Abstract: A training engine is described which has a memory arranged to access a neural network image classifier, the neural network image classifier having been trained using a plurality of training images from an input space, the training images being labeled for a plurality of classes. The training engine has an adversarial example generator which computes a plurality of adversarial images by, for each adversarial image, searching a region in the input space around one of the training images, the region being one in which the neural network is linear, to find an image which is incorrectly classified into the plurality of classes by the neural network. The training engine has a processor which further trains the neural network image classifier using at least the adversarial images.

Abstract: This disclosure describes a system and a method for assigning pixels within agricultural imagery collected from overhead platforms to one or more classes based on spectral and/or spatial content. The system comprises one or more hardware processors configured by machine-readable instructions to: receive output signals provided by one or more remote sensing devices mounted to an overhead platform, the output signals conveying information related to one or more agricultural images; and assign pixels within the agricultural images to one or more classes based on spectral and/or spatial content of the agricultural images, wherein the one or more classes include a signal class and a noise class.

Abstract: A device for detecting and marking ticks and tick bites on a body or limb. The device has an image capturing device that is in communication with image recognition software. Images of skin are analyzed to detect objects consistent with ticks or tick bites. Once such object is detected, the device automatically disperses a marking material in the proximity of the detected tick or tick bite.

Abstract: A target object detection system includes a detection unit and a machine learning unit. The detection unit obtains an image and outputs a notification signal upon determining that a portion of the image resembles a target object by performing a classification operation. The machine learning unit performs a training operation using the image to obtain new weak classifier parameters for update in the detection unit when a determination made using weak classifier parameters used in the classification operation of the detection unit differs from one made using strong classifier parameters.

Abstract: A transformed image is received. The transformed image includes an other-than-visible light image that has been captured using a transformation device. A region of the transformed image is isolated, the region being less than an entirety of the transformed image. By applying to the region a convolutional Neural Network (CNN) which executes using a processor and a memory, and by processing only the region of the transformed image, an object of interest is detected in the region. Upon detecting, an indication is produced to indicate the presence of the object of interest in the region.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for image processing using deep neural networks. One of the methods includes receiving data characterizing an input image; processing the data characterizing the input image using a deep neural network to generate an alternative representation of the input image, wherein the deep neural network comprises a plurality of subnetworks, wherein the subnetworks are arranged in a sequence from lowest to highest, and wherein processing the data characterizing the input image using the deep neural network comprises processing the data through each of the subnetworks in the sequence; and processing the alternative representation of the input image through an output layer to generate an output from the input image.

Abstract: A method for classifying images using a neural network is described. The method utilizes the neural network to generate a deep hash data structure. In one embodiment, the method includes receiving, at a neural network, first data corresponding to a plurality of images of a training image set. The method includes adjusting parameters of the neural network based on concurrent application at the neural network of multiple loss functions to second data corresponding to the plurality of images to generate adjusted parameters. The method includes generating a deep hash data structure based on the adjusted parameters of the neural network. The method further includes sending, via a transmitter to a device, third data corresponding to the deep hash data structure.

Abstract: A card reader may include a main body frame having a card passage, and a bezel which having a card insertion port and attached to a front end side portion of the main body frame. In a case that a width direction of the card is referred to as a first direction and a portion of the main body frame which is covered by the bezel is referred to as a frame front end part, the bezel includes width direction cover parts respectively covering both sides in the first direction of the frame front end part, both ends in the first direction of the frame front end part are opened, and the frame front end part is structured so that side faces in the first direction of the card passage are structured by the width direction cover parts of the bezel which serve as guide faces for a card.

Abstract: A printing apparatus determines whether or not predetermined processing in accordance with a predetermined shape of a medium is executed on an image of a printing target. In a case where it is determined that the predetermined processing is not executed on the image of the printing target, the printing apparatus executes the predetermined processing on the image of the printing target to perform printing. In a case where it is determined that the predetermined processing is executed on the image of the printing target, the printing apparatus prints the image of the printing target on which the predetermined processing is not executed.

