• Advances in concrete construction
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• v.13 no.5
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• pp.385-394
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• 2022

Recently, an increasing number of cutting-edged studies have shown that designing a smart active control for real-time implementation requires piles of hard-work criteria in the design process, including performance controllers to reduce the tracking errors and tolerance to external interference and measure system disturbed perturbations. This article proposes an effective artificial-intelligence method using these rigorous criteria, which can be translated into general control plants for the management of civil engineering installations. To facilitate the calculation, an efficient solution process based on linear matrix (LMI) inequality has been introduced to verify the relevance of the proposed method, and extensive simulators have been carried out for the numerical constructive model in the seismic stimulation of the active rigidity. Additionally, a fuzzy model of the neural network based system (NN) is developed using an interconnected method for LDI (linear differential) representation determined for arbitrary dynamics. This expression is constructed with a nonlinear sector which converts the nonlinear model into a multiple linear deformation of the linear model and a new state sufficient to guarantee the asymptomatic stability of the Lyapunov function of the linear matrix inequality. In the control design, we incorporated H Infinity optimized development algorithm and performance analysis stability. Finally, there is a numerical practical example with simulations to show the results. The implication results in the RMS response with as well as without tuned mass damper (TMD) of the benchmark building under the external excitation, the El-Centro Earthquake, in which it also showed the simulation using evolved bat algorithmic LMI fuzzy controllers in term of RMS in acceleration and displacement of the building.

• International Journal of Computer Science & Network Security
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• v.21 no.12spc
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• pp.703-711
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• 2021

The article is devoted to studying the development of scientific and methodological work and its impact on the quality of students' vocational training in higher pedagogical education institutions by applying information technology. The article aim is to development of the organizational methodological support and pedagogical diagnostics of the effectiveness of the project «Modelling scientific and methodological work in a higher education pedagogical institution by applying information technology » realization in the framework of increasing the level of scientific and methodological work in a higher education pedagogical institution as a factor contributing to enhancing the quality of pedagogical education. The research program of the project activity envisages stating and substantiating the problem of scientific and methodological work by applying information technology in the framework of increasing the level and quality of educational activities in a higher pedagogical education institution through the implementation of the project approach, developing a model for the system of organizational and methodological support of the project implementation as well as monitoring the process and evaluating the results of the project implementation in terms of developing teachers' scientific, methodological, information competency and enhancing students' progress in studying. The set of criteria were developed to evaluate the level of formation of scientific and methodological competency as a result of implementing the project for the development of scientific and methodological work. The scientific and methodological work by applying information technology in the academy was carried out in accordance with the following principles: systematic character, consistent diagnostics, practical focus, scientific organizational and methodological support.

• Journal of the Korea Society of Computer and Information
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• v.27 no.2
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• pp.81-89
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• 2022

This study aims to analyze the images of Instagram posts and to draw implcations regarding the exhibition of . This study collects and crawl 24,295 images from Instagram posts as a dataset. We use the Google Cloud Vision API for labeling the images and a total of 212,567 clusters of labels are finally classified into 9 categories using Word2Vec. The categories of museum spaces, photo zone, architecture category are dominant along with people category. In conclusion, visitors curate their experiences and memories of physical places and spaces while they are experiencing with the exhibition. This result reproves the results of previous studies which emphasize a sense of social presence and place making. The convergent approach of art management and art technology used in this study help museum professionals have an insight on big data based visitor research on a practical level.

• Journal of KIBIM
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• v.12 no.4
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• pp.61-69
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• 2022

Earthmoving operations account for approximately 25% of construction cost, generally executed prior to the construction of buildings and structures with heavy equipment. For the successful completion of earthwork projects, it is crucial to constantly monitor earthwork equipment (e.g., trucks), estimate productivity, and optimize the construction process and equipment on a construction site. Traditional methods however require time-consuming and painstaking tasks for the manual observations of the ongoing field operations. This study proposed the use of a GPS sensor embedded in a smartphone for the tracking and visualization of equipment locations, which are in turn used for the estimation and simulation of cycle times and production rates of ongoing earthwork. This approach is implemented into a digital platform enabling real-time data collection and simulation, particularly in a 2D (e.g., maps) or 3D (e.g., point clouds) virtual environment where the spatial and temporal flows of trucks are visualized. In the case study, the digital platform is applied for an earthmoving operation at the site development work of commercial factories. The results demonstrate that the production rates of various equipment usage scenarios (e.g., the different numbers of trucks) can be estimated through simulation, and then, the optimal number of tucks for the equipment fleet can be determined, thus supporting the practical potential of real-time sensing and simulation for onsite equipment management.

• Journal of Industrial Convergence
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• v.20 no.10
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• pp.113-120
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• 2022

The study aims to explain the effect of bicultural acceptance on depression of multicultural adolescents and to analyze the mediating effect of social withdrawal between two variables. To accomplish the purpose, 1,158 subjects were selected from the 8th(2018) data of the Multicultural Adolescents Panel Study(MAPS), and the data collected were analyzed by using Process Macro Model and Bootstrapping analysis. The major findings are as follows. First, positive bicultural acceptance attitude of multicultural adolescents was shown to decrease their social withdrawal and depression. Second, social withdrawal of multicultural adolescents affected increase of their depression. Third, the effect of bicultural acceptance on depression of multicultural adolescents was partly mediated by their social withdrawal. Based on the above findings, practical alternatives and programs to reduce depression and social withdrawal of multicultural adolescents were suggested.

