Pile or column supported embankments have been increasingly employed to construct highway or railway embankments over soft soils. Piles or columns of stiffer material installed in the soft ground can provide the necessary support by transferring the embankment load to a firm stratum using a soil arching. However, there has been reported to occur a relatively large differential settlement between the piles and the untreated soils. Geosynthetic reinforced pile or column supported embankment (GRPS) is often used to minimize the differential settlement. Two dimensional finite element anlyses have been performed on both the column supported embankments and the geogrid reinforced column supported embankments by using a PLAXIS 2D to evaluate the soil arching effect. Based on the results obtained from finite element analyses, the stress reduction ratio decreases as the area replacement ratio increases in the column supported embankments. For the geogrid reinforced column supported embankments, the geogrid reinforcemnt can reduce differential settlements effectively. In additon, the use of stiffer geogrid is appeared to be more effective in reducing the differential settlements.
The objective of this study is to develop a two-dimensional (2D) flood model that can perform accurate flood analysis with simple input data. The 2D flood inundation models currently used to create flood forecast maps require complex input data and grid generation tools. This sometimes requires a lot of time and effort for flood modeling, and there may be difficulties in constructing input data depending on the situation. In order to compensate for these shortcomings, in this study, a grid-based model that can derive accurate and rapid flood analysis by reflecting correct topography as simple input data was developed. The calculation efficiency was improved by extending the existing 2×2 sub-grid model to a 5×5. In order to examine the accuracy and applicability of the model, it was applied to the Gamcheon Basin where both urban and river flooding occurred due to Typhoon Rusa. For efficient flood analysis according to user's selection, flood wave propagation patterns, accuracy and execution time according to grid size and number of sub-grids were investigated. The developed model is expected to be highly useful for flood disaster mapping as it can present the results of flooding analysis for various situations, from the flood inundation map showing accurate flooding to the flood risk map showing only approximate flooding.
The propagation of impact wave induced by landslide and debris flow occurred on the slope of lake, reservoir and bays is a three-dimensional natural phenomenon associated with strong interaction of debris flow and water flow in complex geometrical environments. We carried out 3D numerical modeling of such impact wave in a bay using a multiphase turbulence flow model and a rheology model for non-Newtonian debris flow. Numerical results are compared with previous experimental result to evaluate the performance of present numerical approach. The results underscore that the reasonable predictions of both thickness and speed of debris flow head penetrating below the water surface are crucial to accurately reproduce the maximum peak height and free surface profiles of impact wave. Two predictions computed using different initial debris flow thicknesses become different from the instant when the peaks of impact waves fall due to the gravity. Numerical modeling using relatively thick initial debris flow thickness appears to well reproduce the water surface profile of impact wave propagating across the bay as well as wave run-up on the opposite slope. The results show that the maximum run-up height on the opposite slope is not sensitive to the initial thickness of debris flows of same total volume. Meanwhile, appropriate rheology model for debris flow consisting of inviscid particle only should be employed to more accurately reproduce the debris flow propagating along the channel bottom.
Journal of the Institute of Convergence Signal Processing
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v.22
no.4
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pp.185-192
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2021
Various methods have been proposed to determine the defect detection of welding bead, and recently sensor data and image data inspection have been steadily announced. There are advantages that sensor data inspection is highly accurate, and two-dimensional-based image data inspection is able to determine the position of the welding bead. However, when analyzing only with sensor data, it is difficult to determine whether the welding has been performed at the correct position. On the other hand, the image data inspection does not have high accuracy due to noise and measurement errors. In this paper, we propose a method that can complement the shortcomings of each inspection method and increase its advantages to improve accuracy and speed up inspection by fusing sensor data inspection which are average current, average volt, and mixed gas data, and image data inspection methods and is implemented as software. In addition, it is intended to allow users to conveniently and intuitively analyze and grasp the results by performing analysis using a graphical user interface(GUI) and checking the data and inspection results used for the inspection. Sensor inspection is performed using the characteristics of each sensor data, and image data is inspected by applying a morphology geodesic active contour algorithm. The experimental results showed 98% accuracy, and when performing the inspection on the four image data, and sensor data the inspection time was about 1.9 seconds, indicating the performance of software that can be used as a real-time inspector in the welding process.
