• Journal of the Korean Society of Systems Engineering
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• v.18 no.1
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• pp.66-83
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• 2022

Artificial Intelligence (AI) is to assumed to be one of next generation technology which determine technological competitiveness and strategic advantage of a certain country. By using the patent data, this study aims to have a comparative analysis of the technological competitiveness of evolving artificial intelligence at different stages of development among the five largest intellectual property offices in the world (IP5). For the analysis data, all AI technology patent data from 1956 to 2019 were utilized according to the classification system presented in the "WIPO 2019 Technology Trend: Artificial Intelligence" report published by the World Intellectual Property Organization (WIPO) in 2019. The results shows that China has already surpassed the United States in terms of the number of patent applications in the field of artificial intelligence technology. However, in the domains of the United States, Europe, Japan, and Korea, the technology competitiveness of the United States is far ahead of China. Interestingly, the rate of increase of Korea's technology competitiveness is also very fast, and it has been shown that the technology strength is ahead of China in non-Chinese domains. The significance of this study can be found in the fact that the temporal and spatial change process of technological competitiveness of significant countries in the field of artificial intelligence technology artificial intelligence was viewed as a macro-framework using the technology index (TS) the differences were compared.

• Human Ecology Research
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• v.61 no.3
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• pp.401-414
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• 2023

This study examined the sequential mediation effects of academic achievement attribution and career decision-making self-efficacy on the effect of paternal and maternal helicopter parenting on high-school students' career preparation behavior. A total of 285 (119 male and 166 female) Korean high-school students in the second grade participated in the study. Research variables were measured using the Career Preparation Behavior Scale (Kim, 1997), Helicopter Parenting Scale (LeMoyne & Buchanan, 2011), Attribution Questionnaire (Weiner, 1979), and Career Decision-Making Self-Efficacy Scale-Short Form (Betz et al., 1996). To examine the sequential mediating effect, data analysis was performed using SPSS 29.0 and PROCESS MACRO (v4.2) Model 6. The results revealed no correlations between helicopter parenting and academic failure attribution. However, higher paternal and maternal helicopter parenting were found to indirectly reduce high-school students' career preparation behavior through lower internal academic success attribution (effort and ability) and higher external academic success attribution (task difficulty and luck), which reduced career decision-making self-efficacy. These findings can be employed to develop more effective intervention programs comprising career guidance for adolescents, which emphasizes the negative effect of helicopter parenting. This study expands the research field, as previous findings on helicopter parenting mostly focus on college students.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.5
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• pp.257-270
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• 2009

In the ways of coping with the rapidly changing environment, the information technology is recognized a critical factor in order to rethink the effectiveness of business management, and enterprise resource planning(ERP) system has emerged as an essential method for strengthening the competitiveness on the strategic level. This empirical study has revealed the following. First, well-organized system management and the strong will and leadership of top management have significantly positive influence on the reduction of cost and time. Second, system management, users' participation, and the strong will and leadership of top management have significantly positive influence on the improvement of management and informational environment. It also proposes the guidelines of how to establish an ERP system successfully in the public enterprises.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.17-25
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• 2023

The alarming global prevalence of Type 2 Diabetes Mellitus (T2DM) has catalyzed an urgent need for robust, early diagnostic methodologies. This study unveils a pioneering approach to predicting T2DM, employing the Extreme Gradient Boosting (XGBoost) algorithm, renowned for its predictive accuracy and computational efficiency. The investigation harnesses a meticulously curated dataset of 4303 samples, extracted from a comprehensive Chinese research study, scrupulously aligned with the World Health Organization's indicators and standards. The dataset encapsulates a multifaceted spectrum of clinical, demographic, and lifestyle attributes. Through an intricate process of hyperparameter optimization, the XGBoost model exhibited an unparalleled best score, elucidating a distinctive combination of parameters such as a learning rate of 0.1, max depth of 3, 150 estimators, and specific colsample strategies. The model's validation accuracy of 0.957, coupled with a sensitivity of 0.9898 and specificity of 0.8897, underlines its robustness in classifying T2DM. A detailed analysis of the confusion matrix further substantiated the model's diagnostic prowess, with an F1-score of 0.9308, illustrating its balanced performance in true positive and negative classifications. The precision and recall metrics provided nuanced insights into the model's ability to minimize false predictions, thereby enhancing its clinical applicability. The research findings not only underline the remarkable efficacy of XGBoost in T2DM prediction but also contribute to the burgeoning field of machine learning applications in personalized healthcare. By elucidating a novel paradigm that accentuates the synergistic integration of multifaceted clinical parameters, this study fosters a promising avenue for precise early detection, risk stratification, and patient-centric intervention in diabetes care. The research serves as a beacon, inspiring further exploration and innovation in leveraging advanced analytical techniques for transformative impacts on predictive diagnostics and chronic disease management.

