• Journal of Advanced Navigation Technology
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• v.27 no.6
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• pp.835-840
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• 2023

RFID(Radio Frequency Identification) systems are attracting attention as a key component of Internet of Things technology due to the cost and energy efficiency of application services. In order to use RFID technology in the IoT application service field, it is necessary to be able to store and manage various information for a long period of time as well as simple recognition between the reader and tag of the RFID system. And in order to read and write information to tags, a performance improvement technology that is strong and reliable in poor wireless channels is needed. In particular, in the UHF(Ultra High Frequency) RFID system, since multiple tags communicate passively in a crowded environment, it is essential to improve the recognition rate and transmission speed of individual tags. In this paper, Middleton's Class A impulsive noise model was selected to analyze the performance of the RFID system in an impulsive noise environment, and FM0 encoding and Miller encoding were applied to the tag to analyze the error rate performance of the RFID system. As a result of analyzing the performance of the RFID system in Middleton's Class A impulsive noise channel, it was found that the larger the Gaussian noise to impulsive noise power ratio and the impulsive noise index, the more similar the characteristics to the Gaussian noise channel.

• Korean Journal of Radiology
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• v.23 no.10
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• pp.949-958
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• 2022

Objective: To investigate the feasibility of using a deep learning-based analysis of auscultation data to predict significant stenosis of arteriovenous fistulas (AVF) in patients undergoing hemodialysis requiring percutaneous transluminal angioplasty (PTA). Materials and Methods: Forty patients (24 male and 16 female; median age, 62.5 years) with dysfunctional native AVF were prospectively recruited. Digital sounds from the AVF shunt were recorded using a wireless electronic stethoscope before (pre-PTA) and after PTA (post-PTA), and the audio files were subsequently converted to mel spectrograms, which were used to construct various deep convolutional neural network (DCNN) models (DenseNet201, EfficientNetB5, and ResNet50). The performance of these models for diagnosing ≥ 50% AVF stenosis was assessed and compared. The ground truth for the presence of ≥ 50% AVF stenosis was obtained using digital subtraction angiography. Gradient-weighted class activation mapping (Grad-CAM) was used to produce visual explanations for DCNN model decisions. Results: Eighty audio files were obtained from the 40 recruited patients and pooled for the study. Mel spectrograms of "pre-PTA" shunt sounds showed patterns corresponding to abnormal high-pitched bruits with systolic accentuation observed in patients with stenotic AVF. The ResNet50 and EfficientNetB5 models yielded an area under the receiver operating characteristic curve of 0.99 and 0.98, respectively, at optimized epochs for predicting ≥ 50% AVF stenosis. However, Grad-CAM heatmaps revealed that only ResNet50 highlighted areas relevant to AVF stenosis in the mel spectrogram. Conclusion: Mel spectrogram-based DCNN models, particularly ResNet50, successfully predicted the presence of significant AVF stenosis requiring PTA in this feasibility study and may potentially be used in AVF surveillance.

• Information Systems Review
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• v.20 no.2
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• pp.21-37
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• 2018

Under ubiquitous work environment, innovative changes occur in work process with ICT. The work process for collaboration through mobile devices and network should be investigated. The research model consists of two major antecedents: autonomy and interdependence as a task characteristic and job satisfaction as ultimate consequence followed by work design theory. To elaborate work design theory, smartwork application (app) use, communication extent, and work-life balance were reviewed from the literature. Data were collected from three ICT firms, which adopted certain smartwork app, and a partial least squares analysis was made on 175 data points. The analysis results show that task interdependence exerts a statistically significant effect on the level of smartwork app usage. Communication extent directly affects job satisfaction and work-life balance. The remarkable point is that smartwork app usage does not affect employees' work-life balance; the former can only affect the latter indirectly by increasing communication extent. This study attempts to explain the organizational impact by considering smartwork app and the effects simultaneously. We proposed and empirically tested the extended work design theory including information technology and its environment. Based on the results, other theoretical and practical contributions are discussed at the end with limitations and further studies.

• 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.

