• International Journal of Advanced Culture Technology
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• 제10권2호
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• pp.220-224
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• 2022

The efficiencies of rates and energy in the fifth generation (5G) wireless channels can be improved via intelligent reflecting surface (IRS) transmissions, towards the sixth generation (6G) mobile communications. While previous works have considered mainly optimizations of IRS transmissions, we propose a performance analysis on the total power in terms of the number of reflecting devices for IRS transmissions in non-orthogonal multiple access (NOMA) networks. First, we derive an analytical expression of the total power gain factor in terms of the number of reflecting devices for the cell-edge user in IRS-NOMA systems. Then we evaluate how many reflecting devices we need to obtain a total power gain in dB. Moreover, we also demonstrate numerically the signal-to-noise ratio (SNR) gain of the IRS-NOMA system over the conventional NOMA system based on the achievable data rate.

• Nuclear Engineering and Technology
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• 제54권8호
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• pp.3106-3116
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• 2022

The present work presents analysis results of the core design optimizations for an annular, prismatic High Temperature Gas-cooled Reactor (HTGR) with passive decay-heat removal features. Its thermal power is 100 MW_t and the operating temperature is 850 ℃ (1123 K). The neutronic calculations are done for the core with heterogeneous distribution of fuel and burnable poison particles (BPPs) to flatten the reactivity swing and power peaking factor (PPF) during the reactor operation as well as for control rod (CR) insertion into the core to restrain a small excess reactivity less than 1$. The next step of the study is done for evaluation of core reactivity coefficient of temperature.

• Advances in concrete construction
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• 제15권4호
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• pp.269-286
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• 2023

In the present study, we aim to utilize the numerical solution frequency results of functionally graded beam under thermal and dynamic loadings to train and test an artificial neural network. In this regard, shear deformable functionally-graded beam structure is considered for obtaining the natural frequency in different conditions of boundary and material grading indices. In this regard, both analytical and numerical solutions based on Navier's approach and differential quadrature method are presented to obtain effects of different parameters on the natural frequency of the structure. Further, the numerical results are utilized to train an artificial neural network (ANN) using AdaGrad optimization algorithm. Finally, the results of the ANN and other solution procedure are presented and comprehensive parametric study is presented to observe effects of geometrical, material and boundary conditions of the free oscillation frequency of the functionally graded beam structure.

• International Journal of Computer Science & Network Security
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• 제23권4호
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• pp.116-122
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• 2023

Sentiment categorization technique be commonly isolated interested in threes significant classifications name Machine Learning Procedure (ML), Lexicon Based Method (LB) also finally, the Hybrid Method. In Machine Learning Methods (ML) utilizes phonetic highlights with apply notable ML algorithm. In this paper, in classification and identification be complete base under in optimizations technique called sequential minimal optimization with Random Forest algorithm (SMORF) for expanding the exhibition and proficiency of sentiment classification framework. The three existing classification algorithms are compared with proposed SMORF algorithm. Imitation result within experiential structure is Precisions (P), recalls (R), F-measures (F) and accuracy metric. The proposed sequential minimal optimization with Random Forest (SMORF) provides the great accuracy.

• Wind and Structures
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• 제34권3호
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• pp.259-274
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• 2022

The present paper is focused on analyzing a set of Computational Fluid Dynamics (CFD) simulation data on reducing orthogonal peak base moment coefficients on a high-rise rectangular building with wings. The study adopts an aerodynamic optimization procedure (AOP) composed of CFD, artificial neural network (ANN), and genetic algorithm (G.A.). A parametric study is primarily accomplished by altering the wing positions with 3D transient CFD analysis using k - ε turbulence models. The CFD technique is validated by taking up a wind tunnel test. The required design parameters are obtained at each design point and used for training ANN. The trained ANN models are used as surrogates to conduct optimization studies using G.A. Two single-objective optimizations are performed to minimize the peak base moment coefficients in the individual directions. An additional multiobjective optimization is implemented with the motivation of diminishing the two orthogonal peak base moments concurrently. Pareto-optimal solutions specifying the preferred building shapes are offered.

• Journal of information and communication convergence engineering
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• 제22권2호
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• pp.98-108
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• 2024

Scrypt is a password-based key derivation function proposed by Colin Percival in 2009 that has a memory-hard structure. Scrypt has been intentionally designed with a memory-intensive structure to make password cracking using ASICs, GPUs, and similar hardware more difficult. However, in this study, we thoroughly analyzed the operation of Scrypt and proposed strategies to maximize computational parallelism in GPU environments. Through these optimizations, we achieved an outstanding performance improvement of 8284.4% compared with traditional CPU-based Scrypt computations. Moreover, the GPU-optimized implementation presented in this paper outperforms the simple GPU-based Scrypt processing by a significant margin, providing a performance improvement of 204.84% in the RTX3090. These results demonstrate the effectiveness of our proposed approach in harnessing the computational power of GPUs and achieving remarkable performance gains in Scrypt calculations. Our proposed implementation is the first GPU implementation of Scrypt, demonstrating the ability to efficiently crack Scrypt.

