• Journal of the Korea institute for structural maintenance and inspection
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• v.20 no.1
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• pp.104-111
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• 2016

The steel frame modular housing of which the research and development has been actively carried out recently cannot be constructed through monolithic placement like the reinforced concrete deck of general structure due to the characteristics of construction method of production in the factory and assembly on the site. And floor vertical vibration and deflection caused by inhabitants' activities may become an important issue in the aspect of usability evaluation due to a decrease in the section size of member, a decrease in weight, and so on. Therefore, this study evaluated the vibration performance of deck by using formula of AISC Design Guide 11(hereinafter AISC formula) which was practically used in general for modules where a stud was and wasn't installed at the center of beam in the longitudinal direction in the modular housing to be studied, and examined the applicability of AISC formula through comparison with the results of analysis using a general-purpose analysis program. On the basis of this, a structural cause for an error to occur between analysis result and AISC formula in the deck of module in which a stud was installed was analysed, and measures for considering this were suggested. Besides, an analysis model with the variables of measures for improving the floor vibration performance of modular housing to be studied was established. And measures having excellent vibration performance and economic feasibility were suggested through vibration response analysis and economic evaluation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.212-215
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• 2022

In the era of so-called digital transformation today, the need for the construction and utilization of big data in various fields has increased. Today, a lot of data is produced and stored in a digital device and media-friendly manner, but the production and storage of data for a long time in the past has been dominated by print books. Therefore, the need for Optical Character Recognition (OCR) technology to utilize the vast amount of print books accumulated for a long time as big data was also required in line with the need for big data. In this study, a system for digitizing the structure and content of a document object inside a scanned book image is proposed. The proposal system largely consists of the following three steps. 1) Recognition of area information by document objects (table, equation, picture, text body) in scanned book image. 2) OCR processing for each area of the text body-table-formula module according to recognized document object areas. 3) The processed document informations gather up and returned to the JSON format. The model proposed in this study uses an open-source project that additional learning and improvement. Intelligent OCR proposed as a system in this study showed commercial OCR software-level performance in processing four types of document objects(table, equation, image, text body).