Abstract: A system of wireless advertising platform has a handheld wireless device that has an inbound wireless data function with a storage function to be able to receive and store, audio, text, image, and flash commercial messages from a message server. The device has a message exposure function that exposes these messages to a device user from the stored memory of the device into the incoming and outgoing communication, to and from the device user. The device has a message tracking function that tracks which messages have been exposed and periodically sends an account record to the message server. The message server receives the account records and uses cumulative account records to create billing statements to the message providers. The communication use cost of the device is discounted to the device user for being exposed messages from revenue from message providers.

Abstract: We describe an artificial neural network comprising: an input layer of input neurons, one or more hidden layers of neurons in successive layers of neurons above the input layer, and at least one further, concept-identifying layer of neurons above the hidden layers. The neural network includes an activation memory coupled to an intermediate, hidden layer of neurons between the input concept-identifying layers to store a pattern of activation of the intermediate layer. The neural network further includes a system to determine an overlap between a plurality of the stored patterns of activation and to activate in the intermediate hidden layer an overlap pattern such that the concept-identifying layer of neurons is configured to identify features of the overlap patterns. We also describe related methods, processor control code, and computing systems for the neural network. Optionally further, higher level concept-identifying layers of neurons may be included.

Abstract: Systems and methods for optimizing artificial neural network (ANN) computations based on automatic determination of a batch size are disclosed. An example method may comprise receiving, by an optimization module, an ANN structure associated with the ANN, and generating, based on the ANN structure, a configuration for a computation engine capable of performing computation of the layers of the ANN. The configuration may include information concerning a batch size of one or more layers of the ANN. The batch size of a layer can be determined based on a bandwidth required to read data related to layer, a number of parameters associated with the layer, and a time the layer processes one input dataset from the batch. The batch size of the layer can differ from the batch size of the ANN. The batch size of the layer may differ from a batch size of another layer of ANN.

Abstract: A centrifugal separator and a method of controlling a centrifugal separator are disclosed. The centrifugal separator includes a rotor delimiting therein a separation space, an inlet for liquid feed mixture, a first outlet for heavy phase, a second outlet for light phase, and at least one channel extending towards a central portion of the rotor. The method includes separating liquid feed mixture into at least the heavy phase and the light phase in the separation space, and determining at the first outlet that a pressure build-up period has passed, and thereafter determining that an abrupt pressure change takes place at the first outlet, and controlling the centrifugal separator in response to the abrupt pressure change.

Abstract: Data processing systems for identifying new indications for a drug can include a computer-readable memory including computer-executable instructions; and at least one processor configured to execute executable logic including the computer-executable instructions and at least one machine learning model to perform one or more operations. The one or more operations can include receiving data representing medical records of a plurality of patients; selecting a set of patients; determining a plurality of patient characteristics of the set of patients; grouping, in accordance with the plurality of patient characteristics, the set of patients to generate a plurality of distinct groups, each of the distinct groups including at least one patient of the set of patients; selecting, based on one or more group selection criteria, a set of distinct groups of the plurality of distinct groups; and identifying one or more relevant patient characteristics by analyzing each distinct group of the set of distinct groups.

Abstract: In embodiments, a processing device detects a margin line in a model of a preparation from one or more images. The processing device determines, for each segment of a plurality of segments of the margin line, a quality score for the segment. The processing device determines that a segment of the margin line has a quality score that is below a quality threshold, wherein the segment of the margin line was generated based on a first set of images. Responsive to determining that the segment of the margin line has the quality score that is below the quality threshold, the processing devices updates the three-dimensional model of the preparation by replacing a portion of the three-dimensional model associated with the segment of the margin line with image data from at least one of a new image or a second set of images.

Abstract: Systems and methods are described for a virtual sensor that determines an amount of grain loss during operation of a combine harvester without any direct measurement of grain loss. An electronic controller is configured to determine values for a set of operating conditions including a plurality of sensor values and actuator settings. The electronic controller then applies an artificial neural network that is configure to receive as inputs the values for the set of operating conditions and to produce as an output a value indicative of an estimate amount of grain loss.

Abstract: The disclosure describes, in part, techniques for performing pre-authorization during a transaction between a merchant a customer. For instance, a payment service may receive, from a merchant device, payment information of a payment instrument that is used to satisfy a cost of a first item. The payment service may then send an authorization request to a card payment network to hold a first amount of funds based on previous purchase activity. The payment service may further send the merchant device information associated with the customer. Next, the payment service may receive an indication that the customer requests to purchase a second item. In response, the payment service may send a request to the card payment network to capture a second amount of funds that is based on the cost of the first item and a cost of the second item. In response, the payment service may receive approval from the card payment network.

Abstract: Systems and methods are disclosed to update ads on user devices that may connect to a network only intermittently by predicting and tracking various metrics associated with ads delivered to the user devices. An example method may include determining a first set of ads that were presented at a first semi-connected device while the first semi-connected device was disconnected from a network, determining a first device identifier associated with the first semi-connected device, and determining, based at least in part on the first device identifier, a first estimated number of ad impressions for a first ad. Example methods may include determining, based at least in part on the first estimated number of ad impressions, that the first semi-connected device is to be updated with the first ad, causing the first ad to be sent to the first semi-connected device, and causing at least one ad of the first set of ads to be removed from the first semi-connected device.

Abstract: An electronic apparatus is provided.

