Comparing Methods for Measuring Walkability

Walkability analyses have gained increased attention for economic, environmental and health reasons, but the methods for assessing walkability have yet to be broadly evaluated. In this paper, five methods for calculating walkability scores are described: in-radius, circle buffers, road network node buffers, road network edge buffers and a fully integrated network approach. Unweighted and various weighted versions are analyzed to capture levels of preference for walking longer distances. The methods are evaluated via an application to train stations in central Tokyo in terms of accuracy, similarity and algorithm performance. The fully integrated network method produces the most accurate results in the shortest amount of processing time, but requires a large upfront investment of time and resources. The circle buffer method runs a bit slower, but does not require any network information and when properly weighted yields walkability scores very similar to the integrated network approach.

The Establishment and Evaluation Method of Prefabricated Building Construction Quality Evaluation Index System Taking into Account Multimedia Sensor Network Nodes

Through in-depth analysis of the characteristics of the quality evaluation stage of prefabricated buildings, the quality evaluation of prefabricated buildings can be divided into three stages: before, during, and after construction. According to the detailed design content of the prefabricated building construction stage, we construct the prefabricated construction quality evaluation index system, use the multimedia sensor network node method to obtain the weight of each evaluation index, comprehensively evaluate the construction quality of the prefabricated building, and finally show through the case analysis results that the multimedia sensor network node method can be of high practical value in the process of prefabricated building construction quality evaluation, and it has improved the domestic prefabricated building construction quality evaluation index system and evaluation quality and has certain reference value.

Physiological Index Monitoring of Wearable Sports Training Based on a Wireless Sensor Network

According to the development needs of wireless sensor networks, this paper uses the combination of embedded system and wireless sensor network technology to design a network node platform. This platform is equipped with a sports training sensor module to measure the physiological indicators of the ward in real time. The network node sends the collected physiological parameters to a remote monitoring center in real time. First, according to the generation mechanism of the physiological index signal and the characteristics of the physiological index signal, the wireless sensor network analysis and processing method are used to denoise the physiological index signal, and the wireless sensor network package is used to extract the characteristics of the physiological index, indicating different types of respiration. The energy characteristics of the sound physiological index signals are different, which verifies the feasibility of the independent component analysis method for separating the physiological index and the physiological index signal of the heart sound. Secondly, the hardware system of physiological index signal acquisition is designed, and the selection principle of the hardware unit is introduced. At the same time, the system structure of the monitor is designed, and then, the wireless sensor network sensor node is researched, the hardware of the wearable monitor system is designed, and the hardware architecture and working mode based on the single-chip MSP430F149 are given. Finally, the wireless hardware platform includes the following main modules: sensor part, preprocessing circuit module, microprocessing module based on MSP430 low power consumption, wireless transceiver module based on RF chip CC2420, and power supply unit used to provide energy.

Work Addiction and Work Engagement: a Network Approach to Cross-Cultural Data

This study aimed to investigate direct relationships of work addiction symptoms with dimensions of work engagement. We used three samples in which work addiction was measured with the Bergen Work Addiction Scale and work engagement was measured with the Utrecht Work Engagement Scale. One sample comprised responses from working Norwegians (n1 = 776), and two samples comprised responses from working Poles (n2 = 719; n3 = 715). We jointly estimated three networks using the fused graphic lasso method. Additionally, we estimated the stability of each network, node centrality, and node predictability and quantitatively compared all networks. The results showed that absorption and mood modification could constitute a bridge between work addiction and work engagement. It suggests that further investigation of properties of absorption and mood modification might be crucial for answering the question of how engaged workers become addicted to work.

Research on Classroom Online Teaching Model of “Learning” Wisdom Music on Wireless Network under the Background of Artificial Intelligence

This article uses a multimodal smart music online teaching method combined with artificial intelligence to address the problem of smart music online teaching and to compensate for the shortcomings of the single modal classification method that only uses audio features for smart music online teaching. The selection of music intelligence models and classification models, as well as the analysis and processing of music characteristics, is the subjects of this article. It mainly studies how to use lyrics and how to combine audio and lyrics to intelligently classify music and teach multimodal and monomodal smart music online. In the online teaching of smart music based on lyrics, on the basis of the traditional wireless network node feature selection method, three parameters of frequency, concentration, and dispersion are introduced to adjust the statistical value of wireless network nodes, and an improved wireless network is proposed. After feature selection, the TFIDF method is used to calculate the weights, and then artificial intelligence is used to perform secondary dimensionality reduction on the lyrics. Experimental data shows that in the process of intelligently classifying lyrics, the accuracy of the traditional wireless network node feature selection method is 58.20%, and the accuracy of the improved wireless network node feature selection method is 67.21%, combined with artificial intelligence and improved wireless, the accuracy of the network node feature selection method is 69.68%. It can be seen that the third method has higher accuracy and lower dimensionality. In the online teaching of multimodal smart music based on audio and lyrics, this article improves the traditional fusion method for the problem of multimodal fusion and compares various fusion methods through experiments. The experimental results show that the improved classification effect of the fusion method is the best, reaching 84.43%, which verifies the feasibility and effectiveness of the method.

Research on Task-Service Network Node Matching Method Based on Multi-Objective Optimization Model in Dynamic Hyper-Network Environment

In order to reduce the cost of manufacturing and service for the Cloud 3D printing (C3DP) manufacturing grid, to solve the problem of resources optimization deployment for no-need preference under circumstance of cloud manufacturing, consider the interests of enterprises which need Cloud 3D printing resources and cloud platform operators, together with QoS and flexibility of both sides in the process of Cloud 3D printing resources configuration service, a task-service network node matching method based on Multi-Objective optimization model in dynamic hyper-network environment is built for resource allocation. This model represents interests of the above-mentioned two parties. In addition, the model examples are solved by modifying Mathematical algorithm of Node Matching and Evolutionary Solutions. Results prove that the model and the algorithm are feasible, effective and stable.