14th week of 2019 patent applcation highlights part 39 |
Patent application number | Title | Published |
20190102632 | Travel Lane Detection Method and Travel Lane Detection Device - A travel lane detection method detects travel lane boundaries according to a plurality of travel lane characteristic points detected by a target detection sensor installed in a vehicle. When a lane change of the vehicle is detected, the method determines continuity of the travel lane characteristic points detected before the lane change is completed with respect to the travel lane characteristic points detected after the lane change is completed while taking account of a lane change amount so as to detect the travel lane boundaries according to the continuity of the travel lane characteristic points. | 2019-04-04 |
20190102633 | TARGET OBJECT ESTIMATING APPARATUS - A target object estimating apparatus comprises parallax information calculating means for calculating parallax information including a parallax between corresponding pixels of taken images taken at a same computation timing, road surface region detecting means for detecting a road surface region in the taken image based on the parallax information, road surface region determining means for determining whether or not each pixel in the taken image corresponds to the road surface region, transition information calculating means for calculating transition information including a change amount of a position of each pixel, using temporally sequential taken images, and estimated value calculating means for estimating a position and a speed of a target object by calculating, based on the parallax/transition information, estimated values of the position and the speed of each pixel. The estimated value calculating means does not calculate the estimated values for a pixel determined to correspond to the road surface region. | 2019-04-04 |
20190102634 | PARKING POSITION DISPLAY PROCESSING APPARATUS, PARKING POSITION DISPLAY METHOD, AND PROGRAM - A parking position display processing apparatus includes: an image capturing unit that captures an image of a surrounding of a vehicle and generates a captured image; a vehicle information acquisition unit that acquires vehicle information of the vehicle; a vehicle surrounding state recognition unit that generates vehicle surrounding information which indicates a state of a surrounding of the vehicle based on the captured image and the vehicle information; a parking position calculation unit that calculates a planned parking position of the vehicle based on the vehicle surrounding information and the vehicle information; a composite image generation unit that generates a composite image from an image which represents the planned parking position and an image which represents the state of the surrounding of the vehicle in the planned parking position based on the planned parking position and the vehicle surrounding information; and a display unit that displays the composite image. | 2019-04-04 |
20190102635 | SYSTEM AND METHOD FOR REMOVING FALSE POSITIVES DURING DETERMINATION OF A PRESENCE OF AT LEAST ONE REAR SEAT PASSENGER - A system and method for removing false positives during determination of a presence of at least one rear seat passenger of a vehicle that include activating an image system to capture images of rear seats of the vehicle to determine the presence of the at least one rear seat passenger. The system and method additionally include deactivating the image system to cease capturing images of the rear seats of the vehicle. The system and method also include reactivating the image system to capture images of the rear seats of the vehicle to determine the presence of the at least one rear seat passenger. The system and method further include presenting a user interface notification that includes a video feed of the rear seats of the vehicle based on the determined presence of the at least one rear seat passenger. | 2019-04-04 |
20190102636 | VEHICULAR VISION SYSTEM USING SMART EYE GLASSES - A vision system for a vehicle includes a control and smart eye glasses worn by a driver of the vehicle. The smart eye glasses include a driver monitoring camera that has a field of view that encompasses at least one eye of the driver when wearing the smart eye glasses. The control includes an image processor that processes image data captured by the driver monitoring camera to determine drowsiness of the driver. Responsive to determination that the driver is drowsy, the control communicates a signal to a portable device in the vehicle and the portable device in the vehicle generates an alert to the driver. | 2019-04-04 |
20190102637 | HUMAN MONITORING SYSTEM INCORPORATING CALIBRATION METHODOLOGY - Related methods are provided for establishing a baseline value to represent an eyelid opening dimension for a person engaged in an activity, where the activity may be driving a vehicle, operating industrial equipment, or performing a monitoring or control function; and for operating a system for monitoring eyelid opening values with real time video data. | 2019-04-04 |
