• Journal of Oriental Neuropsychiatry
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• v.30 no.3
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• pp.251-263
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• 2019

Objectives: The purpose of this study was to review the clinical research trends in the treatment of post traumatic stress disorder (PTSD) in Korean medicine (KM). Methods: We searched MEDLINE, CENTRAL, EMBASE, Google Scholar and five Korean databases through May 2019, for studies on KM to treat PTSD. Clinical research that conducted KM treatment of PTSD patients were included. Two researchers independently conducted study selection and data extraction process. Results: Totally, eight studies were included in this review. Types of traumatic events that patients experienced included physical violence/threatening, traffic accidents, sexual violence and personal tragic events. KM interventions performed included acupuncture, moxibustion, herbal medicine, physical therapy, and KM-based psychotherapy. Treatment duration varied from two days to more than five months. Follow-up began at least one week to three months after the end of treatments. It was reported that the major psychological and/or somatic symptoms of PTSD, such as anxiety, depression, insomnia, and musculoskeletal pain, subjectively improved, as well as other objective outcomes: Impact Event Scale-Revised Korean version (IES-R-K), Beck's Depression Inventory (BDI), State-Trait Anxiety Inventory, Hwabyung Symptoms/characters, Electroencephalography (EEG) change, etc. Statistical studies were conducted in three studies only. Outcomes such as Visual Analogue Scale (VAS), BDI, and IES-R-K showed statistically significant improvement after KM treatments. There was no study reporting adverse events during or after the interventions. Conclusions: According to this review, diverse types of KM treatments have been used among PTSD patients in eight studies. The KM treatments effectively improved psychological and somatic symptoms of PTSD patients. However, the lack of high quality research as well as the lack of standardization of KM treatments for PTSD are limitations. Further methodologically robust clinical trials should be performed, and the standardization of KM treatments for PTSD should be sought.

• Smart Structures and Systems
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• v.29 no.1
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• pp.1-16
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• 2022

Despite recent breakthroughs in deep learning and computer vision fields, the pixel-wise identification of tiny objects in high-resolution images with complex disturbances remains challenging. This study proposes a modified U-net for tiny crack segmentation in real-world steel-box-girder bridges. The modified U-net adopts the common U-net framework and a novel Self-Attention-Self-Adaption (SASA) neuron as the fundamental computing element. The Self-Attention module applies softmax and gate operations to obtain the attention vector. It enables the neuron to focus on the most significant receptive fields when processing large-scale feature maps. The Self-Adaption module consists of a multiplayer perceptron subnet and achieves deeper feature extraction inside a single neuron. For data augmentation, a grid-based crack random elastic deformation (CRED) algorithm is designed to enrich the diversities and irregular shapes of distributed cracks. Grid-based uniform control nodes are first set on both input images and binary labels, random offsets are then employed on these control nodes, and bilinear interpolation is performed for the rest pixels. The proposed SASA neuron and CRED algorithm are simultaneously deployed to train the modified U-net. 200 raw images with a high resolution of 4928 × 3264 are collected, 160 for training and the rest 40 for the test. 512 × 512 patches are generated from the original images by a sliding window with an overlap of 256 as inputs. Results show that the average IoU between the recognized and ground-truth cracks reaches 0.409, which is 29.8% higher than the regular U-net. A five-fold cross-validation study is performed to verify that the proposed method is robust to different training and test images. Ablation experiments further demonstrate the effectiveness of the proposed SASA neuron and CRED algorithm. Promotions of the average IoU individually utilizing the SASA and CRED module add up to the final promotion of the full model, indicating that the SASA and CRED modules contribute to the different stages of model and data in the training process.

• The Korean Journal of Nuclear Medicine
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• v.32 no.5
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• pp.414-424
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• 1998

Purpose: Cross-modality coregistration of positron emission tomography (PET) and magnetic resonance imaging (MR) could enhance the clinical information. In this study we propose a refined technique to improve the robustness of registration, and to implement more realistic visualization of the coregistered images. Materials and Methods: Using the sinogram of PET emission scan, we extracted the robust head boundary and used boundary-enhanced PET to coregister PET with MR. The pixels having 10% of maximum pixel value were considered as the boundary of sinogram. Boundary pixel values were exchanged with maximum value of sinogram. One hundred eighty boundary points were extracted at intervals of about 2 degree using simple threshold method from each slice of MR images. Best affined transformation between the two point sets was performed using least square fitting which should minimize the sum of Euclidean distance between the point sets. We reduced calculation time using pre-defined distance map. Finally we developed an automatic coregistration program using this boundary detection and surface matching technique. We designed a new weighted normalization technique to display the coregistered PET and MR images simultaneously. Results: Using our newly developed method, robust extraction of head boundary was possible and spatial registration was successfully performed. Mean displacement error was less than 2.0 mm. In visualization of coregistered images using weighted normalization method, structures shown in MR image could be realistically represented. Conclusion: Our refined technique could practically enhance the performance of automated three dimensional coregistration.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.12
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• pp.126-134
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• 2017

There have been numerous studies on extracting the R-peak from electrocardiogram (ECG) signals. However, most of the detection methods are complicated to implement in a real-time portable electrocardiograph device and have the disadvantage of requiring a large amount of calculations. R-peak detection requires pre-processing and post-processing related to baseline drift and the removal of noise from the commercial power supply for ECG data. An adaptive filter technique is widely used for R-peak detection, but the R-peak value cannot be detected when the input is lower than a threshold value. Moreover, there is a problem in detecting the P-peak and T-peak values due to the derivation of an erroneous threshold value as a result of noise. We propose a robust R-peak detection algorithm with low complexity and simple computation to solve these problems. The proposed scheme removes the baseline drift in ECG signals using an adaptive filter to solve the problems involved in threshold extraction. We also propose a technique to extract the appropriate threshold value automatically using the minimum and maximum values of the filtered ECG signal. To detect the R-peak from the ECG signal, we propose a threshold neighborhood search technique. Through experiments, we confirmed the improvement of the R-peak detection accuracy of the proposed method and achieved a detection speed that is suitable for a mobile system by reducing the amount of calculation. The experimental results show that the heart rate detection accuracy and sensitivity were very high (about 100%).

