• Journal of Environmental Science International
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• v.3 no.2
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• pp.165-175
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• 1994

An emergy analysis of the main energy flows driving the economy of humans and life support systems was made including environmental energies, fuels, and imports, all expressed as solar emjoules. The total emergy use (4, 373 E20 sej/yr) is 90 per cent from imported sources, fuels and goods and services. The emergy flows from the environment are modest, because the share of global inputs such as ruin and geological uplift flux is modest. Consequently, the ratio of outside investment to attracting natural resources is already large, like other industrialized countries. The population level is already in excess of carrying capacity. The emergy use per person in Korea indicates a moderate emergy standard of living, even though the indigenous resource is very poor. If the present economy were running entirely on stored reserves of fuels, soils, woods, etc., it would last about 2 years. Its carrying capacity for steady state on its renewable sources is only 3.3 million people, compared to 43.3 million in 1991. Continued availability of foreign oil at a favorable balance of emergy trade, currently about 7 to 1 net emergy, is the basis for present economic activity and must decrease as the net emergy of foreign oil purchased goes down. Close economic integration with Middle East may determine how long this is possible in the future.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.5
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• pp.591-598
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• 2019

The statistics of committing suicide in S. Korea is ranked in top with serious attempts of falling among OECD countries since 2003. The rates is slightly dropped by 5 percent point, nevertheless the falling is still high for the age of over 10 years old and this matter must be solved. Most of the case of suicides are the falling based on a trend view of falling which is serious matter and cannot be solved easily for both domestic and foreign countries. For example, the steel net of falling prevent was installed in the Golden Gate Bridge costed by 200 million-dollar. In New Zealand, the steel net of falling prevention had been removed and re-installed beccause of the high suicide rates. Canada and Australia also surrounded the bridge with steel fences to prevent suicide without consideration of the beauty of bridge. Therefore, this paper suggested a comparison study on both falling prevention systems in all countries and patent technologies. Also, it covers the blocking skills of approach in both security and limited area. This paper suggested the technical Rollinder system equipped with the mechanical apprentice to prevent effectively the falling sucides and wall passing. Before the installation of Rollinder System by 2016, there were 33 person who tried to fall in the river in Machang Bridge. However, the number of the committing suicides were dramatically reduced to zero after the installation of the system.

• Journal of Korea Foundry Society
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• v.42 no.2
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• pp.83-93
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• 2022

Throughout this research course, we have analyzed the financial situation of more than 2,700 companies using credit evaluation disclosures from 2017 to 2019. The population was gathered based on the certification of Ppuri companies and Ppuri Expertise companies through the Korea National Ppuri Industry Center, accompanied by the NICE credit evaluation index. For the first time in Korea, we wanted to look at growth, profitability, and stability through financial analysis of the Ppuri industry. Through an indepth analysis, we identified operating income (rate), net income (rate), asset size, and debt ratio, along with three years of Ppuri company workers and total sales fluctuations, and looked at the financial structure per capita. In addition, financial status per person was compared by dividing Ppuri companies into six groups by employee size. Groups were 10 or fewer people, 11 to 20 people, 21 to 50 people, 51 to 200 people, 201-300 people, and 300 or more people; single individual companies were excluded for research convenience. Overall, the financial situation of Ppuri companies was judged to be in a very bad downturn, and financial indicators deteriorated over the course of the three years of investigation. In particular, the smaller the number of employees, the greater the financial fluctuations were and the worse the situations were. Among Ppuri companies, the casting industry, which is the technical starting point for the value chain of the industry, was found to also be in a very bad state, with continued workforce declines, total assets and sales reductions at severe levels, and operating income (rate) and net income (rate) also very poor. This is why we need a suitable and feasible policy direction, something that is difficult but must be allowed to develop.

• Journal of the Korean Geotechnical Society
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• v.37 no.11
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• pp.119-129
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• 2021

The process of constructing the DB in the current geotechnical information DB system needs a lot of human and time resource consumption. In addition, it causes accuracy problems frequently because the current input method is a person viewing the PDF and directly inputting the results. Therefore, this study proposes building an automatic digital DB using AI (artificial intelligence) of boring logs. In order to automatically construct DB for various boring log formats without exception, the boring log forms were classified using the deep learning model ResNet 34 for a total of 6 boring log forms. As a result, the overall accuracy was 99.7, and the ROC_AUC score was 1.0, which separated the boring log forms with very high performance. After that, the text in the PDF is automatically read using the robotic processing automation technique fine-tuned for each form. Furthermore, the general information, strata information, and standard penetration test information were extracted, separated, and saved in the same format provided by the geotechnical information DB system. Finally, the information in the boring log was automatically converted into a DB at a speed of 140 pages per second.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1137-1144
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• 2022

In this study, an artificial intelligence(AI) was developed to help with facial expression practice in order to express emotions. The developed AI used multimodal inputs consisting of sentences and facial images for deep neural networks (DNNs). The DNNs calculated similarities between the emotions predicted by the sentences and the emotions predicted by facial images. The user practiced facial expressions based on the situation given by sentences, and the AI provided the user with numerical feedback based on the similarity between the emotion predicted by sentence and the emotion predicted by facial expression. ResNet34 structure was trained on FER2013 public data to predict emotions from facial images. To predict emotions in sentences, KoBERT model was trained in transfer learning manner using the conversational speech dataset for emotion classification opened to the public by AIHub. The DNN that predicts emotions from the facial images demonstrated 65% accuracy, which is comparable to human emotional classification ability. The DNN that predicts emotions from the sentences achieved 90% accuracy. The performance of the developed AI was evaluated through experiments with changing facial expressions in which an ordinary person was participated.

