检索结果-内蒙古大学图书馆

Surface Modification of (001) Facets Dominated TiO2 with Ozone for Adsorption and Photocatalytic Degradation of Gaseous Toluene

引用

Chinese Journal of Chemical Physics 2019年第5期32卷 611-619页

作者： Yue Yang Zhi-yu Wang Fan Zhang Yi Fan Jing-jing Dong Song Sun Chen Gao Jun Bao National Synchrotron Radiation Laboratory Collaborative Innovation Center of Chemistry for Energy Materials Key Laboratory of Surface and Interface Chemistry and Energy Catalysis of Anhui Higher Education Institutes University of Science and Technology of China Hefei 230029 China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing 100191 China School of Chemistry and Chemical Engineering Anhui University Hefei 230601 China Beijing Advanced Sciences and Innovation center Chinese Academy of Sciences Beijing 101407 China

This study investigated the positive effect of surface modification with ozone on the photocatalytic performance of anatase TiO2 with dominated（001） facets for toluene *** performance of photocatalyst was tested on a home-made volatile organic compounds degradation system. The ozone modification, toluene adsorption and degradation mechanism were established by a combination of various characterization methods, in situ diffuse reflectance infrared fourier transform spectroscopy, and density functional theory *** surface modification with ozone can significantly enhance the photocatalytic degradation performance for toluene. The abundant unsaturated coordinated 5 c-Ti sites on（001）facets act as the adsorption sites for ozone. The formed Ti–O bonds reacted with H2O to generate a large amount of isolated Ti5 c-OH which act as the adsorption sites for toluene,and thus significantly increase the adsorption capacity for toluene. The outstanding photocatalytic performance of ozone-modified TiO2 is due to its high adsorption ability for toluene and the abundant surface hydroxyl groups, which produce very reactive OH·radicals under irradiation. Furthermore, the O2 generated via ozone dissociation could combine with the photogenerated electrons to form superoxide radicals which are also conductive to the toluene degradation.

关键词： Ozone modification (001) Facets Toluene degradation TiO2 In situ diffuse reflectance infrared fourier transform spectroscopy

来源：评论

学校读者我要写书评

暂无评论

Three-Dimensional Reconstruction Method with Parameter Optimization for Point Cloud Based on Kinect v2

Three-Dimensional Reconstruction Method with Parameter Optim...

引用

作者： Kai-zhang WANG Tong-kai LU Qi-hang YANG Xi-hao FU Ze-hong LU Bo-lun WANG Xin JIANG Key Laboratory of Mathematics Informatics and Behavioral Semantics and School of Mathematics and Systems Science Beihang University Peng Cheng Laboratory Beijing Advanced Innovation Center for Big Data and Brain Computing (BDBC) School of Mathematical Science Peking University

Three-Dimensional(3D) reconstruction is a significant part in the field of computer vision. In this paper, we use Kinect v2 to obtain the 3D point cloud. As a consumer used 3D sensor, Kinect has numerous advantages such as low price, relative high dot per inch(DPI) and frames per second(FPS) and strong robustness. During the experiment, the object was placed on a turntable spinning and stop for every 12°, collecting 30 images of point cloud in total. Then we used Iterated Closest Points(ICP) algorithm to calculate the optimal rotation matrix and translation matrix to match all point cloud into the same coordinate. After that, three algorithms including Statistical Outlier Removal, Movement Least Squares(MLS) and Voxelgrid were used to reduce the noise. At last, we applied greedy projection algorithm to generate the triangulate mesh. During the procession, we observed the relationship between parameters and outcome and drew pictures to have the data more visible, which gave out the optimal parameters in return.

