• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.5
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• pp.1135-1144
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• 2018

An electric wheelchair used to be utilized as a piece of equipment for the disabled and the elderly in the past, but the recent changes to its functions and forms have made it available across various fields and purposes. In this paper, we propose a continuous track type of electric wheelchair prototype to be used in various fields and environments and a monitoring system to control it. A frame stress design was applied to improve its stability during driving compared with the previous wheelchairs. In addition, we provide a convenience for free and easy operation of them using the App. based on android. A monitoring system based on C# was also added to control a large number of electric wheelchairs. As a result of the implementation and performance evaluation, the von Mises stress value was measured 4.401% within the normal range through five times of stress interpretations, and its accuracy of communication for system manipulation was recorded about 98.75%, which means that it has been proven to be safer than the previous wheelchairs.

• Korean Journal of Remote Sensing
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• v.26 no.2
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• pp.277-285
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• 2010

Geostationary Ocean Color Imager(GOCI-I), the world's first space-borne ocean color observation geostationary satellite, will be launched on June 2010. Development of GOCI-I took about 6 years, and its expected lifetime is about 7 years. The mission and user requirements of GOCI-II are required to be defined at this moment. Because baseline of the main mission of GOCI-II must be defined during the development time and early operational period of GOCI-I. The main difference between these missions is the global-monitoring capability of GOCI-II, which will meet the necessity of the monitoring and research on climate change in the long-term. The user requirements of GOCI-II will have higher spatial resolution, $250m{\times}250m$, and 12 spectral bands to fulfill GOCI-I's user request, which could not be implemented on GOCI-I for technical reasons. A dedicated panchromatic band will be added for the nighttime observation to obtain fishery information. GOCI-II will have a new capability, supporting user-definable observation requests such as clear sky area without clouds and special-event areas, etc. This will enable higher applicability of GOCI-II products. GOCI-II will perform observations 8 times daily, the same as GOCI-I's. Additionally, daily global observation once or twice daily is planned for GOCI-II. In this paper, we present an improved development and organization structure to solve the problems that have emerged so far. The hardware design of the GOCI-II will proceed in conjunction with domestic or foreign space agencies.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1323-1337
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• 2020

GEO-KOMPSAT-2A AMI (Advanced Meteorological Imager) radiometric calibration evaluation is an essential element not only for functional and performance verification of the payload but for the quality of the sensor data. AMI instrument consists of six reflective channels and ten thermal infrared ones. One of the key parameters representing radiometric properties of the sensor is a SNR (Signal-to-Noise Ratio) for the reflective channels and a NEdT (Noise Equivalent delta Temperature) for the IR ones respectively. Other important radiometric calibration parameters are a dynamic range and a gain value related with the responsivity of detectors. To verify major radiometric calibration performance of AMI, an offline radiometric evaluation tool was developed separately with a real-time AMI data processing system. Using the evaluation tool, validation activities were carried out during the GEO-KOMPSAT-2A In-Orbit Test period. The results from the evaluation tool were cross checked with those of the HARRIS, which is the AMI payload vendor. AMI radiometric evaluation activities were conducted through three phases for both sides (Side 1 and Side 2) of AMI payload. Results showed that performances of the key radiometric properties were outstanding with respect to the radiometric requirements of the payload. The effectiveness of the evaluation tool was verified as well.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.2
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• pp.93-98
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• 2016

For accurate precipitation forecasts the choice of weather factors and prediction method is very important. Recently, machine learning has been widely used for forecasting precipitation, and artificial neural network, one of machine learning techniques, showed good performance. In this paper, we suggest a new method for forecasting precipitation using DBN, one of deep learning techniques. DBN has an advantage that initial weights are set by unsupervised learning, so this compensates for the defects of artificial neural networks. We used past precipitation, temperature, and the parameters of the sun and moon's motion as features for forecasting precipitation. The dataset consists of observation data which had been measured for 40 years from AWS in Seoul. Experiments were based on 8-fold cross validation. As a result of estimation, we got probabilities of test dataset, so threshold was used for the decision of precipitation. CSI and Bias were used for indicating the precision of precipitation. Our experimental results showed that DBN performed better than MLP.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.9
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• pp.830-837
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• 2015

