For some insect groups, wing outline is an important character for species identification. We have constructed a program as the integral part of an automated system to identify insects based on wing outlines (DAIIS). This program includes two main functions: (1) outline digitization and Elliptic Fourier transformation and (2) classifier model training by pattern recognition of support vector machines and model validation. To demonstrate the utility of this program, a sample of 120 owlflies (Neuroptera: Ascalaphidae) was split into training and validation sets. After training, the sample was sorted into seven species using this tool. In five repeated experiments, the mean accuracy for identification of each species ranged from 90% to 98%. The accuracy increased to 99% when the samples were first divided into two groups based on features of their compound eyes. DAIIS can therefore be a useful tool for developing a system of automated insect identification.
In this paper, a simple model, but
with high accuracy for a packed
column liquid desiccant regenerator, to describe the heat and mass
transfer process is developed. By lumping fluids’ thermodynamic
properties and the geometric specifications as constants, two equations
related with seven identified parameters are developed to predict
the heat and mass transfer rate for solution regeneration processes
in the regenerator. Commissioning information and the Levenberg–Marquardt
method are employed to determine the unknown parameters. Compared
with previous models, the presented model is simply constructed and
accurate and requires no iterative computations while applied in predicting
the heat and mass transfer rate once the parameters of the proposed
model are determined. Experimental results demonstrate that the current
model is effective to predict the performance of desiccant regeneration
in the regenerator over wide working conditions. The proposed model
promises to have wide application for real-time performance monitoring,
optimization, and control for liquid desiccant regeneration.
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