Hybrid model- and signal-based chatter detection in the milling process

Chatter causes machining instability and reduces productivity in the metal cutting process. It has negative effects on the surface finish, dimensional accuracy, tool life and machine life. Chatter identification is therefore necessary to control, prevent, or eliminate chatter and to determine the stable machining condition. Previous studies of chatter detection used either model-based or signal-based methods, and each of them has its drawback. Model-based methods use cutting dynamics to develop stability lobe diagram to predict the occurrence of chatter, but the off-line stability estimation couldn’t detect chatter in real time. Signal-based methods apply mostly Fourier analysis to the cutting or vibration signals to identify chatter, but they are heuristic methods and do not consider the cutting dynamics. In this study, the model-based and signal-based chatter detection methods were thoroughly investigated. As a result, a hybrid model- and signal-based chatter detection method was proposed. By analyzing the residual between the force measurement and the output of the cutting force model, milling chatter could be detected and identified efficiently during the milling process.

     

Performance comparison of parallel ILU preconditioners for the incompressible Navier-Stokes equations

Journal of Mechanical Science and Technology - In this paper, the performances of various ILU type parallel preconditioners for the finite element discretization of the incompressible Naiver-Stokes...     

Reduction of flow-induced noise in a household air purifier

Journal of Mechanical Science and Technology - In this study, we propose a design for a household air purifier that reduces the flow-induced noise caused by the impeller of the fan system. The...     

Electrochemical Characterization of Isolated Nitrogenase Cofactors from Azotobacter vinelandii

The nitrogenase cofactors are structurally and functionally unique in biological chemistry. Despite a substantial amount of spectroscopic characterization of protein-bound and isolated nitrogenase cofactors, electrochemical characterization of these cofactors and their related species is far from complete. Herein we present voltammetric studies of three isolated nitrogenase cofactor species: the iron–molybdenum cofactor (M-cluster), iron–vanadium cofactor (V-cluster), and a homologue to the iron–iron cofactor (L-cluster). We observe two reductive events in the redox profiles of all three cofactors. Of the three, the V-cluster is the most reducing. The reduction potentials of the isolated cofactors are significantly more negative than previously measured values within the molybdenum–iron and vanadium–iron proteins. The outcome of this study provides insight into the importance of the heterometal identity, the overall ligation of the cluster, and the impact of the protein scaffolds on the overall electronic structures of the cofactors.     

Evaluation of Phytochemical,Polyphenol Composition and Anti-corrosion Capacity of Cucumis anguria L. Leaf Extract on Metal Surface in Sulfuric Acid Medium

Protection of Metals and Physical Chemistry of Surfaces - Cucumis anguria L. (C. anguria L.) commonly known as Indian gherkin is originally from Africa, though now seen widely in southeast,...     

Tooth instance segmentation from cone-beam CT images through point-based detection and Gaussian disentanglement

Multimedia Tools and Applications - Individual tooth segmentation and identification from cone-beam computed tomography images are preoperative prerequisites for orthodontic treatments. Instance...     

Hydroelastic vibration of the bottom plate of the cylindrical tank coupled with sloshing

Journal of Mechanical Science and Technology - This study is concerned with the hydroelastic vibration of the flexible bottom plate of a cylindrical tank coupled with sloshing. The cylindrical tank...     

Outer Membrane Vesicle Production by Helicobacter pylori Represents an Approach for the Delivery of Virulence Factors CagA,VacA and UreA into Human Gastric Adenocarcinoma (AGS) Cells

Helicobacter pylori infection is the etiology of several gastric-related diseases including gastric cancer. Cytotoxin associated gene A (CagA), vacuolating cytotoxin A (VacA) and α-subunit of urease (UreA) are three major virulence factors of H. pylori, and each of them has a distinct entry pathway and pathogenic mechanism during bacterial infection. H. pylori can shed outer membrane vesicles (OMVs). Therefore, it would be interesting to explore the production kinetics of H. pylori OMVs and its connection with the entry of key virulence factors into host cells. Here, we isolated OMVs from H. pylori 26,695 strain and characterized their properties and interaction kinetics with human gastric adenocarcinoma (AGS) cells. We found that the generation of OMVs and the presence of CagA, VacA and UreA in OMVs were a lasting event throughout different phases of bacterial growth. H. pylori OMVs entered AGS cells mainly through macropinocytosis/phagocytosis. Furthermore, CagA, VacA and UreA could enter AGS cells via OMVs and the treatment with H. pylori OMVs would cause cell death. Comparison of H. pylori 26,695 and clinical strains suggested that the production and characteristics of OMVs are not only limited to laboratory strains commonly in use, but a general phenomenon to most H. pylori strains.     

Efficient exact k-flexible aggregate nearest neighbor search in road networks using the M-tree

The Journal of Supercomputing - This study proposes an efficient exact k-flexible aggregate nearest neighbor (k-FANN) search algorithm in road networks using the M-tree. The state-of-the-art...     

POPS: an off-peak precomputing scheme for privacy-preserving computing

Emerging privacy-preserving technologies help protect sensitive data during application executions. Recently, the secure two-party computing (TPC) scheme has demonstrated its potential, especially for the secure model inference of a deep learning application by protecting both the user input data and the model parameters. Nevertheless, existing TPC protocols incur excessive communications during the program execution, which lengthens the execution time. In this work, we propose the precomputing scheme, POPS, to address the problem, which is done by shifting the required communications from during the execution to the time prior to the execution. Particular, the multiplication triple generation is computed beforehand with POPS to remove the overhead at runtime. We have analyzed the TPC protocols to ensure that the precomputing scheme conforms the existing secure protocols. Our results show that POPS takes a step forward in the secure inference by delivering up to \(20\times \) and \(5\times \) speedups against the prior work for the microbenchmark and the convolutional neural network experiments, respectively.