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IEEE Annual International computer Software and Applications Conference (COMPSAC)

作者： Chunyan Hou Jinsong Wang Chen Chen Kai Shi School of Computer Science and Engineering Tianjin University of Technology Tianjin China College of Computer and Control Engineering Nankai University Tianjin China

ISBN: (纸本)9781538626672

A key problem in any automatic software verification system is the inference of loop invariants. When analyzing program structures involving disjunctive semantics, abstract interpretation has the problem of precision loss. Thus, some techniques were proposed to decompose such loop structures into a semantically equivalent sequence of loops with conjunctive semantics whose invariants can be generated by abstract interpretation directly. However, these works assumed that the iteration processes of nested branches are separate without consideration of non-monotone loop structures where those interweave with each other. In order to solve this problem, we present a novel static analysis technique for non-monotone loops. It analyzes loop convergence condition and traces the transfer between nested branches of finite non-monotone loops. With analytical results, it generates the loop invariants with precise semantics. Meanwhile, it takes advantage of cyclical nature of result expressions to restrict search space and accelerate computation procedure. Finally, experimental results show the potential of our approach, which is also helpful for reasoning about certain program security properties.

关键词： Convergence Semantics Software Static analysis Acceleration Security Standards

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A method of registering virtual objects in monocular augmented reality system 13th

A method of registering virtual objects in monocular augment...

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13th Conference on Image and Graphics Technologies and Applications, IGTA 2018

作者： Wu, Zeye Wang, Pengrui Che, Wujun Institute of Automation Chinese Academy of Sciences Beijing100190 China School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing100049 China AICFVE of Beijing Film Academy Beijing100088 China

ISBN: (纸本)9789811317019

A flexible novel method of registering virtual objects in monocular AR system is presented in this paper. Monocular AR systems use SLAM-related techniques to obtain the camera pose, of which the translation component is on a random scale. We add a scale calibration process to acquire the scale factor from the SLAM map to the real world and provide a closed-form solution of the transformation between two coordinate systems with different scales. We also describe the framework of an AR system based on our method with implementation. The proposed system can easily initialize virtual objects’ position, orientation and size by using a known reference in the real scene and the reference is no longer needed in the later process. Our method is flexible, simple to set up and easy to control. The results show the proposed method can apply to real-time interactive AR applications. © Springer Nature Singapore Pte Ltd., 2018.

关键词： Augmented reality

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Dynamic Prediction of NOx Emissions Based on Factor Analysis and NARX Neural Network

Dynamic Prediction of NOx Emissions Based on Factor Analysis...

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Chinese Automation Congress (CAC)

作者： Chuanyu Tan Yan Bai Xinli Li School of Control and Computer Engineering North China Electric Power University Beijing China

NOx emissions of thermal power plants are closely related to the environment. It is very important to research on the prediction of NOx emissions. However, most of the current models are static and did not take into account the impact of the previous data. Boiler combustion is a process with large delay, and NOx generation also goes through a certain process, so we cannot just focus on the data at the current moment. In this paper, the dynamic prediction model of NOx emissions combining factor analysis and NARX dynamic neural network is proposed. The common factors that play the important roles in NOx formation are extracted based on the factor analysis method. It can eliminate the collinearity of the original data and reduce the complexity of modeling. The factor score matrix of common factors is used as the input of the NARX neural network, and a dynamic model is established, taking full account of the influence of various operating parameters and output parameters on the NOx emission at the previous moment. The simulation results show the effective and feasible of the model in NOx emissions prediction.

关键词： Biological neural networks Predictive models Boilers Combustion Data models Analytical models

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Network Parameter Generation for One-Shot Object Detection

Network Parameter Generation for One-Shot Object Detection

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IEEE International Conference on Unmanned Systems (ICUS)

作者： Kang Wang Jiajia Zhao Yang Wang Shuigeng Zhou Shanghai Key Lab of Intelligent Information Processing and School of Computer Science Fudan University Shanghai China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-Mechanical Engineer Institute Beijing China School of Information Engineering Nanchang University China

ISBN: (纸本)9781728137933

Recent object detection models have achieved satisfactory performance by deep learning with large-scale annotated datasets. However, these models often perform poorly when the training examples are not sufficient enough, especially for one-shot object detection where there is only one training example of each target class. In this paper, we propose a network parameter generation framework for effective one-shot object detection. By leveraging the semantic relationship between the source-domain and the target-domain (new classes), our framework can generate network parameters for the new classes directly. Furthermore, we develop two implementation schemes for this framework: weighting-based parameter generation and regression-based parameter generation. These two schemes use different information to construct the relationship and transfer knowledge from the source-domain to the target-domain. Experiments on the PASCAL-OSCD benchmark show that our methods can significantly boost the performance of one-shot object detection.

