Research and Application of a Multi-Field Co-Simulation Data Extraction Method Based on Adaptive Infinitesimal Element

Regarding the spatial profile extraction method of a multi-field co-simulation dataset,different extraction directions,locations,and numbers of profileswill greatly affect the representativeness and integrity of data.In this study,a multi-field co-simulation data extractionmethod based on adaptive infinitesimal elements is proposed.Themultifield co-simulation dataset based on related infinitesimal elements is constructed,and the candidate directions of data profile extraction undergo dimension reduction by principal component analysis to determine the direction of data extraction.Based on the fireworks algorithm,the data profile with optimal representativeness is searched adaptively in different data extraction intervals to realize the adaptive calculation of data extraction micro-step length.The multi-field co-simulation data extraction process based on adaptive microelement is established and applied to the data extraction process of the multi-field co-simulation dataset of the sintering furnace.Compared with traditional data extraction methods for multi-field co-simulation,the approximate model constructed by the data extracted from the proposed method has higher construction efficiency.Meanwhile,the relative maximum absolute error,root mean square error,and coefficient of determination of the approximationmodel are better than those of the approximation model constructed by the data extracted from traditional methods,indicating higher accuracy,it is verified that the proposed method demonstrates sound adaptability and extraction efficiency.

Scheme Based on Multi-Level Patch Attention and Lesion Localization for Diabetic Retinopathy Grading

Early screening of diabetes retinopathy(DR)plays an important role in preventing irreversible blindness.Existing research has failed to fully explore effective DR lesion information in fundus maps.Besides,traditional attention schemes have not considered the impact of lesion type differences on grading,resulting in unreasonable extraction of important lesion features.Therefore,this paper proposes a DR diagnosis scheme that integrates a multi-level patch attention generator(MPAG)and a lesion localization module(LLM).Firstly,MPAGis used to predict patches of different sizes and generate a weighted attention map based on the prediction score and the types of lesions contained in the patches,fully considering the impact of lesion type differences on grading,solving the problem that the attention maps of lesions cannot be further refined and then adapted to the final DR diagnosis task.Secondly,the LLM generates a global attention map based on localization.Finally,the weighted attention map and global attention map are weighted with the fundus map to fully explore effective DR lesion information and increase the attention of the classification network to lesion details.This paper demonstrates the effectiveness of the proposed method through extensive experiments on the public DDR dataset,obtaining an accuracy of 0.8064.

Deep neural network based on multi-level wavelet and attention for structured illumination microscopy

Structured illumination microscopy(SIM)is a popular and powerful super-resolution(SR)technique in biomedical research.However,the conventional reconstruction algorithm for SIM heavily relies on the accurate prior knowledge of illumination patterns and signal-to-noise ratio(SNR)of raw images.To obtain high-quality SR images,several raw images need to be captured under high fluorescence level,which further restricts SIM’s temporal resolution and its applications.Deep learning(DL)is a data-driven technology that has been used to expand the limits of optical microscopy.In this study,we propose a deep neural network based on multi-level wavelet and attention mechanism(MWAM)for SIM.Our results show that the MWAM network can extract high-frequency information contained in SIM raw images and accurately integrate it into the output image,resulting in superior SR images compared to those generated using wide-field images as input data.We also demonstrate that the number of SIM raw images can be reduced to three,with one image in each illumination orientation,to achieve the optimal tradeoff between temporal and spatial resolution.Furthermore,our MWAM network exhibits superior reconstruction ability on low-SNR images compared to conventional SIM algorithms.We have also analyzed the adaptability of this network on other biological samples and successfully applied the pretrained model to other SIM systems.

Co-Simulation模式软硬件协同仿真体系结构及实现

介绍和对比了HDL Co-Simulation、Vector、Transaction三种主要的软硬件协同仿真模式的执行流程及性能,并对其中的Co-Simulation模式软硬件协同仿真方法进行了体系结构的设计和功能部件的划分,描述了各部分组件的主要功能,并通过软、硬件试验平台对其进行了建模和编程实现,测试了其仿真性能。通过实验表明,该体系结构能够适用于任何Co-Simulation以及Vector模式的软硬件协同仿真实验,并可在保留基奉框架的情况下,通过部分功能的扩充,满足Transaction模式软硬件协同仿真的需求。

Co-simulation of a quadruped robot's mechanical and hydraulic systems based on ADAMS and AMESim

