Abstract: A chamber can be a pathogen control device, which can include a body having at least one internal wall defining an internal chamber, and a layer of a two dimensional material on at least a portion of the at least one internal wall. The two-dimensional material can have at least one edge protruding from the at least one internal wall. A pathogen control system can include the chamber and at least one pressure source operably coupled with an inlet of the internal chamber, and optionally include a depressurization vessel. A method of processing a fluid, such as for controlling pathogens, can include providing the chamber, and flowing a fluid with or without pressurized carbon dioxide or processing fluid through the internal chamber of the chamber to contact an edge of the two-dimensional material. The flow through the chamber can be conducted until at least one pathogen is controlled.

Abstract: A method for securely processing data is provided. The method allows for processing data out of context to assure security and can use a combination of multiple encryptions, hashing techniques, homomorphic searching, two or more key owners and threat detection and response to further enhance the security of the data.

Abstract: Technologies are generally described for normalized standard deviation transition based dosimetry monitoring for laser treatment. In some examples, a response signal may be generated based on a physical response to a laser pulse detected through acoustic or optical means. Each response signal may be a time series of data with a number of points. Standard deviation may be determined for each response signal and normalized using a mean or comparable normalization factor. Thus, a robust distribution may be computed from the response to each laser pulse. A change in the normalized standard deviation from each single pulse's time domain response data may be used to determine how many laser pulses remain before completion of the treatment (similar to event onset response). Thus, laser treatment may be continued based on an estimation of remaining pulses for completion or ceased if completion is reached.

Abstract: Systems and methods for training and using machine learning models to classify vehicles from highway radar systems are provided. The training systems may use auxiliary radar processing to separate events by lane, length, and/or speed, and then use separate event data groups pooled from similar or proximate lanes, lengths, and/or speeds to train multiple models. At estimation time, incoming events may be grouped using similar groupings as those used during training to select which model to use. An incoming event may be applied to the neural network operations of the selected model to generate an estimate. Generating an estimate may involve successive applications of multiple linear convolutions and other steps along varying or alternating dimensions of the in-process data.

Abstract: Techniques described include methods, systems, products, devices, and/or apparatuses related to food processing systems related methods, and food items produced therewith. For example, the food processing system may be configured to fabricate food aggregates from multiple food elements. The food processing system includes a first press body and a second press body. The second press body is positioned and oriented opposite to the first press body and reconfigurable from a first configuration to a second, non-planar configuration. The second, non-planar configuration of the press body is different from the first configuration. At least one of the first or second press bodies is movable in a manner that decreases space between the first and second press bodies, to compress the food elements and form the food aggregate. A dispenser of the food elements is positioned and configured to dispense the food elements between the first and second press bodies.

Abstract: Technologies are described image a treatment area during laser treatment using a time-gated image capture device and an electronic display. During laser treatment, a physician may monitor a treatment area to ensure efficacy and to prevent over-treatment. Light reflected from the area that includes treatment area may be detected by an image capture component and converted to a signal. An image processor may then generate image data based on the signal and provide the image data to be displayed on an electronic device. A gating component may send instructions to the image capture component and/or the image processor to prevent inclusion of light from one or more laser pulses generated during treatment. Excluding light from the laser pulses may prevent glare in captured images allow a monitoring physician to safely and accurately monitor the treatment area.

Abstract: Technologies are generally described for replayable hacktraps for intruder capture with reduced impact on false positives. An example system may generate a replayable set of actions such as scripts and/or file system differences upon detecting the actions being forwarded to a deception network as potentially malicious actions. If the actions are determined not to be malicious, they may be executed on the protected network. Retroactively executing sequestered actions may allow deception countermeasures to be made more aggressive because false positive detections may have fewer negative impacts.

Abstract: Technologies are generally described for customization of treatment based on dosimetric data collected during the treatment. In some examples, a laser treatment procedure may involve the application of multiple laser pulses to a treatment site. During the laser treatment procedure, an effect resulting from the application of one or more of the laser pulses may result in dosimetric data, such as acoustic and/or optical data. The dosimetric data may then be used to determine the efficacy of the laser treatment procedure and/or to adjust, in real-time, a remainder of the laser treatment procedure.

Abstract: Technologies are generally described for normalized standard deviation transition based dosimetry monitoring for laser treatment. In some examples, a response signal may be generated based on a physical response to a laser pulse detected through acoustic or optical means. Each response signal may be a time series of data with a number of points. Standard deviation may be determined for each response signal and normalized using a mean or comparable normalization factor. Thus, a robust distribution may be computed from the response to each laser pulse. A change in the normalized standard deviation from each single pulse's time domain response data may be used to determine how many laser pulses remain before completion of the treatment (similar to event onset response). Thus, laser treatment may be continued based on an estimation of remaining pulses for completion or ceased if completion is reached.

