Fault estimation for time-varying systems with Round-Robin protocol

summary:This paper is concerned with the design problem of finite-horizon $H_\infty$ fault estimator for a class of nonlinear time-varying systems with Round-Robin protocol scheduling. The faults are assumed to occur in a random way governed by a Bernoulli distributed white sequence. The communication between the sensor nodes and fault estimators is implemented via a shared network. In order to prevent the data from collisions, a Round-Robin protocol is utilized to orchestrate the transmission of sensor nodes. By means of the stochastic analysis technique and the completing squares method, a necessary and sufficient condition is established for the existence of fault estimator ensuring that the estimation error dynamics satisfies the prescribed $H_\infty$ constraint. The time-varying parameters of fault estimator are obtained by recursively solving a set of coupled backward Riccati difference equations. A simulation example is given to demonstrate the effectiveness of the proposed design scheme of the fault estimator

A study on compressive anisotropy and nonassociated flow plasticity of the AZ31 Magnesium Alloy in hot rolling

Effect of anisotropy in compression is studied on hot rolling of AZ31 magnesium alloy with a three-dimensional constitutive model based on the quadratic Hill48 yield criterion and nonassociated flow rule (non-AFR). The constitutive model is characterized by compressive tests of AZ31 billets since plastic deformations of materials are mostly caused by compression during rolling processes. The characterized plasticity model is implemented into ABAQUS/Explicit as a user-defined material subroutine (VUMAT) based on semi-implicit backward Euler\u27s method. The subroutine is employed to simulate square-bar rolling processes. The simulation results are compared with rolled specimens and those predicted by the von Mises and the Hill48 yield function under AFR. Moreover, strip rolling is also simulated for AZ31 with the Hill48 yield function under non-AFR. The strip rolling simulation demonstrates that the lateral spread generated by the non-AFR model is in good agreement with experimental data. These comparisons between simulation and experiments validate that the proposed Hill48 yield function under non-AFR provides satisfactory description of plastic deformation behavior in hot rolling for AZ31 alloys in case that the anisotropic parameters in the Hill48 yield function and the non-associated flow rule are calibrated by the compressive experimental results

Driver Cognitive Distraction Detection Using Driving Performance Measures

Driver cognitive distraction is a hazard state, which can easily lead to traffic accidents. This study focuses on detecting the driver cognitive distraction state based on driving performance measures. Characteristic parameters could be directly extracted from Controller Area Network-(CAN-)Bus data, without depending on other sensors, which improves real-time and robustness performance. Three cognitive distraction states (no cognitive distraction, low cognitive distraction, and high cognitive distraction) were defined using different secondary tasks. NLModel, NHModel, LHModel, and NLHModel were developed using SVMs according to different states. The developed system shows promising results, which can correctly classify the driver’s states in approximately 74%. Although the sensitivity for these models is low, it is acceptable because in this situation the driver could control the car sufficiently. Thus, driving performance measures could be used alone to detect driver cognitive state

License Plate Recognition Algorithm for Passenger Cars in Chinese Residential Areas

This paper presents a solution for the license plate recognition problem in residential community administrations in China. License plate images are pre-processed through gradation, middle value filters and edge detection. In the license plate localization module the number of edge points, the length of license plate area and the number of each line of edge points are used for localization. In the recognition module, the paper applies a statistical character method combined with a structure character method to obtain the characters. In addition, more models and template library for the characters which have less difference between each other are built. A character classifier is designed and a fuzzy recognition method is proposed based on the fuzzy decision-making method. Experiments show that the recognition accuracy rate is up to 92%

Development and Characterization of Microsatellite Markers Based on the Chloroplast Genome of Tree Peony

Tree peony (Paeonia suffruticosa Andr.) is a famous ornamental and medicinal flowering species. However, few high-efficiency chloroplast microsatellite markers have been developed for it to be employed in taxonomic identifications and evaluation of germplasm resources to date. In the present study, a total of 139 cpSSR loci were identified across eleven tree peony plastomes. Dinucleotide repeat SSRs (97.12%) were most abundantly repeated for the AT motif (58.27%), followed by the TA motif (30.94%) and the TC motif (7.91%). Twenty-one primer pairs were developed, and amplification tests were conducted for nine tree peony individuals. Furthermore, 19 cpSSR markers were amplified on 60 tree peony accessions by a capillary electrophoresis test. Of 19 cpSSR markers, 12 showed polymorphism with different alleles ranging from 1.333 to 3.000. The Shannon’s information index and polymorphism information content values ranged from 0.038 to 0.887 (mean 0.432) and 0.032 to 0.589 (mean 0.268), respectively. The diversity levels for twelve loci ranged from 0.016 (at loci cpSSR-8 and cpSSR-26) to 0.543 (at locus cpSSR-15), averaging 0.268 for all loci. A total of 14 haplotypes (23.33%) were detected in the three populations. The haplotypic richness ranged from 0.949 to 1.751, with a mean of 1.233 per population. The genetic relationship suggested by the neighbor-joining-based dendrogram divided the genotypes into two clusters. The Jiangnan population was allotted to Cluster II, and the other two populations were distributed into both branches. These newly developed cpSSRs can be utilized for future breeding programs, population genetics investigations, unraveling the genetic relationships between related species, and germplasm management

Prevalence and associated factors of frailty in patients with chronic kidney disease:a cross-sectional analysis of PEAKING study

Aim: Frailty is common and is reported to be associated with adverse outcomes in patients with chronic diseases in Western countries. However, the prevalence of frailty remains unclear in individuals with chronic kidney disease (CKD) in China. We examined the prevalence of frailty and factors associated with frailty in patients with CKD.Methods: This was a cross-sectional analysis of 177 adult patients (mean age 54 ± 15 years, 52% men) with CKD from the open cohort entitled Physical Evaluation and Adverse outcomes for patients with chronic Kidney disease IN Guangdong (PEAKING). Frailty at baseline were assessed by FRAIL scale which included five items: fatigue, resistance, ambulation, illnesses, and loss of weight. Potential risk factors of frailty including age, sex, body mass index, and daily step counts recorded by ActiGraph GT3X + accelerometer were analyzed by multivariate logistic regression analysis.Results: The prevalence of prefrailty and frailty was 50.0% and 11.9% in patients with stages 4-5 CKD, 29.6% and 9.3% in stage 3, and 32.1% and 0 in stages 1-2. In the multivariate logistic regression analysis, an increase of 100 steps per day (OR = 0.95, 95% CI 0.91-0.99, P = 0.01) and an increase of 5 units eGFR (OR = 0.82, 95% CI 0.68-0.99, P = 0.045) were inversely associated with being frail; higher BMI was associated with a higher likelihood of being frail (OR = 1.52, 95% CI 1.11-2.06, P = 0.008) and prefrail (OR = 1.25, 95% CI 1.10-1.42, P = 0.001).Conclusion: Frailty and prefrailty were common in patients with advanced CKD. A lower number of steps per day, lower eGFR, and a higher BMI were associated with frailty in this population

License Plate Recognition Algorithm for Passenger Cars in Chinese Residential Areas

This paper presents a solution for the license plate recognition problem in residential community administrations in China. License plate images are pre-processed through gradation, middle value filters and edge detection. In the license plate localization module the number of edge points, the length of license plate area and the number of each line of edge points are used for localization. In the recognition module, the paper applies a statistical character method combined with a structure character method to obtain the characters. In addition, more models and template library for the characters which have less difference between each other are built. A character classifier is designed and a fuzzy recognition method is proposed based on the fuzzy decision-making method. Experiments show that the recognition accuracy rate is up to 92%