• International Journal of Computer Science & Network Security
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• v.21 no.12spc
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• pp.604-610
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• 2021

Human capital is the defining value of the national economy under market conditions. The manifestation of human capital is realized as an intellectual and creative capital, theoretically grounded and proven. The realization of intellectual capital is realized through the research creativity of scientists and researchers, and creative capital is manifested through artists and thinkers. Accordingly, creativity in market conditions forms a separate source of income and is an essential article in the formation of the GDP of the national economy. This research aims to analyze human capital from the perspective of cultural and creative industries. Research methods: systematization; comparative analysis of individual indicators of advanced countries of the world on the training system; statistical, taking into account macroeconomic indicators to assess the level of national creativity potential; system and logical analysis; method of information synthesis. Research results. The structural and quantitative composition of the factors of intellectual and creative capital formation has been systematized. The article proves that the unique properties of human capital, knowledge, creativity, experience and professional skills are the push factors of creativity development of the national economy and provide the priority development of creative and cultural industry that allows generating the added value on the national scale. The functions of creativity in the sphere of cultural industries are highlighted. It is noted that education and creativity of both intellectual and creative capital are the forming basis. The research of the world's advanced countries on the creativity index has pointed out the Netherlands as the leading country in the quantitative measurement of creativity. The economic development factors of the Netherlands were analyzed from the position of economic creativity, which allowed the formation of a two-factor model providing priority development of creativity in the cultural and creative industries.

• The Journal of Information Systems
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• v.31 no.4
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• pp.25-45
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• 2022

Purpose In this paper, we propose the method to extend topic modeling techniques in order to derive data-based research hypotheses when establishing research hypotheses for social sciences, As a concept in contrast to the existing deductive hypothesis establishment methodology for the social science research, the topic modeling technique was expanded to enable the so-called inductive hypothesis establishment methodology, and an analysis case of the Seongsan Ilchulbong online review based on the proposed methodology was presented. Design/methodology/approach In this paper, an extension architecture and extension algorithm in the form of extending the existing topic modeling were proposed. The extended architecture and algorithm include data processing method based on topic ratio in document, correlation analysis and regression analysis of processed data for topics derived by existing topic modeling. In addition, in this paper, an analysis case of the online review of Seongsan Ilchulbong Peak was presented by applying the extended topic modeling algorithm. An exploratory analysis was performed on the Seongsan Ilchulbong online reviews through the basic text analysis. The data was transformed into 5-point scale to enable correlation and regression analysis based on the topic ratio in each online review. A regression analysis was performed using the derived topics as the independent variable and the review rating as the dependent variable, and hypotheses could be derived based on this, which enable the so-called inductive hypothesis establishment. Findings This paper is meaningful in that it confirmed the possibility of deriving a causal model and setting an inductive hypothesis through an extended analysis of topic modeling.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.6
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• pp.1-11
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• 2022

Recently, climate change has been regarded as a major cause of large-scale forest fires worldwide, and there is concern that more frequent and severe forest fires will occur due to the level of greenhouse gas emissions. In this study, the daily Keetch and Byram Drought Index (KBDI) of the Baekdudaegan in Chungcheong region including Sobaeksan, Songnisan, and Woraksan National Parks were calculated to assess effect of climate change on the forest fire potential- severity of annual maximum KBDI and frequency of high KBDI days. The present (2000~2019) and future KBDI(2021~2040, 2041~2060, 2081~2090) were calculated based on the meteorological observation and the ensemble regional climate model of the SSP1-2.6 and SSP5-8.5 scenarios with a spatial resolution of 1-km provided by Korea Meteorological Administration(KMA). Under the SSP5-8.5 scenario, 6.5℃ increase and 14% precipitation increase are expected at the end of the 21st century. The severity of maximum daily KBDI increases by 48% (+50mm), and the frequency of high KBDI days (> 100 KBDI) increases more than 100 days, which means the high potential for serious forest fires. The analysis results showed that Songnisan National Park has the highest potential for forest fire risk and will continue to be high in intensity and frequency in the future. It is expected that the forest vulnerability of the Baekdudaegan in the Chungcheong region will greatly increase and the difficulty in preventing and suppressing forest fires will increase as the abundance of combustible materials increases along with climate changes.