20190102638 | HUMAN MONITORING SYSTEM INCORPORATING CALIBRATION METHODOLOGY - Method for monitoring eyelid opening values. In one embodiment video image data is acquired with a camera which data are representative of a person engaged in an activity, where the activity may be driving a vehicle, operating industrial equipment, or performing a monitoring or control function. When the person's head undergoes a change in yaw angle, such that eyelids of both eyes of the person are captured with the camera, but one eye is closer to the camera than the other eye, a weighting factor is applied, which factor varies as a function of the yaw angle such that a value representative of eyelid opening data based on both eyes is calculated. | 2019-04-04 |
20190102639 | COMBINED BIOMETRIC RECOGNITION METHOD AND DEVICE - A method for biometrically recognizing individuals, comprising the following steps:
| 2019-04-04 |
20190102640 | ACCELERATING CONVOLUTIONAL NEURAL NETWORK COMPUTATION THROUGHPUT - Convolutional neural network (CNN) components can operate to provide various speed-ups to improve upon or operate as part of an artificial neural network (ANN). A convolution component performs convolution operations that extract data from one or more images, and provides the data to one or more rectified linear units (RELUs). The RELUs are configured to generate non-linear convolution output data. A pooling component generates pooling outputs in parallel with the convolution operations via a pipelining process based on a pooling window for a subset of the non-linear convolution output data. A fully connected (FC) component configured to form an artificial neural network (ANN) that provides ANN outputs based on the pooling outputs and enables a recognition of a pattern in the one or more images based on the ANN outputs. Layers of the FC component are also able to operate in parallel in another pipelining process. | 2019-04-04 |
20190102641 | DIGITAL NEUROMORPHIC (NM) SENSOR ARRAY, DETECTOR, ENGINE AND METHODOLOGIES - A system and methodologies for neuromorphic vision simulate conventional analog NM system functionality and generate digital NM image data that facilitate improved object detection, classification, and tracking. | 2019-04-04 |
20190102642 | METHOD AND APPARATUS FOR MONITORING REGION AROUND VEHICLE - In a monitoring apparatus, an optical flow calculator calculates an optical flow for each of selected pixel regions included in at least one pixel region group of an image. The optical flow for each of the selected pixel regions includes information about a direction and amount of movement of a corresponding part of the at least one target object. An adjuster calculates the sum of areas of all the pixel regions included in the at least one pixel region group of the image, and adjusts a selected number of the optical flows to be matched with the at least one pixel region group as a function of the calculated sum of the areas of all the pixel regions included in the at least one pixel region group. | 2019-04-04 |
20190102643 | IMAGE PROCESSING APPARATUS, IMAGE PROCESSING SYSTEM, IMAGE PROCESSING METHOD, AND STORAGE MEDIUM - An image processing apparatus configured to extract an object region corresponding to a predetermined object from an extraction target image based on image capturing performed by an image capturing apparatus includes an acquisition unit configured to acquire information about an image to be displayed on a display surface located in an image capturing range of the image capturing apparatus, an identification unit configured to identify, as a region from which extraction of the object region is not to be performed, a region corresponding to the display surface in the extraction target image, based on the information acquired by the acquisition unit, and an extraction unit configured to extract the object region formed by part of a plurality of pixels not included in the region identified by the identification unit among a pixel included in the extraction target image. | 2019-04-04 |
20190102644 | METHOD AND APPARATUS FOR VERIFYING AN OBJECT IMAGE IN A CAPTURED OPTICAL IMAGE - A mobile apparatus is provided that includes an image sensor for converting an optical image into an electrical signal. The optical image includes an image of a vehicle license plate. The mobile apparatus includes a license plate detector configured to process the electrical signal to recover information from the vehicle license plate image. Upon capturing of the video that includes the image, a device operation instructor will dynamically determine a highest score of assigned object image scores for each frame of the video generate an operation adjustment control if the determined highest score is less than a predetermined score threshold, which is in turn dynamically displayed during continuous capture of the video by the image sensor. | 2019-04-04 |
20190102645 | INFORMATION PROCESSING APPARATUS, INFORMATION PROCESSING METHOD, AND STORAGE MEDIUM - To appropriately perform blotting out processing for a portion that a user intends to prevent from being displayed for an electronic document having text information on a character string for search, along with image information. The information processing apparatus according to the present invention, in a case where the electronic document is an electronic document in a format searchable for a character string and where a character string obtained by performing OCR processing for a character image object existing in an area and a character string of an invisible text object existing in the area do not match with each other, a setting unit performs re-setting of an area to which blotting out processing is applied for at least one of the character image object and the invisible text object so that both the character strings match with each other. | 2019-04-04 |