Abstract: To prevent the occurrence of a difference in printing results depending on a printer driver to be used despite that the drawing command originates from a GDI application and is the same. An information processing apparatus including a printer driver configured to generate print data compatible with a printing apparatus from input XPS format drawing data, and in the case where the input XPS format drawing data is XPS format drawing data converted by a conversion module from GDI format drawing data that is generated based on print processing of a GDI application and the XPS format drawing data includes a graphics drawing command specifying an object width of 0, the printer driver changes the graphics drawing command into a graphics drawing command specifying drawing with the minimum object width that can be represented by the printing apparatus and generates the print data based on the drawing data including the graphics drawing command after the change.

Abstract: In a pixel of a part where two objects are superimposed, pixel values of the objects are compared to thereby set an attribute of the pixel to an attribute of one of the objects.

Abstract: A print control apparatus includes a receiving unit receiving a print instruction; a first converting unit converting a dimension of a sheet of paper specified in a first unit in the print instruction to a dimension in a second unit different from the first unit; a second converting unit converting the dimension in the second unit to a dimension in a third unit employed by a print apparatus; an acquiring unit acquiring, from the print apparatus, information regarding a standard dimension list in the third unit; a selecting unit selecting, from the information, a standard dimension that matches, within a preset tolerance range, the dimension in the third unit; a generating unit generating print data by processing the print instruction by using the selected dimension; and an output controller specifying the selected dimension to control output of the print apparatus on the basis of the print data.

Abstract: A system and method for arranging shipment and insurance for items being shipped in containers with memory devices. An intelligent shipping agent may receive a request to ship an item. The intelligent shipping agent may search a database or solicit quotations to obtain shipping and insurance services for an item to be shipped from an origination to a final destination. The intelligent agent may find an entry in the database or may select a vendor based on received quotations. The selection may maximize value of a product or service at the lowest cost. The memory device may store shipping and insurance information related to the item being shipped in a data file. The memory device may include input devices and sensors to gather and store information before, during and after shipment.

Abstract: A method and apparatus to authenticate a tamper resistant seal that includes a population of particles embedded in an adhesive, the population including at least one micromachine artifact of a predetermined physical shape.

Abstract: Provided is a method for encoding chipless RFID tags in real-time. The method includes exposing a chipless RFID transponder to a conductive material, the RFID transponder comprising an antenna and a plurality of resonant structures, the plurality of resonant structures together defining a first spectral signature. Each of the plurality of resonant structures includes a respective one of a frequency domain. The method also includes depositing a conductive material on at least one of the resonant structures to short the at least one of the resonant structures. The remainder of the plurality of resonant structures that are not shorted by the conductive material define a second spectral signature for the RFID transponder.

Abstract: A barcode evaluation device is configured to conduct an evaluation, which involves determining whether or not a barcode image is displayable on an image display device and determining whether or not the barcode image is readable with a barcode reading device. The evaluation is conducted based on specifics of the barcode image, specifications of the image display device, and specifications of the barcode reading device without actually displaying and reading the barcode image.

Abstract: A method of generating a semi transparent QR code in which a QR code image and an ordinary color background image are synthesized, and a QR code detection method of separating a QR code and a normal color image from an image obtained by capturing a semi transparent QR code are disclosed.

Abstract: The present disclosure relates to a measuring device and an execution method thereof characterized in that open/close status of a cover body over a can body is recognized, the cover body is unscrewed or extracted from the can body, status of the cover body separated from the can body is detected by an electronic module mounted on the cover body, and the electronic module transmits a message to an appliance with the cover body totally separated from the can body.

Abstract: An RFID transponder (100), comprising a printable surface (1), an antenna element (2), an IC (3), and a ground plane (4) arranged under the antenna element (2). The ground plane (4) comprises one or more opening(s) (6) through said ground plane (4) for enabling near field communication through the ground plane (4).

Abstract: A transaction card includes a monolithic ceramic card body having one or more pockets, and at least one of a magnetic stripe, a barcode, and a laser signature portion. The one or more pockets may be configured to receive at least one of the magnetic stripe, the barcode, a contact chip module, a contactless chip module, a dual interface chip module, a booster antenna, a hologram or commercial indicia. A transaction card may also include a substrate layer having a first side and a second side. A first ceramic layer is connected to the first side of the substrate layer.

