• 한국산업융합학회 논문집
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• 제24권5호
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• pp.635-639
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• 2021

As times goes by, a ton of electric devices have been developing. Nowadays, there are many personal electric goods that are connected each other and have important private information such as identification, account number, passwords, and so on. As many people own at least one electric device, security of the electric devices became significant. To prevent leakage of the information, study of Chaotic TRNG, "Chaotic True Random Number Generator", protecting the information by generating random numbers that are not able to be expected, is essential. In this paper, A chaotic TRNG is introduced is simulated. The proposed Chaotic TRNG is simulated with Virtuoso &, a circuit design program of Cadence that is a software company. For simulating the mentioned Chaotic TRNG, setting values, 0V low and 3V high on Vpulse, 1.2V on V-ref, 3.3V on VDD, and 0V on VSS, are used.

• Nuclear Engineering and Technology
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• 제53권11호
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• pp.3711-3716
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• 2021

The addition of ferric ferrocyanide (Prussian blue; PB) to adsorbents could enhance the adsorption performance of ¹³³Cs. Toward this goal, we present a heterogeneously integrated carbonaceous material platform consisting of PB in direct contact with CO₂-activated carbon filters (PB-CACF). The resulted sample retains 24.39% more PB than vice versa probed by the ultraviolet-visible spectrometer. We leverage this effect to capture ¹³³Cs in the aqueous environment via the increase in ionic strength and micropores. We note that the amount of PB was likely to be the key factor for ¹³³Cs adsorption compared with specific surface characteristics. The revealed adsorption capacity of PB-CACF was 21.69% higher than the bare support. The adsorption characteristics were feasible and spontaneous. Positive values of 𝜟H^o and 𝜟S^o show the endothermic nature and increased randomness. Based on the concept of capturing hazardous materials via hazardous materials, our work will be of interest within the relevant academia for collecting radionuclides in a sufficient manner.

• Geomechanics and Engineering
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• 제18권6호
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• pp.661-668
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• 2019

Seismic vulnerability assessment is a useful tool for rational safety analysis and planning of large and complex structural systems; it can deal with the effects of uncertainties on the performance of significant structural systems. In this study, an efficient dynamic reliability approach, probability density evolution methodology (PDEM), is proposed for seismic vulnerability analysis of earth dams. The PDEM provides the failure probability of different limit states for various levels of ground motion intensity as well as the mean value, standard deviation and probability density function of the performance metric of the earth dam. Combining the seismic reliability with three different performance levels related to the displacement of the earth dam, the seismic fragility curves are constructed without them being limited to a specific functional form. Furthermore, considering the seismic fragility analysis is a significant procedure in the seismic probabilistic risk assessment of structures, the seismic vulnerability results obtained by the dynamic reliability approach are combined with the results of probabilistic seismic hazard and seismic loss analysis to present and address the PDEM-based seismic probabilistic risk assessment framework by a simulated case study of an earth dam.

• Structural Engineering and Mechanics
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• 제71권2호
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• pp.165-173
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• 2019

This paper investigates the probability of failure of reinforced concrete beams for limit state of collapse for flexure and shear. The influence of randomness of the variables on the failure probability is also examined. The Indian standard code for plain and reinforced concrete IS456:2000 is used for the design of beams. Probabilistic models are developed for flexure and shear according to IS456:2000. The loads considered acting on the beam are live load and dead load only. Random variables associated with the limit state equation such as grade of concrete, grade of steel, live load and dead load are identified. Probability of failure is evaluated based on the limit state equation using First Order Reliability Method (FORM). Importance of the random variables on the limit state equations are observed and the variables are accordingly reduced. The effect of the reduced parameters is checked on the probability of failure. The results show the role of each parameter on the design of beam. Thus, the Indian standard guidelines for plain and reinforced concrete IS456:2000 is investigated with the probabilistic and risk-based analysis and design for a simple beam. The results obtained are also compared with the literature and accordingly some suggestions are made.

• Journal of Information Processing Systems
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• 제15권2호
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• pp.288-304
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• 2019

The growth of telemedicine-based wireless communication for images-magnetic resonance imaging (MRI) and computed tomography (CT)-leads to the necessity of learning the concept of image compression. Over the years, the transform based and spatial based compression techniques have attracted many types of researches and achieve better results at the cost of high computational complexity. In order to overcome this, the optimization techniques are considered with the existing image compression techniques. However, it fails to preserve the original content of the diagnostic information and cause artifacts at high compression ratio. In this paper, the concept of histogram based multilevel thresholding (HMT) using entropy is appended with the optimization algorithm to compress the medical images effectively. However, the method becomes time consuming during the measurement of the randomness from the image pixel group and not suitable for medical applications. Hence, an attempt has been made in this paper to develop an HMT based image compression by utilizing the opposition based improved harmony search algorithm (OIHSA) as an optimization technique along with the entropy. Further, the enhancement of the significant information present in the medical images are improved by the proper selection of entropy and the number of thresholds chosen to reconstruct the compressed image.

