• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.175-181
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• 2022

COVID-19 is an acute respiratory syndrome that affects the host's breathing and respiratory system. The novel disease's first case was reported in 2019 and has created a state of emergency in the whole world and declared a global pandemic within months after the first case. The disease created elements of socioeconomic crisis globally. The emergency has made it imperative for professionals to take the necessary measures to make early diagnoses of the disease. The conventional diagnosis for COVID-19 is through Polymerase Chain Reaction (PCR) testing. However, in a lot of rural societies, these tests are not available or take a lot of time to provide results. Hence, we propose a COVID-19 classification system by means of machine learning and transfer learning models. The proposed approach identifies individuals with COVID-19 and distinguishes them from those who are healthy with the help of Deep Visual Embeddings (DVE). Five state-of-the-art models: VGG-19, ResNet50, Inceptionv3, MobileNetv3, and EfficientNetB7, were used in this study along with five different pooling schemes to perform deep feature extraction. In addition, the features are normalized using standard scaling, and 4-fold cross-validation is used to validate the performance over multiple versions of the validation data. The best results of 88.86% UAR, 88.27% Specificity, 89.44% Sensitivity, 88.62% Accuracy, 89.06% Precision, and 87.52% F1-score were obtained using ResNet-50 with Average Pooling and Logistic regression with class weight as the classifier.

• Journal of Korea Trade
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• v.27 no.3
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• pp.87-102
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• 2023

Purpose - Although the importance and necessity of "sustainable supply chain management (SCM)" is emphasized, it is often not realized due to conflicting results, the long time required, and large-scale changes brought about by sustainability. This study used the innovation resistance model to confirm the influence of sustainable SCM innovation resistance factors and dynamic capabilities on adoption intentions. This approach made it possible to understand the factors that hinder adoption of sustainability practices and to identify the relationships among influencing factors. It should also help to establish effective policies or strategies. Design/methodology - Through a literature review, the characteristics of sustainable SCM were classified into relative advantage, compatibility, perceived risk, and complexity. The effects of these innovation characteristics on innovation resistance in sustainable SCM and the effects of innovation resistance on adoption intentions were confirmed. In addition, the effects of SCM capabilities on innovation resistance and adoption intentions were analyzed, and the mediating effect of innovation resistance was analyzed. Findings - Compatibility, perceived risk, and flexibility had significant effects on innovation resistance. In turn, innovation resistance had a significant effect on adoption intention, and flexibility had a significant effect on intention to adopt. A partial mediating effect of resistance to innovation was confirmed. Originality/value - Although many previous studies have acknowledged trade-offs with sustainability, most sustainable SCM studies dealt with the correlations among positive drivers of adoption, practices, and performance. This study confirmed the process of accepting sustainable SCM innovation in a single model and is expected to serve as a cornerstone for future sustainable SCM adoption studies. In addition, our findings should help establish effective policies or strategies to activate SSCM adoption by identifying the factors that hinder the adoption of sustainable SCM.

• Journal of Animal Science and Technology
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• v.65 no.1
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• pp.160-174
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• 2023

The purpose of this study was to compare marbling score, meat quality, juiciness, sarcomere length, and skeletal muscle satellite cell (SMSC) growth and related gene expression between Woori black pig (WB) and the Landrace, Yorkshire, and Duroc (LYD) crossbreed at different body weights (b.w.). WB was developed to improve meat quality and growth efficiency by crossbreeding Duroc with Korean native black pig. A total of 24 pigs were sacrificed when their b.w. reached about 50, 75, 100, and 120 kg. SMSC were isolated from the femoris muscles, and muscle and adipose tissues were sampled from the middle and the subcutaneous part of the femoris of hind legs, respectively. Expression levels of genes including Myoblast determination protein 1 (MyoD), Paired box gene 3 (Pax3), Myosin heavy chain (MyHC), and Myogenin, which are responsible for the growth and development of SMSC, were higher in LYD than the WB. Muscle growth inhibitor myostatin (MSTN), however, was expressed more in WB compared to LYD (p < 0.01). Numbers of SMSC extracted from femoris muscle of LYD at 50, 75, 100, and 120 kg b.w. were 8.5 ± 0.223, 8.6 ± 0.245, 7.2 ± 0.249, and 10.9 ± 0.795, and those from WB were 6.2 ± 0.32, 6.2 ± 0.374, 5.3 ± 0.423, and 17.1 ± 0.315, respectively. Expression of adipogenic genes in adipose tissue including CCAAT/enhancer-binding protein (CEBP)-β, peroxisome proliferator activated receptor (PPAR)-γ, and fatty acid synthase (FASN), were greater in WB when compared with LYD (p < 0.01). Results from the current study suggest that different muscle cell numbers between 2 different breeds might be affected by related gene expression and this warrants further investigation on other growth factors regulating animal growth and development.

