• Journal of the Korea Convergence Society
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• v.12 no.8
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• pp.93-104
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• 2021

In the process of the sustainable development of the world economy, the change and construction of urban living environment has always been the focus of people's attention. Therefore, the purpose of this study is to find out the potential safety hazards in residential areas, and put forward feasible improvement plans under the framework of CPTED theory.One is to collect the necessary literature. Secondly, according to the field investigation and questionnaire survey, sorting out the existing security risks. Finally, this paper puts forward the corresponding improvement and suggestion to this research. The conclusion is as follows: First, based on the six principles of CPTED theory, problems existing in Gamcheon Cultural Village, which is subject to research, were investigated. Second, six of the most serious safety issues (safety handle, landscaping, entrance control, signs, empty space, monitoring) were objectively analyzed, and designs were presented in terms of increasing safety stairs, installing automatic entrances, open access view, unifying signs, and building leisure areas.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.542-558
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• 2023

A digital focus index (DFI) is a value used to determine image focus in scientific apparatus and smart devices. Automatic focus (AF) is an iterative and time-consuming procedure; however, its processing time can be reduced using a general processing unit (GPU) and a multi-core processor (MCP). In this study, parallel architectures of a minimax search algorithm (MSA) are applied to two DFIs: range algorithm (RA) and image contrast (CT). The DFIs are based on a histogram; however, the parallel computation of the histogram is conventionally inefficient because of the bank conflict in shared memory. The parallel architectures of RA and CT are constructed using parallel reduction for MSA, which is performed through parallel relative rating of the image pixel pairs and halved the rating in every step. The array size is then decreased to one, and the minimax is determined at the final reduction. Kernels for the architectures are constructed using open source software to make it relatively platform independent. The kernels are tested in a hexa-core PC and an embedded device using Lenna images of various sizes based on the resolutions of industrial cameras. The performance of the kernels for the DFIs was investigated in terms of processing speed and computational acceleration; the maximum acceleration was 32.6× in the best case and the MCP exhibited a higher performance.

• Journal of Drive and Control
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• v.20 no.2
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• pp.15-23
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• 2023

In this study, two-dimensional location of crops for auto weeding was detected using deep learning. To construct a dataset for soybean detection, an image-capturing system was developed using a mono camera and single-board computer and the system was mounted on a weeding robot to collect soybean images. A dataset was constructed by extracting RoI (region of interest) from the raw image and each sample was labeled with soybean and the background for classification learning. The deep learning model consisted of four convolutional layers and was trained with a weakly supervised learning method that can provide object localization only using image-level labeling. Localization of the soybean area can be visualized via CAM and the two-dimensional position of the soybean was estimated by clustering the pixels associated with the soybean area and transforming the pixel coordinates to world coordinates. The actual position, which is determined manually as pixel coordinates in the image was evaluated and performances were 6.6(X-axis), 5.1(Y-axis) and 1.2(X-axis), 2.2(Y-axis) for MSE and RMSE about world coordinates, respectively. From the results, we confirmed that the center position of the soybean area derived through deep learning was sufficient for use in automatic weeding systems.

• Journal of Korea Water Resources Association
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• v.45 no.5
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• pp.505-516
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• 2012

The study applies a hydrologic simulation model, HEC-1 developed by Hydrologic Engineering Center to Daecheong dam watershed for modeling hourly inflows of Daecheong dam. Although the HEC-1 model provides an automatic optimization technique for some of the parameters, the built-in optimization model is not sufficient in estimating reliable parameters. In particular, the optimization model often fails to estimate the parameters when a large number of parameters exist. In this regard, a main objective of this study is to develop Bayesian Markov Chain Monte Carlo simulation based HEC-1 model (BHEC-1). The Clark IUH method for transformation of precipitation excess to runoff and the soil conservation service runoff curve method for abstractions were used in Bayesian Monte Carlo simulation. Simulations of runoff at the Daecheong station in the HEC-1 model under Bayesian optimization scheme allow the posterior probability distributions of the hydrograph thus providing uncertainties in rainfall-runoff process. The proposed model showed a powerful performance in terms of estimating model parameters and deriving full uncertainties so that the model can be applied to various hydrologic problems such as frequency curve derivation, dam risk analysis and climate change study.

