• International conference on construction engineering and project management
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• 2020.12a
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• pp.455-462
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• 2020

Noise which is unwanted sound is a serious pollutant that can affect human health, as well as the working and living environment if exposed to humans. However, current noise management on the construction project is generally conducted after the noise exceeds the regulation standard, which increases the conflicts with inhabitants near the construction site and threats to the safety and productivity of construction workers. To overcome the limitations of the current noise management methods, the activities of construction equipment which is the main source of construction noise need to be managed throughout the construction period in real-time. Therefore, this paper proposed a framework for automatically detecting noise sources in construction sites in real-time based on convolutional neural networks (CNNs) according to the following four steps: (i) Step 1: Definition of the noise sources; (ii) Step 2: Data preparation; (iii) Step 3: Noise source classification using the audio CNN; and (iv) Step 4: Noise source detection using the visual CNN. The short-time Fourier transform (STFT) and temporal image processing are used to contain temporal features of the audio and visual data. In addition, the AlexNet and You Only Look Once v3 (YOLOv3) algorithms have been adopted to classify and detect the noise sources in real-time. As a result, the proposed framework is expected to immediately find construction activities as current noise sources on the video of the construction site. The proposed framework could be helpful for environmental construction managers to efficiently identify and control the noise by automatically detecting the noise sources among many activities carried out by various types of construction equipment. Thereby, not only conflicts between inhabitants and construction companies caused by construction noise can be prevented, but also the noise-related health risks and productivity degradation for construction workers and inhabitants near the construction site can be minimized.

• Proceedings of the KSR Conference
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• 2003.05a
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• pp.321-325
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• 2003

The technology for the multi-dimensional terrain perspective view can be used as an important factors in planning and designing for the various construction projects. In this study, the stereo image perspective view has been generated for the multi-dimension analysis by combining useful digital map and remotely sensed satellite images. In the course of experimenting with the multi-dimensional topography generated by the combination of the front-projected image by the precise GCP and DEM from the contour line, the technology has been developed to offer the multi-dimensional access to the potential construction sites from the nearby main roads. This stereo image bird's eye view has made it possible to make multi-dimensional analysis on the terrain, which provides real time virtual access to the designated construction sites and will be a versatile application for development planning and construction projects.

• Journal of the Korean Association of Geographic Information Studies
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• v.5 no.3
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• pp.1-8
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• 2002

The technology for the three-dimensional terrain perspective view can be used as an important factor in planning and designing for the various construction projects. In this study, the stereo image perspective view has been generated for the multi-dimension analysis by combining useful digital map and remotely sensed satellite images. In the course of experimenting with the three-dimensional topography generated by the combination of the orthopimage by the precise GCP and DEM from the contour line, the technology has been developed to offer the multi-dimensional access to the potential construction sites from the nearby main roads. This stereo image bird's eye view has made it possible to make multi-dimensional analysis on the terrain, which provides real-time virtual access to the designated construction sites and will be a versatile application for development planning and construction projects.

• Journal of the Korean Institute of Landscape Architecture
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• v.33 no.1 s.108
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• pp.33-48
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• 2005

The purpose of this study was to discover the landscape visual image of the slope scene and their harmony with surrounding sceneries. This research utilized the basic study tool of psycho-physics and processed the case study of ten types of slope construction scene along the highway. The analysis was performed by the data obtained from the questionnaires and the photos for the slope construction scene. The questionnaires for analysis the image of the slope construction scene and their harmony with surrounding sceneries were designed using semantic differential scale and 5 point Likert-scale. The major findings were as follows. 1. At the part of the visual preferences analysis, the slope revegetation methods showed high level of preferences generally than on the slope structure methods. While the slope revegetation methods were estimated friendly, continuity, harmonious, soft, light and wide, the slope revegetation methods were estimated unstable, female, static, simple, omnipresent, appeared as policeman of weak inclination. Also the slope structure methods were estimated stable, manly, complicated, steep and healthy but rough, unharmonious, unfamiliar and heavy. 2. Psychological factors, related to the satisfaction for the slope revegetation methods were composed of three factors, aesthetic, individuality and physical character. And the slope structure methods were composed of five factors, aesthetic, individuality, stability, physical character, and complexity. 3. At the part of harmony with surrounding landscapes, the slope revegetation methods were evaluated highly but the slope structure methods received the lowest evaluation. Also the harmony analysis with surrounding view on the slope revegetation methods showed degree of high more than average in all texture, form, color and scale but the slope structure methods showed degree of fewer than average degree in form, scale, color and texture.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.1
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• pp.105-111
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• 2009

A construction can be more convenient and safer with adequate informations. Consequently, studies on collecting various informations using newest surveying technology and applying these informations to a construction have been making progress recently. Digital images are easy to obtain and contain various informations. Therefore, with the recent development of image processing technology, the application field of digital images is getting wider. In this study, we proposed to use a fisheye lens camera in underground construction sites, especially tunnels, to overcome inconvenience in photographing with general lens cameras. A program for mapping the surface of a tunnel and making a mosaic image is also developed. This mosaic image can be applied to observe and analyze abnormal phenomenons on tunnel surface like cracks, water leakage, exfoliates, and so on.

