Abstract: A truck for carrying and dispensing material includes a frame, a hopper mounted on the frame and having an opening along a lower end portion of the hopper, and a conveyor positioned underneath the hopper, wherein the conveyor comprises a conveyor belt and first and second side walls attached to opposing longitudinal side edge portions of the conveyor belt.

Abstract: Embodiments described herein provide for automatically classifying the types of devices that place calls to a call center. A call center system can detect whether an incoming call originated from voice assistant device using trained classification models received from a call analysis service. Embodiments described herein provide for methods and systems in which a computer executes machine learning algorithms that programmatically train (or otherwise generate) global or tailored classification models based on the various types of features of an audio signal and call data. A classification model is deployed to one or more call centers, where the model is used by call center computers executing classification processes for determining whether incoming telephone calls originated from a voice assistant device, such as Amazon Alexa® and Google Home®, or another type of device (e.g., cellular/mobile phone, landline phone, VoIP).

Abstract: A computer may train a single-class machine learning using normal speech recordings. The machine learning model or any other model may estimate the normal range of parameters of a physical speech production model based on the normal speech recordings. For example, the computer may use a source-filter model of speech production, where voiced speech is represented by a pulse train and unvoiced speech by a random noise and a combination of the pulse train and the random noise is passed through an auto-regressive filter that emulates the human vocal tract. The computer leverages the fact that intentional modification of human voice introduces errors to source-filter model or any other physical model of speech production. The computer may identify anomalies in the physical model to generate a voice modification score for an audio signal. The voice modification score may indicate a degree of abnormality of human voice in the audio signal.

Abstract: A computer may train a single-class machine learning using normal speech recordings. The machine learning model or any other model may estimate the normal range of parameters of a physical speech production model based on the normal speech recordings. For example, the computer may use a source-filter model of speech production, where voiced speech is represented by a pulse train and unvoiced speech by a random noise and a combination of the pulse train and the random noise is passed through an auto-regressive filter that emulates the human vocal tract. The computer leverages the fact that intentional modification of human voice introduces errors to source-filter model or any other physical model of speech production. The computer may identify anomalies in the physical model to generate a voice modification score for an audio signal. The voice modification score may indicate a degree of abnormality of human voice in the audio signal.

Abstract: Embodiments described herein provide for automatically classifying the types of devices that place calls to a call center. A call center system can detect whether an incoming call originated from voice assistant device using trained classification models received from a call analysis service. Embodiments described herein provide for methods and systems in which a computer executes machine learning algorithms that programmatically train (or otherwise generate) global or tailored classification models based on the various types of features of an audio signal and call data. A classification model is deployed to one or more call centers, where the model is used by call center computers executing classification processes for determining whether incoming telephone calls originated from a voice assistant device, such as Amazon Alexa® and Google Home®, or another type of device (e.g., cellular/mobile phone, landline phone, VoIP).

Abstract: In one representative embodiment, a vehicle has a frame, a material hopper mounted on the frame, a swing arm assembly coupled to the frame, and a conveyor mounted on the swing arm assembly. The swing arm assembly can have a support bracket configured to pivot relative to the hopper about a vertical pivot axis, the support bracket also configured to pivot relative to the hopper about a horizontal pivot axis, wherein the support bracket is configured to support the conveyor for pivoting movement of the conveyor relative to the hopper about the vertical pivot axis and about the horizontal pivot axis to move the conveyor from a first, stowed position extending alongside one of the sides of the hopper to a second, use position extending rearwardly away from the rear end of the hopper.

Abstract: A dual modality sensor comprises a tissue-contact electrode having a first surface configured for receiving an electrical signal from a user's tissue when attached thereto; and a mechanical sensor overlying the cutaneous electrode and configured to sense a mechanical displacement of the first surface through the electrode. The electrode and the mechanical sensor thereby provide electrical and mechanical signals which originate from precisely the same tissue location.

Abstract: A computer may train a single-class machine learning using normal speech recordings. The machine learning model or any other model may estimate the normal range of parameters of a physical speech production model based on the normal speech recordings. For example, the computer may use a source-filter model of speech production, where voiced speech is represented by a pulse train and unvoiced speech by a random noise and a combination of the pulse train and the random noise is passed through an auto-regressive filter that emulates the human vocal tract. The computer leverages the fact that intentional modification of human voice introduces errors to source-filter model or any other physical model of speech production. The computer may identify anomalies in the physical model to generate a voice modification score for an audio signal. The voice modification score may indicate a degree of abnormality of human voice in the audio signal.

Abstract: In one representative embodiment, a vehicle has a frame, a material hopper mounted on the frame, a swing arm assembly coupled to the frame, and a conveyor mounted on the swing arm assembly. The swing arm assembly can have a support bracket configured to pivot relative to the hopper about a vertical pivot axis, the support bracket also configured to pivot relative to the hopper about a horizontal pivot axis, wherein the support bracket is configured to support the conveyor for pivoting movement of the conveyor relative to the hopper about the vertical pivot axis and about the horizontal pivot axis to move the conveyor from a first, stowed position extending alongside one of the sides of the hopper to a second, use position extending rearwardly away from the rear end of the hopper.

Abstract: A dual modality sensor comprises a tissue-contact electrode having a first surface configured for receiving an electrical signal from a user's tissue when attached thereto; and a mechanical sensor overlying the cutaneous electrode and configured to sense a mechanical displacement of the first surface through the electrode. The electrode and the mechanical sensor thereby provide electrical and mechanical signals which originate from precisely the same tissue location.

