Abstract: The disclosure relates to a method for creating an improved forecasting model. The method includes identifying a plurality of drivers affecting actual sales or demand of a product or service; receiving a respective data set for each of the drivers; generating one or more lagged data sets for each driver by applying lags to the data set associated with the driver; for each driver: forming a group of data sets by grouping the data set associated with the driver with the lagged data sets for the driver; and selecting a data set in the group of data sets that best correlates with sales or demand changes of the product or service; determining which one or more of the selected data sets for the drivers increases forecasting accuracy for sales or demand of the product or service; and training a forecasting model using the one or more selected data sets.

Abstract: Methods and systems for alkylate production involving a multi-zone alkylation reactor. The multi-zone alkylation reactor includes a plurality of alkylation zones spaced vertically in a series configuration and a partition splitting the plurality of alkylation zones into at least two mechanically separated catalytic volumes.

Abstract: This disclosure describes techniques for providing instructions when receiving biometric data associated with a user. For instance, a device may detect a portion of a user, such as a hand. The device may then display a first graphical element indicating a target location for placing the portion of the user above the user-recognition device. Additionally, the device may determine locations of the portion of the user above the device. The device may then display a second graphical element indicating the locations, such as when the locations are not proximate to the target location. Additionally, the device may display instructions for moving the portion of the user to the target location. Based on detecting that the location of the portion of the user is proximate to the target location, the device may send data representing the portion of the user to a remote system.

Abstract: Systems and methods for providing resilient persistent connections for communication are disclosed. Methods include identifying, at a first device, a second device registered with a client connection service; obtaining, from the client connection service, a first resource identifier for delivering request messages to the second device via the client connection service; identifying, based on the obtained first resource identifier, a first target resource for a first request message directed to the second device, wherein the first target resource specifies a first host included in the client connection service; sending, to the client connection service via the data communication network, the first request message to the first target resource for delivery to the second device by the client connection service; and receiving, from the client connection service via the data communication network, a first response message provided by the second device as a response to the first request message.

Abstract: A neural network is trained to process input data and generate a classification value that characterizes the input with respect to an ordered continuum of classes. For example, the input data may comprise an image and the classification value may be indicative of a quality of the image. The ordered continuum of classes may represent classes of quality of the image ranging from “worst”, “bad”, “normal”, “good”, to “best”. During training, loss values are determined using an ordered classification loss function. The ordered classification loss function maintains monotonicity in the loss values that corresponds to placement in the continuum. For example, the classification value for a “bad” image will be less than the classification value indicative of a “best” image. The classification value may be used for subsequent processing. For example, biometric input data may be required to have a minimum classification value for further processing.

Abstract: Processes and systems for fluid catalytic cracking (FCC) of hydrocarbon feeds using a multiple riser FCC reactor are described. The conditions in each riser can be tailored for handling a different feed. For example, one riser may be configured to crack heavy hydrocarbons, such as vacuum gas oil (VGO) to yield medium and light products. Other risers may be configured to crack low and/or medium hydrocarbons to yield light olefins. Embodiments of the disclosed processes and systems may be used to provide a product spectrum that has greater amounts of light olefins.

Abstract: Biometric input, such as an image of a hand, may be processed to determine embedding vector data that may be used to identify users. Accuracy of the identification is improved by using high resolution inputs to a deep convolutional neural network (DCNN) that is trained to generate the embedding vector data that is representative of features in the input. Training data sets are expensive to develop and thus may be relatively small. During training of the DCNN, confidence loss values corresponding to the entire input as well as particular patches or portions of the input are determined. These patch-wise confidence loss values mitigate potential overfitting during training of the DCNN and improve overall performance of the trained DCNN to determine embedding vector data suitable for identification.

Abstract: A system for scanning an object 112 is provided. The system includes a continuous conveyor belt 102, a first electromagnetic radiation sensor 104, a second electromagnetic radiation sensor, a tunnel 106, an electromagnetic radiation generator 108, a third electromagnetic radiation sensor, a fourth electromagnetic radiation sensor 110 and a processor. The continuous conveyor belt 102 receives the object 112 and moves the object 112 in forward direction. The first electromagnetic radiation sensor scans the object 112 that is travelling through the continuous conveyor belt 102. The tunnel 106 receives the object 112 from the continuous conveyor belt 102 after scanned through the first electromagnetic radiation sensor 104. The second electromagnetic radiation sensor is positioned inside the tunnel 106 at entry point. The electromagnetic radiation generator 108 receives a second signal from the second electromagnetic radiation sensor to generate an angular beam of electromagnetic radiation on the object 112.

Abstract: An apparatus includes processing circuitry configured to output, to a plurality of devices, an initial superframe configured in an initial superframe mode of a plurality of superframe modes. Each superframe mode of the plurality of superframe modes allocating each slot of a plurality of slots for wireless communication to a first protocol, a second protocol, or a third protocol. In response to determining a change in bandwidth, the processing circuitry is configured to select an updated superframe mode from the plurality of superframe modes. The processing circuitry is further configured to output, to the plurality of devices, an updated superframe configured in the updated superframe mode.