• Atmosphere
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• v.24 no.3
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• pp.433-444
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• 2014

Although the Radar-AWS Rainrate (RAR) calculation system operated by Korea Meteorological Administration estimated precipitation using 2-dimensional composite components of single polarization radars, this system has several limitations in estimating the precipitation accurately. To to overcome limitations of the RAR system, the Korea Meteorological Administration developed and operated the RMQ (Radar-based Multi-sensor Quantitative Precipitation Estimation) system, the improved version of NMQ (National Mosaic and Multi-sensor Quantitative Precipitation Estimation) system of NSSL (National Severe Storms Laboratory) for the Korean Peninsula. This study introduced the RMQ system domestically for the first time and verified the precipitation estimation performance of the RMQ system. The RMQ system consists of 4 main parts as the process of handling the single radar data, merging 3D reflectivity, QPE, and displaying result images. The first process (handling of the single radar data) has the pre-process of a radar data (transformation of data format and quality control), the production of a vertical profile of reflectivity and the correction of bright-band, and the conduction of hydrid scan reflectivity. The next process (merger of 3D reflectivity) produces the 3D composite reflectivity field after correcting the quality controlled single radar reflectivity. The QPE process classifies the precipitation types using multi-sensor information and estimates quantitative precipitation using several Z-R relationships which are proper for precipitation types. This process also corrects the precipitation using the AWS position with local gauge correction technique. The last process displays the final results transformed into images in the web-site. This study also estimated the accuracy of the RMQ system with five events in 2012 summer season and compared the results of the RAR (Radar-AWS Rainrate) and RMQ systems. The RMQ system ($2.36mm\;hr^{-1}$ in RMSE on average) is superior to the RAR system ($8.33mm\;hr^{-1}$ in RMSE) and improved by 73.25% in RMSE and 25.56% in correlation coefficient on average. The precipitation composite field images produced by the RMQ system are almost identical to the AWS (Automatic Weather Statioin) images. Therefore, the RMQ system has contributed to improve the accuracy of precipitation estimation using weather radars and operation of the RMQ system in the work field in future enables to cope with the extreme weather conditions actively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.12
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• pp.6420-6426
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• 2013

The indoor areas for the commercial use of automatic monitoring systems of mobile robot localization improves the cognitive abilities and the needs of the environment with this emerging and existing mobile robot localization, and object recognition methods commonly around its great sensor are leveraged. On the other hand, there is a difficulty with a problem-solving self-location estimation in indoor mobile robots using only the sensors of the robot. Therefore, in this paper, a self-position estimation method for an enhanced and effective mobile robot is proposed using a marker and CCTV video that is already installed in the building. In particular, after recognizing a square mobile robot and the object from the input image, and the vertices were confirmed, the feature points of the marker were found, and marker recognition was then performed. First, a self-position estimation of the mobile robot was performed according to the relationship of the image marker and a coordinate transformation was performed. In particular, the estimation was converted to an absolute coordinate value based on CCTV information, such as robots and obstacles. The study results can be used to make a convenient self-position estimation of the robot in the indoor areas to verify the self-position estimation method of the mobile robot. In addition, experimental operation was performed based on the actual robot system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.1C
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• pp.26-35
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• 2006

In this paper, an automatic mobile robot system for a intelligent path planning using the detection scheme of the spatial coordinates based on stereo camera is proposed. In the proposed system, face area of a moving person is detected from a left image among the stereo image pairs by using the YCbCr color model and its center coordinates are computed by using the centroid method and then using these data, the stereo camera embedded on the mobile robot can be controlled for tracking the moving target in real-time. Moreover, using the disparity map obtained from the left and right images captured by the tracking-controlled stereo camera system and the perspective transformation between a 3-D scene and an image plane, depth information can be detected. Finally, based-on the analysis of these calculated coordinates, a mobile robot system is derived as a intelligent path planning and a estimation. From some experiments on robot driving with 240 frames of the stereo images, it is analyzed that error ratio between the calculated and measured values of the distance between the mobile robot and the objects, and relative distance between the other objects is found to be very low value of $2.19\%$ and $1.52\%$ on average, respectably.

