• Journal of the Society of Disaster Information
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• v.16 no.4
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• pp.682-690
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• 2020

Purpose: This study builds a database by collecting and refining disaster occurrence data and real-time weather and atmospheric data. In conjunction with the public data provided by the API, we propose a service model for the Big Data-based Urban Safety Index. Method: The plan is to provide a way to collect various information related to disaster occurrence by utilizing public data and SNS, and to identify and cope with disaster situations in areas of interest by real-time dashboards. Result: Compared with the prediction model by extracting the characteristics of the local safety index and weather and air relationship by area, the regional safety index in the area of traffic accidents confirmed that there is a significant correlation with weather and atmospheric data. Conclusion: It proposed a system that generates a prediction model for safety index based on machine learning algorithm and displays safety index by sector on a map in areas of interest to users.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.2
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• pp.147-178
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• 2021

In this study, co-word analysis was conducted to investigate the intellectual structure of the domestic open access area. Through KCI and RISS, 124 research articles related to open access in Korea were selected for analysis, and a total of 1,157 keywords were extracted from the title and abstract. Network analysis was performed on the selected keywords. As a result, 3 domains and 20 clusters were extracted, and intellectual relations among keywords from open access area were visualized through PFnet. The centrality analysis of weighted networks was used to identify the core keywords in this area. Finally, 5 clusters from cluster analysis were displayed on a multidimensional scaling map, and the intellectual structure was proposed based on the correlation between keywords. The results of this study can visually identify and can be used as basic data for predicting the future direction of open access research in Korea.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.1-19
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• 2021

The graph-based tag recommendation algorithm FolkRank can effectively utilize the relationships between three entities, namely users, items and tags, and achieve better tag recommendation performance. However, FolkRank does not consider the internal relationships of user-user, item-item and tag-tag. This leads to the failure of FolkRank to effectively map the tagging behavior which contains user neighbors and item neighbors to a tripartite graph. For item-item relationships, we can dig out items that are very similar to the target item, even though the target item may not have a strong connection to these similar items in the user-item-tag graph of FolkRank. Hence this paper proposes an improved FolkRank algorithm named FolkRank++, which fully considers the user-user and item-item internal relationships in tag recommendation by adding the correlation information between users or items. Based on the traditional FolkRank algorithm, an initial weight is also given to target user and target item's neighbors to supply the user-user and item-item relationships. The above work is mainly completed from two aspects: (1) Finding items similar to target item according to the attribute information, and obtaining similar users of the target user according to the history behavior of the user tagging items. (2) Calculating the weighted degree of items and users to evaluate their importance, then assigning initial weights to similar items and users. Experimental results show that this method has better recommendation performance.

• Journal of Plant Biotechnology
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• v.48 no.1
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• pp.12-17
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• 2021

Saponarin found in young barley sprouts has a variety of beneficial biological and pharmacological properties, including antioxidant, hypoglycemic, antimicrobial, and hepatoprotective activities. Our previous work demonstrated that saponarin content was correlated with the expression levels of three biosynthetic pathway genes [chalcone synthase (HvCHS1), chalcone isomerase (HvCHI), and UDP-Glc:isovitexin 7-O-glucosyltransferase (HvOGT1)] in young barley seedlings under various abiotic stress conditions. In this study, we investigated the saponarin content and expression levels of three saponarin biosynthetic pathway genes in hulled and hulless domestic barley cultivars. In the early developmental stages, some hulled barley cultivars (Kunalbori1 and Heukdahyang) had much higher saponarin contents than did the hulless barley cultivars. An RNA expression analysis showed that in most barley cultivars, decreased saponarin content correlated with reduced expression of HvCHS1 and HvCHI, but not HvOGT1. Heat map analysis revealed both specific increases in HvCHS1 expression in certain hulled and hulless barley cultivars, as well as general changes that occurred during the different developmental stages of each barley cultivar. In summary, our results provide a molecular genetic basis for the metabolic engineering of barley plants to enhance their saponarin content.

• Journal of the Korean Society of Safety
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• v.36 no.4
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• pp.20-28
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• 2021

With an increase in the commercialization of electricity, and the development of advanced and large electric devices and various wireless radio wave services, concerns over the effects of electromagnetic fields on human health have increased. Accordingly, the World Health Organization encouraged the development of international standards by establishing the 'International Electromagnetic Fields Project' in 1996 based on studies on the harmful effects of electromagnetic fields on the human body. Moreover, the National Institute of Environmental Health Sciences (NIEHS) classified electromagnetic fields as possible carcinogens under Group 2B category, even though they have been found to have a weak correlation with those effects on human health. Mid-to-large-sized electric facilities used at industrial sites mostly adopt a commercial frequency of 60 Hz, and workers handling these facilities are exposed to such extremely low frequency (ELF) fields for a long time. A previous study suggested that exposure to ELF electromagnetic fields with frequency ranges from 0 to 300 Hz, even for a short time, at densities higher than 100 μT may have harmful effects on human body as it affects the activation of nerve cells in the central nervous system by inducing an electric field and current and stimulating muscles and the nervous system in the body. Such studies, however, focused on home appliances used by ordinary people, and research on facilities utilizing high-capacity current and operated by workers at industrial sites is lacking. Therefore, in this study, a 3000 kilowatt generator, which is a high-capacity electric facility employed at industrial sites, was investigated, and the size of the magnetic fields generated during its no-load and high-load operations per distance to produce a map was measured to reveal spots deemed hazardous according to domestic and international exposure standards. The findings of this study is expected to alleviate workers' anxiety about the harmful effects of magnetic fields on their body and to minimize the level of exposure during operations.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.4
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• pp.1-10
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• 2022

Attempts to interpret human perspectives using computer vision have been developed in various fields. In this paper, we propose a method for evaluating the walking environment through semantic segmentation results of images from road images. First, the Kakao Map API was used to collect road images, and four-way images were collected from about 50,000 points in JeonJu. 20% of the collected images build datasets through crowdsourcing-based paired comparisons, and train various regression models using paired comparison data. In order to derive the walkability score of the image data, the ranking score is calculated using the Trueskill algorithm, which is a ranking algorithm, and the walkability and analysis using various regression models are performed using the constructed data. Through this study, it is shown that the walkability of Jeonju can be evaluated and scores can be derived through the correlation between pixel distribution classification information rather than human vision.

