• Wind and Structures
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• v.21 no.5
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• pp.461-487
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• 2015

In recent years, the Graphics Processing Unit (GPU) has become a competitive computing technology in comparison with the standard Central Processing Unit (CPU) technology due to reduced unit cost, energy and computing time. This paper describes the derivation and implementation of GPU-based algorithms for the analysis of wind loading uncertainty on high-rise systems, in line with the research field of probability-based wind engineering. The study begins by presenting an application of the GPU technology to basic linear algebra problems to demonstrate advantages and limitations. Subsequently, Monte-Carlo integration and synthetic generation of wind turbulence are examined. Finally, the GPU architecture is used for the dynamic analysis of three high-rise structural systems under uncertain wind loads. In the first example the fragility analysis of a single degree-of-freedom structure is illustrated. Since fragility analysis employs sampling-based Monte Carlo simulation, it is feasible to distribute the evaluation of different random parameters among different GPU threads and to compute the results in parallel. In the second case the fragility analysis is carried out on a continuum structure, i.e., a tall building, in which double integration is required to evaluate the generalized turbulent wind load and the dynamic response in the frequency domain. The third example examines the computation of the generalized coupled wind load and response on a tall building in both along-wind and cross-wind directions. It is concluded that the GPU can perform computational tasks on average 10 times faster than the CPU.

• Geomechanics and Engineering
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• v.24 no.4
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• pp.359-370
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• 2021

Joint roughness is combination of primary and secondary roughness. Ordinarily primary roughness is a geostatistical part of a joint surface that has a periodic nature but secondary roughness or unevenness is a statistical part of that which have a random nature. Using roughness generating algorithms is a useful method for evaluation of joint roughness. In this paper after determining geostatistical parameters of the joint profile, were presented two roughness generating algorithms using Mount-Carlo method for evaluation of primary (GJRGAP) and secondary (GJRGAS) roughness. These based on geostatistical parameters (range and sill) and statistical parameters (standard deviation of asperities height, SDH, and standard deviation of asperities angle, SDA) for generation two-dimensional joint roughness profiles. In this study different geostatistical regions were defined depending on the range and SDH. As SDH increases, the height of the generated asperities increases and asperities become sharper and at a specific range (a specific curve) relation between SDH and SDA is linear. As the range in GJRGAP becomes larger (the base of the asperities) the shape of asperities becomes flatter. The results illustrate that joint profiles have larger SDA with increase of SDH and decrease of range. Consequencely increase of SDA leads to joint roughness parameters such Z2, Z3 and RP increases. The results showed that secondary roughness or unevenness has a great influence on roughness values. In general, it can be concluded that the shape and size of asperities are appropriate parameters to approach the field scale from the laboratory scale.

• ETRI Journal
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• v.44 no.5
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• pp.794-804
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• 2022

Transformer models have had a great impact on natural language processing (NLP) in recent years by realizing outstanding and efficient contextualized language models. Recent studies have used transformer-based language models for various NLP tasks, including Persian named entity recognition (NER). However, in complex tasks, for example, NER, it is difficult to determine which contextualized embedding will produce the best representation for the tasks. Considering the lack of comparative studies to investigate the use of different contextualized pretrained models with sequence modeling classifiers, we conducted a comparative study about using different classifiers and embedding models. In this paper, we use different transformer-based language models tuned with different classifiers, and we evaluate these models on the Persian NER task. We perform a comparative analysis to assess the impact of text representation and text classification methods on Persian NER performance. We train and evaluate the models on three different Persian NER datasets, that is, MoNa, Peyma, and Arman. Experimental results demonstrate that XLM-R with a linear layer and conditional random field (CRF) layer exhibited the best performance. This model achieved phrase-based F-measures of 70.04, 86.37, and 79.25 and word-based F scores of 78, 84.02, and 89.73 on the MoNa, Peyma, and Arman datasets, respectively. These results represent state-of-the-art performance on the Persian NER task.

• Radiation Oncology Journal
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• v.14 no.1
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• pp.69-76
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• 1996

Purpose : The aim of this study is to investigate the random and systematic errors and tumor movement using electronic portal imaging device in lung cancer patients for the adequate margin in the treatment planning of 3-dimensional conformal therapy. Material and Methods : The electronic portal imaging device is matrix ion chamber type(Portal Vision, Varian). Ten patients of lung cancer treated with chest irradiation were selected for this study. Patients were treated in the supine position without immobilization device. All treatments were delivered by an 10 MV linear accelerator that had the portal imaging system mounted to its ganrty. AP or PA field Portal images were only analyzed. Radiation therapy field included the tumor, mediastinum and supraclavicular lymph nodes. A total of 103 portal images were analyzed for set-up deviation and 10 multiple images were analyzed for tumor movement because of respiration and cardiac motion. Result : The average values of setup displacements in the x, y direction was 1.41 mm, 1 78 mm, respectively. The standard deviation of systematic component was 4.63 mm, 4.11 mm along the x, y axis, respectively while the random component was 4.17 mm in the x direction and 3.31 mm in the y direction. The average displacement from respiratory movement was 12.2 mm with a standard deviation of 4.03 mm. Conclusion : The overall set-up displacement includes both random and systematic component and respiratory movement. About 10 mm, 25 mm margins along x, y axis which considered the set-up displacement and tumor movement were required for initial 3-dimensional conformal treatment planning in the lung cancer patients and portal images should be made and analyzed during first week of treatment, individually.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.6
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• pp.453-460
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• 2017