• IMMUNE NETWORK
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• v.21 no.5
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• pp.34.1-34.16
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• 2021

Sjögren's syndrome (SS) is an autoimmune disease characterized by dryness of the mouth and eyes. The glandular dysfunction in SS involves not only T cell-mediated destruction of the glands but also autoantibodies against the type 3 muscarinic acetylcholine receptor or aquaporin 5 (AQP5) that interfere with the secretion process. Studies on the breakage of tolerance and induction of autoantibodies to these autoantigens could benefit SS patients. To break tolerance, we utilized a PmE-L peptide derived from the AQP5-homologous aquaporin of Prevotella melaninogenica (PmAqp) that contained both a B cell "E" epitope and a T cell epitope. Repeated subcutaneous immunization of C57BL/6 mice with the PmE-L peptide efficiently induced the production of Abs against the "E" epitope of mouse/human AQP5 (AQP5E), and we aimed to characterize the antigen specificity, the sequences of AQP5E-specific B cell receptors, and salivary gland phenotypes of these mice. Sera containing anti-AQP5E IgG not only stained mouse Aqp5 expressed in the submandibular glands but also detected PmApq and PmE-L by immunoblotting, suggesting molecular mimicry. Characterization of the AQP5E-specific autoantibodies selected from the screening of phage display Ab libraries and mapping of the B cell receptor repertoires revealed that the AQP5E-specific B cells acquired the ability to bind to the Ag through cumulative somatic hypermutation. Importantly, animals with anti-AQP5E Abs had decreased salivary flow rates without immune cell infiltration into the salivary glands. This model will be useful for investigating the role of anti-AQP5 autoantibodies in glandular dysfunction in SS and testing new therapeutics targeting autoantibody production.

• IMMUNE NETWORK
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• v.20 no.4
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• pp.32.1-32.15
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• 2020

Influenza virus is the major cause of seasonal and pandemic flu. Currently, oseltamivir, a potent and selective inhibitor of neuraminidase of influenza A and B viruses, is the drug of choice for treating patients with influenza virus infection. However, recent emergence of oseltamivir-resistant influenza viruses has limited its efficacy. Morin hydrate (3,5,7,2',4'-pentahydroxyflavone) is a flavonoid isolated from Morus alba L. It has antioxidant, anti-inflammatory, neuroprotective, and anticancer effects partly by the inhibition of the NF-κB signaling pathway. However, its effects on influenza virus have not been studied. We evaluated the antiviral activity of morin hydrate against influenza A/Puerto Rico/8/1934 (A/PR/8; H1N1) and oseltamivir-resistant A/PR/8 influenza viruses in vitro. To determine its mode of action, we carried out time course experiments, and time of addition, hemolysis inhibition, and hemagglutination assays. The effects of the co-administration of morin hydrate and oseltamivir were assessed using the murine model of A/PR/8 infection. We found that morin hydrate reduced hemagglutination by A/PR/8 in vitro. It alleviated the symptoms of A/PR/8-infection, and reduced the levels of pro-inflammatory cytokines and chemokines, such as TNF-α and CCL2, in infected mice. Co-administration of morin hydrate and oseltamivir phosphate reduced the virus titers and attenuated pulmonary inflammation. Our results suggest that morin hydrate exhibits antiviral activity by inhibiting the entry of the virus.

• Journal of the Economic Geographical Society of Korea
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• v.26 no.4
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• pp.458-476
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• 2023

This study analyzes previous research on 'The Self-Governance of the Commons' to overcome 'The Tragedy of the Commons', and derives elements for successful commons management. These factors are compared and analyzed with the social and economic attributes of the Jeju Haenyeo community, a successful community self-governance model. In addition, in the recently changing environment, it is revealed whether this internal community mechanism can be useful in the future. The goal is to reveal what social and economic factors will help the sustainability of the Jeju haenyeo community in the future. As a result of analyzing the internal operating mechanism of the Jeju haenyeo community, the production and distribution system that improves trust and reciprocity, the inherent sense of community, the division of roles between formal and informal organizations, and the institutionalized explicit and implicit norms within the organization served as internal and external strengths of community sustainability. However, the closure of the network, the crisis of productivity, the weakening of homogeneity, and the emergence of new subjects acted as internal and external weaknesses. In conclusion, for the sustainability of the Jeju Haenyeo community, it is necessary to reorganize the reproductive function of labor using the haenyeo school, to maintain clarity on the subject of livelihood and cultural transmission, and guarantee the income of Haenyeo.

• Journal of the Society of Disaster Information
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• v.20 no.1
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• pp.222-231
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• 2024

Purpose: The purpose of this study is to study how to activate the use of public transportation by identifying the main factors that reduce the use of public transportation due to external influences such as COVID-19 infectious diseases. Method: This study analyzed the connection between the traffic behavior and the characteristics of public transportation use in the metropolitan area changed by COVID-19 with COVID-19 indicators, and analyzed social and environmental factors affecting traffic. Results: It was analyzed that the traffic behavior in the metropolitan area moves from commercial areas to tourist resort areas, the number of COVID-19 deaths affects the use of public transportation, and the lower the deviation between population density, agricultural and forestry areas, and gender ratios due to social and environmental factors, the more significant differences are shown. Conclusion: In the future, it will be able to be activated as a basic analysis model for revitalizing the city's transportation system, regional bases, and various social and economic indicators, such as quarantine of public transportation and social distancing, and can be used as basic data for establishing public transport policy directions according to major influencing factors.

