Patents by Inventor Ozlem Aslan

Ozlem Aslan has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20210387911
    Abstract: A fiber for concrete reinforcement is provided including 85 wt. % to 98 wt. % of a polypropylene, 2 wt. % to 10 wt. % of a polycarbonate, and up to 5 wt. % of a compatibilizer, wherein the fiber has a tensile strength of at least 600 MPa and a modulus of at least 6 GPa.
    Type: Application
    Filed: August 29, 2019
    Publication date: December 16, 2021
    Applicant: ADFIL N.V.
    Inventors: Ives SWENNEN, Özlem ASLAN, Jeroen SMET, Lien VAN DER SCHUEREN, Luc RUYS
  • Publication number: 20210332504
    Abstract: An article includes continuous filaments of 85 wt. % to 98 wt. % of a polypropylene and 2 wt. % to 10 wt. % of a polycarbonate. The continuous filament has a tensile strength of at least 650 MPa and/or a modulus of at least 10 GPa, and can advantageously be used for example in multifilament yarns, in ropes, in woven fabrics, in nonwovens, in strapping tapes and in straight warp knitted fabrics.
    Type: Application
    Filed: April 23, 2021
    Publication date: October 28, 2021
    Applicant: ADFIL NV.
    Inventors: Ives SWENNEN, Özlem ASLAN, Jeroen SMET, Lien VAN DER SCHUEREN, Luc RUYS
  • Publication number: 20170132528
    Abstract: Multiple machine learning models can be jointly trained in parallel. An example process for jointly training multiple machine learning models includes providing a set of machine learning models that are to learn a respective task, the set of machine learning models including a first machine learning model and a second machine learning model. The process can initiate training of the first machine learning model to learn a task using training data. During the training of the first machine learning model, information can be passed between the first machine learning model and the second machine learning model. Such passing of information (or “transfer of knowledge”) between the machine learning models can be accomplished via the formulation, and optimization, of an objective function that comprises model parameters that are based on the multiple machine learning models in the set.
    Type: Application
    Filed: June 28, 2016
    Publication date: May 11, 2017
    Inventors: Ozlem Aslan, Rich Caruana, Matthew R. Richardson, Abdelrahman Mohamed, Matthai Philipose, Krzysztof Geras, Gregor Urban, Shengjie Wang