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"abstract": "While several datasets for autonomous navigation have become available in recent years, they have tended to focus on structured driving environments. This usually corresponds to well-delineated infrastructure such as lanes, a small number of well-defined categories for traffic participants, low variation in object or background appearance and strong adherence to traffic rules. We propose DS, a novel dataset for road scene understanding in unstructured environments where the above assumptions are largely not satisfied. It consists of 10,004 images, finely annotated with 34 classes collected from 182 drive sequences on Indian roads. The label set is expanded in comparison to popular benchmarks such as Cityscapes, to account for new classes. It also reflects label distributions of road scenes significantly different from existing datasets, with most classes displaying greater within-class diversity. Consistent with real driving behaviors, it also identifies new classes such as drivable areas besides the road. We propose a new four-level label hierarchy, which allows varying degrees of complexity and opens up possibilities for new training methods. Our empirical study provides an in-depth analysis of the label characteristics. State-of-the-art methods for semantic segmentation achieve much lower accuracies on our dataset, demonstrating its distinction compared to Cityscapes. Finally, we propose that our dataset is an ideal opportunity for new problems such as domain adaptation, few-shot learning and behavior prediction in road scenes.",
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"title": "Unsupervised Labeling and Extraction of Phrase-based Concepts in Vulnerability Descriptions",
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"abstract": "People usually describe the key characteristics of software vulnerabilities in natural language mixed with domain-specific names and concepts. This textual nature poses a significant challenge for the automatic analysis of vulnerabilities. Automatic extraction of key vulnerability aspects is highly desirable but demands significant effort to manually label data for model training. In this paper, we propose an unsupervised approach to label and extract important vulnerability concepts in textural vulnerability descriptions (TVDs). We focus on three types of phrase-based vulnerability concepts (root cause, attack vector, and impact) as they are much more difficult to label and extract than name- or number-based entities (i.e., vendor, product, and version). Our approach is based on a key observation that the same-type of phrases, no matter how they differ in sentence structures and phrase expressions, usually share syntactically similar paths in the sentence parsing trees. Therefore, we propose two path representations (absolute paths and relative paths) and use an auto-encoder to encode such syntactic similarities. To address the discrete nature of our paths, we enhance traditional Variational Auto-encoder (VAE) with Gumble-Max trick for categorical data distribution, and thus creates a Categorical VAE (CaVAE). In the latent space of absolute and relative paths, we further use FIt-TSNE and clustering techniques to generate clusters of the same-type of concepts. Our evaluation confirms the effectiveness of our CaVAE for encoding path representations and the accuracy of vulnerability concepts in the resulting clusters. In a concept classification task, our unsupervisedly labeled vulnerability concepts outperform the two manually labeled datasets from previous work.",
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"normalizedAbstract": "People usually describe the key characteristics of software vulnerabilities in natural language mixed with domain-specific names and concepts. This textual nature poses a significant challenge for the automatic analysis of vulnerabilities. Automatic extraction of key vulnerability aspects is highly desirable but demands significant effort to manually label data for model training. In this paper, we propose an unsupervised approach to label and extract important vulnerability concepts in textural vulnerability descriptions (TVDs). We focus on three types of phrase-based vulnerability concepts (root cause, attack vector, and impact) as they are much more difficult to label and extract than name- or number-based entities (i.e., vendor, product, and version). Our approach is based on a key observation that the same-type of phrases, no matter how they differ in sentence structures and phrase expressions, usually share syntactically similar paths in the sentence parsing trees. Therefore, we propose two path representations (absolute paths and relative paths) and use an auto-encoder to encode such syntactic similarities. To address the discrete nature of our paths, we enhance traditional Variational Auto-encoder (VAE) with Gumble-Max trick for categorical data distribution, and thus creates a Categorical VAE (CaVAE). In the latent space of absolute and relative paths, we further use FIt-TSNE and clustering techniques to generate clusters of the same-type of concepts. Our evaluation confirms the effectiveness of our CaVAE for encoding path representations and the accuracy of vulnerability concepts in the resulting clusters. In a concept classification task, our unsupervisedly labeled vulnerability concepts outperform the two manually labeled datasets from previous work.",