Abstract: The present disclosure concerns a system for transporting drill cuttings from an offshore drilling platform. In a representative embodiment, a bulk material storage and conveying system for a waterborne vessel comprises a first conveyor system including one or more upper conveyors extending lengthwise of the vessel. The system also comprises a plurality of containers located below the first conveyor system arranged in one or more rows, and a second conveyor system including one or more lower conveyors located below the one or more containers. The first conveyor system is configured to selectively dispense bulk material into the one or more containers, and the plurality of containers are configured to selectively dispense bulk material onto different locations along the length of the one or more lower conveyors. The system can further include an offloading conveyor assembly configured to convey drill cuttings from the lower conveyors to trucks on land.

Abstract: A hearing aid comprises an amplifier (303, 309, 317), an input transducer (301), an output transducer (824) and a signal processing device (825). The amplifier (303, 309, 317) and the signal processing device (825) are connected. The hearing aid further comprises at least two electrodes (201-205) adapted for detecting electrical signals such as brain waves, the at least two electrodes (201-205) being connected to a differential amplifier (303, 309, 317), which in turn is connected to the signal processing device, and means for modifying the operation of said hearing aid in dependence of the detected signals. The invention further provides a method for adaptation of a hearing aid.

Abstract: Systems and methods for mounting of plug-in electronic dongles are provided. In one embodiment, an electronics mounting adapter device comprises: a base member that includes a cavity and at least one cable stabilizing element configured to secure a cable connector of a cable within the cavity, wherein the cable is routed though an opening in the base member into the cavity; a cover coupled to the base member by at least one fastener; one or more mounting provisions for securing the base member to a mounting surface; and at least one clamping element configured to clamp a dongle within the cavity, wherein the dongle is coupled to the cable connector.

Abstract: The present disclosure concerns a system for transporting drill cuttings from an offshore drilling platform. In a representative embodiment, a bulk material storage and conveying system for a waterborne vessel comprises a first conveyor system including one or more upper conveyors extending lengthwise of the vessel. The system also comprises a plurality of containers located below the first conveyor system arranged in one or more rows, and a second conveyor system including one or more lower conveyors located below the one or more containers. The first conveyor system is configured to selectively dispense bulk material into the one or more containers, and the plurality of containers are configured to selectively dispense bulk material onto different locations along the length of the one or more lower conveyors. The system can further include an offloading conveyor assembly configured to convey drill cuttings from the lower conveyors to trucks on land.

Abstract: Systems and methods for mounting of plug-in electronic dongles are provided. In one embodiment, an electronics mounting adapter device comprises: a base member that includes a cavity and at least one cable stabilizing element configured to secure a cable connector of a cable within the cavity, wherein the cable is routed though an opening in the base member into the cavity; a cover coupled to the base member by at least one fastener; one or more mounting provisions for securing the base member to a mounting surface; and at least one clamping element configured to clamp a dongle within the cavity, wherein the dongle is coupled to the cable connector.

Abstract: A hearing aid comprises an amplifier (303, 309, 317), an input transducer (301), an output transducer (824) and a signal processing device (825). The amplifier (303, 309, 317) and the signal processing device (825) are connected. The hearing aid further comprises at least two electrodes (201-205) adapted for detecting electrical signals such as brain waves, the at least two electrodes (201-205) being connected to a differential amplifier (303, 309, 317), which in turn is connected to the signal processing device, and means for modifying the operation of said hearing aid in dependence of the detected signals. The invention further provides a method for adaptation of a hearing aid.

Abstract: An mobile material placer or slinger with a placer conveyor having a gear-to-gear pivoting mechanism. The mobile material placer includes a body, a material hopper coupled to the body and configured to receive and store material, a feeder conveyor coupled to the body, and a placer conveyor pivotally coupled to the body about a vertical axis. The gear-to-gear pivoting mechanism includes a first gear attached to the body of the material placer and that drives a second gear fixedly mounted to the placer conveyor.

Abstract: A display device includes a substrate. At least a portion of a plurality of pixel circuits are disposed over or integrated into a first surface of the substrate, and arranged in a matrix. A control device is disposed over a second surface of the substrate.

Abstract: An mobile material placer with a placer conveyor having a high-speed direct hydraulic drive mechanism. The mobile material placer includes a body, a material hopper coupled to the body and configured to receive and store material, a feeder conveyor coupled to the body, and a placer conveyor pivotally coupled to the body. The placer conveyor includes a frame, at least a drive axle and a secondary axle rotatably coupled to the frame, each axle having at least one roller mounted thereon. An endless belt extends around and frictionally engages the rollers. A direct hydraulic drive mechanism is provided and causes the drive to rotate. The rotating axle causes the rollers to rotate and thereby drive the endless belt at a high-speed. The direct hydraulic drive mechanism is configured to drive the endless belt at a linear velocity of at least 3,000 ft/min.

Abstract: An mobile material placer or slinger with a placer conveyor having a gear-to-gear pivoting mechanism. The mobile material placer includes a body, a material hopper coupled to the body and configured to receive and store material, a feeder conveyor coupled to the body, and a placer conveyor pivotally coupled to the body about a vertical axis. The gear-to-gear pivoting mechanism includes a first gear attached to the body of the material placer and that drives a second gear fixedly mounted to the placer conveyor.