• Journal of Satellite, Information and Communications
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• v.10 no.1
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• pp.56-61
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• 2015

In this paper, the 3D positioning of IoT sensors with the Unity engine of android platform based home-hub was proposde for IoT(Internet of Things) users. Especially, the monitoring of IoT sensor and battery status was designed with the clustering of IoT sensor's position. The 3D positioning of RSSI(received signal strength indicator) and angle for new IoT sensor according to clustering method was described with the cooperation of beacon and received arrival signal time. This unity engine based smart hub platform can monitor the working situation of IoT sensors, and apply 3D video with texture for the life-cycling of many IoT sensors simultaneously. rs was described with RSSI(received signal strength indicator) and received angle.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.38 no.1
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• pp.45-52
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• 2001

The proximal isovelocity surface area (PISA) method is an effective way of measuring the regurgitant blood flow rate in the mitral valve. This method defines the modelling required to describe the geometry of the isotach of the PISA. In the normal PISA flow model, the flow rate is calculated assuming that the surface of the isotach is either hemispherical or non-hemispherical numerically. However, this paper evaluated the estimate flow rate using a direct surface subdivision flow model based on the height field after isotach extraction using a region-based scheme. To validate the proposed method, the various PISA flow models were compared using pusatile color Doppler images with flow rates ranging from $30\;cm^3/sec\;to\;60\;cm^3/sec$ flow rate. Whereas the hemispherical flow model had a mean value of $29\;cm^3/sec$ and underestimated the measured flow rate by 35%, the proposed model and non-hemispherical model produced a c;ame mean value of $45\;cm^3/sec$, moreover, both flow models produced a similar pulsatile flow rate.

• The Journal of Bigdata
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• v.6 no.2
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• pp.71-84
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• 2021

Since small and medium-sized enterprises fell short of the securement of technological competitiveness in the field of big data and artificial intelligence (AI) field-core technologies of the Fourth Industrial Revolution, it is important to strengthen the competitiveness of the overall industry through technology commercialization. In this study, we aimed to propose a priority related to technology transfer and commercialization for practical use of public research results. We utilized public research performance information, improving missing values of 6T classification by deep learning model with an ensemble method. Then, we conducted topic modeling to derive the converging fields of big data and AI. We classified the technology fields into four different segments in the technology portfolio based on technology activity and technology efficiency, estimating the potential of technology commercialization for those fields. We proposed a priority of technology commercialization for 10 detailed technology fields that require long-term investment. Through systematic analysis, active utilization of technology, and efficient technology transfer and commercialization can be promoted.

• Korean Journal of Remote Sensing
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• v.36 no.3
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• pp.487-501
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• 2020

As a viable option for retrieval of LST (Land Surface Temperature), this paper presents a DNN (Deep Neural Network) based approach using 148 Landsat 8 images for South Korea. Because the brightness temperature and emissivity for the band 10 (approx. 11-㎛ wavelength) of Landsat 8 are derived by combining physics-based equations and empirical coefficients, they include uncertainties according to regional conditions such as meteorology, climate, topography, and vegetation. To overcome this, we used several land surface variables such as NDVI (Normalized Difference Vegetation Index), land cover types, topographic factors (elevation, slope, aspect, and ruggedness) as well as the T₀ calculated from the brightness temperature and emissivity. We optimized four seasonal DNN models using the input variables and in-situ observations from ASOS (Automated Synoptic Observing System) to retrieve the LST, which is an advanced approach when compared with the existing method of the bias correction using a linear equation. The validation statistics from the 1,728 matchups during 2013-2019 showed a good performance of the CC=0.910~0.917 and RMSE=3.245~3.365℃, especially for spring and fall. Also, our DNN models produced a stable LST for all types of land cover. A future work using big data from Landsat 5/7/8 with additional land surface variables will be necessary for a more reliable retrieval of LST for high-resolution satellite images.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.5
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• pp.379-387
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• 2006

The real world is spatially modelled conceptually either as discrete objects or earth surface. The generated data models are then usually represented as vector and raster respectively. Although there are limited cases where only one data model is sufficient to solve the spatial problem at hand, it is now generally accepted that GIS should be able to handle various types of data model. Recent advances in spatial technology introduced even more variety of heterogeneous data models and the need is ever growing to handle and manage efficiently these large variety of spatial data. The OGC (Open GIS Consortium), an international organization pursuing standardization in the geospatial industry. recently introduced the GMLJP2 (Geographic Mark-Up Language JP2) format which enables store and handle heterogeneous spatial data. The GMLJP2 format, which is based on the JP2 format which is an abbreviation for JPEG2000 wavelet image compression format, takes advantage of the versatility of the GML capabilities to add extra data on top of the compressed image. This study takes a close look into the GMLJP2 format to analyse and exploit its potential to handle and mange hetergeneous spatial data. Aerial image, digital map and LIDAR data were successfully transformed end archived into a single GMLJP2 file. A simple viewing program was made to view the heterogeneous spatial data from this single file.

