• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.77-83
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• 2020

The heat treatment facility is in a situation where the scope of application of the remote IOT system is expanding due to the harsh environment caused by high heat and long working hours among the root industries. In this heat treatment process environment, the IOT middleware is required to play a pivotal role in interpreting, managing and controlling data information of IoT devices (sensors, etc.). Until now, the system controlled by the heat treatment remotely was operated with the command of the operator's batch system without overall monitoring of the site situation. However, for the safety and precise control of the heat treatment facility, it is necessary to control various sensors and recognize the surrounding work environment. As a solution to this, the heat treatment safety support system presented in this paper proposes a support system that can detect the access of the work manpower to the heat treatment furnace through thermal image detection and operate safely when ordering work from a remote location. In addition, an OPEN CV-based deterioration analysis system using DNN deep learning network was constructed for faster and more accurate recognition than general fixed hot spot monitoring-based thermal image analysis. Through this, we would like to propose a system that can be used universally in the heat treatment environment and support the safety management specialized in the heat treatment industry.

• Journal of the Korean Geotechnical Society
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• v.38 no.11
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• pp.43-54
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• 2022

The settlement at the railroad foundation is often the leading cause of track irregularity and potential derailment. The control of such deformation is considered necessary in track maintenance practice. Nevertheless, the monitoring process performed by in situ surveying requires an excessive amount of manpower and cost. The InSAR, a remote sensing technique by RADAR satellite, is used to overcome such a burden. The PS-InSAR technique is preferred for a long-term precise monitoring method. However, this study aims to obtain relatively brief analysis results from only two satellite images using the D-InSAR technique, while a minimum of 25 images are required for PS-InSAR. This study verifies the precision of D-InSAR within a few millimeters by inspecting railroad facilities and land settlements in Korea Railroad Research Institute's test track with images from TerraSAR-X Satellite. Multiple corner reflectors were adopted and installed on an embankment and the building roof to raise the surface reflectivity. Those reflectors were slightly adjusted periodically to verify the detecting performance. The results revealed the optimum distance between corner reflectors. Further, the deformation of railway tracks, slopes, and concrete structures was analyzed successively. In conclusion, this study indicates that the D-InSAR technique effectively monitors the short-term deformation of a broad area such as railway structures.

• Korean Journal of Optics and Photonics
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• v.34 no.1
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• pp.22-30
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• 2023

The use of segmented mirrors is one of the ways to make the primary mirror of a spaceborne satellite larger, where several small mirrors are combined into a large monolithic mirror. To align multiple segmented mirrors as one large mirror, there must be no discontinuity in the x, y-axis (tilt) and axial alignment error (piston) between adjacent mirrors. When the tilt and piston are removed, we can collect the light in one direction and get an expected clear image. Therefore, we need a precise wavefront sensor that can measure the alignment error of the segmented mirrors in nm scale. The tilt error can be easily detected by the point spread image of the segmented mirrors, while the piston error is hard to detect because of the absence of apparent features, but makes a downgraded image. In this paper we used an optical testing interferometer such as a Fizeau interferometer, which has various advantages when aligning the segmented mirror on the ground, and focused on measuring the axial displacement error of a segmented mirror as the basic research of measuring the piston errors between adjacent mirrors. First, we calculated the relationship between the axial displacement error of the segmented mirror and the surface defocus error of the interferometer and verified the calculated formula through experiments. Using the experimental results, we analyzed the measurement uncertainty and obtained the limitation of the Fizeau interferometer in detecting axial displacement errors.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.33-43
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• 2024

This research assessed the applicability of the You Only Look Once (YOLO)v8 and DeepLabv3+ models for the effective detection of compost heaps, identified as a significant source of non-point source pollution. Utilizing high-resolution imagery acquired through Unmanned Aerial Vehicles(UAVs), the study conducted a comprehensive comparison and analysis of the quantitative and qualitative performances. In the quantitative evaluation, the YOLOv8 model demonstrated superior performance across various metrics, particularly in its ability to accurately distinguish the presence or absence of covers on compost heaps. These outcomes imply that the YOLOv8 model is highly effective in the precise detection and classification of compost heaps, thereby providing a novel approach for assessing the management grades of compost heaps and contributing to non-point source pollution management. This study suggests that utilizing UAVs and deep learning technologies for detecting and managing compost heaps can address the constraints linked to traditional field survey methods, thereby facilitating the establishment of accurate and effective non-point source pollution management strategies, and contributing to the safeguarding of aquatic environments.

