• The Journal of Korea Robotics Society
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• v.16 no.3
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• pp.189-198
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• 2021

In this paper, we introduce the software/hardware system that can reliably calculate the distance from sensor to the model regardless of point cloud density. As the 3d point cloud map is widely adopted for SLAM and computer vision, the accuracy of point cloud map is of great importance. However, the 3D point cloud map obtained from Lidar may reveal different point cloud density depending on the choice of sensor, measurement distance and the object shape. Currently, when measuring map accuracy, high reflective bands are used to generate specific points in point cloud map where distances are measured manually. This manual process is time and labor consuming being highly affected by Lidar sparsity level. To overcome these problems, this paper presents a hardware design that leverage high intensity point from three planar surface. Furthermore, by calculating distance from sensor to the device, we verified that the automated method is much faster than the manual procedure and robust to sparsity by testing with RGB-D camera and Lidar. As will be shown, the system performance is not limited to indoor environment by progressing the experiment using Lidar sensor at outdoor environment.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.157-164
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• 2021

The aim of this study is to provide empirical evaluation of the accuracy of data-model fit using growing levels of invariance models. Overall model accuracy of factor solutions was evaluated by the examination of the order for testing three levels of measurement invariance (MIV) starting with configural invariance (model 0). Model testing was evaluated by the Chi-square difference test (∆𝛘²) between two groups, and root mean square error of approximation (RMSEA), comparative fit index (CFI), and Tucker-Lewis index (TLI) were used to evaluate the all-model fits. Factorial invariance result revealed that stability of the models was varying over increasing levels of measurement as a function of variable-to-factor ratio (VTF), subject-to-variable ratio (STV), and their interactions. There were invariant factor loadings and invariant intercepts among the groups indicating that measurement invariance was achieved. For VTF ratio (3:1, 6:1, and 9:1), the models started to show accuracy over levels of measurement when STV ratio was 6:1. Yet, the frequency of stability models over 1000 replications increased (from 69% to 89%) as STV ratio increased. The models showed more accuracy at or above 39:1 STV.

• Journal of Astronomy and Space Sciences
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• v.35 no.4
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• pp.263-277
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• 2018

This paper presents a vision-based relative pose estimation algorithm and its validation through both numerical and hardware experiments. The algorithm and the hardware system were simultaneously designed considering actual experimental conditions. Two estimation techniques were utilized to estimate relative pose; one was a nonlinear least square method for initial estimation, and the other was an extended Kalman Filter for subsequent on-line estimation. A measurement model of the vision sensor and equations of motion including nonlinear perturbations were utilized in the estimation process. Numerical simulations were performed and analyzed for both the autonomous docking and formation flying scenarios. A configuration of LED-based beacons was designed to avoid measurement singularity, and its structural information was implemented in the estimation algorithm. The proposed algorithm was verified again in the experimental environment by using the Autonomous Spacecraft Test Environment for Rendezvous In proXimity (ASTERIX) facility. Additionally, a laser distance meter was added to the estimation algorithm to improve the relative position estimation accuracy. Throughout this study, the performance required for autonomous docking could be presented by confirming the change in estimation accuracy with respect to the level of measurement error. In addition, hardware experiments confirmed the effectiveness of the suggested algorithm and its applicability to actual tasks in the real world.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.123-130
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• 2018

Triangulation is one of the fundamental problems in computational geometry and computer graphics community, and it has huge application areas such as 3D printing, computer-aided engineering, surface reconstruction, surface visualization, and so on. The Delaunay refinement algorithm is a well-known method to generate quality triangular meshes when point cloud and/or constrained edges are given in two- or three-dimensional space. In this paper, we propose a simple but efficient algorithm to triangulate Voronoi surfaces of Voronoi diagram of spheres in 3-dimensional Euclidean space. The proposed algorithm is based on the Ruppert's Delaunay refinement algorithm, and we modified the algorithm to be applied to the triangulation of Voronoi surfaces in two ways. First, a new method to deciding the location of a newly added vertex on the surface in 3-dimensional space is proposed. Second, a new efficient but effective way of estimating approximation error between Voronoi surface and triangulation. Because the proposed algorithm generates a triangular mesh for Voronoi surfaces with guaranteed quality, users can control the level of quality of the resulting triangulation that their application problems require. We have implemented and tested the proposed algorithm for random non-intersecting spheres, and the experimental result shows the proposed algorithm produces quality triangulations on Voronoi surfaces satisfying the quality criterion.

• Journal of the Korean Solar Energy Society
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• v.39 no.4
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• pp.55-67
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• 2019

Recently, as the amount of particulate matter blowing from China increases, the domestic air environment is rapidly deteriorating. This pollution of the atmosphere greatly affects the light energy reaching the ground. Particularly, since the light enters the solar cell module in various forms, the amount of input energy of the solar power generation system may be changed depending on the ratio of direct beam irradiation and diffused horizontal irradiation. In this paper, we analyze how the ratio of direct beam component and diffused component on global horizontal irradiation varies with the atmospheric conditions. In addition, the reliability of the regression equation, designed to decompose the global horizontal irradiation into horizontal direct beam irradiation and diffused horizontal irradiation, was verified according to the level of air pollution. So, we derive the most suitable decomposition model for use in domestic climatic conditions in Korea by comparing the ratio of direct and diffuse component on the horizontal which is calculated with Perez model and Watanabe model using the meteorological weather data observed for 14 months. Finally, to reduce the error of the transposition result, we verified the reliability of the decomposition which depends on the atmospheric environment.

