• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.503-506
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• 2022

The absolute decreasing in the school-age population due to the low fertility rate that has lasted for more than 20 years is a result of the lack of filling in universities. The lack of filling in general universities is more serious in universities of local area than universities in the metropolitan area, and in two-year junior colleges rather than general universities. The purpose of this study is to how the highschool grading system and university rankings have an effect on the lack of filling enterance quota for new students.

• Korean Journal of Occupational Health Nursing
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• v.32 no.1
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• pp.1-8
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• 2023

Purpose: This descriptive study analyzed the factors affecting turnover intention among married nurses in small- and medium-sized hospitals with less than 300 beds. Methods: Data were collected from 177 married nurses located in K city from April 8, 2022 to April 21, 2022 using a questionnaire. Descriptive statistics, independent tests, one-way ANOVA, Pearson's correlation coefficient test, and multiple regression were analyzed using the SPSS/WIN 22 program. Results: Nurses rated items on a scale of five points. Their average rating for job satisfaction was 3.43±0.30, resilience was 3.51±0.38, and role conflict was 2.60±0.63. The nursing practice environment was rated 3.12±0.44, and turnover intention was 3.14±0.62 points. Age, job satisfaction, and nursing practice environment accounted for 25.1% of turnover intention (F=6.90, p<.001). Conclusion: To decrease married nurses' turnover intention in small- and medium-sized hospitals with less than 300 beds, these findings can help develop a program that addresses the causes of high turnover amongst married nurses in local hospitals.

• Journal of Forest and Environmental Science
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• v.26 no.1
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• pp.9-15
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• 2010

This paper analyzes data on the plant species diversity and their contribution to the livelihoods of rural people in five villages of Domar upazila, Nilphamari district, Bangladesh. Assessment was done by means of multistage random sampling. Information collected from a total of 40 households ranging from small, medium and large categories. A total of 52 plant species belonging to 34 families were identified as being important to local livelihoods. Fruits (37%), timber (23%) and medicinal (17%) species were the most important plant use categories. Determination of the relative density of the different species revealed that Areca catechu constitutes 19.17% of homestead vegetation of the area followed by Artocarpus heterophyllus, which occupies 10.34%. Margalef index showed that there is no major difference (5.11 for large, 5.49 for medium, 4.73 for small) across the different size classes and Shannon-Weiner Index of the study area varies from 2.75 to 2.98. Results show that the average annual homestead income varied from US$108.69 to US$291.67 and contribute 6.63% of the household income.

• Journal of Korean Society for Atmospheric Environment
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• v.4 no.1
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• pp.45-57
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• 1988

This is a close relationship between energy consumption and the way in which we develop and manage our regions. This study has estimated and compared energy requirements for the journey to work, resulting from alternative population and employment growth patterns in a rural-urban regional settlement of Korea. The broad scope of work was as follows: i) Select the study area ii) Formulate alternative growth patterns iii) Develop the Hansen and double-constrained gravity model iv) Application of Vogel's approximation method and the developed Hansen and gravity model to the case study area. v) Analyze the relationship between spatial structure, transport energy-requirements and environmental pollution. At issue here is the trade-off between air pollution averages and variations. Policies concentrating manufacturing industry and other regional facilities, for instance, may indeed reduce average pollution levels at the benefit of less-car miles, thus, reducing auto pollution, in the region, but increase local pollution peaks.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.69.3-70
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• 2021

We present the chemical properties of star-forming dwarf galaxies (SFDGs) in five filamentary structures (Leo II A, Leo II B, Leo Minor, Canes Venatici, and Virgo III) around the Virgo cluster using the Sloan Digital Sky Survey optical spectroscopic data and Galaxy Evolution Explorer ultraviolet photometric data. We investigate the relationship between stellar mass, gas-phase metallicity, and specific star formation rate (sSFR) of SFDGs in the Virgo filaments in comparison to those in the Virgo cluster and field. We find that, at a given stellar mass, SFDGs in the Virgo filaments show lower metallicity and higher sSFR than those in the Virgo cluster on average. We observe that SFDGs in the Virgo III filament show enhanced metallicities and suppressed star formation activities comparable to those in the Virgo cluster, whereas SFDGs in the other four filaments exhibit similar properties to the field counterparts. Moreover, about half of the galaxies in the Virgo III filament are found to be morphologically transitional dwarf galaxies that are supposed to be on the way to transforming into quiescent dwarf early-type galaxies. Based on the analysis of the galaxy perturbation parameter, we propose that the local environment represented by the galaxy interactions might be responsible for the contrasting features in "chemical pre-processing" found in the Virgo filaments.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.36.1-37
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• 2021

