检索结果-内蒙古大学图书馆

arXiv 2022年

作者： Hao, Wanming Li, Junjie Sun, Gangcan Huang, Chongwen Zeng, Ming Dobre, Octavia A. Yuen, Chau The School of Electrical and Information Engineering Zhengzhou University Zhengzhou450001 China The College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China The Department of Electrical Engineering and Computer Engineering Universite Laval QCG1V 0A6 Canada The Faculty of Engineering and Applied Science Memorial University St. JohnsNLA1B 3X5 Canada The Singapore University of Technology and Design 487372 Singapore

In this paper, we investigate the energy efficiency (EE) problem under reconfigurable intelligent surface (RIS)aided secure cell-free networks, where multiple legitimate users and eavesdroppers (Eves) exist. We formulate a max-min secure EE optimization problem by jointly designing the distributed active beamforming and artificial noise at base stations as well as the passive beamforming at RISs under practical constraints. To deal with it, we first divide the original optimization problem into two sub-ones, and then propose an iterative optimization algorithm to solve each sub-problem based on the fractional programming, constrained convex-convex procedure (CCCP) and semi-definite programming (SDP) techniques. After that, these two sub-problems are alternatively solved until convergence, and the final solutions are obtained. Next, we extend to the imperfect channel state information of the Eves' links, and investigate the robust SEE beamforming optimization problem by bringing the outage probability constraints. Based on this, we first transform the uncertain outage probability constraints into the certain ones by the bernstein-type inequality and sphere boundary techniques, and then propose an alternatively iterative algorithm to obtain the solutions of the original problem based on the S-procedure, successive convex approximation, CCCP and SDP techniques. Finally, the simulation results are conducted to show the effectiveness of the proposed schemes. © 2022, CC BY.

关键词： Beamforming

来源：评论

学校读者我要写书评

暂无评论

COVIDX-Net: A Framework of Deep Learning Classifiers to Diagnose COVID-19 in X-Ray Images

arXiv

引用

arXiv 2020年

作者： Hemdan, Ezz El-Din Shouman, Marwa A. Karar, Mohamed Esmail Department of Computer Science and Engineering Faculty of Electronic Engineering Menoufia University Egypt Department of Industrial Electronics and Control Engineering Faculty of Electronic Engineering Menoufia University Egypt Department of Computer Engineering College of Computing and Information Technology Shaqra University Saudi Arabia

Background and Purpose: Coronaviruses (CoV) are perilous viruses that may cause Severe Acute Respiratory Syndrome (SARS-CoV), Middle East Respiratory Syndrome (MERS-CoV). The novel 2019 Coronavirus disease (COVID-19) was discovered as a novel disease pneumonia in the city of Wuhan, China at the end of 2019. Now, it becomes a Coronavirus outbreak around the world, the number of infected people and deaths are increasing rapidly every day according to the updated reports of the World Health Organization (WHO). Therefore, the aim of this article is to introduce a new deep learning framework;namely COVIDX-Net to assist radiologists to automatically diagnose COVID-19 in X-ray images. Materials and Methods: Due to the lack of public COVID-19 datasets, the study is validated on 50 Chest X-ray images with 25 confirmed positive COVID-19 cases. The COVIDX-Net includes seven different architectures of deep convolutional neural network models, such as modified Visual Geometry Group Network (VGG19) and the second version of Google MobileNet. Each deep neural network model is able to analyze the normalized intensities of the X-ray image to classify the patient status either negative or positive COVID-19 case. Results: Experiments and evaluation of the COVIDX-Net have been successfully done based on 80-20% of X-ray images for the model training and testing phases, respectively. The VGG19 and Dense Convolutional Network (DenseNet) models showed a good and similar performance of automated COVID-19 classification with f1-scores of 0.89 and 0.91 for normal and COVID-19, respectively. The worst classification performance is obtained for the InceptionV3 model with f1-scores of 0.67 for normal cases and 0.00 for COVID-19 cases. Conclusions: This study demonstrated the useful application of deep learning models to classify COVID-19 in X-ray images based on the proposed COVIDX-Net framework. Clinical studies are the next milestone of this research work. Copyright © 2020, The Authors. All ri

关键词： Coronavirus

来源：评论

学校读者我要写书评

暂无评论

Conditional score-based diffusion models for solving inverse problems in mechanics

arXiv

引用

arXiv 2024年

作者： Dasgupta, Agnimitra Ramaswamy, Harisankar Murgoitio-Esandi, Javier Foo, Ken Li, Runze Zhou, Qifa Kennedy, Brendan F. Oberai, Assad A. Department of Aerospace & Mechanical Engineering University of Southern California Los AngelesCA90089 United States BRITElab Harry Perkins Institute of Medical Research QEII Medical Centre NedlandsWA6009 Australia Centre for Medical Research The University of Western Australia PerthWA6009 Australia Department of Electrical Electronic & Computer Engineering School of Engineering The University of Western Australia PerthWA6009 Australia Institute of Physics Faculty of Physics Astronomy and Informatics Nicolaus Copernicus University in Toruń Grudziadzka 5 Torun87-100 Poland Department of Mechanical Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Alfred E. Mann Department of Biomedical Engineering University of Southern California Los AngelesCA90089 United States

