• Korean Journal of Agricultural Science
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• v.49 no.1
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• pp.31-43
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• 2022

The global trade environment is rapidly changing. The spread of COVID-19 promotes digitalization, and online transactions are becoming the new normal. Currently, Korea is actively introducing information and communication technology (ICT) that uses the internet of things (IoT) in relation to agriculture. However, few studies have analyzed the impact of digitalization on trade in the agricultural sector. Thus, the purpose of this study is to examine how the introduction of digital technology can affect the economy and trade of Korea. In this study, we estimate the impact of introducing digital technologies using the computable general equilibrium (CGE) model. The results of this analysis indicate that the GDP could increase by 3.82% to 10.53%. Also, agricultural production and trade according to the model will significantly increase to 8.67% and 5.72%, respectively, through a productivity increase from Blockchain, IoT, and artificial intelligence (AI) technologies, despite logistics inefficiencies. Although the effects of digitalization could be significant, farmers are still struggling to introduce digital technologies, stemming from the fact that government support systems are concentrated in only a few sub-sectors. In this regard, support in this area must be expanded and diversified according to the current environment of agriculture in Korea.

• Journal of the Korean Institute of Gas
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• v.26 no.4
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• pp.41-57
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• 2022

The global demand for carbon neutrality in response to climate change is in a situation where it is necessary to prepare countermeasures for carbon trade barriers for some countries, including Korea, which is classified as an export-led economic structure and greenhouse gas exporter. Therefore, digital transformation, which is one of the predictable ways for the carbon-neutral transition model to be applied, should be introduced early. By applying digital technology to industrial gas manufacturing facilities used in one of the major industries, high-tech manufacturing industry, and hydrogen gas facilities, which are emerging as eco-friendly energy, abnormal detection, and diagnosis services are provided with cloud-based predictive diagnosis monitoring technology including operating knowledge. Here are the trends. Small and medium-sized companies that are in the blind spot of carbon-neutral implementation by confirming the direction of abnormal diagnosis predictive monitoring through optimization, augmented reality technology, IoT and AI knowledge inference, etc., rather than simply monitoring real-time facility status It can be seen that it is possible to disseminate technologies such as consensus knowledge in the engineering domain and predictive diagnostic monitoring that match the economic feasibility and efficiency of the technology. It is hoped that it will be used as a way to seek countermeasures against carbon emission trade barriers based on the highest level of ICT technology.

• Journal of Venture Innovation
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• v.5 no.4
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• pp.179-189
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• 2022

In the face of revolutionary changes in industry, the relationship between labor and income needs to be reconceptualized in the period of social revolution. The absolute decrease in labor due to the absence of labor is caused by automation, smartization, AI, robot labor, etc., which we must accept whether we want to or not. However, while gross social product and capital of the state or society increase, individual income is likely to decrease. During this transformation period, the state or politics must prepare for the problems caused by the decline in individual income. Until now, there have been various levels of discussion on social welfare or social security from the perspective of welfare or assistance. Attempts or studies at the experimental level have been conducted at the level of many countries or local governments and have found positive and negative effects. There is no basic income system that is widely implemented at the national level, and various discussions are taking place from a future-oriented perspective. Therefore, I propose to look at it from a new perspective based on the perspective so far. We explored that it is part of a positive approach to examine the importance and necessity of basic income in terms of working hours, quality of labor, income, quality of life, value of spare time, and work-life balance. The goal is to actively accept the absolute lack of working hours, replacement of mechanical labor, and polarization due to changes in the industry paradigm, and to look at the problems that come from a positive perspective. If we are going to accept it anyway, we should not look at these issues as short-sighted, but prepare them preemptively and establish a primitive plan from a long-term and overall perspective. Smartphones have changed the world over the past decade and have been lost, but wouldn't there be a lot of new discoveries? Shouldn't we think of it as a great opportunity to improve the quality of life through technological changes?

• Korean Journal of Microbiology
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• v.35 no.3
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• pp.218-225
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• 1999

We isolated the ANRI fragment from Aspergillus nidulons that could autononlously replicate and enhance transformation efficiency about $10^4$ fold compared lo the integrative vector in Saccha,omgcer cerevisioe. In A. nidulans recombinant plasmid pLJ16-4.5 which carries the 4.5 kb EcoRI fragment of ANRI showed a 170-[old increase of transformation efficiency compared to the integrative vector pLJ16 and could be recovered from iransfonnants as an intact form. Estimated copy number of transforming plasmid pLJ16-4.5 was scored as 2 to 3 copies in transformed A. nidulans. Recoinbinant plasinid pILJ16-4.5 is inilotically unstable; being lost Irom 65% of aswual progeny of transformants on selective medium and 90% on complete medium. Southern analysis of transformant DNA showed that the pILJ16-4.5 is maintained in free form. The sequencing data showed that ANRl fragment was originated from mitochondiral DNA of A. nid~ilans and contained high AT content as much as 74.7%. One ARS consensus sequence (A/T)TTr4T(A/G)TTT(AiT). I I ARS-like sequence (agreement 10 of 11) and ABFl binding core consensus sequence (TCN7ACG). Also six gyrase binding core consensus sequence (YRTGNYNNY: y=C or T, R=A or G, N=A, G, C or T) of $\Phi$X174 and SV40 DNA and one b site (CACTTTACC) combining with gyrase in ColEl are shown. ANRl can be developed as a repl&ng plasinid for lransfoimation system in A. nirlulmis.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.8 no.1
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• pp.97-105
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• 1998