关键词： 3D Reconstruction Parameter optimization Kinect v2

来源：评论

学校读者我要写书评

暂无评论

Adaptive NMS: Refining pedestrian detection in a crowd

arXiv

引用

arXiv 2019年

作者： Liu, Songtao Huang, Di Wang, Yunhong Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University State Key Laboratory of Software Development Environment Beihang University School of Computer Science and Engineering Beihang University Beijing100191

Pedestrian detection in a crowd is a very challenging issue. This paper addresses this problem by a novel NonMaximum Suppression (NMS) algorithm to better refine the bounding boxes given by detectors. The contributions are threefold: (1) we propose adaptive-NMS, which applies a dynamic suppression threshold to an instance, according to the target density;(2) we design an efficient subnetwork to learn density scores, which can be conveniently embedded into both the single-stage and two-stage detectors;and (3) we achieve state of the art results on the CityPersons and CrowdHuman benchmarks. Copyright © 2019, The Authors. All rights reserved.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Refining HTN methods via task insertion with preferences (ArXiv version)

arXiv

引用

arXiv 2019年

作者： Xiao, Zhanhao Wan, Hai Zhuo, Hankui Hankz Herzig, Andreas Perrussel, Laurent Chen, Peilin School of Data and Computer Science Sun Yat-sen University Guangzhou China IRIT Toulouse France University of Toulouse Toulouse France Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education China Guangdong Province Key Laboratory of Big Data Analysis and Processing China

Hierarchical Task Network (HTN) planning is showing its power in real-world planning. Although domain experts have partial hierarchical domain knowledge, it is time-consuming to specify all HTN methods, leaving them incomplete. On the other hand, traditional HTN learning approaches focus only on declarative goals, omitting the hierarchical domain knowledge. In this paper, we propose a novel learning framework to refine HTN methods via task insertion with completely preserving the original methods. As it is difficult to identify incomplete methods without designating declarative goals for compound tasks, we introduce the notion of prioritized preference to capture the incompleteness possibility of methods. Specifically, the framework first computes the preferred completion profile w.r.t. the prioritized preference to refine the incomplete methods. Then it finds the minimal set of refined methods via a method substitution operation. Experimental analysis demonstrates that our approach is effective, especially in solving new HTN planning instances. Copyright © 2019, The Authors. All rights reserved.

关键词： Domain Knowledge

来源：评论

学校读者我要写书评

暂无评论

Adaptive unimodal cost volume filtering for deep stereo matching

arXiv

引用

arXiv 2019年

作者： Zhang, Youmin Chen, Yimin Bai, Xiao Yu, Suihanjin Yu, Kun Li, Zhiwei Yang, Kuiyuan State Key Laboratory of Software Development Environment School of Computer Science and Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing Jiangxi Research Institute Beihang University Beijing China DeepMotion

State-of-the-art deep learning based stereo matching approaches treat disparity estimation as a regression problem, where loss function is directly defined on true disparities and their estimated ones. However, disparity is just a byproduct of a matching process modeled by cost volume, while indirectly learning cost volume driven by disparity regression is prone to overfitting since the cost volume is under constrained. In this paper, we propose to directly add constraints to the cost volume by filtering cost volume with unimodal distribution peaked at true disparities. In addition, variances of the unimodal distributions for each pixel are estimated to explicitly model matching uncertainty under different contexts. The proposed architecture achieves state-of-the-art performance on Scene Flow and two KITTI stereo benchmarks. In particular, our method ranked the 1st place of KITTI 2012 evaluation and the 4th place of KITTI 2015 evaluation (recorded on 2019.8.20). The codes of AcfNet are available at: https://***/DeepMotionAIResearch/ DenseMatchingBenchmark. Copyright © 2019, The Authors. All rights reserved.

关键词： Uncertainty analysis

来源：评论

学校读者我要写书评

暂无评论

A Novel Differential System Construction Method for Complex Surface Based on Aerodynamic Design

A Novel Differential System Construction Method for Complex ...

