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Fluorescence spectroscopy attracted more and more attention in pesticide residue detection field because of its advantages of non-destructive, non-contact, high speed and no requirement of complex pre-process procedure. However, given that the concentration of the pesticide detected via fluorescence spectroscopy is calculated in accordance with the Beer-Lambert law, this method can only be used to detect samples containing a single kind of pesticide or several kinds of pesticides with completely different fluorescence which is not in accordance with practical cases. In this article, to overcome this disadvantage, back-propagation (BP) neural network algorithm was introduced to detect multiple kinds of pesticides via fluorescence spectroscopy. The results from four kinds of pesticides which are usually used for fruits and vegetables indicated the effectiveness of BP neural network algorithm.

A distributed energy system (DES) using controlled power electronics converters delivers power to loads, via conventional, as well as a number of renewable, energy sources. However, stability concerns retard the integration of power electronics converters into an existing DES. Therefore, due to the high penetration of power converters, the overall network analysis of DES is becoming increasingly difficult. Impedance-based DES modeling emerged as an effective technique as it reduces the system into source and load subsystems and offers easier analysis of the dynamic interactions between them. These models can be obtained using either analytical calculations, simulations, or experimental measurements. In this work, firstly, a line-to-line current injection technique is used for the measurement of alternating current (AC) impedances. Since it requires repeated injections, a d q -domain impedance measurement methodology based upon a set of independent perturbations and measurements is proposed. The perturbation is injected via a sweep signal which is preprocessed by the digital signal processor (DSP) prior to injection. The d q reference frame is synchronized with the three-phase AC system using a low-bandwidth phase-locked loop (PLL). The close matching of impedance parameters measured in simulation using the proposed approach with those obtained using analytical expressions and the line-to-line current injection technique verifies the effectiveness of the approach. Furthermore, the method was also implemented experimentally, and the close matching of the results with the analytical and simulation results validates the overall modeling and measurement procedure.

Research shows that traditional end-to-end delay upper bound in wireless sensor network (WSN) is pessimistic. Thus based on network calculus, this paper presents a network model with the arrival curve regulated by the leaky bucket and rate-latency service curve, and derivates an improved deterministic upper bound of end-to-end delay in WSN by improving the output bound of a flow traversing a node. Due to the stricter output bound, the delay upper bound derived in the paper is simpler and more accurate, which is useful for topology control and routing protocol design in delay-guaranteed WSN in order to improve the quality of service. Numerical results show that the paper's delay bounds are improved well, which are much tighter than traditional delay bounds.