检索结果-内蒙古大学图书馆

Structure and motifs of iron oxides from 1 to 3 TPa

Physical Review Materials 2022年第4期6卷 043602-043602页

作者： Feng Zheng Yang Sun Renhai Wang Yimei Fang Feng Zhang Bo Da Shunqing Wu Cai-Zhuang Wang Renata M. Wentzcovitch Kai-Ming Ho Department of Physics OSED Key Laboratory of Low Dimensional Condensed Matter Physics (Department of Education of Fujian Province) Jiujiang Research Institute Xiamen University Xiamen 361005 China Department of Applied Physics and Applied Mathematics Columbia University New York New York 10027 USA School of Physics and Optoelectronic Engineering Guangdong University of Technology Guangzhou 510006 China Department of Physics Iowa State University Ames Iowa 50011 USA Research and Services Division of Materials Data and Integrated System National Institute for Materials Science 1-1 Namiki Tsukuba Ibaraki 305-0044 Japan Department of Earth and Environmental Sciences Columbia University New York New York 10027 USA Lamont–Doherty Earth Observatory Columbia University Palisades New York 10964 USA

Iron oxides are fundamental components of planet-forming materials. Understanding the Fe-O system's behavior and properties under high pressure can help us identify many new phases and states possible in exoplanetary interiors, especially terrestrial ones. Using the adaptive genetic algorithm, we investigate the structure of iron oxides for a wide range of stoichiometries (0.25≤xO≤0.8) at 1, 2, and 3 TPa. Five ground-state structures with Fe2O, FeO, Fe3O5, FeO2, and FeO4 compositions are identified. Phonon calculations confirm their dynamical stability. The ab initio molecular dynamics simulations confirm the thermal stability of Fe-rich phases at high temperatures. The calculated density of states suggests that, except for FeO4, all phases are metallic, but their carrier densities decrease with increasing pressure and oxygen content. The cluster alignment analysis of stable and metastable phases shows that several motifs may coexist in a structure of iron oxides with low O content. In contrast, most iron oxides with high O content adopt a simple bcc motif at TPa pressures. Our results provide a crystal structure database of iron oxides for modeling and understanding the interiors of exoplanets.

关键词： Crystal structure Pressure effects Structural phase transition First-principles calculations Genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

A more compact object detector head network with feature enhancement and relational reasoning

arXiv

引用

arXiv 2021年

作者： Zhang, Wenchao Fu, Chong Chang, Xiangshi Zhao, Tengfei Li, Xiang Sham, Chiu-Wing School of Computer Science and Engineering Northeastern University Shenyang110819 China Engineering Research Center of Security Technology of Complex Network System Ministry of Education China Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Northeastern University Shenyang110819 China Baidu Smart Life Group NO. 10 Xibeiwang East Street Ke Ji Yuan Haidian District Beijing100193 China School of Computer Science University of Auckland New Zealand

Modeling implicit feature interaction patterns is of significant importance to object detection tasks. However, in the two-stage detectors, due to the excessive use of hand-crafted components, it is very difficult to reason about the implicit relationship of the instance features. To tackle this problem, we analyze three different levels of feature interaction relationships, namely, the dependency relationship between the cropped local features and global features, the feature autocorrelation within the instance, and the cross-correlation relationship between the instances. To this end, we propose a more compact object detector head network (CODH), which can not only preserve global context information and condense the information density, but also allows instance-wise feature enhancement and relational reasoning in a larger matrix space. Without bells and whistles, our method can effectively improve the detection performance while significantly reducing the parameters of the model, e.g., with our method, the parameters of the head network is 0.6× smaller than the state-of-the-art Cascade R-CNN, yet the performance boost is 1.3% on COCO test-dev. Without losing generality, we can also build a more lighter head network for other multi-stage detectors by assembling our method. Copyright © 2021, The Authors. All rights reserved.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