• Journal of Ocean Engineering and Technology
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• v.33 no.4
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• pp.330-339
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• 2019

Radiant heat shields are normally installed on offshore oil and gas platforms to protect personnel, equipment, and structures from the thermal radiation emitted by a flare system. A heat shield should be individually designed to reduce the thermal radiation to the target level, and then manufactured and installed after the performance verification. However, in general, a heat shield is designed and manufactured by trial and error based on the performance test. For this reason, it is difficult to develop and design radiant heat shields in the Korean shipbuilding and marine equipment industry because of the lack of performance test data and limited experience. In the present study, the results of experiments conducted to verify the performances of radiant heat shields were analyzed, and the thermal radiation characteristics and performance characteristics of the radiant heat shields were investigated. The insights and conclusions developed in the present study will be useful in terms of the design and development of radiant heat shield, as well as in their performance verification tests.

• BMB Reports
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• v.52 no.9
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• pp.540-547
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• 2019

Immune repertoire is a collection of enormously diverse adaptive immune cells within an individual. As the repertoire shapes and represents immunological conditions, identification of clones and characterization of diversity are critical for understanding how to protect ourselves against various illness such as infectious diseases and cancers. Over the past several years, fast growing technologies for high throughput sequencing have facilitated rapid advancement of repertoire research, enabling us to observe the diversity of repertoire at an unprecedented level. Here, we focus on B cell receptor (BCR) repertoire and review approaches to B cell isolation and sequencing library construction. These experiments should be carefully designed according to BCR regions to be interrogated, such as heavy chain full length, complementarity determining regions, and isotypes. We also highlight preprocessing steps to remove sequencing and PCR errors with unique molecular index and bioinformatics techniques. Due to the nature of massive sequence variation in BCR, caution is warranted when interpreting repertoire diversity from error-prone sequencing data. Furthermore, we provide a summary of statistical frameworks and bioinformatics tools for clonal evolution and diversity. Finally, we discuss limitations of current BCR-seq technologies and future perspectives on advances in repertoire sequencing.

• International Journal of Internet, Broadcasting and Communication
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• v.11 no.3
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• pp.106-110
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• 2019

The interaural level difference (ILD) used for the sound localization using stereo signals is to find the difference in energy that the sound source reaches both ears. The conventional ILD does not consider the time difference of the stereo signals, which is a factor of lowering the accuracy. In this paper, we propose a synchronized ILD that obtains the ILD after synchronizing these time differences. This method uses the cross-correlation function (CCF) to calculate the time difference to reach both ears and use it to obtain synchronized ILD. In order to prove the performance of the proposed method, we conducted two sound localization experiments. In each experiment, the synchronized ILD and CCF or only the synchronized ILD were given as inputs of the deep neural networks (DNN), respectively. In this paper, we evaluate the performance of sound localization with mean error and accuracy of sound localization. Experimental results show that the proposed method has better performance than the conventional methods.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.2
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• pp.58.2-58.2
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• 2018

Theoretically, the magnetic helicity transport flux through the solar surface into the upper atmosphere can be estimated indefinitely precisely by magnetic field footpoint tracking if the observational resolution is infinitely fine, even with magnetic flux emergence or submergence. In reality, the temporal and spatial resolutions of observations are limited. When magnetic flux emerging or submerging, the footpoint velocity goes to infinity and the normal magnetic field vanishes at the polarity inversion line. A finite observational resolution thus generates a blackout area in helicity flux estimation near the polarity inversion line. It is questioned how much magnetic helicity is underestimated with a footpoint tracking method due to the absence of information in the blackout area. We adopt the analytical models of Gold-Hoyle and Lundquist force-free flux ropes and let them emerging from below the solar surface. The observation and the helicity integration can start at different emerging stages of the flux rope, i.e., the photospheric plane initially cuts the flux rope at different levels. We calculate the magnetic helicity of the flux rope below the photospheric level, which is eventually to emerge, except the helicity hidden in the region to be swept by the blackout area with different widths. Our calculation suggests that the error in the integrated helicity flux estimate is about half of the real value or even larger when small scale magnetic structures emerge into the solar atmosphere.

• The Journal of the Acoustical Society of Korea
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• v.38 no.3
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• pp.283-289
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• 2019

RLS (Recursive-least-squares) algorithm is known to have good convergence and excellent error level after convergence. However, there is a disadvantage that numerical instability is included in the algorithm due to inverse matrix calculation. In this paper, we propose an algorithm with no matrix inversion to avoid the instability aforementioned. The proposed algorithm still keeps the same convergence performance. In the proposed algorithm, we adopt an averaged gradient-based step size as a self-adjusted step size. In addition, a variable forgetting factor is introduced to provide superior performance for time-varying channel estimation. Through simulations, we compare performance with conventional RLS and show its equivalency. It also shows the merit of the variable forgetting factor in time-varying channels.