• Journal of Korean Society of Disaster and Security
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• v.16 no.2
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• pp.85-98
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• 2023

Flood is one of the most frequent natural disasters worldwide. In Korea, the probability of urban flooding is greatly increasing due to complex factors such as global warming, an increase in impervious areas, and limitations in expanding water supply facilities in existing urban areas. However, large-scale civil engineering works to prevent urban inundation are socially and economically difficult to obtain national consent. Recently the importance of resilience, which is the ability to return to the original state after a disaster through rapid recovery while preparing for natural disasters to a level that the local community can afford socially and economically, is increasing. Accordingly, various studies on urban resilience have been conducted, but the resilience measurement method related to the lifeline that provides essential services of the city is insufficient. However, among lifelines, road networks are important facilities for the transportation of recovery resources and rapid recovery in the event of a natural disaster, so road networks are a major factor that must be considered when measuring the degree of recovery of a city in the field of natural disasters. Therefore, this study proposes a recovery evaluation method considering the characteristics of resilience and road networks in the urban flooding field and analyzes the effect of road networks on urban resilience.

• Journal of The Korean Astronomical Society
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• v.56 no.2
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• pp.231-252
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• 2023

We present the analysis results of the simultaneous multifrequency observations of the blazar 4C +28.07. The observations were conducted by the Interferometric Monitoring of Gamma-ray Bright Active Galactic Nuclei (iMOGABA) program, which is a key science program of the Korean Very Long Baseline Interferometry (VLBI) Network (KVN). Observations of the iMOGABA program for 4C +28.07 were conducted from 16 January 2013 (MJD 56308) to 13 March 2020 (MJD 58921). We also used γ-ray data from the Fermi Large Array Telescope (Fermi-LAT) Light Curve Repository, covering the energy range from 100 MeV to 100 GeV. We divided the iMOGABA data and the Fermi-LAT data into five periods from 0 to 4, according to the prosody of the 22 GHz data and the presence or absence of the data. In order to investigate the characteristics of each period, the light curves were plotted and compared. However, a peak that formed a hill was observed earlier than the period of a strong γ-ray flare at 43-86 GHz in period 3 (MJD 57400-58100). Therefore, we assumed that the minimum total CLEANed flux density for each frequency was quiescent flux (S_q) in which the core of 4C +28.07 emitted the minimum, with the variable flux (S_var) obtained by subtracting S_q from the values of the total CLEANed flux density. We then compared the variability of the spectral indices (α) between adjacent frequencies through a spectral analysis. Most notably, α_22-43 showed optically thick spectra in the absence of a strong γ-ray flare, and when the flare appeared, α_22-43 became optically thinner. In order to find out the characteristics of the magnetic field in the variable region, the magnetic field strength in the synchrotron self-absorption (B_SSA) and the equipartition magnetic field strength (B_eq) were obtained. We found that B_SSA is largely consistent with B_eq within the uncertainty, implying that the SSA region in the source is not significantly deviated from the equipartition condition in the γ-ray quiescent periods.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.5
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• pp.113-119
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• 2023

Most infrastructure structures were completed during periods of economic growth. The number of infrastructure structures reaching their lifespan is increasing, and the proportion of old structures is gradually increasing. The functions and performance of these structures at the time of design may deteriorate and may even lead to safety accidents. To prevent this repercussion, accurate inspection and appropriate repair are requisite. To this end, demand is increasing for computer vision and deep learning technology to accurately detect even minute cracks. However, deep learning algorithms require a large number of training data. In particular, label images indicating the location of cracks in the image are required. To secure a large number of those label images, a lot of labor and time are consumed. To reduce these costs as well as increase detection accuracy, this study proposed a learning structure based on mean teacher method. This learning structure was trained on a dataset of 900 labeled image dataset and 3000 unlabeled image dataset. The crack detection network model was evaluated on over 300 labeled image dataset, and the detection accuracy recorded a mean intersection over union of 89.23% and an F1 score of 89.12%. Through this experiment, it was confirmed that detection performance was improved compared to supervised learning. It is expected that this proposed method will be used in the future to reduce the cost required to secure label images.

