• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.6
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• pp.1045-1057
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• 2022

Recently, the National Institute of Standards and Technology (NIST) announced four cryptographic algorithms as a standard candidates of Post-Quantum Cryptography (PQC). In this paper, we show that private key can be exposed by a non-profiling-based power analysis attack such as Correlation Power Analysis (CPA) and Differential Deep Learning Analysis (DDLA) on CRYSTALS-KYBER algorithm, which is decided as a standard in the PKE/KEM field. As a result of experiments, it was successful in recovering the linear polynomial coefficient of the private key. Furthermore, the private key can be sufficiently recovered with a 13.0 Normalized Maximum Margin (NMM) value when Hamming Weight of intermediate values is used as a label in DDLA. In addition, these non-profiling attacks can be prevented by applying countermeasures that randomly divides the ciphertext during the decryption process and randomizes the starting point of the coefficient-wise multiplication operation.

• Korean Journal of Optics and Photonics
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• v.7 no.3
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• pp.272-279
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• 1996

A simple transfer matrix algorithm to analyze the properties of 2 dimensional waveguides is introduced. We applied this algorithm to strained InGaAs/InGaAsP GINSCH MQW laser structures. We studied how optical confinement factor and effective refractive index, which are important in calculating the modal gain, depend on the structure parameters such as waveguide width, shape of GRIN, and number of quantum wells. Especially we suggested that the concept of effective waveguide width is very useful in understanding the GRINSCH waveguide.

• Journal of Electrical Engineering and Technology
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• v.9 no.5
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• pp.1670-1676
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• 2014

This paper presents the modeling of Single Electron Transistor (SET) based on Physical model of a device and its equivalent circuit. The physical model is derived from Schrodinger equation. The wave function of the electrode is calculated using Hartree-Fock method and the quantum dot calculation is obtained from WKB approximation. The resulting wave functions are used to compute tunneling rates. From the tunneling rate the current is calculated. The equivalent circuit model discuss about the effect of capacitance on tunneling probability and free energy change. The parameters of equivalent circuit are extracted and optimized using genetic algorithm. The effect of tunneling probability, temperature variation effect on tunneling rate, coulomb blockade effect and current voltage characteristics are discussed.

• Korean Journal of Optics and Photonics
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• v.28 no.4
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• pp.166-171
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• 2017

Hydrogen gas is a green energy sources because it features no emission of pollutants during combustion. But hydrogen gas is very dangerous, being flammable and very explosive. Hydrogen gas detection is very important for the safety of a nuclear power plant. Hydrogen gas is generated by oxidation of nuclear fuel cladding during a critical accident, and leads to serious secondary damage in the containment building. This paper discusses the development of a Raman lidar system for remote detection and measurement of hydrogen gas. A small, portable Raman lidar system was designed, and a measurement algorithm was developed to quantitatively measure hydrogen gas concentration. To verify the capability of measuring hydrogen gas with the developed Raman lidar system, experiments were carried out under daytime outdoor conditions by using a gas chamber that can adjust the hydrogen gas density. As results, our Raman lidar system is able to measure a minimum density of 0.67 vol. % hydrogen gas at a distance of 20 m.

• Journal of the Korean Society for Nondestructive Testing
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• v.25 no.5
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• pp.391-399
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• 2005

Laser-generated ultrasonic inspection system is a non-contact scanning inspection device with high spatial resolution and wide bandwidth. The amplitude of laser-generated ultrasound is varied according to the energy of pulse laser and the surface conditions of an object where the CW measuring laser beam is pointing. In this paper, we correct the generating errors by measuring the energy of pulse laser beam and correct the measuring errors by extracting the gain information of laser interferometer at each time. h dynamic stabilizer is developed to stably scan on the surface of an object for an laser-generated ultrasonic inspection system. The developed system generates ultrasound after adaptively finding the maximum gain time of an laser interferometer and processes the signal in real time after digitization with high speed. In this paper, we describe hardware configuration and control algorithm to build a stable laser-generated ultrasonic inspection system. Also, we confirmed through experiments that the proposed correction method for the generating errors and measuring errors is effective to improve the performance of a system.

• Journal of the Korean Society for Nondestructive Testing
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• v.22 no.5
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• pp.465-473
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• 2002

Images are easily corrupted by noise during the data transmission, data capture and data processing. A technical method of noise analyzing and adaptive filtering for reducing of quantum noise in radiography is presented. By adjusting the characteristics of the filter according to local statistics around each pixel of the image as moving windowing, it is possible to suppress noise sufficiently while preserve edge and other significant information required in reading. We have proposed adaptive weighted median(AWM) filters based on local statistics. We show two ways of realizing the AWM filters. One is a simple type of AWM filter, whose weights are given by a simple non-linear function of three local characteristics. The other is the AWM filter which is constructed by homogeneous factor(HF). Homogeneous factor(HF) from the quantum noise models that enables the filter to recognize the local structures of the image is introduced, and an algorithm for determining the HF fitted to the detection systems with various inner statistical properties is proposed. We show by the experimented that the performances of proposed method is superior to these of other filters and models in preserving small details and suppressing the noise at homogeneous region. The proposed algorithms were implemented by visual C++ language on a IBM-PC Pentium 550 for testing purposes, the effects and results of the noise filtering were proposed by comparing with images of the other existing filtering methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.6C
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• pp.570-579
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• 2003

