Abstract: An apparatus for detecting the activity of persons or the state of infrastructures or objects influenced by persons by means of acceleration measurement. The device has an acceleration sensor which is arranged to react to a preset threshold value of a measured acceleration and, when the threshold value is exceeded, to trigger at least one of the actions of data storage, modification of a counter or transmission of a data telegram by radio. The apparatus further comprises an energy converter for converting a primary energy into electrical energy for operating the apparatus or the acceleration sensor. The energy converter is arranged to obtain the primary energy independently of an energy resulting from a measured acceleration.

Abstract: A computer-implemented method for training a classifier, particularly a binary classifier, for classifying input signals to optimize performance according to a non-decomposable metric that measures an alignment between classifications corresponding to input signals of a set of training data and corresponding predicted classifications of the input signals obtained from the classifier. The method includes providing weighting factors that characterize how the non-decomposable metric depends on a plurality of terms from a confusion matrix of the classifications and the predicted classifications, and training the classifier depending on the provided weighting factors.

Abstract: A method for producing separated strip-like laminate components including an electronic component embedded between two laminate layers of a tape-like material. Individual components are placed at defined intervals by a placement device onto a tape-like, lower first laminate layer moved in a conveying direction by a transport device, after which a tape-like, upper second laminate layer moved in the conveying direction is applied to the first laminate layer with embedding of the components to form a laminate tape. The individual strip-like laminate components are cut from the laminate tape by a cutting device having a movable cutting blade, which laminate components are picked up by a gripper device and transported away. The front end of the laminate tape is gripped by the gripper device in the region of a component and moved synchronously with the clocked movement of the transport device by a predetermined distance through the cutting device and positioned relative to the cutting blade.

Abstract: The invention relates to an electric drive unit for a motor vehicle, comprising an electric drive and a multi-stage transmission (6), which is connected downstream of the electric drive and which is arranged, alone or together with the electric drive, in a drive housing (4). The drive housing is composed of a housing shell (11), the interior (11a) of which annularly surrounds the transmission (6), and an end wall (12), which is formed integrally with the housing shell (11). The end wall is provided, at the center thereof, with a transmission opening (17) for the transmission output shaft (18) of the transmission (6). Cooling liquid is conducted through the drive housing in order to cool the components of the transmission.

Abstract: An electromagnetic energy converter for a remote switch. The energy converter has an electrical coil and magnetic components, which comprise at least one permanent magnet and at least one ferromagnetic element. The permanent magnet and/or the ferromagnetic element are each movable between two extreme positions, where the movement of the permanent magnet and/or of the ferromagnetic element between the extreme positions leads to a directional reversal of a magnetic flux in the magnetic circuit. The magnetic flux is enclosed at least in part by the coil. At least one of the extreme positions is configured as a contactless extreme position at which at least two of the magnet components do not contact.

Abstract: An equipment inspection system receives data captured by a sensor of an autonomous vehicle (AV). The captured data describes a current state of equipment for servicing the AV. The equipment inspection system compares the captured data to a model describing an expected state of the equipment. The equipment inspection system determines, based on the comparison, that the equipment differs from the expected state. The equipment inspection system may transmit data describing the current state of the equipment to an equipment manager. The equipment manager may schedule maintenance for the equipment based on the current state of the equipment.

Abstract: A method for communication between autonomous vehicles and personnel can include receiving a signal from a remote computing system, the signal based upon a position of an autonomous vehicle and a first position of a mobile device, wherein the signal identifies that the mobile device is located in a path of the autonomous vehicle, responsive to receipt of the signal from the remote computing system, stopping the autonomous vehicle, receiving an updated signal from the remote computing system, the updated signal based upon a second position of the mobile device, the second position effective to facilitate a determination that the mobile device is no longer within the path of the autonomous vehicle, and responsive to receiving the updated position of the mobile device, resuming operation of the autonomous vehicle along the path. An autonomous vehicle and non-transitory computer-readable medium is also provided.

Abstract: A method for further training of a neural network for processing measurement data, which neural network has been pre-trained with training examples from a set M. In the method: a batch B of new training examples is provided; a subset D?M of the previous training examples is provided; the new training examples from batch B and the previous training examples from subset D are processed by the neural network into outputs respectively; the deviations of the outputs from the respective target outputs are evaluated using a predefined cost function; parameters characterizing the behavior of the neural network are optimized with the aim that, during further processing of previous and new training examples, the evaluation with the cost function is improved in regard to new training examples from batch B and is not made worse in regard to previous training examples from subset D.

Abstract: A light inspection system positions an autonomous vehicle (AV) in a field of view of a camera such that the camera captures an image of a light of the AV. The light inspection system instructs a camera to capture an image of the light while the light is switched on. The light inspection system receives the captured image, determines a luminance of the light based on the image, and determines to service the light in response to the luminance of the light being below a threshold luminance.

Abstract: A computer-implemented method for training a machine learning system. The method includes: ascertaining a first training time series of input signals and a desired training output signal which corresponds to the first training time series, the desired training output signal characterizing a desired classification and/or a desired regression result of the first training time series; ascertaining a first adversarial example when is an overlap between the first training time series and an ascertained first adversarial perturbation, a first noise value of the first adversarial perturbation is not greater than a specifiable threshold, and the specifiable threshold is based on the ascertained noise values of the training time series; ascertaining a training output signal for the first adversarial example using the machine learning system; and adapting at least one parameter of the machine learning system according to a gradient of a loss value.

