Application of a new feature extraction and optimization method to surface defect recognition of cold rolled strips

Considering that the surface defects of cold rolled strips are hard to be recognized by human eyes under high-speed circumstances, an automatic recognition technique was discussed. Spectrum images of defects can be got by fast Fourier transform （FFF） and sum of valid pixels （SVP）, and its optimized center region, which concentrates nearly all energies, are extracted as an original feature set. Using genetic algorithm to optimize the feature set, an optimized feature set with 51 features can be achieved. Using the optimized feature set as an input vector of neural networks, the recognition effects of LVQ neural networks have been studied. Experiment results show that the new method can get a higher classification rate and can settle the automatic recognition problem of surface defects on cold rolled strips ideally.

High sensitivity dual core photonic crystal fiber sensor for simultaneous detection of two samples

The optical control ability of photonic crystal fiber(PCF)is a distinctive property suitable for improving sensing and plasma performance.This article proposes a dual-core D-channel PCF sensor that can detect two samples simultaneously,which effectively solves the problems of coating difficulty and low wavelength sensitivity.The PCF has four layers of air holes,which dramatically reduces the optical fiber loss and is more conducive to the application of sensors in actual production.In addition,by introducing dual cores on the upper and lower sides of the central air hole,reducing the spacing between the core and the gold nanolayer,a stronger evanescent field can be generated in the cladding air hole.The optical fiber sensor can detect the refractive index of two samples simultaneously with a maximum sensitivity of 21300 nm/RIU.To the best of our knowledge,the sensitivity achieved in this work is the highest sensitivity with the dual sample synchronous detection sensors.The detection range of the refraction index is 1.35-1.41,and the resolution of the sensor is 4.695×10^(-6).Overall,the sensor will be suitable for medical detection,organic chemical sensing,analyte detection,and other fields.

Cost-effective generation of A-to-G mutant mice by zygote electroporation of adenine base editor ribonucleoproteins

More than 32,000 pathogenic single nucleotide polymorphisms(SNPs)have been identified in the human genome(Gaudelli et al.,2017).Genetically modified mice with pathogenic SNPs are good models for studies of disease pathogenesis and the development of new therapeutics.Accordingly,an efficient,high-throughput method for the generation of mouse models with SNPs is needed.

Received signal strength indication-based localisation method with unknown path-loss exponent for HVDC electric field measurement

The electric field environment under high-voltage direct current(HVDC)transmission lines is an important design consideration.In the wireless sensor networks for electric field measurement system under the HVDC transmission lines,it is necessary to obtain the electric field distribution with multiple sensors.The accurate localisation of sensing nodes is essential to the analysis of measurement results.However,most current techniques are limited to constant measurement environment with fixed and known path-loss exponent.Here,the authors report a localisation method based on received signal strength indication with unknown path-loss exponent for the localisation of one-dimensional linear topology wireless networks in the electric field measurement system.The optimisation method is utilised to obtain the optimal pass-loss parameter without involving the previous environment parameters.Afterwards,simulations are employed to demonstrate the feasibility and the effectiveness of the proposed method by comparing with other methods.