• IMMUNE NETWORK
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• v.24 no.3
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• pp.15.1-15.18
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• 2024

Osteoarthritis (OA) involves cartilage degeneration, thereby causing inflammation and pain. Cardiovascular diseases, such as dyslipidemia, are risk factors for OA; however, the mechanism is unclear. We investigated the effect of dyslipidemia on the development of OA. Treatment of cartilage cells with low-density lipoprotein (LDL) enhanced abnormal autophagy but suppressed normal autophagy and reduced the activity of transcription factor EB (TFEB), which is important for the function of lysosomes. Treatment of LDL-exposed chondrocytes with rapamycin, which activates TFEB, restored normal autophagy. Also, LDL enhanced the inflammatory death of chondrocytes, an effect reversed by rapamycin. In an animal model of hyperlipidemia-associated OA, dyslipidemia accelerated the development of OA, an effect reversed by treatment with a statin, an anti-dyslipidemia drug, or rapamycin, which activates TFEB. Dyslipidemia reduced the autophagic flux and induced necroptosis in the cartilage tissue of patients with OA. The levels of triglycerides, LDL, and total cholesterol were increased in patients with OA compared to those without OA. The C-reactive protein level of patients with dyslipidemia was higher than that of those without dyslipidemia after total knee replacement arthroplasty. In conclusion, oxidized LDL, an important risk factor of dyslipidemia, inhibited the activity of TFEB and reduced the autophagic flux, thereby inducing necroptosis in chondrocytes.

• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.45-52
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• 2014

The Ubiquitous-City (U-City) is a smart or intelligent city to satisfy human beings' desire to enjoy IT services with any device, anytime, anywhere. It is a future city model based on Internet of everything or things (IoE or IoT). It includes a lot of video cameras which are networked together. The networked video cameras support a lot of U-City services as one of the main input data together with sensors. They generate huge amount of video information, real big data for the U-City all the time. It is usually required that the U-City manipulates the big data in real-time. And it is not easy at all. Also, many times, it is required that the accumulated video data are analyzed to detect an event or find a figure among them. It requires a lot of computational power and usually takes a lot of time. Currently we can find researches which try to reduce the processing time of the big video data. Cloud computing can be a good solution to address this matter. There are many cloud computing methodologies which can be used to address the matter. MapReduce is an interesting and attractive methodology for it. It has many advantages and is getting popularity in many areas. Video cameras evolve day by day so that the resolution improves sharply. It leads to the exponential growth of the produced data by the networked video cameras. We are coping with real big data when we have to deal with video image data which are produced by the good quality video cameras. A video surveillance system was not useful until we find the cloud computing. But it is now being widely spread in U-Cities since we find some useful methodologies. Video data are unstructured data thus it is not easy to find a good research result of analyzing the data with MapReduce. This paper presents an analyzing system for the video surveillance system, which is a cloud-computing based video data management system. It is easy to deploy, flexible and reliable. It consists of the video manager, the video monitors, the storage for the video images, the storage client and streaming IN component. The "video monitor" for the video images consists of "video translater" and "protocol manager". The "storage" contains MapReduce analyzer. All components were designed according to the functional requirement of video surveillance system. The "streaming IN" component receives the video data from the networked video cameras and delivers them to the "storage client". It also manages the bottleneck of the network to smooth the data stream. The "storage client" receives the video data from the "streaming IN" component and stores them to the storage. It also helps other components to access the storage. The "video monitor" component transfers the video data by smoothly streaming and manages the protocol. The "video translator" sub-component enables users to manage the resolution, the codec and the frame rate of the video image. The "protocol" sub-component manages the Real Time Streaming Protocol (RTSP) and Real Time Messaging Protocol (RTMP). We use Hadoop Distributed File System(HDFS) for the storage of cloud computing. Hadoop stores the data in HDFS and provides the platform that can process data with simple MapReduce programming model. We suggest our own methodology to analyze the video images using MapReduce in this paper. That is, the workflow of video analysis is presented and detailed explanation is given in this paper. The performance evaluation was experiment and we found that our proposed system worked well. The performance evaluation results are presented in this paper with analysis. With our cluster system, we used compressed $1920{\times}1080(FHD)$ resolution video data, H.264 codec and HDFS as video storage. We measured the processing time according to the number of frame per mapper. Tracing the optimal splitting size of input data and the processing time according to the number of node, we found the linearity of the system performance.