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"abstract": "Clinical prediction models are often based solely on the use of structured data in electronic health records, e.g. vital parameters and laboratory results, effectively ignoring potentially valuable information recorded in other modalities, such as free-text clinical notes. Here, we report on the development of a multimodal model that combines structured and unstructured data. In particular, we study how best to make use of a clinical language model in a multimodal setup for predicting 30-day all-cause mortality upon hospital admission in patients with COVID-19. We evaluate three strategies for incorporating a domain-specific clinical BERT model in multimodal prediction systems: (i) without fine-tuning, (ii) with unimodal fine-tuning, and (iii) with multimodal fine-tuning. The best-performing model leverages multimodal fine-tuning, in which the clinical BERT model is updated based also on the structured data. This multimodal mortality prediction model is shown to outperform unimodal models that are based on using either only structured data or only unstructured data. The experimental results indicate that clinical prediction models can be improved by including data in other modalities and that multimodal fine-tuning of a clinical language model is an effective strategy for incorporating information from clinical notes in multimodal prediction systems.",
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"title": "Exploring Hate Speech Detection in Multimodal Publications",
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"abstract": "In this work we target the problem of hate speech detection in multimodal publications formed by a text and an image. We gather and annotate a large scale dataset from Twitter, MMHS150K, and propose different models that jointly analyze textual and visual information for hate speech detection, comparing them with unimodal detection. We provide quantitative and qualitative results and analyze the challenges of the proposed task. We find that, even though images are useful for the hate speech detection task, current multimodal models cannot outperform models analyzing only text. We discuss why and open the field and the dataset for further research.",
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"abstract": "A nonlinear analog circuit for coupled image restoration and edge extraction based on Markov Random Fields (MRFs) is presented and analyzed. The circuit is made up of a set of identical linear capacitors and two sets of proper nonlinear resistors. The electric behaviour of the resistive part of the circuit is governed by a generalized potential function whose minima represent the solutions of the MRF problem. The advantages of analogic computations based on MRFs over classical digital approaches are discussed. In particular the real-time MRF-like processing obtained through local interactions between the circuit elements turns out to be the most interesting characteristic of the proposed circuit. Some simulations are described in order to show the performances of the MRF non-linear analog circuit.",
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"content": "A nonlinear analog circuit for coupled image restoration and edge extraction based on Markov Random Fields (MRFs) is presented and analyzed. The circuit is made up of a set of identical linear capacitors and two sets of proper nonlinear resistors. The electric behaviour of the resistive part of the circuit is governed by a generalized potential function whose minima represent the solutions of the MRF problem. The advantages of analogic computations based on MRFs over classical digital approaches are discussed. In particular the real-time MRF-like processing obtained through local interactions between the circuit elements turns out to be the most interesting characteristic of the proposed circuit. Some simulations are described in order to show the performances of the MRF non-linear analog circuit.",
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"abstract": "Multi-target tracking is a worthy studying issue in computer vision. For surveillance video, frequent occlusion and dense crowds complicate the issue. To resolve these difficulties, this paper proposes an effective algorithm of multi-target tracking in videos. Firstly, the faster Rcnn is proposed with the residual network to extract the objects of pedestrians in surveillance videos. The proposedment can effectively eliminate invalid target detection frames, separate peer targets and resist partial occlusions. Then, this paper put forward an accurate and efficient appearance-feature matching network model that is inspired by pedestrian re-identification theory. The deep learning feature-extraction module is composed of the stem Cnn and the Resnet blocks, therefore it can load res-50 caffemodel as pretraining model to increase the accuracy of the feature extraction. Meanwhile, the proposed network can decrease the time of train and test comparing with Resnet. Finally, the obtained multiple target tracking trajectories are further optimized by the strategy of occlusion distinction, deduplication and merging. The experiment results of the 2D MOT 2015 benchmark, KITTI dataset indicate that this proposed algorithm outperforms alternative multiple objects trackers in terms of multiple indicators.",
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"content": "Multi-target tracking is a worthy studying issue in computer vision. For surveillance video, frequent occlusion and dense crowds complicate the issue. To resolve these difficulties, this paper proposes an effective algorithm of multi-target tracking in videos. Firstly, the faster Rcnn is proposed with the residual network to extract the objects of pedestrians in surveillance videos. The proposedment can effectively eliminate invalid target detection frames, separate peer targets and resist partial occlusions. Then, this paper put forward an accurate and efficient appearance-feature matching network model that is inspired by pedestrian re-identification theory. The deep learning feature-extraction module is composed of the stem Cnn and the Resnet blocks, therefore it can load res-50 caffemodel as pretraining model to increase the accuracy of the feature extraction. Meanwhile, the proposed network can decrease the time of train and test comparing with Resnet. Finally, the obtained multiple target tracking trajectories are further optimized by the strategy of occlusion distinction, deduplication and merging. The experiment results of the 2D MOT 2015 benchmark, KITTI dataset indicate that this proposed algorithm outperforms alternative multiple objects trackers in terms of multiple indicators.",
