TRAINING SEMINARS FEATURING INFORMATION ON

Brand Owner (click to sort) Address Description
SHIFTWORK: HOW TO COPE BEHAVIORAL SCIENCE TECHNOLOGY, INC. Legal Department 1000 Town Center Dr., Suite 600 Oxnard CA 93036 Training seminars featuring information on problems associated with evening, night and early morning work schedules and related employee training methods;Pre-recorded videotapes, sold separately, or as a unit with books and booklets, featuring information on problems associated with evening, night and early morning work schedules and related employee training methods;Books and booklets, sold separately or as a unit with pre-recorded videotapes, featuring information on problems associated with evening, night and early morning work schedules and related employee training methods;
SHIFTWORK: HOW TO COPE ROUND-THE-CLOCK RESOURCES, INC. 2 PORTLAND FISH PIER Suite 203 PORTLAND ME 04101 Training seminars featuring information on problems associated with evening, night and early morning work schedules and related employee training methods;Pre-recorded videotapes, sold separately, or as a unit with books and booklets, featuring information on problems associated with evening, night and early morning work schedules and related employee training methods;Books and booklets, sold separately or as a unit with pre-recorded videotapes, featuring information on problems associated with evening, night and early morning work schedules and related employee training methods;
 

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

    
Technical Examples
  1. The present invention enables estimation of desired parameters with less computation cost and with high precision by inputting first training vectors generated from observation patterns and second training vectors generated from estimation targets in order to learn the correlation between observation patterns as inputs and patterns of the estimation targets such that desired outputs are assumed from the inputs, calculating the auto-correlation information of the two training vectors, and cross-correlation information of an average vector, the first training vectors and second training vectors, and using the information, obtaining probable expectation values based on the Bayes theory of the estimation targets with respect to an input pattern.