Frame Construction and Task Analysis of Smart Energy in the Construction of Smart City

Smart energy is the foundation and important component of smart cities, and it is the source of energy that guarantees the efficient and reliable operation of each subsystem of the city. Based on the practical experience in the exploration of the construction of smart energy at home and abroad, and the goal of achieving “three transformations and one center”, the basic principles of the frame construction as well as display construction and physical construction of smart energy have been proposed. Four main tasks of the construction of smart energy have been discussed: infrastructure, energy supply, energy consumption, and management services.

Research on Multi-Scale Feature Fusion Network Algorithm Based on Brain Tumor Medical Image Classification

Gliomas have the highest mortality rate of all brain tumors.Correctly classifying the glioma risk period can help doctors make reasonable treatment plans and improve patients’survival rates.This paper proposes a hierarchical multi-scale attention feature fusion medical image classification network(HMAC-Net),which effectively combines global features and local features.The network framework consists of three parallel layers:The global feature extraction layer,the local feature extraction layer,and the multi-scale feature fusion layer.A linear sparse attention mechanism is designed in the global feature extraction layer to reduce information redundancy.In the local feature extraction layer,a bilateral local attention mechanism is introduced to improve the extraction of relevant information between adjacent slices.In the multi-scale feature fusion layer,a channel fusion block combining convolutional attention mechanism and residual inverse multi-layer perceptron is proposed to prevent gradient disappearance and network degradation and improve feature representation capability.The double-branch iterative multi-scale classification block is used to improve the classification performance.On the brain glioma risk grading dataset,the results of the ablation experiment and comparison experiment show that the proposed HMAC-Net has the best performance in both qualitative analysis of heat maps and quantitative analysis of evaluation indicators.On the dataset of skin cancer classification,the generalization experiment results show that the proposed HMAC-Net has a good generalization effect.

Global Existence,Uniqueness and Pathwise Property of Solutions to a Stochastic Rssler-Lorentz System

The authors integrate two well-known systems, the Rssler and Lorentz systems,to introduce a new chaotic system, called the Lorentz-Rssler system. Then, taking into account the effect of environmental noise, the authors incorporate white noise in both Rssler and Lorentz systems to have a corresponding stochastic system. By deriving the uniform a priori estimates for an approximate system and then taking them to the limit,the authors prove the global existence, uniqueness and the pathwise property of solutions to the Lorentz-Rssler system. Moreover, the authors carried out a number of numerical experiments, and the numerical results demonstrate their theoretic analysis and show some new qualitative properties of solutions which reveal that the Lorentz-Ro¨ssler system could be used to design more complex and more secure nonlinear hop-frequence time series.