• Journal of the Korea Organic Resources Recycling Association
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• v.30 no.4
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• pp.151-163
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• 2022

This study was conducted to promote organic fertilizer(s) that sustain soil productivity for corn production and protect the environment as required by the Act on the promotion of eco-friendly agriculture. It was conducted at the research station of the Organic Agriculture Division of the National Institute of Agricultural. The treatments consisted of Compost (Com), Bokashi as fermented organic fertilizer (FOF), and mixed expeller pressed cake (PC). They were applied at 174 kg N /ha to field corn, together with a 'no fertilizer' check in Randomized Complete Block Design. At eight weeks after transplanting (WAT) corn, compost increased soil carbon (C) and nitrogen (N) to 7.48 and 0.76 g/kg respectively, while other fertilizers maintained the initial levels (before treatment application). At corn harvest (13 WAT), soil chemical properties (total C, total N, pH, electrical conductivity, P₂O₅, Ca, K, and Mg) were similar among all organic fertilizer treatments. For soil respiration, FOF increased soil CO₂ respiration by 31-76% above other fertilizer treatments. However, there were no prominent changes in the trends of CH₄ fluxes following the two mechanical weeding operations. Fermented organic fertilizer affected N₂O emissions between 87-96% lower than other fertilizer treatments. Compared to the initial microbial densities, FOF increased fungi and actinomycete colony foming unit by 25 and 16% at harvest. Therefore, the additional potential of improving soil biological fertility and local availability of raw materials make FOF a better option to sustain soil productivity while protecting the environment.

• Journal of the Institute of Convergence Signal Processing
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• v.21 no.3
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• pp.148-153
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• 2020

In order to obtain high accuracy with an convolutional neural network(CNN), it is necessary to set the optimal hyperparameters. However, the exact value of the hyperparameter that can make high performance is not known, and the optimal hyperparameter value is different based on the type of the dataset, therefore, it is necessary to find it through various experiments. In addition, since the range of hyperparameter values is wide and the number of combinations is large, it is necessary to find the optimal values of the hyperparameters after the experimental design in order to save time and computational costs. In this paper, we suggest an algorithm that use the design of experiments and grid search algorithm to determine the optimal hyperparameters for a classification problem. This algorithm determines the optima values of the hyperparameters that yields high performance using the factorial design of experiments. It is shown that the amount of computational time can be efficiently reduced and the accuracy can be improved by performing a grid search after reducing the search range of each hyperparameter through the experimental design. Moreover, Based on the experimental results, it was shown that the learning rate is the only hyperparameter that has the greatest effect on the performance of the model.

• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.131-142
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• 2021

This research is based on the design of pictures in picture books, and the spatial representation of illustrations in the picture books contains the significantly important objective. Various texts, pictures, spaces, etc. in a picture must have the operator's various editing skills so that spatial arrangement is made smoothly.In this paper, the characteristics of spatial expression of design in picture books are derived by analyzing several examples of paintings and studies on classic picture books. First, the fusion of picture and text, that is, that both picture and text convey spatial information together as elements of the screen. Second, as a characteristic of the coherence of the space design in picture books, the story and content must be smoothly connected when reading the book. Third, when expressing a space, the creator should utilize the strengths and weaknesses of each other between abstract and conceived spatial expressions as needed. Fourth, as a symbolic feature of picture book spatial expression, it can be seen that many symbolic expression techniques are applied to the spatial expression of picture books according to the semiotic principle, which greatly improves the cognitive efficiency of reading picture books. The fifth characteristic is that the spatial expression of an excellent picture book has excellent interesting element, rich design means, and interestingly conveys screen contents and screen format to readers. In this research, it is thought that designers and artists should guide the creation within a spatial framework as designing picture books, thus greatly improving the efficiency of the creation process, while also provide a reader-centered visual Interesting experience.