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"abstract": "The current deep learning based visual tracking approaches have been very successful by learning the target classification and/or estimation model from a large amount of supervised training data in offline mode. However, most of them can still fail in tracking objects due to some more challenging issues such as dense distractor objects, confusing background, motion blurs, and so on. Inspired by the human “visual tracking” capability which leverages motion cues to distinguish the target from the background, we propose a Two-Stream Residual Convolutional Network (TS-RCN) for visual tracking, which successfully exploits both appearance and motion features for model update. Our TS-RCN can be integrated with existing deep learning based visual trackers. To further improve the tracking performance, we adopt a “wider” residual network ResNeXt as its feature extraction backbone. To the best of our knowledge, TS-RCN is the first end-to-end trainable two-stream visual tracking system, which makes full use of both appearance and motion features of the target. We have extensively evaluated the TS-RCN on most widely used benchmark datasets including VOT2018, VOT2019, and GOT-10K. The experiment results have successfully demonstrated that our two-stream model can greatly outperform the appearance-based tracker, and achieves state-of-the-art performance. The tracking system can run at up to 38.1 FPS.",
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"abstract": "Nowadays, the GPGPU technology has accelerated many physics-based simulations. SPH (Smoothed Particle Hydrodynamics) is widely used to simulate complex physical phenomena, which using neighbor search as its key procedure. Sorting and grid based method is one of the widely used neighbor search methods on the GPU. This paper presents a new special sorting method to accelerate the neighbor search procedure for SPH systems on the GPU. With our method, the sorting procedure will use the result data of the previous simulation step. Compared with the standard thrust implementation, our method can accelerate the whole simulation when the scale is not very large (nearly 2.3x speedups with 8192 particles in 16*16*16 grid size). While the scale is large, it also does not reduce the performance of the whole simulation.",
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"content": "Nowadays, the GPGPU technology has accelerated many physics-based simulations. SPH (Smoothed Particle Hydrodynamics) is widely used to simulate complex physical phenomena, which using neighbor search as its key procedure. Sorting and grid based method is one of the widely used neighbor search methods on the GPU. This paper presents a new special sorting method to accelerate the neighbor search procedure for SPH systems on the GPU. With our method, the sorting procedure will use the result data of the previous simulation step. Compared with the standard thrust implementation, our method can accelerate the whole simulation when the scale is not very large (nearly 2.3x speedups with 8192 particles in 16*16*16 grid size). While the scale is large, it also does not reduce the performance of the whole simulation.",
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"proceeding": {
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"title": "2022 International Conference on 3D Immersion, Interaction and Multi-sensory Experiences (ICDIIME)",
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"title": "Solid-Fluid Interaction Simulation System Based on SPH Unified Particle Framework",
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"abstract": "Solid-fluid Interaction Simulation is the important research point in the field of fluid simulation. Existing researches mainly focus on the phenomena such as motion, deformation, infiltration, erosion, etc., and less attention is paid to the solid fracture caused by fluid impact. The simulation solutions used by the related researches have weakly coupling with the SPH solid-fluid interaction framework because their solid fracture methods need the geometric form for representing and processing the solid model. For the same reason, their methods have difficulty to parallelize and achieve the balance between Realism and real-time performance. To deal with these problems, a full process parallelization simulation framework is proposed for parallelize each key stage of the simulation system. The framework is based on the SPH unified particle framework and has the advantage of high parallelism of the SPH method because of the particle form of solid used to describe and solve solid field quantities. For solving the solid fracture, a physics-geometry hybrid method with the high parallelism implementation is proposed. This method is also based on particle form to solve the solid field quantities so that have strong coupling with SPH framework. In term of neighborhood particle search, a spatial three-level index sorting based on the unified grid method is proposed to optimize neighborhood search processes including solid particles. Because the spatial characteristics of the solid fracture method is considered, the two methods can be closely combined with each other. In the stage of fluid rendering, in order to avoid the communication between GPU and CPU caused by surface extraction, the Screen Space Fluid Rendering method is adopted. In SSFR, the particle data is directly input into the rendering pipeline on GPU for rendering without transfer to CPU for extracting fluid mesh. For verifying the stability of the parallelized framework, performance and Realism of the simulation system, some scenes with different complexity are constructed for simulating. The results show that the framework can achieve well real-time performance in the scene with 650k particles and 180 solid chunks, and simulation is stable with the effects conformed to the phenomena of real-world physics.",