Ji, Inseo;Kang, Jeon-Woong;Kim, Taeyung;Kang, Min Seo;Kwon, Sun Beom;Hong, Jiwoo
Korean Chemical Engineering Research
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v.60
no.2
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pp.300-307
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2022
Time-resolved serial femtosecond crystallography (TR-SFX) is a powerful technique for determining temporal variations in the structural properties of biomacromolecules on ultra-short time scales without causing structure damage by employing femtosecond X-ray laser pulses generated by an X-ray free electron laser (XFEL). The mixing rate of reactants and biomolecule samples, as well as the hit rate between crystal samples and x-ray pulses, are critical factors determining TR-SFX performance, such as accurate image acquisition and efficient sample consumption. We here develop two distinct sample delivery systems that enable ultra-fast mixing and on-demand droplet injecting via pneumatic application with a square pulse signal. The first strategy relies on inertial mixing, which is caused by the high-speed collision and subsequent coalescence of droplets ejected through a double nozzle, while the second relies on on-demand pneumatic jetting embedded with a 3D-printed micromixer. First, the colliding behaviors of the droplets ejected through the double nozzle, as well as the inertial mixing within the coalesced droplets, are investigated experimentally and numerically. The mixing performance of the pneumatic jetting system with an integrated micromixer is then evaluated by using similar approaches. The sample delivery system devised in this work is very valuable for three-dimensional biomolecular structure analysis, which is critical for elucidating the mechanisms by which certain proteins cause disease, as well as searching for antibody drugs and new drug candidates.
Due to the high incidence of malignant melanoma, the establishment of in vitro models that recapitulate the tumor microenvironment is of great biological and clinical importance for tumor treatment and drug research. In this study, 3D printing technology was used to prepare GelMA/PEGDA composite scaffolds that mimic the microenvironment of human malignant melanoma cell (A375) growth and construct in vitro melanoma micro-models. The GelMA/PEGDA hybrid scaffold was tested by the mechanical property, cell live/dead assay, cell proliferation assay, cytoskeleton staining and drug loading assay. The growth of tumor cells in two- and three-dimensional culture systems and the anti-cancer effect of luteolin were evaluated using the live/dead staining method and the Cell Counting Kit-8 (CCK-8) method. The results showed a high aggregation of tumor cells on the 3D scaffold, which was suitable for long-term culture. Cytoskeleton staining and immunofluorescent protein staining were used to evaluate the degree of differentiation of tumor cells under 2D and 3D culture systems. The results indicated that 3D bioprinted scaffolds were more suitable for tumor cell expansion and differentiation, and the tumor cells were more aggressive. In addition, luteolin was time- and dose-dependent on tumor cells, and tumor cells in the 3D culture system were more resistant to the drug.
Moon, Woon Ki;Noh, Da Hye;Yoo, Jae Sang;Lim, O Young;Kim, Myoung Chul;Kim, Ji Hye;Lee, Jeong Min;Kim, Jai Ku
Ecology and Resilient Infrastructure
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v.9
no.2
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pp.93-99
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2022
It was confirmed that the fish diversity decreased with increasing index of weir's density (IWD) in the four river systems. The IWD showed difference with watershed, it was high in the Nakdong River (NDR). Both two river systems of Gum River (GUR) and Yeongsan River (YSR) were similar, whereas relatively lower density observed in the Han River (HNR) system. A result of 2-Dimensional Kolmogorov-Smirnov (2-DKS) as a nonparametic test showed different threshold values affecting fish diversity with the river systems. The p-values based on Dmax, were significantly different at 0.05 level (except for YSR). The threshold values affecting fish diversity were also different with watershed. The values were 1.6/km of the HNR, 1.3/km of the NDR, and 2.3/km of the GUR, respectively. The fish diversity was decreased when IWD is over threshold values. The IWD of total 404 rivers (about 33%) among 1,217 surveyed in this study showed above threshold value. These rivers should be considered first for evaluating river continuity. The IWD and threshold value suggested in this study would be useful for selecting a stream priority for river connectivity study.
Medical image segmentation is the most important task in radiation therapy. Especially, when segmenting medical images, the liver is one of the most difficult organs to segment because it has various shapes and is close to other organs. Therefore, automatic segmentation of the liver in computed tomography (CT) images is a difficult task. Since tumors also have low contrast in surrounding tissues, and the shape, location, size, and number of tumors vary from patient to patient, accurate tumor segmentation takes a long time. In this study, we propose a method algorithm for automatically segmenting the liver and tumor for this purpose. As an advantage of setting the boundaries of the tumor, the liver and tumor were automatically segmented from the CT image using the 2D CoordConv DeepLab V3+ model using the CoordConv layer. For tumors, only cropped liver images were used to improve accuracy. Additionally, to increase the segmentation accuracy, augmentation, preprocess, loss function, and hyperparameter were used to find optimal values. We compared the CoordConv DeepLab v3+ model using the CoordConv layer and the DeepLab V3+ model without the CoordConv layer to determine whether they affected the segmentation accuracy. The data sets used included 131 hepatic tumor segmentation (LiTS) challenge data sets (100 train sets, 16 validation sets, and 15 test sets). Additional learned data were tested using 15 clinical data from Seoul St. Mary's Hospital. The evaluation was compared with the study results learned with a two-dimensional deep learning-based model. Dice values without the CoordConv layer achieved 0.965 ± 0.01 for liver segmentation and 0.925 ± 0.04 for tumor segmentation using the LiTS data set. Results from the clinical data set achieved 0.927 ± 0.02 for liver division and 0.903 ± 0.05 for tumor division. The dice values using the CoordConv layer achieved 0.989 ± 0.02 for liver segmentation and 0.937 ± 0.07 for tumor segmentation using the LiTS data set. Results from the clinical data set achieved 0.944 ± 0.02 for liver division and 0.916 ± 0.18 for tumor division. The use of CoordConv layers improves the segmentation accuracy. The highest of the most recently published values were 0.960 and 0.749 for liver and tumor division, respectively. However, better performance was achieved with 0.989 and 0.937 results for liver and tumor, which would have been used with the algorithm proposed in this study. The algorithm proposed in this study can play a useful role in treatment planning by improving contouring accuracy and reducing time when segmentation evaluation of liver and tumor is performed. And accurate identification of liver anatomy in medical imaging applications, such as surgical planning, as well as radiotherapy, which can leverage the findings of this study, can help clinical evaluation of the risks and benefits of liver intervention.
