Application of Machine Learning for Tool Condition Monitoring in Turning

The machining process is primarily used to remove material using cutting tools. Any variation in tool state affects the quality of a finished job and causes disturbances. So, a tool monitoring scheme (TMS) for categorization and supervision of failures has become the utmost priority. To respond, traditional TMS followed by the machine learning (ML) analysis is advocated in this paper. Classification in ML is supervised based learning method wherein the ML algorithm learn from the training data input fed to it and then employ this model to categorize the new datasets for precise prediction of a class and observation. In the current study, investigation on the single point cutting tool is carried out while turning a stainless steel (SS) workpeice on the manual lathe trainer. The vibrations developed during this activity are examined for failure-free and various failure states of a tool. The statistical modeling is then incorporated to trace vital signs from vibration signals. The multiple-binary-rule-based model for categorization is designed using the decision tree. Lastly, various tree-based algorithms are used for the categorization of tool conditions. The Random Forest offered the highest classification accuracy, i.e., 92.6%.

     

Quantum Key Distribution with Untrusted Detectors Accessible to an Eavesdropper

JETP Letters - A simple fundamental modification of quantum key distribution protocols has been proposed: it is not required to protect the results of avalanche detectors from an eavesdropper, but...     

Optimal Control of Nonlinear Fractional-Order Systems with Multiple Time-Varying Delays

Journal of Optimization Theory and Applications - This paper considers an optimal control problem governed by nonlinear fractional-order systems with multiple time-varying delays and subject to...     

Dynamic stability of a class of fractional-order nonlinear systems via fixed point theory

In this paper, the problem of the uniform stability for a class of fuzzy fractional-order genetic regulatory networks with random discrete delays, distributed delays, and parameter uncertainties is studied. Although there is a portion of literature on using fixed point theorems to study the stability of fractional neural networks, most of them required the fractional order to be in $\left(\frac{1}{2},1\right)$. However, the case of the fractional-order belonging to $(0,\frac{1}{2})$ has not been discussed. To solve it, this work proposes a novel idea of using fixed point theory to study the stability of fuzzy (0,1) order neural networks, the problem of the uniqueness of the solution of the considered genetic regulatory networks is resolved, and a novel sufficient condition to guarantee the uniform stability of above genetic regulatory networks is also derived. Eventually, an example is given to demonstrate that the obtained result is effective.     

Carbohydrate-based nanostructured catalysts: applications in organic transformations

The requirement of green and sustainable materials to prepare heterogeneous catalysts has intensified for practical reasons over the past few decades. Carbohydrates are possibly the most plentiful and renewable organic materials in nature with inimitable physiochemical properties, plausible low-cost and large-scale production, and sustainability features could be exploited in the generation of nanostructured heterogeneous catalysts. This review article outlines the organic transformations catalyzed by diverse carbohydrate-based nanostructured catalysts in greener and environmentally friendly processes. Selected examples are highlighted for a variety of organic reactions exploiting the proposed catalysts’ reactivity and reusability, and interactions with the intrinsic nature of the applied carbohydrate supports; advantages and speculated challenges of the introduced catalysts are deliberated as well.     

Intermetallic Compounds CsnMk (М = Na,K, Rb,Pt, Au,Hg, Te): Geometrical and Topological Analysis,Cluster Precursors,and Self-Assembly of Crystal Structures

Crystallography Reports - A geometrical and topological analysis has been performed, and self-assembly of the crystal structures of intermetallic compounds CsnMk (М = Na, K, Rb, Pt, Au, Hg,...     

X-ray Diffraction Study of Structural Changes in High-Strength Ceramics Based on Zirconium Oxide with Additions of Ytterbium and Neodymium Oxides after Hydrothermal Treatment

Crystallography Reports - A surface structural analysis of two ceramic samples of zirconium oxide (ZrO2) sintered at 1550°C, stabilized in the tetragonal form, before and after hydrothermal...     

BENDING OF THIN ELECTROMAGNETOELASTIC PLATES

Journal of Applied Mechanics and Technical Physics - Main correlations in the theory of bending of thin electromagnetoelastic plates are obtained, in which complex potentials are used. Exact...     

Filtration with Multiple Species of Particles

Transport in Porous Media - Membrane filtration of feed containing multiple species of particles is a common process in the industrial setting. In this work, we propose a model for filtration of a...     

Inverse central ordering for the Newton interpolation formula

Numerical Algorithms - An inverse central ordering of the nodes is proposed for the Newton interpolation formula. This ordering may improve the stability for certain distributions of nodes. For...