• Journal of the Korea Society of Computer and Information
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• v.18 no.10
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• pp.109-119
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• 2013

An unmanned ground vehicle(UGV) today plays a significant role in both civilian and military areas. Predominantly these systems are used to replace humans in hazardous situations. To take unmanned ground vehicles systems to the next level and increase their capabilities and the range of missions they are able to perform in the combat field, new technologies are needed in the area of command and control. For this reason, we present war field simulator based on information fusion technology to efficiently control UGV. In this paper, we present the war field simulator which is made of critical components, that is, simulation controller, virtual image viewer, and remote control device to efficiently control UGV in the future combat fields. In our information fusion technology, improved methods of target detection, recognition, and location are proposed. In addition, time reduction method of target detection is also proposed. In the consequence of the operation test, we expect that our war field simulator based on information fusion technology plays an important role in the future military operation significantly.

• Journal of the Korean Geophysical Society
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• v.2 no.1
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• pp.75-88
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• 1999

A recent major subject of geophysical exploration is research into 3-D subsurface imaging with a composite information from the various geophysical data. In an attempt to interpret Schlumberger sounding data for the study area in 2-D and 3-D view, resistivity imaging was firstly performed and then pseudo-3-D resistivity volume was reconstructed by interpolating several 1-D resistivity plots. Electrical resistivity discontinuities such as fracture zone were successfully clarified in pseudo-3-D resistivity volume. The low resistivity zone mainly associated with fracture zone appears to develop down to granitic basement in the central part of the study area. Seismic velocity near the lineament is estimated to be approximately as small as 3,000 m/s, and weathering-layer for the southeastern part is interpreted to be deeper than for the northwestern part. Geophysical attributes such as electrical resistivity, seismic velocity, radioactivity for the Chojeong Area were analysed by utilizing a GIS software Arc/Info. The major fault boundaries and fracture zones were resolved through image enhancement of composite section (electrical resistivity and seismic refraction data) and were interpreted to develop in the southeastern part of the area, as characterized by low electrical resistivity and low seismic velocity. However, radioactivity attribute was found to be less sensitive to geological discontinuities, compared to resistivity and seismic velocity attributes.

• Journal of the Korean Vacuum Society
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• v.19 no.2
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• pp.128-133
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• 2010

ZnO:Al films were deposited by DC-pulsed magnetron sputtering using a two-step process involving the control of the oxygen pressure. The seed layers were prepared with various Ar to oxygen flow ratios and the bulk layers were deposited under pure Ar. As the oxygen pressure during the deposition of the seed layer increased, the crystallinity and degree of (002) texturing increased. The resistivity gradually decreased with increasing crystallinity from $4.7\times10^4\Omega{\cdot}cm$ (no seed) to $3.7\times10^4\Omega{\cdot}cm$ (Ar/$O_2$ = 9/1). The etched surface showed a crater-like structure and an abrupt morphology change appeared as the crystallinity was increased. The sample deposited at an Ar/$O_2$ flow ratio of 9/1 showed a very high haze value of 88% at 500 nm, which was explained by the large feature size of the craters, as shown in the AFM image.

• Journal of radiological science and technology
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• v.40 no.4
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• pp.589-594
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• 2017

The objective of this study was to evaluate the enhancement effects of the quantum denoising system (QDS) on brain CT images. This retrospective study was conducted with 45 adults who visited G Radiology located in Gyungbuk for having brain CT tests between Jul 2017 and Oct 2017 after receiving consents. Subjects were divided into a control group (A group; no QDS(-) application during the brain CT test) and a treatment group (B Group; QDS(+) application during the brain CT test). The following conclusions were obtained from the study. The noise values at the Pons part and the Vermis part were significantly (p<0.05) lower in B Group ($Pons=5.41{\pm}1.05HU$; $Vermis=5.28{\pm}0.73HU$) than A Group ($Pons=6.92{\pm}0.98HU$; Vermis=6.72). The SNR values at the Pons part and the Vermis part were significantly (p<0.05) higher in B Group ($Pons=7.28{\pm}2.56$; $Vermis=8.63{\pm}3.04$) than A Group ($Pons=5.21{\pm}1.28$; $Vermis=6.23{\pm}1.49$). In conclusion, the results of this study suggested that the application of QDS to the brain CT test would enhance the signal to noise ratio (SNR) and the contrast to noise ratio (CNR) to provide an image more appropriate for diagnosis.

• Korean Journal of Heritage: History & Science
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• v.46 no.3
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• pp.78-93
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• 2013

The purpose of this study is to analyze college students' perception of national natural heritages, including natural monumentsand scenic sites, in comparison with the similar concepts of national parks and eco-landscape preservation areas, to suggest managerial implications to enhance competitiveness. The first objective of this study is to measure their attitude toward traveling each type of natural heritage and to rate the relative importance of the four types of heritages in terms of preservation. Natural monuments were perceived as the most strongly preserved type, while scenic sites were perceived as the least strongly preserved type. The second objective is to conduct a correspondence analysis to match the concepts of four types of natural heritages with 10 tourist attractions representing the types. It was found that college students have difficulty appropriately identifying the types of 10 tourist attractions. In addition, multi-dimensional scaling (MDS) was implemented to identify the similarities and differences of the four types of natural heritages and to produce a positioning map matching the four types of natural heritages with the six attributes representing each type as a tourist attraction. Natural monuments were perceived very differently from scenic sites and not very differently from eco-landscape preservation areas. There were a few associations between the four types of natural heritages and the six tourism attributes, implying that little effort is made to promote and position each type of natural heritage in terms of tourism. In conclusion, a public awareness program is required to enhance the brand image of natural monuments and scenic sites in comparison to national parks and eco-landscape preservation areas. In addition, local residents who live near the natural heritages should be bolstered to play a managerial role as supporters and contents providers for sustainability.

• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.3
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• pp.419-432
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• 2019

Most of deep learning model training was proceeded by supervised learning, which is to train labeling data composed by inputs and corresponding outputs. Labeling data was directly generated manually, so labeling accuracy of data is relatively high. However, it requires heavy efforts in securing data because of cost and time. Additionally, the main goal of supervised learning is to improve detection performance for 'True Positive' data but not to reduce occurrence of 'False Positive' data. In this paper, the occurrence of unpredictable 'False Positive' appears by trained modes with labeling data and 'True Positive' data in monitoring of deep learning-based CCTV accident detection system, which is under operation at a tunnel monitoring center. Those types of 'False Positive' to 'fire' or 'person' objects were frequently taking place for lights of working vehicle, reflecting sunlight at tunnel entrance, long black feature which occurs to the part of lane or car, etc. To solve this problem, a deep learning model was developed by simultaneously training the 'False Positive' data generated in the field and the labeling data. As a result, in comparison with the model that was trained only by the existing labeling data, the re-inference performance with respect to the labeling data was improved. In addition, re-inference of the 'False Positive' data shows that the number of 'False Positive' for the persons were more reduced in case of training model including many 'False Positive' data. By training of the 'False Positive' data, the capability of field application of the deep learning model was improved automatically.

• Journal of the Korean Society of Radiology
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• v.16 no.5
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• pp.537-543
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• 2022

The purpose of this simulation study was to evaluate the possibility of pancreas detection through effective atomic number information using dual-energy computed tomography(CT). The effective atomic number of 10 tissue-equivalent materials were estimated through stoichiometric calibration. For stoichiometric calibration, HU values at low-energy (80 kV) and high-energy (140 kV) for 10 tissue-equivalent materials were used. Based on this method, the effective atomic number image of the tissue-equivalent material was extracted through an iterative algorithm. According to the results, the attenuation ratio in accordance with the effective atomic number was estimated to have an R² value of 0.9999, and the effective atomic number of Pancreas, Water, Liver, Blood, Spongiosa, and Cortical bone was overall within 1% accuracy compared to the theoretical value. Conventional pancreatic cancer examination uses a contrast medium, so there is a possibility of potential side effects of the contrast medium. In order to solve this problem, it is thought that it will be possible to contribute to an accurate and safe examination by extracting the effective atomic number using dual-energy CT without contrast enhancement. Based on this study, future research will be conducted on the detection of pancreatic cancer using the HU value of pancreatic cancer based on clinical images.

• Land and Housing Review
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• v.14 no.1
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• pp.83-97
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• 2023

The study aims to provide an academic basis for the preservation and restoration of abandoned paddy wetland and the enhancement of its carbon accumulation function. First, the temporal change of the wetlands was analysed, and a typological classification system for wetlands was attempted with the goal of carbon reduction. The types of wetland were classified based on three variables: hydrological environment, vegetation, and carbon accumulation, with a special attention on the function of carbon accumulation. The types of abandoned paddy wetlands were classified into 12 categories based on hydrologic variables- either high or low levels of water inflow potential-, vegetation variables with either dominance of aquatic plants or terrestrial plants, and three carbon accumulation variables including organic matter production, soil organic carbon accumulation, and decomposition. It was found that the development period of abandoned paddy analyzed with aerial photographs provided by the National Geographic Information Institute happened between 2010 and 2015. In the case of the wetland in Daejeon 1 (DJMN01) farming stopped by 1990 and it appeared to be a similar structure to natural wetlands after 2010 . Over the past 40 years the abandoned paddy wetland changed to a high proportion of forests and agricultural lands. As time went by, such forests and agricultural lands tended to decrease rapidly and the lands were covered by artificial grass and other types of forests.

• Journal of the Korean Society for information Management
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• v.39 no.3
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• pp.165-193
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• 2022

It can be said that digital technology is at the center of the change in the modern work environment. In particular, in general public institutions that prove their work with records produced by business management systems and document production systems, the record management system is also the work environment itself. Gimpo City applied for the 2021 public cloud leading project of the National Information Society Agency (NIA) to proactively respond to the 4th industrial revolution technology era and implemented a public cloud-based AI-OCR technology enhancement project with 330 million won in support of 330 million won. Through this, it was converted into data beyond the limitations of non-electronic records limited to search and image viewing that depend on standardized index values. In addition, a 98% recognition rate was realized by applying a new technology called AI-OCR. Since digital technology has been used to improve work efficiency, productivity, development cost, and record management service levels of internal and external users, we would like to share the direction of enhancing expertise in the record management and implementation of work environment innovation.

• 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.