Rajeev Kumar

To study the development trend of embedded platforms in home appliances Internet of Things, an application of embedded Linux in the design of IoT gateway is designed. ARM microprocessor S3C2410, EM310 radio frequency module, and Ethernet DM9000A module are used to realize the home network information-processing platform. The platform utilizes existing network facilities, RF modules, and network interface modules to realize the interconnection of the home perception network through wireless or wired links. For experimental analysis, Ping the central server from the IoT node B is set to twice: The first time ttl = 255 time = 1.9 ms, the second time: ttl = 255 time = 2.4 ms. After application verification, the system has the characteristics of low cost, small size, low power consumption, and vital ease of use. It can not only integrate the home Internet and the IoT gateway but also directly run application-layer communication protocols such as HTTP/mqtt between IoT nodes and Internet terminals. The design supports multi-hop communication and significantly increases the deployment range of IoT nodes without signal relay equipment, hence reducing the cost of IoT networking and the complexity of the network architecture.

Over the years, the urban heat vulnerability has evolved as a pressing global concern for researchers and policymakers alike. Numerous studies have aimed at mitigating the adverse effects of urban heat vulnerability on public health and safety. However, the critical task of selecting the most fitting indicator for urban heat islands in public spaces is not emphasized in the existing studies, considering the diverse indices available. Beyond identification, studies that delve into the prioritization of these indices and the determination of optimal variables along with their respective weights are scanty. The present study attempts to address these gaps in urban heat vulnerability research through the lens of natural solutions. The study employs a fuzzy analytical hierarchy approach to ascertain the weights of selected criteria, providing a nuanced understanding of the multifaceted factors influencing their applicability. Real-time impact estimation using the fuzzy technique for order of preference by similarity to ideal solutions enhances the practicality of the findings. The results reveal a set of pivotal characteristics crucial for constructing a robust heat vulnerability index, facilitating the prioritization of selected criteria. The implementation of this hybrid methodology culminates in a streamlined, precise, and practical tool for evaluating heat vulnerability in hot urban public spaces. These findings contribute valuable insights to the academic discourse and offer a tangible resource for policymakers and practitioners. The proactive approach provides a roadmap for addressing impending challenges related to urban heat vulnerability, marking a positive step toward creating resilient and sustainable urban environments.

This paper presents a method for the study of the influence of stability of a power transformer on the power system based on the vibration principle. Traditionally, the EMD and EEMD algorithms are employed to test the box vibration signal data of the power transformer under three working conditions. The proposed method utilizes a partial EMD screening along with MPEEMD method for the online monitoring of power transformer. A complete online monitoring system is designed by using the STM32 processor and LabVIEW system. The proposed system is compared with EMD and EEMD algorithms in terms of the number of IMFs obtained by decomposition, maximum correlation coefficient, and mean square error. The inherent mode correlation, when compared with the mean square error of the reconstructed signal, shows that the reconstruction error of MPEEMD algorithm is 4.762×10−15 which is better than the traditional EMD algorithm. It is observed from the results that the proposed method outperforms both EMD and EEMD algorithms.

Background As noise brings great error in the analysis of metallographic images, an adaptive weighted mean filtering method proposed to overcome the shortcomings of the standard mean filtering method. Methods The method used to detect the pulse noise points in the image, and then the modified mean method used to filter out the detected noise points. Patents on metallographic image processing have discussed for the development of the proposed methodology. Results It is shown that filter window can be filtered in comparison with the conventional 3×3, 5×5 and 7×7 filt window to reduce noise detection and reduce the complexity of the weight calculation. Conclusion It can be concluded that this method can better protect the details of the image, has better filtering effect than the standard mean filtering, and its processing speed is faster than the median filtering of the large window, which has profound significance for the edge detection and processing of the metallographic image.