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"abstractType": "Regular",
"content": "Solid-fluid Interaction Simulation is the important research point in the field of fluid simulation. Existing researches mainly focus on the phenomena such as motion, deformation, infiltration, erosion, etc., and less attention is paid to the solid fracture caused by fluid impact. The simulation solutions used by the related researches have weakly coupling with the SPH solid-fluid interaction framework because their solid fracture methods need the geometric form for representing and processing the solid model. For the same reason, their methods have difficulty to parallelize and achieve the balance between Realism and real-time performance. To deal with these problems, a full process parallelization simulation framework is proposed for parallelize each key stage of the simulation system. The framework is based on the SPH unified particle framework and has the advantage of high parallelism of the SPH method because of the particle form of solid used to describe and solve solid field quantities. For solving the solid fracture, a physics-geometry hybrid method with the high parallelism implementation is proposed. This method is also based on particle form to solve the solid field quantities so that have strong coupling with SPH framework. In term of neighborhood particle search, a spatial three-level index sorting based on the unified grid method is proposed to optimize neighborhood search processes including solid particles. Because the spatial characteristics of the solid fracture method is considered, the two methods can be closely combined with each other. In the stage of fluid rendering, in order to avoid the communication between GPU and CPU caused by surface extraction, the Screen Space Fluid Rendering method is adopted. In SSFR, the particle data is directly input into the rendering pipeline on GPU for rendering without transfer to CPU for extracting fluid mesh. For verifying the stability of the parallelized framework, performance and Realism of the simulation system, some scenes with different complexity are constructed for simulating. The results show that the framework can achieve well real-time performance in the scene with 650k particles and 180 solid chunks, and simulation is stable with the effects conformed to the phenomena of real-world physics.",
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"normalizedAbstract": "Solid-fluid Interaction Simulation is the important research point in the field of fluid simulation. Existing researches mainly focus on the phenomena such as motion, deformation, infiltration, erosion, etc., and less attention is paid to the solid fracture caused by fluid impact. The simulation solutions used by the related researches have weakly coupling with the SPH solid-fluid interaction framework because their solid fracture methods need the geometric form for representing and processing the solid model. For the same reason, their methods have difficulty to parallelize and achieve the balance between Realism and real-time performance. To deal with these problems, a full process parallelization simulation framework is proposed for parallelize each key stage of the simulation system. The framework is based on the SPH unified particle framework and has the advantage of high parallelism of the SPH method because of the particle form of solid used to describe and solve solid field quantities. For solving the solid fracture, a physics-geometry hybrid method with the high parallelism implementation is proposed. This method is also based on particle form to solve the solid field quantities so that have strong coupling with SPH framework. In term of neighborhood particle search, a spatial three-level index sorting based on the unified grid method is proposed to optimize neighborhood search processes including solid particles. Because the spatial characteristics of the solid fracture method is considered, the two methods can be closely combined with each other. In the stage of fluid rendering, in order to avoid the communication between GPU and CPU caused by surface extraction, the Screen Space Fluid Rendering method is adopted. In SSFR, the particle data is directly input into the rendering pipeline on GPU for rendering without transfer to CPU for extracting fluid mesh. For verifying the stability of the parallelized framework, performance and Realism of the simulation system, some scenes with different complexity are constructed for simulating. The results show that the framework can achieve well real-time performance in the scene with 650k particles and 180 solid chunks, and simulation is stable with the effects conformed to the phenomena of real-world physics.",
"fno": "900900a048",
"keywords": [
"Computational Fluid Dynamics",
"Deformation",
"Flow Simulation",
"Fracture",
"Geometry",
"Hydrodynamics",
"Rendering Computer Graphics",
"Search Problems",
"Solid Modelling",
"180 Solid Chunks",
"Erosion",
"Fluid Impact",
"Fluid Mesh",
"Fluid Simulation",
"High Parallelism Implementation",
"Important Research Point",
"Neighborhood Particle Search",
"Neighborhood Search Processes",
"Parallelize Each Key Stage",
"Particle Data",
"Particle Form",
"Physics Geometry Hybrid Method",
"Process Parallelization Simulation Framework",
"Real Time Performance",
"Related Researches",