End-to-End AI-Based Point-of-Care Diagnosis system for Classifying Respiratory Illnesses and Early Detection of COVID-19

arXiv

引用

arXiv 2020年

作者： Belkacem, Abdelkader Nasreddine Ouhbi, Sofia Lakas, Abderrahmane Benkhelifa, Elhadj Chen, Chao Department of Computer and Network Engineering CIT UAEU UAE Department of Computer Science and Software Engineering CIT UAEU UAE Cloud Computing and Applications Reseach Lab Staffordshire University United Kingdom Key Laboratory of Complex System Control Theory and Application Tianjin University of Technology China

Respiratory symptoms can be a caused by different underlying conditions, and are often caused by viral infections, such as Influenza-like illnesses or other emerging viruses like the Coronavirus. These respiratory viruses, often, have common symptoms, including coughing, high temperature, congested nose, and difficulty breathing. However, early diagnosis of the type of the virus, can be crucial, especially in cases such as the recent COVID-19 pandemic. One of the factors that contributed to the spread of the pandemic, was the late diagnosis or confusing it with regular flu-like symptoms. Science has proved that one of the possible differentiators of the underlying causes of these different respiratory diseases is coughing, which comes in different types and forms. Therefore, a reliable lab-free tool for early and more accurate diagnosis that can differentiate between different respiratory diseases is very much needed. This paper proposes an end-to-end portable system that can record data from patients with symptom, including coughs (voluntary or involuntary) and translate them into health data for diagnosis, and with the aid of machine learning, classify them into different respiratory illnesses, including COVID-19. With the ongoing efforts to stop the spread of the COVID-19 disease everywhere today, and against similar diseases in the future, our proposed low cost and user-friendly solution can play an important part in the early diagnosis. Copyright © 2020, The Authors. All rights reserved.

关键词： Diagnosis

来源：评论

学校读者我要写书评

暂无评论

Finite time anti-synchronization of complex-valued neural networks with bounded asynchronous time-varying delays

arXiv

引用

arXiv 2019年

作者： Liu, Xiwei Li, Zihan Department of Computer Science and Technology Tongji University Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai201804 China

In this paper, we studied the finite time anti-synchronization of master-slave coupled complex-valued neural networks (CVNNs) with bounded asynchronous time-varying delays. With the decomposing technique and the generalized {ξ, ∞}-norm, several criteria for ensuring the finite-time anti-synchronization are obtained. The whole anti-synchronization process can be divided into two parts: first, the norm of each error state component will change from initial values to 1 in finite time, then from 1 to 0 in fixed time. Therefore, the whole time is finite. Finally, one typical numerical example is presented to demonstrate the correctness of our obtained results. key words: Anti-synchronization, asynchronous, complex-valued neural network, finite time, time-varying delay Copyright © 2019, The Authors. All rights reserved.

关键词： Time varying control systems

来源：评论

学校读者我要写书评

暂无评论

Research and implementation of POI recommendation system integrating temporal feature 3

Research and implementation of POI recommendation system int...

引用

3rd IEEE International Conference on Big Data Analysis, ICBDA 2018

作者： Liu, Jinxin Jiao, Xu Jin, Youzhi Liu, Xinyu Liu, Li Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology Tianjin China

ISBN: (纸本)9781538647936

Point-of-Interest is an interesting research topic of personalized recommendation. In this paper, a new position-based recommendation framework is proposing by using the time attribute. We establish a user matrix with user check-in data sets that contain time and location information. The user matrix is divided into the sub-matrices according to the set period and then every sub-matrix is decomposed into the user checking preference matrix and position feature matrix by using the non-negative matrix factorization. The user's attendance preferences at each time are integrated to get the user's final check-in preference for the candidate location to make recommendations more consistent with the needs of users. © 2018 IEEE.

