• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.31 no.1C
• /
• pp.26-35
• /
• 2006

In this paper, an automatic mobile robot system for a intelligent path planning using the detection scheme of the spatial coordinates based on stereo camera is proposed. In the proposed system, face area of a moving person is detected from a left image among the stereo image pairs by using the YCbCr color model and its center coordinates are computed by using the centroid method and then using these data, the stereo camera embedded on the mobile robot can be controlled for tracking the moving target in real-time. Moreover, using the disparity map obtained from the left and right images captured by the tracking-controlled stereo camera system and the perspective transformation between a 3-D scene and an image plane, depth information can be detected. Finally, based-on the analysis of these calculated coordinates, a mobile robot system is derived as a intelligent path planning and a estimation. From some experiments on robot driving with 240 frames of the stereo images, it is analyzed that error ratio between the calculated and measured values of the distance between the mobile robot and the objects, and relative distance between the other objects is found to be very low value of $2.19\%$ and $1.52\%$ on average, respectably.

• Journal of Broadcast Engineering
• /
• v.14 no.6
• /
• pp.749-768
• /
• 2009

In this paper, an intra prediction offset compensation method is proposed to improve intra prediction in H.264/AVC. In H.264/AVC, intra prediction based on various directions improves the coding efficiency by removing spatial correlation between neighboring blocks. In details, neighboring pixels in reconstructed block can be used as intra reference block for the current block to be coded when intra prediction method is used. In order to reduce further the prediction error of the intra reference block, the proposed method introduces an intra prediction offset which is determined in the sense of the rate-distortion optimization and is added to the conventional intra prediction block. Besides the intra prediction offset compensation, the coefficient thresholding method which is used for inter coding in JM 11.0, is used for chroma component in intra block, which leads the improvement of the luma coding efficiency of the proposed method. In experiments, we show that the proposed method achieves average 2.45% in High Profile condition and maximum 4.41% of bitrate reduction relative to JM 11.0.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.5A
• /
• pp.401-407
• /
• 2009

The multi-band (MB) ultra-wideband (UWB) communication system divides its available frequency spectrum in 3.1 to 10.6GHz into 16 sub-bands, which leads to inherent disparities between carrier frequencies of each sub-band. For instance, the highest carrier frequency is 2.65 times higher than the lowest one. Since the propagation loss is proportional to the square of the transmission frequency, the propagation loss on the sub-band having the highest carrier frequency is approximately 7 times larger than that on the sub-band having the lowest carrier frequency, which results in disparities between received signal powers on each sub-band. In this paper, we propose a novel correlation scheme for frequency hopping (FH) MB UWB communications, where the correlation time is adaptively adjusted relative to the sub-band, which reduces the disparity between the received signal energies on each sub-band. Such compensation for lower received powers on sub-bands having higher carrier frequency leads to an improvement on the total average bit error rate (BER) of the entire FH MB UWB communication system. We analyze the performance of the proposed correlation scheme in Nakagami fading channels, and it is shown that the performance gain provided by the proposed correlator is more significant as the Nakagami fading index n increases (i.e., better channel conditions).

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.44 no.1
• /
• pp.100-107
• /
• 2007

AABR(automated auditory brainstem response) test is used for the screening purpose of hearing ability of neonates. In this paper, algorithm using Rolle's theorem is suggested for automatic detection of the ensemble averaged ABR waveform. The ABR waveforms were recorded from 55 normal-hearing ears of neonates at screening levels varying from 30 to 60 dBnHL. Recorded signals were analyzed by expert audiologist and by the proposed algorithm. The results showed that the proposed algorithm correctly identified latencies of the major ABR waves (III, V) with latent difference below 0.2 ms. No significant differences were found between the two methods. We also analyzed the ABR signals using derivative algorithm and compared the results with proposed algorithm. The number of detected candidate waves using the proposed algorithm was 47 % less than that of the existing one. The proposed method had lower relative errors (0.01 % error at 60dBnHL) compared to the existing one. By using proposed algorithm, clinicians can detect and label waves III and V more objectively and quantitatively than the manual detection method.

