• Microbiology and Biotechnology Letters
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• v.48 no.4
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• pp.506-514
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• 2020

4-Hydroxybenzyl alcohol (4-HB alcohol) is one of the major active components of Gastrodia elata Blume, with beneficial effects on neurological disorders such as headache, convulsive behavior, and dizziness. Here, we developed a metabolically engineered Corynebacterium glutamicum strain able to produce 4-HB alcohol from 4-hydroxybenzoate (4-HBA). First, the strain APS963 was obtained from the APS809 strain via the insertion of aroK from Methanocaldococcus jannaschii into the NCgl2922-deleted locus. As carboxylic acid reductase from Nocardia iowensis catalyzes the reduction of 4HBA to 4-hydroxybenzaldehyde (4-HB aldehyde), we then introduced a codon-optimized car gene into the genome of APS963, generating the GAS177 strain. Then, we deleted creG coding for a putative short-chain dehydrogenase and inserted ubiCpr encoding a product-resistant chorismate-pyruvate lyase into the pcaHG-deleted locus. The resulting engineered GAS355 strain accumulated 2.3 g/l 4-HB alcohol with 0.32 g/l 4-HBA and 0.3 g/l 4-HB aldehyde as byproducts from 8% glucose after 48 h of culture.

• Knowledge Management Research
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• v.21 no.4
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• pp.1-19
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• 2020

Recently, implementation of telemedicine in Korea has been conducted as one of pilot projects with public health doctors. To manage and expand telemedicine services sustainably, it is necessary to understand the positions of various stakeholders. The purpose of this study is to observe and describe major phenomena around stakeholders related to telemedicine to capture major issues following the implementation of telemedicine. This study interviewed 24 research participants, including public health doctors who participated in the pilot project for telemedicine services. As a result of analyzing the interview manuscript using the grounded theory method, totally 68 concepts were derived at the coding stage, and 19 sub-categories, 11 categories, were proposed through the categorization process. In addition, through the elicitation concepts and categories of this study, conflicts among stakeholders were explained, conceptual models that presented the process of resolving conflicts, and five types of stakeholders were proposed. This study has theoretical and practical implications in that it captures and describes important issues from stakeholders in telemedicine services. The results of this study are expected to give some hints for problem solving to all of the stakeholders who wish to successfully build telemedicine services.

• Biomolecules & Therapeutics
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• v.29 no.2
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• pp.234-247
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• 2021

We used a heterozygous gene deletion library of fission yeasts comprising all essential and non-essential genes for a microarray screening of target genes of the antifungal terbinafine, which inhibits ergosterol synthesis via the Erg1 enzyme. We identified 14 heterozygous strains corresponding to 10 non-essential [7 ribosomal-protein (RP) coding genes, spt7, spt20, and elp2] and 4 essential genes (tif302, rpl2501, rpl31, and erg1). Expectedly, their erg1 mRNA and protein levels had decreased compared to the control strain SP286. When we studied the action mechanism of the non-essential target genes using cognate haploid deletion strains, knockout of SAGA-subunit genes caused a down-regulation in erg1 transcription compared to the control strain ED668. However, knockout of RP genes conferred no susceptibility to ergosterol-targeting antifungals. Surprisingly, the RP genes participated in the erg1 transcription as components of repressor complexes as observed in a comparison analysis of the experimental ratio of erg1 mRNA. To understand the action mechanism of the interaction between the drug and the novel essential target genes, we performed isobologram assays with terbinafine and econazole (or cycloheximide). Terbinafine susceptibility of the tif302 heterozygous strain was attributed to both decreased erg1 mRNA levels and inhibition of translation. Moreover, Tif302 was required for efficacy of both terbinafine and cycloheximide. Based on a molecular modeling analysis, terbinafine could directly bind to Tif302 in yeasts, suggesting Tif302 as a potential off-target of terbinafine. In conclusion, this genome-wide screening system can be harnessed for the identification and characterization of target genes under any condition of interest.

• Journal of Food Hygiene and Safety
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• v.35 no.6
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• pp.607-617
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• 2020

Human bio-monitoring (HBM) data is a very important resource for tracking total exposure and concentrations of a parent chemical or its metabolites in human biomarkers. However, until now, it was difficult to execute the integration of different types of HBM data due to incompatibility problems caused by gaps in study design, chemical description and coding system between different sources in Korea. In this study, we presented a standardized code system and HBM knowledge model (KM) based on relational database modeling methodology. For this purpose, we used 11 raw datasets collected from the Ministry of Food and Drug Safety (MFDS) between 2006 and 2018. We then constructed the HBM database (DB) using a total of 205,491 concentration-related data points for 18,870 participants and 86 chemicals. In addition, we developed a summary report-type statistical analysis program to verify the inputted HBM datasets. This study will contribute to promoting the sustainable creation and versatile utilization of big-data for HBM results at the MFDS.

• Journal of the Korea Convergence Society
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• v.12 no.8
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• pp.215-228
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• 2021

The purpose of this qualitative study was to identify cultural factors among older Americans that could influence them to accept new welfare technologies. This study also explored how social and cultural-based plans could increase the acceptability of welfare technologies for improving the quality of life of older adults in the future. In-depth interviews were conducted with ten professionals who work with older adults. The collected interview data were subsequently analyzed using a two-cycle open coding process. The data analysis generated 29 codes that were organized into 7 primary codes, or categories, and 22 secondary codes nested within the primary codes. Several themes were identified: individualism, family-oriented culture, pragmatism, low-context culture, privacy, fun-seeking culture, and a less hierarchical culture. These findings will inform the development of a future survey to examine the relationship between older adults' intentions when using technology and socio-cultural factors in community settings. In order to explore the different impact levels of the cultural factors found in this study, the future study will need to include measures for identifying socio-cultural variations among individuals in one country or across countries.

