Abstract: A radiation-sensitive device is disclosed. The radiation-sensitive device includes: a plurality of single photon avalanche diodes (SPADs), and processing circuitry configured to determine an intensity of incident radiation using at least one of the plurality SPADs. An amount of the SPADs used to determine the intensity of the incident radiation varies in relation to the intensity of the incident radiation. Also disclosed in an associated method of determining an intensity of radiation incident upon such a radiation-sensitive device, and uses of the radiation-sensitive device in an electronic-nose or point-of-care apparatus, or for ambient light sensing.

Abstract: A radiation-sensitive device is disclosed. The device includes an array of single photon avalanche diodes (SPADs) and circuitry configured to measure an intensity of incident radiation from the array of SPADs with a plurality of different measurement windows to provide an associated plurality of results. The circuitry is configured to determine the intensity of the incident radiation from one of the plurality of results, a selection of the result determined by whether the result exceeds a maximum count defined, at least in part, by a duration of the measurement window associated with the result. An associated method of increasing a dynamic range of a radiation-sensitive device comprising an array of SPADs is also disclosed.

Abstract: A radiation-sensitive device is disclosed. The device comprises a plurality of single photon avalanche diodes (SPADs) and circuitry configured to adapt a read-out rate of the plurality of SPADs in relation to an intensity of incident radiation. Also disclosed is an associated method of increasing a dynamic range of a radiation-sensitive device comprising a plurality of SPADs. The method comprises adapting a read-out rate of the plurality of SPADs in relation to an intensity of incident radiation.

Abstract: Systems and methods for managing visual allocation are provided herein that use models to determine states based on visual data and, based thereon, output feedback based on the determined states. Visual data is initially obtained by a visual allocation management system. The visual data includes eye image sequences of a person in a particular state, such as engaging in a task or activity. Visual features can be identified from the visual data, such that glance information including direction and duration can be calculated. The visual data, information derived therefrom, and/or other contextual data is input into the models, which correspond to states, to calculate probabilities that the particular state that the person is engaged in is one of the modeled states. Based on the state identified as having the highest probability, an optimal feedback, such as a warning or instruction, can be output to a connected devices, systems, or objects.

Abstract: A sensing system comprising a measurement sensor configured to detect electromagnetic radiation and a reference sensor configured to detect a source of measurement uncertainty. The sensing system further comprises a shield configured to reduce an interaction between the electromagnetic radiation and the reference sensor.

Abstract: Systems and methods for managing visual allocation are provided herein that use models to determine states based on visual data and, based thereon, output feedback based on the determined states. Visual data is initially obtained by a visual allocation management system. The visual data includes eye image sequences of a person in a particular state, such as engaging in a task or activity. Visual features can be identified from the visual data, such that glance information including direction and duration can be calculated. The visual data, information derived therefrom, and/or other contextual data is input into the models, which correspond to states, to calculate probabilities that the particular state that the person is engaged in is one of the modeled states. Based on the state identified as having the highest probability, an optimal feedback, such as a warning or instruction, can be output to a connected devices, systems, or objects.

Abstract: Systems and methods for managing visual allocation are provided herein that use models to determine states based on visual data and, based thereon, output feedback based on the determined states. Visual data is initially obtained by a visual allocation management system. The visual data includes eye image sequences of a person in a particular state, such as engaging in a task or activity. Visual features can be identified from the visual data, such that glance information including direction and duration can be calculated. The visual data, information derived therefrom, and/or other contextual data is input into the models, which correspond to states, to calculate probabilities that the particular state that the person is engaged in is one of the modeled states. Based on the state identified as having the highest probability, an optimal feedback, such as a warning or instruction, can be output to a connected devices, systems, or objects.

Abstract: Systems and methods for assessing resource allocation are provided. In some exemplary embodiments, the system uses an attention buffer to classify glances by a person and/or automated system, the buffer determining the impact the glances have on the person and/or automated system's situation awareness level. The attention buffer calculates on a continuous basis a buffer value that is representative of the situation awareness level for the person and/or automated system at a particular moment in time. The calculated buffer values, referred to as moment-to-moment buffer values, among other names, can be used as data points, and/or they can also be used to direct action by the system and/or person to alter the situation awareness level of the person and/or automated system.

Abstract: Systems and methods for assessing resource allocation are provided. In some exemplary embodiments, the system uses an attention buffer to classify glances by a person and/or automated system, the buffer determining the impact the glances have on the person and/or automated system's situation awareness level. The attention buffer calculates on a continuous basis a buffer value that is representative of the situation awareness level for the person and/or automated system at a particular moment in time. The calculated buffer values, referred to as moment-to-moment buffer values, among other names, can be used as data points, and/or they can also be used to direct action by the system and/or person to alter the situation awareness level of the person and/or automated system.

Abstract: Systems and methods for managing visual allocation are provided herein that use models to determine states based on visual data and, based thereon, output feedback based on the determined states. Visual data is initially obtained by a visual allocation management system. The visual data includes eye image sequences of a person in a particular state, such as engaging in a task or activity. Visual features can be identified from the visual data, such that glance information including direction and duration can be calculated. The visual data, information derived therefrom, and/or other contextual data is input into the models, which correspond to states, to calculate probabilities that the particular state that the person is engaged in is one of the modeled states. Based on the state identified as having the highest probability, an optimal feedback, such as a warning or instruction, can be output to a connected devices, systems, or objects.

Abstract: A high voltage driver circuit for devices such as non-volatile memories, in which a low voltage driver is combined in two different ways with a high voltage driver In one, input-independent embodiment, a low voltage driver (Q7, Q8) is connected directly in parallel with a high voltage driver, thereby providing a high voltage signal path for high voltage operations and a low voltage signal path for low voltage operations. In an alternative, partially input-dependent embodiment, a low voltage driver is connected to the output of a high voltage driver (Q9, Q10), which may comprise a partial level shifter (Q 1 B Q6).