• Korean Journal of Agricultural and Forest Meteorology
• /
• v.18 no.4
• /
• pp.208-220
• /
• 2016

Automatic Mountain Meteorology Observation System (AMOS) is an important ingredient for several climatological and forest disaster prediction studies. In this study, we select the optimal sites for AMOS in the mountain areas of Honam and Jeju in order to prevent forest disasters such as forest fires and landslides. So, this study used spatial dataset such as national forest map, forest roads, hiking trails and 30m DEM(Digital Elevation Model) as well as forest risk map(forest fire and landslide), national AWS information to extract optimal site selection of AMOS. Technical methods for optimal site selection of the AMOS was the firstly used multifractal model, IDW interpolation, spatial redundancy for 2.5km AWS buffering analysis, and 200m buffering analysis by using ArcGIS. Secondly, optimal sites selected by spatial analysis were estimated site accessibility, observatory environment of solar power and wireless communication through field survey. The threshold score for the final selection of the sites have to be higher than 70 points in the field assessment. In the result, a total of 159 polygons in national forest map were extracted by the spatial analysis and a total of 64 secondary candidate sites were selected for the ridge and the top of the area using Google Earth. Finally, a total of 26 optimal sites were selected by quantitative assessment based on field survey. Our selection criteria will serve for the establishment of the AMOS network for the best observations of weather conditions in the national forests. The effective observation network may enhance the mountain weather observations, which leads to accurate prediction of forest disasters.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.40 no.1
• /
• pp.1-14
• /
• 2022

In order to conduct rapid, accurate and safe surveying at the excavation site, In this study, the possibility of underground facility survey using drones and the expected effect of 3D visualization were obtained as follows. Phantom4Pro 20MP drones have a 30m flight altitude and a redundant 85% flight plan, securing a GSD (Ground Sampling Distance) value of 0.85mm and 4points of GCP (Groud Control Point)and 2points of check point were calculated, and 7.3mm of ground control point and 11mm of check point were obtained. The importance of GCP was confirmed when measured with low-cost drones. If there is no ground reference point, the error range of X value is derived from -81.2 cm to +90.0 cm, and the error range of Y value is +6.8 cm to 155.9 cm. This study classifies point cloud data using the Pix4D program. I'm sorting underground facility data and road pavement data, and visualized 3D data of road and underground facilities of actual model through overlapping process. Overlaid point cloud data can be used to check the location and depth of the place you want through the Open Source program CloudCompare. This study will become a new paradigm of underground facility surveying.

• Journal of Korea Port Economic Association
• /
• v.39 no.4
• /
• pp.295-308
• /
• 2023

Busan Port, as Korea's representative trading port, handles a variety of port cargo from bulk cargo to container cargo. Busan Port is currently functioning as a container specialized port for North Port and Busan New Port, and Gamcheon Port is also handling container cargo mainly in bulk cargo. This study intends to examine the overlapping cargoes and specialized cargoes between these ports and Busan Port as the amount of import and export cargoes in ports designated as trade ports in Korea is increasing. In order to understand the characteristics of the major cargoes handled in the port, the quantitative change is confirmed through the total cargo volume of major domestic ports and the trend of changes in import/export cargo between Busan Port and major ports is analyzed. There are many specialized investigation methods, but as the most basic method, we will examine quantitative changes and causes by simply examining the data for 10 years as the amount of change by cargo. In addition, the causes of these fluctuations should be reclassified into domestic and foreign causes by identifying changes in customers in different ports and shipping volumes, changes in consumption areas, and transshipment volumes. Through the analysis of the major cargo volume of each port, the characteristics and fluctuation trends of major cargo handled in Busan Port and other ports are identified, and the competitive cargoes of each port are verified. Through this, the characteristics and competitiveness of the port are inferred, and implications for the cargo volume of Busan Port and future countermeasures are suggested.

• Spatial Information Research
• /
• v.9 no.1
• /
• pp.107-124
• /
• 2001

The purpose of this research is to develop system and to establish methodology for managing spatial Database in Land Management Information System(LMIS). Spatial Database which is used by a various public department such as parcel survey and registry, land use planning and Land value appraisal in local government, is composed of parcel map, topographic map and zoning map. Spatial data has been constructed and managed by various department and then hard to maintain accuracy and coinsistency. So, it is important to establish the basic data management concept that source data(ex : parcel map, topographic map, zoning map, etc.) should be managed by responsible department. at the same time, application data for bussiness (ex : individual parcel price map) must be recomposed from base map by it's own objects. This is, Spatial data management system (SDMS) should be designed, developed according to this concept for managing consistency among data, reducing construction and management cost of database. Our SDMS was developed based on Open LMIS middleware architecture using OpenGIS CORBA specification for standard interface, RUP(Rational Unified Process) for development methodology, UML(Unified Modeling Language) for system design and VisiBroker, C++, CAD system for system implementation.

