The four-railway-network integration is the policy guidance of multi-type rail transit for intensive resource usage, transportation efficiency enhancement, and regional society and economy development. The synergia im...
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By introducing an optic-null medium into the finite embedded transformation,a reflectionless spatial beam bender is designed,which can steer the output beam by a fixed pre-designed angleβfor an arbitrary incident ***...
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By introducing an optic-null medium into the finite embedded transformation,a reflectionless spatial beam bender is designed,which can steer the output beam by a fixed pre-designed angleβfor an arbitrary incident *** bending angleβof the beam bender is determined by the geometrical angle of the device,which can be changed by simply choosing different geometrical *** various bending angles,the designed spatial beam bender can be realized by the same materials(i.e.,an optic-null medium),which is a homogenous anisotropic *** simulations verify the reflectionless bending effect and rotated imaging ability of the proposed beam bender.A reduction model of the optic-null medium is studied,which can also be used for a reflectionless spatial beam bender with a pre-designed bending angle.
As a highly developed region, Guangdong province has substantial industrial emissions. Its subtropical monsoon climate, characterized by abundant hydrothermal conditions, contributes to a substantial biomass potential...
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Membrane fouling poses a significant challenge to the sustainable development of membrane bioreactor(MBR)technologies for wastewater *** accurate prediction of the membrane filtration process is of great importance fo...
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Membrane fouling poses a significant challenge to the sustainable development of membrane bioreactor(MBR)technologies for wastewater *** accurate prediction of the membrane filtration process is of great importance for identifying and controlling *** learning methods address the limitations of traditional statistical approaches,such as low accuracy,poor generalization ability,and slow convergence,particularly in predicting complex filtration and fouling processes within the realm of big *** article provides an in-depth exposition of machine learning *** study then reviews advances in MBRs that utilize machine learning methods,including artificial neural networks(ANN),support vector machines(SVM),decision trees,and ensemble *** on current literature,this study summarizes and compares the model input and output characteristics(including foulant characteristics,solution environments,filtration conditions,operating conditions,and time factors),as well as the selection of models and optimization *** modeling procedures of SVM,random forest(RF),back propagation neural network(BPNN),long short-term memory(LSTM),and genetic algorithm-back propagation(GA-BP)methods are elucidated through a tutorial *** simulation results demonstrated that all five methods yielded accurate predictions with R2>***,the existing challenges in the implementation of machine learning models in MBRs were *** is notable that integration of deep learning,automated machine learning(AutoML)and explainable artificial intelligence(XAI)may facilitate the deployment of models in practical engineering *** insights presented here are expected to facilitate the establishment of an intelligent control framework for MBR processes in future endeavors.
Although metallic nanostructures have been attracting tremendous research interest in nanoscience and nanotechnologies, it is known that environmental attacks, such as surface oxidation, can easily initiate cracking o...
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Wide-range and high-efficiency DC-DC converters are in high demand for various applications, such as distributed systems, electric vehicles, and DC buildings. Resonant switched capacitor converters (ReSCC) can achieve...
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Waves seriously impact port construction, worldwide route planning, military activities, and wave power generation. To improve the accuracy of significant wave height prediction, we proposed a novel prediction method,...
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A wheel-legged robot is equipped with Stewart parallel mechanism, constituting a reconfigurable robot which can change its wheelbase, robot body height, and achieve omnidirectional steering. The legged character effec...
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ISBN:
(纸本)9798400712647
A wheel-legged robot is equipped with Stewart parallel mechanism, constituting a reconfigurable robot which can change its wheelbase, robot body height, and achieve omnidirectional steering. The legged character effectively improves the terrain adaptability, which concerns our planning concentration. We introduced an optimization-based whole-body trajectory planning algorithm to navigate robot in rugged terrain. The planner combines terrain data and stability, allowing lower-level motion generator and controller to operate more efficiently. The Model Predictive control(MPC)-based method updates the footholds and CoG trajectories, which builds upon the support polygon constraints on optimization. The simulations of methodology working in several structure-obstacle scene demonstrated and compared the availability of approach.
Cloud-based railway interlocking system is a novel solution for interlocking systems with the development of cloud computing. The load balancing problem caused by imbalanced resources in computing platforms is an esse...
Cloud-based railway interlocking system is a novel solution for interlocking systems with the development of cloud computing. The load balancing problem caused by imbalanced resources in computing platforms is an essential problem in realizing cloud-based railway interlocking system. Conventional load balancing algorithms focus on makespan, throughput and costs. However, a load balancing algorithm for a cloud-based railway interlocking system should focus on optimizing resource utilization and execution time. To this end, we propose a hybrid meta-heurisite algorithm called Improved Genetic Annealing Algorithm (IGAA). The proposed algorithm can guarantee global optimization ability by using the Metropolis criterion and can converge rapidly due to the parallel searching characteristic of the Genetic Algorithm. Finally, the feasibility and effectiveness of the proposed algorithm are verified by experiments.
Clock synchronization is one of the essential problems for the cloud-based railway interlocking system, which is related to task processing and information synchronization. To improve the convergence rate and performa...
Clock synchronization is one of the essential problems for the cloud-based railway interlocking system, which is related to task processing and information synchronization. To improve the convergence rate and performance of a classical distributed clock synchronization algorithm, this paper proposes an exponential smoothing predictor-based distributed clock synchronization algorithm for the cloud-based railway interlocking system. Firstly, a classical distributed clock synchronization algorithm is conducted to get a convergent clock for distributed computing nodes. Then, to improve the convergence rate and performance, we introduce an exponential smoothing predictor to the classical method. Moreover, the convergence condition and convergence rate of our proposed method were analyzed theoretically. Finally, the simulation results show that the proposed algorithm has a better convergence performance than a classical method and can meet the requirements of a cloud-based railway interlocking system.
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