"Screen Space Fluid Rendering Method",
"Simulation Solutions",
"Solid Field Quantities",
"Solid Fracture Method",
"Solid Model",
"Solid Particles",
"Solid Fluid Interaction Simulation System",
"SPH Framework",
"SPH Method",
"SPH Solid Fluid Interaction Framework",
"SPH Unified Particle Framework",
"Unified Grid Method",
"Couplings",
"Solid Modeling",
"Fluids",
"Simulation",
"Graphics Processing Units",
"Solids",
"Rendering Computer Graphics",
"Fluid Simulation",
"Solid Fluid Interaction",
"Smoothed Particle Hydrodynamics",
"Solid Fracture",
"Parallelized Calculation"
],
"authors": [
{
"affiliation": "School of Control and Computer Engineering, North China Electric Power University,Baoding,Hebei,China",
"fullName": "Xuqiang Shao",
"givenName": "Xuqiang",
"surname": "Shao",
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{
"affiliation": "School of Control and Computer Engineering, North China Electric Power University,Baoding,Hebei,China",
"fullName": "Xin Zhang",
"givenName": "Xin",
"surname": "Zhang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "School of Control and Computer Engineering, North China Electric Power University,Baoding,Hebei,China",
"fullName": "Shihe Yang",
"givenName": "Shihe",
"surname": "Yang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "School of Control and Computer Engineering, North China Electric Power University,Baoding,Hebei,China",
"fullName": "Yizhong Jin",
"givenName": "Yizhong",
"surname": "Jin",
"__typename": "ArticleAuthorType"
}
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"pages": "48-54",
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"title": "Exploiting temporal parallelism in particle-based incompressive fluid simulation on FPGA",
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"abstract": "While the semiconductor manufacturing process is shrinking, the Bytes per Flop (B/F) ratio on recent machines is becoming lower. Particle-based computational fluid dynamics (CFD) methods such as Moving Particle Simulation (MPS) require a higher B/F ratio than that of stencil-based CFD methods. Techniques to reduce the B/F ratio by exploiting temporal parallelism is becoming popular in stencil-based CFD methods on CPU and GPU. It is also reported that a technique to combine temporal blocking with stencil buffer is suitable for FPGA and can outperform CPU and GPU. On the other hand, it has been considered that temporal parallelism cannot be exploited in the particle-based CFD methods. This is because the number of particles in each bucket, a three-dimensional grid covering a computational domain, changes every time-step. In this paper, we propose a technique to exploit temporal parallelism in MPS method, a particle-based CFD method for incompressive fluid. The key idea is that the buckets in MPS can be considered as stencils in stencil-based CFD. This is because the maximum number of particles in a bucket can be assumed empirically in the case of an incompressible fluid. To the best of our knowledge, this is the first research which exploits temporal parallelism in the particle-based incompressible fluid method. We implemented the proposed technique with a degree of temporal parallelism of three. We also optimized it on Intel Arria10 FPGA in Intel HLS, and measured the performance and resource consumption. The result shows that the optimized implementation with a degree of temporal parallelism of three achieved 2.1 times speedup compared with implementation without exploiting temporal parallelism on CPU.",
"abstracts": [
{
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"content": "While the semiconductor manufacturing process is shrinking, the Bytes per Flop (B/F) ratio on recent machines is becoming lower. Particle-based computational fluid dynamics (CFD) methods such as Moving Particle Simulation (MPS) require a higher B/F ratio than that of stencil-based CFD methods. Techniques to reduce the B/F ratio by exploiting temporal parallelism is becoming popular in stencil-based CFD methods on CPU and GPU. It is also reported that a technique to combine temporal blocking with stencil buffer is suitable for FPGA and can outperform CPU and GPU. On the other hand, it has been considered that temporal parallelism cannot be exploited in the particle-based CFD methods. This is because the number of particles in each bucket, a three-dimensional grid covering a computational domain, changes every time-step. In this paper, we propose a technique to exploit temporal parallelism in MPS method, a particle-based CFD method for incompressive fluid. The key idea is that the buckets in MPS can be considered as stencils in stencil-based CFD. This is because the maximum number of particles in a bucket can be assumed empirically in the case of an incompressible fluid. To the best of our knowledge, this is the first research which exploits temporal parallelism in the particle-based incompressible fluid method. We implemented the proposed technique with a degree of temporal parallelism of three. We also optimized it on Intel Arria10 FPGA in Intel HLS, and measured the performance and resource consumption. The result shows that the optimized implementation with a degree of temporal parallelism of three achieved 2.1 times speedup compared with implementation without exploiting temporal parallelism on CPU.",
"__typename": "ArticleAbstractType"
