Abstract:
In some examples, a computing device may be configured to simulate the deduction process of human mind by generating new data based on existing data and newly received data that is semantically relevant to the existing data.
Abstract:
In some examples, a computing device may be configured to simulate the deduction process of human mind by generating new data based on existing data and newly received data that is semantically relevant to the existing data.
Abstract:
Technologies to provide a secure data storage service in a cloud computing environment are generally disclosed. In some examples, a method comprises: partitioning a data resource into data particles, assigning logic groups to the data particles, assigning physical storage groups to the data particles, and/or storing each physical storage group at corresponding storage resource, receiving a request for the data resource, determining whether the request for the data resource is valid, and if the request is valid, transmitting the data particles of the data resource to the client. The method enables improved security for accessing data, and also improves the user experience in cloud computing environments.
Abstract:
In at least some examples, a control center, which provides remote driving assistance service, may be configured to receive traffic data from sensors and to identify an area of congested traffic, based on the received traffic data, within a predetermined range of the sensors. When the control center receives a request for the remote driving assistance service, from a vehicle within the predetermined range of the sensor, the control center may generate and transmit remote driving commands to the vehicle.
Abstract:
In an SM-MIMO wireless communication system, multiple transmitting antennae may be utilized to transmit wireless signals that carry signal sequences. A selection of the multiple transmitting antennae may be configured to represent a portion of the signal sequences so that channel state information (CSI) is not required at the receiving end of the SM-MIMO system.
Abstract:
To automatically sort multiple contacts of a user, in some examples, a system may be configured to monitor physiological signals, which reflect the emotional responses, of the user during communications between the user and his/her contacts and, further, to classify the contacts into multiple contact groups that may be sorted by the emotional responses of the user.
Abstract:
Technologies are generally described for methods and systems effective to monitor a data access activity. In some examples, a method may include receiving, by a processor, a destination concept. The processor may identify a set of concepts, which may include the destination concept and at least one related concept associated with the destination concept, in an ontology. The processor may generate a planned path, which may define a first data access order associated with access of at least one of the related concepts and the destination concept, using the set of concepts. The processor may generate a browsing path which may define a second data access order associated with the data access activity. The processor may compare the planned path with the browsing path. The processor may determine a deviation based on the comparison of the planned path and the browsing path. The processor may monitor the data access activity using the deviation.
Abstract:
Technologies are generally described for systems, devices and methods effective to process a composite task to be applied to an ontology. In some examples, the methods may include a processor receiving a composite task. The methods may include the processor transforming the composite task into a set of atomic tasks. The set of atomic tasks may include at least a first atomic task, a second atomic task, and a third atomic task. The methods may include the processor determining that the first atomic task is equivalent to the second atomic task based on the ontology. The methods may include the processor removing the second atomic task from the set of atomic tasks to generate a list of atomic tasks. The methods may include the processor applying the list of atomic tasks to the ontology.
Abstract:
Technologies are generally described for performing a reasoning task based on a set of semantic data. In some examples, a method and a system for process a scalable and dynamical set of semantic data are described. The method may include extracting, by an incremental reasoning system, a first set of relevant data from the set of semantic data based on the reasoning task. The method may include generating, by the incremental reasoning system, a first set of reasoning results by performing the reasoning task based on the first set of relevant data. The method may further include maintaining, by the incremental reasoning system, a relevance tree based on the first set of relevant data, wherein the incremental reasoning system is configured to extract a second set of relevant data from the set of semantic data based on the relevance tree and generate a second set of reasoning results based on the second set of relevant data.
Abstract:
Technologies are generally described to dynamically alter a game while a gamer is playing the game so as to affect the gaming experience experienced by the gamer. According to some examples, one or more physiological signals may be collected from a gamer as the gamer is playing a game. Based on the collected physiological signals, a Quality of Experience (QoE) vector that indicates the gaming experience of the gamer may be generated. The QoE vector may then be compared with a corresponding value of a predetermined QoE function, and the game may be altered based on the comparison.