• International conference on construction engineering and project management
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• 2009.05a
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• pp.30-31
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• 2009

Early detection of schedule delay in field construction activities is vital to project management. It provides the opportunity to initiate remedial actions and increases the chance of controlling such overruns or minimizing their impacts. This entails project managers to design, implement, and maintain a systematic approach for progress monitoring to promptly identify, process and communicate discrepancies between actual and as-planned performances as early as possible. Despite importance, systematic implementation of progress monitoring is challenging: (1) Current progress monitoring is time-consuming as it needs extensive as-planned and as-built data collection; (2) The excessive amount of work required to be performed may cause human-errors and reduce the quality of manually collected data and since only an approximate visual inspection is usually performed, makes the collected data subjective; (3) Existing methods of progress monitoring are also non-systematic and may also create a time-lag between the time progress is reported and the time progress is actually accomplished; (4) Progress reports are visually complex, and do not reflect spatial aspects of construction; and (5) Current reporting methods increase the time required to describe and explain progress in coordination meetings and in turn could delay the decision making process. In summary, with current methods, it may be not be easy to understand the progress situation clearly and quickly. To overcome such inefficiencies, this research focuses on exploring application of unsorted daily progress photograph logs - available on any construction site - as well as IFC-based 4D models for progress monitoring. Our approach is based on computing, from the images themselves, the photographer's locations and orientations, along with a sparse 3D geometric representation of the as-built scene using daily progress photographs and superimposition of the reconstructed scene over the as-planned 4D model. Within such an environment, progress photographs are registered in the virtual as-planned environment, allowing a large unstructured collection of daily construction images to be interactively explored. In addition, sparse reconstructed scenes superimposed over 4D models allow site images to be geo-registered with the as-planned components and consequently, a location-based image processing technique to be implemented and progress data to be extracted automatically. The result of progress comparison study between as-planned and as-built performances can subsequently be visualized in the D4AR - 4D Augmented Reality - environment using a traffic light metaphor. In such an environment, project participants would be able to: 1) use the 4D as-planned model as a baseline for progress monitoring, compare it to daily construction photographs and study workspace logistics; 2) interactively and remotely explore registered construction photographs in a 3D environment; 3) analyze registered images and quantify as-built progress; 4) measure discrepancies between as-planned and as-built performances; and 5) visually represent progress discrepancies through superimposition of 4D as-planned models over progress photographs, make control decisions and effectively communicate those with project participants. We present our preliminary results on two ongoing construction projects and discuss implementation, perceived benefits and future potential enhancement of this new technology in construction, in all fronts of automatic data collection, processing and communication.

• Journal of Computational Design and Engineering
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• v.1 no.1
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• pp.13-26
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• 2014

Recently, renovations of plant equipment have been more frequent because of the shortened lifespans of the products, and as-built models from large-scale laser-scanned data is expected to streamline rebuilding processes. However, the laser-scanned data of an existing plant has an enormous amount of points, captures intricate objects, and includes a high noise level, so the manual reconstruction of a 3D model is very time-consuming and costly. Among plant equipment, piping systems account for the greatest proportion. Therefore, the purpose of this research was to propose an algorithm which could automatically recognize a piping system from the terrestrial laser-scanned data of plant equipment. The straight portion of pipes, connecting parts, and connection relationship of the piping system can be recognized in this algorithm. Normal-based region growing and cylinder surface fitting can extract all possible locations of pipes, including straight pipes, elbows, and junctions. Tracing the axes of a piping system enables the recognition of the positions of these elements and their connection relationship. Using only point clouds, the recognition algorithm can be performed in a fully automatic way. The algorithm was applied to large-scale scanned data of an oil rig and a chemical plant. Recognition rates of about 86%, 88%, and 71% were achieved straight pipes, elbows, and junctions, respectively.

