• Korean Chemical Engineering Research
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• v.62 no.1
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• pp.27-35
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• 2024

Fuel gases such as methane and propane are used in explosion hazardous area of domestic plants and can form non-uniform mixtures with the influence of process conditions due to leakage. The fire-explosion risk assessment using literature data measured under uniform mixtures, damage prediction can be obtained the different results from actual explosion accidents by gas leaks. An explosion characteristics such as explosion pressure and flame velocity of non-uniform gas mixtures with concentration change similar to that of facility leak were examined. The experiments were conducted in a closed 0.82 m long stainless steel duct with observation recorded by color high speed camera and piezo pressure sensor. Also we proposed the quantification method of non-uniform mixtures from a regression analysis model on the change of concentration difference with time in explosion duct. For the non-uniform condition of this study, the area of flame surface enlarged with increasing the concentration non-uniform in the flame propagation of methane and was similar to the wrinkled flame structure existing in a turbulent flame. The time to peak pressure of methane decreased as the non-uniform increased and the explosion pressure increased with increasing the non-uniform. The ranges of K_G (Deflagration index) of methane with the concentration non-uniform were 1.30 to 1.58 [MPa·m/s] and the increase rate of K_G was 17.7% in methane with changing from uniform to non-uniform.

• Journal of The Korean Association For Science Education
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• v.34 no.5
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• pp.437-447
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• 2014

Learning progressions (LP), which describe how students may develop more sophisticated understanding over a defined period of time, can inform the design of instructional materials and assessment by providing a coherent, systematic measure of what can be regarded as "level appropriate." We developed LPs for the nature of matter for grades K-16. In order to empirically test Korean students, we revised one of the constructs and associated assessment items based on Korean National Science Standards. The assessment was administered to 124 Korean secondary students to measure their knowledge and submicroscopic representations, and to assign them to a level of learning progression for the particle nature of matter. We characterized the level of students' understanding and models of the particle nature of matter, and described how students interpret various representations of atoms and molecules to explain scientific phenomena. The results revealed that students have difficulties in understanding the relationship between the macroscopic and molecular levels of phenomena, even in high school science. Their difficulties may be attributed to a limited understanding of scientific modeling, a lack of understanding of the models used to represent the particle nature of matter, or limited understanding of the structure of matter. This work will inform assessment and curriculum materials development related to the fundamental relationship between macroscopic, observed phenomena and the behavior of atoms and molecules, and can be used to create individualized learning environments. In addition, the results contribute to scientific research literature on learning progressions on the nature of matter.

• Journal of the Microelectronics and Packaging Society
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• v.19 no.1
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• pp.61-66
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• 2012

Chemical Mechanical Planarization (CMP) is a polishing process used in the microelectronic fabrication industries to achieve a globally planar wafer surface for the manufacturing of integrated circuits. Pad conditioning plays an important role in the CMP process to maintain a material removal rate (MRR) and its uniformity. For metal CMP process, highly acidic slurry containing strong oxidizer is being used. It would affect the conditioner surface which normally made of metal such as Nickel and its alloy. If conditioner surface is corroded, diamonds on the conditioner surface would be fallen out from the surface. Because of this phenomenon, not only life time of conditioners is decreased, but also more scratches are generated. To protect the conditioners from corrosion, thin organic film deposition on the metal surface is suggested without requiring current conditioner manufacturing process. To prepare the anti-corrosion film on metal conditioner surface, vapor SAM (self-assembled monolayer) and FC (Fluorocarbon) -CVD (SRN-504, Sorona, Korea) films were prepared on both nickel and nickel alloy surfaces. Vapor SAM method was used for SAM deposition using both Dodecanethiol (DT) and Perfluoroctyltrichloro silane (FOTS). FC films were prepared in different thickness of 10 nm, 50 nm and 100 nm on conditioner surfaces. Electrochemical analysis such as potentiodynamic polarization and impedance, and contact angle measurements were carried out to evaluate the coating characteristics. Impedance data was analyzed by an electrical equivalent circuit model. The observed contact angle is higher than 90o after thin film deposition, which confirms that the coatings deposited on the surfaces are densely packed. The results of potentiodynamic polarization and the impedance show that modified surfaces have better performance than bare metal surfaces which could be applied to increase the life time and reliability of conditioner during W CMP.

