• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.471-485
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• 2023

As data sharing increases explosively, such information encoded in QR code is completely public as private messages are not securely protected. This paper proposes a new 'PROMISE' framework for hiding information based on the QR code projection matrix by using image segmentation without modifying the essential QR code characteristics. Projection matrix mapping, matrix scrambling, fusion image segmentation and steganography with SEL(secret embedding logic) are part of the PROMISE framework. The QR code could be mapped to determine the segmentation site of the fusion image as a binary information matrix. To further protect the site information, matrix scrambling could be adopted after the mapping phase. Image segmentation is then performed on the fusion image and the SEL module is applied to embed the secret message into the fusion image. Matrix transformation and SEL parameters should be uploaded to the server as the secret key for authorized users to decode the private message. And it was possible to further obtain the private message hidden by the framework we proposed. Experimental findings show that when compared to some traditional information hiding methods, better anti-detection performance, greater secret key space and lower complexity could be obtained in our work.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1114-1121
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• 2022

Construction laborers and crews play a critical role in achieving a safe and productive construction site. Many past research studies used top-down approaches/perspectives for studying the impact of laborers' performance on overall construction site outputs with limited flexibility in accounting for laborers' various characteristics. However, the recent reap in computational advances allowed applications of bottom-up architectures, which can potentially incorporate heterogeneous characteristics of laborers' individual behavioral and decision-making features effectively. Accordingly, agent-based modeling (ABM), as a tool to leverage a bottom-up methodological approach, has been widely adopted by recent research. Existing literature investigated the influence of changes in laborers' behaviors and interactions on either construction sites' safety performance or productivity performance individually, leaving the tradeoff between safety and productivity in this context relatively unexplored. Accordingly, this study aims to develop an agent-based framework to study the tradeoff between project safety and productivity performances resulting from changes in laborers' behaviors after attending safety trainings. Our findings via simulations indicate that proper safety trainings can improve safety performance without negatively impacting productivity performance.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.736-743
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• 2022

Construction workers experience a high rate of fatal incidents from mobile equipment in the industry. One of the major causes is the decline in the acoustic condition of workers due to the constant exposure to construction noise. Previous studies have proposed various ways in which audio sensing and machine learning techniques can be used to track equipment's movement on the construction site but not on the audibility of safety signals. This study develops a novel framework to help automate safety surveillance in the construction site. This is done by detecting the audio sound at a different signal-to-noise ratio of -10db, -5db, 0db, 5db, and 10db to notify the worker of imminent dangers of mobile equipment. The scope of this study is focused on developing a signal processing model to help improve the audible sense of mobile equipment for workers. This study includes three-phase: (a) collect audio data of construction equipment, (b) develop a novel audio-based machine learning model for automated detection of collision hazards to be integrated into intelligent hearing protection devices, and (c) conduct field experiments to investigate the system' efficiency and latency. The outcomes showed that the proposed model detects equipment correctly and can timely notify the workers of hazardous situations.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.205-209
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• 2015

A significant amount of data including ongoing construction activities, work quantities, resources utilized by contractors, and site conditions is collected in highway construction sites on a daily basis by resident engineers. This data is commonly known as daily work reports (DWRs) in the U.S. Although a lot of time and effort is invested in collecting the DWR data, its utilization has been very limited. This paper discusses current practices of collecting and utilizing DWR data among various Departments of Transportation in the U.S., and discusses the challenges and opportunities for better collection and utilization of the data. An extensive literature review and two nationwide surveys in the U.S. were conducted as a part of this study. Finally, it provides a set of recommendations to effectively address the challenges identified and maximize the benefits of utilizing DWR data such as supporting various decisions for highway project development process. The findings of this study are implementable ideas that can aid DOTs in making data-driven decisions throughout the project development processes in the future.

• Geomechanics and Engineering
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• v.37 no.3
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• pp.279-291
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• 2024

The "Korea Institute of Geoscience and Mineral (KIGAM) Quake" is a web-based open platform developed for publicly serving seismological data from 61 stations operated by KIGAM in Korea. The service provides meta-information related to observatory sites, sensors, and recorders necessary for utilizing the seismological data, as well as mainly observed continuous and strong-motion waveforms. The data is available through both the web and International Federation of Digital Seismograph Networks (FDSN) web services (open API), a unified data-providing interface in seismology. The platform aims to strengthen its open nature by offering a signal processing function for strong ground motions that can be controlled by user requests. The processed results can be downloaded in ASCII format, designed to meet the increased demands and accessibility in the earthquake engineering field. The platform also offers earthquake research information produced by KIGAM, such as recent major earthquake source information and academic annual report of earthquakes. Additionally, a site flat file was constructed for the geotechnical characteristics of 61 KIGAM station (KGNET) sites based on direct investigations and estimations.

