Abstract: The present invention concerns a pharmaceutical composition where a checkpoint inhibitor is combined with an oncolytic virus and the use of said combination for the treatment of cancer.

Abstract: A method for creating a second series of individual images with a first series of individual images, the individual images of the first or the second series of individual images having been captured with an objective, includes determining the entrance pupil and the field of vision of the objective for the individual images of the first series and creating or adapting the individual images of the second series in accordance with the entrance pupil and the field of vision of the objective of the individual image in question of the first series.

Abstract: According to embodiments, a recurrent neural network (RNN) is equipped with a set data structure whose operations are differentiable, which data structure can be used to store information for a long period of time. This differentiable set data structure can “remember” an event in the sequence of sequential data that may impact another event much later in the sequence, thereby allowing the RNN to classify the sequence based on many kinds of long dependencies. An RNN that is equipped with the differentiable set data structure can be properly trained with backpropagation and gradient descent optimizations. According to embodiments, a differentiable set data structure can be used to store and retrieve information with a simple set-like interface. According to further embodiments, the RNN can be extended to support several add operations, which can make the differentiable set data structure behave like a Bloom filter.

Abstract: A multi-level stacked AW filter package including a first acoustic wave (AW) filter stacked on a second AW filter employs semiconductor fabrication methods and structures, including a metallization layer comprising interconnects to couple a contact surface to the second AW filter. Each AW filter includes an AW filter circuit on a semiconductor substrate. A second substrate disposed on a frame on the substrate protects the AW filter circuit. In a multi-level AW filter package, the second substrate of the first AW filter comprises a glass substrate with a similar expansion rate as the semiconductor substrate. The interconnects coupling the second AW filter to the contact surface are disposed on insulators on the side wall surfaces of the semiconductor substrates of the first AW filter for isolation. In a stacked AW filter package comprising a single AW filter, the interconnects couple the contact surface to the AW filter.

Abstract: Embodiments employ an inference method for neural networks that enforces deterministic constraints on outputs without performing post-processing or expensive discrete search over the feasible space. Instead, for each input, the continuous weights are nudged until the network's unconstrained inference procedure generates an output that satisfies the constraints. This is achieved by expressing the hard constraints as an optimization problem over the continuous weights and employing backpropagation to change the weights of the network. Embodiments optimize over the energy of the violating outputs; since the weights directly determine the output through the energy, embodiments are able to manipulate the unconstrained inference procedure to produce outputs that conform to global constraints.

Abstract: Systems and methods are disclosed to build and execute a decision system based on multiple machine learned decision models. In embodiments, the decision system performs a hashing technique to reduce relevant features of the input data into a feature vector for each decision model. The feature vector reduces the dimensionality of the feature universe of the input data, and its use allows the decision models to be trained and executed using less computing resources. In embodiments, the decision system implements an ensembled decision model that makes decisions based on a combination function that combines the decision results of the individual models in the ensemble. The decision models employ different hashing techniques to hash the input features differently, so that errors caused by the feature hashing of individual models are reduced in the aggregate.

Abstract: A method for creating a second series of individual images with a first series of individual images, the individual images of the first or the second series of individual images having been captured with an objective, includes determining the entrance pupil and the field of vision of the objective for the individual images of the first series and creating or adapting the individual images of the second series in accordance with the entrance pupil and the field of vision of the objective of the individual image in question of the first series.

Abstract: Multipurpose systems can include networked devices configured to include microphones, motion sensors, video cameras, touchscreens, optical sensors, speakers, or other suitable devices. The networked devices can include networking capabilities that enable the networked device to communicate with target devices and other networked devices. A system of networked devices can identify a target location or a target device by analyzing audio signals received at microphones of the networked devices. For example, a plurality of networked devices can identify a particular networked device that is in closest proximity to a user by analyzing an audio intensity of an audio signal received at the plurality of networked devices. The identified networked device can serve as a master device that can control a state of target devices.

Abstract: Systems and methods are described for a network video camera device. Specifically, various techniques and systems are provided for embodiments of a network video camera with a blocking mechanism for privacy and control of the blocking mechanism. Embodiments of the present invention include a network video capture device. The network video capture device comprises a lens connected to a housing; a blocking mechanism, wherein the a blocking mechanism is configured to selectively block the lens from capturing video images, and wherein the blocking mechanism includes a physical body; an indication device, wherein the indication device is configured to provide visible feedback that the lens is blocked; and a circuit board having a data processor, a wireless transceiver, and a memory configured to store a customizable setting associated with the blocking mechanism.

Abstract: Systems and methods are described for a network video camera device. Specifically, various techniques and systems are provided for embodiments of a network video camera with a blocking mechanism for privacy and control of the blocking mechanism. Embodiments of the present invention include a network video capture device. The network video capture device comprises a lens connected to a housing; a blocking mechanism, wherein the a blocking mechanism is configured to selectively block the lens from capturing video images, and wherein the blocking mechanism includes a physical body; an indication device, wherein the indication device is configured to provide visible feedback that the lens is blocked; and a circuit board having a data processor, a wireless transceiver, and a memory configured to store a customizable setting associated with the blocking mechanism.

Abstract: Systems and methods are described for a network video camera device. Specifically, various techniques and systems are provided for embodiments of a network video camera with a blocking mechanism for privacy and control of the blocking mechanism. Embodiments of the present invention include a network video capture device. The network video capture device comprises a lens connected to a housing; a blocking mechanism, wherein the a blocking mechanism is configured to selectively block the lens from capturing video images, and wherein the blocking mechanism includes a physical body; an indication device, wherein the indication device is configured to provide visible feedback that the lens is blocked; and a circuit board having a data processor, a wireless transceiver, and a memory configured to store a customizable setting associated with the blocking mechanism.

