• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.5
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• pp.780-790
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• 2022

Quantitative risk levels must be presented by analyzing the causes and consequences of accidents and predicting the occurrence patterns of the accidents. For the analysis of marine accidents related to vessel traffic, research on the traffic such as collision risk analysis and navigational path finding has been mainly conducted. The analysis of the occurrence pattern of marine accidents has been presented according to the traditional statistical analysis. This study intends to present a marine accident prediction model using the statistics on marine accidents related to vessel traffic. Statistical data from 1998 to 2021, which can be accumulated by month and hourly data among the Korean domestic marine accidents, were converted into structured time series data. The predictive model was built using a long short-term memory network, which is a representative artificial intelligence model. As a result of verifying the performance of the proposed model through the validation data, the RMSEs were noted to be 52.5471 and 126.5893 in the initial neural network model, and as a result of the updated model with observed datasets, the RMSEs were improved to 31.3680 and 36.3967, respectively. Based on the proposed model, the occurrence pattern of marine accidents could be predicted by learning the features of various marine accidents. In further research, a quantitative presentation of the risk of marine accidents and the development of region-based hazard maps are required.

• Journal of the Society of Disaster Information
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• v.19 no.1
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• pp.195-203
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• 2023

Purpose: This study intends to check validity of tools for awareness of Business Continuity through measurement and analysis on the sub factors of Business Continuity by employees of railway-related organizations. Method: Based on the preceding study, sub factors of the awareness of Business Continuity are divided into 7 and the total of 29 questions were delivered to employees of railway-related organizations for investigation and analysis through the online survey tool. Result: According to EFA result, the number of factors of awareness of Business Continuity based on the theoretical ground was reduced to 7 and the total coefficient of determination was 82.616%. Checking the questions by factor, all the questions were loaded as intended. Conclusion: Validity of measurement tools of Business Continuity whose sub factors are the Context of Organization, Leadership, Planning, Operation, Support, Performance evaluation, and Improvement for railway organizations were secured through the Exploratory Factor Analysis of this study. As for the further tasks, studies on the structural relationship among internalization of business continuity, organization effectiveness, learning support environment, etc are required.

• Journal of the Society of Disaster Information
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• v.18 no.4
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• pp.883-890
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• 2022

Purpose: Currently, in the case of domestic fire fighting facility design, it is difficult to secure highquality manpower due to low design costs and overheated competition between companies, so there is a limit to improving the fire safety performance of buildings. Accordingly, AI-based firefighting design solutions were studied to solve these problems and secure leading fire engineering technologies. Method: Through AutoCAD, which is widely used in existing fire fighting design, the procedures required for basic design and implementation design were processed, and AI technology was utilized through the YOLO v4 object recognition deep learning model. Result: Through the design process for fire fighting facilities, the facility was determined and the drawing design automation was carried out. In addition, by learning images of doors and pillars, artificial intelligence recognized the part and implemented the function of selecting boundary areas and installing piping and fire fighting facilities. Conclusion: Based on artificial intelligence technology, it was confirmed that human and material resources could be reduced when creating basic and implementation design drawings for building fire protection facilities, and technology was secured in artificial intelligence-based fire fighting design through prior technology development.

• Journal of the Korean Electrochemical Society
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• v.25 no.4
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• pp.174-183
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• 2022

Polymer electrolyte fuel cells and water electrolysis are attracting attention in terms of high energy density and high purity hydrogen production. The catalyst layer for the polymer electrolyte fuel cell and water electrolysis is a porous electrode composed of a precious metal-based electrocatalyst and an ionomer binder. Among them, the ionomer binder plays an important role in the formation of a three-dimensional network for ion conduction in the catalyst layer and the formation of pores for the movement of materials required or generated for the electrode reaction. In terms of the use of commercial perfluorinated ionomers, the content of the ionomer, the physical properties of the ionomer, and the type of the dispersing solvent system greatly determine the performance and durability of the catalyst layer. Until now, many studies have been reported on the method of using an ionomer for the catalyst layer for polymer electrolyte fuel cells. This review summarizes the research results on the use of ionomer binders in the fuel cell aspect reported so far, and aims to provide useful information for the research on the ionomer binder for the catalyst layer, which is one of the key elements of polymer electrolyte water electrolysis to accelerate the hydrogen economy era.

• Journal of Space Technology and Applications
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• v.3 no.1
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• pp.86-99
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• 2023

The mass spectrometer, being an essential scientific instrument for uncovering the origin of the solar system and life, has been used since the early 1970s on board spacecraft to obtain information of neutral and ionized elements in the atmosphere and surface of the moon, planets, asteroids, and comets. According to the 4th Basic Plan for the Promotion of Space Development (2023-2027), Korea plans to conduct lunar landing in 2032 and Mars landing in 2045 as the core goals of the plan and focuses on developing the technologies required for unmanned robotic exploration missions. In this regard, it is crucial to develop the technology of a mass spectrometer, which is the most fundamental payload for space exploration for maximized scientific achievements, however never tried before in any domestic space missions. We describe in this paper the principle of a domestically developed quadrupole mass spectrometer, its prototype model, and the test results of its performance. We conclude this paper with intended future improvements.

• Korean Journal of Optics and Photonics
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• v.34 no.2
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• pp.53-60
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• 2023

We designed a catadioptric objective lens with a 0.6 numerical aperture (NA) for semiconductor inspection at 193 nm. The objective lens meets major requirements such as a spatial resolution of 200 nm and a field of view (FOV) of 0.15 mm or more. We selected a wavelength of 266 nm for autofocus based on the availability of the light source. First, we built the objective lenses of three lens groups: a focusing lens group, a field-lens group, and an NA conversion group. In particular, the NA conversion group is a group of catadioptric lenses that convert the numerical aperture of the beam focused by the prior groups to the required value, i.e., 0.6. The last design comprises 11 optical elements with root-mean-squared (RMS) wavefront aberrations less than λ/80 over the entire field of view. We also achieved the athermalization of the objective lens with focus-shift alone satisfying the performance of RMS wavefront aberration below λ/30 at a temperature range of 20 ± 1.2 ℃.