The performance of turbo codes is investigated in the direct detection optical PPM channel. We assume that an ideal photon counter is used as an optical detector and that the channel has background noise as well as quantum noise. Resulting channel model is M-ary PPM Poisson channel. We propose the structure of the transmitter and receiver for applying turbo codes to this channel. We also derive turbo decoding algorithm for the proposed coding system, by modifying the calculation of the branch metric inherent in the original turbo decoding algorithm developed for the AWGN channel. Analytical bounds are derived and computer simulation is performed to analyze the performance of the proposed coding scheme, and the results are compared with the performances of Reed-Solomon codes and convolutional codes.

• Current Optics and Photonics
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• v.6 no.1
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• pp.92-103
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• 2022

The development of midinfrared (mid-IR) quantum cascade lasers (QCLs) has enabled rapid high-contrast measurement of the mid-IR spectra of biological tissues. Several studies have compared the differences between the mid-IR spectra of colon cancer and noncancerous colon tissues. Most mid-IR spectrum classification studies have been proposed as machine-learning-based algorithms, but this results in deviations depending on the initial data and threshold values. We aim to develop a process for classifying colon cancer and noncancerous colon tissues through a deep-learning-based convolutional-neural-network (CNN) model. First, we image the midinfrared spectrum for the CNN model, an image-based deep-learning (DL) algorithm. Then, it is trained with the CNN algorithm and the classification ratio is evaluated using the test data. When the tissue microarray (TMA) and routine pathological slide are tested, the ML-based support-vector-machine (SVM) model produces biased results, whereas we confirm that the CNN model classifies colon cancer and noncancerous colon tissues. These results demonstrate that the CNN model using midinfrared-spectrum images is effective at classifying colon cancer tissue and noncancerous colon tissue, and not only submillimeter-sized TMA but also routine colon cancer tissue samples a few tens of millimeters in size.

• Computers and Concrete
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• v.30 no.2
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• pp.127-141
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• 2022

In this paper, a numerical procedure is proposed for achieving the minimum cost design of reinforced concrete polygonal column cross-sections under compression and biaxial bending. A methodology is developed to integrate the metaheuristic algorithm Quantum Particle Swarm Optimization (QPSO) with an algorithm for the evaluation of the strength of reinforced concrete cross-sections under combined axial load and biaxial bending, according to the design criteria of Brazilian Standard ABNT NBR 6118:2014. The objective function formulation takes into account the costs of concrete, reinforcement, and formwork. The cross-section dimensions, the number and diameter of rebar and the concrete strength are taken as discrete design variables. This methodology is applied to polygonal cross-sections, such as rectangular sections, rectangular hollow sections, and L-shaped cross-sections. To evaluate the efficiency of the methodology, the optimal solutions obtained were compared to results reported by other authors using conventional methods or alternative optimization techniques. An additional study investigates the effect on final costs for an alternative parametrization of rebar positioning on the cross-section. The proposed optimization method proved to be efficient in the search for optimal solutions, presenting consistent results that confirm the importance of using optimization techniques in the design of reinforced concrete structures.

• Nuclear Engineering and Technology
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• v.56 no.5
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• pp.1654-1666
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• 2024

The goal of this research is to propose a way to maximize small modular reactor (SMR) utilization to gain better market feasibility in support of carbon neutrality. For that purpose, a comprehensive tool was developed, combining off-design thermohydraulic models, economic objective models (levelized cost of electricity, annual profit), non-economic models (saved CO2), a parameter input sampling method (Latin hypercube sampling, LHS), and a multi-objective evolutionary algorithm (Non-dominated Sorting Algorithm-2, NSGA2 method) for optimizing a SMR-combined heat and power cycle (CHP) system design. Considering multiple objectives, it was shown that NSGA2+LHS method can find better optimal solution sets with similar computational costs compared to a conventional weighted sum (WS) method. Out of multiple multi-objective optimal design configurations for a 105 MWe design generation rating, a chosen reference SMR-CHP system resulted in its levelized cost of electricity (LCOE) below $60/MWh for various heat prices, showing economic competitiveness for energy market conditions similar to South Korea. Examined economic feasibility may vary significantly based on CHP heat prices, and extensive consideration of the regional heat market may be required for SMR-CHP regional optimization. Nonetheless, with reasonable heat market prices (e.g. district heating prices comparable to those in Europe and Korea), SMR can still become highly competitive in the energy market if coupled with a CHP system.