• Wind and Structures
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• v.37 no.4
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• pp.255-274
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• 2023

The aim of this paper is to enhance the accuracy of predicting time-averaged external surface pressures on low-rise buildings by utilizing Computational Fluid Dynamics (CFD) simulations. To achieve this, benchmark studies of the Silsoe cube and the Texas Tech University (TTU) experimental building are employed for comparison with simulation results. The paper is structured into three main sections. In the initial part, an appropriate domain size is selected based on the precision of mean pressure coefficients on the windward face of the cube, utilizing Reynolds Averaged Navier-Stokes (RANS) turbulence models. Subsequently, recommendations regarding the optimal computational domain size for an isolated building are provided based on revised findings. Moving on to the second part, the Silsoe cube model is examined within a horizontally homogeneous computational domain using more accurate turbulence models, such as Large Eddy Simulation (LES) and hybrid RANS-LES models. For computational efficiency, transient simulation settings are employed, building upon previous studies by the authors at the Windstorm Impact, Science, and Engineering (WISE) Lab, Louisiana State University (LSU). An optimal meshing strategy is determined for LES based on a grid convergence study. Three hybrid RANS-LES cases are investigated to achieve desired enhancements in the distribution of mean pressure coefficients on the Silsoe cube. In the final part, a 1:10 scale model of the TTU building is studied, incorporating the insights gained from the second part. The generated flow characteristics, including vertical profiles of mean velocity, turbulence intensity, and velocity spectra (small and large eddies), exhibit good agreement with full-scale (TTU) measurements. The results indicate promising roof pressures achieved through the careful consideration of meshing strategy, time step, domain size, inflow turbulence, near-wall treatment, and turbulence models. Moreover, this paper demonstrates an improvement in mean roof pressures compared to other state-of-the-art studies, thus highlighting the significance of CFD simulations in building aerodynamics.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.10
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• pp.2768-2787
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• 2023

As an important research direction of the application of computer science in the medical field, the automatic generation technology of radiology report has attracted wide attention in the academic community. Because the proportion of normal regions in radiology images is much larger than that of abnormal regions, words describing diseases are often masked by other words, resulting in significant feature loss during the calculation process, which affects the quality of generated reports. In addition, the huge difference between visual features and semantic features causes traditional multi-modal fusion method to fail to generate long narrative structures consisting of multiple sentences, which are required for medical reports. To address these challenges, we propose a multi-feature optimization Transformer (MFOT) for generating radiology reports. In detail, a multi-dimensional mapping attention (MDMA) module is designed to encode the visual grid features from different dimensions to reduce the loss of primary features in the encoding process; a feature pre-fusion (FP) module is constructed to enhance the interaction ability between multi-modal features, so as to generate a reasonably structured radiology report; a detail enhanced attention (DEA) module is proposed to enhance the extraction and utilization of key features and reduce the loss of key features. In conclusion, we evaluate the performance of our proposed model against prevailing mainstream models by utilizing widely-recognized radiology report datasets, namely IU X-Ray and MIMIC-CXR. The experimental outcomes demonstrate that our model achieves SOTA performance on both datasets, compared with the base model, the average improvement of six key indicators is 19.9% and 18.0% respectively. These findings substantiate the efficacy of our model in the domain of automated radiology report generation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.5
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• pp.361-366
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• 2017

As the recent development of computing architecture and application software technology, real world simulation, which is the ultimate destination of computer simulation, is emerging as a practical issue in several research sectors. In this paper, metal plate motion in a square shock tube for small time interval was calculated using a supercomputing-based fluid-structure-combustion multi-physics simulation tool called Illinois Rocstar, developed in a US national R amp; D program at the University of Illinois. Afterwards, the simulation results were compared with those from experiments. The coupled solvers for unsteady compressible fluid dynamics and for structural analysis were based on the finite volume structured grid system and the large deformation linear elastic model, respectively. In addition, a strong correlation between calculation and experiment was shown, probably because of the predictor-corrector time-integration scheme framework. In the future, additional validation studies and code improvements for higher accuracy will be conducted to obtain a reliable open-source software research tool.

• The Journal of the Korea Contents Association
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• v.13 no.2
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• pp.211-219
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• 2013

The analysis method using Big Data has evolved based on the Big data Management Technology. There are quite a few researching institutions anticipating new era in data analysis using Big Data and IT vendors has been sided with them launching standardized technologies for Big Data management technologies. Big Data is also affected by improvements of IT gadgets IT environment. Foreran by social media, analyzing method of unstructured data is being developed focusing on diversity of analyzing method, anticipation and optimization. In the past, data analyzing methods were confined to the optimization of structured data through data mining, OLAP, statics analysis. This data analysis was solely used for decision making for Chief Officers. In the new era of data analysis, however, are evolutions in various aspects of technologies; the diversity in analyzing method using new paradigm and the new data analysis experts and so forth. In addition, new patterns of data analysis will be found with the development of high performance computing environment and Big Data management techniques. Accordingly, this paper is dedicated to define the possible analyzing method of social media using Big Data. this paper is proposed practical use analysis for social media analysis through data mining analysis methodology.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.19 no.1
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• pp.81-96
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• 2007

Nonlinear shoaling characteristics over surf zone are numerically investigated based on spatially averaged NavierStokes equation. We also test the validity of gradient model for turbulent stresses due to wave breaking using the data acquainted during SUPERTANK LABORATORY DATA COLLECTION PROJECT(Krauss et al., 1992). It turns out that the characteristics length scale of breaking induced current is not negligible, which firmly stands against ever popular gradient model, ${\kappa}-{\varepsilon}$ model, but favors Large Eddy Simulation with finer grid. Based on these observations, we model the residual stress of spatially averaged NavierStokes equation after Lagrangian Dynamic Smagorinsky(Meneveau et al., 1996). We numerically integrate newly proposed wave equations using SPH with Gaussian kernel function. Severely deformed water surface profile, free falling water particle, queuing splash after landing of water particle on the free surface and wave finger due to structured vortex on rear side of wave crest(Narayanaswamy and Dalrymple, 2002) are successfully duplicated in the numerical simulation of wave propagation over uniform slope beach, which so far have been regarded very difficult features to mimic in the computational fluid mechanics.