Space debris has been a major issue recently for the space-active nations because its growing population is expected to increase the collision risk with operational satellites. Radar and electro-optical system has been used for space debris surveillance, which may cause unnecessary anti-collision manoeuvers due to their low tracking accuracy. So an additional tracking system is required to improve the predicted orbit accuracy and then to jude the anti-collision maneouvers more efficiently. The laser tracking system has been considered as an alternative to decrease these unnecessary manoeuvers. Korea Astronomy and Space Science Institute has been developing a space object laser tracking system which is capable of laser tracking for satellites with retro-reflectors and for space debris using high power laser, and satellite imaging using adaptive optics. In this study, the tracking capability is analyzed for space debris using high power laser based on link budget, false alarm probability and signal detection probability.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.9
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• pp.493-501
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• 2016

In this study, core technologies of a traction system on a mountain tram operating on the track of mountain road full of sharp curves and steep gradients were developed. In domestic mountain resort areas, sometimes the transportation service is not provided in winter because of ice and heavy snow on roads, so a mountain railway service independent of the climate and geographic conditions is needed. A traction system was designed taking into account of the power of a traction motor to climb the gradient of 120 ‰, which is common in domestic mountainous areas. and power transmission system was designed to consider the installation space for the traction system. In addition, a reduction gear and a propeller shaft were developed. An elastic pinion was developed and applied to the rack & pinion bogie system for steep gradient so that noise and vibration generated by contact between the steel gears could be reduced. Impact comparison tests showed that the vibration level of the elastic pinion is one-third lower than that of previous steel pinion. Independent rotating wheels and axles were developed for the bogie system to operate on the sharp curve of a 10 meter radius. In addition, the band braking system was developed to enhance the braking force during running on the steep gradient. A test for the braking force showed it exerts the required braking force. The performance of the developed core components were verified by the tests and finally they were applied to the bogie system running on the track of steep gradient and sharp curve.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1089-1098
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• 2020

In this study, we propose a method to detect red tide Cochlodinium Polykrikoide using by machine learning and geostationary marine satellite images. To learn the machine learning model, GOCI Level 2 data were used, and the red tide location data of the National Fisheries Research and Development Institute was used. The machine learning model used logistic regression model, decision tree model, and random forest model. As a result of the performance evaluation, compared to the traditional GOCI image-based red tide detection algorithm without machine learning (Son et al., 2012) (75%), it was confirmed that the accuracy was improved by about 13~22%p (88~98%). In addition, as a result of comparing and analyzing the detection performance between machine learning models, the random forest model (98%) showed the highest detection accuracy.It is believed that this machine learning-based red tide detection algorithm can be used to detect red tide early in the future and track and monitor its movement and spread.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.12
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• pp.1079-1088
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• 2015

Parallelism and performance enhancement of calculating view factors in KSDS developed by KARI is introduced in this paper. View factor is an essential parameters of radiation thermal analysis for a spacecraft, and the amount of computation of them is not negligible. Especially, independent integration of view factors at each position of the orbit because the relative displace between solar panel and main body of a satellite varies with the position on the orbit. This paper introduces a range of parallelism of computing view factor and their performance, detection of obstructions by spatial search algorithm based on KD-Tree, and the reduction of the calculation of view factors of a satellite with relative motion between solar panel and main body, called updating fractional view factor matrix, for satellite thermal analysis.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.1
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• pp.56-62
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• 2011

A Satellite transponder is mounted on the Satellite and performs radio communications with the ground station. A Digital transponder compared to The analog transponder is made easy and accurate performance prediction. Also Modulation Scheme, Data Rate, Loop Bandwidth, Modulation Index and etc. can be changed on orbit, by implementing FPGA can reduce the weight and volume. The core technology of digital transponder is Carrier Recovery loop. Dynamic Range, Frequency Tracking Range, Frequency Tracking Rate and Coherent performance are determined by the performance of the Carrier Recovery loop. In this paper, we proposed the structure of Carrier Recovery loop for the Satellite digital transponder, then tested and verified the structure.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.8
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• pp.767-773
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• 2008

Galileo is a new civil Global Navigation Satellite System(GNSS) developed by Europe. GIOVE-A, a satellite to test Galileo system performance, transmits navigation signal on orbit. Evaluation of Galileo system and development of Galileo receiver needs to analyze GIOVE-A signals. In this paper, we received GIOVE-A signals and processed it using GIOVE-A Interface Control Document(ICD). Signal acquisition, tracking and navigation message decoding made grasping current signal status possible. Bandwidth increase by BOC modulation is one of the difference from GPS. Therefore, we investigated feasibility of conventional GPS L1 RF front-end to receive GIOVE-A E1 signal by evaluation of receiving performance of navigation signal on each bandpass filter of RF front-end.