Abstract: A chamber can be a pathogen control device, which can include a body having at least one internal wall defining an internal chamber, and a layer of a two dimensional material on at least a portion of the at least one internal wall. The two-dimensional material can have at least one edge protruding from the at least one internal wall. A pathogen control system can include the chamber and at least one pressure source operably coupled with an inlet of the internal chamber, and optionally include a depressurization vessel. A method of processing a fluid, such as for controlling pathogens, can include providing the chamber, and flowing a fluid with or without pressurized carbon dioxide or processing fluid through the internal chamber of the chamber to contact an edge of the two-dimensional material. The flow through the chamber can be conducted until at least one pathogen is controlled.

Abstract: Systems and methods for training and using machine learning models to classify vehicles from highway radar systems are provided. The training systems may use auxiliary radar processing to separate events by lane, length, and/or speed, and then use separate event data groups pooled from similar or proximate lanes, lengths, and/or speeds to train multiple models. At estimation time, incoming events may be grouped using similar groupings as those used during training to select which model to use. An incoming event may be applied to the neural network operations of the selected model to generate an estimate. Generating an estimate may involve successive applications of multiple linear convolutions and other steps along varying or alternating dimensions of the in-process data.

Abstract: Technologies are generally described for identification and use of attractors in crowd control. In some examples, a crowd guidance system may receive a guidance request relating to a device associated with an individual in a crowd. The crowd guidance system may use information in the guidance request and a model of the crowd to determine one or more visual features that can be used to guide the individual. The crowd guidance system may provide the feature(s) to the device, which may then provide image data indicating the feature(s) to the individual for guidance.

Abstract: Technologies related to intermediary graphics rendition are generally described. In some examples, an intermediary computing device may store graphics models in a model store. A server computing device may generate and send a compositing flow to the intermediary computing device. The compositing flow may comprise model identifiers and model rendering information. The intermediary computing device may retrieve models identified in the compositing flow from the model store, and provide the identified models and model rendering information to a Graphics Processing Unit (GPU) for rendering. The GPU may render graphics for delivery via a network to a client device.

Abstract: Techniques described herein generally relate to a task management system for a chip multiprocessor having multiple processor cores. The task management system tracks the changing instruction set capabilities of each processor core and selects processor cores for use based on the tracked capabilities. In this way, a processor core with one or more failed processing elements can still be used effectively, since the processor core may be selected to process instruction sets that do not use the failed processing elements.

Abstract: Technologies are generally described for identification and use of attractors in crowd control. In some examples, social forces associated with individuals within a crowd may be extracted from a crowd model. One or more attractors may then be determined from the social forces, where an attractor is an individual that other crowd members tend to follow. The determined attractors may then be used to guide the overall flow of the crowd.

Abstract: Examples are disclosed for a wireless device handoff between a first wireless network and a second wireless network.

Abstract: Technologies related to multiple variable coverage memory for database indexing are generally described. Disclosed methods may be performed to implement high-speed database access to digital service provider customer data as the digital service provider builds an optimized index for a database. Initially, the digital service provider may maintain an appropriate level of service by keeping a relatively slow performing, basic index in a relatively high performance first memory. As the digital service provider builds the optimized index, the digital service provider may maintain the appropriate level of service by gradually shifting from use of the first memory to the use of a relatively lower performance second memory.

Abstract: Technologies related to intermediary graphics rendition are generally described. In some examples, an intermediary computing device may store graphics models in a model store. A server computing device may generate and send a compositing flow to the intermediary computing device. The compositing flow may comprise model identifiers and model rendering information. The intermediary computing device may retrieve models identified in the compositing flow from the model store, and provide the identified models and model rendering information to a Graphics Processing Unit (GPU) for rendering. The GPU may render graphics for delivery via a network to a client device.

Abstract: The present disclosure generally relates to instruction optimization (or otherwise improved execution of instructions) using voltage-based functional performance variation. In some examples, a method is described that includes instruction optimization (or otherwise improved execution of instructions) using voltage-based functional performance variation. In some examples, the method includes characterizing a workload for a multi-core processor to identify one or more subunits of individual cores of the multi-core processor for utilization by instructions included in the workload, selecting a voltage at which to operate cores of the multi-core processor, and assigning individual ones of the instructions of the workload to a core of the cores of the multi-core processor based on performance of the identified one or more subunits of the individual cores at the selected voltage.

Abstract: Technologies related to scene analysis for improved eye tracking are generally described. In some examples, detected gaze targets may be derived from gaze direction information from an eye-facing sensor. Detected gaze target positions and/or motion may be improved by capturing and analyzing digital scene information from a scene visible by the eye. Digital scene information captured by a digital camera may be analyzed to identify potential gaze targets, such as stationary gaze targets, moving gaze targets, and/or accelerating gaze targets. Detected gaze targets may be modified to positions of selected gaze targets.