High voltage power transmission lines have been to keep the proper dip for maintenance. Powerline dips at a random point are conventionally measured by the direct or indirect observation but it is not only unsafe but labor-intensive. Therefore in this study we applied the photogrammetric technique to remotely measure the powerline dips. Since it is not easy to extract conjugate points from linear powerlines, we exploited the epipolar lines acrossing the powerlines for 3D mapping of the powerlines and dip measurements. The vertical mapping accuracy estimated at two field-surveyed power line points was 15~16cm that are within 5% of deflection at the points and less than 3% of the powerline dip.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.537-544
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• 2020

Advances in detection techniques, such as mutation and obfuscation, are being advanced with the development of malware technology. In the malware detection technology, unknown malware detection technology is important, and a method for Malware Authorship Attribution that detects an unknown malicious code by identifying the author through distributed malware is being studied. In this paper, we try to extract the compiler information affecting the binary-based author identification method and to investigate the sensitivity of feature selection, probability and non-probability models, and optimization to classification efficiency between studies. In the experiment, the feature selection method through information gain and the support vector machine, which is a non-probability model, showed high efficiency. Among the optimization studies, high classification accuracy was obtained through feature selection and model optimization through the proposed framework, and resulted in 48% feature reduction and 53 faster execution speed. Through this study, we can confirm the sensitivity of feature selection, model, and optimization methods to classification efficiency.

• Journal of the Korean Geotechnical Society
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• v.16 no.4
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• pp.63-70
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• 2000

The quantitative analyses and the mechanical interpretation of discontinuity planes are the most important factor for the study of strength and deformation properties of rock masses containing discontinuity planes. However, the relationship between the factors investigated in the field and the actual mechanical properties of discontinuity planes is not fully understood. The main purpose of this study is to investigate the effects of density, length, and spacing of joints on elastic modulus of rock masses as these values vary. A new parameter which has a direct relation with the elastic modulus of discontinuity planes is also preposed in this study. The combination of finite element methods and homogenization methods has been used for the numerical analyses of a uintcell with discontinuity planes, which is generated using random-number generation methods. The elastic modulus of the discontinuity plane is found from the numerical analyses. The final results propose not only the relation between the investigation parameters of discontinuity planes and the elastic modulus of rock masses but also a new parameter, an effect area ratio having a linear relation with the elastic modulus of rock masses.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.12
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• pp.1035-1044
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• 2013

Because of the high specific stiffness and strength inherent in the sandwich structure composed of facesheet that resists in-plane loads and a core that resists out-of-plane loads, it is often used for large and light-weighted structures. However, inevitably the increased flexibility allows greater deformation-based disturbances in the structures. Thus, it is necessary to analyze the structural safety. To obtain more accurate analytical results, the input disturbances must more closely simulate real load conditions; to improve accuracy, non-linear elements such as gust effects were considered. In addition, the structural safety was analyzed for the iso-grid sandwich panel structure using fluid-structure interactions. For a more realistic simulation, flow velocity fields, which consider the effects of irregular gust fluctuation, were generated and the coupled field was analyzed by mapping the pressure and displacement.

• Journal of the Korean Society of Radiology
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• v.14 no.1
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• pp.69-75
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• 2020

Multilayer mirrors have widely been used not only in the industry but also in the medical field. X-ray reflectivity was measured by X-ray diffractometer to evaluate the performance of W/C multilayer mirror with 40 layers. Genetic algorithm are used to obtain thickness, density, and interfacial roughness for each of the 40 layers. The existing uniform random selection causes a problem that the solution does not converge or the error increases even if it convergence. To reduce the time to calculate the fitness of the genetic algorithm, the genetic algorithm was written in C/C++ parallel programming. The genetic algorithm showed excellent scalability of linear time increase with increasing number of generation and population. The genetic algorithm was selected with uniform and Gaussian randomness of 1:1 to improve the convergence of solution. The improved genetic algorithm can be applied to characterize each layer of a sample with more than a few tens of layers, such as a multilayer mirror.

• Journal of the Korean Chemical Society
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• v.57 no.6
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• pp.744-754
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• 2013

Quantitative structure-activity relationship (QSAR) analysis for recently synthesized imidazole-(benz)azole and imidazole - piperazine derivatives was studied for their anticancer activities against breast (MCF-7) cell lines. The statistically significant 2D-QSAR models ($r^2=0.8901$; $q^2=0.8130$; F test = 36.4635; $r^2$ se = 0.1696; $q^2$ se = 0.12212; pred_$r^2=0.4229$; pred_$r^2$ se = 0.4606 and $r^2=0.8763$; $q^2=0.7617$; F test = 31.8737; $r^2$ se = 0.1951; $q^2$ se = 0.2708; pred_$r^2=0.4386$; pred_$r^2$ se = 0.3950) were developed using molecular design suite (VLifeMDS 4.2). The study was performed with 18 compounds (data set) using random selection and manual selection methods used for the division of the data set into training and test set. Multiple linear regression (MLR) methodology with stepwise (SW) forward-backward variable selection method was used for building the QSAR models. The results of the 2D-QSAR models were further compared with 3D-QSAR models generated by kNN-MFA, (k-Nearest Neighbor Molecular Field Analysis) investigating the substitutional requirements for the favorable anticancer activity. The results derived may be useful in further designing novel imidazole-(benz)azole and imidazole-piperazine derivatives against breast (MCF-7) cell lines prior to synthesis.