• Journal of the Korea Convergence Society
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• v.10 no.6
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• pp.41-47
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• 2019

It is very important to search for and obtain an example of a similar judgment in case of court judgment. The existing judge's document search uses a method of searching through key-words entered by the user. However, if it is necessary to input an accurate keyword and the keyword is unknown, it is impossible to search for the necessary document. In addition, the detected document may have different contents. In this paper, we want to improve the effectiveness of the method of vectorizing a document into a three-dimensional space, calculating cosine similarity, and searching close documents in order to search an accurate judge's example. Therefore, after analyzing the similarity of words used in the judge's example, a method is provided for extracting the mode and inserting it into the text of the text, thereby providing a method for improving the cosine similarity of the document to be retrieved. It is hoped that users will be able to provide a fast, accurate search trying to find an example of a tax-related judge through the proposed model.

• Atmosphere
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• v.28 no.4
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• pp.457-467
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• 2018

This study investigated the variability of spring (March-May) forest fire risk in Korea for the period 1991~2017 and analyzed its relationship with large-scale climate factors. The Forest Weather Index (FWI) representing the meteorological risk for forest fire occurrences calculated based on observational data and its relationship with large-scale climate factors were analyzed. We performed the empirical orthogonal function (EOF) analysis on the spring FWI. The leading EOF mode of FWI accounting for about 70% of total variability was found to be highly correlated with total number of forest fire occurrences in Korea. The high FWI, forest fire occurrence risk, in Korea, is associated with warmer atmosphere temperature in midwest Eurasia-China-Korea peninsula, cyclonic circulation anomaly in northeastern China-Korea peninsula-northwest pacific, westerly wind anomaly in central China-Korea peninsula, and low humidity in Korea. These are further related with warmer sea surface temperature and enhanced outgoing longwave radiation over Western Pacific, which represents a typical condition for a La $Ni\tilde{n}a$ episode. This suggests that large-scale climate factors over East Asia and ENSO could have a significant influence on the occurrence of spring forest fires in Korea.

• Nuclear Engineering and Technology
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• v.51 no.6
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• pp.1708-1714
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• 2019

The purpose of the critical evaluation of the spent fuel pool (SFP) is to verify that the maximum effective multiplication factor ($K_{eff}$) is less than the critical safety limit at 100% stored condition of the spent fuel with the maximum reactivity. At nuclear power plants, the storage standard of spent fuel, ie, the loading curve, is established to prevent criticality from being generated in SFP. Here, the loading curve refers to a graph showing the minimum discharged burnup versus the initial enrichment of spent fuel. Recently, US NRC proposed the new critical safety assessment guideline (DSS-ISG-2010-01, Revision 0) of PWR SFPs and most of utilities in US is following it. Of course, the licensed criterion of the maximum effective multiplication factor of SFP remains unchanged and it should be less than 0.95 from the 95% probability and the 95% confidence level. However, the new guideline is including the new evaluation methodologies like the application of the axial burnup profile, the validation of depletion and criticality code, and trend analysis. Among the new evaluation methodologies, the most important factor that affects $K_{eff}$ is the axial burnup profile of spent fuel. US NRC recommends to consider the axial burnup profiles presented in NUREG-6801 in criticality analysis. In this paper, criticality effect was evaluated considering three profiles, respectively: i) Axial burnup profiles presented in NUREG-6801. ii) Representative PWR axial burnup profile. iii) Uniform axial burnup profile. As the result, the case applying the axial burnup profiles presented in NUREG-6801 showed the highest $K_{eff}$ among three cases. Therefore, we need to introduce a new methodology because it can be issued if the axial burnup profiles presented in NUREG/CR-6801 are applied to the domestic nuclear power plants without any other consideration.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.5
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• pp.101-108
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• 2019

The domestic duck industry is the sixth-largest among the livestock industries. However, 34.3% of duck houses were the duck houses arbitrarily converted from plastic greenhouses. This type of duck house was difficult to properly manage internal air temperature and humidity environment. Humidity environment inside duck houses is an important factor that directly affects the productivity and disease occurrence of the duck. Although the humidity environments of litters (bedding materials) affect directly the inside environment of duck houses, there are only few studies related to humidity environment of litters. In this study, evaporation rates from litters were evaluated according to air temperature, relative humidity, water contents of litters, and wind speed. The experimental chamber was made to measure evaporation rates from litters. Temperature and humidity controlled chamber was utilized during the conduct of the laboratory experiments. Using the measured data, a multi linear regression analysis was carried out to derive the calculation formula of evaporation rates from litters. In order to improve the accuracy of the multi linear regression model, the partial vapor pressure directly related to evaporation was also considered. Variance inflation factors of air temperature, relative humidity, partial vapor pressure, water contents of litters, and wind speed were calculated to identify multicollinearity problem. The Multiple $R^2$ and adjusted-$R^2$ of regression model were calculated at 0.76 and 0.71, respectively. Therefore, the regression models were developed in this study can be used to estimate evaporation rates from the litter of duck houses.