关键词： Object detection Detectors Head Training Feature extraction Task analysis Training data

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Condensate Throttling Based Coordinated System Optimization with Improved Simplex Method for an 1000-MW USC Power Unit

Condensate Throttling Based Coordinated System Optimization ...

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Chinese Automation Congress (CAC)

作者： Liangyu Ma Qianqian Li Fan Li Peiyao Zhang School of Control and Computer Engineering North China Electric Power University Baoding China

In order to absorb more new energy power sources, regional load dispatch center puts up very high requirement for the operation flexibility, load fast-following and deep peak load regulation ability of an ultra-supercritical (USC) power unit. Therefore, it is very significant to adopt advanced control strategies to optimize the Coordinated control System (CCS). In this work, the load prediction neural network model considering `condensate throttling' and the main steam pressure prediction model are developed by taking a 1000MW ultra-supercritical power unit as the object investigated. Based on the established models, a classic optimization theory-improved simplex method is selected as the CCS optimization algorithm. An intelligent coordination optimization scheme with condensate throttling is designed, and the real-time optimization program is developed with MATLAB software. Detailed simulation tests are carried out in the full-scope simulator of the 1000MW power unit. Simulation results indicate that the proposed scheme can effectively improve the coordinated control quality with faster load response, less main steam pressure fluctuation during dynamic load-changing process.

关键词： Load modeling Predictive models Valves Optimization Turbines Data models Reflection

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The Numerical Simulation and Experimental Research on Combustion Process in 660MW Boiler

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IOP Conference Series: Earth and Environmental Science 2020年第1期526卷

作者： Lei Yu Hui Tian Zhen Chang School of Control and Computer Engineering North China Electric Power University Beijing 102206 China Patent Examination Cooperation Sichuan Center of the Patent Office Chengdu 610000 China

In order to solve the problems of thermal insulation and ash prevention of the furnace combustion layer temperature detection devices installed on the boiler furnace, FLUENT software is used to numerically simulate the actual combustion process in the furnace of 660 MW power plant boiler, and the combustion status of each layer in the furnace is analyzed and studied. And then, according to the results of data simulation the thermal insulation and ash prevention technology implementation of the furnace combustion temperature detection devices is guided. The installation operation test results show that the furnace combustion temperature detection devices work within the range of instrument allowed −20°C~85°C temperature, which can obtain the direct, rapid, real-time furnace combustion temperature data that provides a valuable source of data for further optimization control of boiler combustion process.

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Hierarchical Attention Networks for Image Classification of Remote Sensing Images Based on Visual Q&A Methods

Hierarchical Attention Networks for Image Classification of ...

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Chinese Automation Congress (CAC)

作者： Haochen Li Tian Wang Mengyi Zhang Aichun Zhu Guangcun Shan Hichem Snoussi School of Automation Science and Electrical Engineering Beihang University Beijing China College of Electrical Engineering and Control Science Nanjing Tech University Nanjing China School of Computer Science and Technology Nanjing Tech University Nanjing China School of Instrumentation Science and Opto-electronic Engineering Beihang University Beijing China Institue Charles Delaunay-LM2S FRE CNRS 2019 University of Technology of Troyes Troyes France

This paper provides a mixed attention network for remote sensing image classification whose idea comes from VQA methods. In this way, it could deal with more complex requests beyond just identifying what is in the picture. The HAN (Hierarchial Attention Network) consists of an attention model to detect details on one hand and a self-attention model to detect global information on the other hand. Through attention heat maps we could see division of work is really effective and the HAN has a great performance on NWPU-RESISC45 data set. Furthermore, we may add some other subnetworks to reinforce this ability in the future.