• Journal of the Korean Society of Radiology
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• v.82 no.1
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• pp.99-115
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• 2021

Various sequences have been developed for MRI to aid in the radiologic diagnosis. Among the various MR sequences, susceptibility-weighted imaging (SWI) is a high-spatial-resolution, three-dimensional gradient-echo MR sequence, which is very sensitive in detecting deoxyhemoglobin, ferritin, hemosiderin, and bone minerals through local magnetic field distortion. In this regard, SWI has been used for the diagnosis and treatment of various neurologic disorders, and the improved image quality has enabled to acquire more useful information for radiologists. Here, we explain the principle of various signals on SWI arising in neurological disorders and provide a retrospective review of many cases of clinically or pathologically proven disease or components with distinctive imaging features of various neurological diseases. Additionally, we outline a short and condensed overview of principles of SWI in relation to neurological disorders and describe various cases with characteristic imaging features on SWI. There are many different types diseases involving the brain parenchyma, and they have distinct SWI features. SWI is an effective imaging tool that provides complementary information for the diagnosis of various diseases.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.29-37
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• 2024

In this paper, we propose an efficient image processing system to detect and track the movement of specific objects such as patients. The proposed system extracts the outline area of an object from a binarized difference image by applying a thinning algorithm that enables more precise detection compared to previous algorithms and is advantageous for mixed-mode design. The binarization and thinning steps, which require a lot of computation, are designed based on RTL (Register Transfer Level) and replaced with optimized hardware blocks through logic circuit synthesis. The designed binarization and thinning block was synthesized into a logic circuit using the standard 180n CMOS library and its operation was verified through simulation. To compare software-based performance, performance analysis of binary and thinning operations was also performed by applying sample images with 640 × 360 resolution in a 32-bit FPGA embedded system environment. As a result of verification, it was confirmed that the mixed-mode design can improve the processing speed by 93.8% in the binary and thinning stages compared to the previous software-only processing speed. The proposed mixed-mode system for object recognition is expected to be able to efficiently monitor patient movements even in an edge computing environment where artificial intelligence networks are not applied.

• Korean Journal of Remote Sensing
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• v.30 no.2
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• pp.185-205
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• 2014

SAR ground moving target indicator (GMTI) has long been an important issue for SAR advanced applications. As spatial resolution of space-borne SAR system has been significantly improved recently, the GMTI becomes a very useful tool. Various GMTI techniques have been developed particularly using multi-channel SAR systems. It is, however, still problematic to detect ground moving targets within single channel SAR images while it is not practical to access high resolution multi-channel space-borne SAR systems. Once a ground moving target is detected, it is possible to retrieve twodimensional velocities of the target from single channel space-borne SAR with an accuracy of about 5 % if moving faster than 3 m/s. This paper presents a quick-and-dirty method for detecting ground moving targets from single channel SAR single-look complex (SLC) images by differentiation. Since the signal powers of derivatives present Doppler centroid and rate, it is very efficient and effective for detection of non-stationary targets. The derivatives correlate well with velocities retrieved by a precise method with a correlation coefficient $R^2$ of 0.62, which is well enough to detect the ground moving targets. While the approach is theoretically straightforward, it is necessary to remove the effects of residual Doppler rate before finalizing the ground moving target candidates. The confidence level of results largely depends on the efficiency and effectiveness of the residual Doppler rate removal method. Application results using TerraSAR-X and truck-mounted corner reflectors validated the efficiency of the method. While the derivatives of moving targets remain easily detectable, the signal energy of stationary corner reflectors was suppressed by about 18.5 dB. It results in an easy detection of ground targets moving faster than 8.8 km/h. The proposed method is applicable to any high resolution single channel SAR systems including KOMPSAT-5.

• Nuclear Medicine and Molecular Imaging
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• v.43 no.1
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• pp.72-78
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• 2009

