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Wireless Remote Water Meter Design of Automatic Meter Reading System
Zhu HengJun,Zhu YiSheng 보안공학연구지원센터 2015 International Journal of Smart Home Vol.9 No.12
By wireless communication through GPRS internet, a remote water metering system with low cost, accuracy and adaptable to complex environment was designed. In this paper, the analysis on the scheme confirmation, the development of management software was carried out, and the integrated design of the system based on GPRS was studied. The general planning and the technical requirements on the user’s water consumption detecting system was also put forward, based on the S3C2440 chip.
A design and Implementation of Portable Spectrum Analyzer
Zhu Hengjun,Wang Wenxing 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.12
With the progress of society signal measurement and analysis have more widely range of applications, but the spectrum analyzer was generally expensive to make it difficult for popularization and application. In this paper, a design methodology of low cost, stable reliable spectrum analyzer based on the idea of Software Defined Radio (SDR) is presented, which consists of three functional units. The STM32 is the core of spectrum analyzer and is the key base to signal acquisition and analysis of the system. This paper designs the detailed hardware circuit and the software and optimizes the display program to obtain a higher refresh rate. Through testing the design is stable and reliable, simple and practical, and suitable for use in scientific research and industry production.
Machine learning-based prediction and performance study of transparent soil properties
Bo Wang,Hengjun Hou,Zhengwei Zhu,Wang Xiao 국제구조공학회 2021 Smart Structures and Systems, An International Jou Vol.28 No.2
An indispensable process of geotechnical modeling with transparent soils involves analyzing images and soil property simulations. This study proposes an objective framework for quantitative analysis of the influential mechanism of three key factors, namely, different aggregate proportions (DAP), solvent ratio (SR), and solute solution ratio (SSR) on transparent soils’ transparency and shear strength. 125 groups of transparent soil samples considering these three factors were prepared to investigate their impact on transparency and shear strength through Elastic Net regression. Spearman correlation analysis was performed for transparency and shear strength. Furthermore, by comparing the performance of XGBoost, GBDT, Random Forest, and SVR after hyperparameter tuning in predicting transparency and shear strength, XGBoost proved to be the optimal machine learning model with the lowest MSE of 0.0048 and 0.0306 and was innovatively adopted to analyze how various factors affect the transparency and shear strength, thus enhancing the interpretability of machine learning. A ranking system, according to the importance scores of XGBoost, shows that SSR was the most important factor affecting both shear strength and transparency of transparent soils, with importance scores being 0.45 and 0.57, respectively. Our study may shed light on the preparation and performance study of transparent soils.