• Journal of Environmental Impact Assessment
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• v.22 no.5
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• pp.455-466
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• 2013

The aim of this study is to seek application plans of National Ecosystem Survey database based on comparison and examination of feasible analysis methods for distribution characteristics of alien plants. In order to set up a correlation analysis method between alien plants and environmental factors, we had reviewed the 3rd National Ecosystem Survey guide book and consequently, two kinds of analysis method were tested. One was 1/25,000 scale map boundary based analysis and the other was representative mountain area based analysis. In this study we restricted the research area to select reliable surveyed database from whole "2011 National Ecosystem Survey flora database" according to two major criteria. First, an area defined by 1/25,000 scale map boundary and representative mountain area where the number of surveyed flora records should be within top 20%. Second, land cover map should also be built up inside that area. As a result, 25 map boundaries and 25 representative mountain areas were extracted to be analyzed. To limit a boundary for every representative mountain area we had analyzed distribution of environmental factors around that area by manual inspection with SPOT-5 remote sensed satellite image then designated 3km buffer zone from each alien plant location in that area. After then, naturalized index (NI) and urbanized index (UI) was calculated and correlations analysis was carried out. With the result of correlation analysis by map boundary only agricultural land area showed significant value of r (0.4~0.6, correlated) and the rest of factors did not. In the case of representative mountain area, the result showed that agricultural land, road and forest area showed significant value of r (0.6~0.8, highly correlated) which was corresponding to existing researches. Therefore, representative mountain area based method is preferable when using the alien plants database of National Ecosystem Survey for species distribution analysis. And also, considering the way of database utilization is strongly suggested at the first stage of survey planning for promoting active use of national ecosystem survey database.

• Journal of Korea Spatial Information System Society
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• v.7 no.2 s.14
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• pp.29-38
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• 2005

Even though underground conduits have became important city-infra structures which should be exhaustively and efficiently managed, there is few systems which supports the well-defined facility management standards. Due to the lack of the supporting systems, experts must visit underground conduits scattered several cities over the country to see and check the status of the underground conduits including built-in facilities. This type of management gives us a little bit delayed status information at the end of so much time and money costs. In this paper, to solve this problem and manage the conduit synthetically, we developed a web-based facility management system for underground conduits by using information technologies. The developed management system has a simplified map drawing interface to depict the overall architectures and locations of underground conduits and their built-in facilities into sketch maps. And, the system uses the 3D panorama image technology with zooming functions in addition to still images and video images to give the feeling of a spot inspection. Moreover, since the system accumulates the data of repair/reinforcement, occasional inspections and safety diagnosis, conduit managers can synthetically and effectively manage the facilities within underground conduits and themselves.

• Journal of KIISE:Software and Applications
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• v.33 no.11
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• pp.942-952
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• 2006

We propose an automatic segmentation method for identifying pulmonary structures using gray-level information of chest CT images. Our method consists of following five steps. First, to segment pulmonary structures based on the difference of gray-level value, we select the threshold using optimal thresholding. Second, we separate the thorax from the background air and then the lungs and airways from the thorax by applying the inverse operation of 2D region growing in chest CT images. To eliminate non-pulmonary structures which has similar intensities with the lungs, we use 3D connected component labeling. Third, we segment the trachea and left and right mainstem bronchi using 3D branch-based region growing in chest CT images. Fourth, we can obtain accurate lung boundaries by subtracting the result of third step from the result of second step. Finally, we select the threshold in accordance with histogram analysis and then segment radio-dense pulmonary vessels by applying gray-level thresholding to the result of the second step. To evaluate the accuracy of proposed method, we make a visual inspection of segmentation result of lungs, airways and pulmonary vessels. We compare the result of the conventional region growing with the result of proposed 3D branch-based region growing. Experimental results show that our proposed method extracts lung boundaries, airways, and pulmonary vessels automatically and accurately.

• Journal of radiological science and technology
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• v.35 no.2
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• pp.151-156
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• 2012

$^{18}F$-fluorodeoxyglucose ($^{18}F$-FDG) causes a significant amount of radioactivity retention in kidneys and urinary tract and degrades image quality and diagnostic performance. Diuretics are used to perform tests and prevent the urinary tract retention of $^{18}F$-FDG. The purpose of the study is to investigate how the diuretics affect images and excretion rates of $^{18}F$-FDG. The study consists of a group using diuretics for patients with no primary tumors or transfer lesions in kidneys according to PET/CT images, a group using physiological saline and the control group injecting only $^{18}F$-FDG and SUVs are measured by configuring interested areas for each group. Also, SUVs are compared and evaluated depending on the lasix injection after basic inspection and injecting $^{18}F$-FDG for quantitative analysis. The study shows that images with decreased background radioactivity and increased urine excretion due to using diuretics. However, an opposite result that there is no change in the amount of radioactivity in urine appears. The study concludes that the diuretics may decrease background radioactivity in the images but may not affect the $^{18}F$-FDG excretion.

