• Journal of Life Science
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• v.33 no.9
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• pp.754-765
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• 2023

Exosomes are a type of extracellular vesicle containing proteins and messenger and microRNAs; they are secreted by all cell types. Once released, exosomes are selectively taken up by other cells adjacent or at a distance, releasing their contents and reprogramming the target cells. Since exosomes are natural vesicles produced by cells as small sizes, it is generally accepted that exosomes have a non-toxic nature and non-immunogenic behaviors. Recently, exosomes have elicited scientific attention as drug delivery vehicles to the central nervous system. The central nervous system has a blood-brain barrier that makes it difficult for drugs to penetrate. Thus, the blood-brain barrier has been a major obstacle to the development of drugs for treating neurodegenerative diseases. However, accumulating evidence suggests that exosomes can cross the blood-brain barrier primarily through transcytosis. Consequently, exosomes are expected to become a new delivery vehicle that can cross the blood-brain barrier and deliver drugs into the brain parenchyma. In addition, since different types of exosomes are secreted depending on the cell type and disease state, exosomes can also be utilized as biomarkers for the diagnosis of diseases in the central nervous system. In this review, we summarized recent research trends on exosomes, including clinical trials as biomarkers and treatment options for diseases in the central nervous system.

• Journal of Advanced Navigation Technology
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• v.17 no.1
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• pp.69-79
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• 2013

In this paper, DCT(Discrete Cosine Transform) and CAVLC(Context Adaptive Variable Length Coding) are co-designed as hardware IP with software operation of the other modules in H.264/AVC codec. In order to increase the operation speed, a new method using SHIFT table is proposed. As a result, enhancement of about 16(%) in the operation speed is obtained. Designed Hardware IPs are downloaded into Virtex-4 FX60 FPGA in the ML-410 development board and H.264/AVC encoding is performed with Microblaze CPU implemented in FPGA. Software modules are developed from JM13.2 to make C code. In order to verify the designed Hardware IPs, Modelsim program is used for functional simulation. As a result that all Hardware IPs and software modules are downloaded into the FPGA, improvement of processing speed about multiples of 16 in case of DCT hardware IP and multiples of 10 in case of CAVLC compared with software-only processing. Although this paper deals with co-design of H/W and S/W for H.264, it can be utilized for the other embedded system design.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.12
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• pp.511-517
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• 2016

Current oil-type potential transformers for trains are filled with insulating oil, which could have problems like explosions due to rising inner pressure during train operation. Therefore, mold and dry-type potential transformers are being developed to prevent explosions. One problem in manufacturing mold-type transformers is preventing void formation around the coiled core inside the mold during epoxy filling, which could cause an electrical spark. Micro voids can remain in the resin after filling, and macro voids can occur due to the structure shape. A transformer that is being developed has a cavity at the junction of the core and the coil for better performance, and when highly viscous epoxy flows inside the cavity channel, macro voids can form inside it. Therefore, in this study, the free-surface flow of the mold filling procedure was analyzed numerically by applying the VOF method. The results were used to understand the phenomena of void formation inside the cavity and to modify the process conditions to reduce voids.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.3 no.4
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• pp.301-307
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• 2005

The morphology of the high burnup $UO_2$ spent fuel, which was oxidized and annealed in a PIA (Post Irradiation Annealing) apparatus, has been observed. The high burnup fuel irradiated in Ulchin Unit 2, average rod burnup 57,000 MWd/tU, was transported to the KAERI's PIEF. The test specimen was used with about 200 mg of the spent $UO_2$ fuel fragment of the local burnup 65,000 MWd/tU. This specimen was annealed at $1400^{\circ}C$ for 4hrs after the oxidation for 3hrs to grain boundary using the PIA apparatus in a hot-cell. In order to oxidize the grain boundary, the oxidation temperature increased up to $500^{\circ}C$ and held for 3hrs in the mixed gas (60 ml He and 100 ml STD-air) atmosphere. The amount of 85Kr during the whole test process was measured to know the fission gas release behavior using the online system of a beta counter and a gamma counter. The detailed micro-structure was observed by a SEM to confirm the change of the fuel morphology after this test. As the annealing temperature increased, the fission products were observed to move to the grain surface and grain boundary of the $UO_2$ matrix. This specimen was re-structured through the reduction process, and the grain sizes were distributed from 5 to $10\;{\mu}m$.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.217-242
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• 2022

With the launch of Artificial Intelligence(AI)-based intelligent products on the market, innovative changes are taking place not only in business but also in consumers' daily lives. Intelligent products have the potential to realize technology differentiation and increase market competitiveness through advanced functions of artificial intelligence. However, there is no new product development methodology that can sufficiently reflect the characteristics of artificial intelligence for the purpose of developing intelligent products with high market acceptance. This study proposes a KANO-QFD integrated model as a methodology for intelligent product development. As a specific example of the empirical analysis, the types of consumer requirements for hair loss prediction and treatment device were classified, and the relative importance and priority of engineering characteristics were derived to suggest the direction of intelligent medical product development. As a result of a survey of 130 consumers, accurate prediction of future hair loss progress, future hair loss and improved future after treatment realized and viewed on a smartphone, sophisticated design, and treatment using laser and LED combined light energy were realized as attractive quality factors among the KANO categories. As a result of the analysis based on House of Quality of QFD, learning data for hair loss diagnosis and prediction, micro camera resolution for scalp scan, hair loss type classification model, customized personal account management, and hair loss progress diagnosis model were derived. This study is significant in that it presented directions for the development of artificial intelligence-based intelligent medical product that were not previously preceded.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4717-4737
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• 2017

