Abstract: The present invention relates to the provision of an automated system and a computer-implemented method for detecting a disease such as nasopharyngeal cancer (NPC) based upon the use of either a Fuzzy Inference (FI) system or a deep learning-fuzzy inference (DeLFI) hybrid model to analyse immunofluorescence assay (IFA) images. For NPC detection, the system and method of the invention would distinguish between Epstein Barr Virus (EBV) Early Antigen (EA) positive and negative cells, and identify cellular patterns which are indicative of NPC. The DeLFI hybrid model requires less human evaluation and thereby has the potential to improve the scalability and accuracy of NPC detection.

Abstract: A trip planner is provided for creating, modifying, categorizing, and sharing online trip plans. A trip plan includes a list of items such as hotels, restaurants, and tourist attractions selected from a travel guide or provided by a user. An item can have a street address for positioning the item on a map, an image and description of the item, and other metadata assigned by the user, such as tags and notes. The trip planner can generate an itinerary listing the items, and a corresponding map showing the locations of the items. A trip plan can be shared with other users, who can locate the trip plan by searching for the tags or other metadata.

Abstract: A trip planner is provided for creating, modifying, categorizing, and sharing online trip plans. A trip plan includes a list of items such as hotels, restaurants, and tourist attractions selected from a travel guide or provided by a user. An item can have a street address for positioning the item on a map, an image and description of the item, and other metadata assigned by the user, such as tags and notes. The trip planner can generate an itinerary listing the items, and a corresponding map showing the locations of the items. A trip plan can be shared with other users, who can locate the trip plan by searching for the tags or other metadata.