• Journal of Korea Trade
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• v.26 no.1
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• pp.20-32
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• 2022

Purpose - This paper intends to make theoretical analysis and empirical test on the factors influencing China's export to South Korea, and draw conclusions about China's export efficiency and trade potential. Based on the conclusions, the reasons for China's trade deficit with South Korea are found, and a solution is put forward for solving the problem of China's trade deficit with South Korea. Design/methodology - Based on the data of 2004-2017 years in China, this paper uses the stochastic frontier gravity model to analyze the influencing factors of China's export to South Korea, as well as the export efficiency of each province and the export potential that can be explored. Findings - First, in terms of the factors affecting China's export trade to South Korea, the GDP of the provinces and cities in China, the FDI of South Korea to the provinces and cities in China, the GDP of South Korea, the population and education level of provinces and cities in China can significantly promote the export scale of Chinese provinces and cities to South Korea. The distance between Chinese provincial capitals and the South Korean capital significantly hinders Chinese exports to South Korea; Second, in terms of export trade efficiency, the trade exchange rate of the economically developed cities along the eastern coast of China and several provinces that are close to South Korea is higher than that of the cities in the central and western regions; Third, economic globalization makes trade more convenient, the average export trade efficiency of China's exports to South Korea showed an upward trend. However, under the influence of the 2008 global financial crisis, the export trade efficiency declined from 2008 to 2009, indicating that the impact of the financial crisis on the trade efficiency cannot be ignored. Originality/value - This paper finds out the influencing factors of China's export to South Korea, analyzes the export efficiency of different provinces and cities, excavates the export potential, and puts forward some suggestions for the balanced development of China and South Korea trade in the next step.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.3 no.2
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• pp.67-72
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• 2022

Ecological research relies on the interpretation of large amounts of visual data obtained from extensive wildlife surveys, but such large-scale image interpretation is costly and time-consuming. Using an artificial intelligence (AI) machine learning model, especially convolution neural networks (CNN), it is possible to streamline these manual tasks on image information and to protect wildlife and record and predict behavior. Ecological research using deep-learning-based object recognition technology includes various research purposes such as identifying, detecting, and identifying species of wild animals, and identification of the location of poachers in real-time. These advances in the application of AI technology can enable efficient management of endangered wildlife, animal detection in various environments, and real-time analysis of image information collected by unmanned aerial vehicles. Furthermore, the need for school education and social use on biodiversity and environmental issues using AI is raised. School education and citizen science related to ecological activities using AI technology can enhance environmental awareness, and strengthen more knowledge and problem-solving skills in science and research processes. Under these prospects, in this paper, we compare the results of our early 2013 study, which automatically identified African cichlid fish species using photographic data of them, with the results of reanalysis by CNN deep learning method. By using PyTorch and PyTorch Lightning frameworks, we achieve an accuracy of 82.54% and an F1-score of 0.77 with minimal programming and data preprocessing effort. This is a significant improvement over the previous our machine learning methods, which required heavy feature engineering costs and had 78% accuracy.

• Steel and Composite Structures
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• v.44 no.3
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• pp.437-450
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• 2022

When the vertical load-bearing members in high-rise structures fail locally, the beam-column joints play an important role in the redistribution of the internal forces. In this paper, a static laboratory test of three full-scale flush flange beam-reinforced connections with side and cover plates (CP-FBSP connection) with double half-span steel beams and single L-shaped columns composed of concrete-filled steel tubes (L-CFST columns) was conducted. The influence of the side plate width and cover plate thickness on the progressive collapse resistance of the substructure was thoroughly analyzed. The failure mode, vertical force-displacement curves, strain variation, reaction force of the pin support and development of internal force in the section with the assumed plastic hinge were discussed. Then, through the verified finite element model, the corresponding analyses of the thickness and length of the side plates, the connecting length between the steel beam flange and cover plate, and the vertical-force eccentricity were carried out. The results show that the failure of all the specimens occurred through the cracking of the beam flange or the cover plate, and the beam chord rotations measured by the test were all greater than 0.085 rad. Increasing the length, thickness and width of the side plates slightly reduced the progressive collapse resistance of the substructures. The vertical-force eccentricity along the beam length reduced the progressive collapse resistance of the substructure. An increase in the connecting length between the beam flange and cover plate can significantly improve the progressive collapse resistance of substructures.