Abstract: A device may receive access information that permits access to messages associated with an electronic messaging account. The device may process the messages associated with the electronic messaging account to identify one or more of the messages that include at least one coupon after receiving the access information. The one or more of the messages may be identified using at least two of an image processing technique, a text processing technique, or a code processing technique. The device may store information identifying the one or more of the messages that include the at least one coupon after processing the messages. The device may perform one or more actions to facilitate use of the at least one coupon in association with completing a transaction.

Abstract: Methods and systems for AP location based content presentation are provided. According to one embodiment, a web service receives from a widget executing within a web page requested by a wireless computing device of multiple wireless computing devices operating within an enterprise, a unique identifier of the wireless computing device. An access point (AP) identifier is determined for an AP of multiple APs of the enterprise that is servicing the wireless computing device by querying a log database with the unique identifier. AP specific content is displayed within the web page as a result of the web service retrieving the AP specific content from a content database based on the AP identifier and returning the AP specific content to the widget.

Abstract: Systems and methods for generating and actively improving clinical queues are provided. In one embodiment, a method includes generating, with a plurality of predictive models, a plurality of risk scores for each individual a plurality of individuals based on medical claims of each individual, transmitting a clinical queue to a client device associated with a healthcare provider, the clinical queue comprising a list of individuals prioritized for healthcare intervention based on the plurality of risk scores, receiving feedback from the client device regarding the clinical queue, and updating at least one predictive model of the plurality of predictive models based on the feedback. In this way, members may be identified for intervention in a timely manner, multiple assessment methods may be combined to generate clinical queues, and the assessment methods may be actively improved over time.

Abstract: A system and method for providing local approximations of query results are provided. The method includes querying a primary neural network with at least one test query, wherein the at least one test query includes a real test result derived from executing the at least one training query on a data set; receiving from the primary neural network a predicted test result in response to the at least one test query; sending, based on the predicted test result, a model of a primary neural network to a local machine; and storing the model of a local neural network of the local machine, wherein the local neural network is configured to generate a prediction in response to a user query received by the local machine.

Abstract: Some embodiments provide a method for training parameters of a network. the method receives a machine-trained (MT) network with multiple layers of computation nodes. Each computation node of a set of the layers computes an output value based on a set of input values and a set of trained weight values. A first layer of the MT network includes a first number of filters. The method replaces the first layer with (i) a second layer having a second number of filters that is less than the first number of filters and (ii) a third layer having the first number of filters. Output values of computation nodes of the second layer are quantized and the third layer using the quantized output values of the second layer as input values.

Abstract: A method for predicting side effects of a combination of drugs administered concurrently includes training a multi-modal cell complex neural network (MCXN) on a dataset. The MCXN includes nodes representing the drugs and proteins, pair-wise relationships between nodes representing interactions between pairs of drugs and/or proteins, and k-wise relationships between the nodes representing interactions between k drugs and/or proteins, where k¿2. The training dataset includes a list of drugs, a list of proteins, and pharmacological information about the drugs in the list of drugs and proteins in the list of proteins. A specification of the combination of at least three drugs to be administered concurrently is input to the MCXN which predicts probabilities that administering the combination of drugs concurrently results in potential side effects. It also predicts both frequencies of the potential side effects and severities of the potential side effects.

Abstract: Described are methods, devices and applications for learning noise distribution on information from any data processing method. In an embodiment of the described technology, a method includes determining an amount of shredding used in a shredding operation by which source data is converted into shredded data, and transferring the shredded data over an external network to a remote server for a data processing task. The shredding reduces the information content and incurs a limited degradation to an accuracy of the data processing task due to the shredding operation.

Abstract: Methods and systems are described that mark and/or correct margin lines and/or other features of dental sites. In one example a three-dimensional model of a dental site is generated from intraoral scan data of the dental site, the three-dimensional model comprising a representation of a preparation tooth. An image of the preparation tooth is received or generated. Data from the image is processed using a trained machine learning model that has been trained to identify margin lines of preparation teeth, wherein the trained machine learning model outputs a probability map comprising, for each pixel in the image, a probability that the pixel depicts a margin line. The three-dimensional model of the dental site is then updated by marking the margin line on the representation of the preparation tooth based on the probability map.

Abstract: A system, having a memory that stores computer executable components, and a processor that executes the computer executable components, reduces data size in connection with training a neural network by exploiting spatial locality to weight matrices and effecting frequency transformation and compression. A receiving component receives neural network data in the form of a compressed frequency-domain weight matrix. A segmentation component segments the initial weight matrix into original sub-components, wherein respective original sub-components have spatial weights. A sampling component applies a generalized weight distribution to the respective original sub-components to generate respective normalized sub-components. A transform component applies a transform to the respective normalized sub-components.

Abstract: A method of providing physiological self-regulation challenges prior to participating in a series of activities or exercises at a series of predefined locations includes determining a physiological goal associated with each location. A sensing device measures a physiological state of a user, and a mobile communication device communicates to a user whether or not the user has achieved the physiological goal for the challenge. The level of difficulty of the physiological goal may be reduced if the user does not meet the goal. The physiological goal may comprise a brain state that is conducive to learning, and the sensing device may be configured to measure brain state values representing cognitive engagement. Upon achievement of each physiological goal, the participant is provided with a reward such as information concerning the current predefined location and/or information concerning the next predefined location.