• Journal of Advanced Navigation Technology
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• v.20 no.4
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• pp.321-328
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• 2016

Typical MLC NAND flash devices are considered less reliable than SLC NAND flash devices. Although raw bit error rate (RBER) of MLC flash had been considered approximately 1000times or more higher than that of SLC flash, recent research conducted on Google's data center shows that it is much lower than such expectation. Based on the research, we devised In Drive Data Duplication (IDDD) scheme that efficiently exploit MLC flash's sufficient capacity to improve its data reliability without structural complexity increment using SSD intrinsic firmware layer, and showed the data reliability expectation of MLC flash could be significantly higher than that of SLC flash from measured and calculated error rates. Even though RBER of SLC flash was lower than that of MLC flash in 44 out of 48 cases we studied, applying IDDD scheme, RBER of MLC flash was became lower than that of SLC in all 48 cases and uncorrectable bit error rate (UBER) of MLC flash was became lower than that of SLC flash in 45 out of 48 cases.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.22 no.2
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• pp.353-364
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• 1998

This paper describes the design processes and evaluation results of a small-sized six-axis force/torque sensor. The new six-axis force/torque sensor including S-type structure has been developed using a parallel plate structure as a basic sensing element. In order tominimize coupling errors, the location of strain gages has been determined based on the finite element analysis and the connections of strain gages have been made such that the bridge circuit with 4 strain gages becomes balanced. Several design modifications result in a similar strain sensitivity for six-axis forces and moments, and the reduced coupling errors of 2.6% FS between each forces and moments. Calibration test results show that the six-axis load cell developed which has light weight of 135g and the maximum capacities of 196 N in forces and 19.6 N.m in moments is estimated to be within 7.1% FS in coupling error.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.39 no.12
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• pp.1022-1032
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• 2002

A multibit DRAM BIST methodology reducing redundancy programming overhead has been proposed. It is capable of counting and locating faulty bits simultaneously with the test. If DRAM cells are composed of n blocks generally, the proposed BIST can detect the state of no error, the location of faulty bit block if there is one error and the existence of errors in more than two blocks, which are n + 2 states totally, with only n comparators and an 3 state encoder. Based on the proposed BIST methodology, the testing scheme which can detect the number and locations of faulty bits with the errors in two or more blocks, can be easily implemented. Based on performance evaluation, the test and redundancy programming time of 64MEG DRAM with 8 blocks is reduced by 1/750 times with 0.115% circuit overhead.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.6 no.1
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• pp.54-57
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• 2005

A soft error rate neutrons is a growing problem fur terrestrial integrated circuits with technology scaling. In the acceleration test with high-density neutron beam, a latch-up prohibits accurate estimations of the soft error rate (SER). This paper presents results of analysis for the latch-up characteristics in the circumstance corresponding to the acceleration SER test for SRAM. Simulation results, using a two-dimensional device simulator, show that the deep p-well structure has better latch-up immunity compared to normal twin and triple well structures. In addition, it is more effective to minimize the distance to ground power compared with controlling a path to the $V_{DD}$ power.

• Journal of the Korean Solar Energy Society
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• v.29 no.2
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• pp.70-75
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• 2009

In this experiment, we did sampling 6 kinds of photovoltaic modules and analyzed the discrepancy of measurement results between l laboratory and 4 PV makers to have performance repeatability at Standard Test Condition(STC) condition. From the KIER's results, Korea's standard test laboratory, other laboratory showed -10% measurement variation. The causes came from correction of reference cell, test condition and the state of skill. Form the comparison test, we analyzed the problems. But three PV maker reduced measurement variation, other one PV maker and one test laboratory didn't improve the problems of correction of reference cell, test condition and the state of skill. Also, High Efficiency Module had a big discrepancy of -10.0$\sim$-6.2% among 3 laboratories which have a less than 10msec light pulse duration time. This made low spectrum response speed so the Fill Factor decreased maximum output power under 10msec light pulse duration time

