Abstract: Described are automated systems and methods for the handling and processing of items at material handling facility. The exemplary systems and methods can receive the items from various upstream processes and systems and can process and handle the items so that they can be provided to various downstream processes and systems. The exemplary systems and methods can provide modular systems and methods that can perform automated singulation, sortation, retrieval, and packing of items without any manual handling.

Abstract: Embodiments of the present disclosure relate scheduling maintenance services for a special-purpose vehicle. In an exemplary embodiment, a user device comprises a user interface, a processor, and memory comprising instructions that when executed by the processor cause the processor to output, to the user interface, a plurality of service method icons. The plurality of service methods comprise a first service method icon corresponding to a service being performed on the special-purpose vehicle at a first location and a second service method icon corresponding to the service being performed on the special-purpose vehicle at a second location. The first location and the second location are different locations. The memory also comprises instructions that when executed by the processor cause the processor to receive, via the user interface, a selection of a service method icon of the plurality of service method icons and send, to a scheduling server, a signal corresponding to the selected service method icon.

Abstract: A terpolymer composition is described that contains a statistical amount of 50-98 wt % of a first repeating AA-BB comonomer unit; 1-25 wt % of a second repeating AA-BB comonomer unit; and 1-25 wt % of a repeating lactam comonomer unit or 1-25 wt % of a third repeating AA-BB comonomer unit, where the terpolymer composition exhibits a high melting point similar to that of PA66 while also exhibiting a significantly reduced crystallization rate and crystallization temperature.

Abstract: The present disclosure is directed towards methods and systems for determining multimodal image edits for a digital image. The systems and methods receive a digital image and analyze the digital image. The systems and methods further generate a feature vector of the digital image, wherein each value of the feature vector represents a respective feature of the digital image. Additionally, based on the feature vector and determined latent variables, the systems and methods generate a plurality of determined image edits for the digital image, which includes determining a plurality of set of potential image attribute values and selecting a plurality of sets of determined image attribute values from the plurality of sets of potential image attribute values wherein each set of determined image attribute values comprises a determined image edit of the plurality of image edits.

Abstract: A terpolymer composition is described that contains a statistical amount of 50-98 wt % of a first repeating AA-BB comonomer unit; 1-25 wt % of a second repeating AA-BB comonomer unit; and 1-25 wt % of a repeating lactam comonomer unit or 1-25 wt % of a third repeating AA-BB comonomer unit, where the terpolymer composition exhibits a high melting point similar to that of PA66 while also exhibiting a significantly reduced crystallization rate and crystallization temperature.

Abstract: A terpolymer composition is described that contains a statistical amount of 50-98 wt % of a first repeating AA-BB comonomer unit; 1-25 wt % of a second repeating AA-BB comonomer unit; and 1-25 wt % of a repeating lactam comonomer unit or 1-25 wt % of a third repeating AA-BB comonomer unit, where the terpolymer composition exhibits a high melting point similar to that of PA66 while also exhibiting a significantly reduced crystallization rate and crystallization temperature.

Abstract: A digital medium environment includes an asset processing application that performs editing of assets. A projection function is trained using pairs of actions pertaining to software edits, and assets resulting from the actions to learn a joint embedding between the actions and the assets. The projection function is used in the asset processing application to recommend software actions to create an asset, and also to recommend assets to demonstrate the effects of software actions. Recommendations are based on ranking distance measures that measure distances between actions representations and asset representations in a vector space.

Abstract: The present disclosure is directed towards methods and systems for determining multimodal image edits for a digital image. The systems and methods receive a digital image and analyze the digital image. The systems and methods further generate a feature vector of the digital image, wherein each value of the feature vector represents a respective feature of the digital image. Additionally, based on the feature vector and determined latent variables, the systems and methods generate a plurality of determined image edits for the digital image, which includes determining a plurality of set of potential image attribute values and selecting a plurality of sets of determined image attribute values from the plurality of sets of potential image attribute values wherein each set of determined image attribute values comprises a determined image edit of the plurality of image edits.

Abstract: The present disclosure is directed towards methods and systems for determining multimodal image edits for a digital image. The systems and methods receive a digital image and analyze the digital image. The systems and methods further generate a feature vector of the digital image, wherein each value of the feature vector represents a respective feature of the digital image. Additionally, based on the feature vector and determined latent variables, the systems and methods generate a plurality of determined image edits for the digital image, which includes determining a plurality of set of potential image attribute values and selecting a plurality of sets of determined image attribute values from the plurality of sets of potential image attribute values wherein each set of determined image attribute values comprises a determined image edit of the plurality of image edits.

Abstract: A terpolymer composition is described that contains a statistical amount of 50-98 wt % of a first repeating AA-BB comonomer unit; 1-25 wt % of a second repeating AA-BB comonomer unit; and 1-25 wt % of a repeating lactam comonomer unit or 1-25 wt % of a third repeating AA-BB comonomer unit, where the terpolymer composition exhibits a high melting point similar to that of PA66 while also exhibiting a significantly reduced crystallization rate and crystallization temperature.

