Results 61 to 70 of about 6,147,181 (407)
FEBS Open Bio, EarlyView.Comparative analysis of chloroplast genomes from 14 genera of Thymelaeaceae revealed variation in gene content, ranging from 128 to 142 genes, primarily influenced by IR expansion/contraction events and pseudogenization of ndhF, ndhI, and ndhG. Two large inversions were detected within the large single‐copy region, including a synapomorphic inversion ...
Abdullah +8 more
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Chaotic Characteristics and the Application of SVM in the Tool Wear State Recognition
MATEC Web of Conferences, 2016 Metal cutting process is a nonlinear system to obtain the tool wear state and chaos theory are introduced tool wear and feature extraction of acoustic emission signal analysis and classification of tool wear state and wear prediction based on support ...
Guan Shan, Pang Hongyang, Kang Zhenxing
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An Influence of Parameters of Micro-electrical Discharge Machining on Wear of Tool Electrode
Archive of Mechanical Engineering, 2017 To achieve better precision of features generated using the micro-electrical discharge machining (micro-EDM), there is a necessity to minimize the wear of the tool electrode, because a change in the dimensions of the electrode is reflected directly or ...
Puthumana Govindan
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Lubricants, 2022 Tool wear behavior is mainly influenced by cutting parameters for a given tool–workpiece pair and cutting process. Rapid tool wear increases production costs and deteriorates machining quality in manufacturing industries.
Delin Liu, Zhanqiang Liu, Bing Wang
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SNUPN‐Related Muscular Dystrophy: Novel Phenotypic, Pathological and Functional Protein Insights
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective SNUPN‐related muscular dystrophy or LGMDR29 is a new entity that covers from a congenital or childhood onset pure muscular dystrophy to more complex phenotypes combining neurodevelopmental features, cataracts, or spinocerebellar ataxia. So far, 12 different variants have been described.
Nuria Muelas +18 more
wiley +1 more source
IEEE Access, 2021 Reliable and precise multi-step-ahead tool wear state prediction is significant to modern industries for maintaining part quality and reducing cost. This study proposes a Clustering Feature-based Recurrent Fuzzy Neural Network (CFRFNN) for tool wear ...
Jiachen Yao, Baochun Lu, Junli Zhang
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Hard turning with variable micro-geometry PcBN tools [PDF]
, 2008 Cataloged from PDF version of article.This paper presents investigations on hard turning with variable edge design PcBN inserts. Turning of hardened AISI 4340 steel with uniform and variable edge design PcBN inserts is conducted, forces and tool wear ...
Karpat, Y., Ozel, T., Srivastava, A.
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Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background Myasthenia gravis (MG) is a rare disorder characterized by fluctuating muscle weakness with potential life‐threatening crises. Timely interventions may be delayed by limited access to care and fragmented documentation. Our objective was to develop predictive algorithms for MG deterioration using multimodal telemedicine data ...
Maike Stein +7 more
wiley +1 more source
Havacılık ve Uzay Teknolojileri Dergisi, 2003 The main goal of this work is to study the influence of the tool failure mechanisms and on the tool life. Aiming to achieve this goal, several tool failure mechanisms are explained.
Ufuk Özdemir, Muzaffer Erten
doaj
Tool wear status recognition based on Mahalanobis distance
The Journal of Engineering, 2019 To improve the reliability of current signal monitoring tool wear status, a method based on Mahalanobis distance to identify tool wear status is proposed. First, the obtained current signal is analysed in time domain, frequency domain and wavelet domain,
Yiqian He, Min Huang, Weiwei Sun
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