• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.245-247
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• 2022

Backscattered x-ray imaging is a technology capable of acquiring an image inside an irradiated object by measuring X-rays scattered from an object. For image acquisition, the system must include an X-ray generator and a detection system for measuring scattered x-rays. The imaging device must acquire a real-time signal at sampling intervals for x-rays generated by passing through a high-speed rotating collimator, and for this purpose, a high-speed signal acquisition device is required. We developed a high-speed multi-channel signal acquisition device for converting and transmitting signals generated by the sensor unit composed of a large-area plastic scintillator and a photomultiplier tube. The developed detector is a system capable of acquiring signals at intervals of at least 15u seconds and converting and transmitting signals of up to 6 channels. And a system includes remote control functions such as high voltage, signal gain, and low level discrimination for individual calibration of each sensor. Currently, we are conducting an application test for image acquisition under various conditions.

• Journal of the Daesoon Academy of Sciences
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• v.24_1
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• pp.315-349
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• 2014

This paper was carried out to bring the researches on Cultivation Practice of Daesoonjinrihoe which have been at a standstill after analyzing the directions of studies on Cultivation Practice and diagnosing its problems, in addition to that, the paper was also conducted in a way of discussing the research directions in the future. This work enables scholars who have interests in Daesoon Thoughts to easily comprehend over the length and breadth of Cultivation Practice of Daesoonjinrihoe as well as help them understand what level of researches regarding Cultivation Practice has been demanded. Furthermore, this paper will be a step-stone for scholars to ponder how and on what perspective they approach a wide variety of studies on Daesoon Thoughts. The problems reflected on the previous researches on Cultivation Practice are summarized as follows: first, except a few researches in general, problem recognition, research target, style, method, and content are not diverged from the frame defined by Jang Byeong-Gil, who set it up in Daesoon Religion and Thought (Daesoon Jonggyo Sasang) in 1989. Proliferating overlapped researches without developing problem awareness is of great concern. And such researching climate has gradually set in. Secondly, there are numerous researches intending to reveal the researcher's forceful attitude implying faith. Thirdly, most of the previous researches neglect to focus on defining the range of researches. Fourthly, when defining concepts, more thorough insight is needed. Lastly, the researches on analysing symbols and attempting signification analysis are relatively few, only to find many errors. To solve these problems, this paper suggests to develop theories which back up Cultivation Practice by researching on the fields of theory of mind-nature(心性), theory of mind-qi(心氣), theory of pain, Religious Ethics, viewpoint of God/gods, and psychology. Secondly, all the symbols and meanings of elements shown in Cultivation Practice need analyzing more elaborately sophisticatedly and more in-depth. In order to fulfil this goal, by adapting the recent trends of historical studies, it is essential to attempt to engraft Cultivation Practice of Daesoonjinrihoe on cultural phenomena, to analyze thick layers of meanings beneath its surface, to interpret differently, utilizing various perspectives such as focusing on the gender problems, and to extract true meanings out of Cultivation Practice by analyzing everyday events which can occur in real cultivation practices. Thirdly, the terms and concepts regarding Cultivation Practice base the principle themselves. Fourthly, by utilizing methodology of comparative studies on religions, the comparative researches on cultivation practice of different religious traditions are also needed. Lastly, the history of aspects on Cultivation Practice such as transition of mantras, processes which have been conducted through proprieties of prayer and training should be collected and classified. In this context, this work is very important since it helps understand the aspects of transition of originality and characteristics in Cultivation Practice of Daesoonjinrihoe according to passage of time.

• Journal of the Korean neurological association
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• v.35 no.1
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• pp.8-15
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• 2017