• Structural Engineering and Mechanics
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• v.81 no.6
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• pp.715-728
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• 2022

A new type of buckling-restrained braces (BRBs) with a longitudinally profiled steel plate working as the core (LPBRB) is proposed and experimentally investigated. Different from conventional BRBs with a constant thickness core, both stiffness and strength of the longitudinally profiled steel core along its longitudinal direction can change through itself variable thickness, thus the construction of LPBRB saves material and reduces the processing cost. Four full-scale component tests were conducted under quasi-static cyclic loading to evaluate the seismic performance of LPBRB. Three stiffening methods were used to improve the fatigue performance of LPBRBs, which were bolt-assembled T-shaped stiffening ribs, partly-welded stiffening ribs and stiffening segment without rib. The experimental results showed LPBRB specimens displayed stable hysteretic behavior and satisfactory seismic property. There was no instability or rupture until the axial ductility ratio achieved 11.0. Failure modes included the out-of-plane buckling of the stiffening part outside the restraining member and core plate fatigue fracture around the longitudinally profiled segment. The effect of the stiffening methods on the fatigue performance is discussed. The critical buckling load of longitudinally profiled segment is derived using Euler theory. The local bulging behavior of the outer steel tube is analyzed with an equivalent beam model. The design recommendations for LPBRB are presented finally.

• Wind and Structures
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• v.34 no.2
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• pp.215-230
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• 2022

Majority of transmission line system failures at many locations worldwide have been caused by severe localized wind events in the form of tornadoes and downbursts. This study evaluates the structural response of two different transmission line systems under equivalent F2 tornadoes obtained from real incidents. Two multi-span self-supported transmission line systems are considered in the study. Nonlinear three-dimensional finite element models are developed for both systems. The finite element models simulate six spans and five towers. Computational Fluid Dynamics (CFD) simulations are used to develop the tornado wind fields. Using a proper scaling method for geometry and velocity, full-scale tornado flow fields for the Stockton, KS, 2005 and Goshen County WY, 2009 are developed and considered together with a previously developed tornado wind field. The tornado wind profiles are obtained in terms of tangential, radial, and axial velocities. The simulated tornadoes are then normalized to the maximum velocity value for F2 tornadoes in order to compare the effect of different tornadoes having an equal magnitude. The tornado wind fields are incorporated into a three-dimensional finite element model. By varying the location of the tornado relative to the transmission line systems, base shears of the tower of interest and peak internal forces in the tower members are evaluated. Sensitivity analysis is conducted to assess the variation of the structural behaviour of the studied transmission lines associated with the location of the tornado relative to the tower of interest. The tornado-induced forces in both lines due to the three different normalized tornadoes are compared with corresponding values evaluated using the simplified load case method recently incorporated in the ASCE-74 (2020) guidelines, which was previously developed based on the research conducted at Western University.

• Imaging Science in Dentistry
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• v.52 no.3
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• pp.239-244
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• 2022

Purpose: Despite the proliferation of numerous morphometric and anthropometric methods for sex identification based on linear, angular, and regional measurements of various parts of the body, these methods are subject to error due to the observer's knowledge and expertise. This study aimed to explore the possibility of automated sex determination using convolutional neural networks(CNNs) based on lateral cephalometric radiographs. Materials and Methods: Lateral cephalometric radiographs of 1,476 Iranian subjects (794 women and 682 men) from 18 to 49 years of age were included. Lateral cephalometric radiographs were considered as a network input and output layer including 2 classes(male and female). Eighty percent of the data was used as a training set and the rest as a test set. Hyperparameter tuning of each network was done after preprocessing and data augmentation steps. The predictive performance of different architectures (DenseNet, ResNet, and VGG) was evaluated based on their accuracy in test sets. Results: The CNN based on the DenseNet121 architecture, with an overall accuracy of 90%, had the best predictive power in sex determination. The prediction accuracy of this model was almost equal for men and women. Furthermore, with all architectures, the use of transfer learning improved predictive performance. Conclusion: The results confirmed that a CNN could predict a person's sex with high accuracy. This prediction was independent of human bias because feature extraction was done automatically. However, for more accurate sex determination on a wider scale, further studies with larger sample sizes are desirable.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.6
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• pp.102-111
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• 2022

The aim of this study is to assess the seismic performance of octagonal hollow cross section reinforced concrete bridge pier, and to investigate the effect of longitudinal reinforcement ratios on the failure behavior. Four octagonal hollow section RC bridge columns of small scale model were tested under a quasi-static cyclically reversed horizontal load with constant axial load. The volumetric ratio of transverse spiral hoop of all specimens was maintained constant(0.206%), the ratios of longitudinal reinforcement were varied(2.36 ~ 4.71%). Failure behavior and seismic performance were investigated. Three specimens with the exception of lap spliced specimen showed flexure-shear failure at final stage. The test results with the exception of lap spliced specimen showed that the displacement ductility factor and accumulated energy dissipation decreased in inverse proportion to the ratio of longitudinal steel.