Abstract: A multilayer wiring coupling dual interface card carrier tape module is provided, including: a carrier tape base layer, an electrode diaphragm layer, a tuning capacitance layer, a radio-frequency identification coil layer, a bonding pad and a via hole. One surface of the carrier-band base layer is the front surface of the carrier-band module, and the other surface of the carrier-band base layer is the back surface of the carrier-band module. The electrode diaphragm layer and the tuning capacitance layer are located on the front surface of the carrier-band base layer, and the radio-frequency identification coil layer and the bonding pad are located on the back surface of the carrier-band base layer. The bonding pad is arranged according to a pin position of a chip. Hole metallization processing is conducted on the via hole for realizing an electrical connection between the electrode diaphragm layer and the bonding pad.

Abstract: A method for authenticating a closure assembly of a container including a closure and an over pack covering at least the closure. The overpack including a first radio frequency identification tag having a first unique identifier, the method includes reading the first unique identifier the closure including a second radio frequency identification tag including a second unique identifier and a storage unit including at least data relating to an overpack/closure pair including the unique identifiers of a closure and an overpack associated with the closure reading the first unique identifier and comparing the identifiers of the overpack and of the closure thus read to verify that the pair being authenticated does coincide with the pair defined in the data assembly, emitting a communication signal corresponding to the result of the verification, the closure assembly including means for destroying at least one of the identification tags when the container is opened.

Abstract: In various embodiments, a chip card module for a chip card is provided. The chip card module may include a carrier with a first side and an opposite second side, a chip arranged over the first side of the carrier, an antenna arranged over the carrier. The antenna may be electrically conductively coupled to the chip and configured to inductively couple to a second antenna formed on a chip card body of the chip card. The chip card module may further include a capacitor electrically conductively coupled to the chip, the capacitor including a first electrode arranged over the first side of the carrier, and a second electrode arranged over the second side of the carrier.

Abstract: Provided are an information recording object and a reading device devised so that embedded information is difficult to guess. The information recording object 30 provided with a combined image comprising an image C1 printed in a lustrous layer 31 and an image C2 formed on the image C1 and printed in a transparent layer 32 is characterized in that: the image C1 and the image C2 are each printed with an ink for which the amount of reflected light differs according to viewing angle; for the combined image, one image is visible depending on the viewing angle; the image C2 is an image in which there is a regularity in feature points in a spatial frequency domain F2; and the image C1 is an image in which the feature points in a spatial frequency domain F1 are disposed at positions that block said regularity.

Abstract: Techniques are described herein that are capable of implementing a context-aware digital personal assistant (DPA) that supports multiple accounts and/or facilitating interaction among digital personal assistants. For example, a user may be signed-in with accounts of a DPA. Content from content streams associated with the respective accounts may be selectively combined based on at least the user's context. In another example, users who are signed-in with accounts of a DPA may share a user experience provided by the DPA. Content from content streams associated with the respective accounts may be selectively combined based on at least one or more of the users' context. In yet another example, a first DPA associated with a first user may be caused to perform an operation on behalf of a second DPA associated with a second user or to delegate the operation to the second DPA.

Abstract: A neural network processing system includes one source node having a source memory and a source core, and one destination node having a destination memory and a destination core, the source core and the destination core being von-Neumann cores, the destination memory including weight data storage areas for storing weight data corresponding to each node, an accumulation memory for accumulating the weight data, and an event address memory, the destination core identifying the weight data storage area and accumulating the weight data to store the accumulated weight data in the accumulation memory, the source memory including a data set having first information for identifying the destination node and second information for identifying the weight data storage area, and the source core reading the data set and sending the second information in the data set to the destination node to conduct remote memory write.

Abstract: A system receives and executes a sequence of tensor instructions, for example, instructions for performing a neural network computation. The system may be implemented as a multiprocessor architecture, for example, hardware for performing a neural network computation. A tensor instruction specifies a tensor computation receiving one or more input tensors for determining an output tensor. The system stores a decimal position associated with a plurality of values of a tensor. The system performs the tensor computation of a tensor instruction to determine a plurality of values of the output tensor. The system collects statistics describing the plurality of values of the output tensor and determines a decimal position for the plurality of values based on the collected statistics.

