Construction Method of Rail Transit Oriented Metropolitan Area under the Integration of Four Networks

In the process of metropolitan area integration,the current rail transit development is not enough to support the rapid expansion of the economy and population of the metropolitan area.It is necessary to attach importance to the important role of rail transit as a support system,promote the integrated development of the metropolitan area,and create a metropolitan area on the track.Through the problems in rail transit development,the development concept of “four networks integration” of rail transit is put forward.From multiple aspects of planning,construction and operation,reasonable promotion strategies are proposed,which could provide feasible suggestions for promoting the construction of metropolitan area on the track.

Smart Home Networking: Lessons from Combining Wireless and Powerline Networking

Integrating the power grid technology with renewable power generation technologies, Demand Response (DR) programs enabled by the Advanced Metering Infrastructure (AMI) were introduced into the power grid in the interest of both utilities and residents. They help to achieve load balance and increase the grid reliability by encouraging residents to reduce their power usage during peak load periods in return for incentives. To automate this process, appliances, in-house sensors, and the AMI controller need to be networked together. In this paper, we compare mainstream network technologies applicable to home appliance control and propose a solution combining Power Line Communication (PLC) with wireless communication in smart homes for the purpose of energy saving. We extended NS-2, a popular network simulator, to model such combined network scenarios. Using a number of different routing strategies, we then model and evaluate the network performance of DR programs in smart homes in such a combined network.

A Review on the Mullins Effect in Tough Elastomers and Gels

Tough elastomers and gels have garnered broad research interest due to their wide-ranging potential applications.However,during the loading and unloading cycles,a clear stress softening behavior can be observed in many material systems,which is also named as the Mullins effect.In this work,we aim to provide a complete review of the Mullins effect in soft yet tough materials,specifically focusing on nanocomposite gels,double-network hydrogels,and multi-network elastomers.We first revisit the experimental observations for these soft materials.We then discuss the recent developments of constitutive models,emphasizing novel developments in the damage mechanisms or network representations.Some phenomenological models will also be briefly introduced.Particular attention is then placed on the anisotropic and multiaxial modeling aspects.It is demonstrated that most of the existing models fail to accurately predict the multiaxial data,posing a significant challenge for developing future anisotropic models tailored for tough gels and elastomers.

Automatic grape leaf diseases identification via UnitedModel based on multiple convolutional neural networks

Grape diseases are main factors causing serious grapes reduction.So it is urgent to develop an automatic identification method for grape leaf diseases.Deep learning techniques have recently achieved impressive successes in various computer vision problems,which inspires us to apply them to grape diseases identification task.In this paper,a united convolutional neural networks(CNNs)architecture based on an integrated method is proposed.The proposed CNNs architecture,i.e.,UnitedModel is designed to distinguish leaves with common grape diseases i.e.,black rot,esca and isariopsis leaf spot from healthy leaves.The combination of multiple CNNs enables the proposed UnitedModel to extract complementary discriminative features.Thus the representative ability of United-Model has been enhanced.The UnitedModel has been evaluated on the hold-out PlantVillage dataset and has been compared with several state-of-the-art CNN models.The experimental results have shown that UnitedModel achieves the best performance on various evaluation metrics.The UnitedModel achieves an average validation accuracy of 99.17%and a test accuracy of 98.57%,which can serve as a decision support tool to help farmers identify grape diseases.