• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2497-2517
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• 2020

For compressed sensing (CS) applications, it is significant to construct deterministic measurement matrices with good practical features, including good sensing performance, low memory cost, low computational complexity and easy hardware implementation. In this paper, a deterministic construction method of bipolar measurement matrices is presented based on binary sequence family (BSF). This method is of interest to be applied for sparse signal restore and image block CS. Coherence is an important tool to describe and compare the performance of various sensing matrices. Lower coherence implies higher reconstruction accuracy. The coherence of proposed measurement matrices is analyzed and derived to be smaller than the corresponding Gaussian and Bernoulli random matrices. Simulation experiments show that the proposed matrices outperform the corresponding Gaussian, Bernoulli, binary and chaotic bipolar matrices in reconstruction accuracy. Meanwhile, the proposed matrices can reduce the reconstruction time compared with their Gaussian counterpart. Moreover, the proposed matrices are very efficient for sensing performance, memory, complexity and hardware realization, which is beneficial to practical CS.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.83.1-83.1
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• 2012

The galaxy cluster is a good laboratory to test the cosmological model as well as the evolution of galaxies in the dense region. However the lack of wide and deep near-IR datasets has prevented to identify galaxy clusters at z>1. Here we merge a wide, deep near-IR datasets of UKIDSS DXS (J and K bands) and IMS (J band) with the CFHT Legacy Survey (CFHTLS) ugriz catalogue to detect galaxy clusters. We identify candidate galaxy clusters at z>0.8, where the near-IR dataset plays an important role to detect galaxies efficiently. The cluster mass is also estimated based on the cluster richness and the semi-analytical cosmological simulation.

• Nuclear Engineering and Technology
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• v.53 no.12
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• pp.4067-4071
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• 2021

The ¹³C (α,n)¹⁶O reaction cross-section is important data for nuclear physics, astrophysical, and neutrino physics experiments, however, they exhibit uncertainties due to the discrepancies in the experimental data. In this study, using the Nedis-2m program code, the energy spectrum of α-induced neutrons in a thin carbon target was calculated and the corresponding reaction cross-section was refined in the alpha particle energy range of 5-8 MeV. The results were used to calculate the intensity and energy spectrum of background neutrons produced in the liquid scintillator of KamLAND. The results will be useful in a variety of astrophysical and neutrino experiments especially those based on LS or Gd-LS detectors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4645-4664
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• 2019

It is significant to construct deterministic measurement matrices with easy hardware implementation, good sensing performance and good cryptographic property for practical compressed sensing (CS) applications. In this paper, a deterministic construction method of bipolar chaotic measurement matrices is presented based on binary sequence family (BSF) and Chebyshev chaotic sequence. The column vectors of these matrices are the sequences of BSF, where 1 is substituted with -1 and 0 is with 1. The proposed matrices, which exploit the pseudo-randomness of Chebyshev sequence, are sensitive to the initial state. The performance of proposed matrices is analyzed from the perspective of coherence. Theoretical analysis and simulation experiments show that the proposed matrices have limited influence on the recovery accuracy in different initial states and they outperform their Gaussian and Bernoulli counterparts in recovery accuracy. The proposed matrices can make the hardware implement easy by means of linear feedback shift register (LFSR) structures and numeric converter, which is conducive to practical CS.

• Journal of the Korean Society of Visualization
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• v.21 no.1
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• pp.119-126
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• 2023

Acquiring experimental data for PIV verification or machine learning training data is resource-demanding, leading to an increasing interest in synthetic particle images as simulation data. Conventional synthetic particle image generation algorithms do not follow physical laws, and the use of CFD is time-consuming and requires computing resources. In this study, we propose a new method for synthetic particle image generation, based on a Physics-Informed Neural Networks(PINN). The PINN is utilized to infer the flow fields, enabling the generation of synthetic particle images that follow physical laws with reduced computation time and have no constraints on spatial resolution compared to CFD. The proposed method is expected to contribute to the verification of PIV algorithms.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.10
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• pp.479-486
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• 2017

Recently, GPGPU has been able to increase the degradation of computer performance, and it is now possible to run physically based real-time simulations on PCs that require high computational complexity. Physical calculations applied in physics simulation can be performed by parallel processing, and can be efficiently performed using parallel computation using Compute shader recently supported by OpenGL 4.3 and Unity 4.0. In this paper, we measure and compare the number of performance in real - time physics simulation in OpenGL running on various platforms and Unity, a content creation tool supporting various platforms. Particle simulation experiments show that particle simulation using Unity performs faster than 136.04%. It is expected that it will be able to select better development tools for future multi - platform support.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.11_12
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• pp.692-704
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• 2005