• The Journal of Bigdata
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• v.8 no.1
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• pp.49-59
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• 2023

There are various items in the safety and health standards of the manufacturing industry, but they can be divided into work-related diseases and musculoskeletal diseases according to the standards for sickness and accident victims. Musculoskeletal diseases occur frequently in manufacturing and can lead to a decrease in labor productivity and a weakening of competitiveness in manufacturing. In this paper, to detect the musculoskeletal harmful factors of manufacturing workers, we defined the musculoskeletal load work factor analysis, harmful load working postures, and key points matching, and constructed data for Artificial Intelligence(AI) learning. To check the effectiveness of the suggested dataset, AI algorithms such as YOLO, Lite-HRNet, and EfficientNet were used to train and verify. Our experimental results the human detection accuracy is 99%, the key points matching accuracy of the detected person is @AP0.5 88%, and the accuracy of working postures evaluation by integrating the inferred matching positions is LEGS 72.2%, NECT 85.7%, TRUNK 81.9%, UPPERARM 79.8%, and LOWERARM 92.7%, and considered the necessity for research that can prevent deep learning-based musculoskeletal diseases.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.167-181
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• 2023

This study utilized TEXTOM, a social network analysis program to analyze changes in current tourism behavior after travel restrictions were eased after the outbreak of COVID-19. Data on the keywords 'domestic travel' and 'overseas travel' were collected from blogs, cafes, and news provided by Naver, Google, and Daum. The collection period was set from April to December 2022 when social distancing was lifted, and 2019 and 2020 were each set as one year and compared and analyzed with 2022. A total of 80 key words were extracted through text mining and centrality analysis was performed using NetDraw. Finally, through the CONCOR, the correlated keywords were clustered into 4. As a result of the study, tourism behavior in 2022 shows tourism recovery before the outbreak of COVID-19, segmentation of travel based on each person's preferred theme, prioritization of each country's corona mitigation policy, and then selecting a tourist destination. It is expected to provide basic data for the development of tourism marketing strategies and tourism products for the newly emerging tourism ecosystem after COVID-19.

• Journal of the Korean Society for Library and Information Science
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• v.49 no.1
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• pp.45-67
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• 2015

The purpose of this study is to analyse the semantic relations of terms in STNet, a structured terminology dictionary based on author keywords of humanities, social sciences, and art and sport in the Korea Citation Index (KCI) and to describe the procedure for optimizing the relation types and specifying the name of relationships. The results indicate that four logical criteria, such as creating new names for relationships or limitation of typing the relationship by the appearance frequency of same type, consideration of direction of relationship, reflection to accept the existing name of relationships, are required for the optimization of the typing and naming the relationships. We applied these criteria to the relationships in the class "real person" of STNet and the result shows that 1,135 out of 1,743 uncertain relationships such as RT, RT_X or RT_Y are specified and clarified. This rate of optimization with ca. 65% represents the usefulness of the criteria applicable to the cases of database construction and retrieval.

• Smart Media Journal
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• v.9 no.3
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• pp.122-129
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• 2020

The possibility that an asymptotic coronavirus-19 infected person around the world is not aware of his infection and can spread it to people around him is still a very important issue in that the public is not free from anxiety and fear over the spread of the epidemic. In this paper, the K-means clustering algorithm and deep learning-based crowd aggregation were proposed to determine the possibility of contact with confirmed cases of infectious diseases. As a result of 300 iterations of all input learning images, the PSNR value was 21.51, and the final MAE value for the entire data set was 67.984. This means the average absolute error between observations and the average absolute error of fewer than 4,000 people in each CCTV scene, including the calculation of the distance and infection rate from the confirmed patient and the surrounding persons, the net group of potential patient movements, and the prediction of the infection rate.

• Nuclear Engineering and Technology
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• v.52 no.10
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• pp.2370-2378
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• 2020

Building materials contribute significantly to the indoor radon and thoron levels. Therefore, parameters that influence the exhalation rates of radon and thoron from building material need to be analyzed closely. As a preliminary study, the effects of humidity on exhalation rates were measured using a system with an accumulation chamber and RAD7 detector for Korean brick, Korean soil, and Indonesian brick. Resulting doses to a person who resides in a room constructed from the building materials were assessed by UNSCEAR method for different air exchange rates. The measurements have revealed that Korean brick exhaled the highest radon and thoron while Indonesian brick exhaled the lowest thoron. Results showed that for a typical low dense material, radon and thoron exhalation rate will increase until reached its maximum at a certain value of humidity and will remain saturated above it. Analysis on concentration and effective dose showed that radon is strongly affected by air exchange rate (ACH). This is showed by about 66 times decrease of radon dose from 0.00 h^-1 to those of 0.50 h^-1 ACH and decrease by a factor of 2 from 0.50 h^-1 to those of 0.80 h^-1. In case of thoron, the ACH doesn't have significant effects on effective dose.