Object (computer science)

About: Object (computer science) is a research topic. Over the lifetime, 106024 publications have been published within this topic receiving 1360115 citations. The topic is also known as: obj & Rq.

Method and apparatus for maintaining the status of objects in computer networks using virtual state machines

Abstract: A network appliance for monitoring, diagnosing and documenting problems among a plurality of devices and processes (objects) coupled to a computer network utilizes periodic polling and collection of object-generated trap data to monitor the status of objects on the computer network. The status of a multitude of objects is maintained in memory utilizing virtual state machines which contain a small amount of persistent data but which are modeled after one of a plurality of finite state machines. The memory further maintains dependency data related to each object which identifies parent/child relationships with other objects at the same or different layers of the OSI network protocol model. A decision engine verifies through on-demand polling that a device is down. A root cause analysis module utilizes status and dependency data to locate the highest object in the parent/child relationship tree that is affected to determine the root cause of a problem. Once a problem has been verified, a “case” is opened and notification alerts may be sent out to one or more devices. A user interface allows all objects within the network to be displayed with their respective status and their respective parent/child dependency objects in various formats.

Apparatus and methods for converting an electronic mail to a postal mail at the receiving station

Abstract: A method of generating mail objects from email messages. The method is performed by a computer system having at least one database containing identifiers for senders of email messages, identifiers for corresponding recipients of mail objects, and address information for both the senders and recipients. The method is broadly comprised steps of three steps: (1) receiving an email message from a sender; (2) locating in the database an identifier for the sender and an identifier for a recipient specified in the email message; and (3) generating a mail object from the email message using the address information in the database for the sender and for the recipient.

ERNIE-ViL: Knowledge Enhanced Vision-Language Representations Through Scene Graph

Abstract: We propose a knowledge-enhanced approach, ERNIE-ViL, to learn joint representations of vision and language. ERNIE-ViL tries to construct the detailed semantic connections (objects, attributes of objects and relationships between objects in visual scenes) across vision and language, which are essential to vision-language cross-modal tasks. Incorporating knowledge from scene graphs, ERNIE-ViL constructs Scene Graph Prediction tasks, i.e., Object Prediction, Attribute Prediction and Relationship Prediction in the pre-training phase. More specifically, these prediction tasks are implemented by predicting nodes of different types in the scene graph parsed from the sentence. Thus, ERNIE-ViL can model the joint representation characterizing the alignments of the detailed semantics across vision and language. Pre-trained on two large image-text alignment datasets (Conceptual Captions and SBU), ERNIE-ViL learns better and more robust joint representations. It achieves state-of-the-art performance on 5 vision-language downstream tasks after fine-tuning ERNIE-ViL. Furthermore, it ranked the 1st place on the VCR leader-board with an absolute improvement of 3.7%.

A Neural Theory of Attentive Visual Search: Interactions of Boundary, Surface, Spatial, and Object Representations

Abstract: Visual search data are given a unified quantitative explanation by a model of how spatial maps in the parietal cortex and object recognition categories in the inferotemporal cortex deploy attentional resources as they reciprocally interact with visual representations in the prestriate cortex The model visual representations are organized into multiple boundary and surface representations Visual search in the model is initiated by organizing multiple items that lie within a given boundary or surface representation into a candidate search grouping These items are compared with object recognition categories to test for matches or mismatches Mismatches can trigger deeper searches and recursive selection of new groupings until a target object is identified The model provides an alternative to Feature Integration and Guided Search models

Object-oriented computer user interface

Abstract: A computer user interface includes a mechanism for graphically representing and displaying user-definable objects of multiple types. The object types that can be represented include data records, not limited to a particular kind of data, and agents. An agent processes information automatically on behalf of the user. Another mechanism allows a user to define objects, for example by using a template. These two mechanisms act together to allow each object to be displayed to the user and acted upon by the user in a uniform way regardless of type. For example, templates for defining objects allow a specification to be input by a user defining processing that can be performed by an agent.