We propose a framework to perform Bayesian inference using conditional score-based diffusion models to solve a class of inverse problems in mechanics involving the inference of a specimen’s spatially varying material properties from noisy measurements of its mechanical response to loading. Conditional score-based diffusion models are generative models that learn to approximate the score function of a conditional distribution using samples from the joint distribution. More specifically, the score functions corresponding to multiple realizations of the measurement are approximated using a single neural network, the so-called score network, which is subsequently used to sample the posterior distribution using an appropriate Markov chain Monte Carlo scheme based on Langevin dynamics. Training the score network only requires simulating the forward model. Hence, the proposed approach can accommodate black-box forward models and complex measurement noise. Moreover, once the score network has been trained, it can be re-used to solve the inverse problem for different realizations of the measurements. We demonstrate the efficacy of the proposed approach on a suite of high-dimensional inverse problems in mechanics that involve inferring heterogeneous material properties from noisy measurements. Some examples we consider involve synthetic data, while others include data collected from actual elastography experiments. Further, our applications demonstrate that the proposed approach can handle different measurement modalities, complex patterns in the inferred quantities, non-Gaussian and non-additive noise models, and nonlinear black-box forward models. The results show that the proposed framework can solve large-scale physics-based inverse problems efficiently. © 2024, CC BY.

关键词： Markov chains

来源：评论

学校读者我要写书评

暂无评论

The Important Role of Diatomite on Multifunctional Modified Separator of Li-S Battery

SSRN

引用

SSRN 2024年

作者： Yan, Chenyu Jiang, Zhiyi Yang, Caihong Dong, Xiongbo Zhang, Shilin Tu, Feiyue Li, Tianbao Li, Mitch Guijun Tang, Aidong Yang, Huaming Engineering Research Center of Nano-Geomaterials of Ministry of Education Laboratory of Advanced Mineral Materials Key Laboratory of Functional Geomaterials in China Nonmetallic Minerals Industry Faculty of Materials Science and Chemistry China University of Geosciences Wuhan430074 China College of Chemistry and Chemical Engineering Central South University Changsha410083 China Changsha Research Institute of Mining and Metallurgy Co. LTD Changsha410012 China Division of Integrative Systems and Design Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong School of Minerals Processing and Bioengineering Central South University Changsha410083 China

The commercial applications of Li-S batteries are limited by decreased cycling performance caused by the shuttle effect of polysulfides, slower kinetic reaction rates, and lithium anode dendrites. This study demonstrates the important role of diatomite (DT) in regulating cycle performance of modified separator for Li-S batteries. A multifunctional separator (Co/NC/DT) with DT as a carrier assembled high loading Co nanocluster (size 2-4 nm) is prepared. The N-doped carbon is immobilized via Si-N bond between DT and N-doped carbon. The depth profiles of XPS indicates that the ratio of pyrrolic N to pyridinic N of Co/NC/DT reaches 5.31 at the etching of 100 nm vs 0.83 for Co/NC at surface, which suggesting that mainly N species is pyrrolic N after the addition of DT. Theoretical calculations confirm that cobalt nanoclusters grown on pyrrolic N-doped carbon have a lower adsorption energy for a series of polysulfides species compared to that on pyridinic N-doped carbon and can reduce the energy barrier, especially only 0.09 eV for reduction from Li2S6 to Li2S4. In-situ X-ray diffraction analysis confirms Co/NC/DT can effectively promote formation of Li2S. Lithium anode in-situ optical microscopy observation shows the modified separator could reduce lithium dendrites effectively. Li-S battery assembled with the modified separator can reach an initial capacity of 1331.3 mAh g-1 at 0.2 C and cycle 1500 cycles at 1.0 C with a decay of only 0.039% per cycle. Through regulation of DT, Co/NC/DT accelerates the conversion from long-chain sulfur to short-chain sulfur and Li+ transfer rate, resulting in improving cycling performance. © 2024, The Authors. All rights reserved.

关键词： Separators

来源：评论

学校读者我要写书评

暂无评论

Development of a PZT device-based power-generating shoes for disaster-affected areas

Development of a PZT device-based power-generating shoes for...

