The present disclosure relates to a system, method, and computer program for recommending products using a neural network architecture that directly learns a user's predicted rating for an item from user and item data. A set of encoding neural networks maps each input source for user and item data to a lower-dimensional vector space. The individual lower-dimensional vector outputs of the encoding neural networks are combined to create a single multidimensional vector representation of user and item data. A prediction neural network is trained to predict a user's rating for an item based on the single multidimensional vector representation of user and item data. The neural network architecture allows for more efficient optimization and faster convergence that recommendations systems that rely on autoencoders. The system recommends items to users based on the users' predicted ratings for items.

Embodiments of the present disclosure relate to a device, a method, an apparatus and a computer-readable medium for signal equalization. According to the embodiments of the present disclosure, a balance between equalization performance and effects is achieved by using a linear equalizer and a nonlinear equalizer. In addition, signals from different uplinks are equalized using adaptive parameters, to achieve optimal equalization of various signals.

Provided is a method for providing measured values of a technical installation in which measured values in at least one measurement series are captured, wherein a respective measured value is provided by a measurement sensor for a respective physical measurement variable in the technical installation for a respective measurement time. The measured values are categorized as normal measured values or anomalous measured values with the aid of a threshold value comparison and at least one further method stage. The further method stage comprises calculating one or more statistical position parameters for selected measured values from the same measurement series and/or different measurement series. The method makes it possible to increase the reliability of the measured values provided. A technical system comprising the technical installation, at least one measurement sensor and a program-controlled device, and a method for operating the technical system are also proposed.

The present disclosure relates to a system, method, and computer program for recommending products using a neural network architecture that directly learns a user's predicted rating for an item from user and item data. A set of encoding neural networks maps each input source for user and item data to a lower-dimensional vector space. The individual lower-dimensional vector outputs of the encoding neural networks are combined to create a single multidimensional vector representation of user and item data. A prediction neural network is trained to predict a user's rating for an item based on the single multidimensional vector representation of user and item data. The neural network architecture allows for more efficient optimization and faster convergence that recommendations systems that rely on autoencoders. The system recommends items to users based on the users' predicted ratings for items.

Embodiments of the present disclosure relate to a device, a method, an apparatus and a computer-readable medium for signal equalization. According to the embodiments of the present disclosure, a balance between equalization performance and effects is achieved by using a linear equalizer and a nonlinear equalizer. In addition, signals from different uplinks are equalized using adaptive parameters, to achieve optimal equalization of various signals.

A system and method to perform dynamic bandwidth adjustment among two or more vehicle sensors includes receiving input. The input includes data from each of the two or more vehicle sensors. The two or more vehicle sensors include a camera, an audio detector, a radar system, or a lidar system. The method also includes determining a bandwidth at which each of the two or more vehicle sensors should provide the data, and providing a control signal to each of the two or more vehicle sensors to adjust the bandwidth based on the determining.

Disclosed here are systems, methods, and apparatuses for single-ended electro-absorption modulators (EAMs) with electrical combining. In particular, systems and methods are disclosed for performing optical encoding and multiplication operation for optical signal without applying a sign value. The optical output can be converted into a photocurrent input and the sign value can be applied to the photocurrent input on an electrical layer.

Provided is a method for providing measured values of a technical installation in which measured values in at least one measurement series are captured, wherein a respective measured value is provided by a measurement sensor for a respective physical measurement variable in the technical installation for a respective measurement time. The measured values are categorized as normal measured values or anomalous measured values with the aid of a threshold value comparison and at least one further method stage. The further method stage comprises calculating one or more statistical position parameters for selected measured values from the same measurement series and/or different measurement series.

The method makes it possible to increase the reliability of the measured values provided.

A technical system comprising the technical installation, at least one measurement sensor and a program-controlled device, and a method for operating the technical system are also proposed.

Described is a communication system having a transmitter comprising a first optical module, the first optical module comprising a plurality of Micro-Ring Modulators (MRMs); and a receiver comprising a second optical module, the second optical module comprising a plurality of Micro Ring Resonators (MRRs), wherein the first optical module and the second optical module are connected by an optical waveguide; and at least one comb laser external to an optical co-package comprising the transmitter or the receiver, the at least one comb laser irradiating the optical waveguide, the at least one comb laser emitting light in a plurality of wavelengths, where at least one first MRM and at least one first MRR are adjusted to operate in at least one first wavelengths from the plurality of wavelengths, and at least one second MRM and at least one second MRR are adjusted to operate in at least one second wavelength from the plurality of wavelengths.

A system and method to perform dynamic bandwidth adjustment among two or more vehicle sensors includes receiving input. The input includes data from each of the two or more vehicle sensors. The two or more vehicle sensors include a camera, an audio detector, a radar system, or a lidar system. The method also includes determining a bandwidth at which each of the two or more vehicle sensors should provide the data, and providing a control signal to each of the two or more vehicle sensors to adjust the bandwidth based on the determining.