关键词： Feature extraction Remote sensing Airplanes Task analysis Visualization Airports Graphics processing units

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Short-term Wind Speed Forecasting Model Based on Spiking Neural Network

Short-term Wind Speed Forecasting Model Based on Spiking Neu...

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International Conference on Advanced Mechatronic Systems (ICAMechS)

作者： Fengyang Han Runmin Li Dianwei Qian School of Control and Computer Engineering North China Electric Power University Beijing China

Short-term wind speed forecasting plays an important role in the daily power system operation. Therefore, this paper presents a novel model based on spiking neural network (SNN) used spike response model (SRM). Further, to achieve both smaller training errors and higher precision forecasting, the basic SpikeProp learning algorithm is improved by adaptively adjusting the learning rate and adding momentum items. Then, this paper selects the actual sampling data from a wind farm to verify the effectiveness and advantages of the proposed model.

关键词： Neurons Wind speed Biological neural networks Forecasting Training Encoding Delays

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Quantum repeaters: From quantum networks to the quantum internet

arXiv

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arXiv 2022年

作者： Azuma, Koji Economou, Sophia E. Elkouss, David Hilaire, Paul Jiang, Liang Lo, Hoi-Kwong Tzitrin, Ilan NTT Basic Research Laboratories NTT Corporation 3-1 Morinosato Wakamiya Kanagawa Atsugi243-0198 Japan NTT Research Center for Theoretical Quantum Physics NTT Corporation 3-1 Morinosato-Wakamiya Kanagawa Atsugi243-0198 Japan Department of Physics Virginia Tech BlacksburgVA24061 United States QuTech Delft University of Technology Lorentzweg 1 Delft2628 CJ Netherlands Networked Quantum Devices Unit Okinawa Institute of Science and Technology Graduate University Okinawa Japan Quandela SAS 10 Boulevard Thomas Gobert Palaiseau91120 France Pritzker School of Molecular Engineering The University of Chicago ChicagoIL60637 United States Quantum Bridge Technologies Inc. 100 College Street TorontoONM5G 1L5 Canada Department of Physics University of Hong Kong Pokfulam Hong Kong Center for Quantum Information and Quantum Control Department of Physics Department of Electrical & Computer Engineering University of Toronto TorontoM5S 3G4 Canada Department of Physics University of Toronto Toronto Canada

A quantum internet is the holy grail of quantum information processing, enabling the deployment of a broad range of quantum technologies and protocols on a global scale. However, numerous challenges exist before the quantum internet can become a reality. Perhaps the most crucial of these is the realization of a quantum repeater, an essential component in the long-distance transmission of quantum information. As the analog of a classical repeater, extender, or booster, the quantum repeater works to overcome loss and noise in the quantum channels comprising a quantum network. Here, we review the conceptual frameworks and architectures for quantum repeaters, as well as the experimental progress towards their realization. We also discuss the various near-term proposals to overcome the limits to the communication rates set by point-to-point quantum communication. Finally, we overview how quantum repeaters fit within the broader challenge of designing and implementing a quantum internet. Copyright © 2022, The Authors. All rights reserved.

关键词： Quantum optics

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Modeling and Simulation of Indoor Environment Parameters Based on Least Squares 29

Modeling and Simulation of Indoor Environment Parameters Bas...

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第29届中国控制与决策会议

作者： ZENG Deliang JIAN Yifan DENG Zhiguang YANG Yang North China Electric Power University School of Control and Computer Engineering

ISBN: (纸本)9781509046584

Indoor building environment for energy saving and human health has important significance and the main criterion for evaluating its quality is environmental *** experimental scheme for obtaining the mathematical model of the main parameters is designed by analyzing the parameters that affect the environmental *** scheme establishes a discrete bilinear model with parameters and control variables,and uses the the least squares method to obtain the model parameters based on the experimental *** simulation results show that the experimental scheme of this paper has strong universality and adaptability,and the model with the deviation of the real system is small,which can be used as the model basis for optimizing the control of the indoor building environment.

关键词： indoor building environment environmental comfort discrete bilinear model least squares Optimization control

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