• Journal of KIBIM
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• v.9 no.2
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• pp.11-20
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• 2019

The use of drones and laser scanners have the potential to drastically reduce the time and costs of conventional techniques employed for field survey of cultural heritage buildings. Moreover, point cloud data can be utilized to create an as-built Building Information Model (BIM), providing a repository for consistent operations information. However, BIM creation is not a requisite for heritage buildings, and their technological possibilities and barriers have not been documented. This research explored the processes required to convert a heritage university building to a BIM model, using existing off-the-shelf software applications. Point cloud data was gathered from drones for the exterior, while a laser scanner was employed for the interior of the building. The point clouds were preprocessed and used as references for the geometry of the building elements, including walls, slabs, windows, doors, and staircases. The BIM model was subsequently created for the individual elements using existing and custom libraries. The model was used to extract 2D CAD drawings that met the requirements of Korea's heritage preservation specifications. The experiment showed that technical improvements were needed to overcome issues of occlusion, modeling errors due to modeler's subjective judgements and point cloud data cleaning and filtering techniques.

• Journal of Korea Planning Association
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• v.54 no.2
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• pp.93-108
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• 2019

This study examines the relationship between three-dimensional urban built environment and urban surface temperature using LANDSAT 8 satellite image data in Seoul city. The image was divided into 600m×600m grid units as an unit of analysis. Due to the high level of spatial dependency in surface temperature, this study uses spatial statistics to take into account spatial auto-correlation. The spatial error model shows the best goodness of fit. The analysis results show that the three-dimensional built environment and transport environment as well as natural environment have statistically significant associations with surface temperature. First, natural environment variables such as green space, streams and river, and average elevation show statistically significant negative association with surface temperature. Second, the building area shows a positive association with surface temperature. In addition, while sky view factor (SVF) has a positive association with surface temperature, surface roughness (SR) shows a negative association with it. Third, transportation related variables such as road density, railway density, and traffic volume show positive associations with surface temperature. Moreover, this study finds that SVF and SR have different effects on surface temperature in regard to the levels of total floor areas in built environment. The results indicate that interactions between floor area ratio (FAR) and three-dimensional built environmental variables such as SVF and SR should be considered to reduce urban surface temperature.

• Korean Management Science Review
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• v.32 no.1
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• pp.15-33
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• 2015

Under complete information, introducing additional constraints to a portfolio will have a negative impact on performance. However, real-life investments inevitably involve use of error-prone estimations, such as expected stock returns. In addition to the reality of incomplete data, investments of most Korean domestic equity funds are regulated externally by the government, as well as internally, resulting in limited maximum investment allocation to single stocks and risk free assets. This paper presents an investment framework, which takes such real-life situations into account, based on a newly developed portfolio selection model considering realistic constraints under incomplete information. Additionally, we examined the effects of additional constraints on portfolio's performance under incomplete information, taking the well-known Samsung and SK group stocks as performance benchmarks during the period beginning from the launch of each commercial fund, 2005 and 2007 respectively, up to 2013. The empirical study shows that an investment model, built under incomplete information with additional constraints, outperformed a model built without any constraints, and benchmarks, in terms of rate of return, standard deviation of returns, and Sharpe ratio.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.649-655
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• 2021

This study purposes to cross-validate its performance by applying the optimal seismic vulnerability assessment model based on previous studies conducted in Gyeongju to other regions. The test area was Pohang City, the occurrence site for the 2017 Pohang Earthquake, and the dataset was built the same influencing factors and earthquake-damaged buildings as in the previous studies. The validation dataset was built via random sampling, and the prediction accuracy was derived by applying it to a model based on a random forest (RF) of Gyeongju. The accuracy of the model success and prediction in Gyeongju was 100% and 94.9%, respectively, and as a result of confirming the prediction accuracy by applying the Pohang validation dataset, it appeared as 70.4%.