Today, smart grids, smart homes, smart water networks, and intelligent transportation, are infrastructure systems that connect our world more than we ever thought possible and are associated with a single concept, the Internet of Things (IoT). The number of devices connected to the IoT and hence the number of traffic flow increases continuously, as well as the emergence of new applications. Although cutting-edge hardware technology can be employed to achieve a fast implementation to handle this huge data streams, there will always be a limit on size of traffic supported by a given architecture. However, recent cloud-based big data technologies fortunately offer an ideal environment to handle this issue. Moreover, the ever-increasing high volume of traffic created on demand presents great challenges for flow management. As a solution, flow aggregation decreases the number of flows needed to be processed by the network. The previous works in the literature prove that most of aggregation strategies designed for smart grids aim at optimizing system operation performance. They consider a common identifier to aggregate traffic on each device, having its independent static aggregation policy. In this paper, we propose a dynamic approach to aggregate flows based on traffic characteristics and device preferences. Our algorithm runs on a big data platform to provide an end-to-end network visibility of flows, which performs high-speed and high-volume computations to identify the clusters of similar flows and aggregate massive number of mice flows into a few meta-flows. Compared with existing solutions, our approach dynamically aggregates large number of such small flows into fewer flows, based on traffic characteristics and access node preferences. Using this approach, we alleviate the problem of processing a large amount of micro flows, and also significantly improve the accuracy of meeting the access node QoS demands. We conducted experiments, using a dataset of up to 100,000 flows, and studied the performance of our algorithm analytically. The experimental results are presented to show the promising effectiveness and scalability of our proposed approach.

• Journal of Korea Technology Innovation Society
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• v.12 no.1
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• pp.189-211
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• 2009

The importance of searching the weak signal has been increasingly recognized to cope with rapidly changing circumstances as an environmental analysis technique. This study proposed the NEST process for the searching for the weak signal. The NEST (New & Emerging Signals of Trends) is a micro environmental analysis process based on both quantitative and qualitative method. For this, the weak signal Searching Board is developed and traditional methods as global monitoring, trend analysis, brainstorming and delphi method are implemented to NEST. The NEST process is consists of three stage modules; the global monitoring stage in search of seeds information related to the environmental change, the weak signal analysis stage using the weak signal Tracking Board, and the delphi valuation stage for objectifying the final result. The NEST provides the weak signal of the promising technology which can bring new paradigm and the Up-Coming Trends which can lead new trend in the future. These outputs can be used to select promising technology from firm level to national level. The NEST system can be effectively operated as well as in small group so that small and medium innovative firms can develop and execute their own NEST process individually.

• Korean Journal of Remote Sensing
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• v.38 no.6_4
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• pp.1955-1969
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• 2022

Most of the public and private users who use national satellite information such as the KOMPSAT series mainly use Electro-Optical and Infrared (EO/IR) satellite images, and the utilization of Synthetic Aperture Radar (SAR) images is relatively insufficient. As KOMPSAT-5 currently in operation, KOMPSAT-6 and micro SAR satellite constellation systems are scheduled to be launched in the future, the demand for utilization of SAR satellite information is increasing in various fields. Accordingly, it is necessary to possess core technology for SAR utilization that can support the utilization of SAR satellite information for users. Due to the all-weather properties of SAR system, change detection technology is a key application technology. However, until now, the development of technology that automatic change detection and cueing using SAR images is insufficient. Through this study, the requirements of automatic change detection and cueing function using multi-temporal KOMPSAT-5 SAR satellite images were derived and a prototype program was developed. This prototype program aims to secure independent SAR utilization technology and promote the utilization of domestic SAR satellite information by practitioners in public sector organizations in Korea.

• 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.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.4
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• pp.129-134
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• 2017

In the present society, our current technology associated with bakery industry has been improved as much as technical development can get abreast of the Western one where the bread has originated and has been awarded and ranked in the highest level of many bakery or pastry competitions. In these trends, many people are running for high value added business such as bakery industry and bakery $caf{\acute{e}}$, etc. with big interest. However, high labor cost of technician and difficulties in human resource management become obstruction factors in the growth of the bakery industries. Therefore, in this paper, the designed system for both dividing and rounding dough quickly and exactly at the same time was studied. The main function of this system is to divide the original dough into 3 tracks and then, to place 4 doughs in the inner track, 12 doughs in the mid track, 20 doughs in the outer track, totally 36 doughs in a routine. It takes much energy because 36 doughs can be completed in a routine. Therefore, this system uses hydraulic pressure and a 0.75Kw induction motor is used for dough rounding. This system can make primarily fermented dough into 36 divided doughs very quickly and exactly on a guide panel at the desired weight by dividing it within 1-9 seconds and by rounding each within 1-9 seconds. This system is very effective in bakery industry to minimize labor cost and it is expected to supply more hygienic products to the customers.