Inverse kinematic control algorithm for a welding robot - positioner system to trace a 3D complex curve

The welding robots equipped with rotary positioners have been widely used in several manufacturing industries. However, for welding a 3D complex weld seam, a great deal of points should be created to ensure the weld path smooth. This is a boring job and is a great challenge - rotary positioner system since the robot and the positioner must move simultaneously at the same time. Therefore, in this article, a new inverse kinematics solution is proposed to generate the movement codes for a six DOFs welding robot incorporated with a rotary positioner. In the algorithm, the kinematic error is minimized, and the actual welding error is controlled so that it is always less than an allowable limit. It has shown that the proposed algorithm is useful in developing an offline CAD-based programming tool for robots when welding complex 3D paths. The use of the algorithm increases the accuracy of the end-effector positioning and orientation, and reduces the time for teaching a welding robot - positioner system. Simulation scenarios demonstrate the potency of the suggested method

A Cosine Similarity-based Method for Out-of-Distribution Detection

The ability to detect OOD data is a crucial aspect of practical machine learning applications. In this work, we show that cosine similarity between the test feature and the typical ID feature is a good indicator of OOD data. We propose Class Typical Matching (CTM), a post hoc OOD detection algorithm that uses a cosine similarity scoring function. Extensive experiments on multiple benchmarks show that CTM outperforms existing post hoc OOD detection methods.Comment: Accepted paper at ICML 2023 Workshop on Spurious Correlations, Invariance, and Stability. 10 pages (4 main + appendix

Stimulation of shoot regeneration through leaf thin cell layer culture of Passiflora edulis Sims.

Passiflora edulis Sims. belonged to the genus Passiflora, is one of the important economic crops of the world as well as Vietnam. Nowadays, the commercial P. edulis is mainly propagated by seeds, cuttings and grafting; however, these methods still have some limitations such as genetic degradation and heterogeneity and the spread of pathogenic viruses. Micro-propagation has been used for clonal breeding and disease-free plant breeding, as well as providing a source of materials for Passiflora breeding. In this study, leaf explants of P. edulis Sims. (2.0-month-old) excised from the in vitro culture of ex vitro axillary buds cut longitudinally and transversally into thin cell layers (lTCL and tTCL) were used as plant materials to evaluate the shoot regeneration. In addition, the effects of explant age and lighting condition on shoot regeneration were also investigated. After 8 weeks of culture, the results showed that shoot regeneration rate (100%) and shoot multiplication coefficient (13.33) of the in vitro leaf-tTCL-4 were higher than those of other treatments and control. The shoot regeneration rate of P. edulis Sims. also varied with the change of explant age. The highest shoot regeneration rate (100%) was obtained from leaf explants of 1.5-month-old shoots after 8 weeks of culture. Moreover, the light (fluorescent lamps with photoperiod of 16 hours/day and lighting intensity of 40 - 45 μmol.m-2.s-1) improved not only morphogenesis rate, but also shoot regeneration rate (100%) of leaf explants after 8 weeks of culture. This study provided a novel method for rapid micro-propagation of P. edulis Sims

Class based Influence Functions for Error Detection

Influence functions (IFs) are a powerful tool for detecting anomalous examples in large scale datasets. However, they are unstable when applied to deep networks. In this paper, we provide an explanation for the instability of IFs and develop a solution to this problem. We show that IFs are unreliable when the two data points belong to two different classes. Our solution leverages class information to improve the stability of IFs. Extensive experiments show that our modification significantly improves the performance and stability of IFs while incurring no additional computational cost.Comment: Thang Nguyen-Duc, Hoang Thanh-Tung, and Quan Hung Tran are co-first authors of this paper. 12 pages, 12 figures. Accepted to ACL 202

Numerical simulation of all-normal dispersion visible to near-infrared supercontinuum generation in photonic crystal fibers with core filled chloroform

This study proposes a photonic crystal fiber made of fused silica glass, with the core infiltrated with chloroform as a new source of supercontinuum (SC) spectrum. We numerically study the guiding properties of the fiber structure in terms of characteristic dispersion and mode area of the fundamental mode. Based on the results, we optimized the structural geometries of the CHCl3-core photonic crystal fiber to support the broadband SC generations. The fiber structure with a lattice constant of 1 μm, a filling factor of 0.8, and the diameter of the first-ring air holes equaling 0.5 μm operates in all-normal dispersion. The SC with a broadened spectral bandwidth of 0.64 to 1.80 μm is formed by using a pump pulse with a wavelength of 850 nm, 120 fs duration, and power of 0.833 kW. That fiber would be a good candidate for all-fiber SC sources as cost-effective alternative to glass core fibers