Radio Sources Segmentation and Classification with Deep Learning

Modern large radio continuum surveys have high sensitivity and resolution, and can resolve previously undetected extended and diffuse emissions, which brings great challenges for the detection and morphological classification of extended sources. We present HeTu-v2, a deep learning-based source detector that uses the combined networks of Mask Region-based Convolutional Neural Networks (Mask R-CNN) and a Transformer block to achieve high-quality radio sources segmentation and classification. The sources are classified into 5 categories: Compact or point-like sources (CS), Fanaroff-Riley Type I (FRI), Fanaroff-Riley Type II (FRII), Head-Tail (HT), and Core-Jet (CJ) sources. HeTu-v2 has been trained and validated with the data from the Faint Images of the Radio Sky at Twenty-one centimeters (FIRST). We found that HeTu-v2 has a high accuracy with a mean average precision ($AP_{\rm @50:5:95}$) of 77.8%, which is 15.6 points and 11.3 points higher than that of HeTu-v1 and the original Mask R-CNN respectively. We produced a FIRST morphological catalog (FIRST-HeTu) using HeTu-v2, which contains 835,435 sources and achieves 98.6% of completeness and up to 98.5% of accuracy compared to the latest 2014 data release of the FIRST survey. HeTu-v2 could also be employed for other astronomical tasks like building sky models, associating radio components, and classifying radio galaxies

Variable structure intelligent control for mango drying with air source heat pump

Objective: To improve the energy efficiency of mango drying in the air source heat pump system so as to save energy. Methods: The process of drying mangoes was subdivided, and a variable structure control was used to adjust the temperature and humidity of drying room intelligently and dynamically to improve energy efficiency. Each drying process stage was divided into three parts, namely far away from the conversion point, near the conversion point, and closing to the conversion point. For the first two parts, a constrained nonlinear autoregressive neural network (NARX) with external inputs was used to intelligently adjust the temperature and humidity settings so as to save electricity, while for the third part, a PI controller was used to accurately control the dehumidification amount at the conversion point of the drying process so as to ensure the quality of mango drying. Results: Compared with conventional segmented constant temperature and humidity drying methods, the proposed control method could save 8.63% of electricity with a guaranteed quality of mango drying. Conclusion: The proposed subdivided variable structure control method can significantly improve the energy efficiency of heat pump drying systems, and achieve drying quality similar to conventional segmented constant temperature and humidity methods

Drag reduction in turbulent channel flow using bidirectional wavy Lorentz force

Turbulent control and drag reduction in a channel flow via a bidirectional traveling wave induced by spanwise oscillating Lorentz force have been investigated in the paper. The results based on the direct numerical simulation (DNS) indicate that the bidirectional wavy Lorentz force with appropriate control parameters can result in a regular decline of near-wall streaks and vortex structures with respect to the flow direction, leading to the effective suppression of turbulence generation and significant reduction in skin-friction drag. In addition, experiments are carried out in a water tunnel via electro-magnetic (EM) actuators designed to produce the bidirectional traveling wave excitation as described in calculations. As a result, the actual substantial drag reduction is realized successfully in these experiments

Boundary Criteria for the Stability of Delay Differential-Algebraic Equations

This paper is concerned with the asymptotic stability of delay differential-algebraic equations. Two stability criteria described by evaluating a corresponding harmonic analytical function on the boundary of a certain region are presented. Stability regions are also presented so as to show the method geometrically. Our results are not reported

A new stability analysis for a class of nonlinear delay differential-algebraic equations and implicit Euler methods

Solving nonlinear problems through linearization.Although the linearization process is local,under certain conditions,linearization within the local neighborhood of some solution may not affect the original equations.Based on this idea,we consider the stability and asymptotic stability of a class of nonlinear delay differential-algebraic equations and numerical methods of implicit Euler methods by means of linearization process.Sufficient conditions for stability and asymptotic stability are obtained

Stability criteria for delay differential-algebraic equations

The asymptotic stability of delay differential-algebraic equations are researched in this paper.Two stability criteria described by evaluating a corresponding harmonic function on the boundary of a torus region are presented