• Journal of Cadastre & Land InformatiX
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• v.51 no.2
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• pp.141-150
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• 2021

Fine dust is a substance that greatly affects human health, and various studies have been conducted in this regard. Due to the human influence of particulate matter, various studies are being conducted to predict particulate matter grade using past data measured in the monitoring network of Seoul city. In this paper, predictive model have focused on particulate matter concentration in May, 2019, Seoul. The air pollutant variables were used to training such as SO₂, CO, NO₂, O₃. The predictive model based on Adaboost, and training model was dividing PM₁₀ and PM_2.5. As a result of the prediction performance comparison through confusion matrix, the Adaboost model was more conformable for predicting the particulate matter concentration grade. Although air pollutant variables have a higher correlation with PM2.5, training model need to train a lot of data and to use additional variables such as traffic volume to predict more effective PM₁₀ and PM_2.5 distribution grade.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.70.1-70.1
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• 2021

We examine the HI gas kinematics and distributions of galaxy pairs in group or cluster environments from high-resolution Australian Square Kilometer Array Pathfinder (ASKAP) WALLABY pilot observations. We use 32 well-resolved close pair galaxies from the Hydra, Norma, and NGC 4636, two clusters and a group of which are identified by their spectroscopy information and additional visual inspection. We perform profile decomposition of HI velocity profiles of the galaxies using a new tool, BAYGAUD which allows us to separate a line-of-sight velocity profile into an optimal number of Gaussian components based on Bayesian MCMC techniques. Then, we construct super profiles via stacking of individual HI velocity profiles after aligning their central velocities. We fit a model which consists of double Gaussian components to the super profiles, and classify them as kinematically cold and warm HI gas components with respect to their velocity dispersions, narrower or wider 𝜎, respectively. The kinematically cold HI gas reservoir (M_cold/M_HI) of the paired galaxies is found to be relatively higher than that of unpaired control samples in the clusters and the group, showing a positive correlation with the HI mass in general. Additionally, we quantify the gravitational instability of the HI gas disk of the sample galaxies using their Toomre Q parameters and HI morphological disturbances. While no significant difference is found for the Q parameter values between the paired and unpaired galaxies, the paired galaxies tend to have larger HI asymmetry values which are derived using their moment0 map compared to those of the non-paired control sample galaxies in the distribution.

• Plant Breeding and Biotechnology
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• v.1 no.1
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• pp.1-8
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• 2013

Low-temperature stress is an important factor controlling the growth and development of rice (Oryza sativa L.) in temperate region. In this study, a molecular linkage map consisting of 136 SSR markers was employed to identify QTL associated with cold tolerance at the seedling stage. 80 recombinant inbred lines (RILs) from an intersubspecific cross between Milyang23 (O. sativa ssp. Indica) and Hapcheonaengmi3, a japonica weedy rice and the parents were evaluated for leaf discoloration and SAPD value of seedlings. Rice plants were grown for 15 days in the low-temperature condition (13/20℃ day/night) and the control condition (25/20℃ day/night) in the growth chamber. The degree of leaf discoloration showed a highly significant correlation with the SPAD value in the low-temperature plot (r = -0.708, P < 0.0001). A total of four QTLs for SPAD were identified and the phenotypic variance explained by each QTL ranged from 5.4 to 16.0%. Two QTLs detected in the control condition were located on chromosomes 2 and 5, respectively. Two QTL on chromosomes 1 and 4 were detected at the low-temperature condition and Hapcheonaengmi3 alleles increased the SPAD values at these loci. Substitution mapping was conducted to delimit the position of qSPA-4 using introgression lines derived from the same cross. Results indicated that qSPA-4 was located in a 810-Kb region flanked by RM16333 and RM16368. The results indicated that Hapcheonaengmi3 contains QTL alleles that are likely to improve cold tolerance of Indica rice.

• Journal of Wind Energy
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• v.13 no.2
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• pp.42-52
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• 2022

In this paper, we propose a time-series generation methodology using a generative adversarial network (GAN) for long-term prediction of wind and sea conditions, which are information necessary for operations and maintenance (O&M) planning and optimal plans for offshore wind farms. It is a "Conditional TimeGAN" that is able to control time-series data with monthly conditions while maintaining a time dependency between time-series. For the generated time-series data, the similarity of the statistical distribution by direction was confirmed through wave and wind rose diagram visualization. It was also found that the statistical distribution and feature correlation between the real data and the generated time-series data was similar through PCA, t-SNE, and heat map visualization algorithms. The proposed time-series generation methodology can be applied to monthly or annual marine weather prediction including probabilistic correlations between various features (wind speed, wind direction, wave height, wave direction, wave period and their time-series characteristics). It is expected that it will be able to provide an optimal plan for the maintenance and optimization of offshore wind farms based on more accurate long-term predictions of sea and wind conditions by using the proposed model.