Abstract: A computer-based method includes receiving an input signal at a neuron in a computer-based neural network that includes a plurality of neuron layers, applying a first non-linear transform to the input signal at the neuron to produce a plain signal, and calculating a weighted sum of a first component of the input signal and the plain signal at the neuron. In a typical implementation, the first non-linear transform is a function of the first component of the input signal and at least a second component of the input signal.

Abstract: Self-organizing logic gates formed from a combination of memristor devices and dynamic correction modules configured to provide a stable operation upon application of a signal to any terminal. A SOLG of the invention can accept signals from any terminal and does not require an absence of signals at any other terminal. Terminal signals can superpose and the gate finds equilibrium, if an equilibrium exists.

Abstract: Described is a system for decoding spiking reservoirs even when the spiking reservoir has continuous synaptic plasticity. The system uses a set of training patterns to train a neural network having a spiking reservoir comprised of spiking neurons. A test pattern duration d is estimated for a set of test patterns P, and each test pattern is presented to the spiking reservoir for a duration of d/P seconds. Output spikes from the spiking reservoir are generated via readout neurons. The output spikes are measured and the measurements are used to compute firing rate codes, each firing rate code corresponding to a test pattern in the set of test patterns P. The firing rate codes are used to decode performance of the neural network by computing a discriminability index (DI) to discriminate between test patterns in the set of test patterns P.

Abstract: Described is a sparse inference module that can be incorporated into a deep learning system. For example, the deep learning system includes a plurality of hierarchical feature channel layers, each feature channel layer having a set of filters. A plurality of sparse inference modules can be included such that a sparse inference module resides electronically within each feature channel layer. Each sparse inference module is configured to receive data and match the data against a plurality of pattern templates to generate a degree of match value for each of the pattern templates, with the degree of match values being sparsified such that only those degree of match values that exceed a predetermined threshold, or a fixed number of the top degree of match values, are provided to subsequent feature channels in the plurality of hierarchical feature channels, while other, losing degree of match values are quenched to zero.

Abstract: A hardware-based programmable deep learning processor (DLP) is proposed, wherein the DLP comprises with a plurality of accelerators dedicated for deep learning processing. Specifically, the DLP includes a plurality of tensor engines configured to perform operations for pattern recognition and classification based on a neural network. Each tensor engine includes one or more matrix multiplier (MatrixMul) engines each configured to perform a plurality of dense and/or sparse vector-matrix and matrix-matrix multiplication operations, one or more convolutional network (ConvNet) engines each configured to perform a plurality of efficient convolution operations on sparse or dense matrices, one or more vector floating point units (VectorFPUs) each configured to perform floating point vector operations, and a data engine configured to retrieve and store multi-dimensional data to both on-chip and external memories.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for using recurrent neural networks to analyze health events. One of the methods includes: processing each of a plurality of initial temporal sequences of health events to generate, for each of the initial temporal sequences, a respective network internal state of a recurrent neural network for each time step in the initial temporal sequence; storing, for each of the initial temporal sequences, one or more of the network internal states for the time steps in the temporal sequence in a repository; obtaining a first temporal sequence; processing the first temporal sequence using the recurrent neural network to generate a sequence internal state for the first temporal sequence; and selecting one or more initial temporal sequences that are likely to include health events that are predictive of future health events in the first temporal sequence.

Abstract: Methods, systems, and apparatus include computer programs encoded on a computer-readable storage medium, including a system for providing content and that includes subsystems. An attribute inference subsystem analyzes content items and tags each content item with attributes that may affect performance and that are related to attribute types selected from a group comprising content concepts, format, included content, semantics or syntax. Attributes can be identified by the attribute inference subsystem or a sponsor of a respective content item. An analysis subsystem evaluates a log of served content items that have been tagged to identify salient attributes related to one or more performance metrics and inferences related to the identified salient attributes. An experiment subsystem automatically creates one or more experiments to substantiate the inferences related to the identified salient attributes.