• The Journal of the Korea Contents Association
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• v.21 no.5
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• pp.488-498
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• 2021

This study applied Flipped Learning teaching and learning method to Basics Cooking Practice Subject using YouTube. The purpose of this study is to investigate whether the curriculum is properly progressing by grasping the effects of before and after learning and analyzing learners' subjectivity through the learning process. The investigation period was conducted from August 01, 2020 to September 10, 2020. According to the research design of Q Methodology, it was divided into five stages: Q sample selection, P sample selection, Q sorting, coding and recruiting, conclusion and discussion. As a result of the analysis, the first type (N=5): Prior Learning effect, the second type (N=7): Simulation practice effect, and the third type (N=3): self-efficacy effect. As a result, by applying the flipped learning teaching method of the Basics Cooking Practice Subject using YouTube, positive effects such as inducing interest in the class and increasing confidence were found in active learners, but some learners lacked understanding of the system of the class operation method. However, the lack of number of training sessions compared to other subjects is considered to be a solution to be solved later.

• Journal of Broadcast Engineering
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• v.27 no.2
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• pp.216-227
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• 2022

The MPEG-I (Immersive) group is working on a standardization project for immersive video that provides 6 degrees of freedom (6DoF). The MPEG Immersion Video (MIV) standard technology is intended to provide limited 6DoF based on depth map-based image rendering (DIBR) technique. Many efficient coding methods have been suggested for MIV, but efficient transmission strategies have received little attention in MPEG-I. This paper proposes group-based adaptive rendering method for immersive video streaming. Each group can be transmitted independently using group-based encoding, enabling adaptive transmission depending on the user's viewport. In the rendering process, the proposed method derives weights of group for view synthesis and allocate high quality bitstream according to a given viewport. The proposed method is implemented through the Test Model for Immersive Video (TMIV) test model. The proposed method demonstrates 17.0% Bjontegaard-delta rate (BD-rate) savings on the peak signalto-noise ratio (PSNR) and 14.6% on the Immersive Video PSNR(IV-PSNR) in terms of various end-to-end evaluation metrics in the experiment.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.33 no.6
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• pp.257-264
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• 2021

This study established a numerical model capable of calculating the wave overtopping rate of coastal structures by nonlinear irregular waves using the FUNWAVE-TVD model, a fully nonlinear Boussinesq equation model. Here, a numerical model was established by coding the mean value approach equations of EurOtop (2018) and empirical formula by Goda (2009), and adding them as subroutines of the FUNWAVE-TVD model. The verification of the model was performed by numerically calculating the wave overtopping rate of nonlinear irregular waves on vertical wall structures and comparing them with the experimental results presented in EurOtop (2018). As a result of the verification, the numerical calculation result according to the EurOtop equation of this model was very well matched with the experimental result in all relative freeboard (R_c/H_mo) range under non-impulsive wave conditions, and the numerical calculation result of empirical formula was evaluated slightly smaller than the experimental result in R_c/H_mo < 0.8 and slightly larger than the experimental result in R_c/H_mo > 0.8. The results of this model were well represented in both the exponential curve and the power curve under impulsive wave conditions. Therefore, it was confirmed that this numerical model can simulate the wave overtopping rate caused by nonlinear irregular waves in an vertical wall structure.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.1
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• pp.56-61
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• 2022

In this paper, we classify and present AI algorithms and natural language processing methods used in chatbots. A framework that can be used to implement a chatbot is also described. A chatbot is a system with a structure that interprets the input string by constructing the user interface in a conversational manner and selects an appropriate answer to the input string from the learned data and outputs it. However, training is required to generate an appropriate set of answers to a question and hardware with considerable computational power is required. Therefore, there is a limit to the practice of not only developing companies but also students learning AI development. Currently, chatbots are replacing the existing traditional tasks, and a practice course to understand and implement the system is required. RNN and Char-CNN are used to increase the accuracy of answering questions by learning unstructured data by applying technologies such as deep learning beyond the level of responding only to standardized data. In order to implement a chatbot, it is necessary to understand such a theory. In addition, the students presented examples of implementation of the entire system by utilizing the methods that can be used for coding education and the platform where existing developers and students can implement chatbots.

• Journal of Broadcast Engineering
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• v.27 no.3
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• pp.318-331
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• 2022

With the recent development of hardware computing devices and software based frameworks, machine tasks using deep learning networks are expected to be utilized in various industrial fields and personal IoT devices. However, in order to overcome the limitations of high cost device for utilizing the deep learning network and that the user may not receive the results requested when only the machine task results are transmitted from the server, Collaborative Intelligence (CI) proposed the transmission of feature maps as a solution. In this paper, an efficient compression method for feature maps with vast data sizes to support the CI paradigm was analyzed and presented through experiments. This method increases redundancy by applying feature map reordering to improve compression efficiency in traditional video codecs, and proposes a feature map method that improves compression efficiency and maintains the performance of machine tasks by simultaneously utilizing image compression format and video compression format. As a result of the experiment, the proposed method shows 14.29% gain in BD-rate of BPP and mAP compared to the feature compression anchor of MPEG-VCM.