Abstract: Sound processing using a product-of-filters model is described. In one or more implementations, a model is formed by one or more computing devices for a time frame of sound data as a product of filters. The model is utilized by the one or more computing devices to perform one or more sound processing techniques on the time frame of the sound data.

Abstract: The present disclosure is directed towards methods and systems for determining multimodal image edits for a digital image. The systems and methods receive a digital image and analyze the digital image. The systems and methods further generate a feature vector of the digital image, wherein each value of the feature vector represents a respective feature of the digital image. Additionally, based on the feature vector and determined latent variables, the systems and methods generate a plurality of determined image edits for the digital image, which includes determining a plurality of set of potential image attribute values and selecting a plurality of sets of determined image attribute values from the plurality of sets of potential image attribute values wherein each set of determined image attribute values comprises a determined image edit of the plurality of image edits.

Abstract: A digital medium environment includes an asset processing application that performs editing of assets. A projection function is trained using pairs of actions pertaining to software edits, and assets resulting from the actions to learn a joint embedding between the actions and the assets. The projection function is used in the asset processing application to recommend software actions to create an asset, and also to recommend assets to demonstrate the effects of software actions. Recommendations are based on ranking distance measures that measure distances between actions representations and asset representations in a vector space.

Abstract: Sound processing techniques using recurrent neural networks are described. In one or more implementations, temporal dependencies are captured in sound data that are modeled through use of a recurrent neural network (RNN). The captured temporal dependencies are employed as part of feature extraction performed using nonnegative matrix factorization (NMF). One or more sound processing techniques are performed on the sound data based at least in part on the feature extraction.

Abstract: Sound enhancement techniques through dereverberation are described. In one or more implementations, a method is described of enhancing sound data through removal of reverberation from the sound data by one or more computing devices. The method includes obtaining a model that describes primary sound data that is to be utilized as a prior that assumes no prior knowledge about specifics of the sound data from which the reverberation is to be removed. A reverberation kernel is computed having parameters that, when applied to the model that describes the primary sound data, corresponds to the sound data from which the reverberation is to be removed. The reverberation is removed from the sound data using the reverberation kernel.

Abstract: Methods and systems for source separation based on determining a number of bases for a nonnegative matrix factorization (NMF) model are disclosed. A method includes receiving, at a computing device, a mixed signal including a combination of first signal data and second signal data. The method also includes generating, by the computing device, a time-frequency representation of the mixed signal. The method further includes determining, by applying a structured stochastic variational inference (SSVI) algorithm to the NMF model, a number of bases for a dictionary of signal-related components of the mixed signal. The method uses the number of bases and the time-frequency representation to construct the dictionary and an activation matrix of weights, the weights indicating how active each one of the signal-related components is at a given time. The method then uses the dictionary and the activation matrix to separate the first signal data from the second signal data.

Abstract: Methods and systems for source separation based on determining a number of bases for a nonnegative matrix factorization (NMF) model are disclosed. A method includes receiving, at a computing device, a mixed signal including a combination of first signal data and second signal data. The method also includes generating, by the computing device, a time-frequency representation of the mixed signal. The method further includes determining, by applying a structured stochastic variational inference (SSVI) algorithm to the NMF model, a number of bases for a dictionary of signal-related components of the mixed signal. The method uses the number of bases and the time-frequency representation to construct the dictionary and an activation matrix of weights, the weights indicating how active each one of the signal-related components is at a given time. The method then uses the dictionary and the activation matrix to separate the first signal data from the second signal data.

Abstract: Sound enhancement techniques through dereverberation are described. In one or more implementations, a method is described of enhancing sound data through removal of reverberation from the sound data by one or more computing devices. The method includes obtaining a model that describes primary sound data that is to be utilized as a prior that assumes no prior knowledge about specifics of the sound data from which the reverberation is to be removed. A reverberation kernel is computed having parameters that, when applied to the model that describes the primary sound data, corresponds to the sound data from which the reverberation is to be removed. The reverberation is removed from the sound data using the reverberation kernel.

Abstract: Sound processing techniques using recurrent neural networks are described. In one or more implementations, temporal dependencies are captured in sound data that are modeled through use of a recurrent neural network (RNN). The captured temporal dependencies are employed as part of feature extraction performed using nonnegative matrix factorization (NMF). One or more sound processing techniques are performed on the sound data based at least in part on the feature extraction.

Abstract: An antibacterial cleaning composition for hard surfaces is made from a flexible superabsorbent material and an antibacterial agent. The composition can be applied to various liquid and solid surface contaminants, including blood, vomit, fecal matter, urine, glass, food, etc. The composition may be applied to the contaminated hard surface by several methods including pouring, rolling, spraying or foaming. Once cured, the antimicrobial cleaning composition is removed from the surface, taking the contaminant along with it and leaving behind a clean surface.