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22nd International Middle East Power systems Conference, MEPCON 2021

作者： Bedawy, Ahmed Mahmoud, Karar Sasaki, Yutaka Zoka, Yoshifumi Yorino, Naoto Lehtonen, Matti South Valley University Faculty of Engineering Department of Electrical Engineering Qena Egypt Aswan University Facultty of Engineering Department of Electrical Engineering Aswan Egypt Graduate School of Advanced Science and Engineering Hiroshima University Higashi Hiroshima Japan Aalto University Department of Electrical Engineering and Automation Espoo Finland

ISBN: (纸本)9781665419987

Recently, regulating the voltage in active distribution systems has become a significant concern for network management. Furthermore, as renewable energy sources are intermittent, they cause a stressful operation for the conventional voltage regulation systems by requiring more control actions. This study presents a cooperative strategy for voltage regulation based on the coordination between the traditional voltage regulators (VRs) and the photovoltaic (PV) inverters' reactive power. The objective of the proposed strategy is to decrease the excessive operations of the VRs while minimizing the voltage violations, considering the advantage of the fast-reacting operation of the inverters. Specifically, multi-agents control architecture is introduced to manage the VRs and the reactive power capability of the PV as independent control agents. The simulations of the IEEE 34-bus test system with different PV generations profiles (clear and cloudy days) confirm the effectiveness of the proposed control approach. © 2021 IEEE.

关键词： Voltage regulators

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Arbitrarily structured quantum emission with a multifunctional metalens

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eLight 2023年第1期3卷 75-84页

作者： Chi Li Jaehyuck Jang Trevon Badloe Tieshan Yang Joohoon Kim Jaekyung Kim Minh Nguyen Stefan A.Maier Junsuk Rho Haoran Ren Igor Aharonovich School of Mathematical and Physical Sciences University of Technology SydneyUltimoNSW 2007Australia School of Physics and Astronomy Monash UniversityMelbourneVIC 3800Australia Department of Chemical Engineering Pohang University of Science and Technology(POSTECH)Pohang 37673Republic of Korea Department of Mechanical Engineering Pohang University of Science and Technology(POSTECH)Pohang 37673Republic of Korea Graduate School of Artificial Intelligence Pohang University of Science and Technology(POSTECH)Pohang 37673Republic of Korea Department of Physics Imperial College LondonLondon SW72AZUK POSCO-POSTECH-RIST Convergence Research Centre for Flat Optics and Metaphotonics Pohang 37673Republic of Korea National Institute of Nanomaterials Technology(NINT) Pohang 37673Republic of Korea ARC Centre of Excellence for Transformative Meta-Optical Systems University of Technology SydneyUltimoNSW 2007Australia

Structuring light emission from single-photon emitters(SPEs)in multiple degrees of freedom is of great importance for quantum information processing towards higher ***,traditional control of emission from quantum light sources relies on the use of multiple bulky optical elements or nanostructured resonators with limited functionalities,constraining the potential of multi-dimensional *** we introduce the use of an ultrathin polarisation-beam-splitting metalens for the arbitrary structuring of quantum emission at room *** to the complete and independent polarisation and phase control at the single meta-atom level,the designed metalens enables simultaneous mapping of quantum emission from ultra-bright defects in hexagonal boron nitride and imprinting of an arbitrary wavefront onto orthogonal polarisation states of the *** hybrid quantum metalens enables simultaneous manipulation of multiple degrees of freedom of a quantum light source,including directionality,polarisation,and orbital angular *** could unleash the full potential of solid-state SPEs for their use as high-dimensional quantum sources for advanced quantum photonic applications.

关键词： temperature quantum arbitrary

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Data-Driven Discovery of Stochastic Differential Equations

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engineering 2022年第10期17卷 244-252页

作者： Yasen Wang Huazhen Fang Junyang Jin Guijun Ma Xin He Xing Dai Zuogong Yue Cheng Cheng Hai-Tao Zhang Donglin Pu Dongrui Wu Ye Yuan Jorge Gonçalves Jürgen Kurths Han Ding School of Mechanical Science and Engineering Huazhong University of Science and TechnologyWuhan 430074China State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China Department of Mechanical Engineering University of KansasLawrenceKS 66045USA HUST-Wuxi Research Institute Wuxi 214174China Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China Department of Plant Sciences University of CambridgeCambridge CB23EAUK Luxembourg Centre for Systems Biomedicine University of LuxembourgBelvaux 4367Luxembourg Department of Physics Humboldt University of BerlinBerlin 12489Germany Department of Complexity Science Potsdam Institute for Climate Impact ResearchPotsdam 14473Germany

