Focusing on regional financial services, this paper analyzes the variables affecting non-financial businesses getting loans through the region economic services function, and then proposes countermeasures to improve it. The DPC algorithm is applied to the financial analysis in this paper because of its fast speed and high accuracy. The AD-DPC approach is suggested in this study as a solution to the issue that the computation of local density relies on the choice of the truncation length parameter dc and the clustering sites must be manually chosen. This strategy lessens the subjectivity and volatility that the fictitious label dc brings. For the DPC algorithm by using a one-step assignment strategy, i.e., assigning the labels of clustering centers to all non-clustering centroids at one time, such a strategy is poorly fault-tolerant, this paper proposes the DAS-DPC algorithm on the basis of AD-DPC. Through experiments, ADAS-DPC is optimal for ARI metrics in the dataset. Among them, the ARI indexes of ADAS-DPC algorithm are 0.832, 0.895, 0.768 and 0.757 in the datasets Iris, Wine, Seed and Sonar. It shows that the ADAS-DPC algorithm can not only handle the datasets with complex shapes, large density differences between clusters and tightly connected clusters, but also improve the clustering performance of the algorithm for high-dimensional data.
This paper first describes the applications of digital signal processors in software radio, speech compression coding, modems and GPS systems, demonstrating the versatility of digital signal processors in practical communication systems. Next, digital signal processing oriented electronic communication practices are presented in the system design section to design high performance communication systems for specific communication needs and environmental conditions. The digital signal processing platform used in the platform architecture is optimized for signal processing and data transmission. The BER is 0.008% when the signal-to-noise ratio is -10 dB. The time complexity of digital signal processing is 7.2 ms when the number of communication nodes is 1000. It shows that digital signal processing oriented electronic communication engineering is important for improving the performance, reliability and efficiency of communication systems.
In this paper, strategies in image preprocessing, hardware composition and detection methods are considered to improve computerized machine vision detection accuracy. First, image preprocessing and image enhancement are performed to improve the quality of the input image. Second, the hardware composition of the computer vision online inspection system is optimized by focusing on the light source selection and the performance of the image acquisition card in spatial applications. Combined with spatial application calculations, methods such as frequency domain method and Canny operator are used in order to improve the accuracy of machine vision detection. Finally, in the same test environment, the machine vision detection requires only 400MB and the detection accuracy ranges from 85.13% to 99.42%. With these comprehensive strategies, this paper provides a comprehensive and effective approach for computerized machine vision detection in spatial applications to improve detection accuracy and meet demanding application scenarios.
As an expression of the informal economy, the night market is not only a place that could attract locals to buy goods but also a place where tourists can experience the local characteristics. While the night market brought economic vitality to the city's economy, it also brought some issues. A comprehensive literature review of night markets revealed that existing studies paid less attention to outdoor night markets' spatial operations and waste management. Grounded in the connection between sustainability and night markets, the present study reflected on existing research findings by adopting different periods of fieldwork to conduct a case study of the night market in Jalan 17/1A, Selangor, Malaysia. The study focused on three aspects of night markets: spatial operations, waste, and waste recycling. It found that night market operations brought localized regional economic benefits while causing more severe pollution issues, significantly affecting the region's environmental health and sustainable development. The findings revealed that local government regulation of night market businesses in Malaysia is weak (the issuance of business licenses is informed of the operational guidelines), and there is also no relevant monitoring and penalties by the local government to intervene in the misbehavior of night market consumers. Based on the results of the field survey and combined with the concept of sustainable development, the present study recommended suggestions for the future spatial operation and waste management of night markets. Innovative and novel perspectives of the study combined qualitative observations and data analysis to comprehensively examine how spatial considerations and waste management strategies intersect in the unique context of night markets—aiming to fill the gaps in the sustainability of night market operations and to protect the ecology of the surrounding territorial environment, contributing to the discourse on sustainable development.
In recent years, PEST analysis and its application in decision-making has become a hot topic, and this paper proposes a new model of PEST analysis based on neutral cognitive map static analysis.The proposed framework consists of five activities, identifying PEST factors and sub-factors, modeling the interrelationships among PEST factors, calculating centrality measures, categorizing the factors, and ranking the factors.The results show that the impact factor of the US breeding patent on the development of agricultural science and technology has reached the level of interrelationship, and the uncertainty is included in the analysis. Using this model to analyze the impact of U.S.-China breeding patents on the development of agricultural science and technology, we ranked the factors according to their interrelationships and incorporated uncertainty into the analysis. The results showed that the impact factor of U.S. breeding patents on the development of agricultural science and technology reached 0.70, and the index of the Gross Agricultural Product (GAP) caused by patents was greater than 100. The quantitative analysis of the impact of Sino-US cooperation in agricultural science and technology using PEST analysis has scientifically and accurately grasped the quantitative law of Sino-US agricultural science and technology cooperation.
