Results 131 to 140 of about 4,450 (211)

Multi-Residue Determination and Risk Assessment of EU-Relevant Pharmaceuticals, Pesticides, and UV-Filters in Drinking Water. [PDF]

Pharmaceuticals (Basel)
Quintela IM, Gorito AM, Barbosa MO, Silva AMT, Ribeiro ARL.   +4 more
europepmc   +1 more source

Cutting Characteristics of Tapping with MQL system

Proceedings of JSPE Semestrial Meeting, 2005
Suda, Satoshi, Yokota, Hideo, Ibi, Masanori, Wakabayashi, Toshiaki   +3 more
openaire   +1 more source

Intelligent tool wear monitoring using XGBoost, SVR, and DNN models in NMQL environment. [PDF]

Sci Rep
Almomani O, Venkatesh B, Chaudhary SP, Mishra A, Sujai S, Juneja S, Pradhan P, Venkatesan SP, Bhowmik A, Tamene Y.   +9 more
europepmc   +1 more source

Solid-Phase Extraction Based on Captiva EMR-Lipid for Determination of 19 Aromatic Amine Antioxidants and Two <i>p</i>-Phenylenediamine Quinones in Human Plasma. [PDF]

Toxics
Liang B, Deng Q, Pan Z, Du B, Zeng L.
europepmc   +1 more source

First Application of QuEChERS-GC-MS Analysis for Polycyclic Aromatic Hydrocarbons Detection in Human Adipose Tissue. [PDF]

ACS Omega
Franchin A, Gregoris E, Sorarù L, Stocco E, Vindigni V, Porzionato A, Brunelli D, Macchi V, Gambaro A, Roman M.   +9 more
europepmc   +1 more source

Multi-objective optimization of surface roughness and MRR in AISI 316L stainless steel processed by MQL end milling using taguchi, RSM, ANN, and RFR methods. [PDF]

Sci Rep
Natesh CP, Siddeshkumar NG, Srinivasa G, Shivaramakrishna A, Pruthvi HM, Prasad CD, Shashidhara YM, Amarendra HJ, Tiwari A, Aden AA.   +9 more
europepmc   +1 more source

High Speed Grooving with Applying MQL

High Speed Grooving with Applying MQL
identifier:oai:t2r2.star.titech.ac.jp ...
openaire  

CBN cutting tool's surface roughness and tool wear prediction using JOA-optimized CNN-LSTM. [PDF]

Sci Rep
Khetre S, Bongale A, Kumar S.
europepmc   +1 more source

Effects of MQL on Drilling (1st Report)

Journal of the Japan Society for Precision Engineering, 2007
MAKIYAMA, Tadashi, SEKIYA, Katsuhiko, YAMADA, Keiji, YAMANE, Yasuo   +3 more
openaire   +1 more source

Prediction of cutting parameters and reduction of output parameters using machine learning in milling of Inconel 718 alloy. [PDF]

Sci Rep
Hamıd MWH, Özlü B, Ulaş HB, Demir H.
europepmc   +1 more source