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"normalizedAbstract": "While the semiconductor manufacturing process is shrinking, the Bytes per Flop (B/F) ratio on recent machines is becoming lower. Particle-based computational fluid dynamics (CFD) methods such as Moving Particle Simulation (MPS) require a higher B/F ratio than that of stencil-based CFD methods. Techniques to reduce the B/F ratio by exploiting temporal parallelism is becoming popular in stencil-based CFD methods on CPU and GPU. It is also reported that a technique to combine temporal blocking with stencil buffer is suitable for FPGA and can outperform CPU and GPU. On the other hand, it has been considered that temporal parallelism cannot be exploited in the particle-based CFD methods. This is because the number of particles in each bucket, a three-dimensional grid covering a computational domain, changes every time-step. In this paper, we propose a technique to exploit temporal parallelism in MPS method, a particle-based CFD method for incompressive fluid. The key idea is that the buckets in MPS can be considered as stencils in stencil-based CFD. This is because the maximum number of particles in a bucket can be assumed empirically in the case of an incompressible fluid. To the best of our knowledge, this is the first research which exploits temporal parallelism in the particle-based incompressible fluid method. We implemented the proposed technique with a degree of temporal parallelism of three. We also optimized it on Intel Arria10 FPGA in Intel HLS, and measured the performance and resource consumption. The result shows that the optimized implementation with a degree of temporal parallelism of three achieved 2.1 times speedup compared with implementation without exploiting temporal parallelism on CPU.",
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"Particle Based Computational Fluid Dynamics Methods",
"Semiconductor Manufacturing Process",
"Bytes Per Flop Ratio",
"CPU",
"GPU",
"Moving Particle Simulation",
"Semiconductor Device Measurement",
"Fluids",
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"Graphics Processing Units",
"Parallel Processing",
"Particle Measurements",
"Field Programmable Gate Arrays",
"MPS Method",
"Incompressive Fluid",
"FPGA",
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"givenName": "Manfred",
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{
"abstractType": "Regular",
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"abstract": "X-ray angiographic images are regarded as the gold standard in the intra-operation of vascular diseases due to their high imaging quality and speed. However, due to many vascular- similar structures existing in the images, the accurate segmentation of the coronary artery is challenging. In this paper, we proposed a width-aware U-Net model by supervising the segmentation procedure using the label mask and centerline- derived width map. In our model, the centerlines of label masks are extracted and width maps are then computed. Together with the label mask, the width maps are then utilized to supervise the segmentation network. By comparing the proposed network with other state-of-the-art models, we can achieve superior results in discarding non-vascular artefacts and preserving the integrity of the whole vascular tree.",
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"content": "In many scientific fields including the medical field, we often utilize translucent viewing, that is, see-through viewing, to investigate the inner 3D structures of complex objects. On the other hand, it is known that stereoscopic vision is effective in allowing us to intuitively understand 3D shapes and to realize natural depth feel of visualized scenes. It is expected that the combination of these two visualization techniques, that is, translucent viewing and the stereoscopic vision, namely translucent stereoscopic visualization, should be effective for our easier and intuitive understanding of inner structures of 3D objects. However, the cognitive effects that arise when combining these two techniques have not been fully understood for us until now. In this paper, we investigate the cognitive effects that arise when combining these two techniques of computer visualization. We specially focus on medical volume visualization to investigate influences of the luminance gradient, which is inherent in the stochastic point-based rendering (SPBR) that we proposed recently. We conducted psychophysical experiments in which observers analysed the perceived 3D structure based on translucent stereoscopic visualization. The experiments are executed under the conditions of monocular, binocular viewing and motion parallax. We found that the luminance gradient is effective in the perceived depth magnitude in the translucent stereoscopic viewing of medical volume data.",
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"normalizedAbstract": "In many scientific fields including the medical field, we often utilize translucent viewing, that is, see-through viewing, to investigate the inner 3D structures of complex objects. On the other hand, it is known that stereoscopic vision is effective in allowing us to intuitively understand 3D shapes and to realize natural depth feel of visualized scenes. It is expected that the combination of these two visualization techniques, that is, translucent viewing and the stereoscopic vision, namely translucent stereoscopic visualization, should be effective for our easier and intuitive understanding of inner structures of 3D objects. However, the cognitive effects that arise when combining these two techniques have not been fully understood for us until now. In this paper, we investigate the cognitive effects that arise when combining these two techniques of computer visualization. We specially focus on medical volume visualization to investigate influences of the luminance gradient, which is inherent in the stochastic point-based rendering (SPBR) that we proposed recently. We conducted psychophysical experiments in which observers analysed the perceived 3D structure based on translucent stereoscopic visualization. The experiments are executed under the conditions of monocular, binocular viewing and motion parallax. We found that the luminance gradient is effective in the perceived depth magnitude in the translucent stereoscopic viewing of medical volume data.",