Abstract: Embodiments make novel use of random data structures to facilitate streaming inference for a Latent Dirichlet Allocation (LDA) model. Utilizing random data structures facilitates streaming inference by entirely avoiding the need for pre-computation, which is generally an obstacle to many current “streaming” variants of LDA as described above. Specifically, streaming inference—based on an inference algorithm such as Stochastic Cellular Automata (SCA), Gibbs sampling, and/or Stochastic Expectation Maximization (SEM)—is implemented using a count-min sketch to track sufficient statistics for the inference procedure. Use of a count-min sketch avoids the need to know the vocabulary size V a priori. Also, use of a count-min sketch directly enables feature hashing, which addresses the problem of effectively encoding words into indices without the need of pre-computation. Approximate counters are also used within the count-min sketch to avoid bit overflow issues with the counts in the sketch.

Abstract: Systems and methods are disclosed to build and execute a decision system based on multiple machine learned decision models. In embodiments, the decision system performs a hashing technique to reduce relevant features of the input data into a feature vector for each decision model. The feature vector reduces the dimensionality of the feature universe of the input data, and its use allows the decision models to be trained and executed using less computing resources. In embodiments, the decision system implements an ensembled decision model that makes decisions based on a combination function that combines the decision results of the individual models in the ensemble. The decision models employ different hashing techniques to hash the input features differently, so that errors caused by the feature hashing of individual models are reduced in the aggregate.

Abstract: The present invention relates to a method for simulating an image recording by an optical sensor of a coordinate measuring machine for inspecting a measurement object, comprising the following steps: providing a first data set representing a model of the measurement object, a second data set representing a model of an illumination of the measurement object, and a third data set representing a model of an optics of the optical sensor, and rendering an image stack on the basis of the first data set, the second data set and the third data set, wherein the image stack has a plurality of virtual images of at least one partial region of the measurement object, wherein each virtual image is rendered at least with a different second and/or different third data set. Furthermore, the present invention relates to a method for optimizing an image recording by a coordinate measuring machine.

Abstract: According to embodiments, a recurrent neural network (RNN) is equipped with a set data structure whose operations are differentiable, which data structure can be used to store information for a long period of time. This differentiable set data structure can “remember” an event in the sequence of sequential data that may impact another event much later in the sequence, thereby allowing the RNN to classify the sequence based on many kinds of long dependencies. An RNN that is equipped with the differentiable set data structure can be properly trained with backpropagation and gradient descent optimizations. According to embodiments, a differentiable set data structure can be used to store and retrieve information with a simple set-like interface. According to further embodiments, the RNN can be extended to support several add operations, which can make the differentiable set data structure behave like a Bloom filter.

Abstract: Embodiments employ an inference method for neural networks that enforces deterministic constraints on outputs without performing post-processing or expensive discrete search over the feasible space. Instead, for each input, the continuous weights are nudged until the network's unconstrained inference procedure generates an output that satisfies the constraints. This is achieved by expressing the hard constraints as an optimization problem over the continuous weights and employing backpropagation to change the weights of the network. Embodiments optimize over the energy of the violating outputs; since the weights directly determine the output through the energy, embodiments are able to manipulate the unconstrained inference procedure to produce outputs that conform to global constraints.

Abstract: The present invention relates to a method for simulating an image recording by an optical sensor of a coordinate measuring machine for inspecting a measurement object, comprising the following steps: providing a first data set representing a model of the measurement object, a second data set representing a model of an illumination of the measurement object, and a third data set representing a model of an optics of the optical sensor, and rendering an image stack on the basis of the first data set, the second data set and the third data set, wherein the image stack has a plurality of virtual images of at least one partial region of the measurement object, wherein each virtual image is rendered at least with a different second and/or different third data set. Furthermore, the present invention relates to a method for optimizing an image recording by a coordinate measuring machine.

Abstract: Systems and methods are described for a network video camera device. Specifically, various techniques and systems are provided for embodiments of a network video camera with a blocking mechanism for privacy and control of the blocking mechanism. Embodiments of the present invention include a network video capture device. The network video capture device comprises a lens connected to a housing; a blocking mechanism, wherein the a blocking mechanism is configured to selectively block the lens from capturing video images, and wherein the blocking mechanism includes a physical body; an indication device, wherein the indication device is configured to provide visible feedback that the lens is blocked; and a circuit board having a data processor, a wireless transceiver, and a memory configured to store a customizable setting associated with the blocking mechanism.

Abstract: Techniques and systems for controlling a network video camera with physical privacy feedback are provided. For example, computing device, a method, and a computer-program product may be provided. The computing device may include one or more lenses and one or more blocking mechanisms, wherein the one or more blocking mechanisms are configured to selectively block the one or more lenses from capturing video images, and wherein the one or more blocking mechanisms include a physical body that provides visible feedback that the one or more lenses are blocked. The computing device, method, and computer-program product may include detecting an occurrence of an event, and activating the one or more blocking mechanisms to block the one or more lenses from capturing video images, wherein the one or more blocking mechanisms are activated to block the one or more lenses when the occurrence of the event is detected.

Abstract: Techniques and systems are provided for controlling a network video camera with physical privacy feedback to capture one or more images of a scene. For example, computing device, a method, and a computer-program product may be provided. The computing device may include one or more lenses and one or more blocking mechanisms, wherein the one or more blocking mechanisms are configured to selectively block the one or more lenses from capturing video images, and wherein the one or more blocking mechanisms include a physical body that provides visible feedback that the one or more lenses are blocked. The computing device, method, and computer-program product may include detecting movement of a blocking mechanism from a first position in which a lens is exposed to a second position in which the lens is blocked, and capturing one or more images of a scene, wherein the one or more images of the scene are captured when the movement of the blocking mechanism is detected.