Design and Implementation of Electrostatic Spraying Automatic Controlling System Based on PLC

Abstract: The objective of this study was to improve the spraying efficiency and meet the demand of modern agricultural. A new generation of electrostatic sprayer which we designed realized the goals. The automatic controlling system is successfully designed. PLC (Programmable Logic Controller) was taken as the control core of the system and LCD touch screen was employed for human-computer interaction interface. The system integrates kinds of techniques including programming, pressure monitoring and sensor technology, etc. The main structure of this equipment, working principle and control system hardware selection will be also introduced in the study. Human-computer interaction software was programmed by the software of Pro Tool/Pro CS. System controlling software was programmed in form of ladder diagram, which realized kinds of functions including ESD protection, accurate quantification, automatic controlling and humanized operation. Test results show that the effective spraying range is between 5 to 6 m, the Volume Median Diameter (VMD) is 47.48 µm and the Ultra-Low Volume spray (ULV) is realized. The spray deposition rate and effective availability of pesticide is higher than old sprayer. And also this new sprayer runs steadily

Design and Performance of Inductive Electrostatic Sprayer

Abstract: In order to improve spraying results, an inductive electrostatic sprayer was designed. The performance of the sprayer was then tested. The test result shows that the charge-to-mass ratio can reach 0.951 mc/Kg when electrostatic voltage is 20 KV and working pressure is 0.25 to 0.4 MPa. The particle size distribution of charged droplets are more concentrated than that of uncharged droplets, the axial velocity of charged droplets is faster than that of uncharged droplets, and the velocity distribution uniformity is also improved. The average deposition rate under charging conditions is 14% higher than that in uncharged conditions. Moreover, the deposit rate of the back of the leaf is evident

Finite Element Approximations for Stokes-Darcy Flow with Beavers-Joseph Interface Conditions

Numerical solutions using finite element methods are considered for transient flow in a porous medium coupled to free flow in embedded conduits. Such situations arise, for example, for groundwater flows in karst aquifers. the coupled flow is modeled by the Darcy equation in a porous medium and the Stokes equations in the conduit domain. on the interface between the matrix and conduit, Beavers-Joseph interface conditions, instead of the simplified Beavers-Joseph-Saffman conditions, are imposed. Convergence and error estimates for finite element approximations are obtained. Numerical experiments illustrate the validity of the theoretical results. © 2010 Society for Industrial and Applied Mathematics

What Makes Pre-trained Language Models Better Zero/Few-shot Learners?

In this paper, we propose a theoretical framework to explain the efficacy of prompt learning in zero/few-shot scenarios. First, we prove that conventional pre-training and fine-tuning paradigm fails in few-shot scenarios due to overfitting the unrepresentative labelled data. We then detail the assumption that prompt learning is more effective because it empowers pre-trained language model that is built upon massive text corpora, as well as domain-related human knowledge to participate more in prediction and thereby reduces the impact of limited label information provided by the small training set. We further hypothesize that language discrepancy can measure the quality of prompting. Comprehensive experiments are performed to verify our assumptions. More remarkably, inspired by the theoretical framework, we propose an annotation-agnostic template selection method based on perplexity, which enables us to ``forecast'' the prompting performance in advance. This approach is especially encouraging because existing work still relies on development set to post-hoc evaluate templates. Experiments show that this method leads to significant prediction benefits compared to state-of-the-art zero-shot methods