检索结果-内蒙古大学图书馆

HIV-Positive Men Are More Likely to Be Hyper Linked Within College Student Social Network-Northeast China,2017-2018

China CDC weekly 2022年第43期4卷 951-955页

作者： Menglong Li Huichao Wu Hongmei Yan Jiawulan Zunong Hongtao Hui Hailong Li Zhenhua Yang Sten HVermund Yifei Hu Department of Child Adolescent Health and Maternal CareSchool of Public HealthCapital Medical UniversityBeijingChina General Management Office Xidan CampusPeking Union Medical College HospitalBeijingChina Department of HIV/STD Prevention and Control Heilongjiang Provincial Center for Disease Control and PreventionHarbin CityHeilongjiang ProvinceChina Heilongjiang Kangtong Community Harbin CityHeilongjiang ProvinceChina School of Computer and Information Engineering Harbin University of CommerceHarbin CityHeilongjiang ProvinceChina Dean of the office Yale School of Public HealthYale UniversityNew HavenCTUSA.

What is already known about this topic?Men who have sex with men(MSM)bear a disproportionate burden of new human immunodeficiency virus(HIV)infections and young MSM demonstrate parallel internet-driven HIV incident infection and dynamic social *** is added by this report?The HIV positive prevalence and incidence among college MSM were 3.8%and 2.9 per 100 person-years,respectively,while these rates were 13.9%and 10.5 per 100 person-years,respectively,among their social *** overall HIV positive prevalence was 7.2%in Northeast ***-positive MSM have comparatively more social contacts than HIVseronegative *** are the implications for public health practice?Hyper-linkages found in app-based social networks play an important role in HIV transmission via risky sexual behavior and suggest options for online intervention to promote HIV prevention.

关键词： Northeast prevalence HIV

来源：评论

学校读者我要写书评

暂无评论

Early warning of abnormal state of wind turbine based on principal component analysis and RBF neural network

Early warning of abnormal state of wind turbine based on pri...

引用

Power and Electrical engineering (ACPEE), 5th Asia Conference on

作者： Sihan Chen Yongguang Ma Liangyu Ma Fuyu Qiao Hao Yang School of Control and Computer Engineering North China Electric Power University Baoding China

This paper proposes an early warning method for abnormal state of wind turbines based on PCA-RBF neural network model. According to the operation and control principle of the wind turbine, determine the power as the output parameter of the model, and use correlation analysis to filter out the input parameters with strong correlation with the output power of the unit, and use the RBF and PCA-RBF methods to establish normal operating conditions Comparative analysis of the unit model. The experimental results show that the input parameters determined by the correlation coefficient are more reasonable, and the model established by the PCA-RBF neural network is more accurate than the traditional RBF neural network model. Therefore, the neural network model based on PCA-RBF is selected, combined with the sliding window method to monitor the operating status of the unit, and realize the early warning of the abnormal status of the wind turbine. The example shows that the method can give early warning in time before the failure, which proves the feasibility of the method.

关键词： Electrical engineering Analytical models Correlation Neural networks Predictive models Maintenance engineering Wind turbines

来源：评论

学校读者我要写书评

暂无评论

A Novel Edge Computing Offloading and Privacy-preserving Scheme for Energy Internet

A Novel Edge Computing Offloading and Privacy-preserving Sch...

引用

Cryptography, Security and Privacy (CSP), IEEE International Conference on

作者： Kunchang Li Xu Han Yifan Yang Shuhao Wang Runhua Shi Jianbin Li School of control and Computer Engineering North China Electric Power University Beijing China

ISBN: (数字)9781728186214

ISBN: (纸本)9781728186221

With the rapid development of Internet of things technology, “massive” data generated by Internet of things terminals, which leads to the problem of excessive cloud computing pressure and network delay. Therefore, edge computing emerges as the time requires. At the same time, the privacy security of edge computing is particularly important. In this paper, ZSS short signature algorithm and Paillier homomorphic cryptosystem are used to propose a secure and efficient edge computing privacy-preserving in energy Internet. The scheme can achieve data confidentiality and privacy-preserving. Finally, the model of unloading is established to solve the problem quickly. Experimental results show that our scheme has less computation and communication overhead.

关键词： Privacy Data privacy Computational modeling Delays Cryptography Internet of Things Edge computing

来源：评论

学校读者我要写书评

暂无评论

FPN-GAN: Multi-class Small Object Detection in Remote Sensing Images

FPN-GAN: Multi-class Small Object Detection in Remote Sensin...

