• Tunnel and Underground Space
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• v.33 no.6
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• pp.508-518
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• 2023

This paper presents a new approach for the automatic mapping of discontinuities in a tunnel face based on its 3D digital model reconstructed by LiDAR scan or photogrammetry techniques. The main idea revolves around the identification of discontinuity areas in the 3D digital model of a tunnel face by segmenting its 2D projected images using a deep-learning semantic segmentation model called U-Net. The proposed deep learning model integrates various features including the projected RGB image, depth map image, and local surface properties-based images i.e., normal vector and curvature images to effectively segment areas of discontinuity in the images. Subsequently, the segmentation results are projected back onto the 3D model using depth maps and projection matrices to obtain an accurate representation of the location and extent of discontinuities within the 3D space. The performance of the segmentation model is evaluated by comparing the segmented results with their corresponding ground truths, which demonstrates the high accuracy of segmentation results with the intersection-over-union metric of approximately 0.8. Despite still being limited in training data, this method exhibits promising potential to address the limitations of conventional approaches, which only rely on normal vectors and unsupervised machine learning algorithms for grouping points in the 3D model into distinct sets of discontinuities.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.2
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• pp.169-176
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• 2013

To generate the walking path of a humanoid robot in an unknown environment, the shapes of obstacles around the robot should be detected accurately. However, doing so incurs a very large computational cost. Therefore this study proposes a method to classify the obstacle shape into three types: a shape small enough for the robot to go over, a shape planar enough for the robot foot to make contact with, and an uncertain shape that must be avoided by the robot. To classify the obstacle shape, first, the range and the number of the obstacles is detected. If an obstacle can make contact with the robot foot, the shape of an obstacle is accurately derived. If an obstacle has uncertain shape or small size, the shape of an obstacle is not detected to minimize the computational load. Experimental results show that the proposed algorithm efficiently classifies the shapes of obstacles around the robot in real time with low computational load.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.1111-1122
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• 2020

The purpose of this research aims to develop the creative economy sector of rural communities in Trenggalek Regency, East Java, Indonesia by mapping the creative economy sub-sectors in Trenggalek Regency. The creative economy industry has been shown to have a positive effect on GDP in many developing countries and developed countries. In urban areas, the creative economy is often associated with the development of advanced technology, such that it is unlikely to evolve in rural communities. However, the rural environmental landscape, which not only has a wealth of creative human capital but also a cultural heritage, also encourages the growth of the creative economy sector in rural areas. This qualitative research was conducted for 60 working days through in-depth interviews, focus group discussions, observation and literature review. More precisely, first, it identified the potential of the creative economy both sectorally and regionally. Second, it identified the leading creative economy subsectors and compiled a creative economic development road map. After defining and mapping the potential of the creative economy, four of the sixteen sub-sectors of the creative economy were identified to be developed through a strategic plan for the growth of the creative economy using urban branding, innovative industrial centers and renewable resources.

• Journal of the Ergonomics Society of Korea
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• v.34 no.6
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• pp.563-581
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• 2015

Objective: This study was conducted to investigate the potential of sematic network analysis for design research. Background: As HCD (Human-Centered Design) was emphasized, lots of design research methodologies were developed and used in order to find user needs. However, it is still difficult to discover users' latent needs. This study suggests the semantic network analysis as a complementary means for design research, and proved its potential through the practical application, which compares multi-screen purchase and usage behaviors between America and China. Method: We conducted an in-depth interview with 32 consumers from USA and China, and analyzed interview texts through semantic network analysis. Cross cultural differences in purchase and usage behaviors were investigated, based on measuring centrality and community modularity of devices, functions, key buying factors and brands. Results: Americans use more services and functions in the multi-screen environment, compared to Chinese. As a device substitutes other devices, traditional boundaries of the devices are disappearing in the USA. Americans consider function to recall Apple, but Chinese consider function, design and brand to recall Apple, Sony and Samsung as an important brand at the time of their purchase. Conclusion: This study shows the potential of semantic network analysis for design research through the practical application. Semantic network analysis presents how the concepts regarding a theme are structured in the cognitive map of users with visual images and quantitative data. Therefore, it can complement the qualitative analysis of the existing design research. Application: As the design environment becomes more and more complicated like multi-screen environment, semantic network analysis, which is able to provide design insights in the intuitive and holistic perspective, will be acknowledged as an effective tool for further design research.

• Journal of the Korean Geotechnical Society
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• v.31 no.11
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• pp.49-60
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• 2015

Open-water sediment disposal has many applications in costal construction. Dumping of sediment in open water can be divided into descending stage under water and sedimentation stage on the seabed, and retained rate is evaluated from analyzed results of these two successive stages. Descending particle cloud have two distinct thermal and swam phase, and trajectory equations for each phase are derived to describe settling velocity and radius of particle cloud. For sedimentation stage, a numerical simulator is used to calculate growth factors for particle fiction angle and current velocity. Retained rate is defined as a mass rate of remained sediment inside the circle which has a center at dumping point on the sea level and user-defined effective radius. Retained rate map for Singapore coast is presented with water depth of 20 m, current velocity of 0.0~1.5 m/s, and effective radius of 5 m. It will decrease sediment mass loss during disposal operation and minimize surrounding environmental pollution.