• Journal of Ecology and Environment
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• v.44 no.4
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• pp.212-221
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• 2020

Background: Rapid industrialization has caused various impacts on nature, including heavy metal pollution. However, the impacts of industrialization vary depending on the types of industrializing activity and surrounding environment. South Korea is a proper region because the rapid socio-economical changes have been occurred since the late nineteenth century. Therefore, in this study, we estimate the anthropogenic impacts on an ecosystem from a sediment core of Yonghwasil-mot, an irrigation reservoir on the western coast of Korea, in terms of heavy metal concentrations, nutrient influx, and pollen composition. Results: The sediment accumulation rate (SAR) determined by 210Pb geochronology showed two abrupt peaks in the 1930s and 1950s, presumably because of smelting activity and the Korean War, respectively. The following gradual increase in SAR may reflect the urbanization of recent decades. The average concentrations of arsenic (As), copper (Cu), and lead (Pb) during the twentieth century were > 48% compared to those before the nineteenth century, supporting the influence of smelting activity. However, at the beginning of the twenty-first century, the As, Cu, and Pb concentrations decreased by 19% compared to levels in the twentieth century, which is coincident with the closure of the smelter in 1989 and government policy banning leaded gasoline since 1993. The pollen assemblage and nutrient input records exhibit changes in vegetation cover and water level of the reservoir corresponding to anthropogenic deforestation and reforestation, as well as to land-use alteration. Conclusions: Our results show that the rapid socio-economic development since the twentieth century clearly affected the vegetation cover, land use, and metal pollutions.

• Journal of Convergence for Information Technology
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• v.11 no.7
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• pp.31-38
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• 2021

In this paper, in order to obtain the optimization of the RNN model used for sentiment analysis, the correlation of each model was studied by observing the trend of loss and accuracy according to hyperparameter tuning. As a research method, after configuring the hidden layer with LSTM and the embedding layer that are most optimized to process sequential data, the loss and accuracy of each model were measured by tuning the unit, batch-size, and embedding size of the LSTM. As a result of the measurement, the loss was 41.9% and the accuracy was 11.4%, and the trend of the optimization model showed a consistently stable graph, confirming that the tuning of the hyperparameter had a profound effect on the model. In addition, it was confirmed that the decision of the embedding size among the three hyperparameters had the greatest influence on the model. In the future, this research will be continued, and research on an algorithm that allows the model to directly find the optimal hyperparameter will continue.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.2
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• pp.85-92
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• 2021

Ambient Air Vaporizer (AAV) is an essential facility in the process of generating natural gas that uses air in the atmosphere as a medium for heat exchange to vaporize liquid natural gas into gas-state gas. AAV is more economical and eco-friendly in that it uses less energy compared to the previously used Submerged vaporizer (SMV) and Open-rack vaporizer (ORV). However, AAV is not often applied to actual processes because it is heavily affected by external environments such as atmospheric temperature and humidity. With insufficient operational experience and facility operations that rely on the intuition of the operator, the actual operation of AAV is very inefficient. To address these challenges, this paper proposes an artificial intelligence-based model that can intelligent AAV operations based on operational big data. The proposed artificial intelligence model is used deep neural networks, and the superiority of the artificial intelligence model is verified through multiple regression analysis and comparison. In this paper, the proposed model simulates based on data collected from real-world processes and compared to existing data, showing a 48.8% decrease in power usage compared to previous data. The techniques proposed in this paper can be used to improve the energy efficiency of the current natural gas generation process, and can be applied to other processes in the future.

• Journal of the Korea Society of Computer and Information
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• v.26 no.3
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• pp.29-34
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• 2021

With the advent of the 4th industrial revolution era, IT technology is creating new services that have not existed by converging with various existing industries and fields. In particular, in the field of artificial intelligence, chatbots and the latest technologies have developed dramatically with the development of natural language processing technology, and various business processes are processed through chatbots. This study is a study on a system that provides a close answer to the question the user wants to find by creating a structural form for legal inquiries through Slot Filling-based chatbot technology, and inputting a predetermined type of question. Using the proposal system, it is possible to construct question-and-answer data in a more structured form of legal information, which is unstructured data in text form. In addition, by managing the accumulated Q&A data through a big data storage system such as Apache Hive and recycling the data for learning, the reliability of the response can be expected to continuously improve.

• Journal of Convergence for Information Technology
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• v.11 no.5
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• pp.17-22
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• 2021

It is difficult for the hearing impaired to use the counseling service without sign language interpretation. Due to the shortage of sign language interpreters, it takes a lot of time to connect to sign language interpreters, or there are many cases where the connection is not available. Therefore, in this paper, we propose a system that captures sign language as an image using OpenCV and CNN (Convolutional Neural Network), recognizes sign language motion, and converts the meaning of sign language into textual data and provides it to users. The counselor can conduct counseling by reading the stored sign language translation counseling contents. Consultation is possible without a professional sign language interpreter, reducing the burden of waiting for a sign language interpreter. If the proposed system is applied to counseling services for the hearing impaired, it is expected to improve the effectiveness of counseling and promote academic research on counseling for the hearing impaired in the future.

• Journal of Korean Society of Archives and Records Management
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• v.22 no.4
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• pp.45-65
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• 2022

YouTube videos of public institutions are digital public records that need to be managed and preserved. As such, the video and the metadata describing the video should also be preserved. This study aims to select the key metadata elements necessary for archiving videos published on YouTube by public institutions. To this end, five high-level areas, namely the description, structure, management, preservation, and user participation, and the metadata elements of 10 subareas, were designed by referring to NAK 8, PREMIS, ISAD(G), and YouTube metadata. Afterward, the metadata elements designed by 14 experts were verified. Lastly, the validity and reliability of the evaluation results were verified. Of the 63 elements, 33 satisfied the validity and reliability criteria. Thus, these elements were selected as the core metadata for archiving YouTube videos in public institutions.