J Li

How to identify the key nodes effectively in urban traffic networks to achieve the equitable resource allocation face to the complex traffic network? This issue needs to be solved in current traffic management. This study considered the urban traffic network topology and network traffic status, put forward an improved model based on the economics of the input-output method by introducing a virtual node to the selected network set up with the flow of urban traffic network, sensor nodes by Leontief inverse matrix calculation coefficient to determine node importance, according to the node importance to deliberate attack traffic network to analyze its robustness, to test the accuracy and practicability of the method. The results show that this improved method adopted to measure the importance of traffic nodes from the global scope has the advantages of fast calculation and simple process and provides a more reliable basis for rational allocation of transport resources.

Since the bilateral commerce between the USA and China changes greatly and Chinese government continues to reform and delegate power in the economic field, it is of importance to study the Uniform Commercial Code of the USA. The study specifically studies the features of modal verbs in the UCC through the comparison with the United States Code and Frown. With the help of Antconc, the distribution of modal verbs, the modal value of the three sets of corpora are examined and analyzed based on the theory of Halliday’s systemic-functional grammar. The results show that there are significant differences between the three sets of corpora and the three main features of modal verbs in the UCC are: the high frequency use of may, the relatively lower frequency use of legal modal verb shall, and the much higher frequency of must and may not. The seemingly contrary usages within the UCC are discussed and explained with the background of the legislation and the legal thoughts of the major legislator in a sociosemiotic approach. With both the quantitative and qualitative analysis combining the examples, the study hopes to shed light on the related legal translation and further enhance the understanding of the modal verbs in the UCC as well as legal discourse in a more general context.

Pellet is widely used in blast furnace ironmaking. Pellet quality affects the effect of ironmaking, the existing control system of grating-rotary kiln mainly adopts manual control mode, and the quality of pellet production largely depends on the experience, fatigue, and sense of responsibility of the site operators. The use of the Internet of things technology in the integration and improvement of enterprise information level, to achieve fine, intelligent production management, at the same time, is conducive to promoting steel enterprises to reduce costs and increase efficiency, energy conservation and emission reduction, transformation and upgrading, and taking a new road to industrialization. According to the working principle and technological characteristics of the grate-rotary kiln at all stages, this paper designs the management system of firing pellets based on convolutional neural network and IoT technology, so as to realize automatic recognition of image data obtained by the perceptual layer and make an intelligent analysis of it. The system can classify the working conditions of the current equipment, so as to judge whether the production process parameters of the grate-rotary kiln are up to the standard, thus achieving the goal of controlling the quality of the finished pellet.

Music is an abstract art form that uses sound as its means of expression. It has deeply affected our lives. This paper proposes a method for extracting segment features from nonmultiple cluster music files. We divide each piece of music into multiple segments and extract the features of each segment. The specific process includes nonmultiple cluster music file note extraction, main melody extraction, segment division, and segment feature extraction. The segment feature is extracted from a segment of a piece of music, contains the main melody and accompaniment information of the segment, and can reflect the sequence relationship of the notes. This paper proposes a performance style conversion network based on recurrent neural network and convolutional neural network. The bidirectional recurrent neural network based on Gated Recurrent Unit is used to extract different styles of note feature vector sequences, and the extracted note feature vector sequence is used to predict the intensity of a specific style, and the intensity changes of different styles of nonmultiple cluster music are better learned. Through the comparison, the multiclassification strategy of “one-to-the-rest” is selected, and the fuzzy recurrent neural network is applied to the shortcomings of the unrecognizable area. Finally, according to the feature extraction method and the principle of the classifier algorithm studied in this paper, a music style classification system is implemented in the MATLAB environment. Experimental simulation shows that this system can effectively classify music performance styles.