Abstract: Apparatus are provided, which include a wireless transmit interface and a wireless receive interface. A payload receive processor is provided to identify a receive overhead portion from received data received via the receive interface, and it is configured to retrieve payload data in relation to the receive overhead portion in accordance with a data structure protocol. A payload transmit processor is provided to define or modify a transmit overhead portion in transmit data to be transmitted via the transmit interface. The payload transmit processor is configured to position payload data in relation to the transmit overhead portion in accordance with a data structure protocol. A controller is provided, to determine a given wireless media location defined at least in part by the controller determining a given frequency band, from among plural frequency bands, for a given data transfer, via wireless media, between a given node and a separate node.

Abstract: A system and method are provided that distill an organization's information security plan into a detailed and unambiguous security object model. The developed security object model provides a visualization of complex relationships between individual elements and levels that is usable to carry into effect the organization's information security plan. Configuration control and a verifiable level of security compliance are provided through implementation of the organization's information security plan by the developed security object model. The developed security object model is hosted on a computing platform in communication with at least the organization's network to provide information security plan compliance, configuration control and gap analysis in a usable form to the organization.

Abstract: A system and method are provided that distill an organization's information security plan into a detailed and unambiguous security object model. The developed security object model provides a visualization of complex relationships between individual elements and levels that is usable to carry into effect the organization's information security plan. Configuration control and a verifiable level of security compliance are provided through implementation of the organization's information security plan by the developed security object model. The developed security object model is hosted on a computing platform in communication with at least the organization's network to provide information security plan compliance, configuration control and gap analysis in a usable form to the organization.

Abstract: A method for advanced condition monitoring of an asset system includes sensing actual values of an operating condition for an operating regime of the asset system using at least one sensor; estimating sensed values of the operating condition by using an auto-associative neural network; determining a residual vector between the estimated sensed values and the actual values; and performing a fault diagnostic on the residual vector. In another method, an operating space of the asset system is segmented into operating regimes; the auto-associative neural network determines estimates of actual measured values; a residual vector is determined from the auto-associative neural network; a fault diagnostic is performed on the residual vector; and a change of the operation of the asset system is determined by analysis of the residual vector. An alert is provided if necessary. A smart sensor system includes an on-board processing unit for performing the method of the invention.

Abstract: Health information communications systems and methods are disclosed. In one embodiment, the system includes one or more medical sensors providing one or more health information data types. The system further includes a patient communications device coupled to at least one medical sensor over a communications network. Particularly, the patient communications device includes a patient quality of service (QoS) manager that dynamically specifies a set of data quality management parameters for transporting at least some of the health information and modifies at least some of the health information into value factored health information. Additionally, the system includes a specialist communications device communicatively coupled to the patient communication device over the communications network. The specialist communications device includes a specialist QoS manager that provides measured channel characteristics to the patient communications device.

Abstract: A method for advanced condition monitoring of an asset system includes monitoring a variable of an asset system using the at least one sensor of a smart sensor system; determining whether the asset system has departed from normal operation; and identifying the variable of the asset system indicating the departure from normal operation. In another method, the time sequential values of the monitored variable is analyzed by using a Rank Permutation Transformation test, a Hotelling's T2 statistic test, and a Likelihood Ratio Test; and a change of an operating condition of the asset system is determined using the analyzed values. An alert is provided if necessary. A smart sensor system includes an on-board processing unit for performing the method of the invention.

Abstract: System, device and methods that provide proximate environmental and security intelligence to a guard making a security tour or round in an installation, as well as that provide for certifying that the guard has visited designated and known checkpoints on or about the times at which the guard is expected at those checkpoints.

Abstract: System, device and methods that provide proximate environmental and security intelligence to a guard making a security tour or round in an installation, as well as that provide for certifying that the guard has visited designated and known checkpoints on or about the times at which the guard is expected at those checkpoints.

Abstract: A method for advanced condition monitoring of an asset system includes using a plurality of auto-associative neural networks to determine estimates of actual values sensed by at least one sensor in at least one of the plurality of operating regimes; determining a residual between the estimated sensed values and the actual values sensed by the at least one sensor from each of the plurality of auto-associative neural networks; and combining the residuals by using a fuzzy supervisory model blender; performing a fault diagnostic on the combined residuals; and determining a change of the operation of the asset system by analysis of the combined residuals. An alert is provided if necessary. A smart sensor system includes an on-board processing unit for performing the method of the invention.

