• The Journal of Korea Robotics Society
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• v.17 no.1
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• pp.25-31
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• 2022

Moving among multiple floors is one of the most challenging tasks for indoor autonomous robots. Most of the previous researches for indoor mapping and localization have focused on singular floor environment. In this paper, we present an algorithm that creates a multi-floor map using 3D point cloud. We implement localization within the multi-floor map using a LiDAR and an IMU. Our algorithm builds a multi-floor map by constructing a single-floor map using a LOAM-based algorithm, and stacking them through global registration that aligns the common sections in the map of each floor. The localization in the multi-floor map was performed by adding the height information to the NDT (Normal Distribution Transform)-based registration method. The mean error of the multi-floor map showed 0.29 m and 0.43 m errors in the x, and y-axis, respectively. In addition, the mean error of yaw was 1.00°, and the error rate of height was 0.063. The real-world test for localization was performed on the third floor. It showed the mean square error of 0.116 m, and the average differential time of 0.01 sec. This study will be able to help indoor autonomous robots to operate on multiple floors.

• Advances in concrete construction
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• v.10 no.6
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• pp.527-536
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• 2020

In this study, a process is proposed to calculate analytical correction values for the vertical shortening of all columns on all floors in a high-rise building that minimizes the error between the structural analysis predictions and values measured during construction. The weight ratio and the most probable value were accordingly considered based on the properties of the shortening value analyzed at several points in each construction stage and the distance between these measured points and unmeasured points at which the shortening was predicted. The effective range and shortening value normalization were considered using the column grouping concept. These tools were applied to calculate the error ratio between the predicted and measured values on a floor where a measured point exists, and then determine the estimated error ratio and estimated error value for the unmeasured point using this error ratio. At points on a floor where no measured point exists, the estimated error ratio and the estimated error value were calculated by applying the most probable value considering the weight ratio for the nearest floor where measured points exist. In this manner, the error values and estimated error values can be determined at all points in a structure. Then, the analytical correction value, defined as this error or estimated error value, was applied by adding it to the predicted value. Finally, the adequacy of the proposed correction method was verified against measurements by applying the analytical corrections to all unmeasured points based on the points where the measurement exists.

• Geomechanics and Engineering
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• v.23 no.1
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• pp.51-59
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• 2020

In this paper, the WEKA platform was used to mine and analyze measured data of floor failure depth and a prediction system of floor failure depth was developed with Java. Based on the standardization and discretization of 35-set measured data of floor failure depth in China, the grey correlation degree analysis on five factors affecting the floor failure depth was carried out. The correlation order from big to small is: mining depth, working face length, floor failure resistance, mining thickness, dip angle of coal seams. Naive Bayes model, neural network model and decision tree model were used for learning and training, and the accuracy of the confusion matrix, detailed accuracy and node error rate were analyzed. Finally, artificial neural network was concluded to be the optimal model. Based on Java language, a prediction system of floor failure depth was developed. With the easy operation in the system, the prediction from measured data and error analyses were performed for nine sets of data. The results show that the WEKA prediction formula has the smallest relative error and the best prediction effect. Besides, the applicability of WEKA prediction formula was analyzed. The results show that WEKA prediction has a better applicability under the coal seam mining depth of 110 m~550 m, dip angle of coal seams of 0°~15° and working face length of 30 m~135 m.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.6B
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• pp.1024-1031
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• 1999

In order to transmit high-speed wide band signals efficiently in multipath fading environments, M-ary QAM signalling combined with OFDM transmission technique is applied. In this paper, the effect of synchronization error caused by carrier frequency offset and SER(Symbol Error Rate) performance of OFDM-16QAM and OFDM-64QAM are theoretically analyzed. Our result shows that as the number of sub-carrier in OFDM system increases the frequency-offset caused inter-channel interference(ICI) increases significantly, and that an error floor occurs even at high SNR of OFDM system. For OFDM-64QAM, the error floor occurs at SER=1$\times$10-7 when a normalized frequency-offset is 0.001, in which the SNR degradation is much greater than that of OFDM-16QAM. From this study the maximum allowable frequency-offset of OFDM-16QAM and OFDM-64QAM systems can be determined to meet the specific SER requirement.

• ETRI Journal
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• v.36 no.1
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• pp.171-174
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• 2014

In weighted bit-flipping-based algorithms for low-density parity-check (LDPC) codes, due to the existence of overconfident incorrectly received bits, the metric values of the corresponding bits will always be wrong in the decoding process. Since these bits cannot be flipped, decoding failure results. To solve this problem, an improved parallel weighted bit flipping algorithm is proposed. Specifically, a reliability-saturation strategy is adopted to increase the flipping probability of the overconfident incorrectly received bits. Simulation results show that the error floor of LDPC codes is greatly lowered.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.10
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• pp.852-857
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• 2013

In this paper we propose a design algorithm for nonbinary LDPC (low-density parity-check) codes with low error-floors. The proposed algorithm determines the nonbinary values of the nonzero entries in the parity-check matrix in order to maximize the binary minimum distance of the designed nonbinary LDPC codes. We verify the performance of the designed nonbinary LDPC codes in the error-floor region by Monte Carlo simulation and importance sampling over BPSK (binary phase-shift keying) modulation.

• ETRI Journal
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• v.37 no.1
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• pp.54-60
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• 2015

The use of serial concatenated codes is an effective technique for alleviating the error floor phenomenon of low-density parity-check (LDPC) codes. An enhanced sum-product algorithm (SPA) for LDPC codes, which is suitable for serial concatenated codes, is proposed in this paper. The proposed algorithm minimizes the number of errors by using the failed check nodes (FCNs) in LDPC decoding. Hence, the error-correcting capability of the serial concatenated code can be improved. The number of FCNs is simply obtained by the syndrome test, which is performed during the SPA. Hence, the decoding procedure of the proposed algorithm is similar to that of the conventional algorithm. The error performance of the proposed algorithm is analyzed and compared with that of the conventional algorithm. As a result, a gain of 1.4 dB can be obtained by the proposed algorithm at a bit error rate of $10^{-8}$. In addition, the error performance of the proposed algorithm with just 30 iterations is shown to be superior to that of the conventional algorithm with 100 iterations.

• Journal of Advanced Marine Engineering and Technology
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• v.33 no.5
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• pp.738-745
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• 2009

Underwater acoustic communication has multipath error because of reflection by sea-level and sea-bottom. The multipath of underwater channel causes receive signal to make error floor. In this paper, we propose the underwater communication system using various channel coding schemes such as RS coding, convolutional code, turbo code and concatenated code for overcoming the multipath effect in underwater channel. As shown in simulation results, characteristic of multipath error is similar to that of random error. So interleaver has not effect on error correcting. For correcting of error floor by multipath, it is necessary to use strong channel codes like turbo code. Turbo code is one of the iterative codes. And the performance of concatenated codes including RS code has better performance than using singular channel codes.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.10
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• pp.1111-1116
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• 2014

In this paper, in order to improve performance of LDPC codes, we propose an effective algorithm with lowering error floor of LDPC codes. This method is done by breaking trapping sets, mostly caused by an undesirable structure. This algorithm is not need to observe all the errors, only need to break the trapping sets, to effect the effectiveness. Simulation results show that its performance can be significantly improved with this decoding algorithm.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.811-812
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• 2013