• Animal Bioscience
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• v.35 no.1
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• pp.115-125
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• 2022

Objective: Intramuscular fat (IMF) is a critical economic indicator of pork quality. Studies on IMF among different pig breeds have been performed via high-throughput sequencing, but comparisons within the same pig breed remain unreported. Methods: This study was performed to explore the gene profile and identify candidate long noncoding RNA (lncRNAs) and mRNAs associated with IMF deposition among Laiwu pigs with different IMF contents. Based on the longissimus dorsi muscle IMF content, eight pigs from the same breed and management were selected and divided into two groups: a high IMF (>12%, H) and low IMF group (<5%, L). Whole-transcriptome sequencing was performed to explore the differentially expressed (DE) genes between these two groups. Results: The IMF content varied greatly among Laiwu pig individuals (2.17% to 13.93%). Seventeen DE lncRNAs (11 upregulated and 6 downregulated) and 180 mRNAs (112 upregulated and 68 downregulated) were found. Gene Ontology analysis indicated that the following biological processes played an important role in IMF deposition: fatty acid and lipid biosynthetic processes; the extracellular signal-regulated kinase cascade; and white fat cell differentiation. In addition, the peroxisome proliferator-activated receptor, phosphatidylinositol-3-kinase-protein kinase B, and mammalian target of rapamycin pathways were enriched in the pathway analysis. Intersection analysis of the target genes of DE lncRNAs and mRNAs revealed seven candidate genes associated with IMF accumulation. Five DE lncRNAs and 20 DE mRNAs based on the pig quantitative trait locus database were identified and shown to be related to fat deposition. The expression of five DE lncRNAs and mRNAs was verified by quantitative real time polymerase chain reaction (qRT-PCR). The results of qRT-PCR and RNA-sequencing were consistent. Conclusion: These results demonstrated that the different IMF contents among pig individuals may be due to the DE lncRNAs and mRNAs associated with lipid droplets and fat deposition.

• Journal of Veterinary Science
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• v.23 no.4
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• pp.55.1-55.12
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• 2022

Background: ASF was first reported in Kenya in 1910 in 1921. In China, ASF spread to 31 provinces including Henan and Jiangsu within six months after it was first reported on August 3, 2018. The epidemic almost affected the whole China, causing direct economic losses of tens of billions of yuan. Cause great loss to our pig industry. As ELISA is cheap and easy to operate, OIE regards it as the preferred serological method for ASF detection. P54 protein has good antigenicity and is an ideal antigen for detection. Objective: To identify a conservative site in the African swine fever virus (ASFV) p54 protein and perform a Cloth-enzyme-linked immunosorbent assay (ELISA) for detecting the ASFV antibody in order to reduce risks posed by using the live virus in diagnostic assays. Method: We used bioinformatics methods to predict the antigen epitope of the ASFV p54 protein in combination with the antigenic index and artificially synthesized the predicted antigen epitope peptides. Using ASFV-positive serum and specific monoclonal antibodies (mAbs), we performed indirect ELISA and blocking ELISA to verify the immunological properties of the predicted epitope polypeptide. Results: The results of our prediction revealed that the possible antigen epitope regions were A23-29, A36-45, A72-94, A114-120, A124-130, and A137-150. The indirect ELISA showed that the peptides A23-29, A36-45, A72-94, A114-120, and A137-150 have good antigenicity. Moreover, the A36-45 polypeptide can react specifically with the mAb secreted by hybridoma cells, and its binding site contains a minimum number of essential amino acids in the sequence 37DIQFINPY44. Conclusions: Our study confirmed a conservative antigenic site in the ASFV p54 protein and its amino acid sequence. A competitive ELISA method for detecting ASFV antibodies was established based on recombinant p54 and matching mAb. Moreover, testing the protein sequence alignment verified that the method can theoretically detect antibodies produced by pigs affected by nearly all ASFVs worldwide.

• Journal of Korea Water Resources Association
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• v.55 no.9
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• pp.657-668
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• 2022

With the occurrence of localized heavy rain while river flow has increased, both flow and rainfall cause riverside flood damages. As the degree of damage varies according to the level of social and economic impact, it is required to secure sufficient forecast lead time for flood response in areas with high population and asset density. In this study, the author established a flood risk matrix using ensemble rainfall runoff modeling and evaluated its applicability in order to increase the damage reduction effect by securing the time required for flood response. The flood risk matrix constructs the flood damage impact level (X-axis) using flood damage data and predicts the likelihood of flood occurrence (Y-axis) according to the result of ensemble rainfall runoff modeling using LENS rainfall data and as well as probabilistic forecasting. Therefore, the author introduced a method for determining the impact level of flood damage using historical flood damage data and quantitative flood damage assessment methods. It was compared with the existing flood warning data and the damage situation at the flood warning points in the Taehwa River Basin and the Hyeongsan River Basin in the Nakdong River Region. As a result, the analysis showed that it was possible to predict the time and degree of flood risk from up to three days in advance. Hence, it will be helpful for damage reduction activities by securing the lead time for flood response.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.141-148
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• 2022