引用

作者： Dan-lei YE Xin JIANG Guan-ying HUO Cheng SU Ze-hong LU Bo-lun WANG Zhi-ming ZHENG Key Laboratory of Mathematics Informatics and Behavioral Semantics (LMIB) School of Mathematics and Systems Science Beihang University Peng Cheng Laboratory Beijing Advanced Innovation Center for Big Data and Brain Computing (BDBC) School of Mathematical Science Peking University

In this paper, a novel complex surface construction method for aerodynamic design is proposed based on differential system. In order to simplify the process of calculating and analyzing the flow field above the surface, we introduce a high-dimensional truncation method of Navier-Stokes equations to transform the complex partial differential system into an ordinary one. Concretely, we excute the Fourier expansion along some selected directions which are called wave vector sets, preserving the local properties of the solutions of Navier-Stokes equations. Further, we use the truncated ordinary differential system to describe the shape of complex surface. Experiments show that our differential system construction method for complex surface dedicated to aerodynamic design has better fitting results than the traditional linear fitting method.

关键词： High-dimensional truncation Navier-Stokes equations Nonlinear ordinary differential system

来源：评论

学校读者我要写书评

暂无评论

KE-GAN: Knowledge Embedded Generative Adversarial Networks for Semi-Supervised Scene Parsing

KE-GAN: Knowledge Embedded Generative Adversarial Networks f...

引用

IEEE/CVF Conference on Computer Vision and Pattern Recognition

作者： Mengshi Qi Yunhong Wang Jie Qin Annan Li State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University China Beijing Advanced Innovation Center for Big Data and Brain Computing Inception Institute of Artificial Intelligence UAE

In recent years, scene parsing has captured increasing attention in computer vision. Previous works have demonstrated promising performance in this task. However, they mainly utilize holistic features, whilst neglecting the rich semantic knowledge and inter-object relationships in the scene. In addition, these methods usually require a large number of pixel-level annotations, which is too expensive in practice. In this paper, we propose a novel Knowledge Embedded Generative Adversarial Networks, dubbed as KE-GAN, to tackle the challenging problem in a semi-supervised fashion. KE-GAN captures semantic consistencies of different categories by devising a Knowledge Graph from the large-scale text corpus. In addition to readily-available unlabeled data, we generate synthetic images to unveil rich structural information underlying the images. Moreover, a pyramid architecture is incorporated into the discriminator to acquire multi-scale contextual information for better parsing results. Extensive experimental results on four standard benchmarks demonstrate that KE-GAN is capable of improving semantic consistencies and learning better representations for scene parsing, resulting in the state-of-the-art performance.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Distributed State Estimation for Heterogeneous Mobile Sensor Networks with Sensor Faults

Distributed State Estimation for Heterogeneous Mobile Sensor...

引用

第三十八届中国控制会议

作者： Yingrong Yu Siting Peng Qingdong Li Xiwang Dong Zhang Ren Science and Technology on Aircraft Control Laboratory School of Automation Science and Electrical Engineering Beihang University Beijing Electro-Mechanical Engineering Institute Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University

Consensus-based distributed state estimation for homogeneous mobile sensor networks has been widely studied currently. However, the sensors used for target detection and tracking in practical applications usually have different physical properties, different measuring range or accuracy. In order to realize data exchange between sensors which are of heterogeneity and to obtain a consistent and precise target state estimation result, an improved Cubature Kalman Filtering(CKF) method based on weighted average consensus theory is put forward herein. Moreover, the adverse impacts caused by sensor faults have been taken into consideration in modeling. The stochastic boundedness of the estimation errors for the discussed sensor networks is proved in the paper. Finally, numerical simulations are provided to demonstrate the validity of the proposed method.