Abstract: Ontology-based reasoning apparatus and method using knowledge of an expert are disclosed. The ontology-based reasoning apparatus includes an input unit through which a plurality of the knowledge of the expert including a condition and a result are inputted, a conversion unit configured to convert the inputted knowledge to ontology-based rules, and a reasoning performing unit configured to reason a conclusion by using the converted rules and generate an explanation of a rule corresponding to cause of the conclusion. Here, the rule includes a condition node corresponding to the condition, a result node corresponding to the result and an edge for connecting the condition node to the result node, the edge includes an edge direction and an edge value, and the edge value corresponds to an explanation about relation between the condition node and the result node.

Abstract: The invention relates to a system for visualizing and simulating personal knowledge structures in a company which has one or more business units. It comprises a first server for storing a first dataset, which describes a model of the company structure, wherein for each employee position in the company an employee target profile is defined, which comprises an employee target competence profile; and for storing a second dataset, which specifies the sales achieved for the individual business units; and for storing a third dataset, which depicts recorded employee actual competence profiles. Furthermore, it contains a second server which comprises a program that calculates a plurality of indexes based on the data of the first dataset, second dataset, and third datasets, in particular the human potential and/or the economic temperature.

Abstract: A computer implemented method comprising: inputting steps of at least two processes into the computer; storing process step input products and process step output products in a shared, non-transitory database as they are generated; establishing an input product filter for each process step with performance-triggering-criteria-defined property/value filters, where one step's output product passes the input product filter of another step; periodically searching the shared database for input products; determining whether each step in any of the processes has been executed, is in the process of being executed, or is awaiting execution; dynamically and automatically assembling or altering a set of steps composing any given process depending on the input products available in the shared database; and comparing the input/output products property values to target property values to automatically assess the status, effectiveness and efficiency of the individual steps and each process as a whole.

Abstract: Described is system for data classification using formal concept analysis (FCA). In a training phase, the system generates a FCA classification lattice, having a structure, using a set of training data. The set of training data comprises training presentations and classifications corresponding to the training presentations. In a classification phase, a set of test data having classes that are hierarchical in nature is classified using the structure of the FCA classification lattice.

Abstract: Systems and methods for enhancing exploratory data analysis using a recommender system are provided. The recommender system receives feedback when a set of raw data is analyzed (e.g., from one or more data analysts exploring a data set). Based on the collected feedback, the recommender system can automatically infer the need for certain analytical operations to be performed on a data set. These inferences can be used by the recommender system to infer analytical operations when new data sets are analyzed.

Abstract: A database comprises historical information of a user's response to previous notifications. The database is accessed to determine a time at which to provide a (new) notification to the user, utilizing at least: a) current user activity status (e.g., determined from measurement information collected from one or more personal devices and/or user calendar events; b) time/day; and c) context information about the notification (e.g., geo-location, indoors/outdoors) including notification type (e.g., calendar entry, email, IM). The user gets the notification via a portable device at the determined time. A machine learning model can select the determined time by discriminating features of the previous notifications for which the user immediately attended versus those that were deferred and/or ignored. Content of the notification can also be altered in view of such discriminating features so as to increase a likelihood the user will immediately attend to the provided notification.

Abstract: In one aspect, a system for pre-fetching performance data in a monitored environment is disclosed. The system can include a processor; a memory; and one or more modules stored in the memory. The one or more modules are executable by the processor to perform operations including: record queries that request for application performance data with latencies longer than a threshold; learn access patterns in the recorded queries with latencies longer than the threshold; pre-fetch and cache the application performance data requested by the recorded queries before the same recorded queries are requested next time; and provide the pre-fetched application performance data from the cache when the same recorded queries are requested next time.

Abstract: Knowledge inference apparatus and method to determine emerging industrial trends and adapt strategic reasoning thereof are provided. In some aspects, user data, user stimulus-responses and user tracked data is received at a knowledge inference apparatus from multiple compute devices. The knowledge inference apparatus can generate compressed multidimensional profiles corresponding to multiple users and infer based on the received data, and the compressed multidimensional profiles multiple emerging trends developing in an industry. In some other aspects, the knowledge inference apparatus can further develop individualized strategic information for the multiple users to adequately respond to the inferred emerging trends.

