Abstract: Systems and methods are provided for modeling and simulating a communication network operating under at least one communication protocol, which supports a Smart Grid electricity network. Communication performance data of the communication network are generated by a processor based on operating behavior of the Smart Grid with a plurality of assets under a first condition. Devices in the Smart grid are grouped in bins for rapid modeling. One or more different configurations of the communication network are entered into the processor and related performance data is also generated. Network configurations are compared based on the generated performance data which may include end-to-end delay and reception rate. Processor based systems to perform modeling methods are also provided.

Abstract: A building system includes a communication network, a plurality of wireless nodes, a plurality of passive wireless devices, a plurality of sensors, and a processing circuit. The wireless nodes are disposed within a building and are operably coupled to the communication network. Each passive wireless device is affixed to an object within the building, and contains first information regarding at least one property of the object. Each the passive wireless device is configured to communicate wirelessly to the wireless nodes using power derived from communication signals detected in the passive wireless device. The sensors are configured to generate second information representative of sensed temperature throughout the building, each sensor operably connected to the communication network. The processing circuit is operably coupled to receive the first information from the wireless devices and the second information from the sensors.

Abstract: A building system includes a communication network, a plurality of wireless nodes, a plurality of passive wireless devices, and a processing circuit. The plurality of wireless nodes are disposed within a building operably and are coupled to the communication network. Each of the passive wireless devices is affixed to or within an object within the building. At least some of the objects constitute fixtures within the building. Each passive wireless device contains first information regarding at least one property of the object, and is configured to communicate wirelessly to at least one of the wireless nodes using power derived from communication signals detected in the passive wireless device. The processing circuit operably is coupled to receive the first information from the wireless devices, the processing circuit configured to update a model of at least a portion of a building based at least in part on the at least one property of the objects.

Abstract: A system and a method for a blind direction of arrival estimation is provided for a nonlinear 1-dimensional array of M receivers of J<M unknown signals transmitted through an unknown channel and subject to Gaussian noise. The method overcomes the conditions of that signals be disjoint in the time-frequency domain and/or statistically independent. A likelihood function evaluates a probability for the directions of arrivals. A weighting and regularization scheme selects relevant frequency components. A joint likelihood function of all frequencies is interpreted as a cost or objective function. The time domain is included into the estimation procedure by using a particle filter that operates on the constructed likelihood function and a simple transition kernel for the directions.

Abstract: Methods for one-class learning using support vector machines from a plurality of data batches are provided. A first support vector machine is learned from the plurality of data batches by a processor. A new data batch is received by the processor and is classified by the first support vector machine. If a non-zero loss classification occurs a new support vector machine is trained using the first support vector machine and the new data batch only. Data batches can be discarded if they are represented by the current support vector machine or after being used for training an updated support vector machine. Weighing factors applied to update the first support vector machine depend upon a parameter which is optimized iteratively. Support vectors do not need to be recalculated. A classifier is learned in a number of stages equal to the number of data batches processed on-line.

Abstract: Own voice recognition (OVR) for hearing aids, detects time instances where the person wearing the device is speaking. Classification of the own voice is performed dependent on a fixed or adaptive detection threshold. Automatic tuning in a real-time system depends on general noise statistics in the input signals. The noise is removed from the received signal and is characterized by signal-to-noise ratio and noise color. An optimal detection threshold for own voice recognition is determined based on the noise characteristics. A noise detection model is created by smoothed Voronoi tessellation. Own voice detection is performed by a processor.

Abstract: A method for controlling packet flow in a packet transmission network. The method includes determining a parameter representative of packet congestion on the network, and adjusting a flow of packets onto the network in accordance with such parameter. The adjusting is a function of the time history of the parameter and the time average of such parameter relative to predetermined threshold levels. The adjusting selects one of a plurality of states, transitions between the states being a function of the time history of the parameter and the time average of such parameter relative to predetermined threshold levels.

Abstract: A method for measuring degree of packet congestion on a channel of a packet communication network. The method includes: during a training mode, generating an mathematical relationship between the degree of packet congestion on the channel and a plurality of measurable features of the network over a plurality of network conditions; and, during a subsequent normal operating mode, periodically measuring the plurality of measurable features and applying the generated mathematical relationship to such periodically measured plurality of measurable features to determine actual degree of congestion on the channel; and comparing the actual degree of congestion on the channel with a predetermined channel congestion threshold level. The degree of packet congestion on the channel is saturation level. The measurable features include: lime delay between transmission starts and terminations of the previously transmitted packet; the fraction of time the channel is busy; and. average number of packet transmission retries.

Abstract: A method for measuring degree of packet congestion on a channel of a packet communication network. The method includes: during a training mode, generating an mathematical relationship between the degree of packet congestion on the channel and a plurality of measurable features of the network over a plurality of network conditions; and, during a subsequent normal operating mode, periodically measuring the plurality of measurable features and applying the generated mathematical relationship to such periodically measured plurality of measurable features to determine actual degree of congestion on the channel; and comparing the actual degree of congestion on the channel with a predetermined channel congestion threshold level. The degree of packet congestion on the channel is saturation level. The measurable features include: time delay between transmission starts and terminations of the previously transmitted packet; the fraction of time the channel is busy; and, average number of packet transmission retries.

Abstract: A method for controlling congestion for real-time video transmission in a wireless network includes receiving a packet loss rate of a video camera in a wireless network, receiving an estimated maximum throughput of the video camera from the camera to a server, decrementing a bit transmission rate when the packet loss rate is greater than a first predetermined threshold, incrementing the bit transmission rate when the packet loss rate is less than a second predetermined threshold for a predetermined time period, and transmitting the bit transmission rate to a video encoder that is part of an application layer of a network communication protocol for the wireless network.