引用

IEEE International Conference on Cloud Computing and Big Data Analysis (ICCCBDA)

作者： Tanvir Ahmad Xiaona Chen Ali Syed Saqlain Yinglong Ma School of Control and Computer Engineering North China Electric Power University Beijing China

Despite the recent dramatic advances in object detection, detecting a small object in general and in remote sensing images is still a challenging problem. One main reason for this is the appearance of small objects in images. Specifically low resolution and noisy representation makes it hard to detect small objects. We tickle down this problem by proposing a novel object detector based on Generative adversarial network (GAN), which we called FPN-GAN in short. The proposed method is composed of GAN, Resnet-50 as a backbone, and Feature Pyramid Network for detection. We combine both of these methods to achieve a single end to end GAN model for multi class-small object detection and image enhancement simultaneously. Extensive experiments on a challenging benchmark DIOR remote sensing dataset demonstrate the superiority of the proposed method for small objects as well as large and the medium size objects.

关键词： Training Image resolution Object detection Benchmark testing Generative adversarial networks Feature extraction Sensors

来源：评论

学校读者我要写书评

暂无评论

Linear Active Disturbance Rejection control of Output Probability Density Function

Linear Active Disturbance Rejection Control of Output Probab...

引用

computer Information Science and Artificial Intelligence (CISAI), International Conference on

作者： Jinfang Zhang Li Zhang Guodou Huang Junxiong Huang School of Control and Computer Engineering North China Electric Power University Beijing China

ISBN: (纸本)9781665406932

Many practical systems are non-Gaussian, and their modeling has always been the core concern in the field of industrial control. Probability density function is a vital way to deal with the modeling of stochastic distributed systems. In this paper, a probability density function shape control method for nonlinear stochastic system response has been proposed. On the basis of establishing the mathematical model of the system based on the B-spline, a linear active disturbance rejection control method has been presented, and the specific implementation steps of the algorithm have been deduced. The simulation results show that the output probability density function can effectively track the target probability density function based on the proposed algorithm.

关键词： Robust control Target tracking Shape control Simulation Stochastic systems Stochastic processes Probability density function

来源：评论

学校读者我要写书评

暂无评论

Enhanced pH sensing with Ce-doped YTixOy sensing membrane in high-performance electrolyte–insulator–semiconductor devices

引用

Materials Chemistry and Physics 2024年 311卷

作者： Singh, Kanishk Tai, Li-Chia Her, Jim-Long Pan, Tung-Ming Department of Electronics Engineering Chang Gung University Taoyuan33302 Taiwan Department of Electrical and Computer Engineering National Yang-Ming Chiao Tung University Hsinchu30010 Taiwan Institute of Electrical and Control Engineering National Yang-Ming Chiao Tung University Hsinchu30010 Taiwan Division of Natural Science Center for General Education Chang Gung University Taoyuan33302 Taiwan Division of Urology Chang Gung Memorial Hospital Taoyuan33305 Taiwan

Electrolyte-insulator-semiconductor (EIS)-based sensors are a novel class of electronic chips designed for biochemical sensing that offer a direct electronic readout, making them part of a new generation of sensing technologies. To enhance the pH sensitivity, in this research we fabricated the CeYTixOy-based EIS sensors with different Ce concentrations (1 %, 5 %, and 10%) by the solution-processing method. The crystal orientation, surface topography, and chemical composition of the sensing film were examined by X-ray diffraction, atomic force microscopy, and X-ray photoelectron spectroscopy, respectively. The CeYTixOy-based EIS sensor treated with an optimal 5% Ce concentration displays a Super-Nernstian pH response of 66.59 mV/pH with an excellent linearity of 0.99. In the context of reliability, the device exhibited a smaller hysteresis voltage of 7 mV and a lower drift rate of 0.75 mV/h. This result may be attributed to the optimal Ce content in the CeYTixOy leads to the formation of redox couple Ce4+/Ce3+ resulting in less than one electron transferred per proton in the redox reaction. © 2023 Elsevier B.V.

关键词： Cerium compounds

来源：评论

学校读者我要写书评

暂无评论

Feedforward control in the Presence of Input Nonlinearities: With Application to a Wirebonder

引用

IFAC-PapersOnLine 2023年第2期56卷 1895-1900页

作者： Maurice Poot Jilles van Hulst Kai Wa Yan Dragan Kostić Jim Portegies Tom Oomen CST Dept. of Mechanical Engineering Eindhoven University of Technology Eindhoven The Netherlands Center of Competency ASMPT Beuningen The Netherlands CASA Dept. of Mathematics and Computer Science Eindhoven University of Technology Eindhoven The Netherlands Delft Center for Systems and Control Delft University of Technology Delft The Netherlands

The increasing demands on throughput and accuracy of semiconductor manufacturing equipment necessitates accurate feedforward motion control that includes compensation of input nonlinearities. The aim of this paper is to develop a data-driven feedforward approach consisting of a Wiener feedforward, i.e., linear parameterization with an output nonlinearity, to achieve high tracking accuracy and task flexibility for a class of Hammerstein systems. The developed approach exploits iterative learning control to learn a feedforward signal from data that minimizes the error and utilizes a control-relevant cost function to learn the parameters of a Wiener feedforward parameterization. Experimental validation on a wirebonder shows that the developed approach enables high tracking accuracy and task flexibility.