• Nuclear Engineering and Technology
• /
• v.52 no.11
• /
• pp.2452-2459
• /
• 2020

Neutron spectrum is essential to the safe operation of reactors. Traditional online neutron spectrum measurement methods still have room to improve accuracy for the application cases of wide energy range. From the application of artificial neural network (ANN) algorithm in spectrum unfolding, its accuracy is difficult to be improved for lacking of enough effective training data. In this paper, an adaptive deviation-resistant neutron spectrum unfolding method based on transfer learning was developed. The model of ANN was trained with thousands of neutron spectra generated with Monte Carlo transport calculation to construct a coarse-grained unfolded spectrum. In order to improve the accuracy of the unfolded spectrum, results of the previous ANN model combined with some specific eigenvalues of the current system were put into the dataset for training the deeper ANN model, and fine-grained unfolded spectrum could be achieved through the deeper ANN model. The method could realize accurate spectrum unfolding while maintaining universality, combined with detectors covering wide energy range, it could improve the accuracy of spectrum measurement methods for wide energy range. This method was verified with a fast neutron reactor BN-600. The mean square error (MSE), average relative deviation (ARD) and spectrum quality (Qs) were selected to evaluate the final results and they all demonstrated that the developed method was much more precise than traditional spectrum unfolding methods.

• Nuclear Engineering and Technology
• /
• v.53 no.6
• /
• pp.1834-1845
• /
• 2021

Liquid lead-bismuth cooled fast reactor is one of the most promising reactor types among the fourth-generation nuclear energy systems. The flow and heat transfer characteristics of lead-bismuth eutectic (LBE) are completely different from ordinary fluids due to its special thermal properties, causing that the traditional Reynolds analogy is no longer recommended and appropriate. More accurate turbulence flow and heat transfer model for the liquid metal lead-bismuth should be developed and applied in CFD simulation. In this paper, a specific CFD solver for simulating the flow and heat transfer of liquid lead-bismuth based on the k - 𝜀 - k_𝜃 - 𝜀_𝜃 model was developed based on the open source platform OpenFOAM. Then the advantage of proposed model was demonstrated and validated against a set of experimental data. Finally, the simulation of LBE turbulent flow and heat transfer in a 7-pin wire-wrapped rod bundle with the k - 𝜀 - k_𝜃 - 𝜀_𝜃 model was carried out. The influence of wire on the flow and heat transfer characteristics and the three-dimensional distribution of key thermal hydraulic parameters such as temperature, cross-flow velocity and Nusselt number were studied and presented. Compared with the traditional SED model with a constant Pr_t = 1.5 or 2.0, the k - 𝜀 - k_𝜃 - 𝜀_𝜃 model is more accurate on predicting the turbulence flow and heat transfer of liquid lead-bismuth. The average relative error of the k - 𝜀 - k_𝜃 - 𝜀_𝜃 model is reduced by 11.1% at most under the simulation conditions in this paper. This work is meaningful for the thermal hydraulic analysis and structure design of fuel assembly in the liquid lead-bismuth cooled fast reactor.

• Journal of Korea Water Resources Association
• /
• v.52 no.7
• /
• pp.463-473
• /
• 2019

This study compared the characteristics of the optimization technique and the water supply and demand forecast using K-WEAP (Korea-Water Evaluation and Planning System) model and MODSIM (Modified SIMYLD) model considering wtaer supply priority. Currently, The national water resources plan applied same priority for municipal, industrial and agricultural demand. the K-WEAP model performs the ratio allocation to satisfy the maximum satisfaction rate, whereas the MODSIM model should be applied to the water supply priority of demands. As a result of applying the priority, water shortage decreased by an average of $1,035,000m^3$ than same prioritized results. It is due to the increase of the return flow rate as the distribution of Municipal and industrial water increases. Comparing the analysis results of K-WEAP and MODSIM applying the priorities, the relative error was within 5.3% and the coefficient of determination ($R^2$) was 0.9999. In addition, if both models provide reasonable water balance analysis results, K-WEAP is superior to GUI convenience for model construction and data processing. However, MODSIM is more effective in simulation time efficiency. It is expected that it will be able to carry out analysis according to various scenarios using the model.

