• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.5
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• pp.417-428
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• 2017

In this paper, we describe the architectural design, unit component hardware design and core software design(Helmet Pose Tracking Software and Terrain Elevation Data Correction Software) of IHDS(Intelligent Helmet Display System), and describe the results of unit test and integration test. According to the trend of the latest helmet display system, the specifications which includes 3D map display, FLIR(Forward Looking Infra-Red) display, hybrid helmet pose tracking, visor reflection type of binocular optical system, NVC(Night Vision Camera) display, lightweight composite helmet shell were applied to the design. Especially, we proposed unique design concepts such as the automatic correction of altitude error of 3D map data, high precision image registration, multi-color lighting optical system, transmissive image emitting surface using diffraction optical element, tracking camera minimizing latency time of helmet pose estimation and air pockets for helmet fixation on head. After completing the prototype of all system components, unit tests and system integration tests were performed to verify the functions and performance.

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.172-178
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• 2023

In this paper, performance of autoencoder based OFDM communication systems is compared with IEEE 802.11a Wireless Lan System (Wi-Fi). The proposed autoencoder based OFDM system is composed of the following steps. First, one sub-carrier's transmitter - channel - receiver system is created by autoencoder. Then learning process of the one sub-carrier autoencoder generates constellation map. Secondly, using the plural sub-carrier autoencoder systems, parallel bundle is configured with inserting IFFT and FFT before and after the channel to configure OFDM system. Finally, the receiver part of the OFDM communication system was updated by re-learning process for adapting channel condition such as multipath channel. For performance comparison, IEEE802.11a and the proposed autoencoder based OFDM system are compared. For channel estimation, Wi-Fi uses initial long preamble to measure channel condition. but Autoencoder needs re-learning process to create an equalizer which compensate a distortion caused by the transmission channel. Therefore, this autoencoder based system has basic advantage to the Wi-Fi system. For the comparison of the system, additive random noise and 2-wave and 4-wave multipaths are assumed in the transmission path with no inter-symbol interference. A simulation was performed to compare the conventional type and the autoencoder. As a result of the simulation, the autoencoder properly generated automatic constellations with QPSK, 16QAM, and 64QAM. In the previous simulation, the received data was relearned, thus the performance was poor, but the performance improved by making the initial value of reception a random number. A function equivalent to an equalizer for multipath channels has been realized in OFDM systems. As a future task, there is not include error correction at this time, we plan to make further improvements by incorporating error correction in the future.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.5
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• pp.1027-1034
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• 2024

This study aims to address the issues of outliers and missing values in AI-based smart farming to improve data quality and enhance the accuracy of agricultural predictive activities. By utilizing real data provided by the Rural Development Administration (RDA) and the Korea Agency of Education, Promotion, and Information Service in Food, Agriculture, Forestry, and Fisheries (EPIS), outlier detection and missing value imputation techniques were applied to collect and manage high-quality data. For successful smart farm operations, an IoT-based AI automatic growth measurement model is essential, and achieving a high data quality index through stable data preprocessing is crucial. In this study, various methods for correcting outliers and imputing missing values in growth data were applied, and the proposed preprocessing strategies were validated using machine learning performance evaluation indices. The results showed significant improvements in model performance, with high predictive accuracy observed in key evaluation metrics such as ROC and AUC.

• The Korean Journal of Nuclear Medicine Technology
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• v.17 no.2
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• pp.78-83
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• 2013