引用

International Conference on Telecommunication, electronic and computer engineering 2019, ICTEC 2019

作者： Tsukagoshi, S. Seto, K. Hashimoto, S. Basari, A.A. Division of Electronics and Informatics School of Science and Technology Faculty of Gunma University 1-5-1 Tenjin-cho Kiryu Gunma376-8515 Japan Faculty of Electronic and Computer Engineering Universiti Teknikal Malaysia Melaka Hang Tuah Jaya Durian Tunggal Melaka76100 Malaysia

A PZT device is an element that generates electric power when an impact is applied by vibration. Currently, PZT devices are installed on the floor near the ticket gates to supply power to station equipment, and on the floor of bridges to turn on LEDs at night. Since the current generated by the PZT device is small, there is a disadvantage that the electric power obtained is small. In this paper, we developed a power-generating shoe using PZT devices for use in disaster-affected areas where power shortages tend to occur. The validity of the developed power-generating shoes is experimentally evaluated under the variation of PZT device, shoes and secondary batteries. At present, the result is that it is possible to charge about 1.5% of mobile phones at the maximum. In order to reduce loss and obtain more power, it is necessary to improve shoes and to build a charge / discharge circuit. © 2020 IOP Publishing Ltd. All rights reserved.

关键词： Floors

来源：评论

学校读者我要写书评

暂无评论

Low-sampling rate data-based failure diagnosis by using self-powered system

Low-sampling rate data-based failure diagnosis by using self...

引用

International Conference on Telecommunication, electronic and computer engineering 2019, ICTEC 2019

作者： Okada, S. Hashimoto, S. Basari, A.A. Division of Electronics and Informatics School of Science and Technology Faculty of Gunma University 1-5-1 Tenjin-cho Kiryu Gunma376-8515 Japan Faculty of Electronic and Computer Engineering Universiti Teknikal Malaysia Melaka Hang Tuah Jaya Durian Tunggal Melaka76100 Malaysia

In recent years, in order to solve critical problems such as global warming and climate change that have been occurring in the world, research on the application of power generation methods which are harmless to the environment has been underway. In this paper, a fault diagnosis method using the self-powered sensing system based on vibration power generation is proposed. Frequency analysis is known as a general failure diagnosis method. However, due to the limitation of the generated power, the sampling period of data acquisition is as large as a few-ten millisecond. For this reason, it is difficult to use frequency analysis for fault diagnosis using vibration power generation. Therefore, a fault diagnosis system corresponding to an increase in the sampling period is constructed by introducing machine learning. An acceleration sensor used for data acquisition is driven by the vibration power generator attached to factory equipment. The diagnosis is performed by wireless-transmitted acceleration data. By introducing a machine learning strategy into the diagnosis, accurate diagnosis can be performed even for data with low-sampling rate. The effectiveness of the proposed diagnosis method is experimentally evaluated by using the factory equipment. © 2020 IOP Publishing Ltd. All rights reserved.

关键词： Failure analysis

来源：评论

学校读者我要写书评

暂无评论

Low-resolution human pose estimation

arXiv

引用

arXiv 2021年

作者： Wang, Chen Zhang, Feng Zhu, Xiatian Ge, Shuzhi Sam School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China School of Computer Science and Technology Nanjing University of Posts and Telecommunications Nanjing China Centre for Vision Speech and Signal Processing Faculty of Engineering and Physical Sciences University of Surrey GuildfordGU2 7XH United Kingdom Department of Electrical and Computer Engineering National University of Singapore Singapore Singapore

Human pose estimation has achieved significant progress on images with high imaging resolution. However, low-resolution imagery data bring nontrivial challenges which are still under-studied. To fill this gap, we start with investigating existing methods and reveal that the most dominant heatmap-based methods would suffer more severe model performance degradation from low-resolution, and offset learning is an effective strategy. Established on this observation, in this work we propose a novel Confidence-Aware Learning (CAL) method which further addresses two fundamental limitations of existing offset learning methods: inconsistent training and testing, decoupled heatmap and offset learning. Specifically, CAL selectively weighs the learning of heatmap and offset with respect to ground-truth and most confident prediction, whilst capturing the statistical importance of model output in mini-batch learning manner. Extensive experiments conducted on the COCO benchmark show that our method outperforms significantly the state-of-the-art methods for low-resolution human pose estimation. © 2021, CC BY-SA.

关键词： Learning systems

来源：评论

学校读者我要写书评

暂无评论

Thermal Non-Equilibrium Analysis on PN junction 21

Thermal Non-Equilibrium Analysis on PN junction

引用

21st International Conference on electronic Packaging technology, ICEPT 2020

作者： Gao, Chenshan Wang, Shaogang Tan, Chunjian Liu, Xu Zhou, Quan Ye, Huaiyu Education Ministry of China Chongqing University and College of Optoelectronic Engineering Chongqing University Key Laboratory of Optoelectronic Technology Systems Chongqing China Delft University of Technology Faculty of Electrical Engineering Mathematics and Computer Science Delft Netherlands Delft University of Technology Electronic Components Technology and Materials Delft Netherlands Chongqing University Shenzhen Institute of Wide-bandgap Semiconductors Delft University of Technology Chongqing China

