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Maritime Power has gradually increased as a national strategy. In this process, gross marine products continue to grow, and the marine industry has become the most fundamental and critical object. The spatial layout and industrial organization of maritime enterprises are fundamental related tasks. Domestic research can be divided into two main categories, based on the data used. One is to use economic and social statistical data, which have a large spatial scope but large granularity and cannot reflect the details of the industrial layout. The other is to use point-of-interest data, which are often not fully mined owing to the heavy workload of data processing. Therefore, there is little relevant content on departmental and urban comparisons in the existing research. Four representative cities-Dalian, Qingdao, Ningbo, and Xiamen-were selected as the research areas. According to the Industrial Classification for Ocean Industries and Their Related Activities, the research objects were identified as the marine core layer, marine support layer, and marine peripheral layer industries and further refined into eight subcategories. This study is based on the information of maritime enterprises registered for business registration, and uses Python to crawl geographic coordinates to improve the spatial information of enterprises. An innovative task is to identify the industry categories of enterprises. This task was performed using fastText, Convolutional Neural Networks, and Recurrent Neural Network. Thus, a spatial enterprise information database, including multiple marine industry departments, was established. Kernel density analysis, standard deviational ellipse analysis, buffer analysis, and other methods were used. Finally, by comparing the visualization results of the marine industrial spatial layout in the four cities, we delved into the marine industrial spatial differentiation patterns. In the experiment, machine learning models, such as artificial neural networks, exhibited high accuracy and recall when completing human recognition tasks, and these methods were effective. Empirical research on the spatial layout and industrial organization of maritime enterprises revealed the following: 1)From the perspective of spatial pattern, the overall pattern is a balanced pattern of "large dispersion and small agglomeration." By comparing the distribution and organization of different types of marine industries, we found that there is industry agglomeration in the location selection of enterprises, resulting in industry agglomeration characteristics. The land sea relationship is reflected in the high-density single peak or "coastal zone-city center" Multimodal distribution pattern. 2) From the perspective of spatial organization mode, industrial clusters have multilevel hierarchical characteristics corresponding to population size and administrative levels. In addition to single core structures, multi core structures generally exhibit a "primary-secondary dual core" or "primary core-multiple radial" pattern, with spatial connections between core intervals forming a multi node axis or network structure. 3) From the perspective of spatial matching relationships, the elliptical area is positively related to the urban area, the direction of the long axis is close to the coastal direction, and the industrial distribution has a clear matching relationship with the urban center, ports, and other transportation hubs, bay terrain, coastline, and other spatial elements.

DC line protection is the key to the development of flexible DC grids, and fault identification within 3 ms is required. Existing scholars have proposed a digital twinning based flexible DC line protection method with high speed and sensitivity advantages. However, its reliability is easily affected by transformer measurements, which may lead to protection misoperation. The requirements of DC control protection equipment can be hardly meted by existing bad data detection methods with insufficient accuracy and rapidity. Therefore, in order to improve the reliability of this protection method, a self-correcting method of bad data based on the moving average method is proposed in this paper. The predicted value of the measured data is obtained by using the moving average method according to the time sequence characteristics of the steady change of the measured data, and the bad data is detected and corrected by comparing the predicted error and the actual error, without iterative calculation and pre-trained model. The results of a simulation test using the four-terminal flexible DC grid show that the proposed method has higher accuracy and rapidity with good error correction performance than any existing method does, and it can be adapted to the protection method and improve the anti-interference capability as well as the reliability of protection in an effective manner.

This article, through the method of questionnaire survey and based on the technical analysis of SPSS, investigates the current application of commercial AI in labor education during the transition phase from kindergarten to elementary school. On the basis of analyzing the reasons, corresponding solutions are proposed.

This study presents an innovative approach utilising molecular dynamics simulations to elucidate the polymerisation and neck formation mechanisms of phenolic resin during laser powder bed fusion (L-PBF). By developing system and dual-particle models and employing infrared thermal imaging, we established a heat source model for phenolic resin under varying parameters. Our molecular dynamics simulations, using the ReaxFF reactive force field, indicate that high-power lasers significantly enhance cross-linking, achieving a peak polymerisation degree of 78.9% at 30W and 35W power levels. Conversely, increased scanning speed slows product degradation, reducing the polymerisation degree. The interplay of laser power and scanning speed influences polymerisation, with total input energy and heating rate impacting polymerisation and molecular size. Additionally, we investigated neck formation, revealing that small vortices evolve into larger ones during sintering, promoting neck formation. Optical microscopy confirmed diverse neck shapes under different conditions. Quantitative data showed that at a scanning speed of 1000 mm/s, the polymerisation degree reached 93%, with only 2 molecules remaining post-simulation. At 30W power, the largest individual molecule observed was C849H703O117. This research offers crucial insights for selective laser sintering processes, emphasising the importance of high energy input and optimal heating rates for well-formed necks. [ABSTRACT FROM AUTHOR]