• Journal of Advanced Navigation Technology
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• v.25 no.1
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• pp.115-123
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• 2021

Pine nuts are Korea's representative nut forest products and profitable crops. However, pine nuts are harvested by climbing the trees themselves, thus the risk is high. In order to solve this problem, it is necessary to harvest pine nuts using a robot or an unmanned aerial vehicle(UAV). In this paper, we propose a deep learning based detection method for harvesting pine nut in UAV aerial images. For this, a video was recorded in a real pine forest using UAV, and a data augmentation technique was used to supplement a small number of data. As the data for 3D detection, Unity3D was used to model the virtual pine nut and the virtual environment, and the labeling was acquired using the 3D transformation method of the coordinate system. Deep learning algorithms for detection of pine nuts distribution area and 2D and 3D detection of pine nuts objects were used DeepLabV3+, YOLOv4, and CenterNet, respectively. As a result of the experiment, the detection rate of pine nuts distribution area was 82.15%, the 2D detection rate was 86.93%, and the 3D detection rate was 59.45%.

• Journal of Korea Water Resources Association
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• v.56 no.spc1
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• pp.1027-1036
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• 2023

Coastal topographic information is crucial in coastal management, but point measurment based approeaches, which are labor intensive, are generally applied to land and underwater, separately. This study introduces an efficient method enabling land and undetwater surveys using an unmanned aerial vehicle (UAV). This method involves applying two different algorithms to measure the topography on land and water depth, respectively, using UAV imagery and merge them to reconstruct whole coastal digital elevation model. Acquisition of the landside terrain is achieved using the Structure-from-Motion Multi-View Stereo technique with spatial scan imagery. Independently, underwater bathymetry is retrieved by employing a depth inversion technique with a drone-acquired wave field video. After merging the two digital elevation models into a local coordinate, interpolation is performed for areas where terrain measurement is not feasible, ultimately obtaining a continuous nearshore terrain. We applied the proposed survey technique to Jangsa Beach, South Korea, and verified that detailed terrain characteristics, such as berm, can be measured. The proposed UAV-based survey method has significant efficiency in terms of time, cost, and safety compared to existing methods.

• Journal of the Korean Society of Radiology
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• v.11 no.5
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• pp.371-377
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• 2017

General phantom for practical X-ray photography Practical phantom is an indispensable textbook for radiology, but it is difficult for existing commercially available phantom to be equipped with various kinds of phantom because it is an expensive import. Using 3D printing technology, I would like to make the general phantom for practical X-ray photography less expensive and easier. We would like to use a skeleton model that was produced based on CT image data using a 3D printer of FDM (Fused Deposition Modeling) method as a phantom for general X-ray imaging. 3D slicer 4.7.0 program is used to convert CT DICOM image data into STL file, convert it to G-code conversion process, output it to 3D printer, and create skeleton model. The phantom of the completed phantom was photographed by X - ray and CT, and compared with actual medical images and phantoms on the market, there was a detailed difference between actual medical images and bone density, but it could be utilized as a practical phantom. 3D phonemes that can be used for general X-ray practice can be manufactured at low cost by utilizing 3D printers which are low cost and distributed and free 3D slicer program for research. According to the future diversification and research of 3D printing technology, it will be possible to apply to various fields such as health education and medical service.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.3
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• pp.37-43
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• 2009

The new still image compression standard JPEG2000 is consisted of DWT and EBCOT. In this paper, proposed and designed new algorithm in efficient EBCOT. BPC based on the contort. Proposed BPC Algorithm is forecasted coding pass using Sigstage, column, mpass value. BAC design apply 4-pipeline stage. EBCOT designed using Verilog HDL. Verification and Synthesis using Xillinx FPGA technology.

• Spatial Information Research
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• v.15 no.1
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• pp.53-65
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• 2007

Terrestrial laser scanner provides highly accurate, 3D images and by sweeping a laser beam over a scene or object, the laser scanner is able to record millions of 3D points' coordinates in a short period, so becoming distinguished in various application fields as one of the representative surveying instruments. This study deals with 3D building boundary extraction using Terrestrial Laser Scanner. The results shows that high accuracy 3D coordinates for building boundaries are possibly acquired fast, but terrestrial laser scanner is a ground-based system, so "no roofs", and "no lower part of building" due to trees and electric-poles, etc. It is expected that the combination of total station, terrestrial laser scanner, airborne laser scanner with aerial photogrammetry will contribute to the acquisition of an effective 3D spatial information.