LociScan,a tool for screening genetic marker combinations for plant variety discrimination

To reduce the cost and increase the efficiency of plant genetic marker fingerprinting for variety discrimination,it is desirable to identify the optimal marker combinations.We describe a marker combination screening model based on the genetic algorithm(GA)and implemented in a software tool,Loci Scan.Ratio-based variety discrimination power provided the largest optimization space among multiple fitness functions.Among GA parameters,an increase in population size and generation number enlarged optimization depth but also calculation workload.Exhaustive algorithm afforded the same optimization depth as GA but vastly increased calculation time.In comparison with two other software tools,Loci Scan accommodated missing data,reduced calculation time,and offered more fitness functions.In large datasets,the sample size of training data exerted the strongest influence on calculation time,whereas the marker size of training data showed no effect,and target marker number had limited effect on analysis speed.

ABORT-like detector to combat active deceptive jamming in a network of LFM radars

This paper studies an electronic counter-counter measures（ECCM） scheme combating against deceptive electronic counter measure（ECM） techniques. An adaptive detector exploiting generalized likelihood ratio test（GRLT） criterion is applied to detect the presence of deceptive jamming in fractional Fourier transform（Fr FT） domain. First, the generating mechanism of spurious frequencies is analyzed based on the Volterra serial. The proposed nonlinear distortion model based on power amplifier behavior is robust in distortion analysis when the memory effect is considered.Second, a modified adaptive beamformer orthogonal rejection test（ABORT） like detector in closed form is built. The proposed detector can discriminate the echo and deceptive jamming adaptively by exploiting primary data and secondary data. This ECCM scheme is capable of guaranteeing the performance without the restriction of orthogonality, which is essential for the ABORT detectors. The expansion to radar network is discussed as a special case at the final part of this paper. Numerical simulations demonstrate the effectiveness of the proposed method.

The classification of handwriting features of the Kazakh language written in Latin script

In 2017,the Republic of Kazakhstan began the phased transition of its alphabet from Cyrillic to Latin script.This transition has presented significant challenges to Kazakhstani document examiners,who have yet to develop appropriate methodologies for the analysis of handwriting samples written in the Kazakh language using Latin letters.This study aims to identify distinguishing macro and micro features of letters within Kazakh writing samples produced using the Latin alphabet and determine their frequencies of occurrence and discriminating power indices.Micro features were examined using the four most frequently appearing letters:“a”,“y”,“e”and“n”.A comparative analysis of tested Latin letters with those of a similar configuration in Cyrillic demonstrated differences in the number of distinguishing features,as well as in the frequency of occurrence and discriminating power indices of similar features.These results show that separate statistical bases should be used for Latin and Cyrillic letters when analysing handwriting samples based on the frequencies of occurrence of micro and macro writing features.