• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.25-30
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• 2022

The article is devoted to the actual problem of the use of digital technologies in modern cinema in developed countries. The purpose of the study is to identify the essence of the term "cyberdramaturgy" and the problems of its use in modern film production. The research methodology is based on a systematic approach and includes the methods of the general scientific group (analysis, synthesis, deduction, induction), as well as a number of special methods: the method of content analysis of scientific literature on the research topic; sociological survey method; as well as the method of statistical analysis. The results of the survey were analyzed using the Neural Designer program (a tool for advanced statistical analytics) and translated into a graphical diagram format for clarity of perception. Answers in 75 questionnaires were evaluated by the average score for six analysis criteria, which made it possible to bring all the calculations to a 10-point scale. As a result of the study, the author of the article concluded the following: directors believe that the use of cyber analogues of actors and backgrounds leads to the blurring of genres, the hybridization of cinema and animation; directors are also concerned about the problem of replacing the director himself with a special program. The writers are completely concerned with the problem of machine scripting with almost infinite variability beyond the human imagination. Directors-producers believe that the cyberdramaturgy development will lead to completely new standards of cinematic quality, sharply different from the traditional assessment of acting and scene setting, to the appreciation of 3D animation as the highest category in the art. Such innovations actually devalue all international cinematography awards, as cyberdrama reduces the value of cyberactors to zero. It is impossible to bail out an "Oscar" or a "Golden Globe" award for a digital double or a separate cyber model that is used in the film instead of the actors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4420-4438
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• 2021

Image dehazing is an ill-posed problem which is far from being solved. Traditional image dehazing methods often yield mediocre effects and possess substandard processing speed, while modern deep learning methods perform best only in certain datasets. The haze removal effect when processed by said methods is unsatisfactory, meaning the generalization performance fails to meet the requirements. Concurrently, due to the limited processing speed, most dehazing algorithms cannot be employed in the industry. To alleviate said problems, a lightweight fast dehazing network based on a multiple scale-patch framework (MSP) is proposed in the present paper. Firstly, the multi-scale structure is employed as the backbone network and the multi-patch structure as the supplementary network. Dehazing through a single network causes problems, such as loss of object details and color in some image areas, the multi-patch structure was employed for MSP as an information supplement. In the algorithm image processing module, the image is segmented up and down for processed separately. Secondly, MSP generates a clear dehazing effect and significant robustness when targeting real-world homogeneous and nonhomogeneous hazy maps and different datasets. Compared with existing dehazing methods, MSP demonstrated a fast inference speed and the feasibility of real-time processing. The overall size and model parameters of the entire dehazing model are 20.75M and 6.8M, and the processing time for the single image is 0.026s. Experiments on NTIRE 2018 and NTIRE 2020 demonstrate that MSP can achieve superior performance among the state-of-the-art methods, such as PSNR, SSIM, LPIPS, and individual subjective evaluation.

• Journal of Korea Entertainment Industry Association
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• v.13 no.3
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• pp.333-342
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• 2019

The purpose of this study is to compare and analyze the cases of the multiplex cinema industry of CJ CGV, Lotte Cinema and Megabox to study what CJ CGV's innovative core competence is from a management strategy perspective. Through this, the core competence strategies, Value, Rareness, Inimitability, and Organization(VRIO) were analyzed in order to derive from the major success factors based on the expansion process of Cultureplex. According to the analysis results, CJ CGV's differentiated value roots from Cultureplex, which CJ CGV priorities in creating movie theaters a cultural entertainment hub. The ability of CJ CGV in transforming the cinema into a cultural and living playground through technological innovation is it's cutting edge from its competitors under the rareness factor. A CJ CGV attains its inimitability by establishing social brand power as an inclusive social contribution. An organization of CJ CGV is a globalization worldwide. CJ CGV is to increase the brand value of cultural experience movie theaters and enhance customer satisfaction by expanding the use of existing movie theaters and pioneering with innovative development to theaters. As more to be sought out from this thesis, CJ CGV has steadily increased its competitive edge, raising its core competence of business value.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.8
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• pp.541-550
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• 2017

