• Journal of KIBIM
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• v.13 no.4
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• pp.96-105
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• 2023

This study focuses on developing a building object recognition technology for efficient use in the remodeling of buildings constructed without drawings. In the era of the 4th industrial revolution, smart technologies are being developed. This research contributes to the architectural field by introducing a deep learning-based method for automatic object classification and recognition, utilizing point cloud data. We use a TD3D network with voxels, optimizing its performance through adjustments in voxel size and number of blocks. This technology enables the classification of building objects such as walls, floors, and roofs from 3D scanning data, labeling them in polygonal forms to minimize boundary ambiguities. However, challenges in object boundary classifications were observed. The model facilitates the automatic classification of non-building objects, thereby reducing manual effort in data matching processes. It also distinguishes between elements to be demolished or retained during remodeling. The study minimized data set loss space by labeling using the extremities of the x, y, and z coordinates. The research aims to enhance the efficiency of building object classification and improve the quality of architectural plans by reducing manpower and time during remodeling. The study aligns with its goal of developing an efficient classification technology. Future work can extend to creating classified objects using parametric tools with polygon-labeled datasets, offering meaningful numerical analysis for remodeling processes. Continued research in this direction is anticipated to significantly advance the efficiency of building remodeling techniques.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2015.11a
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• pp.64-65
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• 2015

As construction projects have increased in size and height recently, lifting accounts for increasingly greater portion and tower cranes are used more frequently. At present, the selection and arrangement of tower crane are depend on the experience of experts. However, since the number of experts is fairly limited and a database for tower cranes regarding lifting capacity, operation properties, rent, etc has not been widely employed, tower cranes are often not effectively selected and arranged which can cause cost overruns and delays in the lifting work. To address such issues, this study attempts to perform a basic study for development of automatic arrangement algorithm of tower crane using drawing recognition. If relevant database is established and the algorithm suggested in this study is refined more systematically, even beginning level engineers will be able to plan tower crane arrangement in a way comparable to experienced experts.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.443-452
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• 2020

Worker's awkward postures and unreasonable physical load can be corrected by monitoring construction activities, thereby increasing the safety and productivity of construction workers and projects. However, manual identification is time-consuming and contains high human variance. In this regard, an automated activity recognition system based on inertial measurement unit can help in rapidly and precisely collecting motion data. With the acceleration data, the machine learning algorithm will be used to train classifiers for automatically categorizing activities. However, input acceleration data are extracted either from designed experiments or simple construction work in previous studies. Thus, collected data series are discontinuous and activity categories are insufficient for real construction circumstances. This study aims to collect acceleration data during long-term continuous work in a construction project and validate the feasibility of activity recognition algorithm with the continuous motion data. The data collection covers two different workers performing formwork at the same site. An accelerator, as well as portable camera, is attached to the worker during the entire working session for simultaneously recording motion data and working activity. The supervised machine learning-based models are trained to classify activity in hierarchical levels, which reaches a 96.9% testing accuracy of recognizing rest and work and 85.6% testing accuracy of identifying stationary, traveling, and rebar installation actions.

• Journal of the Korea Institute of Building Construction
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• v.20 no.3
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• pp.289-296
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• 2020

This study suggests a methodology for automatically extracting placing information from 2D reinforced concrete details drawings and generating a 3D reinforcement placing model to develop a mobile augmented reality for bar placing work. To make it easier for users to acquire placing information, it is suggested that users takes pictures of structural drawings using a camera built into a mobile device and extract placing information using vision recognition and the OCR(Optical Character Registration) tool. In addition, an augmented reality app is implemented using the game engine to allow users to automatically generate 3D reinforcement placing model and review the 3D models by superimposing them with real images. Details are described for application to the proposed methodology using the previously developed programming tools, and the results of implementing reinforcement augmented reality models for typical members at construction sites are reviewed. It is expected that the methodology presented as a result of application can be used for learning bar placing work or construction review.