• Korean Journal of Ichthyology
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• v.35 no.4
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• pp.217-223
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• 2023

The 886-bp sequence of the mitochondrial region encoding the cytb gene was used to identify the origin of the Goryeong (GR) population of Pungitius kaibarae and to characterize genetic diversity and structure among wild populations. The GR population showed the lowest haplotype diversity (H_d=0.000), while the highest haplotype diversity was confirmed at 0.755 among the Goseoung (GS) population. Nucleotide diversity ranged was the highest diversity at 0.00291 in the GS population and the lowest diversity at 0.00000 in the GR population. The GR population was genetically closest to the Pohang (PH) population. The haplotype network confirmed that the GR population was most similar to the PH population. The GR population also clustered with the PH population with high bootstrap support (98%) in a phylogenetic tree. We thus conclude that the GR population is derived from a population similar to the PH population.

• IMMUNE NETWORK
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• v.22 no.5
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• pp.42.1-42.20
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• 2022

Vaccination with tumor peptide epitopes associated with MHC class I molecules is an attractive approach directed at inducing tumor-specific CTLs. However, challenges remain in improving the therapeutic efficacy of peptide epitope vaccines, including the low immunogenicity of peptide epitopes and insufficient stimulation of innate immune components in vivo. To overcome this, we aimed to develop and test an innovative strategy that elicits potent CTL responses against tumor epitopes. The essential feature of this strategy is vaccination using tumor epitope-loaded nanoparticles (NPs) in combination with polyinosinic-polycytidylic acid (poly-IC) and anti-PD1 mAb. Carboxylated NPs were prepared using poly(lactic-co-glycolic acid) and poly(ethylene/maleic anhydride), covalently conjugated with anti-H-2K^b mAbs, and then attached to H-2K^b molecules isolated from the tumor mass (H-2^b). Native peptides associated with the H-2K^b molecules of H-2K^b-attached NPs were exchanged with tumor peptide epitopes. Tumor peptide epitope-loaded NPs efficiently induced tumor-specific CTLs when used to immunize tumor-bearing mice as well as normal mice. This activity of the NPs significantly was increased when co-administered with poly-IC. Accordingly, the NPs exerted significant anti-tumor effects in mice implanted with EG7-OVA thymoma or B16-F10 melanoma, and the anti-tumor activity of the NPs was significantly increased when applied in combination with poly-IC. The most potent anti-tumor activity was observed when the NPs were co-administered with both poly-IC and anti-PD1 mAb. Immunization with tumor epitope-loaded NPs in combination with poly-IC and anti-PD1 mAb in tumor-bearing mice can be a powerful means to induce tumor-specific CTLs with therapeutic anti-tumor activity.

• Information Systems Review
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• v.22 no.4
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• pp.75-92
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• 2020

As population and generation structures change, more and more customers tend to avoid facing relation due to the development of information technology and spread of smart phones. This phenomenon consists with efficiency and immediacy, which are the consumption patterns of modern customers who are used to information technology, so offline network-oriented distribution companies actively try to switch their sales and services to untact patterns. Recently, untact services are boosted in various fields, but beauty products are not easy to be recommended through untact services due to many options depending on skin types and conditions. There have been many studies on recommendations and development of recommendation systems in the online beauty field, but most of them are the ones that develop recommendation algorithm using survey or social data. In other words, there were not enough studies that classify segments based on user information such as skin types and product preference. Therefore, this study classifies customer segments using machine learning technique K-prototypesalgorithm based on customer information and search log data of mobile application, which is one of untact services in the beauty field, based on which, untact marketing strategy is suggested. This study expands the scope of the previous literature by classifying customer segments using the machine learning technique. This study is practically meaningful in that it classifies customer segments by reflecting new consumption trend of untact service, and based on this, it suggests a specific plan that can be used in untact services of the beauty field.

• Information Systems Review
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• v.22 no.2
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• pp.25-41
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• 2020

Along with the expectation about 5G network commercialization, interests in realistic and immersive media industries such as virtual reality (VR) are increasing. However, most of studies on VR still focus on video technologies instead of factors for popularity and consumption. Thus, the main objective of this research is to identify meaningful factors, which affect the view counts of VR videos and to provide business implications of the content strategies for VR video creators and service providers. Using a regression analysis with 700 VR videos, this study tries to find major factors that affect the view counts of VR videos. As a result, user assessment factors such as number of likes and sicknesses have a strong influence on the view counts. In addition, the result shows that both general information factors (video length and age) and content characteristic factors (series, one source multi use (OSMU), and category) are all influential factors. The findings suggest that it is necessary to support recommendation and curation based on user assessments for increasing popularity and diffusion of VR video streaming.