The purpose of this study is to develop a personality education program for university students based on animation. The selection of the animation media to be used in the character education program to cultivate the eight core value virtues, eg, efficacy, honesty, responsibility, respect, consideration, communication and cooperation, Based on the eight elements of self - identity of college students, such as job, religion, politics, philosophical lifestyle, friendship, heterosexuality, gender roles and leisure activities. The process of developing personality education program model and activity based on animation of this college student is as follows. The necessity of developing personality education program for college students, Setting basic direction of character education program based on animation, Selection of animation media, Development of personality education program model based on animation, Development of personality education program activity based on animation of self identification, And finalization of personality education program based on final animation. In this study, a total of 16 characters were developed according to the sub - factors of self - identity in the personality education program of university students based on animation.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.5
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• pp.211-218
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• 2016

This study focuses on the evaluation on the satisfaction of school education system based on perception levels of students corresponding to school locations. Twenty eight variables concerning with school education system were selected based on literature review and six factors such as reliability, sympathy, student supporting system, teachers' ability, principal physical environments, secondary physical environments were extracted by factor analysis. Satisfaction evaluation was performed by SERVPERP model based on perception level, and differences among respondents as well as school locations were analyzed by t-test and ANOVA. The results said there is no difference on teachers' ability factors. Especially, perception levels of students in rural area were lower than those in urban area except teachers' ability and secondary physical environments factors. Most respondents dissatisfy the school education system and they have no intention to recommend their school facilities (hardware) as well as educational programs (software) to other students in different schools.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.3
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• pp.291-300
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• 2016

The emergence of smart devices and IoT leads to the appearance of O2O service to blur the difference between online and offline. As online services' merits were added to the offline market, it caused a change in the dynamics of the offline industry, which means the offline-space's digitization. Unlike these changing aspects of the offline market, exhibition industry grows steadily in the industry, however it is also possible to create a new value added by combining O2O service. We conducted a survey targeting 20 spectators in '2015 Seoul Design Festival' at COEX. The survey was used to analysis of the spatial structure and generate the dataset for machine learning. We identified problems with the analysis study of the existing spatial structure, and based on this investigation we propose a new method for analyzing a spatial structure. Also by processing a machine learning technique based on the generated dataset, we propose a novel evaluation model of exhibition-space cells for O2O service layout.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.7
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• pp.719-728
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• 2018

Each country has its preferred image and how to convey it effectively. The study aims to find traditional Korean makeup methods and ways to effectively convey a preferred image. Among the ancient manuscripts of Joseon Dynasty, the book " Galgap Collection " has ten ancestors who express their favorite eyebrows in the form of a grandfather. In this study, we applied tens of thousands of words to the actual model to solve the problem and make up the methods of literature, the Internet, and example. The model stimuli were measured by conducting a street experiment of 10 makeup experts and 70 men and women's blinds. The result was that the " Gaewon- .aemi " type seemed to be the best, attractive and most consistent with the shape of the thinking eyebrows and the current fashion of eyebrows. In a variety of nonverbal ways expressed in the classics, the study looked at ways to use visual poetry to communicate effectively. This research will help transform design ideas and help understand cultural trends of different times.

• Geomechanics and Engineering
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• v.31 no.2
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• pp.129-147
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• 2022

