Abstract: A resilient classifier for using with a rule-based system is provided. A system for classifying data for a rule-based system, may include: a system(s) for generating two training data sets, one data set is generated from input data while the second data set is generated from disturbed data; a system for merging the two training data sets; and a system for training a data classifier with the merged training data sets. As a result, the classification of data becomes more accurate, including when disturbed data is encountered.

Abstract: At least one embodiment of the invention addresses the problem of accidental user operation (e.g., dialing) of a mobile communication device such as a mobile telephone. In this regard, embodiments of the invention provide a proactive solution for preventing unintended operation of a mobile device based on various types of input data of the device, most notably sensory data.

Abstract: Systems and methods are provided for building and implementing ontology-based information resources. More specifically, multi-user collaborative, semi-automatic systems and methods are provided for constructing ontology-based information resources that are shared by a community of users, wherein ontology categories evolve over time based on categorization rules that are specified by the community of users as well as categorization rules that are automatically learned from knowledge obtained as a result of multi-user interactions and categorization decisions.

Abstract: The invention addresses the disadvantage of automated vehicle traffic management systems by providing a solution for predicting and avoiding traffic congestion before the congestion is experienced. The invention includes a decentralized mechanism for predicting congestion. An exemplary embodiment of the invention uses a system of sensors to determine current traffic flow; the sensors communicate their state to a network of servers and then an algorithm is applied to the collected data to predict traffic congestion; upon detection of congestion, signals are communicated to the system controllers to prevent the traffic congestion.

Abstract: A resilient classifier for using with a rule-based system is provided. A system for classifying data for a rule-based system, may include: a system(s) for generating two training data sets, one data set is generated from input data while the second data set is generated from disturbed data; a system for merging the two training data sets; and a system for training a data classifier with the merged training data sets. As a result, the classification of data becomes more accurate, including when disturbed data is encountered.

Abstract: Systems and methods for adaptive signal sampling and sample quantization for resource-constrained stream processing. Exemplary embodiments include a signal sampling and signal quantization method for a data stream from a ECG sensor into a pervasive device, the method including adaptively sampling the data stream, compressing data samples from the data stream, reducing the number of samples via quantization, defining a utility function for signal reconstruction, and formulating optimization on the reconstructed signal that is jointly sampled and quantized.

Abstract: The invention addresses the disadvantage of automated vehicle traffic management systems by providing a solution for predicting and avoiding traffic congestion before the congestion is experienced. The invention includes a decentralized mechanism for predicting congestion. An exemplary embodiment of the invention uses a system of sensors to determine current traffic flow; the sensors communicate their state to a network of servers and then an algorithm is applied to the collected data to predict traffic congestion; upon detection of congestion, signals are communicated to the system controllers to prevent the traffic congestion.

Abstract: The invention addresses the disadvantage of automated vehicle traffic management systems by providing a solution for predicting and avoiding traffic congestion before the congestion is experienced. The invention includes a decentralized mechanism for predicting congestion. An exemplary embodiment of the invention uses a system of sensors to determine current traffic flow; the sensors communicate their state to a network of servers and then an algorithm is applied to the collected data to predict traffic congestion; upon detection of congestion, signals are communicated to the system controllers to prevent the traffic congestion.

Abstract: A method, apparatus and computer product that enables a processor associated with a node in a computer system having various nodes, the nodes having sensors which provide data, and the nodes being connected by a communications facility acquiring local data from the sensor and remote data from other nodes via the data transfer facility. The nodes process data from a local sensor at the node and from remote sensors at other nodes; and analyze the local data, data from other nodes and local decisions made at and received from other nodes to make a local decision for action at the node. A local decision made at a node is in turn communicated to other nodes.

Abstract: A method, apparatus and computer product that enables a processor associated with a node in a computer system having various nodes, the nodes having sensors which provide data, and the nodes being connected by a communications facility acquiring local data from the sensor and remote data from other nodes via the data transfer facility. The nodes process data from a local sensor at the node and from remote sensors at other nodes; and analyze the local data, data from other nodes and local decisions made at and received from other nodes to make a local decision for action at the node. A local decision made at a node is in turn communicated to other nodes.