• International conference on construction engineering and project management
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• 2009.05a
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• pp.1068-1074
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• 2009

The progress is widely used as a critical index for successful construction project management. In spite of the importance of progress measurement, the excessive management effort to collect and maintain detailed data has been highlighted as a major barrier to measurement of highly accurate progress. In order to reduce the required workload and to enhance accuracy, several researches have been conducted. These researches can be categorized into two groups. First group focuses on automated data collection utilizing advanced technologies only for limited construction tasks. The second group is a research area where the standard progress measurement methodologies encompassing entire construction tasks are investigated. Topics include the adjusting the level of details, standardizing work processes, and applying flexible WBS. However, the techniques for automated data collection are not fully investigated yet in the second group. Combining these two research areas can provide a solution for more effective progress management in terms of enhancing accuracy and optimizing workload. However, there has been no comprehensive research addressing these two research groups in an integrated manner. In this context, the purpose of this paper is to propose a methodology that identifies the most suitable measurement method and data acquisition technology (e.g., GPS, RFID, etc.) for entire construction tasks of a project. The proposed methodology in this paper will be able to facilitate the selection process of data acquisition technologies for entire construction tasks of a project and to support the overall enhancement of automated progress management.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.27-29
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• 2009

Real-time control of on-site construction, based on high quality data, is essential to identify discrepancies between actual and planned performances. Additionally, real-time control enables timely corrective measures to be taken when needed to reduce the damages caused by the discrepancies. The focus of the presentation will be on our work, which uses automated data technologies to collect data needed for real time control.

• Proceedings of the Korean Geotechical Society Conference
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• 2000.11a
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• pp.607-614
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• 2000

A cost-effective automated slope monitoring system is developed to monitor hazardous cut slopes along highways. This automated slope monitoring system consists of data-collection and visual monitoring, data-transmitting, database and internet service, and alarm system. Wire-line extensometer, automatic raingauge, and CCD camera are selected as monitoring instruments in this system, after consideration of failure characteristics of roadside cut slopes in the country. This paper describes the important features of this newly developed automated slope monitoring system.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.17-22
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• 2011

A considerable number of construction disasters occur on pathways. Safety management is usually performed on construction sites to prevent accidents in activity areas. This means that the safety management level of hazards on pathways is relatively minimized. Many researchers have noted that hazard identification is fundamental to safety management. Thus, algorithms for helping safety managers to identify hazardous areas are developed using automated data collection technology. These algorithms primarily search for potential hazardous areas by comparing workers' location logs based on a real-time location system and optimal routes based on BIM. Potential hazardous areas are filtered by identified hazardous areas and activity areas. After that, safety managers are provided with information about potential hazardous areas and can establish proper safety countermeasures. This can help to improve safety on construction sites.

• Korean Journal of Construction Engineering and Management
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• v.11 no.6
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• pp.14-23
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• 2010

A considerable number of construction disasters occurs on pathway. A safety management in construction sites is usually performed to prevent accidents in activity areas. This means that safety management level of hazards on pathway is relatively minified. Many researchers have introduced that a hazard identification is fundamental of safety management. Thus, algorithms for helping safety managers' hazardous area identification is developed using automated data collection technology. These algorithms primarily search potential hazardous area by comparing workers' location logs based on real-time locating system and optimal routes based on BIM. And potential hazardous areas is filtered by identified hazardous areas and activity areas. After that, safety managers are provided with information about potential hazardous areas and can establish proper safety countermeasures. This can help improving safety in construction sites.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1324-1327
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• 2009

Social infrastructure is the basis of public welfare and should be recognized and managed as important assets. Bridge is one of the most important infrastructures to be managed systematically because the impact of the failure is critical. It is essential to monitor the performance of bridges in order to manage them as an asset. But current analytical methods such as predictive modeling and structural analysis are very complicated and difficult to use in practice. To apply these methods, structural and material condition data collection should be performed in each element of bridge. But it is difficult to collect these detailed data in large numbers and various kinds of bridges. Therefore, it is necessary to collect data of major measurement items and predict the life of bridges roughly with advanced information technologies. When certain measurement items reach predefined limits in the monitoring bridges, precise performance measurement will be done by detailed site measurement. This paper describes the selection of major measurement items that can represent the tendency of bridge life and introduces automated bridge data collection test-bed using wireless sensor network technology. The following will be major parts of this paper: 1) Examining the features of conventional bridge management system and data collection method 2) Mileage concept as a bridge life indicator and measuring method of the indicator 3) Test-bed of automated and real-time based bridge life indicator monitoring system using wireless sensor network