关键词： Non-negative matrix factorization

来源：评论

学校读者我要写书评

暂无评论

Joint Channel Estimation and Decoding Design for 5G-Enabled V2V Channel

引用

China Communications 2018年第7期15卷 39-46页

作者： Xuanfan Shen Yong Liao Xuewu Dai Ming Zhao Kai Liu Dan Wang Center of Communication and TT&C Chongqing University The State Key Laboratory of Integrated Services Networks Xidian University Faculty of Engineering and Environment Northumbria University Key Laboratory of Dependable Service Computing in Cyber Physical Society Chongqing University Ministry of Education Chongqing Key Laboratory of Mobile Communication Technology Chongqing University of Posts and Telecommunication

This paper addresses the problem of channel estimation in 5G-enabled vehicular-to-vehicular(V2V) channels with high-mobility environments and non-stationary feature. Considering orthogonal frequency division multiplexing(OFDM) system, we perform extended Kalman filter(EKF) for channel estimation in conjunction with Iterative Detector & Decoder(IDD) at the receiver to improve the estimation accuracy. The EKF is proposed for jointly estimating the channel frequency response and the time-varying time correlation coefficients. And the IDD structure is adopted to reduce the estimation errors in EKF. The simulation results show that, compared with traditional methods, the proposed method effectively promotes the system performance.

关键词： orthogonal frequency division multiplexing（OFDM）non-stationary channel estimation extended Kalman filter（EKF）Iterative Detector ＆ Decoder（IDD）vehicular-to-vehicular（V2V）

来源：评论

学校读者我要写书评

暂无评论

Point adversarial self mining: A simple method for facial expression recognition

arXiv

引用

arXiv 2020年

作者： Liu, Ping Lin, Yuewei Meng, Zibo Lu, Lu Deng, Weihong Zhou, Joey Tianyi Yang, Yi Institute of High Performance Computing Agency for Science Technology and Research Singapore Singapore Centre for Artificial Intelligence University of Technology Sydney Sydney Australia Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunications Beijing China Brookhaven National Laboratory UptonNY United States InnoPeak Technology Inc. Palo AltoCA United States Key Laboratory of Medical Molecular Virology School of Basic Medical Sciences Fudan University Shanghai China

In this paper, we propose a simple yet effective approach, named Point Adversarial Self Mining (PASM), to improve the recognition accuracy in facial expression recognition. Unlike previous works focusing on designing specific architectures or loss functions to solve this problem, PASM boosts the network capability by simulating human learning processes: providing updated learning materials and guidance from more capable teachers. Specifically, to generate new learning materials, PASM leverages a point adversarial attack method and a trained teacher network to locate the most informative position related to the target task, generating harder learning samples to refine the network. The searched position is highly adaptive since it considers both the statistical information of each sample and the teacher network capability. Other than being provided new learning materials, the student network also receives guidance from the teacher network. After the student network finishes training, the student network changes its role and acts as a teacher, generating new learning materials and providing stronger guidance to train a better student network. The adaptive learning materials generation and teacher/student update can be conducted more than one time, improving the network capability iteratively. Extensive experimental results validate the efficacy of our method over the existing state of the arts for facial expression recognition. Copyright © 2020, The Authors. All rights reserved.

关键词： Iterative methods

来源：评论

学校读者我要写书评

暂无评论

Machine learning approach for the prediction of electron inelastic mean free paths

引用

Physical Review Materials 2021年第3期5卷 033802-033802页

作者： Xun Liu Lihao Yang Zhufeng Hou Bo Da Kenji Nagata Hideki Yoshikawa Shigeo Tanuma Yang Sun Zejun Ding Hefei National Laboratory for Physical Sciences at Microscale and Department of Physics University of Science and Technology of China Hefei Anhui 230026 People's Republic of China Research and Services Division of Materials Data and Integrated System National Institute for Materials Science 1-1 Namiki Tsukuba Ibaraki 305-0044 Japan State Key Laboratory of Structural Chemistry Fujian Institute of Research on the Structure of Matter Chinese Academy of Sciences Fuzhou 350002 China Research Center for Advanced Measurement and Characterization National Institute for Materials Science 1-2-1 Sengen Tsukuba Ibaraki 305-0047 Japan Department of Applied Physics and Applied Mathematics Columbia University New York NY 10027 USA