Near-infrared spectroscopy (NIRS), a noninvasive optical method, utilizes the characteristic absorption spectra of hemoglobin in the near-infrared range to provide information on cerebral hemodynamic changes in various clinical situations. NIRS monitoring have been used mainly to detect reduced perfusion of the brain during orthostatic stress for three common forms of orthostatic intolerance (OI); orthostatic hypotension, neurally mediated syncope, and postural orthostatic tachycardia syndrome. Autonomic function testing is an important diagnostic test to assess their autonomic nervous systems for patients with symptom of OI. However, these techniques cannot measure dynamic changes in cerebral blood flow. There are many experimentations about study of NIRS to reveal the pathophysiology of patients with OI. Research using NIRS in other neurologic diseases (stroke, epilepsy and migraine) are ongoing. NIRS have been experimentally used in all stages of stroke and may complement the established diagnostic and monitoring tools. NIRS also provide pathophysiological approach during rehabilitation and secondary prevention of stroke. The hemodynamic response to seizure has long been a topic for discussion in association with the neuronal damage resulting from convulsion. One critical issue when unpredictable events are to be detected is how continuous NIRS data are analyzed. Besides, NIRS studies targeting pathophysiological aspects of migraine may contribute to a deeper understanding of mechanisms relating to aura of migraine. NIRS monitoring may play an important role to trend regional hemodynamic distribution of flow in real time and also highlights the pathophysiology and management of not only patients with OI symptoms but also those with various neurologic diseases.

• Journal of Veterinary Science
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• v.24 no.5
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• pp.73.1-73.16
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• 2023

Background: Highly pathogenic avian influenza virus (HPAIV) is considered a global threat to both human health and the poultry industry. MicroRNAs (miRNA) can modulate the immune system by affecting gene expression patterns in HPAIV-infected chickens. Objectives: To gain further insights into the role of miRNAs in immune responses against H5N1 infection, as well as the development of strategies for breeding disease-resistant chickens, we characterized miRNA expression patterns in tracheal tissues from H5N1-infected Ri chickens. Methods: miRNAs expression was analyzed from two H5N1-infected Ri chicken lines using small RNA sequencing. The target genes of differentially expressed (DE) miRNAs were predicted using miRDB. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis were then conducted. Furthermore, using quantitative real-time polymerase chain reaction, we validated the expression levels of DE miRNAs (miR-22-3p, miR-146b-3p, miR27b-3p, miR-128-3p, miR-2188-5p, miR-451, miR-205a, miR-203a, miR-21-3p, and miR-200a3p) from all comparisons and their immune-related target genes. Results: A total of 53 miRNAs were significantly expressed in the infection samples of the resistant compared to the susceptible line. Network analyses between the DE miRNAs and target genes revealed that DE miRNAs may regulate the expression of target genes involved in the transforming growth factor-beta, mitogen-activated protein kinase, and Toll-like receptor signaling pathways, all of which are related to influenza A virus progression. Conclusions: Collectively, our results provided novel insights into the miRNA expression patterns of tracheal tissues from H5N1-infected Ri chickens. More importantly, our findings offer insights into the relationship between miRNA and immune-related target genes and the role of miRNA in HPAIV infections in chickens.

• Phonetics and Speech Sciences
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• v.15 no.3
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• pp.75-82
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• 2023

Automatic speech recognition (ASR) has been revolutionized with deep learning-based approaches, among which self-supervised learning methods have proven to be particularly effective. In this study, we aim to enhance the performance of OpenAI's Whisper model, a multilingual ASR system on the Korean language. Whisper was pretrained on a large corpus (around 680,000 hours) of web speech data and has demonstrated strong recognition performance for major languages. However, it faces challenges in recognizing languages such as Korean, which is not major language while training. We address this issue by fine-tuning the Whisper model with an additional dataset comprising about 1,000 hours of Korean speech. We also compare its performance against a Transformer model that was trained from scratch using the same dataset. Our results indicate that fine-tuning the Whisper model significantly improved its Korean speech recognition capabilities in terms of character error rate (CER). Specifically, the performance improved with increasing model size. However, the Whisper model's performance on English deteriorated post fine-tuning, emphasizing the need for further research to develop robust multilingual models. Our study demonstrates the potential of utilizing a fine-tuned Whisper model for Korean ASR applications. Future work will focus on multilingual recognition and optimization for real-time inference.

• Journal of Practical Engineering Education
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• v.15 no.2
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• pp.439 -447
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• 2023

This paper aims to develop a map for optimized class space using ZEP among the metaverse platforms. As a research method, the classroom space was organized so that the subject of learning became a learner, and the classroom space was modified and supplemented to optimize while being applied to elementary school computer classes. The contents of the study investigated learners' prior perception of metaverse, and compared and analyzed the advantages and disadvantages of the metaverse platform. In addition, the map was designed by reflecting the results of the survey, and after applying the map to the class, necessary APIs and apps were installed to supplement it. As a result, the learner became the subject of learning in the metaverse space, freely identified the space, and actively participated in the class. In particular, we found that students who were passive offline and those who had a low participation rate due to lack of skills participated more actively. In particular, students who were passive offline or whose participation was low due to lack of skills participated more actively. If API and JavaScript programs are added to collect log data of learners for learning analysis, real-time feedback is possible for learners, and learner feedback is possible for instructors with statistical data. If this is possible, the metaverse space can fully expect the role of a learning assistant for learners and a teaching assistant for instructors.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.27-35
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• 2023