• Journal of Korean Clinical Nursing Research
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• v.15 no.1
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• pp.149-165
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• 2009

Purpose: This study was done to identify the causes of turnover in nursing staff in small and medium‐size hospitals and prepare measures to decrease turnover. Nurses in these hospitals were surveyed focusing on their nursing activities, reasons for turnover, and content of their work. Method: A mail survey of hospitals with 300 beds or less was conducted using a questionnaire including items on the current state of nursing, performance of nursing tasks, turnover of nurses, working conditions, and supports and policies related to insufficient number of nurses. Results: The average number of nurses per 100 beds was 37.5, 3.3 less than the prescribed level of 40.8. The turnover rate was higher when the level of remuneration for nursing care was low, and the most frequent reason for nurses leaving was 'move to another hospital', showing that there is a continuous chain of moves for nurses. Other frequent reasons were situations related to working conditions such as childbirth, child care, irregular working hours, night work, and low wages. Conclusion: To guarantee adequate nursing coverage in these hospitals, working conditions for nurses should be improved, including higher wages, a more flexible work system, and installation and operation of 24-hour child care facilities.

• Smart Structures and Systems
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• v.29 no.5
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• pp.661-675
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• 2022

In this paper, an electric vehicle drives with efficient control and low cost hardware using four quadrant DC converter with Permanent Magnet Direct Current (PMDC) motor fed by DC boost converter is presented. The main idea of this work is to improve the energy efficiency of the conversion chain of an electric vehicle by inserting a boost converter between the battery and the four quadrant-DC motor chopper assembly. Consequently, this method makes it possible to maintain the amplification gain of the 4 quadrant chopper constant regardless of the battery voltage drop and even in the presence of a fault in the battery. One of the most important control problems is control under heavy uncertainty conditions. The higher order sliding mode control technique is introduced for the adjustment of DC bus voltage and mechanical motor speed. To implement the proposed approach in the automotive field, experimental tests were carried out. The performances obtained show the usefulness of this system for a better energy management of an electric vehicle and an ideal control under different operating conditions and constraints, mostly at nominal operation, in the presence of a load torque, when reversing the direction of rotation of the motor speed and even in case of battery chamber failure. The whole system has been tested experimentally and its performance has been analyzed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.12
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• pp.1794-1799
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• 2022

Recently, the increasing number of overloaded vehicles on the road poses a risk to traffic safety, such as falling objects, road damage, and chain collisions due to the abnormal weight distribution, and can cause great damage once an accident occurs. therefore we propose to build an object detection-based AI model to identify overloaded vehicles that cause such social problems. In addition, we present a simple yet effective method to construct an object detection model for the large-scale vehicle images. In particular, we utilize the large-scale of vehicle image sets provided by open AI-Hub, which include the overloaded vehicles. We inspected the specific features of sizes of vehicles and types of image sources, and pre-processed these images to train a deep learning-based object detection model. Also, we propose an integrated system for tracking the detected vehicles. Finally, we demonstrated that the detection performance of the overloaded vehicle was improved by about 23% compared to the one using raw data.

• Korean Journal of Veterinary Service
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• v.46 no.2
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• pp.123-135
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• 2023

Feline calicivirus (FCV) is considered the main viral pathogen of feline upper respiratory tract disease (URTD). The frequent mutations of field FCV strains result in the poor diagnostic sensitivity of previously developed molecular diagnostic assays. In this study, a more sensitive real-time reverse transcription-polymerase chain reaction (qRT-PCR) assay was developed for broad detection of currently circulating FCVs and comparatively evaluated the diagnostic performance with previously developed qRT-PCR assay using clinical samples collected from Korean cat populations. The developed qRT-PCR assay specifically amplified the FCV p30 gene with a detection limit of below 10 copies/reaction. The assay showed high repeatability and reproducibility, with coefficients of intra-assay and inter-assay variation of less than 2%. Based on the clinical evaluation using 94 clinical samples obtained from URTD-suspected cats, the detection rate of FCV by the developed qRT-PCR assay was 47.9%, which was higher than that of the previous qRT-PCR assay (43.6%). The prevalence of FCV determined by the new qRT-PCR assay in this study was much higher than those of previous Korean studies determined by conventional RT-PCR assays. Due to the high sensitivity, specificity, and accuracy, the new qRT-PCR assay developed in this study will serve as a promising tool for etiological and epidemiological studies of FCV circulating in Korea. Furthermore, the prevalence data obtained in this study will contribute to expanding knowledge about the epidemiology of FCV in Korea.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2023.04a
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• pp.62-62
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• 2023