In order to observe the change and fluctuation in flow and pressure of a hydraulic quadruped robot＇s hydraulic system when the robot walks on trot gait,a co-simulation method based on ADAMS and AMESim is proposed. Firstly,the change rule in each swing angle of the hydraulic quadruped robot＇s four legs is analyzed and converted to the displacement change of the hydraulic cylinder by calculating their geometric relationship.Secondly,the robot＇s dynamic model is built in ADAMS and its hydraulic and control system models are built in AMESim. The displacement change of the hydraulic cylinder in the hydraulic system is used as the driving function of the dynamics model in ADAMS,and the driving force of the dynamics model is used as the loads of the hydraulic system in AMESim. By introducing the PID closed-loop control in the control system,the co-simulation between hydraulic system and mechanical system is implemented. Finally,the curve of hydraulic cylinders＇ loads,flow and pressure are analyzed and the results show that they fluctuate highly in accordance with the real situation. The study provides data support for the development of a hydraulic quadruped robot＇s physical prototype.

Explicit–Implicit Co-Simulation Techniques for Dynamic Responses of a Passenger Car on Arbitrary Road Surfaces

To study the durability of a passenger car, this work investigates numerical simulation techniques. The investigations are based on an explicit implicit approach in which substructure techniques are used to reduce the simulation time, allowing full vehicle dynamic analyses to be performed on a timescale that is dif cult or impossible with the conventional nite element model (FEM). The model used here includes all necessary nonlinearities in order to maintain accuracy. All key components of the car structure are modeled with deformable materials. Tire road interactions are modeled in the explicit package with contact-impact interfaces with arbitrary frictional and geometric properties. Key parameters of the responses of the car driven on six different kinds of test road surfaces are examined and compared with experimental values. It can be concluded that the explicit implicit co-simulation techniques used here are ef cient and accurate enough for engineering purposes. This paper also discusses the limitations of the proposed method and outlines possible improvements for future work.

Real-time controller hardware-in-the-loop co-simulation testbed for cooperative control strategy for cyber-physical power system

Various distributed cooperative control schemes have been widely utilized for cyber-physical power system(CPPS),which only require local communications among geographic neighbors to fulfill certain goals.However,the process of evaluating the performance of an algorithm for a CPPS can be affected by the physical target characteristics and real communication conditions.To address this potential problem,a testbed with controller hardware-in-the-loop(CHIL)is proposed in this paper.On the basis of a power grid simulation conducted using the real-time simulator RT-LAB developed by the company OPAL-RT,along with a communication network simulation developed with OPNET,multiple distributed controllers were developed with hardware devices to directly collect the real-time operating data of the power system model in RT-LAB and provide local control.Furthermore,the communication between neighboring controllers was realized using the cyber system modelin OPNET with an Ethernet interface.The hardware controllers produced a real-world control behavior instead of a digital simulation,and precisely simulated the dynamic features of a CPPS with high speed.A classic cooperative control case for active power output was studied to explain the integrated simulation process and validate the effectiveness of the co-simulation testbed.

Co-Simulation Research of the Mechanical-Hydraulic-Control Coupling System of ITER Tractor

The virtual prototyping models of the mechanical, hydraulic and control system of the ITER tractor were built with CATIA, ADAMS and MATLAB/Simulink respectively according to its heavy load and high precision characteristics, and the data transfer between the different models was accomplished by the integration interface between different software. Consequently the virtual experimental platform for the multi-disciplinary co-simulation was established. A co-simulation study of the mechanical-hydraulic-control coupling system of the ITER tractor was carried out. The synchronization servo control of parallel hydraulic cylinders was implemented, and the tracking control of the preconcerted trajectory of the hydraulic cylinders was realized on the established experimental platform. This paper presents the optimization design and technology rebuilding for the complicated coupling system with its theoretic foundation and co-simulation virtual experimental platform.

Co-simulation platform for single-shaft parallel HEVs based on Cruise+Matlab/Simulink

We reversely analyzed the energy management strategy （EMS） for a single-shaft parallel hybrid electric vehicle （HEV）, and build a forward co-simulation platform based on Cruise and Matlab. The vehicle dynamics model is built with Cruise, and control model is set up with Matlab/Simulink environment. The data between the two models are transferred by the Matlab API interface in Cruise. After mechanical and signal connections are completed, we establish the computing tasks and take the simulations of vehicle＇ s power performance, economy, and emission performance. The simulation results match the actual measurement results, which show that the co-simulation platform is correct and feasible. The platform can be used not only for a basic simulation platform to optimize further EMS, but also for the development of actual control system.

Hardware-Software Co-Simulation for SOC Functional Verification

A hardware-software co-simulation method for system on chip (SOC) design is discussed. It is based on an instruction set simulator (ISS) and an event-driven hardware simulator, and a bus interface model that is described in C language provides the interface between the two. The bus interface model and the ISS are linked into a singleton program--the software simulator, which communicate with the hardware simulator through Windows sockets. The implementation of the bus interface model and the synchronization between hardware and software simulator are discussed in detail. Co-simulation control of the hardware simulator is also discussed.