In this paper, we propose a process of increasing productivity by applying a deep learning-based defect detection and classification system to the prepreg fiber manufacturing process, which is in high demand in the field of producing composite materials. In order to apply it to toe prepreg manufacturing equipment that requires a solution due to the occurrence of a large amount of defects in various conditions, the optimal environment was first established by selecting cameras and lights necessary for defect detection and classification model production. In addition, data necessary for the production of multiple classification models were collected and labeled according to normal and defective conditions. The multi-classification model is made based on CNN and applies pre-learning models such as VGGNet, MobileNet, ResNet, etc. to compare performance and identify improvement directions with accuracy and loss graphs. Data augmentation and dropout techniques were applied to identify and improve overfitting problems as major problems. In order to evaluate the performance of the model, a performance evaluation was conducted using the confusion matrix as a performance indicator, and the performance of more than 99% was confirmed. In addition, it checks the classification results for images acquired in real time by applying them to the actual process to check whether the discrimination values are accurately derived.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.5
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• pp.323-330
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• 2023

The development of an analysis model that reflects the microstructure characteristics of polyvinyl alcohol (PVA) fiber-reinforced cementitious composites, which have a highly complex microstructure, enables synergy between efficient material design and real experiments. PVA fiber orientations are an important factor that influences the mechanical behavior of PVA fiber-reinforced cementitious composites. Owing to the difficulty in distinguishing the gray level value obtained from micro-CT images of PVA fibers from adjacent phases, fiber segmentation is time-consuming work. In this study, a micro-CT test with a voxel size of 0.65 ㎛³ was performed to investigate the three-dimensional distribution of fibers. To segment the fibers and generate training data, histogram, morphology, and gradient-based phase-segmentation methods were used. A U-net model was proposed to segment fibers from micro-CT images of PVA fiber-reinforced cementitious composites. Data augmentation was applied to increase the accuracy of the training, using a total of 1024 images as training data. The performance of the model was evaluated using accuracy, precision, recall, and F1 score. The trained model achieved a high fiber segmentation performance and efficiency, and the approach can be applied to other specimens as well.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.6
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• pp.407-414
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• 2023

In this study, an automated jack-up system, applicable to various fields, was employed for 3D concrete printing and developed as a simultaneous liftable 3D concrete printing system. This developed printing system enables safe and precise jack-up by monitoring the measured jack-up distance using Pearson correlation coefficient analysis and a hydraulic system with interquartile range analysis in real-time during 3D concrete printing operations. It is possible to secure the quality of 3D concrete printing structures, which is essential for expanding the application of 3D concrete printing to construct larger structures. Specimens were printed using both conventional 3D concrete printing and simultaneous liftable 3D concrete printing to evaluate the system performance. The printed specimens were investigated using a 3D scanner. The layer-wise diameter and angle of intersection of the scanned specimens were measured, and an analysis was performed to verify the advantages of the simultaneous liftable 3D concrete printing.

• Ecology and Resilient Infrastructure
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• v.10 no.4
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• pp.116-124
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• 2023

As the flood damage on small streams increase due to the increase in frequency of extreme climate events, the need to measure hydraulic data of them has increased for disaster risk management. National Disaster Management Institute, Ministry of Interior and Safety develops CADMT, a CCTV-based automatic discharge measurement technology, and operates pilot small streams to verify its performance and develop disaster risk management technology. The research selects two small streams such as the Neungmac and the Jungsunpil streams to develop the Nomograph by using the 4-Parameter Logistic method using only the observed rainfall data from the Automatic Weather System operated by the Korea Meteorological Agency closest to the small streams and discharge data collected by using the CADMT. To evaluate developed Nomograph, the research forecasts floods discharges in each small stream and compares the result with the observed discharges. As a result of the evaluations, the forecasted value is found to represent the observed value well, so if more accurate observed data are collected and the Nomograph based on it is developed in the future, the high-accuracy flood prediction and warning will be possible.