• Journal of Korean Society of Forest Science
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• v.106 no.3
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• pp.340-352
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• 2017

In This study, we examined the gap between supply and demand of forest policy by year through big data analysis for macroscopic evaluation of the 5th Basic Forest Plan. We collected unstructured data based on keywords related to the projects mentioned in the news, SNS and so on in the relevant year for the policy demand side; and based on the documents published by the Korea Forest Service for the policy supply side. based on the collected data, we specified the network structure through the social network analysis technique, and identified the gap between supply and demand of the Korea Forest Service's policies by comparing the network of the demand side and that of the supply side. The results of big data analysis indicated that the network of the supply side is less radial than that of the demand side, implying that various keywords other than forest could considerably influence on the network. Also we compared the trends of supply and demand for 33 keywords related to 27 major projects. The results showed that 7 keywords shows increasing demand but decreasing supply: sustainable, forest management, forest biota, forest protection, forest disease and pest, urban forest, and North Korea. Since the supply-demand gap is confirmed for the 7 keywords, it is necessary to strengthen the forest policy regarding the 7 keywords in the 6th Basic Plan.

• Journal of the Korean Society of Safety
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• v.32 no.3
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• pp.151-159
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• 2017

This study deals with characteristics and risk of a PM based on user survey result, road driving test and data analysis of PM accident. Text mining method is applied to extract PM accident data from Big Data, which are claim data of private insurance company. Road driving test and survey on safety, convenience, noise, overtake ability, steering ability, and climbing ability of PM are performed to evaluate user's safety and convenience considering domestic road condition. As the result of claim data analysis, annual average increase rate of PM accident is 47.4% and average compensation of personal mobility is higher than that of bicycle by maximum 1.5 times. 79.8% of PM accident is self-caused accident due to unskilled driving and age-specific diagnosis rate of driver over 60 is higher than that of under 60. Diagnosis rate of over 60 at lower limb, foot, rib and spine is especially higher than that of under 60. As the result of road driving test and user survey, satisfaction level on safety and convenience of PM is evaluated as close to that of bicycle and satisfaction level of PM is increased after boarding. Overtake ability, steering ability, and climbing ability of PM are evaluated as same or better than that of bicycle but warning equipment to pedestrian or bike such as horn is required because noise level of PM during driving is too low. Finally, user survey result shows that bicycle road is suitable for PM and safety standard, advance-education and insurance are required for PM. It is suggested that drivers' license for PM can be replaced by advance-education. Results of this study can be used to prepare safety measures and legal basis for PM operation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.6
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• pp.581-590
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• 2017

This study analyzes the effect of floating population, locational characteristics and spatial autocorrelation on foodservice sales using big data provided by the Seoul Institute. Although big data provided by public sector is growing recently, research difficulties are occurred due to the difference of aggregation units of data. In this study, the aggregation unit of a dependent variable, sales of foodservice is SKT unit but those of independent variables are various, which are provided as the aggregation unit of Korea National Statistical Office, administration dong unit and point. To overcome this problem, we convert all data to the SKT aggregation unit. The spatial error model, SEM is used for analysing spatial autocorrelation. Floating population, the number of nearby workers, and the area of aggregation unit effect positively on foodservice sales. In addition, the sales of Jung-gu, Yeongdeungpo-gu and Songpa-gu are less than that of Gangnam-gu. This study provides implications for further study by showing the usefulness and limitations of converting aggregation units of heterogeneous spatial data.

• Design Convergence Study
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• v.15 no.5
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• pp.55-70
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• 2016

Multi shopping malls provide us new life-style nowadays with the term, malling. Multi shopping malls are consisted of selling space, entertainment space and convenience space so that arrangement and circulation planning of each facilities have large influence to users. Based on this influences, this study aims to provide basic data for multi shopping malls' circulation planning. Therefore, this study selected 6 multi shopping malls in Seoul and conducted survey that satisfaction of circulation planning of multi shopping malls. For user satisfaction investigation, we studied concept of multi shopping mall following Korean building act and selected composition and characteristics of circulation. Also, we classified the malls to size and circulation shapes for comparison of the satisfaction results. Classified types are high-rise and low-rise and they are separated to small size and big size. In addition, classified circulation shapes are categorized to net type, loop type, cyclical loop type and multi type by forms of central space and main stream of the malls.

