• KIPS Transactions on Computer and Communication Systems
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• v.9 no.8
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• pp.165-170
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• 2020

As the IoT (Internet of Things) era is activated, a lot of information including personal information is being transmitted through IoT devices. For information protection, it is important to perform cryptography communication, and it is required to use a lightweight security protocol due to performance limitations. Currently, most of the encryption methods used in the security protocol use RSA and ECC (Elliptic Curve Cryptography). However, if a high performance quantum computer is developed and the Shor algorithm is used, it can no longer be used because it can easily solve the stability problems based on the previous RSA and ECC. Therefore, in this paper, we designed a security protocol that is resistant to the computational power of quantum computers. The code-based crypto ROLLO, which is undergoing the NIST (National Institute of Standards and Technology) post quantum cryptography standardization, was used, and a hash and XOR computation with low computational consumption were used for mutual communication between IoT devices. Finally, a comparative analysis and safety analysis of the proposed protocol and the existing protocol were performed.

• Journal of Digital Contents Society
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• v.8 no.3
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• pp.279-288
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• 2007

Recently, Baruah et. al. proposed an optimal Pfair scheduling algorithm in the real-time multiprocessor system environments, and several variants of it were presented. All these algorithms assume the fixed unit quantum size. However, under Pfair based scheduling algorithms that are global scheduling technique, quantum size has direct influence on the scheduling overheads such as task switching and cache reload. We proposed a method for deciding the optimal quantum size[2] and an improved method for the task set whose utilization e is less than or equal to $e\;{\leq}\;p/3+1$[3]. However, these methods use repetitive computation of the task's utilization to determine the optimal quantum size. In this paper, we propose a more efficient method that can determine the optimal quantum size in constant time.

• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.1037-1048
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• 2022

A radioactive isotope identification algorithm is a prerequisite for a low-resolution scintillation detector applied to an unmanned radiation monitoring system. In this paper, a sparse representation with dictionary learning approach is proposed and applied to plastic gamma-ray spectra. Label-consistent K-SVD was used to learn a discriminative dictionary for the spectra corresponding to a mixture of four isotopes (¹³³Ba, ²²Na, ¹³⁷Cs, and ⁶⁰Co). A Monte Carlo simulation was employed to produce the simulated data as learning samples. Experimental measurement was conducted to obtain practical spectra. After determining the hyper parameters, two dictionaries tailored to the learning samples were tested by varying with the source position and the measurement time. They achieved average accuracies of 97.6% and 98.0% for all testing spectra. The average accuracy of each dictionary was above 96% for spectra measured over 2 s. They also showed acceptable performance when the spectra were artificially shifted. Thus, the proposed method could be useful for identifying radioisotopes in gamma-ray spectra from a plastic scintillation detector even when a dictionary is adapted to only simulated data. Furthermore, owing to the outstanding properties of sparse representation, the proposed approach can easily be built into an insitu monitoring system.

• Nuclear Engineering and Technology
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• v.56 no.8
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• pp.3347-3358
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• 2024

Addressing the challenge of identifying an appropriate set of material and irradiation parameters for accurate simulation models using crystal plasticity finite element method (CPFEM), this study proposes a novel two-stage method for nano-indentation modeling of ion-irradiated face-centered cubic (FCC) materials. It includes implementing the strain-gradient crystal plasticity (SGCP) theory with irradiation effects and the calibration of simulation parameters using the particle swarm optimization (PSO) algorithm with experimental data. The proposed method consists of two stages: establishing CPFEM without irradiation effects in stage 1 and modeling irradiation effects based on CPFEM in stage 2. Modeling the nano-indentation test of ion-irradiated stainless steel 304 (SS304) using real experimental data is conducted to evaluate the efficiency of the proposed method. The accuracy of the calibration method using PSO is verified through comparisons between simulation and experimental results for force-indentation depth and hardness-indentation depth relationships under both unirradiated and irradiated conditions. Moreover, effect of ion-irradiation on the mechanical behavior during the nano-indentation of single crystal SS304 is also examined to demonstrate that the proposed method is a powerful approach for nano-indentation modeling of ion-irradiated FCC single crystals using SGCP theory and the PSO algorithm.

