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检索条件"任意字段=23rd ACM International Conference on 3D Web Technology"

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Influence of dielectric Overlay Permittivity on Size and Performance of Miniaturized ESPAR Antenna

Influence of Dielectric Overlay Permittivity on Size and Per...

引用

international conference on Microwaves, Radar and Wireless Communications

作者： M. Czelen M. Rzymowski K. Nyka L. Kulas Faculty of Electronics Telecommunications and Informatics Gdansk University of Technology Gdansk Poland

ISBN: (数字)9788394942175

ISBN: (纸本)9781728157870

In this paper, influence of dielectric overlay permittivity on miniaturized ESPAR antenna parameters is presented. ESPAR antenna is a low-cost and energy-efficient way to implement beam steering capability to a node and improve network performance. The antenna size reduction is obtained by embedding its active and passive elements in ABS based materials of relative permittivity equal to 4, 5.5 and 7.5 in order to achieve network node compact size. Simulation results of three optimized for particular dielectric constant designs are presented and tradeoff between dimensions reduction and performance is discussed. Selected materials and antenna design are dedicated to be fabricated in 3d print technology, so can be easily prototyped.

关键词： Three-dimensional displays dielectric constant Radar antennas Energy efficiency Microwave antenna arrays Permittivity Antenna radiation patterns

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Uncertainty depth estimation with gated images for 3d reconstruction

Uncertainty depth estimation with gated images for 3D recons...

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international conference on Intelligent Transportation

作者： Stefanie Walz Tobias Gruber Werner Ritter Klaus dietmayer Mercedes-Benz AG Wilhelm-Runge-Str Ulm Germany Institute of Measurement Control and Microtechnology Ulm University Albert-Einstein-Allee Ulm Germany

ISBN: (数字)9781728141497

ISBN: (纸本)9781728141503

Gated imaging is an emerging sensor technology for self-driving cars that provides high-contrast images even under adverse weather influence. It has been shown that this technology can even generate high-fidelity dense depth maps with accuracy comparable to scanning LidAR systems. In this work, we extend the recent Gated2depth framework with aleatoric uncertainty providing an additional confidence measure for the depth estimates. This confidence can help to filter out uncertain estimations in regions without any illumination. Moreover, we show that training on dense depth maps generated by LidAR depth completion algorithms can further improve the performance.

关键词： Logic gates Uncertainty Estimation Laser radar Three-dimensional displays Cameras Imaging

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A Survey of Semantic web Based Recommender Systems for E-Learning 23rd

A Survey of Semantic Web Based Recommender Systems for E-Lea...

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23rd international conference on Computational Science and its Applications (ICCSA)

作者： Aktas, Cevat Ciloglugil, Birol Ege Univ Inst Nat Sci Dept Comp Engn TR-35100 Izmir Turkiye Ege Univ Dept Comp Engn TR-35100 Izmir Turkiye

ISBN: (纸本)9783031371042;9783031371059

Recommender systems have been widely used in various domains such as e-commerce, e-learning and the entertainment sector especially for movie and music recommendation. E-learning has gained more attention recently, as the Covid-19 pandemic forced a mandatory shift from face-to-face education to online education. In this regard, taking into consideration the individual differences of learners such as learning styles, prior knowledge level, and motivation level play a vital role in acceptance and usage levels of e-learning systems by the learners and academic success levels of students using these e-learning systems. Semantic web technologies enable modeling these individual differences with ontologies and provide a valuable foundation for knowledge based recommender systems. Various learning resource or learning object ontologies that model learning materials and learner model ontologies that model learner profiles have been developed and used successfully in different educational recommender systems. These ontologies and interaction data of learners with e-learning systems provide valuable data for recommender systems to operate on. Collaborative filtering and content based filtering approaches have been used to analyze these data and implement educational recommender systems. Therefore, in this paper, we provide a review of semantic web based recommender systems conducted at the e-learning domain. We surveyed different aspects of educational recommender systems such as the data sources used for recommendations and the approaches utilized for implementation. Finally, we present the implications, limitations and future work directions in the field of educational recommender systems.

关键词： E-Learning Recommender Systems Semantic web Ontology

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Sea Surface Temperature Prediction Approach Based on 3d CNN and LSTM with Attention Mechanism

Sea Surface Temperature Prediction Approach Based on 3D CNN ...

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international conference on Advanced Communication technology (ICACT)

作者： Baiyou Qiao Zhongqiang Wu Zhong Tang Gang Wu School of Computer Science and Engineering Northeastern University China Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Northeastern University China

ISBN: (数字)9791188428069

ISBN: (纸本)9781665447027

Sea Surface Temperature (SST) is an important physical quantity of the ocean system. The accurate prediction of SST is essential for studying physical ocean phenomena and forecasting the ocean environment information. In this paper, a SST prediction approach based on 3-diminsional Convolutional Neural Network (3d CNN) and Long Short-Term Memory (LSTM) network with attention mechanism is proposed, which considers the spatial correlation and temporal dependency of SST data. Firstly, the machine learning algorithm XGBoost is used to extract the long period time features of each SST data. Then the 3d CNN is used to capture the spatial correlations among SST field data composed of multiple observation points in a selected sea area, followed by the LSTM model to extract the time dependency features of the SST field time series data, and the attention mechanism is added to weight the output of each step of LSTM model to adjust the prediction results and improve the prediction accuracy of the approach. A series of experimental results show that the proposed approach has lower complexity, higher training efficiency and prediction accuracy, which is significantly better than the existing prediction models.