• The Journal of Engineering Geology
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• v.32 no.2
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• pp.221-239
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• 2022

Unknown geotechnical characteristics are key challenges in the design of piles for the plant, civil and building works. Although the N-values which were read through the standard penetration test are important, those N-values of the whole area are not likely acquired in common practice. In this study, the N-value is predicted by means of regression analysis with artificial intelligence (AI). Big data is important to improve learning performance of AI, so circular augmentation method is applied to build up the big data at the current study. The optimal model was chosen among applied AI algorithms, such as artificial neural network, decision tree and auto machine learning. To select optimal model among the above three AI algorithms is to minimize the margin of error. To evaluate the method, actual data and predicted data of six performed projects in Poland, Indonesia and Malaysia were compared. As a result of this study, the AI prediction of this method is proven to be reliable. Therefore, it is realized that the geotechnical characteristics of non-boring points were predictable and the optimal arrangement of structure could be achieved utilizing three dimensional N-value distribution map.

• Journal of Korea Entertainment Industry Association
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• v.15 no.3
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• pp.269-278
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• 2021

This study was inteded to include online social relations and ability use information and communication devices to analyze the elderly's participation in volunteer activities and provide basic data to identify the elderly's participation in volunteer activities. The statistical data of the 2017 National survey of Senior Citizen, only 10,073 people aged 65 or older were sampled out of 10,299 people. The participation rate of volunteering was frequently analyzed, and the difference in participation in volunteer according to the factors was Chi-square analysis and One-way variance analysis. A polynomial regression analysis was conducted to identify the effect factors of participation in volunteering. As a results. 3.9% of older adults are volunteering and 11.5% are experienced in the past. Participation in volunteer activity differed significantly depending on age, education level, economic level, subjective health, body function, ability use information and communication devices, social networks, frequency of face-to-face contact and frequency of non face contact. In the regression analysis, utilization of communication and device, social networking, face to face contact frequency were show to be the effect factors. In order to promote elderly's participation in volunteer activities, consideration of related resources reported in prior studies, social relations, frequency of face-to-face contact and ability to use information and communication devices is considered important.

• Korean Journal of Clinical Laboratory Science
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• v.53 no.2
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• pp.143-150
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• 2021

The recent spread of novel and highly variant pathogenic viruses, including the coronavirus (SARS-CoV-2), has increased the demand for diagnostic testing for rapid confirmation. This has resulted in investigating the functional capability of each space, and preparing facility guidelines to secure the safety of medical technologists. During viral evaluations, there is a requirement of negative pressure facilities along with thread separation, during pre-treatment of samples and before nucleic acid amplification. Space composition therefore needs to be planned by considering unidirectional air flow. This classification of safety management facilities is designated as biosafety level 2, and personal protective equipment is placed accordingly. In case of handling dangerous materials, they need to be carried out of the biosafety cabinet, and sterilizers are required for suitable disposal of infectious agents. A common feature of domestic laboratories is maintenance of the sample pre-treatment space at a negative pressure of -2.5 Pa or less, and arranging separate pre-treatment and reagent preparation spaces during the test process. We believe that the data generated in this study is meaningful, and offers an efficient direction and detailed flow for separation of the inspection process and space functions. Moreover, this study introduces construction of the laboratory by applying the safety management standards.

• Journal of Korea Entertainment Industry Association
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• v.14 no.4
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• pp.341-347
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• 2020

The purpose of this study is to identify factors affecting the perceived health conditions of the elderly in Korea, and to provide basic data on ways to improve the perceived health conditions of the elderly and future direction of the elderly welfare project. As an analysis method, Pearson's correlation was used to examine the correlation betwwen perceived health conditions, ADL, IADL, social participation, depression, nutritional conditions, and multiple regression analysis was used to find out which of these factors influenced. Also, to see the difference in depression according to the degree of perceived health conditions, a post-test(Scheffe) was used after one-way variance analysis(p<0.5). As a result of the analysis, perceived health conditions was positively correlated with ADL, IADL, social participation, and nutritional conditions, and negatively correlated with depressive state. In addition, as a result of examining the degree of depression according to the perceived health status, it showed a significant difference between groups. and the more the group perceived that their health was bad, the more severe it was. perceived health condition was found to be most associated with depressive status. and the positively perceived health conditions showed that the degree of depressive status also decreased, indicating that it is effective to actively manage depression to promote perceived health conditions.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.40 no.4
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• pp.58-66
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• 2022