Abstract: Provided is a numerical controller that is capable of determining a proper timing of swarf discharge and allows an operator to change a swarf discharge method and examine appropriateness of the timing of the swarf discharge on an as needed basis, the numerical controller including a simulation unit that executes a simulation in which a workpiece is machined based on a machining program, a rendered workpiece volume calculation unit that calculates the volume of a rendered workpiece representing the shape of the workpiece rendered by the simulation, and a swarf accumulation amount prediction unit that predicts, based on the volume of the initial rendered workpiece when execution of the simulation is started and the volume of the rendered workpiece when execution of each block included in the machining program is completed, a swarf accumulation amount when the execution of the block is completed.

Abstract: Systems, methods, and computer-readable media for simulating the course of an event or for collecting data for the simulation are provided. A processing unit can receive attributes of synthetic populations and corresponding forecasts of progress of an event, e.g., an epidemic. The processing unit can determine a disease model based on the forecasts and historical data of the event. The disease model can be associated with at least one attribute of each of the synthetic populations. The processing unit can determine a forecast of the progress of the event based on the received forecasts and weights associated with user accounts. In some examples, the processing unit can receive the attributes, present via a user interface a plurality of candidate forecasts of an epidemic, and receive via the user interface a forecast, e.g., rankings or data, of the epidemic with respect to the synthetic population indicated by the attributes.

Abstract: Systems and methods for probability forecasts and an energy transmission and/or energy distribution network are provided. Operational management may be carried out using a network control system with systematic consideration of forecast uncertainties. The probability of a distribution network being operable in a stable manner (e.g., with N-1 certainty) in a planning period is included. The system includes a forecaster for forecasts for a planning period, a forecast analyzer connected to the forecasts from the at least one forecaster, and elements for further information for outputting estimated forecast uncertainties. The system also includes a stability probability analyzer connected to the forecasts from the at least one forecaster, the estimated forecast uncertainties from the forecast analyzer, and elements for further information for outputting at least one item of information relating to an N-1 stability of the distribution network in the planning period.

Abstract: A system and method that includes receiving a problem request and publishing the problem request through a computing platform; accepting a set of responses to the problem request during an ideation stage; at a similarity engine of the computing platform, consolidating the set of responses to a set of base responses; retrieving judgments on base response comparisons of the set of base responses during a judgment stage; and generating a response report for the problem request.

Abstract: Ontology reasoning method and apparatus are disclosed. The ontology reasoning method comprises (a) broadcasting a schema triple to nodes; (b) partitioning triples other than the schema triple and distributing the partitioned triples to the nodes; and (c) reasoning at least one of the schema triple or the triples according to a reasoning rule and then renewing a confidence value of the reasoned triple.

Abstract: Embodiments of the present disclosure allow accuracy of prediction of pollution to be improved. In operation, a prediction of pollution in a future time period is determined. The prediction of pollution indicates predicted data related to a pollution index. Then, matching historical data for the predicted data is determined from historical data related to the pollution index. The matching historical data is obtained in a historical time period corresponding to the future time period. Based on the matching historical data, the prediction of pollution is refined.

Abstract: An information processing system includes: a setting unit to set a normal range showing a range of normal values of monitoring target data of time series signals by defining an upper limit and a lower limit; a determination unit to determine whether the monitoring target data is out of the normal range or not and to feed the determined time which is output in case of deviation and which is judged to be the time for the monitoring target data to turn to be out of the normal range; and a detection unit to determine the start time that is before the determined time entering from the determination unit and which is the time for the monitoring target data to start to show an anomaly on the basis of the degree of deviation showing a deviation of the monitoring target data from a mean of multiple learning data which consist of normal value signals from among already-acquired monitoring target data. This enables the system to more accurately determine the time for the signal to start to show an anomaly.

Abstract: A cognitive state prediction method, system, and non-transitory computer readable medium, include a receiving circuit configured to receive an electronic message sent by a first user, a labeling circuit configured to query a second user to associate a label with the electronic message based on a cognitive state of the first user, and a correlating circuit configured to correlate the label with user data at a time of sending the electronic message, the user data corresponding to data output by at least one of the wearable and an external sensor in a database.