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.3
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• pp.205-216
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• 2014

Multi-camera systems have been widely used as cost-effective tools for the collection of geospatial data for various applications. In order to fully achieve the potential accuracy of these systems for object space reconstruction, careful system calibration should be carried out prior to data collection. Since the structural integrity of the involved cameras' components and system mounting parameters cannot be guaranteed over time, multi-camera system should be frequently calibrated to confirm the stability of the estimated parameters. Therefore, automated techniques are needed to facilitate and speed up the system calibration procedure. The automation of the multi-camera system calibration approach, which was proposed in the first part of this paper, is contingent on the automated detection, localization, and identification of the object space signalized targets in the images. In this paper, the automation of the proposed camera calibration procedure through automatic target extraction and labelling approaches will be presented. The introduced automated system calibration procedure is then implemented for a newly-developed multi-camera system while considering the optimum configuration for the data collection. Experimental results from the implemented system calibration procedure are finally presented to verify the feasibility the proposed automated procedure. Qualitative and quantitative evaluation of the estimated system calibration parameters from two-calibration sessions is also presented to confirm the stability of the cameras' interior orientation and system mounting parameters.

• The KSFM Journal of Fluid Machinery
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• v.17 no.4
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• pp.40-46
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• 2014

This paper describes blower performance characteristics of a automated vacuum waste collection system. Blowers serially connected to six or seven centrifugal blowers are evaluated by experimental measurements to understand blower performances according to blower numbers operated. Two different blowers and duct diameters connected to the main blowers are considered. Data acquisition system is introduced to measure pressure and pressure difference at the main duct simultaneously, which is connected to several blowers serially. A auxiliary blower, which is installed between a filter room and an air deodorizing apparatus, is also added to simulate its performance effect on the main blower. Throughout the experimental measurements of the blower system, it is found that pressure and inlet velocity at the upstream of a blower increase 3.7 and 2.4 times separately by increasing the operating blower numbers from one to seven. It is noted that blower efficiency and pressure measured at the system vary according to the distance between a air intake and a blower system. Auxiliary blower is effective to increase blower inlet suction pressure, while total energy consumption is increased relatively.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.9 no.3
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• pp.13-26
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• 1999

Widespread use of Internet despite numerous positive aspects resulted in increased number of system intrusions and the need for enhanced security mechanisms is urgent. Systematic collection and analysis of log data are essential in intrusion investigation. Unfortunately existing logs are stored in diverse and incompatible format thus making an automated intrusion investigation practically impossible. We examined the types of log data essential in intrusion investigation and implemented a tool to enable systematic collection and efficient analysis of voluminous log data. Our tool based on RBDMS and SQL provides graphical and user-friendly interface. We describe our experience of using the tool in actual intrusion investigation and explain how our tool can be further enhanced.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.463-473
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• 2021

Recently, United States Geological Survey (USGS) distributed Landsat 8 Collection 2 Level 2 Science Product (L2SP). This paper aims to derive land surface temperature from L2SP and to validate it. Validation is made by comparing the land surface temperature with the one calculated from Landsat 8 Collection 1 Level 1 Terrain Precision (L1TP) and the one from Automated Synoptic Observing System (ASOS). L2SP is calculated from Landsat 8 Collection 2 Level 1 data and it provides land surface temperature to users without processing surface reflectance data. Landsat 8 data from 2018 to 2020 is collected and ground sensor data from eight sites of ASOS are used to evaluate L2SP land surface temperature data. To compare ground sensor data with remotely sensed data, 3×3 grid area data near ASOS station is used. As a result of analysis with ASOS data, L2SP and L1TP land surface temperature shows Pearson correlation coefficient of 0.971 and 0.964, respectively. RMSE (Root Mean Square Error) of two results with ASOS data is 4.029℃, 5.247℃ respectively. This result suggests that L2SP data is more adequate to acquire land surface temperature than L1TP. If seasonal difference and geometric features such as slope are considered, the result would improve.