Friction Compensation of an $XY$ Feed Table Using Friction-Model-Based Feedforward and an Inverse-Model-Based Disturbance Observer

Uncompensated friction forces compromise the positioning and tracking accuracy of motion systems. A unique tracking error known as quadrant glitch is the result of complex nonlinear friction behavior at motion reversal or near-zero velocity. Linear-feedback control strategies such as PID, cascade P/PI, or state-feedback control have to be extended with model- and nonmodel-based friction-compensation strategies to acquire sufficiently high path and tracking accuracy. This paper analyzes and validates experimentally three different friction-compensation strategies for a linear motor-based xy feed drive of a high-speed milling machine: (1) friction-model-based feedforward; (2) an inverse-model-based disturbance observer; and (3) the combination of both techniques. The friction models considered are as follows: a simple static-friction model and the recently developed generalized Maxwell-slip (GMS) model. GMS friction-model-based feedforward combined with disturbance observer almost completely eliminates the radial tracking error and quadrant glitches.     

Use of Zebrafish Embryo Assay to Evaluate Toxicity and Safety of Bioreactor-Grown Exopolysaccharides and Endopolysaccharides from European Ganoderma applanatum Mycelium for Future Aquaculture Applications

Natural mycelial exopolysaccharide (EPS) and endopolysaccharide (ENS) extracted from bioreactor-cultivated European Ganoderma applanatum mushrooms are of potential high commercial value for both food and adjacent biopharmaceutical industries. In order to evaluate their potential toxicity for aquaculture application, both EPS (0.01–10 mg/mL) and ENS (0.01–10 mg/mL) extracts were tested for Zebrafish Embryo Toxicity (ZFET); early development effects on Zebrafish Embryos (ZE) were also analyzed between 24 and 120 h post-fertilization (HPF). Both EPS and ENS are considered non-toxic with LC₅₀ of 1.41 mg/mL and 0.87 mg/mL respectively. Both EPS and ENS did not delay hatching and teratogenic defect towards ZE with <1.0 mg/mL, respectively. No significant changes in the ZE heart rate were detected following treatment with the two compounds tested (EPS: 0.01–10 mg/mL: 176.44 ± 0.77 beats/min and ENS: 0.01–10 mg/mL: 148.44 ± 17.75 beats/min) compared to normal ZE (120–180 beats/min). These initial findings support future pre-clinical trials in adult fish models with view to safely using EPS and ENS as potential feed supplements for supplements for development of the aquaculture industry.     

Modified 2 Satisfiability Reverse Analysis Method via Logical PermutationOperator

The effectiveness of the logic mining approach is strongly correlated to the quality of the induced logical representation that represent the behaviour of the data. Specifically, the optimum induced logical representation indicates the capability of the logic mining approach in generalizing the real datasets of different variants and dimensions. The main issues with the logic extracted by the standard logic mining techniques are lack of interpretability and the weakness in terms of the structural and arrangement of the 2 Satisfiability logic causing lower accuracy. To address the issues, the logical permutation serves as an alternative mechanism that can enhance the probability of the 2 Satisfiability logical rule becoming true by utilizingthedefinitive finite arrangement of attributes. This work aims to examine and analyze the significant effect of logical permutation on the performance of data extraction ability of the logic mining approach incorporated with the recurrent discrete Hopfield Neural Network. Based on the theory, the effect of permutation and associate memories in recurrent Hopfield Neural Network will potentially improve the accuracy of the existing logic mining approach. To validate the impact of the logical permutation on the retrieval phase of the logic mining model, the proposed work is experimentally tested on a different class of the benchmark real datasets ranging from the multivariate and time-series datasets. The experimental results show the significant improvement in the proposed logical permutation-based logic mining according to the domains such as compatibility, accuracy, and competitiveness as opposed to the plethora of standard 2 Satisfiability Reverse Analysis methods.     

In vitro antioxidant and in vivo xanthine oxidase inhibitory activities of Pandanus amaryllifolius in potassium oxonate‐induced hyperuricemic rats

Xanthine oxidase (XO) plays an important role in the regulation of uric acid and prevents it from being overproduced as in hyperuricemia disease. The combined effects of antioxidant and xanthine oxidase inhibitor would become a promising approach for hyperuricemia treatment. In this research, the antioxidant and xanthine oxidase inhibitory activities of Pandanus amaryllifolius leaf were evaluated. The leaf water extract (PA‐W) showed highest total phenols, and petroleum ether extract (PA‐PE) showed highest total flavonoids contents. The antioxidant activity of DPPH, metal chelating and hydrogen peroxide was highest in PA‐W extract. The treatment of PA‐W extract at 1000 mg kg^?1 body weight in potassium oxonate‐induced hyperuricemic rats showed significant (P < 0.001) decrease in serum uric acid level by 85% and XO activity by 64%, respectively, as compared to the hyperuricemic rats. In conclusion, the P. amaryllifolius possess the dual effect of antioxidant and XO inhibition as potential therapeutic agents in the hyperuricemia treatment.     