• Geomechanics and Engineering
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• v.34 no.6
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• pp.697-726
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• 2023

Brittleness as an important property of rock plays a crucial role both in the failure process of intact rock and rock mass response to excavation in engineering geological and geotechnical projects. Generally, rock brittleness indices are calculated from the mechanical properties of rocks such as uniaxial compressive strength, tensile strength and modulus of elasticity. These properties are generally determined from complicated, expensive and time-consuming tests in laboratory. For this reason, in the present research, an attempt has been made to predict the rock brittleness indices from simple, inexpensive, and quick laboratory test results namely dry unit weight, porosity, slake-durability index, P-wave velocity, Schmidt rebound hardness, and point load strength index using multiple linear regression, exponential regression, support vector machine (SVM) with various kernels, generating fuzzy inference system, and regression tree ensemble (RTE) with boosting framework. So, this could be considered as an innovation for the present research. For this purpose, the number of 39 rock samples including five igneous, twenty-six sedimentary, and eight metamorphic were collected from different regions of Iran. Mineralogical, physical and mechanical properties as well as five well known rock brittleness indices (i.e., B₁, B₂, B₃, B₄, and B₅) were measured for the selected rock samples before application of the above-mentioned machine learning techniques. The performance of the developed models was evaluated based on several statistical metrics such as mean square error, relative absolute error, root relative absolute error, determination coefficients, variance account for, mean absolute percentage error and standard deviation of the error. The comparison of the obtained results revealed that among the studied methods, SVM is the most suitable one for predicting B₁, B₂ and B₅, while RTE predicts B₃ and B₄ better than other methods.

• 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.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.353-360
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• 2022

Due to the dense and complicated working environment, the construction industry is susceptible to many accidents. Worker's fall is a severe problem at the construction site, including falling into holes or openings because of the inadequate coverings as per the safety rules. During the construction or demolition of a building, openings and holes are formed in the floors and roofs. Many workers neglect to cover openings for ease of work while being aware of the risks of holes, openings, and gaps at heights. However, there are safety rules for worker safety; the holes and openings must be covered to prevent falls. The safety inspector typically examines it by visiting the construction site, which is time-consuming and requires safety manager efforts. Therefore, this study presented a worker-driven approach (the worker is involved in the reporting process) to facilitate safety managers by developing integrated computer vision and inertia sensors-based mobile applications to identify openings. The TensorFlow framework is used to design Convolutional Neural Network (CNN); the designed CNN is trained on a custom dataset for binary class openings and covered and deployed on an android smartphone. When an application captures an image, the device also extracts the accelerometer values to determine the inclination in parallel with the classification task of the device to predict the final output as floor (openings/ covered), wall (openings/covered), and roof (openings / covered). The proposed worker-driven approach will be extended with other case scenarios at the construction site.

• Journal of the Economic Geographical Society of Korea
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• v.25 no.4
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• pp.547-567
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• 2022

In this study, I focus on makerspaces, which have rapidly spread since the late 2000s in the world's major cities. Makerspaces, born amid great social change, reflect the core characteristics of industrial space. I analyze the makerspace based on the theoretical perspectives of urbanism in the macroscopic aspect and placeness in the microscopic aspect. The urbanism of makerspaces is manifested through entry into the inner cities and their connections with urban capabilities. This means that convergence with innovation factors is becoming more important than optimization of factor costs and agglomeration economies in the locational determinants of industrial space. The placeness of makerspaces is being re-formed through an emphasis on taste, the expansion of autonomy, and the strengthening of connections. This reveals how the value creation process within the industrial space is changing, from forming-placelessness through standardization, uniformity, and compartmentalization to forming-placeness through restoration of individual humanity and interaction. The results of the urbanism and placenesss analysis carry implications for the present moment, when it is necessary to diversify the spatial planning of industrial spaces.

• International Journal of Advanced Culture Technology
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• v.11 no.1
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• pp.212-220
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• 2023

The meticulous figure painting is one of the wonders of traditional Chinese painting and has blossomed in art history with its unique and interesting style. The period from the Warring States period to the Song and Yuan dynasties was a glorious period in its history, after which it tended to decline due to changes in painting materials and many socio-historical reasons. The extensive cultural exchanges in the world today, the penetration of Western values and the expansion of information technology have brought a huge impact on Chinese meticulous figure painting, which has developed an active way of thinking and expression after absorbing certain elements of Western culture and thought on the basis of inherited tradition. Contemporary Realistic Figure painters continue to explore new developments in meticulous figure painting in the contemporary context, and give contemporary meticulous figure painting a new cultural and ideological connotation, forming a new look that meets the requirements of the times, with richer and more lively content, subject matter and formal language. Traditional meticulous figure painting is characterised by a highly refined use of line and coloring composition. Contemporary meticulous figure painting focuses on the use of purely formal language and the expression of the personality of the creative subject, with a new outlook on the world of painting. In the contemporary multicultural context, new formal language and methods of expression are constantly being explored to create a new look. In the process of development, contemporary meticulous figure painting has merged the best qualities of traditional and contemporary culture, making it an art with a subtle language, rich in meaning and with the charm of the times and oriental characteristics. The author in the form of contemporary fine brushwork figure painting language as the research object, explore new form of fine brushwork figure painting, and in the contemporary society and multicultural context factors. Innovation, enrich and develop new forms of art language of contemporary social form and aesthetic temperament and interest.

• Korean Journal of Construction Engineering and Management
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• v.24 no.3
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• pp.3-11
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• 2023

This research examines the need for a quantitative and objective method of calculating baseline productivity in the construction industry, which is known for its high volatility in performance and productivity. The existing literature's baseline productivity calculation methods rely heavily on subjective criteria, limiting their effectiveness. Additionally, data collection methods such as the "Five-minute Rating" are costly and time-consuming, making it challenging to collect detailed data at construction sites. To address these issues, this study proposes an objective baseline calculation method using unimpacted productivity BP, a work check sheet to systematically record detailed data, and a data collection and utilization process that minimizes cost and time requirements. This paper also suggests using unimpacted productivity BP and comparative analysis to address the objectivity and reliability issues of existing baseline productivity calculation methods.