关键词： Iterative and repetitive learning control Identification and control methods Nonlinear system identification Data-driven control Learning for control

来源：评论

学校读者我要写书评

暂无评论

A Machine Learning-based Digital Twin for Electric Vehicle Battery Modeling

arXiv

引用

arXiv 2022年

作者： Alamin, Khaled Sidahmed Sidahmed Chen, Yukai Macii, Enrico Poncino, Massimo Vinco, Sara Department of Control and Computer Engineering Politecnico di Torino Turin Italy Interuniversity Department of Regional and Urban Studies and Planning Politecnico di Torino Turin Italy

The widespread adoption of EVs is limited by their reliance on batteries with presently low energy and power densities compared to liquid fuels and are subject to aging and performance deterioration over time. For this reason, monitoring the battery state of charge and state of health during the EV lifetime is a very relevant problem. This work proposes the structure of a battery digital twin designed to reflect battery dynamics at the run time accurately. To ensure a high degree of correctness concerning non-linear phenomena, the digital twin relies on data-driven models trained on traces of battery evolution over time: a state of health model, repeatedly executed to estimate the degradation of maximum battery capacity, and a state of charge model, retrained periodically to reflect the impact of aging. The proposed digital twin structure will be exemplified on a public dataset to motivate its adoption and prove its effectiveness, with a high degree of accuracy and inference and retraining times compatible with onboard execution. © 2022, CC BY.

关键词： Battery management systems

来源：评论

学校读者我要写书评

暂无评论

Research on Optimal Load Distribution of Power Plants Based on Chaos Genetic Algorithm

Research on Optimal Load Distribution of Power Plants Based ...

引用

Power and Electrical engineering (ACPEE), 5th Asia Conference on

作者： Hao Yang Yongguang Ma Sihan Chen Fuyu Qiao School of Control and Computer Engineering North China University of Electric Power Baoding China

According to the structural characteristics of chaotic motion, chaotic variables are introduced into the genetic algorithm optimization process, so that the values of the two are mapped to each other, and the group that adds chaotic disturbances is selected according to the fitness level, and the guidance of mutation operation is increased. Chaos is proposed Genetic algorithm. This improved algorithm is applied to the optimal distribution of plant-level load in power plants, and the coal consumption of thermal power plants is verified by simulation experiments. The results show that this algorithm can obtain better optimization results in the plant-level load optimization distribution problem, allowing the power plant to obtain better economy.

关键词： Economics Chaos Stability analysis Safety Thermal loading Optimization Power generation

来源：评论

学校读者我要写书评

暂无评论

System-aware dynamic partitioning for batch and streaming workloads 21

System-aware dynamic partitioning for batch and streaming wo...

引用

14th IEEE/ACM International Conference on Utility and Cloud Computing, UCC 2021

作者： Zvara, Zoltán Szabó, Péter G. N. Lóránt, Balázs Barnabás Benczúr, András A. Institute for Computer Science and Control Budapest Hungary University of Pécs Faculty of Engineering and Information Technology Pécs Hungary Eötvös University Budapest Doctoral School of Informatics Budapest Hungary

ISBN: (纸本)9781450385640

When processing data streams with highly skewed and nonstationary key distributions, we often observe overloaded partitions when the hash partitioning fails to balance data correctly. To avoid slow tasks that delay the completion of the whole stage of computation, it is necessary to apply adaptive, on-the-fly partitioning that continuously recomputes an optimal partitioner, given the observed key distribution. While such solutions exist for batch processing of static data sets and stateless stream processing, the task is difficult for long-running stateful streaming jobs where key distribution changes over time. Careful checkpointing and operator state migration is necessary to change the partitioning while the operation is running. Our key result is a lightweight on-the-fly Dynamic Repartitioning (DR) module for distributed data processing systems (DDPS), including Apache Spark and Flink, which improves the performance with negligible overhead. DR can adaptively repartition data during execution using our Key Isolator Partitioner (KIP). In our experiments with real workloads and power-law distributions, we reach a speedup of 1.5-6 for a variety of Spark and Flink jobs. © 2021 Owner/Author.

关键词： Batch data processing

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：