• The Journal of the Korea Contents Association
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• v.16 no.5
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• pp.306-317
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• 2016

Both the formal type of architecture and free-form architecture have basic factors and methods for basic expression. Because the use of digital design tools for creation of free-form design mostly depends on the character and ability of designer, this study aims to propose establishment of free-form design creation method as a prototype, including the method to create free-form design, through setting up rules that can be used in common. This study is carried out on the basis of the application of digital design tools used for creation of conceptual free-form styles at the phase of conceptualization and development, which is different from the general theory of free-from design. The free-from style in the modern architecture has begun with the changes in digital design tools and design concepts. In the case study based on the free-form designs in precedent studies, the morphological characteristics have been analyzed and interpreted by using the language of digital design tools, so that this study will suggest the techniques to realize the free-form style on the basis of geometric transformation by using the digital design tools, as well.

• Journal of Educational Research in Mathematics
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• v.19 no.4
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• pp.531-543
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• 2009

This study identified what cognitive attributes are required of eighth graders to solve geometrical problems such as 'Recall,' 'Analyze,' 'Justify,' 'Synthesize/Integrate,' and 'Solve Non-routine Problems' by using the cognitive diagnostic theory. The five attributes are proved as the skills for solving the geometric problems. Many students have not fully mastered the attributes of 'Justify' and 'Synthesize/Integrate'. There was high correlation between these attributes. 'Analyze' best predicted the changes in the geometric achievement. And while students with high levels of geometrical achievement have mastered all the five attributes, those in the mid- and low-level range of performance have mastered fewer attributes.

• Korean Journal of Construction Engineering and Management
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• v.17 no.5
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• pp.89-96
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• 2016

Most data generated in construction projects is unstructured text data. Unstructured data analysis is very needed in order for effective analysis on large amounts of text-based documents, such as contracts, specifications, and RFI. This study analysed previously performed project's bid related documents (bidder inquiry) in overseas construction projects; as a results of the analysis frequent words in documents, association rules among the words, and various document topics were derived. This study suggests effective text analysis approach for massive documents with short time using text mining technique, and this approach is expected to extend the unstructured text data analysis in construction industry.

• Journal of the Korea Institute of Building Construction
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• v.16 no.6
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• pp.579-585
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• 2016

3D laser scanning can be used for scanning the freeform surface and building a model from which the measurements could be taken, in order to solve the difficulty with getting access to the exact freeform shape and position data of the complex building envelope. The shape making process using 3D scanning is as follows: point cloud, mesh surface segmentation, NURBS(Non-Uniform Rational B-spline) surface generation, and parametric solid model generation. In this research, we review previous studies, reverse engineering notion, importance of reverse engineering usage for freeform envelope, and previous cases in order to identify the detail reverse engineering process for prefabrication and construction of freeform panels using 3D laser scanning technology. Therefore, the purpose of this research is to present a basic information which should be considered during design and construction phase and improve quality and constructibility of freeform building by analyzing the reverse engineering process and case study for prefabrication and construction of freeform panels using 3D laser scanning. The research results will enable 3D shape engineering and design parameterization using reverse engineering to be used in various construction projects.

• Water for future
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• v.56 no.8
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• pp.31-36
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• 2023

• Journal of the Korea Convergence Society
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• v.12 no.7
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• pp.45-51
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• 2021

In accordance with the rapid non-face-to-face environment and mobile first strategy, the explosive increase and creation of many structured/unstructured data every year demands new decision making and services using big data in all fields. However, there have been few reference cases of using the Hadoop Ecosystem, which uses the rapidly increasing big data every year to collect and load big data into a standard platform that can be applied in a practical environment, and then store and process well-established big data in a relational database. Therefore, in this study, after collecting unstructured data searched by keywords from social network services based on Hadoop 2.0 through three virtual machine servers in the Spring Framework environment, the collected unstructured data is loaded into Hadoop Distributed File System and HBase based on the loaded unstructured data, it was designed and implemented to store standardized big data in a relational database using a morpheme analyzer. In the future, research on clustering and classification and analysis using machine learning using Hive or Mahout for deep data analysis should be continued.

• The Journal of Bigdata
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• v.6 no.2
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• pp.169-179
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• 2021

Consumers' food consumption behavior is likely to be affected not only by structured data such as consumer panel data but also by unstructured data such as mass media and social media. In this study, a deep learning-based consumption prediction model is generated and verified for the fusion data set linking structured data and unstructured data related to food consumption. The results of the study showed that model accuracy was improved when combining structured data and unstructured data. In addition, unstructured data were found to improve model predictability. As a result of using the SHAP technique to identify the importance of variables, it was found that variables related to blog and video data were on the top list and had a positive correlation with the amount of paprika purchased. In addition, according to the experimental results, it was confirmed that the machine learning model showed higher accuracy than the deep learning model and could be an efficient alternative to the existing time series analysis modeling.

• Nuclear industry
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• v.36 no.1
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• pp.53-62
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• 2016

• Journal of the Korea Institute of Building Construction
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• v.23 no.3
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• pp.251-260
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• 2023

The construction of free-form structures with intricate curved exteriors necessitates the use of bespoke molds. To fulfill this requirement, a blend of Phase Change Material(PCM) and Ultra-High Performance Concrete(UHPC) is utilized. PCM endows the solution with recyclability, while UHPC facilitates the effortless execution of curvature in the mold fabrication process. However, it's worth mentioning that the melting point of PCM hovers around 58-64℃, and the heat emanating from UHPC's hydration process can potentially jeopardize the integrity of the PCM mold. Hence, experimental validation of the mold shape is a prerequisite. In the conducted experiment, UHPC was poured into two distinct mold types: one that incorporated a 3mm silicone sheet mounted on the fabricated PCM mold(Panel A), and the other devoid of the silicone sheet(Panel B). The experimental outcomes revealed that Panel A possessed a thickness of 3.793mm, while Panel B exhibited a thickness of 5.72mm. This suggests that the mold lacking the silicone sheet(Panel B) was more susceptible to the thermal effects of hydration. These investigations furnish invaluable fundamental data for the manufacturing of ultra-high strength irregular panels and PCM molds. They contribute substantially to the enrichment of comprehension and application of these materials within the realm of construction.

• The Korean Journal of Applied Statistics
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• v.31 no.5
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• pp.655-665
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• 2018

Social network services (SNS) have become the most common tool for the communication of public and private opinions as well as public issues; consequently, one may form or drive public opinions to advocate by spreading positive content using SNS. Controversy for survey data based opinion poll accuracy continues in relation to response rate or sampling methodology. This study suggests complementary measures that additionally consider the sentiment analysis results of unstructured data on a social network by data crawling and sentiment dictionary adjustment process. The suggested method shows the improvement of prediction accuracy by decreasing error rates.