The prediction of electron inelastic mean free paths (IMFPs) from simple material parameters is a challenging problem in studies using electron spectroscopy and microscopy. Herein, we propose a machine learning (ML) approach to predict IMFPs from some basic material property data. The ML model showed excellent performance based on the calculated IMFPs for a group of 41 elemental materials [Li, Be, C (graphite), C (diamond), C (glassy), Na, Mg, Al, Si, K, Sc, Ti, V, Cr, Fe, Co, Ni, Cu, Ge, Y, Nb, Mo, Ru, Rh, Pd, Ag, In, Sn, Cs, Gd, Tb, Dy, Hf, Ta, W, Re, Os, Ir, Pt, Au, and Bi] from a previous paper [Shinotsuka et al., Surf. Interface Anal. 47, 871 (2015); Surf. Interface Anal. 47, 1132 (2015)]. which was comparable with that of the robust Tanuma-Powell-Penn (TPP-2M) formula. The developed ML model was then extended to materials that do not have reported IMFPs in the database. The IMFPs for 18 transition and lanthanide metals (Mn, Zn, Zr, Tc, Cd, La, Ce, Pr, Nd, Pm, Sm, Eu, Ho, Er, Tm, Yb, Lu, and Hg) were predicted by the ML model. In the comparison with full-Penn algorithm-calculated IMFPs through two newly found experimental energy loss functions (ELFs), i.e., Mn and Zr, the Gaussian process regression-predicted IMFPs not only agreed well with those calculated using the TPP-2M formula in the energy range >50 eV but were also consistent with the trend of IMFPs calculated through experimental ELFs in the range of 2.7–50 eV, where the TPP-2M formula cannot be used. Our findings suggest that ML is very powerful and efficient and has great potential to complete a database of IMFPs for materials that can prove solutions closer to reality than empirical models on materials with similar physical and chemical properties and can be applied to other different situations for correlated information prediction.

关键词： Data analysis Machine learning Spectroscopy

来源：评论

学校读者我要写书评

暂无评论

Hierarchical attention generative adversarial networks for cross-domain sentiment classification

arXiv

引用

arXiv 2019年

作者： Zhang, Yuebing Miao, Duoqian Wang, Jiaqi Department of Computer Science and Technology Tongji University Shanghai China Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai China

Cross-domain sentiment classification (CDSC) is an importance task in domain adaptation and sentiment classification. Due to the domain discrepancy, a sentiment classifier trained on source domain data may not works well on target domain data. In recent years, many researchers have used deep neural network models for cross-domain sentiment classification task, many of which use Gradient Reversal Layer (GRL) to design an adversarial network structure to train a domain-shared sentiment classifier. Different from those methods, we proposed Hierarchical Attention Generative Adversarial Networks (HAGAN) which alternately trains a generator and a discriminator in order to produce a document representation which is sentimentdistinguishable but domain-indistinguishable. Besides, the HAGAN model applies Bidirectional Gated Recurrent Unit (Bi-GRU) to encode the contextual information of a word and a sentence into the document representation. In addition, the HAGAN model use hierarchical attention mechanism to optimize the document representation and automatically capture the pivots and non-pivots. The experiments on Amazon review dataset show the effectiveness of HAGAN. Copyright © 2019, The Authors. All rights reserved.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Identification based on PRT gravity tunnel of continuous electrocardiogram 14

Identification based on PRT gravity tunnel of continuous ele...

引用

14th International Conference on Natural Computation, Fuzzy systems and Knowledge Discovery, ICNC-FSKD 2018

作者： Dai, Min Meng, Danyang Jia, Feng Ma, Miaoling Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology Tianjin China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology Tianjin China

ISBN: (纸本)9781538680971

An electrocardiogram (ECG)identification method is proposed based on PRT triangle gravity tunnel of continuous electrocardiogram. The PRT center of gravity is defined by the P, R, T fiducial points in ECG signal, and the gravity tunnel of continuous PRT points is described as a matrix. The European distance is used to determine the similarity between two matrices. The performance of the proposed method is tested on MIT-BIH Database and the ECG data collected in practical environment from 25 healthy college students. Several group experiments were carried out and the average recognition accuracy is 99.87%. Comparing with the traditional correlation coefficient method, experimental results show that the average recognition accuracy is increased 1.66% when using the proposed method. © 2018 IEEE.

关键词： Electrocardiograms

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：