Purpose: Bone mineral density (BMD) measurements need to be precise enough to be capable of detecting small changes in bone mass of rats. Using a regular dual-energy X-ray absorptiometry (DXA), we measured many BMD of various skeletal sites in rats to examine precision of DXA in relation to the repositioning on the bones of rats. Materials and Methods: Using DXA and small animal software, scans were performed 4 times in all 12 male rats without repositioning (Group 1a). Another four scans for 6 of 12 rats were done with repositioning between scans (Group 2). Customized regions of interest (ROIs), encapsulate the right hind limb, L1-4, skull and pelvic bones were drawn at each measurement. The precision of the measurements was evaluated by measuring the coefficient of variation (CV) of four measurements of BMD at each skeletal site of all rats with or without repositioning. Significance of differences between group 1b (six rats out of group 1a, which were come under group 2) and group2 were evaluated with Wilcoxon Signed Rank Sum Test. Results: CVs obtained at different skeletal sites of all measurements in Group 1b and 2. It was $3.51{\pm}1.20$, $ 2.62{\pm}1.20$ for the hindlimb (p=0.173), $3.83{\pm}2.02$, $4.59{\pm}2.02$ for L1-4 (p=0.600), $3.73{\pm}1.87$, $1.53{\pm}0.89$ for skull (p=0.046), and $2.92{\pm}0.60$, $1.45{\pm}0.60$ for pelvic bones (p=0.075). Conclusion: Our study demonstrates that the DXA technique has the precision necessary when used to assess BMD for various skeletal sites in rats regardless of repositioning.

• Tuberculosis and Respiratory Diseases
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• v.61 no.5
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• pp.433-439
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• 2006

Background: Although airway hyper-responsiveness is one of the characteristics of asthma. bronchial hyper-responsiveness has also been observed to some degree in patients with chronic obstructive pulmonary disease (COPD). Moreover, several reports have demonstrated that a number of patients have both COPD and asthma. The methacholine bronchial challenge test (MCT) is a widely used method for the detecting and quantifying the airway hyper- responsiveness, and is one of the diagnostic tools in asthma. However, the significance of MCT in differentiating asthma or COPD combined with asthma from pure COPD has not been defined. The aim of this study was to determine the role of MCT in differentiating asthma from pure COPD. Method: This study was performed prospectively and was composed of one hundred eleven patients who had undergone MCT at Chonbuk National University Hospital. Sixty-five asthma patients and 23 COPD patients were enrolled and their MCT data were analyzed and compared with the results of a control group. Result: The positive rates of MCT were 65%, 30%, and 9% in the asthma, COPD, and control groups, respectively. The mean $PC_{20}$ values of the asthma, COPD, and control groups were $8.1{\pm}1.16mg/mL$, $16.9{\pm}2.21mg/mL$, and $22.0{\pm}1.47mg/mL$, respectively. The sensitivity, specificity, positive predictive value, and negative predictive value of MCT for diagnosing asthma were 65%, 84%, 81%, and 69%, respectively. The sensitivity, specificity, positive predictive value, and negative predictive value of MCT (ed note: please check this as I believe that these values correspond to the one $PC_{20}$ value. Please check my changes.) at the new cut-off points of$PC_{20}{\leq}16mg/ml$, were 80%, 75%, 78%, and 78%, respectively. Conclusion: MCT using the new cut-off point can be used as a more precise and useful diagnostic tool for distinguishing asthma from pure COPD.

• Tuberculosis and Respiratory Diseases
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• v.60 no.6
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• pp.645-652
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• 2006

Objective: Patients with lung cancer have a relative high risk of developing secondary primary lung cancers. This study examined the additional value of autofluorescence bronchoscopy (AFB) for diagnosing synchronous lung cancers and premalignant lesions. Methods: Patients diagnosed with lung cancer from January 2005 to December 2005 were enrolled in this study. The patients underwent a lung cancer evaluation, which included white light bronchoscopy (WLB), followed by AFB. In addition to the primary lesions, any abnormal or suspicious lesions detected during WLB and AFB were biopsied. Results: Seventy-six patients had non-small cell lung cancer (NSCLC) and 23 had small cell lung cancer (SCLC). In addition to the primary lesions, 84 endobronchial biopsies were performed in 46 patients. Five definite synchronous cancerous lesions were detected in three patients with initial unresectable NSCLC and in one with SCLC. The secondary malignant lesions found in two patients were considered metastatic because of the presence of mediastinal nodes or systemic involvement. One patient with an unresectable NSCLC, two with a resectable NSCLC, and one with SCLC had severe dysplasia. The detection rate for cancerous lesions by the clinician was 6.0% (6/99) including AFB compared with 3.0% (3/99) with WLB alone. The prevalence of definite synchronized cancer was 4.0% (4/99) after using AFB compared with 2.0% (2/99) before, and the staging-up effect was 1.0% (1/99) after AFB. Since the majority of patients were diagnosed with advanced disease, the subjects with newly detected cancerous lesions did not have their treatment plans altered, except for one patient with a stage-up IV NSCLC who did not undergo radiotherapy. Conclusions: Additional AFB is effective in detecting early secondary cancerous lesions and is a more precise tool in the staging workup of patients with primary lung cancer than with WLB alone.