• Earthquakes and Structures
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• v.27 no.4
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• pp.303-315
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• 2024

This study proposes a comprehensive methodology for estimating accumulative damage of bridge structures under multiple seismic excitations, in the framework of site-specific probabilistic hazard analysis. Specifically, a typical earthquake-prone region in China is chosen to perform probabilistic seismic hazard analysis (PSHA) to find the mean annual rate (MAR) of ground motion intensity at a specific level, based on which, a mass of ground motion observations is selected to construct random earthquake sequences with various number of shocks. Then, nonlinear time history analysis is implemented on the finite element (FE) model of a RC girder bridge at the site of interest, to investigate structural responses under different earthquake sequences, and to develop predictive model for cumulative damage computation, in which, a scalar seismic intensity measure (IM) is adopted and its performance in damage prediction is discussed by an experimental column. Furthermore, a mathematic model is established to calculate occurrence probability of earthquakes with various number of shocks, based on PSHA and homogenous Poisson random process, and a modified cumulative damage indicator is proposed, accounting for probabilistic occurrence of various earthquake scenarios. At end, the applicability of the proposed methodology to main shock and aftershock scenarios is validated, and characteristics of damage accumulation under different multiple earthquake scenarios are discussed.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.4
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• pp.39-46
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• 2014

Network RTK GNSS positioning technique which has been developed to overcome the limitation of Single reference station RTK is used widely in the field of general surveying, cadastre surveying and engineering surveying due to the high accuracy and efficiency. It is specified Network RTK, Single reference station RTK and Static of GNSS as a surveying method in the regulation of Cadastre Re-survey Surveying. In this study, Network RTK and Static GNSS surveying were accomplished at cadastral re-survey field in Hadong, Gyeongnam and the surveying results were compared. Also, to analyze the performance of site calibration in Network RTK surveying, two types of Network RTK surveying with and without site calibration were accomplished and the results was compared. The research result shows that average positioning error between Network RTK(VRS) without site calibration and Static surveying result is 2.44cm and 1.53cm respectively and average positioning error between Network RTK(VRS) with site calibration and Static surveying result is 0.19cm and 0.82cm respectively at two zone. So, it was proved the effect of calibration in network RTK(VRS) surveying.

• Journal of the Korean Society of Marine Environment & Safety
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• v.18 no.6
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• pp.545-550
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• 2012

Wind resource assessment is necessary when designing wind farm. To get the assessment, we must use a long term(20 years) observed wind data but it is so hard. so that we usually measured more than a year on the planned site. From the wind data, we can calculate wind energy related with the wind farm site. However, it calculate wind energy to collect the long term data from Met-mast(Meteorology Mast) station on the site since the Met-mast is unstable from strong wind such as Typhoon or storm surge which is Non-periodic. To solve the lack of the long term data of the site, we usually derive new data from the long term observed data of AWS(Automatic Weather Station) around the wind farm area using mathematical interpolation method. The interpolation method is called MCP(Measure-Correlative-Predict). In this study, based on the MCP Regression Model proposed by us, we estimated the wind energy at Handong site using AEP(Annual Energy Production) from Gujwa AWS data in Jeju. The calculated wind energy at Handong was shown a good agreement between the predicted and the measured results based on the linear regression MCP. Short term AEP was about 7,475MW/year. Long term AEP was about 7,205MW/year. it showed an 3.6% of annual prediction different. It represents difference of 271MW in annual energy production. In comparison with 20years, it shows difference of 5,420MW, and this is about 9 months of energy production. From the results, we found that the proposed linear regression MCP method was very reasonable to estimate the wind resource of wind farm.

• The Journal of Engineering Geology
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• v.25 no.1
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• pp.45-55
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• 2015

Purifying leachate discharged from animal carcass disposal sites requires decisions regarding the locations and numbers of boreholes. An electrical resistivity survey, known to be effective for investigating leachate distribution, was performed to evaluate the range extent of contamination due to local hydrological properties, such as groundwater flow direction, and geological structure. Results of the survey at four sites at a landfill near Icheon and Anseong, Gyeonggi Province, showed low-resistivity zones (20-200 ohm-m) at a depth of 8 m from the surface. Sites 1-4, which contain 5, 2, 4, and 2 boreholes, respectively, were estimated to have a contaminated groundwater acquisition capability of 12.9 m, 13.7 m, 10.1 m, and 18.0 m, and measured pumping capacity of 2,040 m³, 479.8 m³, 1,492.3 m³, and 691.9 m³, respectively.

• Journal of Korean Society for Atmospheric Environment
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• v.34 no.5
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• pp.727-734
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• 2018

In this study, real-time absorption coefficients of carbonaceous species in $PM_{2.5}$ was observed using a dual-spot 7-wavelength Aethalometer between November 1, 2016 and December 31, 2017 at an urban site of Gwangju. In addition, 24-hr integrated $PM_{2.5}$ samples were simultaneously collected at the same site and analyzed for organic carbon and elemental carbon (OC and EC) using the thermal-optical transmittance protocol. A main objective of this study was to estimate mass absorption cross section (MAC) values of black carbon (BC) particles at the study site using the linear regression between aethalometer-based absorption coefficient and filter-based EC concentration. BC particles observed at 880 nm is mainly emitted from combustion of fossil fuels, and their concentration is typically reported as equivalent BC concentration (eBC). eBC concentration calculated using MAC value of $7.77m^2/g$ at wavelength of 880 nm, which was proposed by a manufacturer, ranged from 0.3 to $7.4{\mu}g/m^3$ with an average value of $1.9{\pm}1.2{\mu}g/m^3$, accounting for 7.3% (1.5~20.9%) of $PM_{2.5}$. The relationship between aerosol absorption coefficients at 880 nm and EC concentrations provided BC MAC value of $15.2m^2/g$, ranging from 11.4 to $16.2m^2/g$. The eBC concentrations calculated using the estimated MAC of $15.2m^2/g$ were significantly lower than those reported originally from aethalometer, and ranged from 0.2 to $3.8{\mu}g/m^3$, with an average of $1.0{\pm}0.6{\mu}g/m^3$, accounting for 3.7% of $PM_{2.5}$ (0.8~10.7%). Result from this study suggests that if the MAC value recommended by the manufacturer is applied to calculate the equivalent BC concentration and radiative forcing due to BC absorption, they would result in significant errors, implying investigation of an unique MAC value of BC particles at a study site.