• Journal of Digital Convergence
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• v.20 no.2
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• pp.63-75
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• 2022

In this study, the smart docent interface provided at 25 exhibition halls at domestic and foreign were compared and analyzed based on affordance. Heuristic evaluation techniques were adopted, centered on a small number of experienced people, and six research participants were selected based on Jacob Nielsen's guidelines that five to eight people per set of research can achieve sufficient results. As a result of comparative analysis of affordance, smart docent used in the Oriental showed a higher average value than smart docent used in the Western, but a lower value for sensory affordance alone. In addition, the categories were subdivided to derive the affordance values for each country, and a singularity was found that the sensory affordance of smart docents used in the United States represents the highest value compared to other countries. In conclusion, this study was able to compare the four affordances of smart docents used in domestic and foreign exhibition halls while presenting directions for future behavioral improvement, which could provide practical implication for smart docent interface design and exhibition hall service strategies.

• Journal of Industrial Convergence
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• v.19 no.6
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• pp.59-66
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• 2021

Globally, the prolonged pandemic of COVID-19 (COVID-19) has had a great impact on all industries. In particular, in the field of education, online classes (non-face-to-face) had some negative perceptions of online classes, such as lack of preparation for learning and student dissatisfaction with the class. According to the current situation survey in 2020, non-face-to-face classes accounted for about 56% of the class, and streaming real-time classes and video content-based classes accounted for most of the class. This study empirically analyzes the problems to be solved by online classes through the 2020-2021 survey (software application practical class university students), and explains the detailed program and development plan (implementation result). This study intends to contribute to the development of online learning development of each educational institution after the end of the corona crisis.

• Journal of Korea Entertainment Industry Association
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• v.14 no.7
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• pp.43-54
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• 2020

Negotiation has been an important topic of M&A within entertainment industry. This research is aimed to investigate the process of M&A and related negotiation theories review and to analyze the Nexon sales failure case. M&A is a significant strategic decision-making made to ensure the sustainable competitiveness of Nexon. Nexon is generally more competitive action in negotiation context than rival game corporations. As a result, the negotiation about M&A is not completely succeeded. Nexon need to overcome the distributive strategy based on high anchoring (sales price). Also, Nexon need to be aware that negotiators who focus on the BATNA are more effective in claiming resources. Netmarble have low status and so is expected to be poor negotiation result. Because Nexon is perceived to be of higher status than Netmarble in an M&A process, Nexon is given the power to propose agreements. The practical and academic lessons of the present study are discussed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3544-3564
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• 2022

With the development of the NB-IoT (Narrow band Internet of Things) and smart cities, coupled with the emergence of smart smoke sensors, new requirements and issues have been introduced to study on the deployment of sensors in large spaces. Previous research mainly focuses on the optimization of wireless sensors in some monitoring environments, including three-dimensional terrain or underwater space. There are relatively few studies on the optimization deployment problem of smart smoke sensors, and leaving large spaces with obstacles such as libraries out of consideration. This paper mainly studies the deployment issue of smart smoke sensors in large spaces by considering the fire probability of fire areas and the obstacles in a monitoring area. To cope with the problems of coverage blind areas and coverage redundancy when sensors are deployed randomly in large spaces, we proposed an optimized deployment strategy of smart smoke sensors based on the PSO (Particle Swarm Optimization) algorithm. The deployment problem is transformed into a multi-objective optimization problem with many constraints of fire probability and barriers, while minimizing the deployment cost and maximizing the coverage accuracy. In this regard, we describe the structure model in large space and a coverage model firstly, then a mathematical model containing two objective functions is established. Finally, a deployment strategy based on PSO algorithm is designed, and the performance of the deployment strategy is verified by a number of simulation experiments. The obtained experimental and numerical results demonstrates that our proposed strategy can obtain better performance than uniform deployment strategies in terms of all the objectives concerned, further demonstrates the effectiveness of our strategy. Additionally, the strategy we proposed also provides theoretical guidance and a practical basis for fire emergency management and other departments to better deploy smart smoke sensors in a large space.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.891-897
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• 2022

In big data analysis, raw text data mostly exists in various unstructured data forms, so it becomes a structured data form that can be analyzed only after undergoing heuristic pre-processing and computer post-processing cleansing. Therefore, in this study, unnecessary elements are purified through pre-processing of the collected raw data in order to apply the wordcloud of R program, which is one of the text data analysis techniques, and stopwords are removed in the post-processing process. Then, a case study of wordcloud analysis was conducted, which calculates the frequency of occurrence of words and expresses words with high frequency as key issues. In this study, to improve the problems of the "nested stopword source code" method, which is the existing stopword processing method, using the word cloud technique of R, we propose the use of "general stopword corpus" and "user-defined stopword corpus" and conduct case analysis. The advantages and disadvantages of the proposed "unstructured data cleansing process model" are comparatively verified and presented, and the practical application of word cloud visualization analysis using the "proposed external corpus cleansing technique" is presented.