• Korean Journal of Agricultural Science
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• v.46 no.2
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• pp.381-393
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• 2019

A smart farm is a system that combines information and communication technology (ICT), internet of things (IoT), and agricultural technology that enable a farm to operate with minimal labor and to automatically control of a greenhouse environment. Machine learning based on recently data-driven techniques has emerged with big data technologies and high-performance computing to create opportunities to quantify data intensive processes in agricultural operational environments. This paper presents research on the application of machine learning technology to diagnose the growth status of crops and predicting the harvest time of strawberries in a greenhouse according to image processing techniques. To classify the growth stages of the strawberries, we used object inference and detection with machine learning model based on deep learning neural networks and TensorFlow. The classification accuracy was compared based on the training data volume and training epoch. As a result, it was able to classify with an accuracy of over 90% with 200 training images and 8,000 training steps. The detection and classification of the strawberry maturities could be identified with an accuracy of over 90% at the mature and over mature stages of the strawberries. Concurrently, the experimental results are promising, and they show that this approach can be applied to develop a machine learning model for predicting the strawberry harvesting time and can be used to provide key decision support information to both farmers and policy makers about optimal harvest times and harvest planning.

• Advances in nano research
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• v.16 no.3
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• pp.231-249
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• 2024

When the amplitude of the vibrations is equivalent to that clearance, the vibrations for small amplitudes will really be significantly nonlinear. Nonlinearities will not be significant for amplitudes that are rather modest. Finally, nonlinearities will become crucial once again for big amplitudes. Therefore, the concrete panel system may experience a big amplitude in this work as a result of the high temperature. Based on the 3D modeling of the shell theory, the current work shows the influences of the von Kármán strain-displacement kinematic nonlinearity on the constitutive laws of the structure. The system's governing Equations in the nonlinear form are solved using Kronecker and Hadamard products, the discretization of Equations on the space domain, and Duffing-type Equations. Thermo-elasticity Equations. are used to represent the system's temperature. The harmonic solution technique for the displacement domain and the multiple-scale approach for the time domain are both covered in the section on solution procedures for solving nonlinear Equations. An effective data-driven solution is often utilized to predict how different systems would behave. The number of hidden layers and the learning rate are two hyperparameters for the network that are often chosen manually when required. Additionally, the data-driven method is offered for addressing the nonlinear vibration issue in order to reduce the computing cost of the current study. The conclusions of the present study may be validated by contrasting them with those of data-driven solutions and other published articles. The findings show that certain physical and geometrical characteristics have a significant effect on the existing concrete panel structure's susceptibility to temperature change and GPL weight fraction. For building construction industries, several useful recommendations for improving the thermo-mechanics' behavior of structural concrete panels are presented.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2003.05a
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• pp.29-35
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• 2003

Recently, WRMSD(Work-Related Musculoskeletal Disorders) related to simple and repetitious works has been become big issue and has been studying actively by many korean researchers. However, it is that the researches has been depended on foreign ones because the basic data in each field is short in Korea. In this study, we tried to search the actual conditions and factors on WRMSD of pressing workers. In addition, we tried to search the actual conditions and factors on WRMSD of pressing workers. In addition we examined how the contents of works and postures of workers affected at the disease. Accordingly, these research data will be used for planning the preventive program on WRMSD effectively and implement its program.

• Proceedings of the Korea Concrete Institute Conference
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• 1990.10a
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• pp.157-162
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• 1990

Recently, the multistory building construction of reinforced concrete has increased year by year, trended to be high rise in the view of effective land use planning, costing down of building construction and residential conditions. For this urgent need in construction industry, research and development of workability and engineering properties of high strength concrete has been closed up as one of the big world wide problems to be solved reasonably. It is aim of this study to provide the fundamental data the workability and engineering properties of steel-fiber reinforced high strength concrete containing silica-fume and fly-ash comparing with plain concrete for the practical use and research data accumulation in the side of development of new material in the building construction.

• Journal of the Korea Safety Management & Science
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• v.5 no.4
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• pp.75-85
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• 2003

Recently, WRMSD(Work-Related Musculoskeletal Disorders) that can be frequently found among simple and repetitious works has been a big occupational safety issue, and has begun to being studied actively by many Korean researchers. However, those researches have been largely relied on foreign ones, due to the lack of basic data in Korea. In this study, we have tried to search the actual conditions and factors on WRMSD of press workers in a local company. In addition, we examined how the contents of works and postures of the workers affect the disease. It is expected that the data collected in this study will be able to used for planning the preventive measures on WRMSD effectively and for implementing its corresponding programs.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.222-229
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• 2022

Through this technology development, companies that operate online shopping malls and prospective startups will support education, consulting and expert group matching so that they can solve various issues that may arise in the course of the entire business life cycle, from startups to closures. It is expected that differentiated consulting programs will be designed for companies that currently operate shopping malls and start ups, and customized consulting programs will be provided to improve the effectiveness of consulting while improving customer satisfaction. It is planning to develop a "successful start-up and operation helper" that helps successful start-ups. It is a system that primarily diagnoses problems of prospective entrepreneurs and operators through an automation system at the start-up and operation stage, and professional consultants participate to derive and solve problems, and takes care of all stages of shopping mall birth and growth. In this paper Metaverse based shopping mall Creation is also discussed. Through Big Data creation these accumulated data, we intend to help operators start and operate shopping malls through accurate information by managing all knowledge of shopping malls as a system in the long run.