• Korean Journal of Agricultural and Forest Meteorology
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• v.26 no.2
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• pp.127-139
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• 2024

Climate change has increased extreme weather events likewise heatwaves, heavy rain, and drought. Unlike other natural disaster, drought is a slowly developing phenomenon and thus drought damage increases as the drought continues. Therefore, it is necessary to understand the characteristics and mechanism of drought occurrence. Agricultural drought occurs when the water supply needed by crops becomes insufficient due to lack of soil water. Therefore, soil water is used as a key variable affecting agricultural drought. In this study, we examined the spatio-temporal distribution and trends of drought across the Korean Peninsula by determining the soil available water content (SAWC) through a model that integrated soil, meteorological, and crop data. Moreover, an investigation into the correlation between meteorological variables and the SAWC was conducted to assess how meteorological characteristics influence the nature of drought occurrences. During the soybean cultivation period, the average SAWC was lowest in 2018 at 88.6% and highest in 2021 at 103.2%. Analysis of the spatial distribution of SAWC by growth stage revealed that the lowest SAWC occurred during the flowering stage (S3) in 2018, during the leaf extension stage (S2) in 2019, during the seedling stage (S1) in 2020, again during the flowering stage (S3) in 2021, and during the seedling stage (S1) in 2022. Based on the average SAWC across different growth stages, the frequency of upland drought was the highest at 22 times during the S3 in 2018. The lowest SAWC was primarily influenced by a significant negative correlation with rainfall and evapotranspiration, whereas the highest SAWC showed a significant positive correlation with rainfall and relative humidity, and a significant negative correlation with reference evapotranspiration.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.131-154
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• 2022

Recently, researches on unstructured data analysis have been actively conducted with the development of information and communication technology. In particular, topic modeling is a representative technique for discovering core topics from massive text data. In the early stages of topic modeling, most studies focused only on topic discovery. As the topic modeling field matured, studies on the change of the topic according to the change of time began to be carried out. Accordingly, interest in dynamic topic modeling that handle changes in keywords constituting the topic is also increasing. Dynamic topic modeling identifies major topics from the data of the initial period and manages the change and flow of topics in a way that utilizes topic information of the previous period to derive further topics in subsequent periods. However, it is very difficult to understand and interpret the results of dynamic topic modeling. The results of traditional dynamic topic modeling simply reveal changes in keywords and their rankings. However, this information is insufficient to represent how the meaning of the topic has changed. Therefore, in this study, we propose a method to visualize topics by period by reflecting the meaning of keywords in each topic. In addition, we propose a method that can intuitively interpret changes in topics and relationships between or among topics. The detailed method of visualizing topics by period is as follows. In the first step, dynamic topic modeling is implemented to derive the top keywords of each period and their weight from text data. In the second step, we derive vectors of top keywords of each topic from the pre-trained word embedding model. Then, we perform dimension reduction for the extracted vectors. Then, we formulate a semantic vector of each topic by calculating weight sum of keywords in each vector using topic weight of each keyword. In the third step, we visualize the semantic vector of each topic using matplotlib, and analyze the relationship between or among the topics based on the visualized result. The change of topic can be interpreted in the following manners. From the result of dynamic topic modeling, we identify rising top 5 keywords and descending top 5 keywords for each period to show the change of the topic. Existing many topic visualization studies usually visualize keywords of each topic, but our approach proposed in this study differs from previous studies in that it attempts to visualize each topic itself. To evaluate the practical applicability of the proposed methodology, we performed an experiment on 1,847 abstracts of artificial intelligence-related papers. The experiment was performed by dividing abstracts of artificial intelligence-related papers into three periods (2016-2017, 2018-2019, 2020-2021). We selected seven topics based on the consistency score, and utilized the pre-trained word embedding model of Word2vec trained with 'Wikipedia', an Internet encyclopedia. Based on the proposed methodology, we generated a semantic vector for each topic. Through this, by reflecting the meaning of keywords, we visualized and interpreted the themes by period. Through these experiments, we confirmed that the rising and descending of the topic weight of a keyword can be usefully used to interpret the semantic change of the corresponding topic and to grasp the relationship among topics. In this study, to overcome the limitations of dynamic topic modeling results, we used word embedding and dimension reduction techniques to visualize topics by era. The results of this study are meaningful in that they broadened the scope of topic understanding through the visualization of dynamic topic modeling results. In addition, the academic contribution can be acknowledged in that it laid the foundation for follow-up studies using various word embeddings and dimensionality reduction techniques to improve the performance of the proposed methodology.