• Communications for Statistical Applications and Methods
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• 제31권2호
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• pp.235-246
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• 2024

In high-dimensional data analysis, sufficient dimension reduction (SDR) has been considered as an attractive tool for reducing the dimensionality of predictors while preserving regression information. The principal support vector machine (PSVM) (Li et al., 2011) offers a unified approach for both linear and nonlinear SDR. This article comprehensively explores a variety of SDR methods based on the PSVM, which we call principal machines (PM) for SDR. The PM achieves SDR by solving a sequence of convex optimizations akin to popular supervised learning methods, such as the support vector machine, logistic regression, and quantile regression, to name a few. This makes the PM straightforward to handle and extend in both theoretical and computational aspects, as we will see throughout this article.

• 정보처리학회논문지A
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• 제18A권3호
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• pp.109-114
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• 2011

IR(Intermediate Representation) 최적화 과정은 컴파일러 back-end의 중요한 부분으로서 sub-expression elimination, dead code elimination 등 최적화 기법들을 사용한다. 하지만 IR 최적화 단계에서 생기는 에러들을 검출하고 디버깅하는데 많은 어려움이 있다. 그 첫 번째 이유로는 컴파일 된 어셈블리 코드를 해독하여 에러를 체크하기 어렵고 두 번째로는 IR 최적화 단계에서 에러가 생겼는지 결정 짓기 어렵기 때문이다. 이런 이유들로 인하여, 우리는 C 레벨에서 IR 코드변환 무결점 여부를 체크하기 위한 기법들에 관한 연구를 진행하여 왔다. 우리는 MeCC(Memory Comparison-based Clone) 탐색기를 기반으로 하여, 최적화하기 전 IR코드와 최적화 한 후의 IR코드를 각각 C코드로 다시 변환한 뒤, 이 두 개의 C코드를 MeCC의 입력으로 주고, 결과의 일치 여부를 확인하는 방법을 사용한다. 하지만 MeCC가 완벽한 결과를 알려주지 않기 때문에, 우리는 각 IR 최적화 기법마다의 특징에 대한 정보를 사전에 처리해서 그 결과의 정확도를 높였다. 이 논문에서는 dead code elimination, instruction scheduling 및 common sub-expression elimination 등 최적화 기법들을 이용한 변환 코드들을 예시로 실험하여 최종적으로 MeCC에서의 C 레벨 코드의 정확한 에러 체크 동작여부를 보여준다.

• 한국전자파학회논문지
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• 제20권4호
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• pp.390-395
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• 2009

본 논문에서는 미앤더 스트립라인을 이용한X-대역 광대역 편파 변환기 설계 및 최적화 문제에 대해서 고찰하였다. 편파 변환기에 입사되는 편파를 수직, 수평 성분으로 분리하고 각 편파별로 등가 전송선 모델(transmission line model)을 사용하여 교차 편파 억제율과 편파 변환율을 계산하였다. 또한, 최적화된 파라미터 도출을 위해 유전 알고리즘과 particle swarm optimization에 기반한 하이브리드 알고리즘의 성능을 평가하고 설계에 적용하였다. 최적화된 편파 변환기는 X-대역(8.45$\sim$11.38 GHz)에서 -25 dB 이하의 편파 억제 성능을 보여주고 있으며, 편파 변환 손실은 0.2 dB 이하로 계산되었다. 또한, 이 결과를 상용 시뮬레이션 수치와 비교 분석하였다.

• International Journal of Naval Architecture and Ocean Engineering
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• 제6권2호
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• pp.392-405
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• 2014

SSPA experiences a growing interest in twin skeg ships as one attractive green ship solution. The twin skeg concept is well proven with obvious advantages for the design of ships with full hull forms, restricted draft or highly loaded propellers. SSPA has conducted extensive hull optimizations studies of LNG ships of different size based on an extensive hull data base with over 7,000 models tested, including over 400 twin skeg hull forms. Main hull dimensions and different hull concepts such as twin skeg and single screw were of main interest in the studies. In the present paper, one twin skeg and one single screw 170 K LNG ship were designed for optimally selected main dimension parameters. The twin skeg hull was further optimized and evaluated using SHIPFLOW FRIENDSHIP design package by performing parameter variation in order to modify the shape and positions of the skegs. The finally optimized models were then built and tested in order to confirm the lower power demand of twin skeg designed compaed with the signle screw design. This paper is a full description of one of the design developments of a LNG twin skeg hull, from early dimensional parameter study, through design optimization phase towards the confirmation by model tests.