Abstract: A method for determining a signature vector of a high dimensional dataset includes initializing a mutual interdependence vector wGMIA from a a set X of N input vectors of dimension D, where N?D, randomly selecting a subset S of n vectors from set X, where n is such that n>>1 and n<N, calculating an updated mutual interdependence vector wGMIA from wGMIA—new=wGMIA+S·(ST·S+?I)?1·( 1?MT·wGMIA), where ? is a regularization parameter, M ij = S ij ? k ? S kj ? 2 , I is an identity matrix, and 1 is a vector of ones, and repeating the steps of randomly selecting a subset S from set X, and calculating an updated mutual interdependence vector until convergence, where the mutual interdependence vector is approximately equally correlated with all input vectors X.

Abstract: A method for estimating packet collisions within a wireless network, comprising: for each transmit packet an Access Point (AP) of the network records statistics transmission information; based on this statistical information the AP computes: Total number of slot times generated during this transmission, n; Total number of deferrals, m; and Total number of unsuccessful transmissions, Q s; and using a sequence (m,n,Q) of statistics for each access category (AC), the AP computes the probability of collision for unsuccessful packets, p.

Abstract: A building system includes a communication network, a plurality of wireless nodes, a plurality of passive wireless devices, and a processing circuit. The plurality of wireless nodes are disposed within a building operably and are coupled to the communication network. Each of the passive wireless devices is affixed to or within an object within the building. At least some of the objects constitute fixtures within the building. Each passive wireless device contains first information regarding at least one property of the object, and is configured to communicate wirelessly to at least one of the wireless nodes using power derived from communication signals detected in the passive wireless device. The processing circuit operably is coupled to receive the first information from the wireless devices, the processing circuit configured to update a model of at least a portion of a building based at least in part on the at least one property of the objects.

Abstract: A building system includes a communication network, a plurality of wireless nodes, a plurality of passive wireless devices, a plurality of sensors, and a processing circuit. The wireless nodes are disposed within a building and are operably coupled to the communication network. Each passive wireless device is affixed to an object within the building, and contains first information regarding at least one property of the object. Each the passive wireless device is configured to communicate wirelessly to the wireless nodes using power derived from communication signals detected in the passive wireless device. The sensors are configured to generate second information representative of sensed temperature throughout the building, each sensor operably connected to the communication network. The processing circuit is operably coupled to receive the first information from the wireless devices and the second information from the sensors.

Abstract: A method for controlling packet flow in a packet transmission network. The method includes determining a parameter representative of packet congestion on the network, and adjusting a flow of packets onto the network in accordance with such parameter. The adjusting is a function of the time history of the parameter and the time average of such parameter relative to predetermined threshold levels. The adjusting selects one of a plurality of states, transitions between the states being a function of the time history of the parameter and the time average of such parameter relative to predetermined threshold levels.

Abstract: A method for controlling congestion for real-time video transmission in a wireless network includes receiving a packet loss rate of a video camera in a wireless network, receiving an estimated maximum throughput of the video camera from the camera to a server, decrementing a bit transmission rate when the packet loss rate is greater than a first predetermined threshold, incrementing the bit transmission rate when the packet loss rate is less than a second predetermined threshold for a predetermined time period, and transmitting the bit transmission rate to a video encoder that is part of an application layer of a network communication protocol for the wireless network.

Abstract: A method for measuring degree of packet congestion on a channel of a packet communication network. The method includes: during a training mode, generating an mathematical relationship between the degree of packet congestion on the channel and a plurality of measurable features of the network over a plurality of network conditions; and, during a subsequent normal operating mode, periodically measuring the plurality of measurable features and applying the generated mathematical relationship to such periodically measured plurality of measurable features to determine actual degree of congestion on the channel; and comparing the actual degree of congestion on the channel with a predetermined channel congestion threshold level. The degree of packet congestion on the channel is saturation level. The measurable features include: time delay between transmission starts and terminations of the previously transmitted packet; the fraction of time the channel is busy; and, average number of packet transmission retries.

Abstract: A method for estimating packet collisions within a wireless network, comprising: for each transmit packet an Access Point (AP) of the network records statistics transmission information; based on this statistical information the AP computes: Total number of slot times generated during this transmission, n; Total number of deferrals, m; and Total number of unsuccessful transmissions, Q s; and using a sequence (m,n,Q) of statistics for each access category (AC), the AP computes the probability of collision for unsuccessful packets, p.

Abstract: A system and method for non-square blind source separation (BSS) under coherent noise. The system and method for non-square BSS estimates the mixing parameters of a mixed source signal and filters the estimated mixing parameters so that output noise is reduced and the mixed source signal is separated from the noise. The filtering is accomplished by a linear filter that performs a beamforming for reducing the noise and another linear filter that solves a source separation problem by selecting time-frequency points where, according to a W-disjoint orthogonality assumption, only one source is active.

Abstract: We present, in exemplary embodiments of the present invention, novel systems and methods for syndromic surveillance that can automatically monitor symptoms that may be associated with the early presentation of a syndrome (e.g., fever, coughing, sneezing, runny nose, sniffling, rashes). Although not so limited, the novel surveillance systems described herein can be placed in common areas occupied by a crowd of people, in accordance with local and national laws applicable to such surveillance. Common areas may include public areas (e.g., an airport, train station, sports arena) and private areas (e.g., a doctor's waiting room). The monitored symptoms may be transmitted to a responder (e.g., a person, an information system) outside of the surveillance system, such that the responder can take appropriate action to identifying, treat and quarantine potentially infected individuals, as necessary.