Abstract: Activity of a subject is reported to an entity interested in the arrival of the subject at a destination. Context indicia relating to usage of the device is generated based on sensor data and content data of the device of the subject. The usage of the device includes travel to the destination. An estimated time of arrival (ETA) of the subject at the destination is determined based on the context indicia. An impact on the ETA of any changes in the context indicia is assessed. Content for a timeliness notification is generated based on a predefined degree of candor from among multiple degrees of candor regarding the timeliness of the ETA. Privacy criteria that defines a content limit to the timeliness notification, is applied. Any content of the timeliness notification that exceeds the content limit is removed to produce a minimally-informative notification to be communicated to the entity.

Abstract: Techniques are provided for automatic verification and inference of memory fences in concurrent programs that can bound the store buffers that are used to model relaxed memory models. A method is provided for determining whether a program employing a relaxed memory model satisfies a safety specification. An abstract memory model is obtained of the relaxed memory model. The abstract memory model represents concrete program states of the program as a finite number of abstract states. The safety specification is evaluated for the program on the abstract memory model having the finite number of abstract states. Fence positions at one or more locations can be determined to ensure that the safety specification is satisfied.

Abstract: A framework is provided for automatic inference of memory fences in concurrent programs. A method is provided for generating a set of ordering constraints that prevent executions of a program violating a specification. One or more incoming avoidable transitions are identified for a state and one or more ordering constraints are refined for the state. The set of ordering constraints are generated by taking a conjunction of ordering constraints for all states that violate the specification. One or more fence locations can optionally be selected based on the generated set of ordering constraints.

Abstract: Techniques are provided for automatic verification and inference of memory fences in concurrent programs that can bound the store buffers that are used to model relaxed memory models. A method is provided for determining whether a program employing a relaxed memory model satisfies a safety specification. An abstract memory model is obtained of the relaxed memory model. The abstract memory model represents concrete program states of the program as a finite number of abstract states. The safety specification is evaluated for the program on the abstract memory model having the finite number of abstract states. Fence positions at one or more locations can be determined to ensure that the safety specification is satisfied.

Abstract: A framework is provided for automatic inference of memory fences in concurrent programs. A method is provided for generating a set of ordering constraints that prevent executions of a program violating a specification. One or more incoming avoidable transitions are identified for a state and one or more ordering constraints are refined for the state. The set of ordering constraints are generated by taking a conjunction of ordering constraints for all states that violate the specification. One or more fence locations can optionally be selected based on the generated set of ordering constraints.

Abstract: Described is a speech recognition dialog management system that allows more open-ended conversations between virtual agents and people than are possible using just agent-directed dialogs. The system uses both novel dialog context switching and learning algorithms based on spoken interactions with people. The context switching is performed through processing multiple dialog goals in a last-in-first-out (LIFO) pattern. The recognition accuracy for these new flexible conversations is improved through automated learning from processing errors and addition of new grammars.

Abstract: A speech dialog management system where each dialog is capable of supporting one or more turns of conversation between a user and virtual agent using any one or combination of a communications interface and data interface. The system includes compiled application libraries, which determine the recognition, response, and flow control in a dialog with a user. A process of execution of a compiled application library runs throughout the conversation, putting itself into a dormant state in between processing of the communications from the user. A script manager brokers information between the processes of execution of the compiled application libraries and many communications with users.

Abstract: A speech dialog management system where each dialog is capable of supporting one or more turns of conversation between a user and virtual agent using any one or combination of a communications interface and data interface. The system includes a computer and a computer readable medium, operatively coupled to the computer, that stores scripts and dialog information. Each script determines the recognition, response, and flow control in a dialog while an application running on the computer delivers a result to any one or combination of the communications interface and data interface based on the dialog information and user input.

Abstract: A system and method is disclosed for determining the likelihood that two object patterns arise from the same object source. It is able to do this without having previously been exposed to either of the object patterns. This system utilizes an adaptive processor trained to make this determination using a large number of example patterns in different views and orientations. It accommodates large verifications of how an object source is presented in an image. The system also does not require the storage of any information about any particular pattern, which greatly minimizes the storage requirements and improves the throughput of the system. Further, there is no need for accessing a database of previously stored features from a given pattern source. The system is particularly useful for object patterns which consist of facial images. The system employs a new technique for locating an object of interest within a pattern using an adaptive processor to determine a region of interest.

Abstract: A neural network system and method that can adaptively recognize each of many pattern configurations from a set. The system learns and maintains accurate associations between signal pattern configurations and pattern classes with training from a teaching mechanism. The classifying system consists of a distributed input processor and an adaptive association processor. The input processor decomposes an input pattern into modules of localized contextual elements. These elements in turn are mapped onto pattern classes using a self-organizing associative neural scheme. The associative mapping determines which pattern class best represents the input pattern. The computation is done through gating elements that correspond to the contextual elements. Learning is achieved by modifying the gating elements from a true/false response to the computed probabilities for all classes in the set. The system is a parallel and fault tolerant process.

Abstract: A neural-like network system that adaptively controls a visually guided, two-jointed robot arm to reach spot targets in three dimensions. The system learns and maintains visual-motor calibrations by itself, starting with only loosely defined relationships. The geometry of the system is composed of distributed, interleaved combinations of actuator inputs. It is fault tolerant and uses analog processing. Learning is achieved by modifying the distributions of input weights in the system after each arm positioning. Modifications of the weights are made incrementally according to errors of consistency between the actuator signals used to orient the cameras and those used to move the arm.

Abstract: A real-time network enables robots to accurately learn sensory motor transformation and to self-train and self-calibrate operating parameters after accidents or with wear. Combinations of visual and present position signals are used to relearn a target position map. Target positions in body-centered. visually activated coordinates are mapped into target positions in motor coordinates which are compared with present positions in motor coordinates to generate motor commands. Feedback provides calibrated error signals for adjustment of learned gain with changes in the system due to aging, accidents and the like. A series of prestored motor commands may be performed with a later "go" command.

Abstract: A multi-microelectrode has a plurality of sensing elements formed in a linear array along a face of a metal foil substrate. The foil substrate is sufficiently rigid and tough to have a very small volume along a needle length yet support the array of sensing elements and their leads. The preferred substrate materials are tungsten and molybdenum. The leads are insulated from the substrate and from the surrounding environment. A multi-microelectrode is supported in a microelectrode assembly by a connector which includes a guide channel on a support plate. Electrical contacts which may be conformable to the microelectrode are located in the guide channel, and the microelectrode is clamped against those contacts.