Abstract: A method for advanced condition monitoring of an asset system includes sensing actual values of an operating condition for an operating regime of the asset system using at least one sensor; estimating sensed values of the operating condition by using an auto-associative neural network; determining a residual vector between the estimated sensed values and the actual values; and performing a fault diagnostic on the residual vector. In another method, an operating space of the asset system is segmented into operating regimes; the auto-associative neural network determines estimates of actual measured values; a residual vector is determined from the auto-associative neural network; a fault diagnostic is performed on the residual vector; and a change of the operation of the asset system is determined by analysis of the residual vector. An alert is provided if necessary. A smart sensor system includes an on-board processing unit for performing the method of the invention.

Abstract: A method for advanced condition monitoring of an asset system includes using a plurality of auto-associative neural networks to determine estimates of actual values sensed by at least one sensor in at least one of the plurality of operating regimes; determining a residual between the estimated sensed values and the actual values sensed by the at least one sensor from each of the plurality of auto-associative neural networks; and combining the residuals by using a fuzzy supervisory model blender; performing a fault diagnostic on the combined residuals; and determining a change of the operation of the asset system by analysis of the combined residuals. An alert is provided if necessary. A smart sensor system includes an on-board processing unit for performing the method of the invention.

Abstract: A method for advanced condition monitoring of an asset system includes sensing actual values of an operating condition for an operating regime of the asset system using at least one sensor; estimating sensed values of the operating condition by using an auto-associative neural network; determining a residual vector between the estimated sensed values and the actual values; and performing a fault diagnostic on the residual vector. In another method, an operating space of the asset system is segmented into operating regimes; the auto-associative neural network determines estimates of actual measured values; a residual vector is determined from the auto-associative neural network; a fault diagnostic is performed on the residual vector; and a change of the operation of the asset system is determined by analysis of the residual vector. An alert is provided if necessary. A smart sensor system includes an on-board processing unit for performing the method of the invention.

Abstract: A method, system and apparatus for processing a radiographic image of a scanned object is disclosed. A pixel offset correction is performed in integer format on the radiographic image using saturation arithmetic to produce an image in integer format with any negative corrected values clipped to a value of zero. The resulting pixels are converted to floating point format and the converted pixels are multiplied by a gain factor. Optionally the resulting pixels are recursively averaged with previous results. The resulting pixels are converted to integer format and the converted pixel values are clamped to a maximum value using saturation arithmetic. Non-functional pixel correction is performed in integer format and the resulting pixel values are clamped to a maximum value using saturation arithmetic. An optional processing path replaces the recursive average by a linear average. The resulting pixel values are optionally filtered to enhance features of interest.

Abstract: Apparatus are provided, which include a wireless transmit interface and a wireless receive interface. A payload receive processor is provided to identify a receive overhead portion from received data received via the receive interface, and it is configured to retrieve payload data in relation to the receive overhead portion in accordance with a data structure protocol. A payload transmit processor is provided to define or modify a transmit overhead portion in transmit data to be transmitted via the transmit interface. The payload transmit processor is configured to position payload data in relation to the transmit overhead portion in accordance with a data structure protocol. A controller is provided, to determine a given wireless media location defined at least in part by the controller determining a given frequency band, from among plural frequency bands, for a given data transfer, via wireless media, between a given node and a separate node.

Abstract: Public or private remote access infrastructures in a communication system are used to facilitate communications between a remote site and a centrally located diagnostic center using only local telephone calls. The diagnostic center as well as one or more remote sites at which monitored equipment is located are coupled to a wide area network (WAN). When data are to be transferred from a remote site to the central diagnostic center, the remote site initiates a local telephone call to a point-of-presence (POP) server on the WAN backbone. This could be an Internet Service Provider (ISP) if the Internet is used, or an intranet if a private network is used. Data are then transferred to the POP server. To complete the transfer, the diagnostic center retrieves the data from the POP server using the public or private wide-area network (the Internet or intranet). The data transfer can be performed either on a scheduled basis, or when an alarm condition is detected at the remote site.