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"Data Visualisation",
"Medical Image Processing",
"Rendering Computer Graphics",
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"Three Dimensional Displays",
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"Cognitive Effects",
"Computer Visualization",
"Medical Volume Visualization",
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"Binocular Viewing",
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"Translucent Stereoscopic Viewing",
"Medical Volume Data",
"Depth Recognition",
"3 D Translucent Stereoscopic Imaging",
"Medical Volumes",
"Medical Field",
"Translucent Viewing",
"Inner 3 D Structures",
"Complex Objects",
"Stereoscopic Vision",
"Natural Depth Feel",
"Visualized Scenes",
"Visualization Techniques",
"Intuitive Understanding",
"Stochastic Point Based Rendering",
"Three Dimensional Displays",
"Stereo Image Processing",
"Isosurfaces",
"Rendering Computer Graphics",
"Biomedical Imaging",
"Surface Treatment",
"Translucent Stereoscopic Imaging",
"Depth Recognition",
"Luminance Gradient",
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"fullName": "Yurina Kitaura",
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"surname": "Hasegawa",
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"fullName": "Yuichi Sakano",
"givenName": "Yuichi",
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"fullName": "Roberto Lopez-Gulliver",
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"fullName": "Liang Li",
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"fullName": "Hiroshi Ando",
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"abstract": "Reflectance properties of real-world opaque materials can be represented by bidirectional reflectance distribution function (BRDF). Non-parametric BRDF becomes the main aspect nowadays because of its verisimilitude and generality. This paper introduces our BRDF capture equipment and a new compact non-parametric model based on curves for isotropic BRDF. 3D isotropic BRDF data are captured and assembled into a 2D matrix, then decomposed to several 1D curves through twice matrix decomposition, each curve has its own feature, such as specular shape curve, diffuse color curve, etc. The data are compressed effectively, and then reconstructed by these 1D curves during real-time rendering. More important, artist can edit the captured reflectance by adjusting one or more meaningful 1D curve intuitively. Experimental results show that, our method can capture the reflectance data, model and edit BRDF effectively.",
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{
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"content": "Reflectance properties of real-world opaque materials can be represented by bidirectional reflectance distribution function (BRDF). Non-parametric BRDF becomes the main aspect nowadays because of its verisimilitude and generality. This paper introduces our BRDF capture equipment and a new compact non-parametric model based on curves for isotropic BRDF. 3D isotropic BRDF data are captured and assembled into a 2D matrix, then decomposed to several 1D curves through twice matrix decomposition, each curve has its own feature, such as specular shape curve, diffuse color curve, etc. The data are compressed effectively, and then reconstructed by these 1D curves during real-time rendering. More important, artist can edit the captured reflectance by adjusting one or more meaningful 1D curve intuitively. Experimental results show that, our method can capture the reflectance data, model and edit BRDF effectively.",
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"fullName": "Hu Yong",
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"abstract": "The development of novel analytical BRDF models, as well as adaptive BRDF sampling approaches, rely on the appropriate BRDF measurement of real materials. The quality of measurements is even more critical when it comes to accurately representing anisotropic materials where the character of anisotropy is unknown (locations of anisotropic highlights, their width, shape, etc.). As currently there is a lack of dense yet noise-free BRDF anisotropic datasets, we introduce such unique measurements of three anisotropic fabric materials. In this paper we discuss a method of dense BRDF data acquisition, post processing, missing values interpolation, and analyze properties of the datasets. Our results are compared with photographs, dense data fitted and generated by two state-of-the art anisotropic BRDF models, and alternative measurements available.",
"abstracts": [
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"abstract": "Postural transitions are transitory movements with limited duration bounded by two physical activities, which represent the transition between two activities. Recognition of postural transitions is a challenging task due to low occurrence rate of transitions and short duration than physical activities. Postural transitions may decrease recognition accuracy when postural transitions are unspecified in the recognition system. This paper deals with the occurrence of postural transitions during activity performance. Hence, this paper proposes importance score driven random forests to recognize activities and postural transitions on the smartphone. The proposed model first selects relevant features rely on the relative importance of features, and then feed selected features to random forests. This model shows 100% recognition accuracy on a benchmark dataset and indicates that features created from accelerometer signals are more relevant for recognition than features created from gyroscope signals.",
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"abstract": "In this position paper, we want to point, with a little bit of provocation and maybe a pinch of fun, to some grievances of and also chances for today’s pool of (consumer) VR applications concerning the chosen user posture. In our opinion, the user is considered standing or required to stand in too many cases, and transitions between postures are usually entirely unsupported.",