Biophilic design is an approach that attempts to connect people with nature to promote health, recovery and restoration processes. The purpose of this study was to systematically analyze restorative factors and characteristics of Soswaewon by applying a biophilic design analysis framework. To this end, a biophilic design classification system was established and content analysis and frequency analysis were conducted for 『Soswaewon 48 Young』. the ratio of plant words including bamboo, pine, and plum was the highest, and words related to dynamic water flow or interaction with water as well as various water types such as streams, waterfalls, and ponds were also high. appeared in rank. In addition, multisensory factors, seasonal changes, microclimatic factors, emotional elements that allow people to indirectly experience nature were expressed in various ways. The space layout and circulation provide opportunities to appreciate and experience the rich sensory resources of Soswaewon. In conclusion, this study confirmed the healing and restorative value of Soswaewon from the perspective of biophilic design, and it needs further research on the restorative factors of traditional spaces.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.7
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• pp.1004-1010
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• 2021

Ship-floating object accidents can lead not only to a delay in ship's operations, but also to large scale casualties. Hence, preventive measures are required to avoid them. This study analyzed the spatiotemporal aspects of such collisions based on the data on ship-floating object accidents in sea areas in the last five years, including the collisions in South Korea's territorial seas and exclusive economic zones. We also provide basic data for related research fields. To understand the distribution of the relative density of accidents involving floating objects, the sea area under analysis was visualized as a grid and a two-dimensional histogram was generated. A multinomial logistic regression model was used to analyze the effect of variables such as time of day and season on the collisions. The spatial analysis revealed that the collision density was highest for the areas extending from Geoje Island to Tongyeong, including Jinhae Bay, and that it was high near Jeongok Port in the West Sea and the northern part of Jeju Island. The temporal analysis revealed that the collisions occurred most frequently during the day (71.4%) and in autumn. Furthermore, the likelihood of collision with floating objects was much higher for professional fishing vessels, leisure vessels, and recreational fishing vessels than for cargo vessels during the day and in autumn. The results of this analysis can be used as primary data for the arrangement of Coast Guard vessels, rigid enforcement of regulations, removal of floating objects, and preparation of countermeasures involving preliminary removal of floating objects to prevent accidents by time and season.

• Journal of Internet Computing and Services
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• v.24 no.4
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• pp.127-135
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• 2023

This research paper explores the application of FinBERT, a variational BERT-based model pre-trained on financial domain, for sentiment analysis in the financial domain while focusing on the process of identifying suitable training data and hyperparameters. Our goal is to offer a comprehensive guide on effectively utilizing the FinBERT model for accurate sentiment analysis by employing various datasets and fine-tuning hyperparameters. We outline the architecture and workflow of the proposed approach for fine-tuning the FinBERT model in this study, emphasizing the performance of various datasets and hyperparameters for sentiment analysis tasks. Additionally, we verify the reliability of GPT-3 as a suitable annotator by using it for sentiment labeling tasks. Our results show that the fine-tuned FinBERT model excels across a range of datasets and that the optimal combination is a learning rate of 5e-5 and a batch size of 64, which perform consistently well across all datasets. Furthermore, based on the significant performance improvement of the FinBERT model with our Twitter data in general domain compared to our news data in general domain, we also express uncertainty about the model being further pre-trained only on financial news data. We simplify the complex process of determining the optimal approach to the FinBERT model and provide guidelines for selecting additional training datasets and hyperparameters within the fine-tuning process of financial sentiment analysis models.