The development of the education system and the labor market today requires new conditions for unification and functioning, the introduction of an innovative culture in the field of Education. The construction of modern management of innovative development of a higher education institution requires consideration of the existing theoretical, methodological and practical planes on which its formation is based. The purpose of the article is to substantiate the modern paradigm of organizing the mechanism of managing the innovative development of higher education institutions. Innovation in education is represented not only by the final product of applying novelty in educational and managerial processes in order to qualitatively improve the subject and objects of management and obtain economic, social, scientific, technical, environmental and other effects, but also by the procedure for their constant updating. The classification of innovations in education is presented. Despite the positive developments in the development of Education, numerous problems remain in this area, which is discussed in the article. The concept of innovative development of higher education institutions is described, which defines the prerequisites, goals, principles, tasks and mechanisms of university development for a long-term period and should be based on the following principles: scientific, flexible, efficient and comprehensive. The role of the motivational component of the mechanism of innovative development of higher education institutions is clarified, which allows at the strategic level to create an innovative culture and motivation of innovative activity of each individual, to make a choice of rational directions for solving problems, at the tactical level - to form motives for innovative activity in the most effective directions, at the operational level - to monitor the formation of a system of motives and incentives, to adjust the directions of motivation. The necessity of the functional component of the mechanism, which consists in determining a set of steps and management decisions aimed at achieving certain goals of innovative development of higher education institutions, is proved. The monitoring component of the mechanism is aimed at developing a special system for collecting, processing, storing and distributing information about the stages of development of higher education institutions, prediction based on the objective data on the dynamics and main trends of its development, and elaboration of recommendations.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.2
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• pp.48-55
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• 2022

The color image of the brand comes first and is an important visual element that leads consumers to the consumption of the product. To express more effectively what the brand wants to convey through design, the printing market is striving to print accurate colors that match the intention. In 'offset printing' mainly used in printing, colors are often printed in CMYK (Cyan, Magenta, Yellow, Key) colors. However, it is possible to print more accurate colors by making ink of the desired color instead of dotting CMYK colors. The resulting ink is called 'spot color' ink. Spot color ink is manufactured by repeating the process of mixing the existing inks. In this repetition of trial and error, the manufacturing cost of ink increases, resulting in economic loss, and environmental pollution is caused by wasted inks. In this study, a deep learning algorithm to predict printed spot colors was designed to solve this problem. The algorithm uses a single DNN (Deep Neural Network) model to predict printed spot colors based on the information of the paper and the proportions of inks to mix. More than 8,000 spot color ink data were used for learning, and all color was quantified by dividing the visible light wavelength range into 31 sections and the reflectance for each section. The proposed algorithm predicted more than 80% of spot color inks as very similar colors. The average value of the calculated difference between the actual color and the predicted color through 'Delta E' provided by CIE is 5.29. It is known that when Delta E is less than 10, it is difficult to distinguish the difference in printed color with the naked eye. The algorithm of this study has a more accurate prediction ability than previous studies, and it can be added flexibly even when new inks are added. This can be usefully used in real industrial sites, and it will reduce the attempts of the operator by checking the color of ink in a virtual environment. This will reduce the manufacturing cost of spot color inks and lead to improved working conditions for workers. In addition, it is expected to contribute to solving the environmental pollution problem by reducing unnecessarily wasted ink.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.1
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• pp.1-8
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• 2023

At construction sites, interest in the production of precast materials is increasing due to off-site conditions due to changes in construction site conditions due to increased labor costs and the Act on the Punishment of Serious Accidents. In particular, the precast prestressed hollow slab has a hollow shape in the cross section, so structural performance is secured by reducing weight and controlling deflection through stranded wires. With the application of structural standards, the urgency of securing fire resistance performance is emerging. In this study, a fire-resistance cross section was developed by reducing the concrete filling rate in the cross section and improving the upper and lower flange shapes by optimizing the hollow shape in the cross section of the slab to have the same or better structural performance and economic efficiency compared to the existing hollow slab. The PC hollow slab to which this was applied was subjected to a two-hour fire resistance test using the cross-sectional thickness as a variable, and as a result of the test, fire resistance performance (load bearing capacity, heat shielding property, flame retardance property) was secured. Based on the experimental results, it is determined that fire resistance modeling can be established through numerical analysis simulation, and prediction of fire resistance analysis is possible according to the change of the cross-sectional shape in the future.