Six images of IRC+10216 taken by the Hubble Space Telescope at three epochs in 2001, 2011, and 2016 are compared in the rest frame of the central carbon star. An accurate astrometry has been achieved with the help of Gaia Data Release 2. The positions of the carbon star in the individual epochs are determined using its known proper motion, defining the rest frame of the star. In 2016, a local brightness peak with compact and red nature is detected at the stellar position. A comparison of the color maps between 2016 and 2011 epochs reveals that the reddest spot moved along with the star, suggesting a possibility of its being the dusty material surrounding the carbon star. Relatively red, ambient region is distributed in an Ω shape and well corresponds to the dusty disk previously suggested based on near-infrared polarization observations. In a larger scale, differential proper motion of multiple ring-like pattern in the rest frame of the star is used to derive the average expansion velocity of transverse wind components, resulting in ~12.5 km s-1 (d/123 pc), where d is the distance to IRC+10216. Three dimensional geometry is implied from its comparison with the line-of-sight wind velocity determined from half-widths of submillimeter emission line profiles of abundant molecules. Uneven temporal variations in brightness for different searchlight beams and anisotropic distribution of extended halo are revisited in the context of the stellar light illumination through a porous envelope with postulated longer-term variations for a period of 10 years.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.75.3-75.3
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• 2019

The filament is an interesting structure in the Universe because clusters form at the nodes of filaments and grow through the continuous accretion of individual galaxies and groups from the surrounding filaments. We study the chemical properties of star-forming (SF) galaxies in the five large-scale filamentary structures (Leo II A, Leo II B, Leo Minor, Canes Venatici, and Virgo III) related with the Virgo cluster, with the spectroscopic data taken with the SDSS DR12, and compare them with those of the Virgo cluster and field galaxies. In mass-metallicity relation, most of the SF galaxies in Virgo-related filaments (except Virgo III filament) show lower metallicity on average than the Virgo cluster SF galaxies, but similar to field counterparts. These chemically less evolved feature of SF galaxies in the filaments and field are more pronounced for lower mass galaxies. This is probably because low mass galaxies have low potential wells and are therefore likely to be sensitive to cluster environmental effects. Interestingly, we find that the metallicity enhancement of SF galaxies in the Virgo III filament. In chemical and morphological perspectives, SF galaxies in the Virgo III thought to be transitional objects possibly transformed from SF late-type galaxies and are on the way to red early-type galaxies in the filament environment. This is the first discovery of systematic 'chemical pre-processing' signature for filament galaxies in Local Universe before they fall into the cluster.

• Computers and Concrete
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• v.32 no.5
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• pp.475-486
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• 2023

Nondestructive evaluation (NDE) is an important task of civil engineering structure monitoring and inspection, but minor damage such as small cracks in local structure is difficult to observe. If cracks continued expansion may cause partial or even overall damage to the structure. Therefore, monitoring and detecting the structure in the early stage of crack propagation is important. The crack detection technology based on machine vision has been widely studied, but there are still some problems such as bad recognition effect for small cracks. In this paper, we proposed a deep learning method based on sweep signals to evaluate concrete surface crack with a width less than 1 mm. Two convolutional neural networks (CNNs) are used to analyze the one-dimensional (1D) frequency sweep signal and the two-dimensional (2D) time-frequency image, respectively, and the probability value of average damage (ADPV) is proposed to evaluate the minor damage of structural. Finally, we use the standard deviation of energy ratio change (ERVSD) and infrared thermography (IRT) to compare with ADPV to verify the effectiveness of the method proposed in this paper. The experiment results show that the method proposed in this paper can effectively predict whether the concrete surface is damaged and the severity of damage.

• Journal of Information Processing Systems
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• v.19 no.4
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• pp.427-438
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• 2023

Plenty of works have indicated that single image super-resolution (SISR) models relying on synthetic datasets are difficult to be applied to real scene text image super-resolution (STISR) for its more complex degradation. The up-to-date dataset for realistic STISR is called TextZoom, while the current methods trained on this dataset have not considered the effect of multi-scale features of text images. In this paper, a multi-scale and attention fusion model for realistic STISR is proposed. The multi-scale learning mechanism is introduced to acquire sophisticated feature representations of text images; The spatial and channel attentions are introduced to capture the local information and inter-channel interaction information of text images; At last, this paper designs a multi-scale residual attention module by skillfully fusing multi-scale learning and attention mechanisms. The experiments on TextZoom demonstrate that the model proposed increases scene text recognition's (ASTER) average recognition accuracy by 1.2% compared to text super-resolution network.

• The Journal of Korea Robotics Society
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• v.19 no.1
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• pp.79-91
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• 2024

Large warehouses are building automation systems to increase efficiency. However, small warehouses, military bases, and local stores are unable to introduce automated logistics systems due to lack of space and budget, and are handling tasks manually, failing to improve efficiency. To solve this problem, this study designed small loading and unloading equipment that can be mounted on transportation vehicles. The equipment can be controlled remotely and is automatically controlled from the point where pallets loaded with cargo are visible using real-time video from an attached camera. Cargo recognition and control command generation for automatic control are achieved through a newly designed deep learning model. This model is designed to be optimized for loading and unloading equipment and mission environments based on the YOLOv3 structure. The trained model recognized 10 types of palettes with different shapes and colors with an average accuracy of 100% and estimated the state with an accuracy of 99.47%. In addition, control commands were created to insert forks into pallets without failure in 14 scenarios assuming actual loading and unloading situations.