Abstract: A computer-implemented machine learning system configured to ascertain an output signal based on a time series of input signals of a technical system. The output signal characterizes a classification and/or a regression result of at least one first operating state and/or at least one first operating variable of the technical system. The training of the machine learning system includes: ascertaining a first training time series of input signals from a plurality of training time series and a desired training output signal which corresponds to the first training time series; ascertaining a worst possible training time series which characterizes an overlap of the first training time series with an ascertained first noise signal; ascertaining a training output signal based on the worst possible training time series using the machine learning system; and adapting at least one parameter of the machine learning system according to a gradient of a loss value.

Abstract: Systems and methods are provided for automated detection and disinfection of microbes in autonomous vehicles, to prevent possible transmission of diseases or illness to subsequent users. Automated detection and disinfection of a vehicle includes autonomously scanning various parts of the autonomous vehicle for microbes, selecting a disinfectant based on detected microbes, and autonomously disinfecting at least a portion of the autonomous vehicle.

Abstract: A method for ascertaining an assignment rule in order to merge test results from different tests of the same semiconductor device. The method includes the following steps: adapting a model, e.g., a linear regression model, using the model to predict the test data; calculating costs based on the predictions; using a gradient descent method to minimize the costs.

Abstract: A light inspection system positions an autonomous vehicle (AV) in a field of view of a camera such that the camera captures an image of a light of the AV. The light inspection system instructs a camera to capture an image of the light while the light is switched on. The light inspection system receives the captured image, determines a luminance of the light based on the image, and determines to service the light in response to the luminance of the light being below a threshold luminance.

Abstract: Systems and methods are provided for automated detection and disinfection of microbes in autonomous vehicles, to prevent possible transmission of diseases or illness to subsequent users. Automated detection and disinfection of a vehicle includes autonomously scanning various parts of the autonomous vehicle for microbes, selecting a disinfectant based on detected microbes, and autonomously disinfecting at least a portion of the autonomous vehicle.

Abstract: The disclosure relates to a method for operating a braking system of a vehicle during autonomous parking processes, including a first electronic control unit, a service brake system, and a partial braking system. The first control unit is designed for activating the service brake system and the partial braking system, in which an autonomous parking process is initiated, followed by an activation of the service brake system by the first control unit to generate a braking force. In the event of a failure of the service brake system, the partial braking system is activated by the first control unit to generate a braking force while the autonomous parking process is continued by utilising the partial braking system. The disclosure also relates to a vehicle control system for controlling autonomous parking processes.

Abstract: Predictive maintenance and diagnostics for an electronic module of an autonomous vehicle using modular condition monitoring is described herein. A computing system receives a signal from a data logger which monitors a condition of the electronic module of the autonomous vehicle, wherein the signal is indicative of damage accumulation information thereof. The computing system identifies a type of the electronic module and a damage accumulation threshold for the type of the electronic module to generate a predicted maintenance schedule for the electronic module of the autonomous vehicle. The damage accumulation information can be stored in a data store to define the damage accumulation threshold for the type of the electronic module.

Abstract: Described herein is a server computing system that controls an autonomous vehicle to perform an operation to at least one of measure or isolate an effect of a variable on an actual power consumption by the autonomous vehicle. Data indicative of the actual power consumption, which is generated based on the operation, and data indicative of a projected power consumption, which is accumulated based on prior execution of the operation by a same or different autonomous vehicle, is received by the server computing system to determine whether an energy efficiency of the autonomous vehicle is degraded. The operation may be performed to identify a degraded vehicle system or component of the autonomous vehicle or to identify an autonomous vehicle in a fleet of autonomous vehicles for which further analysis is desirable. An output is generated by the server computing system that is indicative of the energy efficiency prognostics.

Abstract: A computer-implemented method determines a degree of robustness for a robustness of a provided, trained, data-based sensor model for evaluating an input dataset having at least one signal time series in order to determine a model output representing a change-point time. The method includes providing a plurality of unlabeled validation input datasets to the sensor model, and determining a plurality of robust validation input datasets of the plurality of unlabeled validation input datasets that satisfy a first robustness criterion and/or a second robustness criterion. The method further includes determining a proportion of the plurality of robust validation input datasets out of the plurality of unlabeled validation input datasets in order to obtain the degree of robustness.

Abstract: Copolymer, wherein structural units are derived from: i) an acrylic carboxylic acid monomer (4 to 18% by weight), selected from the group consisting of acrylic acid and methacrylic acid, ii) a 5 hydrophobic methacrylate (more than 8% by weight), selected from a group consisting of isopropyl methacrylate, tert-butyl methacrylate and cyclohexyl methacrylate, iii) a N-vinyl lactam, selected from a group consisting of N-vinyl pyrrolidone and N-vinylcaprolactam and optionally iv) 2-hydroxyethyl methacrylate, with the proviso that the total amount of structural units derived from the monomer groups adds up to 100% by weight, and the calculated solubility parameter SP of 10 the copolymer is between 22.0 and 25.0 MPa1/2, and the use of the copolymers as crystallization inhibitors in pharmaceutical dosage forms for inhibiting the recrystallization of an active ingredient in an aqueous environment of a human or animal body.