Abstract: A biometric identification system uses inputs acquired using different modalities. A model having an intersection branch and an XOR branch is trained to determine an embedding using features present in all modalities (an intersection of modalities), and features that are distinctive to each modality (an XOR of that modality relative to the other modality(s)). During training, a first loss function is used to determine a first loss value with respect to the branches. Probability distributions are determined for the output from the branches, corresponding to the intersection and XORs of each modality. A second loss function uses these probability distributions to determine a second loss value. A total loss function for training the model may be a sum of the first loss and the second loss. Once trained, the model may process query inputs to determine embedding data for comparison with embedding data of a previously enrolled user.

Abstract: Various face discrimination systems may benefit from techniques for providing increased accuracy. For example, certain discriminative face verification systems can benefit from L2-constrained softmax loss. A method can include applying an image of a face as an input to a deep convolutional neural network. The method can also include applying an output of a fully connected layer of the deep convolutional neural network to an L2-normalizing layer. The method can further include determining softmax loss based on an output of the L2-normalizing layer.

Abstract: Capacitor pads and methods of manufacturing the same are disclosed herein. An example apparatus disclosed herein includes a substrate to support a die, and a die-side capacitor pad on the substrate, the die-side capacitor pad including a plurality of distinct pad portions, the distinct pad portions spaced apart from one another.

Abstract: An electro-optical system having one or more electro-optical devices integrally formed within a substrate and associated methods are disclosed. An electro-optical system including an electro-optic switch is shown. An electro-optical system including an electro-optic modulator is shown. An electro-optical system including an optical resonator is shown.

Abstract: Systems and methods for providing resilient persistent connections for communication are disclosed. Methods include identifying, at a first device, a second device registered with a client connection service; obtaining, from the client connection service, a first resource identifier for delivering request messages to the second device via the client connection service; identifying, based on the obtained first resource identifier, a first target resource for a first request message directed to the second device, wherein the first target resource specifies a first host included in the client connection service; sending, to the client connection service via the data communication network, the first request message to the first target resource for delivery to the second device by the client connection service; and receiving, from the client connection service via the data communication network, a first response message provided by the second device as a response to the first request message.

Abstract: Systems and methods for providing resilient persistent connections for communication are disclosed. Methods include identifying, at a first device, a second device registered with a client connection service; obtaining, from the client connection service, a first resource identifier for delivering request messages to the second device via the client connection service; identifying, based on the obtained first resource identifier, a first target resource for a first request message directed to the second device, wherein the first target resource specifies a first host included in the client connection service; sending, to the client connection service via the data communication network, the first request message to the first target resource for delivery to the second device by the client connection service; and receiving, from the client connection service via the data communication network, a first response message provided by the second device as a response to the first request message.

Abstract: Provide herein is an ink that can be coated onto a substrate such as a glass slide. The use of at least two distinct wax treated silica powders with different porosities provides the multipurpose functionality of thermal and inkjet printing onto an ink coated substrate for purposed, for example, of labeling.

Abstract: An apparatus includes processing circuitry configured to output, to a plurality of devices, an initial superframe configured in an initial superframe mode of a plurality of superframe modes. Each superframe mode of the plurality of superframe modes allocating each slot of a plurality of slots for wireless communication to a first protocol, a second protocol, or a third protocol. In response to determining a change in bandwidth, the processing circuitry is configured to select an updated superframe mode from the plurality of superframe modes. The processing circuitry is further configured to output, to the plurality of devices, an updated superframe configured in the updated superframe mode.

Abstract: An apparatus includes processing circuitry configured to output, to a plurality of devices, an initial superframe configured in an initial superframe mode of a plurality of superframe modes. Each superframe mode of the plurality of superframe modes allocating each slot of a plurality of slots for wireless communication to a first protocol, a second protocol, or a third protocol. In response to determining a change in bandwidth, the processing circuitry is configured to select an updated superframe mode from the plurality of superframe modes. The processing circuitry is further configured to output, to the plurality of devices, an updated superframe configured in the updated superframe mode.

Abstract: A method and system are provided where a module employing reinforcement learning (RL) can learn to solve the vehicle selection and space allocation problems for the transportation and/or storage of goods. In one embodiment, a method includes: (a) obtaining a specification of a load that includes enclosures of one or more enclosure types, and the specification includes, for each enclosure type: (i) dimensions of an enclosure of the enclosure type, and (ii) a number of enclosures of the enclosure type. The method also includes (b) obtaining a specification of vehicles of one or more vehicle types, where the specification includes, for each vehicle type: (i) dimensions of space available within a vehicle of the vehicle type, and (ii) a number of vehicles of the vehicle type that are available for transportation. The method further includes (c) providing a simulation environment for simulating loading of a vehicle.

Abstract: A method, computer readable medium, and system are disclosed for performing unconstrained appearance-based gaze estimation. The method includes the steps of identifying an image of an eye and a head orientation associated with the image of the eye, determining an orientation for the eye by analyzing, within a convolutional neural network (CNN), the image of the eye and the head orientation associated with the image of the eye, and returning the orientation of the eye.