• Journal of the Daesoon Academy of Sciences
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• v.34
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• pp.141-169
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• 2020

This study focuses on the interpretation and transformation of "The Great Learning" within the Korean new religion, Daesoon Jinrihoe. Joseon Dynasty Korea was a member of the Chinese Character Cultural Sphere in East Asia. The examination and recruitment system of the Yuan Dynasty influenced the Joseon Dynasty for a long historical period. Zhu Xi's (朱熹) version of The Four Books were accepted and applied in imperial examinations during the Joseon Dynasty. The 18th century Confucian thinker, Jeong Yak-Yong (丁若鏞), overturned and rebuilt his own system for studying and interpreting The Four Books (四書學). Zhu Xi and Jeong Yak-Yong's systems of thought influenced Confucianism knowledge in that era. The historical figure deified as the Supreme God by Daesoon Jinrihoe, Kang Jeungsan (姜甑山), was trained in the study of The Four Books within that cultural and philosophical context, and this is especially evident in his interpretation and transmission of "The Great Learning." Kang Jeungsan regarding The Great Learning as deeply important. That text combined Confucian discourse on Principle, Mind, and Practice. In his interpretation, The Great Learning was also a medical and religious book that had holy and mysterious powers. In Mugeuk-do and Taegeuk-do (direct predecessors to Daesoon Jinrihoe), Jo Jeongsan interpreted the concept of Sincerity and Regularizing the Mind and incorporated them into doctrine as 'Sincerity, Respectfulness, and Faithfulness' and 'Guarding against Self-deception.' Park Wudang practiced and spread those doctrines to Korea, and Daesoon Jinrihoe devotees continue to follow those doctrines in present times.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1224-1248
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• 2022

In various sensor network applications, such as climate observation organizations, sensor nodes need to collect information from time to time and pass it on to the recipient of information through multiple bounces. According to field tests, this information corresponds to most of the energy use of the sensor hub. Decreasing the measurement of information transmission in sensor networks becomes an important issue.Compression sensing (CS) can reduce the amount of information delivered to the network and reduce traffic load. However, the total number of classification of information delivered using pure CS is still enormous. The hybrid technique for utilizing CS was proposed to diminish the quantity of transmissions in sensor networks.Further the energy productivity is a test task for the sensor nodes. However, in previous studies, a clustering approach using hybrid CS for a sensor network and an explanatory model was used to investigate the relationship between beam size and number of transmissions of hybrid CS technology. It uses efficient data integration techniques for large networks, but leads to clone attacks or attacks. Here, a new algorithm called SBEA (Snowball Endurance Algorithm) was proposed and tested with a bow. Thus, you can extend the battery life of your WSN by running effective copy detection. Often, multiple nodes, called observers, are selected to verify the reliability of the nodes within the network. Personal data from the source centre (e.g. personality and geographical data) is provided to the observer at the optional witness stage. The trust and reputation system is used to find the reliability of data aggregation across the cluster head and cluster nodes. It is also possible to obtain a mechanism to perform sleep and standby procedures to improve the life of the sensor node. The sniffers have been implemented to monitor the energy of the sensor nodes periodically in the sink. The proposed algorithm SBEA (Snowball Endurance Algorithm) is a combination of ERCD protocol and a combined mobility and routing algorithm that can identify the cluster head and adjacent cluster head nodes.This algorithm is used to yield the network life time and the performance of the sensor nodes can be increased.

• Smart Structures and Systems
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• v.31 no.5
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• pp.469-483
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• 2023