Stochastic differential equations(SDEs)are mathematical models that are widely used to describe complex processes or phenomena perturbed by random noise from different *** identification of SDEs governing a system is often a challenge because of the inherent strong stochasticity of data and the complexity of the system’s *** practical utility of existing parametric approaches for identifying SDEs is usually limited by insufficient data *** study presents a novel framework for identifying SDEs by leveraging the sparse Bayesian learning(SBL)technique to search for a parsimonious,yet physically necessary representation from the space of candidate basis *** importantly,we use the analytical tractability of SBL to develop an efficient way to formulate the linear regression problem for the discovery of SDEs that requires considerably less time-series *** effectiveness of the proposed framework is demonstrated using real data on stock and oil prices,bearing variation,and wind speed,as well as simulated data on well-known stochastic dynamical systems,including the generalized Wiener process and Langevin *** framework aims to assist specialists in extracting stochastic mathematical models from random phenomena in the natural sciences,economics,and engineering fields for analysis,prediction,and decision making.

关键词： Data-driven method System identification Sparse Bayesian learning Stochastic differential equations Random phenomena

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Secondary organic aerosol formation from straw burning using an oxidation flow reactor

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Journal of Environmental sciences 2022年第4期34卷 249-258页

作者： Hui Wang Song Guo Zhijun Wu Kai Qiao Rongzhi Tang Ying Yu Weizhao Xu Wenfei Zhu Liwu Zeng Xiaofeng Huang Lingyan He Mattias Hallquist State Key Joint Laboratory of Environmental Simulation and Pollution Control International Joint Laboratory for Regional Pollution ControlMinistry of Education(IJRC)College of Environmental Sciences and EngineeringPeking UniversityBeijing 100871China Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Nanjing University of Information Science&TechnologyNanjing 10044China Key Laboratory for Urban Habitat Environmental Science and Technology College of Environment and EnergyPeking University Shenzhen Graduate SchoolShenzhen 518055China Department of Chemistry and Molecular Biology Atmospheric ScienceUniversity of GothenburgSE-41296 GothenburgSweden

Herein,we use an oxidation flow reactor,Gothenburg:Potential Aerosol Mass(Go:PAM)reactor,to investigate the secondary organic aerosol(SOA)formation from wheat straw *** burning emissions are exposed to high concentrations of hydroxyl radicals(OH)to simulate processes equivalent to atmospheric oxidation of 0-2.55 *** volatile organic compounds(VOCs)were investigated,and particles were measured before and after the Go:PAM *** influence of water content(i.e.5%and 11%)in wheat straw was also *** burning stages,the flaming stage,and non-flaming stages,were *** particle emission factors(EFs)at a water content of 11%(~3.89 g/kg-fuel)are significantly higher than those at a water content of 5%(~2.26 g/kg-fuel)during the flaming ***,the water content showed no significant influence at the non-flaming *** of aromatics at a non-flaming stage(321.8±46.2 mg/kg-fuel)are larger than that at a flaming stage(130.9±37.1 mg/kg-fuel).The OA enhancement ratios increased with the increase in OH exposure at first and decreased with the additional increment of OH *** maximum OA enhancement ratio is~12 during the non-flaming stages,which is much higher than~1.7 during the flaming *** mass spectrum of the primary wheat burning organic aerosols closely resembles that of resolved biomass burning organic aerosols(BBOA)based on measurements in ambient *** results show that large gap(0%-90%)still remains to estimate biomass burning SOA if only the oxidation of VOCs were included.

