Precise Monitoring of Soil Salinity in China’s Yellow River Delta Using UAV-Borne Multispectral Imagery and a Soil Salinity Retrieval Index

Monitoring salinity information of salinized soil efficiently and precisely using the unmanned aerial vehicle (UAV) is critical for the rational use and sustainable development of arable land resources. The sensitive parameter and a precise retrieval method of soil salinity, however, remain unknown. This study strived to explore the sensitive parameter and construct an optimal method for retrieving soil salinity. The UAV-borne multispectral image in China’s Yellow River Delta was acquired to extract band reflectance, compute vegetation indexes and soil salinity indexes. Soil samples collected from 120 different study sites were used for laboratory salt content measurements. Grey correlation analysis and Pearson correlation coefficient methods were employed to screen sensitive band reflectance and indexes. A new soil salinity retrieval index (SSRI) was then proposed based on the screened sensitive reflectance. The Partial Least Squares Regression (PLSR), Multivariable Linear Regression (MLR), Back Propagation Neural Network (BPNN), Support Vector Machine (SVM), and Random Forest (RF) methods were employed to construct retrieval models based on the sensitive indexes. The results found that green, red, and near-infrared (NIR) bands were sensitive to soil salinity, which can be used to build SSRI. The SSRI-based RF method was the optimal method for accurately retrieving the soil salinity. Its modeling determination coefficient (R2) and Root Mean Square Error (RMSE) were 0.724 and 1.764, respectively; and the validation R2, RMSE, and Residual Predictive Deviation (RPD) were 0.745, 1.879, and 2.211.

Gate Current in p-GaN Gate HEMTs as a Channel Temperature Sensitive Parameter: A Comparative Study between Schottky- and Ohmic-Gate GaN HEMTs

In this work, a comparison between the gate-driving requirements of p-GaN HEMTs with gate contact of Schottky and Ohmic type is presented. Furthermore, the presence of a gate current of different magnitude is experimentally verified for both types of devices. Successively, the possibility of using the gate current as a temperature-sensitive parameter and its monitoring during real circuit operation is proposed. The viability of monitoring the gate current without introducing additional complexity in the gate driver is examined through experimental measurements on commercially available p-GaN HEMTs.

Effect of Undecided and Swing Voters on The Dynamics Voters Model in Presidential Elections

In this paper, we construct the NUS1S2A voters model of two political fanaticism figures which involves undecided and swing voters. We determine the equilibrium points and the threshold parameter of the voters model. We also perform a sensitivity analysis for the threshold number to determine the importance of model parameters. The results of the sensitivity analysis show that the rate of transfer from neutral voters to undecided and swing voters is not the most negative sensitive parameter of the model, even though an increase in its parameter will cause a decrease in voter interest in voting in the presidential elections.

Understanding non-linearity in electrochemical systems using multisine-based non-linear characterization

Background: With the development of advanced characterization techniques, lithium-ion battery non-linearities have recently gained increased attention which can benefit battery health diagnosis and ageing mechanism identification. In comparison to conventional single sine wave-based methods, the multisine-based non-linear characterization method has the advantage of capturing the dynamic voltage response within a short testing duration, and therefore has further development potential for on-board applications. However, understanding lithium-ion battery electrochemical processes that contribute to battery non-linearities is still unclear. Methods: In this paper, the sensitivity of the Doyle–Fuller–Newman model parameters are analysed in the frequency domain to investigate the electrochemical processes that contribute to the non-linear dynamics of the voltage response. To begin with, the non-linearities of the Doyle–Fuller–Newman model with validated parameters are characterized and compared to experimental data from a commercial cell. This demonstrated a significant difference between the mathematical model and the non-linearities determined experimentally. Then, a global sensitivity analysis is applied to determine the most sensitive parameter contributing to battery non-linearities. Finally, the appropriate value of the most sensitive parameter which results in the closest non-linear response to the commercial battery is estimated through minimizing the root mean square error. Results: The results show that the charge transfer coefficient is the most sensitive parameter contributing to battery non-linearities among the Doyle–Fuller–Newman model parameters. The non-linear response of the Doyle–Fuller–Newman model is validated with good agreement with the experimental results, when the Butler–Volmer kinetic is asymmetrical due to the unequal anodic and cathodic charge transfer coefficients.

Assessing the impact of working pressure on water meter registration

Fluctuations in the network pressure of water supply systems affect hydraulic performance and water meter accuracy. The development of metering error curves requires steady-state conditions which are extremely rare in water distribution systems characterized by intermittent supply. Simple deterministic models are suggested and developed from monthly data collected over a 4-year period (2010–2014) for three most dominant meter models (Models 1–3) in the Kampala Water Distribution System (KWDS), Uganda. This study combines pressure and billing information at the same time to understand metering accuracy. Results showed that metering accuracy increased by 4.2, 8.4 and 2.9% when pressure was increased from 10 to 50 m for Models 1–3, respectively. Age did not influence the impact of pressure on meter accuracy. The most sensitive parameter in the model was the meter age. Metering accuracy was relatively constant after a period of 5 years. The least sensitive parameter was the working pressure which caused a slight change to the annual billed volume. The ability of the model to accurately predict the meter registration degenerated with an increasing annual billed volume. Model 2 meters were the best performing and probably the most suitable meters in the KWDS.