The dynamic characteristics of wind turbine blades are usually monitored by contact sensors with the disadvantages of high cost, difficult installation, easy damage to the structure, and difficult signal transmission. In view of the above problems, based on computer vision technology and the improved YOLOv5 (You Only Look Once v5) deep learning model, a non-contact dynamic characteristic monitoring method for wind turbine blade is proposed. First, the original YOLOv5l model of the CSP (Cross Stage Partial) structure is improved by introducing the CSP2_2 structure, which reduce the number of residual components to better the network training speed. On this basis, combined with the Deep sort algorithm, the accuracy of structural displacement monitoring is mended. Secondly, for the disadvantage that the deep learning sample dataset is difficult to collect, the blender software is used to model the wind turbine structure with conditions, illuminations and other practical engineering similar environments changed. In addition, incorporated with the image expansion technology, a modeling-based dataset augmentation method is proposed. Finally, the feasibility of the proposed algorithm is verified by experiments followed by the analytical procedure about the influence of YOLOv5 models, lighting conditions and angles on the recognition results. The results show that the improved YOLOv5 deep learning model not only perform well compared with many other YOLOv5 models, but also has high accuracy in vibration monitoring in different environments. The method can accurately identify the dynamic characteristics of wind turbine blades, and therefore can provide a reference for evaluating the condition of wind turbine blades.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.1
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• pp.170-191
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• 2024

The transmission of confidential data using cover media is called steganography. The three requirements of any effective steganography system are high embedding capacity, security, and imperceptibility. The text file's structure, which makes syntax and grammar more visually obvious than in other media, contributes to its poor imperceptibility. Text steganography is regarded as the most challenging carrier to hide secret data because of its insufficient redundant data compared to other digital objects. Unicode characters, especially non-printing or invisible, are employed for hiding data by mapping a specific amount of secret data bits in each character and inserting the character into cover text spaces. These characters are known with limited spaces to embed secret data. Current studies that used Unicode characters in text steganography focused on increasing the data hiding capacity with insufficient redundant data in a text file. A sequential embedding pattern is often selected and included in all available positions in the cover text. This embedding pattern negatively affects the text steganography system's imperceptibility and security. Thus, this study attempts to solve these limitations using the Part-of-speech (POS) tagging technique combined with the randomization concept in data hiding. Combining these two techniques allows inserting the Unicode characters in randomized patterns with specific positions in the cover text to increase data hiding capacity with minimum effects on imperceptibility and security. Format-preserving encryption (FPE) is also used to encrypt a secret message without changing its size before the embedding processes. By comparing the proposed technique to already existing ones, the results demonstrate that it fulfils the cover file's capacity, imperceptibility, and security requirements.

• Journal of Convergence for Information Technology
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• v.9 no.4
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• pp.1-7
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• 2019

The medical environment, combined with IT technology, is changing the paradigm for medical services from treatment to prevention. In particular, as ICT convergence digital healthcare technology is applied to hospital medical systems, infrastructure technologies such as big data, Internet of Things, and artificial intelligence are being used in conjunction with the cloud. In particular, as medical services are used with IT devices, the quality of medical services is increasingly improving to make them easier for users to access. Medical institutions seeking to incorporate IoT services into cloud health care environment services are trying to reduce hospital operating costs and improve service quality, but have not yet been fully supported. In this paper, a patient information collection model from hospital IoT system, which has established a cloud environment, is proposed. The proposed model prevents third parties from illegally eavesdropping and interfering with patients' biometric information through IoT devices attached to the patient's body at hospitals in cloud environments that have established hospital IoT systems. The proposed model allows clinicians to analyze patients' disease information so that they can collect and treat diseases associated with their eating habits through IoT devices. The analyzed disease information minimizes hospital work to facilitate the handling of prescriptions and care according to the patient's degree of illness.

• The Journal of the Acoustical Society of Korea
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• v.42 no.5
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• pp.441-451
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• 2023

Ultrasound transducers are an essential component of combined photoacoustic and ultrasound imaging systems and play an important role in image evaluation. However, ultrasound transducers are opaque; therefore, light must bypass the ultrasound transducer to reach the target point to produce a photoacoustic image. Providing different paths for the optical and acoustic signals results in a complicated system design, increasing the system volume. To overcome these problems, an optically Transparent Ultrasound Transducer (TUT) was developed. Unlike conventional opaque ultrasound transducers, optically TUT can be fabricated by a variety of manufacturing methods and they are suitable for use with specific piezoelectric elements and serve various purposes. In this study, a comparative analysis of the results of using Lithium Niobate (LNO), Lead Magnesium Niobate-Lead Titanate (PMN-PT), and Polyvinylidene Difluoride (PVDF), which are materials used in piezoelectric element-based TUT. LNO is a piezoelectric element widely used in TUT, and PMN-PT has been actively studied recently with a higher transmission and reception rate than LNO. Existing TUT have lower ultrasound resolution than photoacoustic resolution, but they have recently been manufacturing focused TUT with high ultrasound resolution using PVDF. A comparative analysis of the production results of these TUT was performed.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.9
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• pp.317-322
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• 2022