KIPS Transactions on Computer and Communication Systems
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v.11
no.5
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pp.133-138
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2022
Recently, as GPU performance has improved in HPC and artificial intelligence, its use is becoming more common, but GPU programming is still a big obstacle in terms of productivity. In particular, due to the difficulty of managing host memory and GPU memory separately, research is being actively conducted in terms of convenience and performance, and various CPU-GPU memory transfer programming methods are suggested. Meanwhile, recently many SoC (System on a Chip) products such as Apple M1 and NVIDIA Tegra that bundle CPU, GPU, and integrated memory into one large silicon package are emerging. In this study, data between CPU and GPU devices are used in such an integrated memory device and performance-related research is conducted during transmission. It shows different characteristics from the existing environment in which the host memory and GPU memory in the CPU are separated. Here, we want to compare performance by CPU-GPU data transmission method in NVIDIA SoC chips, which are integrated memory devices, and NVIDIA SMX-based V100 GPU devices. For the experimental workload for performance comparison, a two-dimensional matrix transposition example frequently used in HPC applications was used. We analyzed the following performance factors: the difference in GPU kernel performance according to the CPU-GPU memory transfer method for each GPU device, the transfer performance difference between page-locked memory and pageable memory, overall performance comparison, and performance comparison by workload size. Through this experiment, it was confirmed that the NVIDIA Xavier can maximize the benefits of integrated memory in the SoC chip by supporting I/O cache consistency.
Lamira, Alessando;Mazzi-Chaves, Jardel Francisco;Nicolielo, Laura Ferreira Pinheiro;Leoni, Graziela Bianchi;Silva-Sousa, Alice Correa;Silva-Sousa, Yara Terezinha Correa;Pauwels, Ruben;Buls, Nico;Jacobs, Reinhilde;Sousa-Neto, Manoel Damiao
Imaging Science in Dentistry
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v.52
no.3
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pp.245-258
/
2022
Purpose: This study compared the root canal anatomy between cone-beam computed tomography (CBCT) and micro-computed tomography (micro-CT) images before and after biomechanical preparation and root canal filling. Materials and Methods: Isthmus-containing mesial roots of mandibular molars(n=14) were scanned by micro-CT and 3 CBCT devices: 3D Accuitomo 170 (ACC), NewTom 5G (N5G) and NewTom VGi evo (NEVO). Two calibrated observers evaluated the images for 2-dimensional quantitative parameters, the presence of debris or root perforation, and filling quality in the root canal and isthmus. The kappa coefficient, analysis of variance, and the Tukey test were used for statistical analyses(α=5%). Results: Substantial intra-observer agreement (κ=0.63) was found between micro-CT and ACC, N5G, and NEVO. Debris detection was difficult using ACC (42.9%), N5G (40.0%), and NEVO (40%), with no agreement between micro-CT and ACC, N5G, and NEVO (0.05<κ<0.12). After biomechanical preparation, 2.4%-4.8% of CBCT images showed root perforation that was absent on micro-CT. The 2D parameters showed satisfactory reproducibility between micro-CT and ACC, N5G, and NEVO (intraclass correlation coefficient: 0.60-0.73). Partially filled isthmuses were observed in 2.9% of the ACC images, 8.8% of the N5G and NEVO images, and 26.5% of the micro-CT images, with no agreement between micro-CT and ACC, and poor agreement between micro-CT and N5G and NEVO. Excellent agreement was found for area, perimeter, and the major and minor diameters, while the roundness measures were satisfactory. Conclusion: CBCT images aided in isthmus detection and classification, but did not allow their classification after biomechanical preparation and root canal filling.
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