• Journal of Industrial Convergence
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• v.21 no.1
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• pp.175-185
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• 2023

Recently, novel viral infections such as COVID-19 have spread and pose a serious public health problem. In particular, these diseases have a fatal effect on the elderly, threatening life and causing serious social and economic losses. Accordingly, applications such as telemedicine, healthcare, and disease prevention using the Internet of Things (IoT) and artificial intelligence (AI) have been introduced in many industries to improve disease detection, monitoring, and quarantine performance. However, since existing technologies are not applied quickly and comprehensively to the sudden emergence of infectious diseases, they have not been able to prevent large-scale infection and the nationwide spread of infectious diseases in society. Therefore, in this paper, we try to predict the spread of infection by collecting various infection information with regional limitations through a virus disease information collector and performing AI analysis and severity matching through an AI broker. Finally, through the Korea Centers for Disease Control and Prevention, danger alerts are issued to the elderly, messages are sent to block the spread, and information on evacuation from infected areas is quickly provided. A realistic elderly support system compares the location information of the elderly with the information of the infected area and provides an intuitive danger area (infected area) avoidance function with an augmented reality-based smartphone application. When the elderly visit an infected area is confirmed, quarantine management services are provided automatically. In the future, the proposed system can be used as a method of preventing a crushing accident due to sudden crowd concentration in advance by identifying the location-based user density.

• Korean Chemical Engineering Research
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• v.61 no.1
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• pp.62-67
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• 2023

Due to the prolonged impact of COVID-19, the demand for Information Technology (IT) products is increasing, and their production facilities are expanded. Consequently, the use of harmful and dangerous chemicals are increased, the risk of fire(s) and explosion(s) is also elevated. In order to mitigate these risks, the government sets standards, such as KS C IEC 60079-10-1, and manages explosion-prone hazardous facilities where flammable substances are manufactured, used, and handled. However, using the standards of KS, it is difficult to predict the actual possibility of an explosion in a facility, because ventilation (an important factor) is not considered when setting up a hazardous work environment. In this study, the SEMI S6, Tracer Gas Test was applied to the chemical vapor deposition (CVD) facility, a major part of the display industry, to evaluate ventilation performance and to confirm the possibility of creating a less explosive environment. Based on the results, it was confirmed that the ventilation performance in the assumed scenarios met the standards stipulated in SEMI S6, along with supporting the possibility of creating a less explosive working condition. Therefore, it is recommended to use the prediction tool using engineering techniques, as well as KS standards, in such hazardous environments to prevent accidents and/or reduce economic burden following accidents.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.128-130
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• 2021

This study aims to implement a Regression Analysis system for predicting the appropriate production of flatfish. Due to Korea's signing of FTAs with countries around the world and accelerating market opening, Korean flatfish farming businesses are experiencing many difficulties due to the specificity and uncertainty of the environment. In addition, there is a need for a solution to problems such as sluggish consumption and price drop due to the recent surge in imported seafood such as salmon and yellowtail and changes in people's dietary habits. in this study, Using the python module, xlwings, it was used to obtain for the production amount of flatfish and to predict the amount of flatfish to be produced later. was used to predict the amount of flatfish to be produced in the future. Therefore, based on the analysis results of this prediction of flatfish production, the flatfish aquaculture industry will be able to come up with a plan to achieve an appropriate production volume and control supply and demand, which will reduce unnecessary economic loss and promote new value creation based on data. In addition, through the data approach attempted in this study, various analysis techniques such as artificial neural networks and multiple regression analysis can be used in future research in various fields, which will become the foundation of basic data that can effectively analyze and utilize big data in various industries.

• Korean Journal of Poultry Science
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• v.50 no.2
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• pp.73-80
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• 2023

Vitamin D3 is an essential nutrient which plays an important role in calcium metabolism for eggshell formation, in calcium and phosphorus metabolism for bone mineralization, and in maintaining host immunity. Although there have been a great deal of studies investigating the role of vitamin D3 in eggshell quality and vitamin D3 contents in eggs, no attempts have been made to monitor the eggshell quality and vitamin D3 contents in eggs at farm level. Thus, this survey was conducted to measure eggshell quality and vitamin D3 contents in eggs laid from laying hens fed diets containing different levels of vitamin D3. Eggs from four commercial laying hen farms were sampled before and 1, 2, 3 and 5 weeks after provision of the vitamin D3-enriched diets added with the level of 16,500 IU and 29,000 IU. Dietary vitamin D3 did not affect the eggshell color and breaking strength, but increase the eggshell thickness. In addition, vitamin D3 contents in eggs were elevated as vitamin D3 in diets was increased. It is concluded that addition of dietary vitamin D3 into the diets of laying hens at the commercial laying hen farms could improve eggshell quality and vitamin D3 contents in eggs. It is expected that the prediction equation for egg vitamin D3 contents might be produced if more data on vitamin D3 contents in diets and eggs at the farms are to be analyzed.