关键词： Gothenburg:Potential Aerosol Mass(Go:PAM)reactor Wheat straw burning Flaming Non-flaming Secondary organic aerosol formation

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Computational modeling of multiscale collateral blood supply in a whole-brain-scale arterial network

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PLoS Computational Biology 2023年第9 September期19卷 e1011452-e1011452页

作者： Otani, Tomohiro Nishimura, Nozomi Yamashita, Hiroshi Ii, Satoshi Yamada, Shigeki Watanabe, Yoshiyuki Oshima, Marie Wada, Shigeo Graduate School of Engineering Science Osaka University Osaka Japan Graduate School of Integrated Sciences for Life Hiroshima University Hiroshima Japan Graduate School of Systems Design Tokyo Metropolitan University Tokyo Japan Department of Neurosurgery Nagoya City University Graduate School of Medical Science Aichi Japan Interfaculty Initiative in Information Studies The University of Tokyo Tokyo Japan Department of Radiology Shiga University of Medical Science Shiga Japan

The cerebral arterial network covering the brain cortex has multiscale anastomosis structures with sparse intermediate anastomoses (O[102] μm in diameter) and dense pial networks (O[101] μm in diameter). Recent studies indicate that collateral blood supply by cerebral arterial anastomoses has an essential role in the prognosis of acute ischemic stroke caused by large vessel occlusion. However, the physiological importance of these multiscale morphological properties—and especially of intermediate anastomoses—is poorly understood because of innate structural complexities. In this study, a computational model of multiscale anastomoses in whole-brain-scale cerebral arterial networks was developed and used to evaluate collateral blood supply by anastomoses during middle cerebral artery occlusion. Morphologically validated cerebral arterial networks were constructed by combining medical imaging data and mathematical modeling. Sparse intermediate anastomoses were assigned between adjacent main arterial branches;the pial arterial network was modeled as a dense network structure. Blood flow distributions in the arterial network during middle cerebral artery occlusion simulations were computed. Collateral blood supply by intermediate anastomoses increased sharply with increasing numbers of anastomoses and provided one-order-higher flow recoveries to the occluded region (15%–30%) compared with simulations using a pial network only, even with a small number of intermediate anastomoses (≤10). These findings demonstrate the importance of sparse intermediate anastomoses, which are generally considered redundant structures in cerebral infarction, and provide insights into the physiological significance of the multiscale properties of arterial anastomoses. Copyright: © 2023 Otani et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the ori

关键词： Medical imaging

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Recognition of Multiple Rectangular Stickers for Construction Machines 9

Recognition of Multiple Rectangular Stickers for Constructio...

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9th International Symposium on Computing and Networking Workshops, CANDARW 2021

作者： Nakagawa, Yuki Ohno, Shuichi Yamamoto, Shohei Hiroshima University Graduate School of Advanced Science And Engineering Hiroshima Japan Osaka City University Department of Electrical And Information Engineering Osaka Japan Education And Research Center Hiroshima Japan

ISBN: (纸本)9781665428354

In construction industry, before shipping manufactured products, it is necessary to attach multiple stickers which are specified by each country. Since required stickers depend on the country, there are so many patterns for the stickers. Usually, we visually check whether the specified stickers are attached or not, which is inefficient and subject to human errors. In order to solve these problems, we may resort to automatically recognize the stickers. Recently, a deep learning model called SSD has achieved high recognition rates in object detection. However, since the recognition accuracy depends on the image data to be trained, it is not that easy to create training data for the stickers. The stickers on construction machines are all rectangles. Utilizing this property of stickers, we develop recognition systems. Our proposed methods achieve higher recognition rates than the conventional SSD. © 2021 IEEE.

关键词： Construction industry

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Diffusion with a broad class of stochastic diffusion coefficients

arXiv

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arXiv 2023年

作者： Uchida, Go Washizu, Hitoshi Miyoshi, Hiromi Department of Mechanical Systems Engineering Tokyo Metropolitan University Tokyo1920397 Japan Graduate School of Information Science University of Hyogo Hyogo6500047 Japan

In many physical or biological systems, diffusion can be described by Brownian motions with stochastic diffusion coefficients (DCs). In the present study, we investigate properties of the diffusion with a broad class of stochastic DCs with a novel approach. We show that for a finite time, the propagator is non-Gaussian and heavy-tailed. This means that when the mean square displacements are the same, for a finite time, some of the diffusing particles with stochastic DCs diffuse farther than the particles with deterministic DCs or exhibiting a fractional Brownian motion. We also show that when a stochastic DC is ergodic, the propagator converges to a Gaussian distribution in the long time limit. The speed of convergence is determined by the autocovariance function of the DC. Copyright © 2023, The Authors. All rights reserved.

关键词： Diffusion

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Research of the Information Security Audit System in Organizations

Research of the Information Security Audit System in Organiz...

