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Automated inspection has proven to be the most effective approach to maintaining quality in industrial-scale manufacturing. This study employed the eye-in-hand architecture in conjunction with deep learning and convolutional neural networks to automate the detection of defects in forged aluminum rims for electric vehicles. RobotStudio software was used to simulate the environment and path trajectory for a camera installed on an ABB robot arm to capture 3D images of the rims. Four types of surface defects were examined: (1) dirt spots, (2) paint stains, (3) scratches, and (4) dents. Generative adversarial network (GAN) and deep convolutional generative adversarial networks (DCGAN) were used to generate additional images to expand the depth of the training dataset. We also developed a graphical user interface and software system to mark patterns associated with defects in the images. The defect detection algorithm based on YOLO algorithms made it possible to obtain results more quickly and with higher mean average precision (mAP) than that of existing methods. Experiment results demonstrated the accuracy and efficiency of the proposed system. Our developed system has been shown to be a helpful rim defective detection system for industrial applications.

High-precision trajectory control is considered as an important factor in the performance of industrial two-axis contour motion systems. This research presents an adaptive direct fuzzy cerebellar model articulation controller (CMAC) sliding mode control (DFCMACSMC) for the precise control of the industrial XY-axis motion system. The FCMAC was utilized to approximate an ideal controller, and the weights of FCMAC were on-line tuned by the derived adaptive law based on the Lyapunov criterion. With this derivation in mind, the asymptotic stability of the developed motion system could be guaranteed. The two-axis stage system was experimentally investigated using four contours, namely, circle, bowknot, heart, and star reference contours. The experimental results indicate that the proposed DFCMACSMC method achieved the improved tracking capability, and so reveal that the DFCMACSMC scheme outperformed other schemes of the model uncertainties and cross-coupling interference.

Background/Purpose: Respiratory infections caused by human adenoviruses (HAdV) are worldwide, and have significantly increased recently in Taiwan. This study aimed to clarify the molecular epidemiology and risk factors of HAdV severe infections and pneumonia among Taiwanese children. Methods: Patients with HAdV infections and hospitalized in a medical center between 2009 and 2013 were divided into severe or nonsevere HAdV infections based on whether or not they received intensive care. HAdV pneumonia was identified for comparison. The HAdV genotype was determined by sequencing the partial hexon and fiber genes. The nucleotide sequences were compared by phylogenetic analysis. Results: The 176 patients (97 boys, 79 girls) had a median age of 3.7 years. The HAdV infections circulated year-round. HAdV B3 (54.5%) was the most common genotype, followed by HAdV C2 (21%), HAdV E4 (8%), and HAdV B7 (6.8%). Thirty-two patients needed intensive care. In multivariate analysis, the risk factors for severe HAdV infections were underlying neurologic diseases [odds ratio (OR): 164.9; p

Respiratory syncytial virus (RSV) circulates year round in Taiwan. A novel six consecutive monthly doses of palivizumab for RSV prevention protocol has been approved for high risk preterm infants since December 2010. This study aimed to determine the clinical effectiveness and safety of this novel protocol for the prevention of RSV infection.From April 2011 to March 2013, we enrolled infants born at ≤28 weeks gestation and infants born at ≤35 weeks gestation with chronic lung disease (CLD) who received palivizumab prophylaxis as study group and followed up for 12 months. Historic control, those who were born and followed up between July 2000 and June 2008, were retrieved for propensity score matching. Primary endpoint was RSV-related hospitalization, and secondary endpoints included the length of hospital stay and intensive care unit (ICU) care.We enrolled 127 infants (108 infants born at ≤28 weeks and 19 infants born at 29-35 weeks with CLD). They completed 6-dose palivizumab as scheduled. Among the study group, the RSV-related hospitalizations were 2 (1.6%) within 6 months and 5 (3.9%) within 12 months after discharge. We matched 127 infants in the control group with 127 infants in the study group by propensity score matching. The reduction of RSV-related hospitalization rates were 86% (10.2% vs 1.6%, p = 0.002) within 6 months after discharge and 78% (15.7% vs 3.9%, p = 0.004) within 12 months after discharge. Compared to the control group, the rate of ICU care significantly decreased from 7.1% to 0.8% (p = 0.024) within 6 months after discharge and from 7.9% to 0.8% (p = 0.014) within 12 months after discharge. Adverse events were recorded in 6.4% injections.Six monthly intramuscular administration of palivizumab is effective for prevention of RSV hospitalization in regions with no single seasonal peak of RSV infection such as Taiwan.

BACKGROUND AND AIMS: The glycoprotein (G protein) and fusion protein (F protein) of respiratory syncytial virus (RSV) both show genetic variability, but few studies have examined the F protein gene. This study aimed to characterize the molecular epidemiology and phylodynamics of the F protein gene in clinical RSV strains isolated in northern Taiwan from 2000-2011. METHODS: RSV isolates from children presenting with acute respiratory symptoms between July 2000 and June 2011 were typed based on F protein gene sequences. Phylogeny construction and evaluation were performed using the neighbor-joining (NJ) and maximum likelihood (ML) methods. Phylodynamic patterns in RSV F protein genes were analyzed using the Bayesian Markov Chain Monte Carlo framework. Selection pressure on the F protein gene was detected using the Datamonkey website interface. RESULTS: From a total of 325 clinical RSV strains studied, phylogenetic analysis showed that 83 subgroup A strains (RSV-A) could be further divided into three clusters, whereas 58 subgroup B strains (RSV-B) had no significant clustering. Three amino acids were observed to differ between RSV-A and -B (positions 111, 113, and 114) in CTL HLA-B*57- and HLA-A*01-restricted epitopes. One positive selection site was observed in RSV-B, while none was observed in RSV-A. The evolution rate of the virus had very little change before 2000, then slowed down between 2000 and 2005, and evolved significantly faster after 2005. The dominant subtypes of RSV-A in each epidemic were replaced by different subtypes in the subsequent epidemic. CONCLUSIONS: Before 2004, RSV-A infections were involved in several small epidemics and only very limited numbers of strains evolved and re-emerged in subsequent years. After 2005, the circulating RSV-A strains were different from those of the previous years and continued evolving through 2010. Phylodynamic pattern showed the evolutionary divergence of RSV increased significantly in the recent 5 years in northern Taiwan.

Electromagnets are commonly used as support for machine components and parts in magnetic bearing systems (MBSs). Compared with conventional mechanical bearings, the magnetic bearings have less noise, friction, and vibration, but the magnetic force has a highly nonlinear relationship with the control current and the air gap. This research presents a dynamic sliding mode backstepping control (DSMBC) designed to track the height position of modeless vertical MBS. Because MBS is nonlinear with model uncertainty, the design of estimator should be able to solve the lumped uncertainty. The proposed DSMBC controller can not only stabilize the nonlinear system under mismatched uncertainties, but also provide smooth control effort. The Lyapunov stability criterion and adaptive laws are derived to guarantee the convergence. The adaptive scheme that may be used to adjust the parameter vector is obtained, so the asymptotic stability of the developed system can be guaranteed. The backstepping algorithm is used to design the control system, and the stability and robustness of the MBS system are evaluated. Two position trajectories are considered to evaluate the proposed method. The experimental results show that the DSMBC method can improve the root mean square error (RMSE) by 29.94% compared with the traditional adaptive backstepping controller method under different position tracking conditions. [ABSTRACT FROM AUTHOR]