Antioxidation mechanism of Al metal powders on $Al_2O_3-C$ refractory was investigated in temperature range from 800 to $1400^{\circ}C$. The addition of 5 wt% Al metal powders suppressed the oxidation of carbon in $Al_2O_3$-C sample. The carbons were distributed uniformly on the surface and the interface of the $Al_2O_3$-C-Al. Reaction products of $Al_4C_3$ and AIN were found with a composition of Al-C at temperatures between 800 and $1200^{\circ}C$ and transformed to $Al_2O_3$ above $1400^{\circ}C$. Cavity structures related to the to the formation of $Al_4C_3$ were observed for the AI-C after heating at $1000^{\circ}C$ ofr 1 hour. Thermodynamic mechanism was considered to discuss the formation $Al_4C_3$, AlN and their transformation to $Al_2O_3$, which leads to the effect of oxidation resistance.

• Smart Media Journal
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• v.10 no.3
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• pp.23-30
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• 2021

Although the manufacturing time series data clustering technique is an important grouping solution in the field of detecting and improving manufacturing large data-based equipment and process defects, it has a disadvantage of low accuracy when applying the existing static data target clustering technique to time series data. In this paper, an evolutionary computation-based time series cluster analysis approach is presented to improve the coherence of existing clustering techniques. To this end, first, the image shape resulting from the manufacturing process is converted into one-dimensional time series data using linear scanning, and the optimal sub-clusters for hierarchical cluster analysis and split cluster analysis are derived based on the Pearson distance metric as the target of the transformation data. Finally, by using a genetic algorithm, an optimal cluster combination with minimal similarity is derived for the two cluster analysis results. And the performance superiority of the proposed clustering is verified by comparing the performance with the existing clustering technique for the actual manufacturing process image.

• Korean Journal of Metals and Materials
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• v.48 no.4
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• pp.357-362
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• 2010

Ferromagnetic Mn-Al nanoparticles were prepared using a plasma arc discharge method. The influence of the process parameters on the vaporization rate, composition, particle size, and magnetic properties of the as-produced nanoparticles was investigated. The Mn content was found to be higher in the nanoparticles than in the corresponding mother materials, although the difference diminished with the reaction time. As the $H_2$ content in the reaction gas increased, both the vaporization rate and the particle size increased. With 30 at.% Mn, the average particle diameter was 35.2 nm under a pure Ar gas condition, whereas it was 95.4 nm at a Ar:$H_2$ ratio of 60:40. With the addition of a small amount of carbon, ${\varepsilon}$-phase nanoparticles were successfully synthesized. After a heat treatment in a vacuum for 30 min at $500^{\circ}C$, the nonmagnetic ${\varepsilon}$-phase was transformed into the ferromagnetic ${\tau}$-phase, and a very high coercivity of nearly 5.6 kOe was achieved.

• Journal of the Institute of Convergence Signal Processing
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• v.21 no.4
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• pp.183-194
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• 2020

Recently, the number of hip dysplasia (DDH) that occurs during infant and child growth has been increasing. DDH should be detected and treated as early as possible because it hinders infant growth and causes many other side effects In this study, two modelling techniques were used for multiple training techniques. Based on the results after the first transformation, the training was designed to be possible even with a small amount of data. The vertical flip, rotation, width and height shift functions were used to improve the efficiency of the model. Adam optimization was applied for parameter learning with the learning parameter initially set at 2.0 x 10e-4. Training was stopped when the validation loss was at the minimum. respectively A novel image overlay system using 3D laser scanner and a non-rigid registration method is implemented and its accuracy is evaluated. By using the proposed system, we successfully related the preoperative images with an open organ in the operating room

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.2
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• pp.178-186
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• 2021

COVID-19 occurred in China in December 2019 and spread to the world. Untact culture becoming commonplace due to the spread of COVID-19, is accelerating digital transformation across society. The government is increasing government fund to overcome national crisis situations such as COVID-19. In order to efficiently execute these government funds, the government and policy financial institutions need to come up with two measures. One is to establish a transparent government fund execution process, and the other is to secure the objectivity of the review process. In this paper, to solve this problem, we designed the execution process of government funds from the government to end users with Consortium Blockchain, and designed a machine learning algorithm for internal review of policy financial institutions. The research data proposed in this paper will be helpful in setting the future government policy direction for government fund execution.

• Journal of The Korean Association of Information Education
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• v.26 no.2
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• pp.97-104
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• 2022

As the era of digital transformation begins in earnest, the importance of convergent thinking based on software, artificial intelligence, and big data is increasing. In line with these social needs, this study developed a 5th hour SW-STEAM education program using Monte Carlo simulation techniques for Mendelian inheritance in the field of life science. By programming and implementing Mendelian inheritance using Monte carlo simulation, the program was organized so that not only convergent thinking skills but also related knowledge could be understood in depth. In order to verify the validity of the developed education program, 11 experts in related fields were requested to test the content validity, and the validity was verified by meeting the CVR reference value of 0.59 suggested by Lawshe.