• Journal of Information Processing Systems
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• 제14권6호
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• pp.1385-1397
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• 2018

There are many factors that affect the wind speed. In addition, the randomness of wind speed also leads to low prediction accuracy for wind speed. According to this situation, this paper constructs the short-time forecasting model based on the least squares support vector machines (LSSVM) to forecast the wind speed. The basis of the model used in this paper is support vector regression (SVR), which is used to calculate the regression relationships between the historical data and forecasting data of wind speed. In order to improve the forecast precision, historical data is clustered by cluster analysis so that the historical data whose changing trend is similar with the forecasting data can be filtered out. The filtered historical data is used as the training samples for SVR and the parameters would be optimized by particle swarm optimization (PSO). The forecasting model is tested by actual data and the forecast precision is more accurate than the industry standards. The results prove the feasibility and reliability of the model.

• Nuclear Engineering and Technology
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• 제50권8호
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• pp.1306-1313
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• 2018

The randomness and incipient nature of certain faults in reactor systems warrant a robust and dynamic detection mechanism. Existing models and methods for fault diagnosis using different mathematical/statistical inferences lack incipient and novel faults detection capability. To this end, we propose a fault diagnosis method that utilizes the flexibility of data-driven Support Vector Machine (SVM) for component-level fault diagnosis. The technique integrates separately-built, separately-trained, specialized SVM modules capable of component-level fault diagnosis into a coherent intelligent system, with each SVM module monitoring sub-units of the reactor coolant system. To evaluate the model, marginal faults selected from the failure mode and effect analysis (FMEA) are simulated in the steam generator and pressure boundary of the Chinese CNP300 PWR (Qinshan I NPP) reactor coolant system, using a best-estimate thermal-hydraulic code, RELAP5/SCDAP Mod4.0. Multiclass SVM model is trained with component level parameters that represent the steady state and selected faults in the components. For optimization purposes, we considered and compared the performances of different multiclass models in MATLAB, using different coding matrices, as well as different kernel functions on the representative data derived from the simulation of Qinshan I NPP. An optimum predictive model - the Error Correcting Output Code (ECOC) with TenaryComplete coding matrix - was obtained from experiments, and utilized to diagnose the incipient faults. Some of the important diagnostic results and heuristic model evaluation methods are presented in this paper.

• 한국지진공학회논문집
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• 제25권6호
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• pp.293-303
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• 2021

Seismic fragility functions for unreinforced masonry buildings were derived based on the incremental dynamic analysis of eight representative inelastic numerical models for application to Korea's earthquake damage estimation system. The effects of panel zones formed between piers and spandrels around openings were taken into account explicitly or implicitly regarding stiffness and inelastic deformation capacity. The site response of ground motion records measured at the rock site was used as input ground motion. Limit states were proposed based on the fraction of structural components that do not meet the required performance from the nonlinear static analysis of each model. In addition to the randomness of ground motion considered in the incremental dynamic analysis explicitly, supplementary standard deviation due to uncertainty that was not reflected in the fragility assessment procedure was added. The proposed seismic fragility functions were verified by applying them to the damage estimation of masonry buildings located around the epicenter of the 2017 Pohang earthquake and comparing the result with actual damage statistics.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2009년도 추계학술대회
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• pp.343-346
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• 2009

패턴생성기로 LFSR은 기계 자체에 고유의 선형의존성이 있어 패턴을 생성할 때 bit의 위치를 이동시켜 수열을 생성하기 때문에 생성되는 패턴들의 상관관계가 높고 따라서 오류 검출률이 낮아지게 된다. 이런 문제점을 해소하기 위하여 LFSR은 scan chain 사이에 XOR 게이트의 조합으로 구성된 페이지 쉬프터를 장착하여 출력 테스트 패턴의 난수성을 높임으로써 LFSR 고유의 선형의존성을 줄이고 오류검출률을 높이는 연구가 활발히 진행되어 왔다. 본 논문에서는 PRPG로서 LFSR의 난수성을 높이기 위하여 LFSR에 장착할 수 있는 새롭고 효과적인 페이지 쉬프터를 구성하는 방법을 제안한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권4호
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• pp.1128-1145
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• 2022

Owing to the rapid development of information science, data analysis based on machine learning has become an interdisciplinary and strategic area. Marine predators algorithm (MPA) is a novel metaheuristic algorithm inspired by the foraging strategies of marine organisms. Considering the randomness of these strategies, an improved algorithm called co-evolutionary cultural mechanism-based marine predators algorithm (CECMPA) is proposed. Through this mechanism, search agents in different spaces can share knowledge and experience to improve the performance of the native algorithm. More specifically, CECMPA has a higher probability of avoiding local optimum and can search the global optimum quickly. In this paper, it is the first to use CECMPA to perform feature subset selection and optimize hyperparameters in support vector machine (SVM) simultaneously. For performance evaluation the proposed method, it is tested on twelve datasets from the university of California Irvine (UCI) repository. Moreover, the coronavirus disease 2019 (COVID-19) can be a real-world application and is spreading in many countries. CECMPA is also applied to a COVID-19 dataset. The experimental results and statistical analysis demonstrate that CECMPA is superior to other compared methods in the literature in terms of several evaluation metrics. The proposed method has strong competitive abilities and promising prospects.