• Korean Chemical Engineering Research
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• v.61 no.1
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• pp.68-73
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• 2023

Smoke masks have attracted great interests and have been supplied widely for the improvement of the safety during fire evacuation. However, there is not sufficient research on the practical utility, certification status and easy-donning about commercial smoke masks, therefore it is difficult to determine the actual usefulness of the smoke masks. In this study, we conducted a survey on users' perceptions and experiences about the smoke masks, and investigated the status of certification of 54 commercial smoke masks. We also performed donning tests and examined degrees of discomfort for 4 types of the smoke masks. Although 22% of 235 respondents had experienced the smoke masks before the test, and 23% of the respondents did not know the smoke masks, 93% of the respondents expected that the smoke masks could protect users from fire smokes and toxic gases. It was found that 41% of the commercial smoke masks did not certify according to domestic or overseas performance standards. Most certification standards have not effectively regulated maximum wearing time for the smoke masks. Only ASTM E 2952 and KFIS 024 had specific standards for the maximum wearing time of 30 s. As a result of donning tests for 4 types of smoke masks, the wearing time of the hood-type mask and self-contained smoke mask exceeded 30 s, therefore these types of smoke masks might increase the required safe evacuation time. On the other hand, it was also found that short education about the donning could reduce the wearing time by 19% and numbers of improper wearing by 89%.

• Journal of Bio-Environment Control
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• v.32 no.2
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• pp.139-147
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• 2023

This study aims to select eggplant cultivars adaptive to the hot temperature period greenhouse climate by water consumption, and growth performance of plants and fruits of different European eggplant cultivars, including 'Bartok (BA)', 'Bowie (BO)', 'Black Pearl (BP)', 'Ishbilia (I)', 'Mabel (M)', 'Vestale (VE)' and 'Velia (VL)', in substrate hydroponic cultivation under hot and humid greenhouse conditions. On the 118 DAT, the leaf number and stem dry weight were highest in 'VL', followed by 'M', and there was no significant difference in leaf dry weight among cultivars. The marketable fruit number per plant was 16.4 for 'M', which was higher than other cultivars, and 'VE' and 'VL' were 8.5 and 8.8, respectively. The weight per fruit was low for 'M' at 136 g, and the highest in 'VE' and 'VL' at 332 and 281 g, respectively. There was no significant difference in fruit production per plant. In this study, 'M', which has high water use efficiency and a large number of fruits, and 'VL', which required less quantity to water consumption for producing 200 g of fruit and had a high product weight, will have excellent adaptability in the UAE greenhouse condition.

• Korean Journal of Environmental Biology
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• v.39 no.4
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• pp.486-494
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• 2021

Watermelon (Citrullus lanatus (Thunb.) Matsum. & Nakai) is sensitive to low temperature and shows retarded growth under 10℃. Although early transplanting guarantees higher returns, it requires cost and labor to maintain the appropriate temperature for plant growth. Therefore, cultivars tolerant to chilling stress is necessary to reduce the cost and labor requirements. The purpose of this study is to analyze data on plant growth and fruit enlargement under continuous chilling night temperature to develop new cultivars tolerant to chilling temperature. Two cultivars expected to have chilling tolerance and another cultivar sensitive to chilling temperature were grown in greenhouses with chilling and optimal night temperature conditions. In the early growth stage after transplanting, the cultivars expected to have chilling tolerance showed better vine length, fresh weight and dry weight. However, one of the tolerant cultivars showed significantly lower vine length, leaf length and width, and petiole length than the sensitive cultivar during pollination period and later growth stage, showing genotype specific responses. The fruit length, width, and weight were also significantly lower in the tolerant cultivar. The fruit set ratio was significantly higher in the chilling sensitive cultivar than the two tolerant cultivars. These results suggest that the present chilling tolerant cultivars in watermelon were selected based on their performance in the early growth stage, and further studies on chilling tolerance in different growth and development stages are required to develop cultivars adapted to various forcing cultivation systems.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.3
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• pp.125-132
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• 2022

Sentence compression is a natural language processing task that generates concise sentences that preserves the important meaning of the original sentence. For grammatically appropriate sentence compression, early studies utilized human-defined linguistic rules. Furthermore, while the sequence-to-sequence models perform well on various natural language processing tasks, such as machine translation, there have been studies that utilize it for sentence compression. However, for the linguistic rule-based studies, all rules have to be defined by human, and for the sequence-to-sequence model based studies require a large amount of parallel data for model training. In order to address these challenges, Deleter, a sentence compression model that leverages a pre-trained language model BERT, is proposed. Because the Deleter utilizes perplexity based score computed over BERT to compress sentences, any linguistic rules and parallel dataset is not required for sentence compression. However, because Deleter compresses sentences only considering perplexity, it does not compress sentences by reflecting the linguistic information of the words in the sentences. Furthermore, since the dataset used for pre-learning BERT are far from compressed sentences, there is a problem that this can lad to incorrect sentence compression. In order to address these problems, this paper proposes a method to quantify the importance of linguistic information and reflect it in perplexity-based sentence scoring. Furthermore, by fine-tuning BERT with a corpus of news articles that often contain proper nouns and often omit the unnecessary modifiers, we allow BERT to measure the perplexity appropriate for sentence compression. The evaluations on the English and Korean dataset confirm that the sentence compression performance of sentence-scoring based models can be improved by utilizing the proposed method.