关键词： Cubature Kalman Filter weighted average consensus theory target state estimation mobile sensor networks stochastic boundedness

来源：评论

学校读者我要写书评

暂无评论

Review of artificial intelligence techniques in imaging data acquisition, segmentation and diagnosis for COVID-19

arXiv

引用

arXiv 2020年

作者： Shi, Feng Wang, Jun Shi, Jun Wu, Ziyan Wang, Qian Tang, Zhenyu He, Kelei Shi, Yinghuan Shen, Dinggang Department of Research and Development Shanghai United Imaging Intelligence Co. Ltd. Shanghai200232 Key Laboratory of Specialty Fiber Optics and Optical Access Networks Shanghai Institute for Advanced Communication and Data Science School of Communication and Information Engineering Shanghai University Shanghai200444 United Imaging Intelligence CambridgeMA02140 United States Institute for Medical Imaging Technology School of Biomedical Engineering Shanghai Jiao Tong University Shanghai200030 China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 Medical School of Nanjing University Nanjing China National Institute of Healthcare Data Science Nanjing University Nanjing210093 China National Key Laboratory for Novel Software and Technology Nanjing University Nanjing China

The pandemic of coronavirus disease 2019 (COVID-19) is spreading all over the world. Medical imaging such as X-ray and computed tomography (CT) plays an essential role in the global fight against COVID-19, whereas the recently emerging artificial intelligence (AI) technologies further strengthen the power of the imaging tools and help medical specialists. We hereby review the rapid responses in the community of medical imaging (empowered by AI) toward COVID-19. For example, AI-empowered image acquisition can significantly help automate the scanning procedure and also reshape the workflow with minimal contact to patients, providing the best protection to the imaging technicians. Also, AI ca n improve work efficiency by accurate delination of infections in X-ray and CT images, facilitating subsequent quantification. Moreover, the computer-aided platforms help radiologists make clinical decisions, i.e., for disease diagnosis, tracking, and prognosis. In this review paper, we thus cover the entire pipeline of medical imaging and analysis techniques involved with COVID-19, including image acquisition, segmentation, diagnosis, and follow-up. We particularly focus on the integration of AI with X-ray and CT, both of which are widely used in the frontline hospitals, in order to depict the latest progress of medical imaging and radiology fighting against COVID-19. Copyright © 2020, The Authors. All rights reserved.

关键词： Coronavirus

来源：评论

学校读者我要写书评

暂无评论

Transferring knowledge distillation for multilingual social event detection

arXiv

引用

arXiv 2021年

作者： Ren, Jiaqian Peng, Hao Jiang, Lei Wu, Jia Tong, Yongxin Wang, Lihong Bai, Xu Wang, Bo Yang, Qiang Institute of Information Engineering Chinese Academy of Sciences The School of Cyber Security University of Chinese Academy of Sciences Beijing100041 China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100083 China The School of Cyber Science and Technology Beihang University Beijing100083 China Institute of Information Engineering Chinese Academy of Sciences Beijing100041 China The Department of Computing Macquarie University Sydney Australia The State Key Laboratory of Software Development Environment The School of Computer Science and Engineering Beihang University Beijing100083 China The National Computer Network Emergency Response Technical Team Coordination Center of China Beijing100029 China The Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong AI Group WeBank Co. Ltd. China

Recently published graph neural networks (GNNs) show promising performance at social event detection tasks. However, most studies are oriented toward monolingual data in languages with abundant training samples. This has left the more common multilingual settings and lesser-spoken languages relatively unexplored. Thus, we present a GNN that incorporates cross-lingual word embeddings for detecting events in multilingual data streams. The first exploit is to make the GNN work with multilingual data. For this, we outline a construction strategy that aligns messages in different languages at both the node and semantic levels. Relationships between messages are established by merging entities that are the same but are referred to in different languages. Non-English message representations are converted into English semantic space via the cross-lingual word embeddings. The resulting message graph is then uniformly encoded by a GNN model. In special cases where a lesser-spoken language needs to be detected, a novel cross-lingual knowledge distillation framework, called CLKD, exploits prior knowledge learned from similar threads in English to make up for the paucity of annotated data. Experiments on both synthetic and real-world datasets show the framework to be highly effective at detection in both multilingual data and in languages where training samples are scarce. © 2021, CC BY.

关键词： Embeddings

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：