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.4 s.304
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• pp.1-12
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• 2005

Image registration is a process to establish the spatial correspondence between images of the same scene, which are acquired at different view points, at different times, or by different sensors. This paper presents a new algorithm for robust registration of the images acquired by multiple sensors having different modalities; the EO (electro-optic) and IR(infrared) ones in the paper. The two feature-based and intensity-based approaches are usually possible for image registration. In the former selection of accurate common features is crucial for high performance, but features in the EO image are often not the same as those in the R image. Hence, this approach is inadequate to register the E0/IR images. In the latter normalized mutual Information (nHr) has been widely used as a similarity measure due to its high accuracy and robustness, and NMI-based image registration methods assume that statistical correlation between two images should be global. Unfortunately, since we find out that EO and IR images don't often satisfy this assumption, registration accuracy is not high enough to apply to some applications. In this paper, we propose a two-stage NMI-based registration method based on the analysis of statistical correlation between E0/1R images. In the first stage, for robust registration, we propose two preprocessing schemes: extraction of statistically correlated regions (ESCR) and enhancement of statistical correlation by filtering (ESCF). For each image, ESCR automatically extracts the regions that are highly correlated to the corresponding regions in the other image. And ESCF adaptively filters out each image to enhance statistical correlation between them. In the second stage, two output images are registered by using NMI-based algorithm. The proposed method provides prospective results for various E0/1R sensor image pairs in terms of accuracy, robustness, and speed.

• The Korean Journal of Air & Space Law and Policy
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• v.35 no.1
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• pp.181-202
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• 2020

The Non-Appropriation Principle was stipulated in the OST and the MA. However the MA, creating CHM in international law for the first time, attempted to further limit the prohibitions to include ownership of resources extracted from celestial bodies, its rejection by the U.S. and most of the international spacefaring community prevented it from serving as a binding international treaty. Individuals or private enterprises intending to perform space exploitation must receive approval from the nation and may not appropriate outer space or celestial bodies. In the course of this space activity, each party will be liable. Articles 6 and 7 of the OST and the Liability Convention of 1972 deal with matters concerning those problems. The CSLCA of 2015 and Luxembourg Space Resources Law of 2017 allows States to provide commercial exploration and use of space resources to their own nationals and to companies operated by other countries within their territory. These laws do not violate Article 2 of the OST. In the case of the CSLCA of 2015, the law clearly states that it cannot claim ownership, sovereignty or jurisdiction over certain celestial bodies. Even if scholars claim that the U.S. CSLCA and Luxembourg Space Resources Law violate the non-appropriation principle of the OST, they cannot prevent these two countries from extracting the space resources on "the first come, first served" basis. The legal status of outer space including the moon and other celestial bodies is res extra commercium, like the high seas, where the fishing vessels from each country catch and sell fish without occupying the sea. Major space-faring nations must push for the adoption of an international regulatory committee which will oversee applications and issue permits based on a set of robust, modern, and forward-thinking ideals that are best equipped to govern and protect outer space as individuals, businesses, and nations compete to commercialize space through mining and the extraction of space-based resources. The new Corpus Juris Spatialis on the development of space resources, whether it is a treaty or a soft law such as recommendation and declaration, in the case of the Moon and Mars, will cover a certain amount of area to develop, and the development period by the states should be specified.

• Progress in Medical Physics
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• v.13 no.4
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• pp.209-217
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• 2002

There have been many studies on the application of the reciprocal advantages of multimodality image to define accurate target volume in the Process of radiation treatment planning. For the proper use of the multimodality images, the registration works between different modality images should be performed in advance. In this study, we selected chamfer matching method and mutual information method as most popular methods in recent image registration studies considering the registration accuracy and clinical practicality. And the two registration methods were analyzed to deduce the optimal registration method according to the characteristics of images. Lung phantom of which multimodality images could be acquired was fabricated and CT, MRI and SPECT images of the phantom were used in this study. We developed the registration program which can perform the two registration methods properly and analyzed the registration results which were produced by the developed program in many different images' conditions. Although the overall accuracy of the registration in both chamfer matching method and mutual information method was acceptable, the registration errors in SPECT images which had lower resolution and in degraded images of which data were removed in some part were increased when chamfer matching method was applied. Especially in the case of degraded reference image, chamfer matching methods produce relatively large errors compared with mutual information method. Mutual information method can be estimated as more robust registration method than chamfer matching method in this study because it did not need the prerequisite works, the extraction of accurate contour points, and it produced more accurate registration results consistently regardless of the images' characteristics. The analysis of the registration methods in this study can be expected to provide useful information to the utilization of multimodality images in delineating target volume for radiation treatment planning and in many other clinical applications.