Further Study of the Viscoelastic Phase Separation of Cyanate Ester Modified with Poly(ether imide)

ABSTRACT: In this study, the viscoelastic phase separation process was studied further by time-resolved light scattering, differential scanning calorimetry, and scanning electron microscopy in the system of poly(ether imide)-modified bisphenol-A dicyanate. It was observed that the evolution time of phase structure and relaxation time of diffusion flow of the bisphenol-A dicyanate were similar with the phase diagram of curing conversion versus content of PEI. The results suggested that the viscoelastic phase separation was affected by the curing conversion of the system at the onset point of phase separation

Wild Animal Information Collection Based on Depthwise Separable Convolution in Software Defined IoT Networks

The wild animal information collection based on the wireless sensor network (WSN) has an enormous number of applications, as demonstrated in the literature. Yet, it has many problems, such as low information density and high energy consumption ratio. The traditional Internet of Things (IoT) system has characteristics of limited resources and task specificity. Therefore, we introduce an improved deep neural network (DNN) structure to solve task specificity. In addition, we determine a programmability idea of software-defined network (SDN) to solve the problems of high energy consumption ratio and low information density brought about by low autonomy of equipment. By introducing some advanced network structures, such as attention mechanism, residuals, depthwise (DW) convolution, pointwise (PW) convolution, spatial pyramid pooling (SPP), and feature pyramid networks (FPN), a lightweight object detection network with a fast response is designed. Meanwhile, the concept of control plane and data plane in SDN is introduced, and nodes are divided into different types to facilitate intelligent wake-up, thereby realizing high-precision detection and high information density of the detection system. The results show that the proposed scheme can improve the detection response speed and reduce the model parameters while ensuring detection accuracy in the software-defined IoT networks