• The Journal of Engineering Geology
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• v.2 no.1
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• pp.47-57
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• 1992

Geophysical methods applied to water seepage problem in earth-fill embankment attempt to detect and map the estimate of size and depth of the seepage path. Seepage zones generally produce lOW resistivity anomalies due to high saturation of water. Dipole-dipole resistivity surveying technique, which is actually a combined sounding-profiling procedure, was used to delineate the seepage path through this study. In this study, the finite difference methods to solve the electric potential distribution in 2 112 dimension, was adopted as the numerical scheme for the forward problem. Second order Marquart's method, one the iterative damped least square methods, was selected for the automatic inversion. The computer program was implemented in FORTRAN 77 for 1 6-bit personal computer. In this paper, we present a case history which illustrates the application of dipole-dipole resistivity method to the delineation of water flow in earth-fill structures. Also the automatic two-dimensional resistivity inversion was applied to a field data where the interpretive advantages of the program become evident.

• Journal of Biosystems Engineering
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• v.34 no.5
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• pp.382-389
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• 2009

An in-situ probe-based spectrophotometer has been developed. This system used two spectrometers to measure soil reflectance spectra from 450 nm to 2200 nm. It collects soil electrical conductivity (EC) and insertion force measurements in addition to the optical data. Six fields in Kansas were mapped with the VIS-NIR (visible-near infrared) probe module and sampled for calibration and validation. Results showed that VIS-NIR correlated well with carbon in all six fields, with RPD (the ratio of standard deviation to root mean square error of prediction) of 1.8 or better, RMSE of 0.14 to 0.22%, and $R^2$ of 0.69 to 0.89. From the investigation of carbon variability within the soil profile and by tillage practice, the 0-5 cm depth in a no-till field contained significantly higher levels of carbon than any other locations. Using the selected calibration model with the soil NIR probe data, a soil profile map of estimated carbon was produced, and it was found that estimated carbon values are highly correlated to the lab values. The array of sensors (VIS-NIR, electrical conductivity, insertion force) used in the probe allowed estimating bulk density, and three of the six fields were satisfactory. The VIS-NIR probe also showed the obtained spectra data were well correlated with nitrogen for all fields with RPD scores of 1.84 or better and coefficient of determination ($R^2$) of 0.7 or higher.

• Journal of Korean Society on Water Environment
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• v.28 no.1
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• pp.137-147
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• 2012

Land surface temperature in ecohydrology is a variable that links surface structure to soil processes and yet its spatial prediction across landscapes with variable surface structure is poorly understood. And there are an insufficient number of soil temperature monitoring stations. In this study, a grid-based land surface temperature prediction model is proposed. Target sites are Andong and Namgang dam region. The proposed model is run in the following way. At first, geo-referenced site specific air temperatures are estimated using a kriging technique from data collected from 60 point weather stations. Then surface soil temperature is computed from the estimated geo-referenced site-specific air temperature and normalized difference vegetation index. After the model is calibrated with data collected from observed remote-sensed soil temperature, a soil temperature map is prepared based on the predictions of the model for each geo-referenced site. The daily and monthly simulated soil temperature shows that the proposed model is useful for reproducing observed soil temperature. Soil temperatures at 30 and 50 cm of soil depth are also well simulated.

• Korean Journal of Environmental Agriculture
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• v.28 no.4
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• pp.365-370
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• 2009

The aim of this study was to investigate the vegetation types of Minarimot, in Jeju Islands. The vegetation types were classified by the Z-M school method and cluster analysis. The vegetation in Minarimot was classified into 6 communities and 2 subcommunities: Persicaria thunbergii-Isachne globosa community (vegetation type: A), Scirpus tribangulatus-Eleocharis manillata var. cyclocarpa community (B) (Aneilema keisak subcommunity (B-1) and Caldesia parnassifolia-Potamogeton distinctus subcommunity (B-2)), Eleocharis kuroguwai community (C), Phragmites communis community (D), Scirpus tabernaemontani community(E) and Typha orientalis community (F). These communities were grouped into three main categories according to cluster analysis. The community (A) established at the edge of the wetland which has the driest condition was distinguished as Group I, while the community (B) emerged in the submerged zone was distinguished as Group III. The Group II was designated as the communities (C, D, E, F) between Group I and III, whose communities were occasionally submerged. The result of principal coordinate analysis (PCoA) appeared that the different vegetation established along the wetland were depending on water environment such as water depth and the period submerged.

• Korean Institute of Interior Design Journal
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• v.20 no.3
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• pp.225-232
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• 2011

This study analyzed characteristics of space configuration and exhibition contents in the Neo-classism style museum while carrying out space syntax and visibility graph analysis. Therefore, this research has the purpose to survey the status of existing museum analyze their visual perception space structural characteristics and ultimately utilize their characteristics as basic data in planning out and designing space. As for the research scope, the research selected as research subject 4 Neo-classism style museum in Europe and US that composite set of room to room type and having major space. Research method is that the research analyzed the exhibition space of 4 art museums by using depth-map program which can analyze space with visual graph analysis function and analyzed the visibility among unit areas by each art museum integration and exhibition contents composition. In such analysis method, the research was able to Quantitatively analyze the visual characteristics of exhibition space that induce and adjusts the motion of audience. Visual perception quantitive analysis as in this research will enhance exhibition design by considering the correlation between audience and exhibited items when planning out art museum space to be established later on. Therefore, wien museum integration degree are high because of same openings direction and major space, Also another museums major space integrations are high level degree, and Exhibition area is set of high integration area. So, visitors can perceive exhibition contents easily.