• Atmosphere
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• v.20 no.4
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• pp.467-482
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• 2010

In this study, characteristics of various stability indexes (SI) and environmental parameters (EP) for the lightning are analysed by using 5 upper air observatories (Osan, Gwangju, Jeju, Pohang, and Baengnyeongdo) for the years 2002-2006 over South Korea. The analysed SI and EP are the lifted index, K-index, Showalter stability index, total precipitable water, mixing ratio, wind shear and temperature of lifting condensation level. The lightning data occurred on the range of -2 hr~+1 hr and within 100 km based on the launch time of rawinsonde and observing location are selected. In general, summer averaged temperature and mixing ratio of lower troposphere for the lightning cases are higher about 1 K and $1{\sim}2gkg^{-1}$ than no lightning cases, respectively. The Box-Whisker plot shows that the range of various SI and EP values for lightning and no lightning cases are well separated but overlapping of SI and EP values between lightning and no lightning are not a little. The optimized threshold values for the detection of lightning are determined objectively based on the highest Heidke skill socre (HSS), which is the most favorable validation parameter for the rare event, such as lightning, by using the simulation of SI and EP threshold values. Although the HSS is not high (0.15~0.30) and the number and values of selected SI and EP are dependent on geographic location, the new threshold values can be used as a supplementary tool for the detection or forecast of lightning over South Korea.

• Journal of the Korean Institute of Landscape Architecture
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• v.45 no.3
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• pp.21-29
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• 2017

In this study of visitor place attachment to parks, Scannel and Gilford considered the dimensions of place attachment, and proposed the theoretical framework of PPP(Place, Person, Process) that should be systematically studied from the perspective of person, place and psychological processes. According to Scannel's theoretical basis, this paper puts forward the hypothesis of a structure model of place attachment. In the model, the five independent variables of people, places, cognition, emotion, and behavior have influenced the dependent variable of place attachment. The questionnaire was conducted on 18 neighborhood parks in Kunming, China, and the residents of the 5 neighborhood parks in Daejeon, South Korea. A total of 1,645 valid samples of the questionnaire survey were collected. Through confirmatory factor analysis(CFA) results of the inspection of the various elements, it was shown that the reliabilities of 6 latent variables, such as people, places, cognition, affection, behavior and place attachment, which were composed with the observed variables(30 observed variables in Daejeon, 19 observed variables in Kunming), were all above 0.7 and the data were fit for this study. The hypothesis test results found that the physical environment of the neighborhood parks such as a comfortable environment, pleasant road and convenient facilities would increase the rate of visitors coming back. From the park management perspective, to increase the amount of visitors to the park, the park should increase visibility, provide more organized, varied activities and meetings, or special exhibitions according to the particular characteristics of the individual park, to increase awareness of the park. From the park visitors' psychological perspective, visitors are seeking to enjoy the park facilities and environment not only to bring physical relaxation, but also to bring about a psychological cure. With the commonality of attachment structure between the two countries, to improve the place attachment of neighborhood park visitors, collecting regularly visitor feedback will facilitate the sustainable development of neighborhood park attachment.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.2
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• pp.231-238
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• 2023

