Statistics

Total Visits

Visits
The capacity of statistical features extracted from multiple signals to predict tool wear in the drilling process5432

Total Visits Per Month

July 2019August 2019September 2019October 2019November 2019December 2019
The capacity of statistical features extracted from multiple signals to predict tool wear in the drilling process10030211513
January 2020February 2020March 2020April 2020May 2020June 2020
The capacity of statistical features extracted from multiple signals to predict tool wear in the drilling process57333414
July 2020August 2020September 2020October 2020November 2020December 2020
The capacity of statistical features extracted from multiple signals to predict tool wear in the drilling process1265498
January 2021February 2021March 2021April 2021May 2021June 2021
The capacity of statistical features extracted from multiple signals to predict tool wear in the drilling process541144
July 2021August 2021September 2021October 2021November 2021December 2021
The capacity of statistical features extracted from multiple signals to predict tool wear in the drilling process55322221
January 2022February 2022March 2022April 2022May 2022June 2022
The capacity of statistical features extracted from multiple signals to predict tool wear in the drilling process811101194
July 2022August 2022September 2022October 2022November 2022December 2022
The capacity of statistical features extracted from multiple signals to predict tool wear in the drilling process65316126
January 2023February 2023March 2023April 2023May 2023June 2023
The capacity of statistical features extracted from multiple signals to predict tool wear in the drilling process71528630
July 2023August 2023September 2023October 2023November 2023December 2023
The capacity of statistical features extracted from multiple signals to predict tool wear in the drilling process161000
January 2024February 2024March 2024April 2024May 2024June 2024
The capacity of statistical features extracted from multiple signals to predict tool wear in the drilling process8125271824
July 2024August 2024September 2024October 2024November 2024December 2024
The capacity of statistical features extracted from multiple signals to predict tool wear in the drilling process36431133231
January 2025February 2025March 2025April 2025May 2025June 2025
The capacity of statistical features extracted from multiple signals to predict tool wear in the drilling process811654269243442113
July 2025August 2025September 2025October 2025November 2025December 2025
The capacity of statistical features extracted from multiple signals to predict tool wear in the drilling process2227261127
January 2026February 2026March 2026
The capacity of statistical features extracted from multiple signals to predict tool wear in the drilling process6116

File downloads

Visits
The capacity of statistical features extracted from multiple signals to predict tool wear in the drilling process-POSTPRINT.pdf1620

Top Country Visits

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United States3945
Singapore668
Spain356
Vietnam172
China65
Finland35
Germany32
Japan26
India20
Australia9

Top Cities Visits

Visits
San Mateo3764
Singapore662
Vitoria-Gasteiz323
Ho Chi Minh City28
Boardman25
Ashburn19
Mumbai14
Shanghai14
Placentia9
Dublin8