Abstract: An access point may receive, associated with a computer, information that specifies a group of access points in a network, where the group includes the access point, a second access point and/or a third access point, and the group of access points are proximate to each other. Then, the access point may receive, associated with the computer, instructions for testing to conduct with the second access point or the second access point and the third access point, where the testing involves wired communication with the second access point, and wireless communication with the second access point or the third access point. Next, the access point may perform, based at least in part on the instructions, the testing with the second access point or the second access point and the third access point. Moreover, the access point may provide, addressed to the computer, test results associated with the access point.

Abstract: A computer system is described. During operation, the computer system may receive information specifying communication in a network. Then, the computer system may detect a network problem based at least in part on the information. Moreover, the computer system may automatically determine a remedial action based at least in part on the detected network problem and may automatically perform the determined remedial action. Alternatively, when the remedial action cannot be determined, the computer system may selectively collect additional information for a predefined time interval, e.g., using one or more edge electronic devices or one or more controllers in the network. Next, the computer system may diagnose the network problem and may compute a second remedial action based at least in part on the diagnosis of the network problem. After receiving approval the computer system may automatically perform the second remedial action when a subsequent instance of the network problem is detected.

Abstract: Documents from a set of related documents in a domain are processed to identify keywords associated with each document. The documents are then further processed to identify the documents that are the most similar to each other. For each document, some or all of the keywords that are associated with the similar documents, but not the document itself, are selected as semantic tags for the document. These semantic tags determined for a document represent novel or hidden concepts and contexts that may relate to the document, but that do not actually appear in the document. The documents are used to train a model that generate semantic tags for a document or for keywords associated with the document. The generated model can then be used for a variety of purposes such the creation of an index for a set of documents or for query expansion.

Abstract: An access point may receive, associated with a computer, information that specifies a group of access points in a network, where the group includes the access point, a second access point and/or a third access point, and the group of access points are proximate to each other. Then, the access point may receive, associated with the computer, instructions for testing to conduct with the second access point or the second access point and the third access point, where the testing involves wired communication with the second access point, and wireless communication with the second access point or the third access point. Next, the access point may perform, based at least in part on the instructions, the testing with the second access point or the second access point and the third access point. Moreover, the access point may provide, addressed to the computer, test results associated with the access point.

Abstract: It is known in the art to mitigate load on website servers by providing a virtual waiting room where visitors queue. However, in currently known approaches, queue management is “unfair”, in that a given visitor is not admitted to the website based on the order in which they arrived, but rather on a fixed probability each time they try to gain access. Disclosed herein are improved systems and methods for admitting visitors from the waiting room to the website. In embodiments, queued visitors may be admitted in accordance with a probability function that can be customized by an administrator to achieve queue fairness and/or can be adaptive to website load. The systems and methods disclosed herein are compatible with the RESTful nature of common web transactions.

Abstract: Documents from a set of related documents in a domain are processed to identify keywords associated with each document. The documents are then further processed to identify the documents that are the most similar to each other. For each document, some or all of the keywords that are associated with the similar documents, but not the document itself, are selected as semantic tags for the document. These semantic tags determined for a document represent novel or hidden concepts and contexts that may relate to the document, but that do not actually appear in the document. The documents are used to train a model that generate semantic tags for a document or for keywords associated with the document. The generated model can then be used for a variety of purposes such the creation of an index for a set of documents or for query expansion.

Abstract: Some embodiments are directed to a computer-assisted method for identifying a vehicle. The computer-assisted method can include: receiving, from a stationary sensor, sensor data representing a plurality of moving vehicles; receiving, from a particular vehicle, a communication including sensor data representing the particular vehicle, wherein the sensor data includes at least one of velocity and position for the particular vehicle; and identifying, from the sensor data representing a plurality of moving vehicles, a subset of the data representing the particular vehicle, wherein identifying the subset of data comprises analyzing the sensor data received from the stationary sensor in conjunction with the sensor data received from the particular vehicle.

Abstract: Some embodiments are directed to a computer-assisted method for identifying a vehicle. The computer-assisted method can include: receiving, from a stationary sensor, sensor data representing a plurality of moving vehicles; receiving, from a particular vehicle, a communication including sensor data representing the particular vehicle, wherein the sensor data includes at least one of velocity and position for the particular vehicle; and identifying, from the sensor data representing a plurality of moving vehicles, a subset of the data representing the particular vehicle, wherein identifying the subset of data comprises analyzing the sensor data received from the stationary sensor in conjunction with the sensor data received from the particular vehicle.