patients present with early-stage disease open to curative treatments, such as resection or transplantation, while others can only undergo local therapies or palliative care. Various trans-arterial approaches have been used for treatment of hepatocellular carcinoma in patients who need a down-staging to liver transplantation, and who are not candidates for transplantation or radiofrequency ablation. Transarterial chemoembolization (TACE), transarterial embolization (TAE), drug-eluting beads, and radioembolization have been used for locoregional control, and have been shown to prolong the overall survival when compared with supportive care. In this review, we discuss patient selection, pre- and post-procedure imaging, techniques, safety, and clinical outcomes related to these therapies. Newer advances with future directions in various fields related to trans-arterial therapies are also discussed.

• 대한기관식도과학회지
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• 제17권1호
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• pp.9-13
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• 2011

Endobronchial ultrasound (EBUS), which enables visualization of lesions beyond the bronchus, broadens the fields of bronchoscopy. Two types of ultrasound, radial and linear, are used for bronchoscopy. Radial EBUS is performed by inserting an ultrasound mini-probe through the working channel of a flexible bronchoscope. Evaluation of the depth of invasion of early endobronchial lung cancers using radial EBUS is useful in deciding endobronchial treatment. A central tumor limited to within the cartilaginous layer is a good indication for endobronchial photodynamic therapy. EBUS-guide sheath (GS) technique is a sampling method assisted by localization of peripheral lesions using EBUS. The diagnostic yield of EBUS-GS method is higher than that of conventional transbronchial biopsy. High diagnostic values of EBSU-GS method are reported even in small (${\leq}2cm$) peripheral tumors. Linear EBUS is used for endobronchial ultrasound guided transbronchial needle aspiration (EBUS-TBNA). EBUS-TBNA has high diagnostic yields in mediastinal staging of lung cancer even in patients having radiologically early stage lung cancers with normal CT or PET findings in the mediastinum. EBUS is a valuable method in evaluating early endobronchial tumors and peripheral small lung cancers and as well as in mediastinal staging.

• 대한방사선기술학회지:방사선기술과학
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• 제42권1호
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• pp.9-17
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• 2019

Although digital mammography is a representative method for breast cancer detection. It has a limitation in detecting and classifying breast tumor due to superimposed structures. Machine learning, which is a part of artificial intelligence fields, is a method for analysing a large amount of data using complex algorithms, recognizing patterns and making prediction. In this study, we proposed a technique to improve the diagnostic accuracy of energy-selective mammography by training data using the machine learning algorithm and using dual-energy measurements. A dual-energy images obtained from a photon-counting detector were used for the input data of machine learning algorithms, and we analyzed the accuracy of predicted tumor thickness for verifying the machine learning algorithms. The results showed that the classification accuracy of tumor thickness was above 95% and was improved with an increase of imput data. Therefore, we expect that the diagnostic accuracy of energy-selective mammography can be improved by using machine learning.

• The Journal of Korean Physical Therapy
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• 제34권4호
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• pp.135-139
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• 2022

Purpose: We investigated the satisfaction of physical therapy course according to teaching ways after COVID-19. Methods: 336 students in major of physical therapy were recruited in this study. Based on the classification of subjects in the national examination, the questionnaire was divided into 6 subjects in the basic field of physical therapy, 2 subjects in the field of physical therapy diagnostic evaluation, 8 subjects in the field of physical therapy intervention, and 3 subjects in other fields. The Likert scale was used. Results: In the basic field of physical therapy, all subjects were shown the high score of the satisfactory in face-to-face classes except for the public health and medical law compared to the non-face-to-face classes and mixed classes. Regarding the field of physical therapy diagnostic evaluation, the principle of diagnostic evaluation was shown the high score of the satisfactory in face-to-face classes compared to the non-face-to-face classes and mixed classes. In the field of physical therapy intervention, all subjects were shown the high score of the satisfactory in face-to-face classes compared to the non-face-to-face classes and mixed classes. Conclusion: We found that the face-to-face classes in most of subjects was shown the high score of satisfactory. We believed that our results can be used as basic data for physical therapy major learning methods.