ISBN: (纸本)9781728168265

At present, non-equilibrium thermodynamics is an important theory and method for studying the phenomenon of small scales. In this work, by studying the temperature changes of PN junctions under different voltage conditions and doping concentrations, the micro-scale semiconductor materials PN junctions in non-equilibrium thermodynamics and thermal phenomena are researched. It is found that under the effect of lower voltage, the temperature of the PN junction will first decrease and then increase, and as the voltage increases, this phenomenon will gradually disappear. This shows that under certain voltage conditions, the phenomenon of unbalanced junction temperature of the PN junction exists, which will provide a huge impetus for the development of the reliability of solar cells, light-emitting diodes, high-frequency devices, sensors and measurement methods. © 2020 IEEE.

关键词： Junction temperature

来源：评论

学校读者我要写书评

暂无评论

I-V performance analysis of flexible back Illuminated Dye Sensitized Solar cells (DSSCS) with various platinum catalyst contents 1

I-V performance analysis of flexible back Illuminated Dye Se...

引用

1st International Conference on Emerging Electrical Energy, electronics and Computing Technologies 2019, ICE4CT 2019

作者： Shamsudin, N.H. Shafie, S. Ab Kadir, M.Z.A. Ahmad, F. Chachuli, S.A.M. Sulaiman, Y. Department of Electrical and Electronic Engineering Faculty of Engineering Universiti Putra Malaysia Serdang Selangor43400 Malaysia Faculty of Electrical Engineering Universiti Teknikal Malaysia Melaka Hang Tuah Jaya Durian Tunggal76100 Malaysia Institute of Advanced Technology Universiti Putra Malaysia Serdang Selangor43400 Malaysia Institute of Power Engineering Universiti Tenaga Nasional Putrajaya Campus Selangor Kajang43000 Malaysia Centre for Electromagnetic and Lightning Protection Universiti Putra Malaysia Serdang Selangor43400 Malaysia Department of Electronic System Engineering Malaysia-Japan International Institute of Technology Universiti Teknologi Malaysia Kuala Lumpur53400 Malaysia Faculty of Electronic Engineering and Computer Engineering Universiti Teknikal Malaysia Melaka Melaka76100 Malaysia

Flexible based Dye Sensitized Solar Cells (DSSCs) in nanotechnology revolution have always been in the thick of things where fabrication method and achieving good performances are concerned. Such concerns were adjudicated by improvising four(4) innate DSSCs structures composed of photoanode, semiconductor, electrolyte and counter electrode. This paper aims to observe the impact of changing Platinum(Pt) volumes on the counter electrodes of DSSCs by conducting tests on 0.2mm Titanium (Ti) foil based photoanode DSSCs. The deposition of Pt was varied into 70l, 50l and 30l accordingly by spin coating technique at 1500 rpm. All samples were synthesized, deposited with Pt and assembled before being tested under solar light simulator of 1000W/cm2. Samples with 70l Pt deposition indicated a higher efficiency () of 2.83%, even though it allowed less light penetration, while the 30l Pt deposition sample provided efficiency () of 0.88% with more light penetration. © Published under licence by IOP Publishing Ltd.

关键词： Dye-sensitized solar cells

来源：评论

学校读者我要写书评

暂无评论

Improved Numerical Method for Skin Effect Computing of Conductors Having Rectangular Cross Sections 19

Improved Numerical Method for Skin Effect Computing of Condu...

引用

19th International Symposium on Electromagnetic Fields in Mechatronics, Electrical and electronic engineering, ISEF 2019

作者： Raicevic, Nebojsa Butrylo, Boguslaw Aleksic, Slavoljub Barukcic, Marinko University of Nis Faculty of Electronic Engineering Nis Serbia Bialystok University of Technology Faculty of Electrical Engineering Bialystok Poland University of Osijek Faculty of Electrical Engineering Computer Science and Information Technology Osijek Croatia

ISBN: (纸本)9781728115603

A procedure for numerical solution of skin effect integral equations is presented in this paper. The function of current density, in a conductor having rectangular cross-section, can be approximated by means of the finite functional series with basic functions which automatically satisfy wave equation. The unknown complex coefficients are determined by using least square method and iterative method. Differential evolution optimization algorithm is applied for minimization of error functional. This approach leads to a very accurate solution, even in the case when only two terms in current approximation are adopted, giving a considerable advantage over the existing results. Being that the electromagnetic field components depend on the current density derivation, the proposed method gives very accurate solution not only for current density distribution and resistance, but also for field components and for internal inductivity coefficients. Hybrid Boundary Elements Method is used to determine the current distribution in the cross sections of a group of conductors. © 2019 IEEE.

关键词： Iterative methods

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：