The rapid development of information technology is also bringing about many changes in the medical environment. In particular, it is leading the rapid change of medical image information systems using big data and artificial intelligence (AI). The prescription delivery system (OCS), which consists of an electronic medical record (EMR) and a medical image storage and transmission system (PACS), has rapidly changed the medical environment from analog to digital. When combined with multiple solutions, PACS represents a new direction for advancement in security, interoperability, efficiency and automation. Among them, the combination with artificial intelligence (AI) using big data that can improve the quality of images is actively progressing. In particular, AI PACS, a system that can assist in reading medical images using deep learning technology, was developed in cooperation with universities and industries and is being used in hospitals. As such, in line with the rapid changes in the medical image information system in the medical environment, structural changes in the medical market and changes in medical policies to cope with them are also necessary. On the other hand, medical image information is based on a digital medical image transmission device (DICOM) format method, and is divided into a tomographic volume image, a volume image, and a cross-sectional image, a two-dimensional image, according to a generation method. In addition, recently, many medical institutions are rushing to introduce the next-generation integrated medical information system by promoting smart hospital services. The next-generation integrated medical information system is built as a solution that integrates EMR, electronic consent, big data, AI, precision medicine, and interworking with external institutions. It aims to realize research. Korea's medical image information system is at a world-class level thanks to advanced IT technology and government policies. In particular, the PACS solution is the only field exporting medical information technology to the world. In this study, along with the analysis of the medical image information system using big data, the current trend was grasped based on the historical background of the introduction of the medical image information system in Korea, and the future development direction was predicted. In the future, based on DICOM big data accumulated over 20 years, we plan to conduct research that can increase the image read rate by using AI and deep learning algorithms.

• Korean Journal of Poultry Science
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• v.36 no.2
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• pp.177-186
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• 2009

It is well-known that unregulated over-expression of foreign gene may have unwanted physiological or toxic effects in transgenic animals. To circumvent these problems, we constructed retrovirus vector designed to express the foreign gene under the control of the tetracycline-inducible promoter. However, gene expressions in the tetracycline-inducible expression system (Tet system) are not completely regulated but a little leaky due to the inherent defects in conventional Tet-based systems. A more tightly controllable regulatory system can be achieved when the advanced versions ($rtTA2^SM2$) of rtTA and a minimal promoter in responsive components (pTRE-tight) are used in combination therein. In this study, we tried to produce human thrombopoietin (hTPO) from various target cells and transgenic chickens using the retrovirus vector combined with Tet system. hTPO is the primary regulator of platelet production and has an important role in the survival and expansion of hematopoietic stem cells. In a preliminary experiment in vitro, higher hTPO expression and tighter expression control were observed in chicken embryonic fibroblast (CEF) cells. We also measured the biological activity of the hTPO using Mo7e cells whose proliferation is dependant on hTPO. The biological activity of the recombinant hTPO from CEF was higher than both its commercial counterpart and hTPO from other target cells. The recombinant retrovirus was injected beneath the blastoderm of non-incubated chicken embryos (stage X). Out of 138 injected eggs, 15 chicks hatched after 21 days of incubation. Among them, 8 hatched chicks were hTPO positive. When the Go transgenic chicken was fed doxycycline (0.5 mg per 1 gram of feed), a tetracycline derivative, hTPO concentration of the transgenic chicken blood was 200 ng/mL. Germline transmission of the transgene was confirmed in sperm of the Go transgenic roosters. These results are informative to establish transgenic chickens as bioreactors for the mass production of commercially valuable and biological active human cytokine proteins.