Co-simulation and consumption analysis ofwheel loader on negative loading condition

In order to analyze the energy consumption of wheel loader during working process, a three-dimensional（3D） model of wheel loader is established by Pro/E software, and it is imported into the software SimulationX tobuild the kinetic model of the whole wheel loader. Meanwhile, the simulation model of hydraulic system is builtby the same software. By integrating the simulation model of hydraulic system with the kinetic model, the co-sim-ulation model of wheel loader could be achieved. The precision of co-simulation model of the working device isverified through the comparison between simulation results and test results. The testing results show that, undernegative loading condition, the energy loss in multi-way valve accounts for about 52%. The important energy lossin loader＇s working hydraulic system using constant displacement pump is the large throttling loss of multi-wayvalves. This study provides a reference for designing of a more energy-efficient hydaulic system of wheel loader.

Research on Co-simulation with ADAMS and MATLAB for Servo Tracking System Mounted with a Small Arm

Research on a servo tracking system mounted with a small arm for robot fighting platform based on multi-body system dynamics and intelligent control theory is presented.A multi-body dynamic model which can accurately express dynamic performances of the system is built in ADAMS.In addition,an intelligent PID control model is built with MATLAB/Simulink,and the two models are integrated and co-simulated by the interface of ADAMS/Controls.Simulation experiments indicate that co-simulation technique used for design of the servo tracking system mounted with a small arm can effectively improve its design efficiency,and can also provide theoretical bases for the motion control and performance improvement of the servo tracking system mounted with a small arm.

Theoretical investigation on self-recovery regulation method for diesel engine misalignment through co-simulation

Misalignment is one of the most common faults for the diesel engine.In order to eliminate the misalignment fault of the diesel engine in the process of operation,a targeting self-recovery regulation system is constructed by using a movable base and displacement sensors.Misalignment is monitored and detected in real time,the value of misalignment is calculated rapidly and accurately,andintelligent decision is made.Then,the base is moved reversely with a definite target to drive the shaft to translate or rotate,so that the shafts can be recovered to alignment online.A co-simulation model for the self-recovery system is established which consists of a dynamic model of the crankshaft system and control model.The self-recovery regulation process of misalignment is simulated.The simulation results show that the system can accurately calculate the misalignment values,with an error of less than 5%,and can automatically eliminate the misalignment fault of the diesel engine online.The research results provide theoretical support for the self-recovery regulation of misalignment fault,and due to the universality of structure and principle,the self-recovery system is not only suitable for diesel engine,but also for other rotating machineries.

Co-simulation and Solving of Clapper Type Relay Dynamic Characteristics Based on Multi-software

Based on multi-commercial finite element analysis (FEA) software co-simulation calculating method, the electromagnetic system model was built for solving static and dynamic characteristics of a clap-type rely. Using the Fortran programming language, the solving of differential equation and the calculating of electromagnetic torque interpolation was realized, therefore the MEM coupling system static/dynamic characteristics of the relay was obtained. The validity and accuracy of this method has been confirmed by results of experiments.The conclusions which obtained are valuable in optimizing the clap-type rely production.

FPGA based hardware platform for trapped-ion-based multi-level quantum systems

We report a design and implementation of a field-programmable-gate-arrays(FPGA)based hardware platform,which is used to realize control and signal readout of trapped-ion-based multi-level quantum systems.This platform integrates a four-channel 2.8 Gsps@14 bits arbitrary waveform generator,a 16-channel 1 Gsps@14 bits direct-digital-synthesisbased radio-frequency generator,a 16-channel 8 ns resolution pulse generator,a 10-channel 16 bits digital-to-analogconverter module,and a 2-channel proportion integration differentiation controller.The hardware platform can be applied in the trapped-ion-based multi-level quantum systems,enabling quantum control of multi-level quantum system and highdimensional quantum simulation.The platform is scalable and more channels for control and signal readout can be implemented by utilizing more parallel duplications of the hardware.The hardware platform also has a bright future to be applied in scaled trapped-ion-based quantum systems.

