Zobrazeno 1 - 10
of 47
pro vyhledávání: '"Wael M. Mohammed"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-19 (2024)
Abstract The positron annihilation lifetime (PAL) spectroscopy characteristics of ethylene-propylene-diene monomer rubber (EPDM) composites reinforced with treated wheat husk fibers (WHFs) were investigated for the first time. PAL spectroscopy is emp
Externí odkaz:
https://doaj.org/article/dcbf696422194a30bb7aa49b7677f6ef
Autor:
Saigopal Vasudevan, Mohamed Lamine Mekhalfi, Carlos Blanes, Michela Lecca, Fabio Poiesi, Paul Ian Chippendale, Pablo Malvido Fresnillo, Wael M. Mohammed, Jose L. Martinez Lastra
Publikováno v:
IEEE Access, Vol 12, Pp 152579-152613 (2024)
Vision and Robotic technologies are progressively becoming ubiquitous for automating and digitizing quality control in the food industry. This paper examines the crucial role of advanced automation technologies, including versatile or dedicated robot
Externí odkaz:
https://doaj.org/article/2227ba933c0848ba94d36bc2a326614e
Autor:
E. E. Abdel-Hady, Ahmed Gamal, Hany Hamdy, Mohamed Shaban, M. O. Abdel-Hamed, Mahmoud A. Mohammed, Wael M. Mohammed
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-16 (2023)
Abstract In this work, prepared nanoparticle samples of Ni1-xCrx with a fixed ratio of platinum (3%) were synthesized and loaded onto carbon nanofibers, which were produced by an electrospinning technique and carbonized at 900 °C for 7 h in an argon
Externí odkaz:
https://doaj.org/article/ff2dd87667b145c6b4aa7fa221441ff9
Publikováno v:
Data in Brief, Vol 48, Iss , Pp 109160- (2023)
Machine learning (ML) techniques are widely adopted in manufacturing systems for discovering valuable patterns in shopfloor data. In this regard, machine learning models learn patterns in data to optimize process parameters, forecast equipment deteri
Externí odkaz:
https://doaj.org/article/bde2ded882e64b12bfe88cf102bb1f76
Autor:
Wael M. Mohammed, Igor V. Yanilkin, Amir I. Gumarov, Airat G. Kiiamov, Roman V. Yusupov, Lenar R. Tagirov
Publikováno v:
Beilstein Journal of Nanotechnology, Vol 11, Iss 1, Pp 807-813 (2020)
Single-layer vanadium nitride (VN) and bilayer Pd0.96Fe0.04/VN and VN/Pd0.92Fe0.08 thin-film heterostructures for possible spintronics applications were synthesized on (001)-oriented single-crystalline magnesium oxide (MgO) substrates utilizing a fou
Externí odkaz:
https://doaj.org/article/46f8cb2cb83d4cb48b09c3f31e862ae8
Publikováno v:
Applied Sciences, Vol 13, Iss 3, p 1637 (2023)
In recent years, Industry 4.0 has provided many tools to replicate, monitor, and control physical systems. The purpose is to connect production assets to build cyber-physical systems that ensure the safety, quality, and efficiency of production proce
Externí odkaz:
https://doaj.org/article/57d538a7836b48239c1e30e1580d5d1a
Publikováno v:
Polymers, Vol 15, Iss 1, p 107 (2022)
A casting technique was used to prepare poly(vinyl alcohol) (PVA) blend polymers with different concentrations of Nylon-6,6 to increase the free-volume size and control the ionic conductivity of the blended polymers. The thermal activation energy for
Externí odkaz:
https://doaj.org/article/4e73a324fa2042758871c96c22cd9b59
Autor:
Samu Rautiainen, Matteo Pantano, Konstantinos Traganos, Seyedamir Ahmadi, José Saenz, Wael M. Mohammed, Jose L. Martinez Lastra
Publikováno v:
Machines, Vol 10, Iss 10, p 957 (2022)
Human–robot collaboration (HRC) is one of the key aspects of Industry 4.0 (I4.0) and requires intuitive modalities for humans to communicate seamlessly with robots, such as speech, touch, or bodily gestures. However, utilizing these modalities is u
Externí odkaz:
https://doaj.org/article/a0c90c66cfb14494a579c7e843cd5bbd
Publikováno v:
Machines, Vol 10, Iss 10, p 861 (2022)
The rapid emerging technologies in various fields permitted the creation of simulation tools. These tools are designed to replicate physical systems in order to provide faster, cheaper and more detailed illustrative analysis of the physical system. I
Externí odkaz:
https://doaj.org/article/e3210594861344b7afd29af73a775af1
Energy-Based Prognostics for Gradual Loss of Conveyor Belt Tension in Discrete Manufacturing Systems
Publikováno v:
Energies, Vol 15, Iss 13, p 4705 (2022)
This paper presents a data-driven approach for the prognosis of the gradual behavioural deterioration of conveyor belts used for the transportation of pallets between processing workstations of discrete manufacturing systems. The approach relies on t
Externí odkaz:
https://doaj.org/article/e09d1959680c4627b294d65c26e8825f