• Information Systems Review
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• v.21 no.3
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• pp.1-26
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• 2019

Now we are facing with a possibility of having crimes, which have been only possible offline, in cyber spaces as well.Especially, a recent growth in the use of SNS, promoted by popularization of smart phones, also has led an abrupt increase in cyber crime. It would be important to have a understanding of cyber crime and its characteristics by type as well as factors associated with each type of cyber crime in order to devise appropriate preventive measures against cyber crime. However, most of the previous studies on cyber crimesolely made through literature review or indirect approaches. Therefore, this study has been designed to conduct the interview with actual suspects(criminals) of cyber crime to address factors of cyber crime and to devise specific preventive measures and countermeasures against cyber crime. Especially, among various types of cyber crime, this study aims at addressing the 'trades' and 'financial transaction' of crimes committed using the information and communication network and the 'cyber libel/insult'of crimes committed using unlicensed contents, which have been soared recently and become significant issues. The findings of this study could be beneficial for the society since it has managed to conduct the interview and reveal relationships among major factors of cyber crime. The findings of this study could be used for devising and developing proper preventive and countermeasures against cyber crime, in turn reducing and preventing its damage.

• IMMUNE NETWORK
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• v.22 no.2
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• pp.18.1-18.15
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• 2022

Dysfunction of mitochondrial metabolism is implicated in cellular injury and cell death. While mitochondrial dysfunction is associated with lung injury by lung inflammation, the mechanism by which the impairment of mitochondrial ATP synthesis regulates necroptosis during acute lung injury (ALI) by lung inflammation is unclear. Here, we showed that the impairment of mitochondrial ATP synthesis induces receptor interacting serine/threonine kinase 3 (RIPK3)-dependent necroptosis during lung injury by lung inflammation. We found that the impairment of mitochondrial ATP synthesis by oligomycin, an inhibitor of ATP synthase, resulted in increased lung injury and RIPK3 levels in lung tissues during lung inflammation by LPS in mice. The elevated RIPK3 and RIPK3 phosphorylation levels by oligomycin resulted in high mixed lineage kinase domain-like (MLKL) phosphorylation, the terminal molecule in necroptotic cell death pathway, in lung epithelial cells during lung inflammation. Moreover, the levels of protein in bronchoalveolar lavage fluid (BALF) were increased by the activation of necroptosis via oligomycin during lung inflammation. Furthermore, the levels of ATP5A, a catalytic subunit of the mitochondrial ATP synthase complex for ATP synthesis, were reduced in lung epithelial cells of lung tissues from patients with acute respiratory distress syndrome (ARDS), the most severe form of ALI. The levels of RIPK3, RIPK3 phosphorylation and MLKL phosphorylation were elevated in lung epithelial cells in patients with ARDS. Our results suggest that the impairment of mitochondrial ATP synthesis induces RIPK3-dependent necroptosis in lung epithelial cells during lung injury by lung inflammation.

• IMMUNE NETWORK
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• v.21 no.4
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• pp.26.1-26.28
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• 2021

Asthma exacerbations are a major cause of intractable morbidity, increases in health care costs, and a greater progressive loss of lung function. Asthma exacerbations are most commonly triggered by respiratory viral infections, particularly with human rhinovirus (hRV). Respiratory viral infections are believed to affect the expression of indoleamine 2,3-dioxygenase (IDO), a limiting enzyme in tryptophan catabolism, which is presumed to alter asthmatic airway inflammation. Here, we explored the detailed role of IDO in the progression of asthma exacerbations using a mouse model for asthma exacerbation caused by hRV infection. Our results reveal that IDO is required to prevent neutrophilic inflammation in the course of asthma exacerbation caused by an hRV infection, as corroborated by markedly enhanced Th17- and Th1-type neutrophilia in the airways of IDO-deficient mice. This neutrophilia was closely associated with disrupted expression of tight junctions and enhanced expression of inflammasome-related molecules and mucin-inducing genes. In addition, IDO ablation enhanced allergen-specific Th17- and Th1-biased CD4⁺ T-cell responses following hRV infection. The role of IDO in attenuating Th17- and Th1-type neutrophilic airway inflammation became more apparent in chronic asthma exacerbations after repeated allergen exposures and hRV infections. Furthermore, IDO enzymatic induction in leukocytes derived from the hematopoietic stem cell (HSC) lineage appeared to play a dominant role in attenuating Th17- and Th1-type neutrophilic inflammation in the airway following hRV infection. Therefore, IDO activity in HSC-derived leukocytes is required to regulate Th17- and Th1-type neutrophilic inflammation in the airway during asthma exacerbations caused by hRV infections.