• Progress in Medical Physics
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• v.28 no.4
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• pp.171-180
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• 2017

The purpose of this study is to install a system that compensated for the respiration motion using an articulated robotic manipulator couch which enables a wide range of motions that a Stewart platform cannot provide and to evaluate the performance of various prediction algorithms including proposed algorithm. For that purpose, we built a miniature couch tracking system comprising an articulated robotic manipulator, 3D optical tracking system, a phantom that mimicked respiratory motion, and control software. We performed simulations and experiments using respiratory data of 12 patients to investigate the feasibility of the system and various prediction algorithms, namely linear extrapolation (LE) and double exponential smoothing (ES2) with averaging methods. We confirmed that prediction algorithms worked well during simulation and experiment, with the ES2-averaging algorithm showing the best results. The simulation study showed 43% average and 49% maximum improvement ratios with the ES2-averaging algorithm, and the experimental study with the $QUASAR^{TM}$ phantom showed 51% average and 56% maximum improvement ratios with this algorithm. Our results suggest that the articulated robotic manipulator couch system with the ES2-averaging prediction algorithm can be widely used in the field of radiation therapy, providing a highly efficient and utilizable technology that can enhance the therapeutic effect and improve safety through a noninvasive approach.

• Journal of the Optical Society of Korea
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• v.14 no.3
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• pp.221-227
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• 2010

Aerosol size distribution provides good information for predicting weather changes and understanding cloud formation. Aerosol extinction coefficient and backscattering coefficient are measured by many scientists, but these parameters depend not only on aerosol size but on aerosol concentrations. An algorithm has been developed to measure aerosol parameters such as ${\AA}$ngstr$\ddot{o}$m exponent, color ratio, and LIDAR ratio without any assumptions by using two wavelength rotational Raman LIDAR signals. These parameters are good indicators for the aerosol size. And we can find ${\AA}$ngstr$\ddot{o}$m exponent, color ratio, and LIDAR ratio under various weather conditions. Finally, it can be seen that the ${\AA}$ngstr$\ddot{o}$m exponent has an inverse relationship to the particle size of the aerosol and the color ratio is linearly dependent on the aerosol size. An ${\AA}$ngstr$\ddot{o}$m exponent from 1.2 to 3.1, a color ratio from 0.28 to 1.04, and a LIDAR ratio 66.9 sr at 355 nm and 32.6 sr at 532 nm near the cloud were obtained.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.573-575
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• 2019

Recently, augmented reality (AR) technology has been widely used in a variety of fields such as defense, medical, education, and entertainment. In the augmented reality environment, a user can interact a virtual object by the user 's specific behaviors. Also, it is necessary to use a technique to automatically interacts among the generated virtual objects. In this paper, we propose an authoring model to apply augmented reality environments based on quantum computing inspired entanglement and overlapping phenomenon. For example, it is possible to allow the user to automatically increase and decrease the number of the object with the characteristics of the virtual object without user intervention. As a tested platform for this purpose, this paper provide an augmented reality eco-system environment with automatic interaction among virtual animals.

• Journal of Biomedical Engineering Research
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• v.9 no.1
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• pp.61-66
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• 1988

Because the amount of radiation emerging from the thorax behind the lungs is often literally thousands of times that exiting behind the mediastinum, the dynamic range of X-ray chest image is very large. In order to solve the dynamic range problem, we propose a signal adaptive algorithm which enhances the local contrast and contracts the enhancement of quantum noise by local mean/valiance estimator.

• Bulletin of the Korean Chemical Society
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• v.22 no.4
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• pp.388-394
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• 2001

Quantitative Structure-Activity Relationship (QSAR) have been established of 57 fluorovinyloxyacetamides compounds to correlate and predict EC50 values. Genetic algorithm (GA) and multiple linear regression analysis were used to select the descriptors and to generate the equations that relate the structural features to the biological activities. This equation consists of three descriptors calculated from the molecular structures with molecular mechanics and quantum-chemical methods. The results of MLR and GA show that dipole moment of z-axis, radius of gyration and logP play an important role in growth inhibition of barnyard grass.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.3
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• pp.463-471
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• 2021

Since 2016, National Institute of Standards and Technology (NIST) has been conducting a post quantum cryptography standardization project in preparation for a quantum computing environment. Three rounds are currently in progress, and most of the candidates (5/7) are lattice-based. Lattice-based post quantum cryptography is evaluated to be applicable even in an embedded environment where resources are limited by providing efficient operation processing and appropriate key length. Among them, SABER KEM provides the efficient modulus and Toom-Cook to process polynomial multiplication with computation-intensive tasks. In this paper, we present the optimized implementation of evaluation and interpolation in Toom-Cook algorithm of SABER utilizing ARM/NEON in ARMv8-A platform. In the evaluation process, we propose an efficient interleaving method of ARM/NEON, and in the interpolation process, we introduce an optimized implementation methodology applicable in various embedded environments. As a result, the proposed implementation achieved 3.5 times faster performance in the evaluation process and 5 times faster in the interpolation process than the previous reference implementation.