Abstract: A pathogen detection method. A sample that potentially contains a pathogen is collected. A triangle wave form output is produced. A signal associated with the triangle wave form is transmitted from a voltage-controlled oscillator over a plurality of frequencies. The signal is transmitted through the sample to cause the pathogen in the sample to vibrate at a frequency. The vibrations from the sample are detected. A resonance profile of a pathogen in the sample is calculated based upon the vibrations. A database that includes a resonance profile signature of at least one pathogens is provided. The calculated resonance profile is compared to the resonance profile signature database to determine if the sample includes the pathogen.

Abstract: A method of detecting threats. A threat detection system is provided that includes a controller, a millimeter wave radar with transceiver, a signature database, and a camera. The signature database or machine learning includes time and frequency domain characteristic data for a threat. A signal is emitted by the millimeter wave radar. A return signal is received when the signal bounces off an object. Time and frequency domain characteristic data of the return signal is compared to the signature database, or the machine learned characteristics to determine the threat, anomaly, foreign object, material characteristics, and threat speech recognition.

Abstract: In an illustrative embodiment, systems and methods for verifying safety compliance of a worker positioned on a building structure utilize a motion detector module (MDM) for attaching to a wearable safety harness, where the harness has a lifeline attachment feature for connecting the safety harness to a lifeline anchored to the building structure. The MDM may include a motion sensor for detecting movement of the worker and processing circuitry for detecting, from signals provided by the motion sensor, significant movement indicative of the safety harness being properly worn by the worker and/or proper attachment of the safety harness to a lifeline, and translating the significant movements into compliance information. The MDM may include a proximate sensor for detecting contact between the attachment feature on the harness and a fastener on the lifeline for verifying the compliance information.

Abstract: Systems and methods for pre-processing data to facilitate efficient and accurate machine learning are provided. The data may include market data. The pre-processing may include partitioning the data into windows assigning categories to windows generate a series of vectors. The series of vectors then being input into a computer system that executes a machine learning algorithm to efficiently train a neural network used to identify structure or patterns therein.

Abstract: Systems and methods for pre-processing data to facilitate efficient and accurate machine learning are provided. The data may include market data. The pre-processing may include partitioning the data into windows assigning categories to windows generate a series of vectors. The series of vectors then being input into a computer system that executes a machine learning algorithm to efficiently train a neural network used to identify structure or patterns therein.

Abstract: Systems and methods for monitoring elevations of a set of workers at a job site include reference devices for capturing barometric pressures at different installation elevations on a structure and portable barometric pressure sensors carried by the workers. An atmospheric pressure offset may be calculated using the reference barometric pressures and installation elevations. The atmospheric pressure offset may be applied to atmospheric pressure measurements captured by the barometric pressure sensors carried by the workers to determine worker elevations. The worker elevations may be converted to corresponding floors of the structure.

Abstract: An engine control unit (400) for a full hybrid engine (100, 101) is provided. The full hybrid engine (100, 101) comprises an internal combustion engine (110) and an electric motor (120). The internal combustion engine (110) is coupled to the drivetrain via a clutch (130). The engine control unit (400) is configured to operate the internal combustion engine (110) in a lean-burn mode, to determine a current load level of the full hybrid engine (100, 101), and to compare the current load level to a lean-burn load threshold (210). The lean-burn load threshold (210) defines a load level below which stable operation of the internal combustion engine (110) in the lean-burn mode is impossible and/or undesirable. If the current load level of the full hybrid engine (100, 101) is below the lean-burn load threshold (210), the internal combustion engine (110) is decoupled from the drivetrain and the full hybrid engine (100, 101) is operated in an electric mode.

Abstract: In an illustrative embodiment, systems and methods for verifying safety compliance of a worker positioned on a building structure utilize a motion detector module (MDM) for attaching to a wearable safety harness, where the harness has a lifeline attachment feature for connecting the safety harness to a lifeline anchored to the building structure. The MDM may include a motion sensor for detecting movement of the worker and processing circuitry for detecting, from signals provided by the motion sensor, significant movement indicative of the safety harness being properly worn by the worker and/or proper attachment of the safety harness to a lifeline, and translating the significant movements into compliance information. The MDM may include a proximate sensor for detecting contact between the attachment feature on the harness and a fastener on the lifeline for verifying the compliance information.