• ETRI Journal
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• v.37 no.5
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• pp.979-989
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• 2015

Recently, Hou and others introduced a (2, n) block-based progressive visual cryptographic scheme (BPVCS) in which image blocks can be gradually recovered step by step. In Hou and others' (2, n)-BPVCS, a secret image is subdivided into n non-overlapping image blocks. When t ($2{\leq}t{\leq} n$) participants stack their shadow images, all the image blocks associated with these t participants will be recovered. However, Hou and others' scheme is only a simple 2-out-of-n case. In this paper, we discuss a general (k, n)-BPVCS for any k and n. Our main contribution is to give two constructions (Construction 1 and Construction 2) of this general (k, n)-BPVCS. Also, we theoretically prove that both constructions satisfy a threshold property and progressive recovery of the proposed (k, n)-BPVCS. For k = 2, Construction 1 is reduced to Hou and others' (2, n)-BPVCS.

• KEPCO Journal on Electric Power and Energy
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• v.7 no.2
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• pp.285-293
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• 2021

The construction of underground structures such as power supply lines, communication lines, utility tunnels has significantly increased worldwide for improving urban aesthetics ensuring citizen safety, and efficient use of underground space. Those underground structures are usually constructed along with vertical cylindrical shafts to facilitate their construction and maintenance. When constructing a vertical shaft through the open-cut method, the walls are mostly designed to be flexible, allowing a certain level of displacement. The earth pressure applied to the flexible walls acts as an external force and its accurate estimation is essential for reasonable and economical structure design. The earth pressure applied to the flexible wall is closely interrelated to the displacement of the surrounding ground. This study simulated stepwise excavation for constructing a cylindrical vertical shaft through a centrifugal model experiment. One quadrant of the axisymmetric vertical shaft and the ground were modeled, and ground excavation was simulated by shrinking the vertical shaft. The deformation occurring on the entire ground during the excavation was continuously evaluated through digital image analysis. The digital image analysis evaluated complex ground deformation which varied with wall displacement, distance from the wall, and ground depth. When the ground deformation data accumulate through the method used in this study, they can be used for developing shaft wall models in future for analyzing the earth pressure acting on them.

• Journal of Drive and Control
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• v.19 no.3
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• pp.9-15
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• 2022

This paper proposes a method for constructing and verifying datasets used in deep learning technology, to prevent safety accidents in automated construction machinery or autonomous vehicles. Although open datasets for developing image recognition technologies are challenging to meet requirements desired by users, this study proposes the interface of virtual simulators to facilitate the creation of training datasets desired by users. The pixel-level training image dataset was verified by creating scenarios, including various road types and objects in a virtual environment. Detecting an object from an image may interfere with the accurate path determination due to occlusion areas covered by another object. Thus, we construct a database, for developing an occlusion area detection algorithm in a virtual environment. Additionally, we present the possibility of its use as a deep learning dataset to calculate a grid map, that enables path search considering occlusion areas. Custom datasets are built using the RDBMS system.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.3
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• pp.67-74
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• 2014

Over the last several decades, the United States has experienced a great number of natural disasters. To minimize the impact of the natural hazard events, the U.S. government spent a tremendous amount of money through federal assistant programs. To be eligible for the programs, a mitigation project must be cost effective (more benefits compared to project costs). However, the state and local communities suffering from the natural disasters generally have difficulty in collecting reliable evidence for their damages which can be converted later into benefits when a mitigation project is implemented. Therefore, this paper shows the process of conducting a benefit cost analysis with limited data. Besides, it also provides how to apply the limited data to the analysis through a case study. Consequently, this paper help state and local communities get funding from the federal government, which in turns will improve the image of construction industry by preventing people from natural disasters.

• Magazine of the Korean Society of Agricultural Engineers
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• v.43 no.1
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• pp.75-86
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• 2001

North Korea reported that tideland reclamation projects had been successfully constructed and/or under construction during the period of the third development scheme(1987∼1993), which were 28,400ha in 9 project areas: 8 projects along the western coast and one in the eastern coast. In this study eight projects located in western coast were investigated in order to confirm the detail of works, construction stages and difference from our project formulation methods using the topographic maps published in different years and the recent sattelite image data especially Lansat TM and SPOT PN. Intensity-hue-saturation (IHS) method was adopted to merge two sattelite data for the image enhancement of remote sensing. Construction stages of sea-dikes, land consolidation for paddy and salt pan, reservoir for irrigation and desalinization and the present land use were investigated and estimated the acreage of the development areas. The total gross project areas of 38,105 ha: 16,555 ha completed for paddy or salt pan, 16,826 ha under construction, and 4,724 ha under planning were confirmed, although the area of 27,100 ha in 8 projects were reported to be completed or ongoing on the bimonthly journal of N. Korean Trend published in 1994.