• The Transactions of the Korea Information Processing Society
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• v.7 no.3
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• pp.879-890
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• 2000

Designing a multilevel database application is a complex process, and the entities and their associated security levels must be represented using an appropriate model unambiguously. It is also important to capture the semantics of a multilevel databse application as accurate and complete as possible. Owing to the focus of the IDEA Methodology for designing the non-secure database applications on the data-intensive systems, the Object Model describes the static structure of the objects in an application and their relationships. That is, the Object Model in the IDEA Methodology is an extended Entity-Relationship model giving a static description of objects. The IDEA Methodology has not been developed the multilevel secure database applications, but by using an existing methodology we could take advantage of the various techniques that have already been developed for that methodology. That is, this way is easier to design the multilevel secure schema than to develop a new model from scratch. This paper adds the security features 새？ Object Model in the IDEA Methodology, and presents the transformation from this model to a multilevel secure object oriented schema. This schema will be the preliminary work which can be the general scheme for the automatic mapping to the various commercial multilevel secure database management system such as Informix-Online/Secure, Trusted ORACLE, and Sybase Secure SQL Server.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.1
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• pp.19-28
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• 2019

Images captured by drone have the advantage of quickly constructing spatial information in small areas and are applied to fields that require quick decision making. If an image registration technique that can automatically register the drone image on the ortho-image with the ground coordinate system is applied, it can be used for various analyses. In this study, a methodology for geo-referencing of a single image and sequential images using drones was proposed even if they differ in spatio-temporal resolution using linear features and distinct points. Through the method using linear features, projective transformation parameters for the initial geo-referencing between images were determined, and then finally the geo-referencing of the image was performed through the template matching for distinct points that can be extracted from the images. Experimental results showed that the accuracy of the geo-referencing was high in an area where relief displacement of the terrain was not large. On the other hand, there were some errors in the quantitative aspect of the area where the change of the terrain was large. However, it was considered that the results of geo-referencing of the sequential images could be fully utilized for the qualitative analysis.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.5
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• pp.403-412
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• 2022

As the 4th industrial revolution is in full swing and next-generation ICT(Information & Communications Technology) convergence technology is being developed, various smart construction technologies are being rapidly introduced in the construction field to respond to technological changes. In particular, since the earth-volume calculation process for site design accounts for a large part of the design cost at the construction site, related researches are being actively conducted to improve the efficiency of the process and accurately calculate the earth-volume. The purpose of this study is to present a method for quickly constructing the topography of a construction site in 3D and efficiently calculating earth-volume using the results. For this purpose, the construction site was constructed as a 3D realistic model using large-scale aerial photos obtained from UAV(Unmanned Aerial Vehicle). At this time, since the constructed 3D realistic model has a surface model structure in which volume calculation is impossible, the structure was converted into a 3D solid model to enable volume calculation. And we devised a methodology to calculate earth-volume based on CAD(Computer-Aided Design and Drafting) using the converted solid model. Automatically calculating earth-volume from the solid model by applying the method. As a result, It was possible to confirm a relative deviation of 1.52% from the calculated earth-volume from the existing survey results. In addition, as a result of comparative analysis of the process time required for each method, it was confirmed that the time required is reduced of 60%. The technique presented in this study is expected to be utilized as a technology for smart construction management, such as periodic site monitoring throughout the entire construction process, as well as cost reduction for earth-volume calculation.