• Journal of the Korean Institute of Landscape Architecture
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• v.27 no.2
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• pp.95-107
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• 1999

Shamanism is an ancient culture that is also considered as a religious rite by most of people. So, shamanism is an important part of Korean tradition and should be a significant base to the Korean exterior space organization theme. However in the field of Landscape architecture th principle of exterior spacing has not yet clearly been identified as shamanistic. Therefore believe that this study can exhibit a model for the study of shaministic space language and its application to one of Korean's village Namsa. The results of this study are summarized below; 1. Extracted models are Unspecialized· Circular·Coninuous space. These are analyzed on the basis of the shaministic space language. Also shaministic space languages are based with Korean common belief of eternal human identify, circular view of the world. 2. Applying the shamanistic space models to Namsa village shows that shamanistic space models follow the Korean space organization principle. Some area of the village do not apply, because they were built on the structure of the social hierarchy between families or the difference between head households and collateral households. 3. Applying the shamanistic space model to Namsa village shows that the shamanistic space model follows the Korean space organization principle. Therefore can say that Namsa village was built by a shamanistic system that pursued eternal human identity.

• Journal of Korean Society of Transportation
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• v.22 no.5
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• pp.123-137
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• 2004

The study on traffic assignment is actively being performed which reflect networks status using time. Its background is increasing social needs to use traffic assignment models in not only hardware area of road network plan but also software area of traffic management or control. In addition, multi-class traffic assignment model is receiving study in order to fill a gap between theory and practice of traffic assignment model. This model is made up of two, one of which is multi-driver class and the other multi-vehicle class. The latter is the more realistic because it can be combined with dynamic model. On this background, this study is to build multidynamic model combining the above-mentioned two areas. This has been a theoretic pillar of ITS in which dynamic user equilibrium assignment model is now made an issue, therefore more realistic dynamic model is expected to be built by combining it with multi-class model. In case of multi-vehicle, FIFO would be violated which is necessary to build the dynamic assignment model. This means that it is impossible to build multi-vehicle dynamic model with the existing dynamic assignment modelling method built under the conditions of FIFO. This study builds dynamic network model which could relieve the FIFO conditions. At the same time, simulation method, one of the existing network loading method, is modified to be applied to this study. Also, as a solution(algorithm) area, time dependent shortest path algorithm which has been modified from existing shortest path algorithm and the existing MSA modified algorithm are built. The convergence of the algorithm is examined which is built by calculating dynamic user equilibrium solution adopting the model and algorithm and grid network.

• Journal of the Korean Statistical Society
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• v.31 no.2
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• pp.199-212
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• 2002

This article introduces transfer function model (TFM) with conditional heteroscedasticity where ARCH concept is built into the traditional TFM of Box and Jenkins (1976). Model building strategies such as identification, estimation and diagnostics of the model are discussed and are illustrated via empirical study including simulated data and real data as well. Comparisons with the classical TFM are also made.

• Geomechanics and Engineering
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• v.8 no.4
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• pp.559-594
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• 2015

A nonlinear creep function incorporated into the elastic visco-plastic model may describe the long-term soil deformation more accurately. However, by applying the conventional procedure, there are challenges to determine the model parameters due to limitation of suitable data points. This paper presents a numerical solution to obtain several parameters simultaneously for a nonlinear elastic visco-plastic (EVP) model using the available consolidation data. The finite difference scheme using the Crank-Nicolson procedure is applied to solve a set of coupled partial differential equations of the time dependent strain and pore water pressure dissipation. The model parameters are determined by applying the algorithm of trust-region reflective optimisation in conjunction with the finite difference solution. The proposed method utilises all available consolidation data during dissipation of the excess pore water pressure to determine the required model parameters. Moreover, the reference time in the elastic visco-plastic model can readily be adopted as a unit of time; denoting creep is included in the numerical predictions explicitly from the very first time steps. In this paper, the settlement predictions of thick soft clay layers are presented and discussed to evaluate and compare the accuracy and reliability of the proposed method against the graphical procedure to obtain the model parameters. In addition, comparison of the available experimental results to the numerical predictions confirms the accuracy of the numerical procedure.