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"abstract": "Location-based or Out-of-Home Entertainment refers to experiences such as theme and amusement parks, laser tag and paintball arenas, roller and ice skating rinks, zoos and aquariums, or science centers and museums among many other family entertainment and cultural venues. More recently, location-based VR has emerged as a new category of out-of-home entertainment. These VR experiences can be likened to social entertainment options such as laser tag, where physical movement is an inherent part of the experience versus at-home VR experiences where physical movement often needs to be replaced by artificial locomotion techniques due to tracking space constraints. In this work, we present the first VR study to understand the impact of natural walking in a large physical space on presence and user preference. We compare it with teleportation in the same large space, since teleportation is the most commonly used locomotion technique for consumer, at-home VR. Our results show that walking was overwhelmingly preferred by the participants and teleportation leads to significantly higher self-reported simulator sickness. The data also shows a trend towards higher self-reported presence for natural walking.",
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"content": "Location-based or Out-of-Home Entertainment refers to experiences such as theme and amusement parks, laser tag and paintball arenas, roller and ice skating rinks, zoos and aquariums, or science centers and museums among many other family entertainment and cultural venues. More recently, location-based VR has emerged as a new category of out-of-home entertainment. These VR experiences can be likened to social entertainment options such as laser tag, where physical movement is an inherent part of the experience versus at-home VR experiences where physical movement often needs to be replaced by artificial locomotion techniques due to tracking space constraints. In this work, we present the first VR study to understand the impact of natural walking in a large physical space on presence and user preference. We compare it with teleportation in the same large space, since teleportation is the most commonly used locomotion technique for consumer, at-home VR. Our results show that walking was overwhelmingly preferred by the participants and teleportation leads to significantly higher self-reported simulator sickness. The data also shows a trend towards higher self-reported presence for natural walking.",
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"abstract": "Chinese calligraphy art is of significant importance in Chinese traditional culture, and meanwhile, the way to carry it forward in our information era is a critical issue. Thus, aiming at making a progress of the problem mentioned above, we present a novel method of writing Chinese calligraphy on arbitrary surfaces (triangle mesh). In this paper, Gong Qi calligraphy (i.e. Qi fonts) is chosen as test samples in the reason that it is one of the most famous calligraphy in China for its liquid structure and concise strokes. This paper consists of following four steps. Firstly, each character is decomposed to strokes, and we use the dynamic balance of bouncing disks approach to achieve the strokes' centerlines and corresponding radii which will be applied in vectorizing the strokes of characters through Disk B-Spline Curves. Secondly, both a fast geodesic algorithm and an exponential map method are employed which the former is to calculate the geodesic distance between every two vertexes of the character mapped region, while the latter is to obtain the geodesic coordinates corresponding to every vertexes of the triangle meshes in 3D, namely the geodesic triangulation. Thirdly, 3D points coordinates on surfaces, correspond to vectored character in tangent plane, are acquired on the basis of geodesic triangulation, thereby the character is able to be written on the surfaces. At last, some experiments are accomplished to test and verify the accuracy and efficiency of our method.",
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"content": "Chinese calligraphy art is of significant importance in Chinese traditional culture, and meanwhile, the way to carry it forward in our information era is a critical issue. Thus, aiming at making a progress of the problem mentioned above, we present a novel method of writing Chinese calligraphy on arbitrary surfaces (triangle mesh). In this paper, Gong Qi calligraphy (i.e. Qi fonts) is chosen as test samples in the reason that it is one of the most famous calligraphy in China for its liquid structure and concise strokes. This paper consists of following four steps. Firstly, each character is decomposed to strokes, and we use the dynamic balance of bouncing disks approach to achieve the strokes' centerlines and corresponding radii which will be applied in vectorizing the strokes of characters through Disk B-Spline Curves. Secondly, both a fast geodesic algorithm and an exponential map method are employed which the former is to calculate the geodesic distance between every two vertexes of the character mapped region, while the latter is to obtain the geodesic coordinates corresponding to every vertexes of the triangle meshes in 3D, namely the geodesic triangulation. Thirdly, 3D points coordinates on surfaces, correspond to vectored character in tangent plane, are acquired on the basis of geodesic triangulation, thereby the character is able to be written on the surfaces. At last, some experiments are accomplished to test and verify the accuracy and efficiency of our method.",
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