Zanthoxylum piperitum ("chopi" in Korean) has been used as traditional medicinal plants with high anti-inflammatory, antioxidant, and antifungal activities. The aims of the study were to identify marker compounds and to investigate metabolites variation of chopi according to different parts and harvest times. Every month from June to September, chopi were harvested with three different parts: leaves, leaf-twig mixtures, twigs. Using liquid chromatography-tandem mass spectrometry (LC-MS/MS), two main marker compounds (quercitrin and quercetin-3-O-glucoside) were characterized in 70% ethanol extracts of chopi. Quantification of the two marker compounds were subsequently conducted by high performance liquid chromatography (HPLC), representing that contents of these compounds were higher in leaves and leaf-twig mixtures rather than twigs. For the comprehensive analysis of metabolites associated with production of marker compounds, 35 primary metabolites were identified using gas chromatography-mass spectrometry (GC-MS). Multivariate analysis results represented that plant parts were main contributors to the separation of chopi. However, significant differences were not observed between leaves and leaf-twig mixtures samples. The partial least square (PLS) predictive model revealed that monosaccharides (fructose, galactose, glucose, mannose, xylose) and branched-chain amino acids (isoleucine, valine, leucine) were important determinants for the production of marker compounds together with alanine, inositol, GABA, and theronic acid. This study could be extended to stabilize and utilize chopi as an industrial material, as well as to find good candidates with various nutritional traits.

• Korea Trade Review
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• v.48 no.3
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• pp.243-262
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• 2023

This study provides a systematic review of smart trade contracts, examining the research trends and theoretical background of utilizing smart contracts and blockchain technology for the digitalization and automation of trade contracts. Smart trade contracts are a concept that applies the automated contract system based on blockchain to trade-related transactions. The study analyzes the technical and legal challenges and proposes solutions. The technical aspect covers the development of smart contract platforms, scalability and performance improvements of blockchain networks, and security and privacy concerns. The legal aspect addresses the legal enforceability of smart contracts, automatic execution of contract conditions, and the responsibilities and obligations of contract parties. Smart trade contracts have been found to have applications in various industries such as international trade, supply chain management, finance, insurance, and energy, contributing to the ease of trade finance, efficiency of supply chains, and business model innovation. However, challenges remain in terms of legal regulations, interaction with existing legal frameworks, and technological aspects. Further research is needed, including empirical studies, business model innovation, resolution of legal issues, security and privacy considerations, standardization and collaboration, and user experience studies to address these challenges and explore additional aspects of smart trade contracts.

• Nutrition Research and Practice
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• v.17 no.5
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• pp.827-843
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• 2023

BACKGROUND/OBJECTIVES: Mitochondrial DNA leakage leads to inflammatory responses via endosome activation. This study aims to evaluate whether the perennial grass water extract (Pogonatherum panicum) ameliorate mitochondrial DNA (mtDNA) leakage. MATERIALS/METHODS: The major bioactive constituents of P. paniceum (PPW) were investigated by high-performance liquid chromatography, after which their antioxidant activities were assessed. In addition, RAW 264.7 macrophages were stimulated with lipopolysaccharide, resulting in mitochondrial damage. Quantitative polymerase chain reaction and enzyme-linked immunosorbent assay were used to examine the gene expression and cytokines. RESULTS: Our results showed that PPW extract-treated activated cells significantly decrease reactive oxygen species and nitric oxide levels by reducing the p2^phox and iNOS expression and lowering cytokine-encoding genes, including IL-6, TNF-α, IL-1β, PG-E2 and IFN-γ relative to the lipopolysaccharide (LPS)-activated macrophages. Furthermore, we observed that LPS enhanced the mtDNA leaked into the cytoplasm, increasing the transcription of Tlr9 and signaling both MyD88/Irf7-dependent interferon and MyD88/NF-κb p65-dependent inflammatory cytokine mRNA expression but which was alleviated in the presence of PPW extract. CONCLUSIONS: Our data show that PPW extract has antioxidant and anti-inflammatory activities by facilitating mtDNA leakage and lowering the Tlr9 expression and signaling activation.