• Korean Journal of Remote Sensing
• /
• v.35 no.2
• /
• pp.265-278
• /
• 2019

Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) data help to enable rapid emergency responses through detection of the artificial and natural disasters occurring at night. The DNB data without correction of lunar irradiance effect distributed by Korea Ocean Science Center (KOSC) has advantage for rapid change detection because of direct receiving. In this study, radiance differences according to the phase of the moon was analyzed for urban and mountain areas in Korean Peninsula using the DNB data directly receiving to KOSC. Lunar irradiance correction algorithm was proposed for the change detection. Relative correction was performed by regression analysis between the selected pixels considering the land cover classification in the reference DNB image during the new moon and the input DNB image. As a result of daily difference image analysis, the brightness value change in urban area and mountain area was ${\pm}30$ radiance and below ${\pm}1$ radiance respectively. The object based change detection was performed after the extraction of the main object of interest based on the average image of time series data in order to reduce the matching and geometric error between DNB images. The changes in brightness occurring in mountainous areas were effectively detected after the calibration of lunar irradiance effect, and it showed that the developed technology could be used for real time change detection.

• Journal of the Korean Society of Urban Environment
• /
• v.18 no.4
• /
• pp.547-555
• /
• 2018

In addition to North America and Europe, Korea is also responding to the toxic damage caused by the production and distribution of chemicals. Methods for assessing bio-toxicity of harmful substances have been widely introduced, but it is required of quantitative and speedy information for modeling. For 6 heavy metals, as zinc, copper, chrome, cadmium, mercury and lead, bio-toxicity assessment and kinetics model were constructed using Vibrio fischeri which is widely used luminous bacteria. The degree of luminescence activity and the toxicity of heavy metals were relative limunescence unit, RLU measured as by using a photomultiplier embedded device. The toxicity was assessed by the concentration levels giving under 20% lethality and lethal concentration, $EC_{50}$. In the results, the toxicity order were followed from mercury, lead, copper, chrome, zinc and cadmium. $EC_{{50},{\infty}}$ obtained by trends of $EC_{50}$ by time follows had highly linear agreement with main parameters of bio-toxicity modelling. The average error rates of the reproduced lethality obtained from DAM and TDM model on the basis of body residue, were 10.2% for mercury, lead, copper, chrome and 20.0 for the all 6 methals.

• Korean Journal of Remote Sensing
• /
• v.38 no.5_1
• /
• pp.597-608
• /
• 2022

Remotely sensed data have been used in various fields, such as disasters, agriculture, urban planning, and the military. Recently, the demand for the multitemporal dataset with the high-spatial-resolution has increased. This manuscript proposed an automatic image matching algorithm using a deep learning technique to utilize a multitemporal remotely sensed dataset. The proposed deep learning model was based on High Resolution Net (HRNet), widely used in image segmentation. In this manuscript, denseblock was added to calculate the correlation map between images effectively and to increase learning efficiency. The training of the proposed model was performed using the multitemporal orthophotos of the National Geographic Information Institute (NGII). In order to evaluate the performance of image matching using a deep learning model, a comparative evaluation was performed. As a result of the experiment, the average horizontal error of the proposed algorithm based on 80% of the image matching rate was 3 pixels. At the same time, that of the Zero Normalized Cross-Correlation (ZNCC) was 25 pixels. In particular, it was confirmed that the proposed method is effective even in mountainous and farmland areas where the image changes according to vegetation growth. Therefore, it is expected that the proposed deep learning algorithm can perform relative image registration and image matching of a multitemporal remote sensed dataset.