• Journal of the Computational Structural Engineering Institute of Korea
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• v.13 no.4
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• pp.485-500
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• 2000

In this paper the adaptive crack propagation analysis based on the estimated local and global error in the element-free Galerkin (EFG) method is presented. It is possible to keep consistency and accuracy of analysis in each propagation step by adaptive analysis. The adaptivity analysis in crack propagation is achieved by adding and removing the node along the background integration cell that are refined or recovered as estimated error. These errors are obtained by calculating the difference between the values of the projected stresses and original EFG stresses. To evaluate the performance of proposed adaptive procedure, the convergence behavior is investigated lot several examples. The results of these examples show the efficiency of proposed scheme in crack propagation analysis.

• Nuclear Engineering and Technology
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• v.54 no.8
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• pp.3027-3033
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• 2022

Background: In this study, various types of deep-learning models for predicting in vitro radiosensitivity from gene-expression profiling were compared. Methods: The clonogenic surviving fractions at 2 Gy from previous publications and microarray gene-expression data from the National Cancer Institute-60 cell lines were used to measure the radiosensitivity. Seven different prediction models including three distinct multi-layered perceptrons (MLP), four different convolutional neural networks (CNN) were compared. Folded cross-validation was applied to train and evaluate model performance. The criteria for correct prediction were absolute error < 0.02 or relative error < 10%. The models were compared in terms of prediction accuracy, training time per epoch, training fluctuations, and required calculation resources. Results: The strength of MLP-based models was their fast initial convergence and short training time per epoch. They represented significantly different prediction accuracy depending on the model configuration. The CNN-based models showed relatively high prediction accuracy, low training fluctuations, and a relatively small increase in the memory requirement as the model deepens. Conclusion: Our findings suggest that a CNN-based model with moderate depth would be appropriate when the prediction accuracy is important, and a shallow MLP-based model can be recommended when either the training resources or time are limited.

• Journal of computational fluids engineering
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• v.9 no.1
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• pp.48-56
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• 2004

The numerical simulations with unstructured mesh by cell-centered and vertex-centered approaches were peformed for the quadrilateral and triangular meshes. For 2-D inviscid supersonic vortex flow, the simulation results and the analytic solution were compared and the accuracy was assessed. The calculation efficiency was measured by the parameter defined by the consumed CPU time multiplied by absolute error As a results, equilateral triangular mesh yielded the best accuracy and efficiency among the tested meshes. Cell-centered approach gives a little better efficiency than vertex - centered approach.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.60 no.2
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• pp.99-104
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• 2011

In this paper, the intelligent landscape lighting power control and monitoring system with solar sell generator equipment is proposed. The first, the intelligent landscape lighting power controller is designed using the fuzzy logic control method. And the fuzzy logic controller is used to save power consumption for various reference intensity of the illumination. The second, the GUI monitoring system is presented. It has control and display faculty. And the practical experiment device is used to evaluate the performance criteria of the proposed intelligent landscape lighting power control system with the solar cell power generation equipment. From the experiment results, we present the property of proposed fuzzy controller such as steady state error, the tracking and power consumption characteristic for the reference intensity of illumination. And also we show the superiority of power control as well as the characteristic of GUI monitoring system in the proposed system.

• Journal of the Korean Statistical Society
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• v.27 no.4
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• pp.515-529
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• 1998

Burman (1987) and Hall and Titterington (1987) studied kernel smoothing for sparse multinomial data in detail. Both of their estimators for cell probabilities are sparse asymptotic consistent under some restrictive conditions on the true cell probabilities. Dong and Simonoff (1994) adopted boundary kernels to relieve the restrictive conditions. We propose a local linear kernel estimator which is popular in nonparametric regression to estimate cell probabilities. No boundary adjustment is necessary for this estimator since it adapts automatically to estimation at the boundaries. It is shown that our estimator attains the optimal rate of convergence in mean sum of squared error under sparseness. Some simulation results and a real data application are presented to see the performance of the estimator.