Deep reinforcement learning based multi-level dynamic reconfiguration for urban distribution network:a cloud-edge collaboration architecture

With the construction of the power Internet of Things(IoT),communication between smart devices in urban distribution networks has been gradually moving towards high speed,high compatibility,and low latency,which provides reliable support for reconfiguration optimization in urban distribution networks.Thus,this study proposed a deep reinforcement learning based multi-level dynamic reconfiguration method for urban distribution networks in a cloud-edge collaboration architecture to obtain a real-time optimal multi-level dynamic reconfiguration solution.First,the multi-level dynamic reconfiguration method was discussed,which included feeder-,transformer-,and substation-levels.Subsequently,the multi-agent system was combined with the cloud-edge collaboration architecture to build a deep reinforcement learning model for multi-level dynamic reconfiguration in an urban distribution network.The cloud-edge collaboration architecture can effectively support the multi-agent system to conduct“centralized training and decentralized execution”operation modes and improve the learning efficiency of the model.Thereafter,for a multi-agent system,this study adopted a combination of offline and online learning to endow the model with the ability to realize automatic optimization and updation of the strategy.In the offline learning phase,a Q-learning-based multi-agent conservative Q-learning(MACQL)algorithm was proposed to stabilize the learning results and reduce the risk of the next online learning phase.In the online learning phase,a multi-agent deep deterministic policy gradient(MADDPG)algorithm based on policy gradients was proposed to explore the action space and update the experience pool.Finally,the effectiveness of the proposed method was verified through a simulation analysis of a real-world 445-node system.

Neighborhood Effects and Political Trust: A Multi-level Analysis of Chinese Rural-to-Urban Migrants’ Trust in County Government

Massive rural-to-urban migration in China is consequential for political trust: rural-to-urban migrants have been found to hold lower levels of trust in local government than their rural peers who choose to stay in the countryside (mean 4.92 and 6.34 out of 10, respectively, p < 0.001). This article explores why migrants have a certain level of political trust in their county-level government. Using data of rural-to-urban migrants from the China Family Panel Survey, this study performs a hierarchical linear modeling (HLM) to unpack the multi-level explanatory factors of rural-to-urban migrants’ political trust. Findings show that the individual-level socio-economic characteristics and perceptions of government performance (Level-1), the neighborhood-level characteristics-the physical and social status and environment of neighborhoods (Level-2), and the objective macroeconomic performance of county-level government (Level-3), work together to explain migrants’ trust levels. These results suggest that considering the effects of neighborhood-level factors on rural-to-urban migrants’ political trust merits policy and public management attention in rapidly urbanizing countries.

Pixelated non-volatile programmable photonic integrated circuits with 20-level intermediate states

Multi-level programmable photonic integrated circuits(PICs)and optical metasurfaces have gained widespread attention in many fields,such as neuromorphic photonics,opticalcommunications,and quantum information.In this paper,we propose pixelated programmable Si_(3)N_(4)PICs with record-high 20-level intermediate states at 785 nm wavelength.Such flexibility in phase or amplitude modulation is achieved by a programmable Sb_(2)S_(3)matrix,the footprint of whose elements can be as small as 1.2μm,limited only by the optical diffraction limit of anin-house developed pulsed laser writing system.We believe our work lays the foundation for laser-writing ultra-high-level(20 levels and even more)programmable photonic systems and metasurfaces based on phase change materials,which could catalyze diverse applications such as programmable neuromorphic photonics,biosensing,optical computing,photonic quantum computing,and reconfigurable metasurfaces.

BC-BLPM:A Multi-Level Security Access Control Model Based on Blockchain Technology

Traditional multi-level security(MLS)systems have the defect of centralizing authorized facilities,which is difficult to meet the security requirements of modern distributed peer-to-peer network architecture.Blockchain is widely used in the field of access control with its decentralization,traceability and non-defective modification.Combining the blockchain technology and the Bell-LaPadula model,we propose a new access control model,named BCBLPM,for MLS environment.The“multi-chain”blockchain architecture is used for dividing resources into isolated access domains,providing a fine-grained data protection mechanism.The access control policies are implemented by smart contracts deployed in each access domain,so that the side chains of different access domains storage access records from outside and maintain the integrity of the records.Finally,we implement the BC-BLPM prototype system using the Hyperledger Fabric.The experimental and analytical results show that the model can adapt well to the needs of multi-level security environment,and it has the feasibility of application in actual scenarios.

An effective multi-level algorithm based on ant colony optimization for graph bipartitioning

Partitioning is a fundamental problem with applications to many areas including data mining, parellel processing and Very-large-scale integration （VLSI） design. An effective multi-level algorithm for bisecting graph is proposed. During its coarsening phase, an improved matching approach based on the global information of the graph core is developed with its guidance function. During the refinement phase, the vertex gain is exploited as ant＇s heuristic information and a positive feedback method based on pheromone trails is used to find the global approximate bipartitioning. It is implemented with American National Standards Institute （ANSI） C and compared to MeTiS. The experimental evaluation shows that it performs well and produces encouraging solutions on 18 different graphs benchmarks.