The properties of soil are naturally highly variable and thus, to ensure proper safety and reliability, we need to test a large number of samples across the length and depth. In pile foundations, conducting field tests are highly expensive and the traditional empirical relations too have been proven to be poor in performance. The study proposes a state-of-art Particle Swarm Optimization (PSO) hybridized Artificial Neural Network (ANN), Extreme Learning Machine (ELM) and Adaptive Neuro Fuzzy Inference System (ANFIS); and comparative analysis of metaheuristic models (ANN-PSO, ELM-PSO, ANFIS-PSO) for prediction of bearing capacity of pile foundation trained and tested on dataset of nearly 300 dynamic pile tests from the literature. A novel ensemble model of three hybrid models is constructed to combine and enhance the predictions of the individual models effectively. The authenticity of the dataset is confirmed using descriptive statistics, correlation matrix and sensitivity analysis. Ram weight and diameter of pile are found to be most influential input parameter. The comparative analysis reveals that ANFIS-PSO is the best performing model in testing phase (R² = 0.85, RMSE = 0.01) while ELM-PSO performs best in training phase (R² = 0.88, RMSE = 0.08); while the ensemble provided overall best performance based on the rank score. The performance of ANN-PSO is least satisfactory compared to the other two models. The findings were confirmed using Taylor diagram, error matrix and uncertainty analysis. Based on the results ELM-PSO and ANFIS-PSO is proposed to be used for the prediction of bearing capacity of piles and ensemble learning method of joining the outputs of individual models should be encouraged. The study possesses the potential to assist geotechnical engineers in the design phase of civil engineering projects.

• Wind and Structures
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• v.37 no.4
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• pp.255-274
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• 2023

The aim of this paper is to enhance the accuracy of predicting time-averaged external surface pressures on low-rise buildings by utilizing Computational Fluid Dynamics (CFD) simulations. To achieve this, benchmark studies of the Silsoe cube and the Texas Tech University (TTU) experimental building are employed for comparison with simulation results. The paper is structured into three main sections. In the initial part, an appropriate domain size is selected based on the precision of mean pressure coefficients on the windward face of the cube, utilizing Reynolds Averaged Navier-Stokes (RANS) turbulence models. Subsequently, recommendations regarding the optimal computational domain size for an isolated building are provided based on revised findings. Moving on to the second part, the Silsoe cube model is examined within a horizontally homogeneous computational domain using more accurate turbulence models, such as Large Eddy Simulation (LES) and hybrid RANS-LES models. For computational efficiency, transient simulation settings are employed, building upon previous studies by the authors at the Windstorm Impact, Science, and Engineering (WISE) Lab, Louisiana State University (LSU). An optimal meshing strategy is determined for LES based on a grid convergence study. Three hybrid RANS-LES cases are investigated to achieve desired enhancements in the distribution of mean pressure coefficients on the Silsoe cube. In the final part, a 1:10 scale model of the TTU building is studied, incorporating the insights gained from the second part. The generated flow characteristics, including vertical profiles of mean velocity, turbulence intensity, and velocity spectra (small and large eddies), exhibit good agreement with full-scale (TTU) measurements. The results indicate promising roof pressures achieved through the careful consideration of meshing strategy, time step, domain size, inflow turbulence, near-wall treatment, and turbulence models. Moreover, this paper demonstrates an improvement in mean roof pressures compared to other state-of-the-art studies, thus highlighting the significance of CFD simulations in building aerodynamics.

• Fashion & Textile Research Journal
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• v.25 no.5
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• pp.626-633
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• 2023

This study aimed to reveal the structural relationship between the awareness of the 4th industrial revolution, entrepreneurship knowledge, entrepreneurship mind, and entrepreneurship intention in college students majoring in beauty. To this end, the study used a questionnaire to survey college students majoring in beauty. A total of 300 copies of the questionnaire were distributed, and after weeding out insincere responses, 283 copies were used for a final analysis. The analysis was carried out using SPSS 26.0. The results are as follows: First, the awareness of the 4th industrial revolution had a positive effect on entrepreneurship knowledge, entrepreneurship mind, and entrepreneurship intention of the subjects, and entrepreneurship mind had an effect on entrepreneurship intention. Second, it was verified that the goodness of fit of the structural model on the relationship between the awareness of the 4th industrial revolution and entrepreneurship intention was satisfactory. After analyzing the hypotheses on the structural model, it was discovered that all of them were adopted. In respect to the awareness of the 4th industrial revolution and entrepreneurship intention, the indirect effect of entrepreneurship knowledge and entrepreneurship mind were statistically significant. In conclusion, this study investigated the structural relationship between the awareness of the 4th industrial revolution and entrepreneurship in college students majoring in beauty, with the goal of providing basic data for entrepreneurship education.