• Research in Mathematical Education
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• v.14 no.1
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• pp.33-50
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• 2010

The mathematical thinking which transforms important mathematical content and developed into mathematical structure is a vital process in building up mathematical ability as mathematical knowledge based on structure. Such process based on students' recognition of mathematical concept. Developing mathematical thinking into mathematical structure happens when different cognitive units are connected and compressed to form schema of solution, which could happen through some guided problems. The effort of arithmetic approach in problem solving did not necessarily provide students the structure schema of solution. The using of equation to solve the problem is based on the schema of building equation, and is not necessary recognizing the structure of the solution, as the recognition of structure may be lost in the process of simplification of algebraic expressions, leaving only the final numeric answer of the problem.

• Journal of Distribution Science
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• v.17 no.4
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• pp.17-26
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• 2019

Purpose - Today's companies concentrate intensively on building consumer value and corporate reputation for continuing growth and advancement in an ever-changing global business management environment. This research intended to study the correlation between consumer value and corporate social responsibility (CSR) activities in building corporate reputation with consumers. Research design, data, and methodology - Online and offline surveys were conducted among male and female adults across Korea. Surveys were conducted for three weeks from August 21, 2018 to September 8, 2018. The samples consisted of 350 offline and 112 online surveys, and a combined total of 462 samples was used for final analysis. Result - Higher consumer value means a greater chance that consumers will select that company's products over those of competitors. For competitive advantage purposes, companies use various consumer management strategies to bolster consumer value and corporate reputation with consumers. Conclusions - Brand assets are subject to ethical responsibility, which is a dimension of corporate social responsibility. Of note, one relevant finding about brand assets (similar to findings in previous research) is the existence of confusion about brand recognition and brand image as perceived by customers.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2007.04a
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• pp.97-100
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• 2007

Recently, A demand on productivity improvement has required innovation of construction industry more than fast with a economy condition. A RFID is technology that can be effectively applied at the administration of physical distribution, labor, construction progress, etc at construction industry. Therefore, At this paper, A survey of staffs that work at construction site is practised to study application possibility of RFID technology at construction industry. It shows use possibility through a survey that investigated Recognition and application, etc at construction site. RFID technology is connected with other technologies by being based on this study construction industry will be advanced.

• The Journal of Korea Robotics Society
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• v.2 no.3
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• pp.227-233
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• 2007

Representing an environment as the probabilistic grids is effective to sense outlines of the environment in the mobile robot area. Outlines of an environment can be expressed factually by using the probabilistic grids especially if sonar sensors would be supposed to build an environment map. However, the difficult problem of a sonar such as a specular reflection phenomenon should be overcome to build a grid map through sonar observations. In this paper, the NRF(Neighborhood Recognition Factor) was developed for building a grid map in which the specular reflection effect is minimized. Also the reproduction rate of the gird map built by using NRF was analyzed with respect to a true map. The experiment was conducted in a home environment to verify the proposed technique.

• Speech Sciences
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• v.10 no.4
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• pp.167-177
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• 2003

This paper presents a method of building an exceptional pronunciation dictionary for Korean automatic pronunciation generator. An automatic pronunciation generator is an essential element of speech recognition system and a TTS (Text-To-Speech) system. It is composed of a part of regular rules and an exceptional pronunciation dictionary. The exceptional pronunciation dictionary is created by extracting the words which have exceptional pronunciations from text corpus based on the characteristics of the words of exceptional pronunciation through phonological research and text analysis. Thus, the method contributes to improve performance of Korean automatic pronunciation generator as well as the performance of speech recognition system and TTS system.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2019.05a
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• pp.123-124
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• 2019

In the labor-intensive construction site, potential threats of the musculoskeletal diseases mainly caused by various repetitive physical tasks, vulnerable environment, and the aging of the labor worker exist. However, quantitative measuring method of construction labor worker's work posture has not been improved yet. This study proposed musculoskeletal measuring method by using wearable motion recognition sensor for quantitative evaluation and analysis of working posture of construction workers. This method is expected to be used as a basic data for posture analysis and prevention construction safety accidents, as well as physical workload and labor productivity analysis by labor work type.