关键词： Sea surface Three-dimensional displays Correlation Computational modeling Predictive models Feature extraction Ocean temperature

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Finite Element Analysis of Patient-Specific Heart Model with Simulated Aortic Stenosis

Finite Element Analysis of Patient-Specific Heart Model with...

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IEEE Symposium on Bioinformatics and Bioengineering (BIBE)

作者： Smiljana Tomasevic Igor Saveljic Lazar Velicki Themis Exarchos Nenad Filipovic Faculty of Engineering University of Kragujevac Kragujevac Serbia Bioengineering Research and Development Center - BioIRC Kragujevac Serbia Institute for Information Technologies Kragujevac Serbia Bioengineering Research and Development Center - BioIRC Kragujevac Serbia Serbia Faculty of Medicine Institute of Cardiovascular Diseases Sremska Kamenica University of Novi Sad Novi Sad Serbia Department of Informatics Ionian University Corfu Greece Unit of Medical Technology and Intelligent Information Systems University of Ioannina Ioannina Greece

The main aim of this study was to evaluate the impact of simulated aortic stenosis on velocity and shear stress distribution within the patient-specific heart model by using computational Finite Element (FE) method. The three-dimensional (3d) patient-specific model of heart, including surrounding arterial and vein structures, was reconstructed based on Computed Tomography (CT) scan images in order to obtain the 3d FE mesh. Computational Fluid dynamics (CFd) analysis was performed, with applied equivalent material characteristics and boundary conditions. Using one patient-specific heart model with clinically confirmed hypertrophic cardiomyopathy, three different cases were simulated: (i) without aortic stenosis, (ii) with 30% of aortic stenosis (mild aortic stenosis), and (iii) with 70% of aortic stenosis (severe aortic stenosis). The initial results of the study (velocity and shear stress distribution) were quantified concerning anatomical patient's structures and simulating different degrees of aortic stenosis to analyse the blood flow patterns, as well as the correlation between shear stress and aortic and left ventricular remodelling. It was found that gradient of shear stress distribution increases with stenosis degree, especially in the ascending aorta which can lead to different aortopathies and endothelial diseases. due to the difficulties in obtaining such characteristics in vitro or in vivo, the performed computational analysis gave better insight into the biomechanics of the heart and aortic stenosis that is needed to achieve improvements in surgical repair techniques and presurgical planning.

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Lymph Node Gross Tumor Volume detection in Oncology Imaging via Relationship Learning Using Graph Neural Network 23rd

Lymph Node Gross Tumor Volume Detection in Oncology Imaging ...

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23rd international conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020

作者： Chao, Chun-Hung Zhu, Zhuotun Guo, dazhou Yan, Ke Ho, Tsung-Ying Cai, Jinzheng Harrison, Adam P. Ye, Xianghua Xiao, Jing Yuille, Alan Sun, Min Lu, Le Jin, dakai National Tsing Hua University Hsinchu City Taiwan PAII Inc. BethesdaMD United States Johns Hopkins University BaltimoreMD United States Chang Gung Memorial Hospital Linkou Taiwan The First Affiliated Hospital Zhejiang University Hangzhou China Ping An Technology Shenzhen China

ISBN: (纸本)9783030597276

determining the spread of lymph node gross tumor volume (GTVLN) is essential in defining the respective resection or irradiating regions for the downstream workflows of surgical resection and radiotherapy for many cancers. different from the more common enlarged lymph node (LN), GTVLN also includes smaller ones if associated with high positron emission tomography signals and/or any metastasis signs in CT. This is a daunting task. In this work, we propose a unified LN appearance and inter-LN relationship learning framework to detect the true GTVLN. This is motivated by the prior clinical knowledge that LNs form a connected lymphatic system, and the spread of cancer cells among LNs often follows certain pathways. Specifically, we first utilize a 3d convolutional neural network with ROI-pooling to extract the GTVLN’s instance-wise appearance features. Next, we introduce a graph neural network to further model the inter-LN relationships where the global LN-tumor spatial priors are included in the learning process. This leads to an end-to-end trainable network to detect by classifying GTVLN. We operate our model on a set of GTVLN candidates generated by a preliminary 1st-stage method, which has a sensitivity of > 85 % at the cost of high false positive (FP) (> 15 FPs per patient). We validate our approach on a radiotherapy dataset with 142 paired PET/RTCT scans containing the chest and upper abdominal body parts. The proposed method significantly improves over the state-of-the-art (SOTA) LN classification method by 5.5 % and 13.1 % in F1 score and the averaged sensitivity value at 2, 3, 4, 6 FPs per patient, respectively. © 2020, Springer Nature Switzerland AG.