Purpose: SPECT/CT, a combination of SPECT and CT, is capable of expressing the results of attenuation correction on images biased by automatic program. As a result, this research evaluates the usefulness of images with CT attenuation correction, using various phantoms and images of patients. Materials and Methods: From July of 2012 to September of 2012, this research was conducted on the contrast, spatial resolution, and images of patients. We studied the contrast with IEC body phantom and Jaszczak phantom, while the spatial resolution was evaluated with NEMA triple line phantom. Further, a comparative study was carried out on the quality of the images, on the difference between the images before and after the CT attenuation correction. Results: Compared the differences between the contrast before and after the CT attenuation correction in IEC body phantom. The contrast was improved by 33.6% at minimum, 89.8% at maximum. In case of Jaszczak Phantom, the contrast was enhanced by 9.9% at minimum, 27.8% at maximum. In NEMA Triple line phantom, the resolution was raised by 4.5% in average: 4.4% in horizontal, 4.5% in vertical. In Anthropomorphic Torso Phantom, the perfusion score of the interior wall with the most severe attenuation was measured to be 29.4%. In the experiment carried out on myocardial perfusion SPECT/CT patients, 9% improvement was discovered in the interior wall, where the most dramatic attenuation occurred, after the CT attenuation correction. Conclusion: SPECT/CT proved its clinical usefulness by enabling the acquisition of images with enhanced contrast and spatial resolution compare to the ones resulted from SPECT.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1135-1147
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• 2021

In order to geometrically correct high-resolution satellite imagery, the sensor modeling process that restores the geometric relationship between the satellite sensor and the ground surface at the image acquisition time is required. In general, high-resolution satellites provide RPC (Rational Polynomial Coefficient) information, but the vendor-provided RPC includes geometric distortion caused by the position and orientation of the satellite sensor. GCP (Ground Control Point) is generally used to correct the RPC errors. The representative method of acquiring GCP is field survey to obtain accurate ground coordinates. However, it is difficult to find the GCP in the satellite image due to the quality of the image, land cover change, relief displacement, etc. By using image maps acquired from various sensors as reference data, it is possible to automate the collection of GCP through the image matching algorithm. In this study, the RPC of KOMPSAT-3A satellite image was corrected through the extracted matching point using the UAV (Unmanned Aerial Vehichle) imagery. We propose a pre-porocessing method for the extraction of matching points between the UAV imagery and KOMPSAT-3A satellite image. To this end, the characteristics of matching points extracted by independently applying the SURF (Speeded-Up Robust Features) and the phase correlation, which are representative feature-based matching method and area-based matching method, respectively, were compared. The RPC adjustment parameters were calculated using the matching points extracted through each algorithm. In order to verify the performance and usability of the proposed method, it was compared with the GCP-based RPC correction result. The GCP-based method showed an improvement of correction accuracy by 2.14 pixels for the sample and 5.43 pixelsfor the line compared to the vendor-provided RPC. In the proposed method using SURF and phase correlation methods, the accuracy of sample was improved by 0.83 pixels and 1.49 pixels, and that of line wasimproved by 4.81 pixels and 5.19 pixels, respectively, compared to the vendor-provided RPC. Through the experimental results, the proposed method using the UAV imagery presented the possibility as an alternative to the GCP-based method for the RPC correction.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.449-461
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• 2021

Analysis Ready Data (ARD) for optical satellite images represents a pre-processed product by applying spectral characteristics and viewing parameters for each sensor. The atmospheric correction is one of the fundamental and complicated topics, which helps to produce Top-of-Atmosphere (TOA) and Top-of-Canopy (TOC) reflectance from multi-spectral image sets. Most remote sensing software provides algorithms or processing schemes dedicated to those corrections of the Landsat-8 OLI sensors. Furthermore, Google Earth Engine (GEE), provides direct access to Landsat reflectance products, USGS-based ARD (USGS-ARD), on the cloud environment. We implemented the Orfeo ToolBox (OTB) atmospheric correction extension, an open-source remote sensing software for manipulating and analyzing high-resolution satellite images. This is the first tool because OTB has not provided calibration modules for any Landsat sensors. Using this extension software, we conducted the absolute atmospheric correction on the Landsat-8 OLI images of Railroad Valley, United States (RVUS) to validate their reflectance products using reflectance data sets of RVUS in the RadCalNet portal. The results showed that the reflectance products using the OTB extension for Landsat revealed a difference by less than 5% compared to RadCalNet RVUS data. In addition, we performed a comparative analysis with reflectance products obtained from other open-source tools such as a QGIS semi-automatic classification plugin and SAGA, besides USGS-ARD products. The reflectance products by the OTB extension showed a high consistency to those of USGS-ARD within the acceptable level in the measurement data range of the RadCalNet RVUS, compared to those of the other two open-source tools. In this study, the verification of the atmospheric calibration processor in OTB extension was carried out, and it proved the application possibility for other satellite sensors in the Compact Advanced Satellite (CAS)-500 or new optical satellites.