With the improvement of computer hardware, GPUs(Graphics Processor Units) have tremendous memory bandwidth and computation power. This leads GPUs to use in general purpose computation. Especially, GPU implementation of compute-intensive physics based simulations is actively studied. In the solution of differential equations which are base of physics simulations, tridiagonal matrix systems occur repeatedly by finite-difference approximation. From the point of view of physics based simulations, fast solution of tridiagonal matrix system is important research field. We propose a fast GPU implementation for the solution of tridiagonal matrix systems. In this paper, we implement the cyclic reduction(also known as odd-even reduction) algorithm which is a popular choice for vector processors. We obtained a considerable performance improvement for solving tridiagonal matrix systems over Thomas method and conjugate gradient method. Thomas method is well known as a method for solving tridiagonal matrix systems on CPU and conjugate gradient method has shown good results on GPU. We experimented our proposed method by applying it to heat conduction, advection-diffusion, and shallow water simulations. The results of these simulations have shown a remarkable performance of over 35 frame-per-second on the 1024x1024 grid.

• Nuclear Engineering and Technology
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• v.54 no.10
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• pp.3604-3613
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• 2022

The Physical Protection System (PPS) plays an important role and must effectively deal with various adversary attacks in nuclear security. In specific single adversary path scenarios, we can calculate the PPS effectiveness by EASI (Estimated Adversary Sequence Interruption) through Probability of Interruption (P_I) calculation. EASI uses a single value of the probability of detection (P_D) and the probability of alarm communications (P_C) in the PPS. In this study, we develop a multi-path analysis code based on EASI to evaluate the effectiveness of PPS. Our quantification method for P_I considers the variability and uncertainty of P_D and P_C value by Monte Carlo simulation. We converted the 2-D scheme of the nuclear facility into an Adversary Sequence Diagram (ASD). We used ASD to find the adversary path with the lowest probability of interruption as the most vulnerable paths (MVP). We examined a hypothetical facility (Hypothetical National Nuclear Research Facility - HNNRF) to confirm our code compared with EASI. The results show that implementing the variability extension can estimate the P_I value and its associated uncertainty. The multi-path analysis code allows the analyst to make it easier to assess PPS with more extensive facilities with more complex adversary paths. However, the variability of the P_D value in each protection element allows a significant decrease in the PI value. The possibility of this decrease needs to be an important concern for PPS designers to determine the P_D value correctly or set a higher standard for PPS performance that remains reliable.

• Journal of Korea Game Society
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• v.17 no.1
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• pp.89-98
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• 2017

This paper presents a novel ARAP (as-rigid-as-possible) approach to real-time simulation of physics-based deformation. To cope with one, two and three dimensional deformable bodies in an efficient, robust and uniform manner, we introduce a deformation graph of oriented particles and formulate the corresponding ARAP deformation energy. For stable time integration of the oriented particles, we develop an implicit integration scheme formulated in a variational form. Our method seeks the optimal positions and rotations of the oriented particles by iteratively applying an alternating local/global optimization scheme. The proposed method is easy to implement and computationally efficient to simulate complex deformable models in real time.

• Journal of IKEEE
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• v.17 no.3
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• pp.221-228
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• 2013

About functional parameters of a LED/UVLED (Light Emitting Diode/Ultra Violet LED), one of the most important parameters is the I-V characteristic. By researching factors affect to the I-V characteristic of uvled, we found that beside of the structure of the device itself, there is the influence of the electrode materials, electrode shapes, the process of wiring and packaging. In this work, we want to improve the performance of UVLED to find out the optimal mask design principles. The study is based on theoretical mathematical models, as well as the use of simulation software tool Comsol. From all results obtained, the team has improved mask design to manufacture electrodes for GaN-based UVLED. Electrode masks are designed by three softwares, which are Intellisuite, Klayout and AutoCad. Intellisuite masks would be used in fabrication simulation while Klayout and AutoCad are used to fabricate electrodes in experiments. As well as, we silmulated the structure of an uvled 355nm emission wavelength by TCAD software, in order to compare with uvled sample that has the same emission wavelength.