• Journal of Korean Society of Transportation
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• v.23 no.1
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• pp.45-54
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• 2005

The main purpose of this study is located at developing Ominibus Monitoring System(OMS) for the purpose of the internal management, which enable to establish job standards, find out matters to be improved, and appreciate for its treatment in a systematic way. It is through developing subjective or objective estimation tool with use of importance, perceived level, and complex index at international airport by each principal service items, The direction of this study came towards for the purpose of developing a metric analysis tool, utilizing the Quantitative Secondary Data, Analysing Perceived Data through airport user surveys, systemizing the data collection-input-analysis process, making data image according to the graph of results, planning service encounter and endowing control attribution, and ensuring competitiveness at the minimal international standards. It is much important to set up a pre-investigation plan on the base of existent foreign literature and actual inspection to international airport. Two tasks have been executed together on the base of this pre-investigation; one is developing subjective estimation standards for departing party, entering party, and airport residence and the other is developing objective standards as complementary methods. The study has processed for the monitoring services at airports regularly and irregularly through developing software system for operating standards after ensuring credibility and feasibility of estimation standards with substantial and statistical way.

• 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 the Korea Society of Computer and Information
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• v.28 no.4
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• pp.105-112
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• 2023

In this paper, we propose a new method for displaying colored defects by measuring the relative density with the wide-area and local densities of X-ray. The relative density of one pixel represents a relative difference from the surrounding pixels, and we also suggest a colorization of X-ray images representing these pixels as normal and defective. The traditional method mainly inspects materials such as plastics and metals, which have large differences in transmittance to the object. Our proposed method can be used to detect defects such as sprouts or holes in images obtained by an inspection machine that detects X-rays. In the experiment, the products that could not be seen with the naked eye were colored with pests or sprouts in a specific color so that they could be used in the agricultural product selection system. Products that are uniformly filled with a single ingredient inside, such as potatoes, carrots, and apples, can be detected effectively. However, it does not work well with bumpy products, such as peppers and paprika. The advantage of this method is that, unlike machine learning, it doesn't require large amounts of data. The proposed method could be applied to a screening system using X-rays and used not only in agricultural product screening systems but also in manufacturing processes such as processed food and parts manufacturing, so that it can be actively used to select defective products.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.27-35
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• 2023

In this paper, we propose a process of increasing productivity by applying a deep learning-based defect detection and classification system to the prepreg fiber manufacturing process, which is in high demand in the field of producing composite materials. In order to apply it to toe prepreg manufacturing equipment that requires a solution due to the occurrence of a large amount of defects in various conditions, the optimal environment was first established by selecting cameras and lights necessary for defect detection and classification model production. In addition, data necessary for the production of multiple classification models were collected and labeled according to normal and defective conditions. The multi-classification model is made based on CNN and applies pre-learning models such as VGGNet, MobileNet, ResNet, etc. to compare performance and identify improvement directions with accuracy and loss graphs. Data augmentation and dropout techniques were applied to identify and improve overfitting problems as major problems. In order to evaluate the performance of the model, a performance evaluation was conducted using the confusion matrix as a performance indicator, and the performance of more than 99% was confirmed. In addition, it checks the classification results for images acquired in real time by applying them to the actual process to check whether the discrimination values are accurately derived.

• Tunnel and Underground Space
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• v.34 no.1
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• pp.1-14
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• 2024

An image-reconstruction technology, involving the deployment of an unmanned mobility equipped with high-speed LiDAR (Light Detection And Ranging) has been proposed to reconstruct the shape of abandoned mine. Unmanned mobility operation is remarkably useful in abandoned mines fraught with operational difficulties including, but not limited to, obstacles, sludge, underwater and narrow tunnel with the diameter of 1.5 m or more. For cases of real abandoned mines, quadruped robots, quadcopter drones and underwater drones are respectively deployed on land, air, and water-filled sites. In addition to the advantage of scanning the abandoned mines with 2D solid-state lidar sensors, rotation of radiation at an inclination angle offers an increased efficiency for simultaneous reconstruction of mineshaft shapes and detecting obstacles. Sensor and robot posture were used for computing rotation matrices that helped compute geographical coordinates of the solid-state lidar data. Next, the quadruped robot scanned the actual site to reconstruct tunnel shape. Lastly, the optimal elements necessary to increase utility in actual fields were found and proposed.

• Journal of the Korean Society of Radiology
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• v.5 no.5
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• pp.295-302
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• 2011

To n the field of nuclear medicine, with regard to checking regular patients, from the moment they register up to the doctor's diagnosis, the person in charge of the checks can find errors in the diagnosis, reexamine, reanalyze the results or save images to PACS. Through this process, the results obtained from the readings are delayed due to checks and additional tests which occur in hospitals, causing patient satisfaction and affected reliability. Accordingly, the purpose is to include visual inspection of the results to minimize error, improve efficiency and increase patient satisfaction. Nuclear medicine and imaging tests from examines at Asan Medical Center, Seoul, from March 2008 to December 2008, were analyzed for errors. The first stage, from January 2009 to December 2009, established procedures and know-how. The second stage from January 2010 until June 2010 conducted Pre-and Post-filtering assessment, and the third stage from July 2010 until October 2010 consisted of cross-checks and attaching stickers and comparing error cases. Of 92 errors, the 1st, 2nd and 3rd stage had 32 cases, and there were 46 cases after the 4th stage, with the overall errors reduced by 74.3% from 94.6%. In the field of general nuclear medicine, where various kinds of checks are performed according to the patient's needs, analysis, image composition, differing images in PACS, etc, all have the potential for mistakes to be made. In order to decrease error rates, the image can continuously Cross-Check and Confirm diagnosis.