关键词： Radiotherapy

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Colour triplet-valued wavelets and splines

Colour triplet-valued wavelets and splines

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international Symposium on Image and Signal Processing and Analysis

作者： V. Labunets A. Maidan E. Labunets-Rundblad J. Astola Tampere International Center for Signal Processing Tampere University of Technology Tampere Finland

ISBN: (纸本)9539676940

The concept of colour and and multispectral image recognition connects all the topics we are considering. Colour (multispectral) image processing is investigated using an algebraic approach based on triplet numbers. In the algebraic approach, each image element is considered not as a 3d vector, but as a triplet number. The main goal of the paper is to show that triplet algebra can be used to solve colour image processing problems in a natural and effective manner. We propose novel methods for wavelet transforms and spline implementation in colour space.

关键词： Algebra Color Image processing Image recognition Multispectral imaging Signal processing Wavelet transforms Animals History Visual system

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Optimum design of Cooling Fan considering Experimental Method for Three-Phase Induction Motor

Optimum Design of Cooling Fan considering Experimental Metho...

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international conference on Electrical Machines and Systems (ICEMS)

作者： Min-Seok Kim Jung-Hyung Park Kyu-Seok Lee Sung-Ho Lee Jang-Young Choi Smart Mobility Materials & Components Research Group Korea Institute of Industrial Technology Gwangju Korea Chungnam National University Deajeon Korea

ISBN: (数字)9784886864192

ISBN: (纸本)9781728189307

In this paper, the optimum design method of the cooling fan for the industrial 7.5kW class induction motor is presented. The shape of the cooling fan was made with a 3d printer through the experimental design method. The manufactured cooling fan was optimally designed using test and statistical methods. The optimum design result of cooling fan is validated through IEC60034-2-1.

关键词： Fans Cooling Wind speed Induction motors Mathematical model Blades Linear programming

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dense-JANet for Monocular 3d Object detection

Dense-JANet for Monocular 3D Object Detection

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international conference on Intelligent Transportation

作者： Xiaoqing Shang Zhiwei Cheng Su Shi Zhuanghao Cheng Hongcheng Huang Institute of Automotive Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9781728141497

ISBN: (纸本)9781728141503

3d object detection is one of the vital tasks in many fields, especially for autonomous driving. Among all technology paths for this task, the detection based on monocular images has been proven an efficient way with low cost. However, the performance of most current algorithms is far from satisfactory. The current leading systems can't achieve the accuracy which is comparable with LidAR-based algorithms, while the real-time problems also exist. In this paper, we propose a novel anchor-free model for monocular 3d object detection. We choose the effective modified denseNet as the feature extraction part. The Joint Pyramid Upsampling is applied to fuse features maps for multiply scales, and the Atrous Spatial Pyramid Pooling is used to maximize the context information. Finally, 5 convolution layers are connected with the feature map to predict the information. We call the model dense-JANet and train it on the large autonomous driving dataset, called nuScenes, which has more scenes and data than KITTI. Experiments show that dense-JANet's performance exceeds SOTA model on small object prediction and orientation prediction, while the proposed model can fully meet the real-time requirements.

关键词： Three-dimensional displays Feature extraction Two dimensional displays Object detection Convolution Heating systems Solid modeling

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development of 3d Viscoelastic Crustal deformation Analysis Solver with data-driven Method on GPU 23rd

Development of 3D Viscoelastic Crustal Deformation Analysis...

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23rd international conference on Computational Science, ICCS 2023

作者： Murakami, Sota Fujita, Kohei Ichimura, Tsuyoshi Hori, Takane Hori, Muneo Lalith, Maddegedara Ueda, Naonori Earthquake Research Institute and Department of Civil Engineering The University of Tokyo Tokyo Japan Center for Computational Science RIKEN Kobe Japan Japan Agency for Marine-Earth Science and Technology Yokohama Japan Center for Advanced Intelligence Project RIKEN Tokyo Japan

ISBN: (纸本)9783031360206

In this paper, we developed a 3d viscoelastic analysis solver with a data-driven method on GPUs for fast computation of highly detailed 3d crustal structure models. Here, the initial solution is obtained with high accuracy using a data-driven predictor based on previous time-step results, which reduces the number of multi-grid solver iterations and thus reduces the computation cost. To realize memory saving and high performance on GPUs, the previous time step results are compressed by multiplying a random matrix, and multiple Green’s functions are solved simultaneously to improve the memory-bound matrix-vector product kernel. The developed GPU-based solver attained an 8.6-fold speedup from the state-of-art multi-grid solver when measured on compute nodes of AI Bridging Cloud Infrastructure at National Institute of Advanced Industrial Science and technology. The fast analysis method enabled calculating 372 viscoelastic Green’s functions for a large-scale 3d crustal model of the Nankai Trough region with 4.2 × 10 9 degrees of freedom within 333 s per time step using 160 A100 GPUs, and such results were used to estimate coseismic slip distribution. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Finite element method

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