Multi-angle perception and convolutional neural network for service quality evaluation of cross-border e-commerce logistics enterprise.

The development of cross-border e-commerce logistics services has injected new vitality into the development of international trade, and therefore has become a new hot spot in theoretical research. In order to ensure the healthy development of cross-border e-commerce, it is urgent to build a set of scientific and effective evaluation mechanisms to scientifically evaluate the logistics service quality of cross-border e-commerce. Multi-angle perceptual convolutional neural network is a framework for service scene identification of cross-border e-commerce logistics enterprises based on deep convolutional neural network and multi-angle perceptual width learning.

Geographic information system-based multi-criteria decision-making analysis for investment assessment of wind-photovoltaic-shared energy storage power stations: a case study of Shanxi Province.

As the center of the development of power industry, wind-photovoltaic (PV)-shared energy storage project is the key tool for achieving energy transformation. This research seeks to construct a feasible model for investment appraisal of wind-PV-shared energy storage power stations by combining geographic information system (GIS) and multi-criteria decision-making (MCDM) method. Firstly, a comprehensive criteria system is established from the perspectives of orography, economy, resources, climate, and society, and the evaluation data is described using probabilistic linguistic term sets (PLTSs).

The value of frozen section diagnosis of tumor spread through air spaces in small-sized (≤ 2 cm) non-small cell lung cancer.

Background: The current accuracy of frozen section diagnosis of tumor spread through air spaces (STAS) in non-small cell lung cancer (NSCLC) is poor. However, the accuracy and prognostic value of STAS assessment on frozen sections in small-sized NSCLC (diameter ≤ 2 cm) is unknown.

Methods: Three hundred fifty-two patients with clinical stage I NSCLC (≤ 2 cm) were included, of which the paraffin sections and frozen sections were reviewed.

Design of Sports Event Evaluation and Classification Method Based on Deep Neural Network.

Large-scale sports events with high-level competition as the main content will have a great impact on the host city whether from the economic level or from the social level. With the improvement of human civilization, people realize that the holding of large-scale sports events not only has a positive impact on the economy and society but also brings some negative effects, such as waste of resources and environmental pollution, which have attracted the attention of the government and investors. Therefore, how to scientifically, comprehensively, and reasonably evaluate large-scale sports events, especially the accurate evaluation of their economic and social effects, has become the focus of attention.