TRAINING CLASSES SEMINARS RELATING

Brand Owner Address Description
GLENCOREXSTRATA Glencore International AG Baarermattstrasse 3 CH-6340 Baar Switzerland Training classes and seminars relating to electrolytic refining of raw materials;Treatment and transformation of mineral resources and other raw materials, namely, material transformation of the surface of industrial products during manufacture by application of thin film polyimide preparations, coatings and resins; oil and fuel refining services; information and professional consultancy in connection with electrolytic refining of raw materials;Transport and storage of goods; ship brokerage;Mining extraction; construction of structures for the production of natural gas, crude oil and raw materials; installation, assembly, maintenance and repair of apparatus, machines and tools for use in the treatment and transformation of raw materials, particularly minerals, natural gas and crude oil; information and professional consultancy in connection with electrolytic recovery of raw materials;Financing, financial analysis and consulting relating to finance, investments, securities brokerage; trading of financial instruments and commodities;Professional business consultancy and organization consultancy and business management; retail trade services in the field of extraction and transformation of raw materials, namely, arranging of contractual trade services with third parties;Services in the fields of agriculture, horticulture and forestry, namely, vermin extermination for agriculture, horticulture services, forest habitat restoration;Geological prospecting and exploration, particularly exploration of minerals and raw materials, oil prospecting and creation of analyses for oil-field exploitation;
 

Where the owner name is not linked, that owner no longer owns the brand

    
Technical Examples
  1. The present invention recites a method and computer program product for identifying one or more new pattern classes and incorporating the classes into a pattern recognition classifier as output classes. A plurality of input patterns determined not to be associated with any of a set of at least one represented output class by a pattern recognition classifier are rejected. The rejected pattern samples are then grouped into clusters according to the similarities between the pattern samples. Clusters that represent new pattern classes are identified via independent review. The classifier is then retrained to include the new pattern classes as output classes.