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2023 IEEE International Conference on Smart Information systems and Technologies, SIST 2023

作者： Ziro, Aasso Toibayeva, Shara Gnatyuk, Sergiy Imanbayev, Azamat Iavich, Maksim Zhaybergenova, Zhanshuak School of It and Engineering KazNU Named after Al-Farabi Kazakh-British Technical University Faculty of It Almaty Kazakhstan Named after G. Daukeev Department of Automation and Control Almaty Kazakhstan National Aviation University Faculty of Copmuter Science and Technologies Kyiv Ukraine School of Technology Caucasus University Tbilisi Georgia Astana It University Department of Intelegent Systems and Cybersecurity Astana Kazakhstan

ISBN: (纸本)9798350335040

The field of information security is constantly evolving, and new threats appear every day. To ensure that organizations remain protected from these threats, it is important to have a reliable information security audit system. The purpose of this study is to study the current state of information security audit systems in organizations and identify the best practices for the implementation and maintenance of these systems. In the course of the study, various methods and methods of conducting an information security audit will be analyzed, security analysis tools and information security tools. © 2023 IEEE.

关键词： Security of data

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Deep Reinforcement Learning Based Traffic Signal control: A Comparative Analysis

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Procedia Computer science 2023年 220卷 275-282页

作者： Chunliang Wu Inhi Kim Zhenliang Ma Cho Chun Shik Graduate School of Mobility Korea Advanced Institute of Science and Technology Daejeon 34051 South Korea Department of Civil and Architectural Engineering KTH Royal Institute of Technology Stockholm 11428 Sweden

More recently, the advancement of deep learning techniques enables reinforcement learning (RL) to handle high-dimensional decision-making problems. It brings increasing attention in transport areas. Some work has applied them to solve the intractable traffic signal control (TSC) problem and achieved promising results. However, very few research comprehensively investigates the impacts of key design elements, including state definitions, reward functions and deep reinforcement learning (DRL) methods, on TSC performance. To fill this research gap, this paper first selects commonly used design elements from existing literature. Then, we compare their learning stability and control performance at an isolated intersection under different scenarios via simulation experiments. The experimental results show that the quantitative state (e.g., the number of vehicles on lanes) and image-like state (e.g., vehicle position and speed) have no significant impact on the performance under different traffic demands. However, the impact of various reward functions on performance is vivid, especially under high traffic demand. Also, high-resolution vehicular network data may not be possible to improve control performance versus ordinary camera data. In addition, the value-based DRL algorithms outperform the policy-based algorithm and traditional TSC control methods. The findings of this research would provide insights and guidance for transport engineers to design an efficient DRL-based TSC system in a real traffic environment.

关键词： Traffic signal control (TSC) Reinforcement learning (RL) Deep learning Simulation

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Adaptive Stiffness control of Series Elastic Actuator Manipulators Based on Dynamic System

Adaptive Stiffness Control of Series Elastic Actuator Manipu...

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IEEE International Conference on Automation science and engineering (CASE)

作者： Kunlin Guo Chao Zeng Weiyong Si Ning Wang Chenguang Yang Key Laboratory of Autonomous Systems and Networked Control School of Automation Science and Engineering South China University of Technology Guangzhou China Department of Computer Science University of Liverpool Liverpool UK School of Computer Science and Electronic Engineering University of Essex Colchester Bristol Robotics Laboratory University of the West of England Bristol UK

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

In traditional control methods, Series Elastic Actuator (SEA) joint manipulators are limited by their hardware and can only perform simple tasks with low stiffness. To address this issue, we propose a stiffness adjustment control strategy for SEA manipulators based on Dynamic systems (DS) with good generalization performance. By enhancing the generalization capability of DS in complex tasks and combining posture control, the SEA manipulators can autonomously adjust control gains and postures according to task requirements to achieve higher stiffness at the end-effector. Experimental results involving the activation of air switches with different stiffness levels and installation angles have demonstrated the effectiveness of our proposed method. The results indicate that compared to traditional methods of adjusting the control gain and retraining DS for similar tasks, our approach exhibits superior generalization performance while maintaining end-effector stiffness during interactions.

关键词： Actuators Computer aided software engineering Automation Adaptive systems control systems End effectors Hardware Dynamical systems Manipulator dynamics

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