• Journal of Advanced Navigation Technology
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• v.19 no.6
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• pp.465-472
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• 2015

In order to improve the performance of TCAS it should improve the performance of the sensor, which transmits a variety of information. In this paper, To improve the performance of the existing radar sensors such as being used in behalf of the next generation air traffic control system, ads-b the applied. In addition, ADS-B in a high precision by using information from the correction GPS system, SBAS assume would be able to apply an improved location accuracy for TCAS and analyzed TCAS and ADS-B. Played the simulation results, TCAS equipment receives the help of these ADS-B can calculate a CPA to determine the position of the aircraft in advance, and it was confirmed that it is possible to reduce the unnecessary RA operation, also, the pilot reduction and the workload, it has advantages such as fuel consumption and time associated with the reduced operation unnecessary RA was confirmed.

• The Transactions of the Korea Information Processing Society
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• v.7 no.7
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• pp.2149-2160
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• 2000

Recently many efforts on the development of automatic processing system for delivery sequence sorting have been performed in ETRI, which requires the use of postal4-state bar code system to encode delivery points. The 4-state bar code called postal 4-state barcode for high speed processing that has been specifically designed for information processing of logistics and automatic processing of he mail items. The Information of 4-state bar code indicates mail data such as post code, delivery sequence number, error correction code worked, customer information, and a unique ID. This appear addresses the issue on he reduction of reading error in postal 4-state raster beam based bar code reader. The raster beam scanning features are the unequally distributed number of spots per each unit, which cause reading errors. We propose a method for reducing the bar code reading error by adjusting measured values of bar code width to its average value over each interval. The test results show that the above method reduces the average reading error rate approximately by 99.88%.

• Proceedings of the KWS Conference
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• 2010.05a
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• pp.60-60
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• 2010

Since the curved hull plate was made by a series of manufacturing process including cold bending, manual local heating and correction work, the accuracy of curved plate strongly depends on the proficiency of worker. So the demands on the automatic local heating system for curved hull plate have continuously increased and the various researches relevant to it have been performed. Generally, the heat sources used for local heating were flame and induction heat. In terms of initial cost, flame heating is in a better favorable position than induction heating. However, from the viewpoint of the control of heat, induction heating has more advantage. So the various researches related to apply the induction heating to the automatic forming system has been performed. The purpose of this study is to establish the proper capacity of high frequency induction heating system for forming the curved hull plate. In order to do it, the proper coil shape for local heating was designed and the efficiency of induction heating system was determined by comparing of temperature results obtained by FEA and experiment. With the results, the extensive FEA was performed to identify the effect of heated plate dimension, cooling method and the capacity of induction heating system on the amount of heat loss introduced by induction heating. Based on the results, the proper capacity of high frequency induction heating system was proposed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.4
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• pp.693-699
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• 2006

Digital airborne image must be precisely orthorectified to become geographical information. For orthorectification of airborne images, GPS/INS (Global Positioning System/Inertial Navigation System) and LIDAR (LIght Detection And Ranging) elevation data were employed. In this study, 635 frame airborne images were produced and LIDAR data were converted to raster image for applying to image orthorectification. To derive images with constant brightness, flat field correction was applied to images. The airborne images were geometrically corrected by calculating internal orientation and external orientation using GPS/INS data and then orthorectified using LIDAR digital elevation model image. The precision of orthorectified images was validated by collecting 50 ground control points from arbitrary five images and LIDAR intensity image. As validation result, RMSE (Root Mean Square Error) was 0.387 as almost same as only two times of pixel spatial resolution. It is possible that this automatic orthorectification method of airborne image with higher precision is applied to airborne image industry.