Optimization of UWB indoor positioning based on hardware accelerated Fuzzy ISODATA

Abstract With the development of wireless communication technology, Ultra-Wideband (UWB) has become an important solution for indoor positioning. In complex indoor environments, the influence of non-line-of-sight (NLOS) factors leads to increased positioning errors. To improve the positioning accuracy, fuzzy iterative self-organizing data analysis clustering algorithm (ISODATA) is introduced to process a large amount of UWB data to reduce the influence of NLOS factors, and to stabilize positioning error within 2 cm, enhances the accuracy of the positioning system. To further improve the running efficiency of the algorithm, FPGA is used to accelerate the key computational part of the algorithm, compared with running on the MATLAB platform, which improves the speed about 100 times, enhances the algorithm’s computational speed dramatically

Fine Mapping of Five Grain Size QTLs Which Affect Grain Yield and Quality in Rice

Grain size is a quantitative trait with a complex genetic mechanism, characterized by the combination of grain length (GL), grain width (GW), length to width ration (LWR), and grain thickness (GT). In this study, we conducted quantitative trait loci (QTL) analysis to investigate the genetic basis of grain size using BC1F2 and BC1F2:3 populations derived from two indica lines, Guangzhan 63-4S (GZ63-4S) and TGMS29 (core germplasm number W240). A total of twenty-four QTLs for grain size were identified, among which, three QTLs (qGW1, qGW7, and qGW12) controlling GL and two QTLs (qGW5 and qGL9) controlling GW were validated and subsequently fine mapped to regions ranging from 128 kb to 624 kb. Scanning electron microscopic (SEM) analysis and expression analysis revealed that qGW7 influences cell expansion, while qGL9 affects cell division. Conversely, qGW1, qGW5, and qGW12 promoted both cell division and expansion. Furthermore, negative correlations were observed between grain yield and quality for both qGW7 and qGW12. Nevertheless, qGW5 exhibited the potential to enhance quality without compromising yield. Importantly, we identified two promising QTLs, qGW1 and qGL9, which simultaneously improved both grain yield and quality. In summary, our results laid the foundation for cloning these five QTLs and provided valuable resources for breeding rice varieties with high yield and superior quality