Since there is a limit to the physically visible horizon that sensors for autonomous driving can perceive, complementary utilization of digital map data such as a Local Dynamic Map (LDM) along the probable route of an Autonomous Vehicle (AV) is proposed for safe and efficient driving. Although the amount of digital map data may be insignificant compared to the amount of information collected from the sensors of an AV, efficient management of map data is inevitable for the efficient information processing of AVs. The objective of this study is to analyze the efficiency of information use and information processing time of AV according to the expansion of the active section of LDM-based static road and traffic information. To carry out this objective, a microscopic simulator model, VISSIM and VISSIM COM, was employed, and an area of about 9 km × 13 km was selected in the Busan Metropolitan Area, which includes heterogeneous traffic flows (i.e., uninterrupted and interrupted flows) as well as various road geometries. In addition, the LDM information used in AVs refers to the real high-definition map (HDM) built on the basis of ISO 22726-1. As a result of the analysis, as the electronic horizon area increases, while short links are intensively recognized on interrupted urban roads and the sum of link lengths increases as well, the number of recognized links is relatively small on uninterrupted traffic road but the sum of link lengths is large due to a small number of long links. Therefore, this study showed that an efficient range of electronic horizon for HDM data collection, processing, and management are set as 600 m on interrupted urban roads considering the 12 links corresponding to three downstream intersections and 700 m on uninterrupted traffic road associated with the 10 km sum of link lengths, respectively.

• Journal of Korea Water Resources Association
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• v.56 no.6
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• pp.403-417
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• 2023

In this research, a methodology was developed for constructing an appropriate rainfall image database for estimating rainfall intensity based on CCTV video. The database was constructed in the Large-Scale Climate Environment Chamber of the Korea Conformity Laboratories, which can control variables with high irregularity and variability in real environments. 1,728 scenarios were designed under five different experimental conditions. 36 scenarios and a total of 97,200 frames were selected. Rain streaks were extracted using the k-nearest neighbor algorithm by calculating the difference between each image and the background. To prevent overfitting, data with pixel values greater than set threshold, compared to the average pixel value for each image, were selected. The area with maximum pixel variability was determined by shifting with every 10 pixels and set as a representative area (180×180) for the original image. After re-transforming to 120×120 size as an input data for convolutional neural networks model, image augmentation was progressed under unified shooting conditions. 92% of the data showed within the 10% absolute range of PBIAS. It is clear that the final results in this study have the potential to enhance the accuracy and efficacy of existing real-world CCTV systems with transfer learning.

• Journal of Animal Science and Technology
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• v.55 no.1
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• pp.7-11
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• 2013

The purpose of this study was to estimate (co) variance components of three milk production traits for genetic evaluation using a multiple lactation model. Each of the first five lactations was treated as different traits. For the parameter estimation study, a data set was set up including lactations from cows calved from 2001 to 2009. The total number of raw lactation records in first to fifth parities reached 1,416,589. At least 10 cows were required for each contemporary group, herd-year-season effect. Sires with fewer than 10 daughters were discarded. Lactations with 305d milk yield exceeding 15,000 kg were removed. In total, 1,456 sires of cows were remained after all the selection steps. A complete pedigree consisting of 292,382 records was used for the study. A sire model containing herd-year-season, caving age, and sire additive genetic effects was applied to the selected lactation data and pedigree for estimating (co) variance components via VCE. Heritabilities and genetic or residual correlations were then derived from the (co) variance estimates using R package. Genetic correlations between lactations ranged from 0.76 to 0.98 for milk yield, 0.79~1.00 for fat yield, 0.75~1.00 for protein yield. On individual lactation basis, relatively low heritability values were obtained 0.14~0.23, 0.13~0.20 and 0.14~0.19 for milk, fat, and protein yields, respectively. For the combined lactation heritability values were 0.29, 0.28, and 0.26 for milk, fat, and protein yields. The estimated parameters will be used in national genetic evaluations for production traits.