• Journal of Broadcast Engineering
• /
• v.20 no.5
• /
• pp.687-696
• /
• 2015

JCT-VC (Joint Collaborative Team on Video Coding) continues developing HEVC/Screen Content Coding (HEVC/SCC) as an extension for efficiently coding screen content videos, including computer animations, graphics, and electrical documents, based on HEVC/Range extension (HEVC/RExt.). Color space conversion from RGB space being captured from CCD sensors is popular in natural video coding. However, the conversion is often undesired for screen contents because of a significant loss in perceptual quality. Therefore, several coding tools including cross-component prediction (CCP) and in-loop adaptive color space transform (ACST) have been developed for an efficient screen content video coding in order to reduce the redundancies between color spaces while maintaining the original color space. In this paper, we review the two coding tools, i.e., CCP and ACST exploiting the correlation in the RGB color space and conduct the performance analysis of the coding tools. In our simulation results, CCP and ACST provide 11.7% BD-rate saving and 16.4% BD-rate saving, respectively, while the two coding tools provide 18.2% BD-rate saving in total. Following this idea, if the two coding tools are exclusively selected, we provide 93% encoding measurement time with a 0.3% coding loss.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.20 no.2
• /
• pp.165-172
• /
• 2010

In clinical data minig, choosing the optimal subset of features is such important, not only to reduce the computational complexity but also to improve the usefulness of the model constructed from the given data. Moreover the threshold values (i.e., cut-off points) of selected features are used in a clinical decision criteria of experts for differential diagnosis of diseases. In this paper, we propose a fuzzy discretization approach, which is evaluated by measuring the degree of separation of redundant attribute values in overlapping region, based on spatial distribution of data with continuous attributes. The weighted average of the redundant attribute values is then used to determine the threshold value for each feature and rough set theory is utilized to select a subset of relevant features from the overall features. To verify the validity of the proposed method, we compared experimental results, which applied to classification problem using 668 patients with a chief complaint of dyspnea, based on three discretization methods (i.e., equal-width, equal-frequency, and entropy-based) and proposed discretization method. From the experimental results, we confirm that the discretization methods with fuzzy partition give better results in two evaluation measures, average classification accuracy and G-mean, than those with hard partition.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.25 no.8A
• /
• pp.1096-1103
• /
• 2000

The default server strategy is commonly used for location and state managements of mobile host in mobile computing. With this strategy, we can find the cell of destination mobile host to send data by querying the default server. In SDN(single Default Notification) strategy which is a kind of default server strategy, the call is established after the location and state of the callee is acquired to the query server by querying the default server. But the communication cost overhead from the default server is increased if there are large number of cells and query requests, and if it is too far from the default server to a base station. Still more it will be unable to establish any calls to a mobile host when there is a fault in the default server of this host. In this paper, we suggest add evaluate a default server replication strategy to reduce the communication cost overhead and to make the service available.

• Journal of Korea Multimedia Society
• /
• v.2 no.1
• /
• pp.38-46
• /
• 1999

In this paper, the fractal image compression using the minimizing method of domain region is proposed. It is minimize to domain regions in the process of decoding. Since the conventional fractal decoding applies to IFS(iterative function system) for the total range blocks of the decoded image, its computational complexity is a vast amount. In order to improve this using the number of the referenced times to the domain blocks for the each range blocks, a classification method which divides necessary and unnecessary regions for IFS is suggested. If necessary regions for IFS are reduced, the computational complexity is reduced. The proposed method is to define the minimum domain region that a necessary region for IFS is minimized in the encoding algorithms. That is, a searched region of the domain is limited to the range regions that is similar with the domain regions. So, the domain region is more overlapped. Therefore, there is not influence on image quality or PSNR(peak signal-to-noise ratio). And it can be a fast decoding by reduce the computational complexity for IFS in fractal image decoding.

• Journal of IKEEE
• /
• v.21 no.2
• /
• pp.146-149
• /
• 2017

In this paper, we propose a wide-range radiation measurement system using GM Tube and NaI(TI) detector. The proposed system is designed as a small module optimized to control and count the detector signal of NaI(Tl) Detector and GM Tube. The radiation dose is measured in a wide-range 0.1uSv/h to 10mSv/h in conjunction with two detectors, and two detectors operate simultaneously at 10uSv/h to 100uSv/h, where the measurement interval overlaps. The radiation dose was selected using a wide-range radiation measurement algorithm that controls the on/off function of the detector in the appropriate interval for the overlapped radiation measurable interval. In order to evaluate the performance of the proposed system, it has been confirmed that the measurement uncertainty of each section is measured as ${\pm}7.5%$ and it operates normally under ${\pm}15%$ of the international standard.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.12 no.3
• /
• pp.29-35
• /
• 2012

In this paper, it is presented the method of image recovering which existing is only pixel processing, but suggesting method is concluding image clustering overlap degree after classfying around unit fixel to crowd pixel. Concluding overlap degree threshold value is after identifying pattern pixel and grasping geometry structure of sample pattern and deduction of deciding function. distinguishing feature space is above four dimension is reason of not visual observation of pattern structure. consideration of distribution structure is distance of center of crowd pixel, the number of each crowd pattern pixel and standard deviation. The over threshold value elimate the overlap image and the downward is recovered and established dynamic image. memory storage deduction of 20% and elevation of 15% performance is estimated in recovery of image.