Abstract: In an illustrative embodiment, systems and methods for verifying safety compliance of a worker positioned on a building structure utilize a motion detector module (MDM) for attaching to a wearable safety harness, where the harness has a lifeline attachment feature for connecting the safety harness to a lifeline anchored to the building structure. The MDM may include a motion sensor for detecting movement of the worker and processing circuitry for detecting, from signals provided by the motion sensor, significant movement indicative of the safety harness being properly worn by the worker and/or proper attachment of the safety harness to a lifeline, and translating the significant movements into compliance information. The MDM may include a proximate sensor for detecting contact between the attachment feature on the harness and a fastener on the lifeline for verifying the compliance information.

Abstract: Systems and methods for monitoring elevations of a set of workers at a job site include reference devices for capturing barometric pressures at different installation elevations on a structure and portable barometric pressure sensors carried by the workers. An atmospheric pressure offset may be calculated using the reference barometric pressures and installation elevations. The atmospheric pressure offset may be applied to atmospheric pressure measurements captured by the barometric pressure sensors carried by the workers to determine worker elevations. The worker elevations may be converted to corresponding floors of the structure.

Abstract: A method of detecting threats. A threat detection system is provided that includes a controller, a millimeter wave radar, a signature database and a camera. The signature database or machine learning includes time and frequency domain characteristic data for a threat. A signal is emitted by the millimeter wave radar. A return signal is received when the signal bounces off an object. Time and frequency domain characteristic data of the return signal is compared to the signature database or the machine learned characteristics to determine the threat, anomaly, foreign object and material characteristics.

Abstract: A decision tree based processing system implements a decision tree data structure to process publicly available files, such as websites suspected to contain data generated by a data transaction processing system which may be constantly fluctuating and varying. The data transaction processing system generates the data based on processing electronic data transaction request messages received over a network.

Abstract: Systems and methods are provided for message transmission timing optimization. The system receives a large market disrupting transaction and provides a transaction placement strategy that splits up the transaction to maximizes favorable execution value and minimizes time required to execute the entire transaction.

Abstract: Systems and methods for monitoring elevations of a set of workers at a job site include reference devices for capturing barometric pressures at different installation elevations on a structure and portable barometric pressure sensors carried by the workers. An atmospheric pressure offset may be calculated using the reference barometric pressures and installation elevations. The atmospheric pressure offset may be applied to atmospheric pressure measurements captured by the barometric pressure sensors carried by the workers to determine worker elevations. The worker elevations may be converted to corresponding floors of the structure.

Abstract: A decision tree based processing system implements a decision tree data structure to process publicly available files, such as websites suspected to contain data generated by a data transaction processing system which may be constantly fluctuating and varying. The data transaction processing system generates the data based on processing electronic data transaction request messages received over a network.

Abstract: Systems and methods are provided for message transmission timing optimization. The system receives a large market disrupting transaction and provides a transaction placement strategy that splits up the transaction to maximizes favorable execution value and minimizes time required to execute the entire transaction.

Abstract: Systems and methods for monitoring attachment of a lifeline assembly to a harness worn by a worker utilize a motion detector module (MDM) for attaching to an anchor tether of a lifeline assembly. The MDM may include a weather-resistant housing containing motion sensing circuitry for detecting significant motions associated with movement of the worker, timing circuitry for monitoring time between significant motions, and a communications transceiver for relaying information regarding significant motions and/or lack thereof to a nearby computing device. The nearby computing device may be a portable device carried or worn by the user. Alternatively, the nearby computing device may be a portable device positioned at a job site and configured to monitor multiple MDMs at the site. The MDM and/or computing device may issue audible alerts upon lack of detection of significant motions. The computing device may communicate noncompliance alerts to a remote computing system of a jobsite manager.

Abstract: A decision tree based processing system implements a decision tree data structure to process publicly available files, such as websites suspected to contain data generated by a data transaction processing system which may be constantly fluctuating and varying. The data transaction processing system generates the data based on processing electronic data transaction request messages received over a network.

Abstract: Systems and methods are provided for message transmission timing optimization. The system receives a large market disrupting transaction and provides a transaction placement strategy that splits up the transaction to maximizes favorable execution value and minimizes time required to execute the entire transaction.

Abstract: A method of detecting threats. A threat detection system is provided that includes a controller, a millimeter wave radar, a signature database and a camera. The signature database or machine learning includes time and frequency domain characteristic data for a threat. A signal is emitted by the millimeter wave radar. A return signal is received when the signal bounces off an object. Time and frequency domain characteristic data of the return signal is compared to the signature database or the machine learned characteristics to determine the threat, anomaly, foreign object and material characteristics.