• Nuclear Engineering and Technology
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• v.15 no.2
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• pp.135-141
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• 1983

Computational accuracy of the modified Borresen's coarse-mesh diffusion theory scheme is investigated with the steady-state solutions of the two- and three-dimensional LRA-BWR bench-mark problem. By comparing the numerical results available for the critical eigenvalue and power distribution of the LRA-BWR, it is shown that the modified scheme is capable of predicting the power distribution of the multi-dimensional BWR problem with an improved accuracy.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.6C
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• pp.642-648
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• 2009

In this paper, we use SA (Seysen's Algorithm) instead of LLL (Lenstra-Lenstra-Lovasz) to perform LRA (Lattice Reduction-Aided) detection. By using SA, the complexity of lattice reduction is reduced and the detection performance is improved Although the performance is improved using SA, there still exists a gap in the performance between SA-LRA and ML detection. To reduce the performance difference, we apply list of candidates scheme to SA-LRA. The list of candidates scheme finds a list of candidates. Then, the candidate with the smallest squared Euclidean distance is considered as the estimate of the transmitted signal. Simulation results show that the SA-LRA detection learn to quasi-ML performance. Moreover, the efficiency of the SA is shown to highly improve the channel matrix conditionality.

• The Journal of the Acoustical Society of Korea
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• v.21 no.5
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• pp.494-502
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• 2002

In this paper, the Low Rank Approximation (LRA) method to suppress the interference of signals from temporal fluctuations is applied. The reverberation signals and temporally fluctuating signals are separated from the measured data using the Ink. The Singular value decomposition (SVD) method is applied to extract the low rank and the temporally stable reverberation was extracted using the LRA. The reverberation suppression is performed on the LRA residual value obtained by removing the approximate reverberation signals. In overall, the method can be applied to the suppression of reververation in active sonar system as well as to the modeling of reverberation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.9C
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• pp.915-921
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• 2009

Lenstra-Lenstra-Lovasz (LLL) algorithm, which is one of the lattice reduction (LR) techniques, has been extensively used to obtain better bases of the channel matrix. In this paper, we jointly apply Seysen's lattice reduction Algorithm (SA), instead of LLL, with the conventional linear precoding algorithms. Since SA obtains more orthogonal lattice bases compared to those obtained by LLL, lattice reduction aided (LRA) precoding based on SA algorithm outperforms the LRA precoding with LLL. Simulation results demonstrate that a gain of 0.5dB at target BER of $10^{-5}$ is achieved when SA is used instead of LLL or the LR stage.

• Journal of The Korean Society of Agricultural Engineers
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• v.49 no.3
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• pp.63-68
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• 2007

The LRA(Logistic Regression Analysis) conducts a quantitative analysis by collecting a lot of samples and the AHP(Analytic Hierarchy Program) makes use of expert decision influenced by subjective judgment to a certain degree. This study is to suggest a combination method in mapping landslide hazard by giving equal weight for the result of LRA and AHP. Topographic factors(slope, aspect, elevation), soil dram, soil depth and land use were adopted to classify landslide hazard areas. The three methods(LRA, AHP, the combined approach) was applied to a $520km^2$ region located in the middle of South Korea which have occurred 39 landslides during 1999 and 2003. The suggested method showed 58.9% matching rate for the real landslide sites comparing with the classified areas of high-risk landslide While LRA and AHP Showed 46.1% and 48.7% matching rates respectively. Further studies are recommended to find the optimal combining weight of LRA and AHP with more landslide data.

• Nuclear Engineering and Technology
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• v.42 no.4
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• pp.394-413
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• 2010

The object of this paper is to identify the key elements that impact a radiation dose at EAB (Exclusion Area Boundary). This study is based on the AST (Alternative Source Terms) as defined in Regulatory Guide 1.183. The LOCA (Loss of Coolant Accident) and the LRA (Locked Rotor Accident) are selected as limiting cases. A sensitivity analysis of accidental behavior with respect to various parameters during LOCA and LRA at Kori Unit 1 is also undertaken for the following objectives: to determine the limiting parameters, to find the impact trend of the radiation dose, and to find the safety margin between AST and TID (Technical Information Document) methodologies. This work confirms that key parameters are particulate removal rate, decontamination factor, iodine chemical form, gap fraction, partitioning factor, and the impact of isotopes group. Comparing TID with AST, the radiation dose of TID is about 80% greater than that of AST under a LOCA, and about 60% greater than that of AST for the case of a LRA; thus the safety margin is remarkably increased when the AST is used. In this work, the sensitivity analysis results are presented in terms of a sensitivity index called the "NDD (Normalized Dose Difference)", which compares the impact of parameters with that of a reference case. These values are derived by using a combination of the leak rate (primary to secondary), iodine chemical form, gap fraction, partitioning factor, spray removal rate, source term, and other variables.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.3
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• pp.33-40
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• 2011

This paper presents the prediction and evaluation of landslide using LRA(logistic regression analysis) and ANN (Artificial Neural Network) methods. In order to assess the landslide, we selected Sarabong, Byeoldobong area and Mt. Song-ak in Jeju Island. Five factors which affect the landslide were selected as: slope angle, elevation, porosity, dry density, permeability. So as to predict and evaluate the landslide, firstly the weight value of each factor was analyzed by LRA(logistic regression analysis) and ANN(Artificial Neural Network) methods. Then we got two prediction maps using AcrView software through GIS(Geographic Information System) method. The comparative analysis reveals that the slope angle and porosity play important roles in landslide. Prediction map generated by LRA method is more accurate than ANN method in Jeju. From the prediction map, we found that the most dangerous area is distributed around the road and path.

• Journal of the Korea Convergence Society
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• v.10 no.2
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• pp.309-313
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• 2019

This study examined the response of the EMG of URA, LRA, IO, EO and RFM of various types of abdominal motion (crunch, spine V-up on ball, prone V-up on slide board, prone V-up on TRX, and prone V-up power wheel). The subjects performed anisometric contact of abs during these exercises. Tests have shown that there were no statistically significant differences between EO, URA and LRA between any movements. However, during the inspection of IO, the positive-wawed V-up motion showed significantly greater muscle activity than during the slide movement. Also, EMG activity during crunch was significantly lower than any other five exercises. These results indicate that in the implementation of equilateral absolutism, the equipment-free based exercise gives an impetus similar to equipment-based exercise. Abdominal muscle tissue is considered one of the five components that make up an individual's core. The abdominal muscles also ensure proper functioning of the lumbar spine. Although all abdominal muscles contribute to lumbar stabilization, TA & IO has been shown to perform major stabilizers.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5D
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• pp.861-867
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• 2006

The objective of this study is to analyze the landslide hazard areas by combining LRA (Lgistic Regression Analysis) and AHP (Analytic Hierarchy Program) methods with Remote Sensing and GIS data in Anseong-si. In order to classify landslide hazard areas of seven levels, six topographic factors (slope, aspect, elevation, soil drain, soil depth, and land use) were used as input factors of LRA and AHP methods. As results, high-risk areas for landslide (1 and 2 levels) by LRA and AHP of its own were classified as 46.1% and 48.7%, respectively. A new method by applying weighting factors to the results of LRA and AHP was suggested. High-risk areas for landslide (1 and 2 levels) form the new method was classified as 58.9%.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.6
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• pp.142-147
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• 2004

Satellite laser ranging (SLR), which is the most accurate geodetic method for precise orbit determination of artificial satellites, will be used to determine the precise orbit of STSAT2. This paper will present the development of a Laser Reflector Array (LRA) of STSAT2. Currently one LRA was designed, analyzed, manufactured, optically tested and assembled.