• Progress in Superconductivity and Cryogenics
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• v.17 no.3
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• pp.28-32
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• 2015

Nowadays the magnetic field mapping is widely used in the design and analysis of the NMR/MRI magnet system, and the accuracy of mapping result has become more and more important. There are several factors affecting the accuracy of the mapping such as the mapping method, the precision of the sensor, the position of the measurement points, the calculation accuracy, and so on. In this paper the error due to the misalignment of the measurement points was discussed. The magnetic field in the central volume was mapped using an indirect method in an MRI magnet system and the magnetic field was fitted to a polynomial. Considering the misalignment between the original measurement points and the practical measurement points, there must be some errors in the mapping calculation and we called it positioning error. Several comparisons of the positioning error have been presented through the theoretical estimates and the exact magnetic field values. Finally, the allowable positioning errors were suggested to guarantee the accuracy of the magnetic field mapping within a certain degree for an example case.

• Progress in Superconductivity and Cryogenics
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• v.17 no.2
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• pp.31-35
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• 2015

Mapping is a useful tool in the magnetic field analysis and design. In some specific research area, such as the nuclear magnetic resonance (NMR) or the magnetic resonance imaging (MRI), it is important to map the magnetic field in the interesting space with high accuracy. In this paper, an indirect mapping method in the center volume of an air-core solenoid is presented, based on the solution of the Laplace's equation for the field. Through the mathematical analysis on the mapping calculation, we know that the condition number of the matrix, generated by the measurement points, can greatly affect the error of mapping result. Two different arrangement methods of the measurement points in field mapping are described in this paper: helical cylindrical line (HCL) method and parallel cylindrical line (PCL) method. According to the condition number, the HCL method is recommended to measure the field components using one probe. As a simple example, we mapped the magnetic fields in a MRI main magnet system. Comparing the results in the different methods, it is feasible and convenient to apply the condition number to reduce the error in the field mapping calculation. Finally, some guidelines were presented for the magnetic field mapping in the center volume of the air-core solenoid.

• Proceedings of the Korean Printing Society Conference
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• 2000.12a
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• pp.0.3-0
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• 2000

Gamut mapping is a technique that acts on cross-media reproduction to transform a color between devices for the purpose of enhancing the appearance or preserving the appearance of an image. Gamut mapping essentially produces color conversion error which depends the gamut mapping method, source and destination devices, and sample points for gamut modeling. For color space conversion between monitor colors and printer colors, empirical representation using sample measurements is currently widely utilized. Color samples are uniformly selected in the device space such as CMY or RGB, represented as color patches, and then measured. However, in the case of printer, these color samples are not evenly distributed inside the printer gamut and the color conversion error is increased. Accordingly, this paper introduces a equally distributed color sampling method in CIELAB space, a device-independent color space, to reduce color conversion error, and the performance is analyzed via color space conversion experiments using tetrahedral interpolation.

• Journal of the Korean Graphic Arts Communication Society
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• v.19 no.2
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• pp.58-67
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• 2001

Gamut mapping is a technique that acts on cross-media color reproduction to transform a color between devices for the purpose of enhancing the appearance or preserving the appearance of an image. Gamut mapping essentially produces color conversion error which depends the gamut mapping method, source and destination devices, and sample points for gamut modeling. For color space conversion between monitor colors and printer colors, empirical representation using sample measurements is currently widely utilized. Color samples are uniformly selected in the device space such as CMY or RGB, represented as color patches, and then measured. However, in the case of printer, these color samples are not evenly distributed inside the printer gamut and the color conversion error is increased. Accordingly, this paper introduces a equally distributed color sampling method in CIELAB space, a device- independent color space, to reduce color conversion error, and the performance is analyzed via color space conversion experiments using tetrahedral interpolation.

• Nonlinear Functional Analysis and Applications
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• v.29 no.1
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• pp.15-33
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• 2024

In this article, we considered a class of nonlinear variational hemivariational inequality problems and investigated a gap function and regularized gap function for the problems. We discussed the global error bounds for such inequalities in terms of gap function and regularized gap functions by utilizing the Clarke generalized gradient, relaxed monotonicity, and relaxed Lipschitz continuous mappings. Finally, as applications, we addressed an application to non-stationary non-smooth semi-permeability problems.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.9
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• pp.1040-1047
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• 2011

This paper proposes a novel method based on error back propagation neural networks to fuse laser sensor data and ultrasonic sensor data for enhancing the accuracy of mapping. For navigation of single robot, the robot has to know its initial position and accurate environment information around it. However, due to the inherent properties of sensors, each sensor has its own advantages and drawbacks. In our system, the robot equipped with seven ultrasonic sensors and a laser sensor navigates to map two different corridor environments. The experimental results show the effectiveness of the heterogeneous sensor fusion using an error backpropagation algorithm for mapping.

• 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.

• Journal of the Korean Chemical Society
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• v.52 no.4
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• pp.412-422
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• 2008

• Journal of Korean Elementary Science Education
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• v.28 no.3
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• pp.292-303
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• 2009

In this study, we investigated the characteristics of the analogies, the mapping understanding, and the mapping errors on saturated solution of scientifically-gifted and general elementary students. Fifth graders (n=60) at four scientifically-gifted education institutes in Seoul and/or Gyeonggi province and fifth graders (n=91) at three elementary schools in Seoul were selected and assigned to the scientifically-gifted group and the general group respectively. After the students of each group performed the experiment and were taught about the target concept in the first class, they administered the test on the self-generating analogies on the target concept in the second class. The results revealed that the students in the scientifically-gifted group made more analogies, especially verbal/pictorial, structural/functional, enriched, and higher systematic ones, and had deeper understanding of the analogy than those in the general group. The numbers of the shared attributes included in the student-generated analogies and the scores of the mapping understanding of the students in the scientifically-gifted group were significantly higher than those in the general group. The students in the scientifically-gifted group had fewer mapping errors than those in the general group. However, not a few students in the scientifically-gifted group had at least one mapping error. Educational implications of these findings are discussed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.5C
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• pp.432-438
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• 2010

In this paper we study the effect of bit-to-symbol mappings on the convergence behavior of turbo equalizers employing low-density parity-check (LDPC) codes over high order modulations. We analyze the effective SNR of the outputs from linear minimum mean-squared error (MMSE) equalizers and the convergence property of LDPC decoding for different symbol mappings. Numerical results show that the bit-reliability (BR) mapping provides better performance than random mapping in LDPC-coded turbo equalizers over high order modulations. We also verify the effect of symbol mappings through the noise threshold and error performance.