A5100619559- Plant Physiology and Cultivation Studies
- Postharvest Quality and Shelf Life Management
- Membrane Separation and Gas Transport
- Spectroscopy and Chemometric Analyses
- Advanced Photocatalysis Techniques
- Carbon Dioxide Capture Technologies
- Phytochemicals and Antioxidant Activities
- Covalent Organic Framework Applications
- Soil Mechanics and Vehicle Dynamics
- Agricultural Engineering and Mechanization
- Smart Agriculture and AI
- MXene and MAX Phase Materials
- Botanical Research and Applications
- Catalytic Processes in Materials Science
- Plasmonic and Surface Plasmon Research
- Catalysis and Hydrodesulfurization Studies
- Remote Sensing and Land Use
- Animal Diversity and Health Studies
- Granular flow and fluidized beds
- Air Quality Monitoring and Forecasting
- 2D Materials and Applications
- Atmospheric chemistry and aerosols
- Advanced Fiber Optic Sensors
- Polymer-Based Agricultural Enhancements
- Industrial Gas Emission Control
Sichuan University
2025
West China Hospital of Sichuan University
2025
Xinjiang University
2023-2024
Changzhou University
2022-2024
Tarim University
2020-2024
Hunan University of Science and Technology
2024
Xinjiang Production and Construction Corps
2024
Jiangsu Normal University
2023-2024
China Guodian Corporation (China)
2023-2024
Ludong University
2022-2024
Green roof technology is recognized for mitigating stormwater runoff and energy consumption. Methods to overcome the cost gap between green roofs conventional were recently quantified by incorporating air quality benefits. This study investigates impact of scaling on these benefits at city-wide scale using Washington, DC as a test bed because proposed targets in 20−20−20 vision (20 million ft2 2020) articulated Casey Trees, nonprofit organization. Building-specific analyzed assuming two...
Photocatalytic oxidation desulfurization (PODS) has emerged as a promising, ecofriendly alternative to traditional, energy-intensive fuel methods. Nevertheless, its progress is still hindered due the slow sulfide kinetics in current catalytic systems. Herein, we present MoOx decorated on Cu2O@CuO core-shell catalyst, which enables new, efficient PODS pathway by situ generation of hydrogen peroxide (H2O2) with saturated moist air oxidant source. The photocatalyst delivers remarkable specific...
Abstract The detection of soluble solid content in Korla fragrant pear is a destructive and time‐consuming endeavor. In effort to remedy this, nondestructive testing method based on electrical properties artificial neural network was established this study. Specifically, variations (e.g., equivalent parallel capacitance, quality factor, loss resistance, complex impedance, inductance) pears with accumulated temperature were tested using workbench developed by ourselves. After that the...
To determine the optimal fertilizer discharging performance, a spiral applicator was designed according to orchard agricultural requirements. The influence of different parameter combinations speed, blade diameter, and pitch on coefficient variation (CV) discharge uniformity predicted using neural-network-based model by Box–Behnken design (BBD) test. According extracted results, neural network has good prediction ability, with determination mean relative error reaching 0.99 2.29%,...
To investigate the causes of flow fluctuations in a worm-type distributor during fertilization process, this study employed discrete element method to simulate process. The analysis focused on influences force chain evolution particle and effects rotational speed. results indicate that are not solely attributed its helical structure but closely associated with chains within systems. Furthermore, one-to-one correspondence between force-chain exists. speed was found exert significant axial...
Abstract To scientifically and effectively predict the shelf life of damaged Korla fragrant pears, this paper explores effects maturity, storage temperature, damage degree on their life, which was furthermore predicted employing three neural network modeling methods: Back Propagation Neural Network, General Regression Network (GRNN), Adaptive Network‐based Fuzzy Inference System (ANFIS). A prediction model then built to achieve optimal pears. The results suggest that exert a significant...
Vector Polygons are valuable survey data, serving as crucial outputs of national geographical censuses and a fundamental data source for detecting changes in conditions.Current remote-sensing image change detection methods rely on comparing images but overlook abundant historical vector results, struggle with model generalization, lack adequate samples.Consequently, remains manual process primarily, unable to meet the requirements automated efficient monitoring standardized conditions.Hence,...
Generalized-regression-neural-network (GRNN) and adaptive neuro-fuzzy inference system (ANFIS) models were utilized to develop mathematical for assessing the effects of harvest maturity storage time on quality Korla fragrant pear. The results showed that fruit firmness had high correlations with time. At different maturities, pear decreased increasing time; while under same time, a lower resulted in faster decrease GRNN ANFIS validated be reliable predicting variation tendency In addition,...
It is difficult to control the quality of Korla pear with different degrees maturity during storage. Here, a method was proposed for predicting effects harvest and cold storage time on indices (soluble solid content (SSC) Vitamin C (Vc) content) pear. The generalized regression neural network (GRNN) adaptive neuro-fuzzy inference system (ANFIS) were employed predict changes fragrant fruit results demonstrated that SSC in pears 10%-70% showed continuous increases first 90 d then slight...
The detection method for technological parameter is outdates as the traditional test cycle long well measurement error and amount are huge. Moreover, it difficult to disclose operation mechanism of devices time-consuming laborious. Therefore, numerical simulation was used in this study reveal walnut shell-kernel winnowing device. influence baffle opening combinations, inlet wind velocity angle on cleaning rate loss predicted by neural network model. results demonstrated that primary...
Abstract To design a walnut shell–kernel winnowing device, the aerodynamic characteristics of shells and kernels were studied by combining theoretical computation empirical tests. A method was developed for separation based on an analysis suspending velocity. The performance device evaluated screening rate loss rate. Influences feeding rate, wind speed, vibration frequency simulated, optimal operating parameters acquired. Research results demonstrated that velocity ranges 8.96–13.89...
To predict the weight-loss ratio of Korla fragrant pears effectively, improve commodity value and study variation laws damaged during storage, this predicted by utilizing generalized regression neural network (GRNN), support vector (SVR), partial least squares (PLSR) error back propagation (BPNN). The prediction performances GRNN, SVR, PLSR BPNN models were compared comprehensively, optimal model was determined. In addition, verified. results show that increases gradually with extension...
The separation of walnut kernels and shells has long been regarded as a bottleneck, limiting processing efficiency, product quality, industry advancement. In response to the challenges improving accuracy inadequacy existing equipment for meeting demands, this paper proposes an innovative shell–kernel device based on machine vision technology. An experimental system was constructed, key parameters were optimized enhance its performance. comprises five main modules: material conveyance, image...