Decomposition of interacting machining features based on the reasoning on the design features

Currently, design and machining features diverge in meaning, even when they are interpreting the same object. This divergence of feature interpretation provides a venue for research work to reduce the complexity that arises in recognizing interacting machining features. Therefore, this paper demonstrates the recognition of design features with the aim to eventually decompose the interacting machining features. Loop driving recognition links the CAD data directly to the features to be recognized. The first step is to recognize the design features from B-Reps part. Then geometrical reasoning on these design features is employed to convert the design features to its respective machining features. The process of conversion is in fact the process of decomposing the interacting machining features without having to visit the B-Reps data again. The system takes into account the nesting of the design features that causes more interacting machining features to be decomposed. Finally, output data of both design and machining features are then displayed.     

Survey of Robotics in Education,Taxonomy, Applications,and Platforms during COVID-19

The coronavirus disease 2019 (COVID-19) is characterized as a disease caused by a novel coronavirus known as severe acute respiratory coronavirus syndrome 2 (SARS-CoV-2; formerly known as 2019-nCoV). In December 2019, COVID-19 began to appear in a few countries. By the beginning of 2020, it had spread to most countries across the world. This is when education challenges began to arise. The COVID-19 crisis led to the closure of thousands of schools and universities all over the world. Such a situation requires reliance on e-learning and robotics education for students to continue their studies to avoid the mingling between people and students. In relation to this alternative learning solution, the present study was conducted. A systematic literature review on educational robotics (ER) keywords between 2015–2020 was carried out for the purpose to review a total of 2253 articles from the selected sources; Scopus (452), Taylor & Francis (311), Science Direct (427), IEEE Xplore (221), and Web of Science (842). This review procedure was labelled as Taxonomy 1. After filtering Taxonomy 1, it was found that 98 scientific articles formed the so-called Taxonomy II that was categorized into six categories: (i) Robotics concepts, (ii) Device, (iii) Robotic applications, (iv) Manufacturing robots, (v) Robotics analysis, and (vi) Education/taxonomy. For this study, only 35 articles in this specific field were selected, of which were then assigned into three categories: (i) Application, (ii) Platform, and (iii) Educational. The results show that the application category carries 17.4%, platform 20%, and education 22.85%. This study serves as the application platform to help students, academics, and researchers.     

Vibration impact acoustic emission technique for identification and analysis of defects in carbon steel tubes: Part B Cluster analysis

Current steel tubes inspection techniques are invasive, and the interpretation and evaluation of inspection results are manually done by skilled personnel. Part A of this work details the methodology involved in the newly developed non-invasive, non-destructive tube inspection technique based on the integration of vibration impact (VI) and acoustic emission (AE) systems known as the vibration impact acoustic emission (VIAE) technique. AE signals have been introduced into a series of ASTM A179 seamless steel tubes using the impact hammer. Specifically, a good steel tube as the reference tube and four steel tubes with through-hole artificial defect at different locations were used in this study. The AEs propagation was captured using a high frequency sensor of AE systems. The present study explores the cluster analysis approach based on autoregressive (AR) coefficients to automatically interpret the AE signals. The results from the cluster analysis were graphically illustrated using a dendrogram that demonstrated the arrangement of the natural clusters of AE signals. The AR algorithm appears to be the more effective method in classifying the AE signals into natural groups. This approach has successfully classified AE signals for quick and confident interpretation of defects in carbon steel tubes.     

Physico-mechanical properties of particleboard made from heat-treated rubberwood particles

Physico-mechanical properties of particleboard fabricated from heat-treated rubberwood particles were investigated. Reduction in water absorption and mass loss were observed in heat-treated rubberwood particles, and it was associated with the properties of particleboard. The density and moisture content of the particleboard decreased with increasing treatment temperature and time. Heat treatment of particles improved the dimensional stability of the particleboard, but the mechanical properties were adversely affected.