20190102646 | IMAGE BASED OBJECT DETECTION - Systems and methods are disclosed for image-based object detection and classification. For example, methods may include accessing an image from an image sensor; applying a convolutional neural network to the image to obtain localization data to detect an object depicted in the image and to obtain classification data to classify the object, in which the convolutional neural network has been trained in part using training images with associated localization labels and classification labels and has been trained in part using training images with associated classification labels that lack localization labels; annotating the image based on the localization data and the classification data to obtain an annotated image; and storing, displaying, or transmitting the annotated image. | 2019-04-04 |
20190102647 | MARKER, METHOD OF DETECTING POSITION AND POSE OF MARKER, AND COMPUTER PROGRAM - A marker whose at least one of a position and pose with respect to a capturing unit is estimated includes: quadrilateral specifying points that specify a quadrilateral shape; a first circle group that is a group of a plurality of circles whose centers are present in a line of a first diagonal which is one of two diagonals of the specified quadrilateral shape, and which are included in the quadrilateral shape; a second circle group that is a group of a plurality of circles whose centers are present in a line of a second diagonal which is the other diagonal of the two diagonals than the first diagonal, and which are included in the quadrilateral shape; and a direction-identification point that specifies a direction of the quadrilateral shape. | 2019-04-04 |
20190102648 | SIMPLE PROGRAMMING METHOD AND DEVICE BASED ON IMAGE RECOGNITION - The disclosure discloses a method and device for image recognition. The method comprises: placing instruction blocks in a required order; acquiring an encoded instruction block image that represents the instruction block pattern and the placement order; recognizing a single instruction block image from the encoded instruction block image; comparing the single instruction block image with a standard instruction block image to obtain the matching degree of the instruction block; determining, according to the matching degree, standard instruction blocks corresponding to respective instruction block images; sorting the instruction block images according to the coordinates in the encoded instruction block image; parsing the instruction block images according to the sorting order to obtain instructions. The method for image recognition can help children learning concepts such as manipulation, use and programming of intelligent programmable devices more easily. | 2019-04-04 |
20190102649 | METHODS FOR OPTICAL CHARACTER RECOGNITION (OCR) - A method is provided for Optical Character Recognition (OCR). A plurality of OCR decoding results each having a plurality of positions is obtained from capturing and decoding a plurality of images of the same one or more OCR characters. A recognized character in each OCR decoding result is compared with the recognized character that occupies an identical position in each of the other OCR decoding results. A number of occurrences that each particular recognized character occupies the identical position in the plurality of OCR decoding results is calculated. An individual confidence score is assigned to each particular recognized character based on the number of occurrences, with a highest individual confidence score assigned to a particular recognized character having the greatest number of occurrences. Determining which particular recognized character has been assigned the highest individual confidence score determines which particular recognized character comprises a presumptively valid character for the identical position. | 2019-04-04 |
20190102650 | IMAGE EXTRACTION APPARATUS, IMAGE EXTRACTION METHOD, IMAGE EXTRACTION PROGRAM, AND RECORDING MEDIUM STORING PROGRAM - Provided are an image extraction apparatus and an image extraction method of finding a similar image conforming to a user's intention. A similarity determination condition designation window in which a plurality of similarity determination conditions are displayed is displayed. A user selects a desired similarity determination condition from among the plurality of similarity determination conditions displayed in the displayed similarity determination condition designation window. The user can determine a similarity determination condition, and can thus find a similar image conforming to the user's intention. | 2019-04-04 |
20190102651 | Fine-Grained Image Similarity - Methods, systems, and apparatus, for determining fine-grained image similarity. In one aspect, a method includes training an image embedding function on image triplets by selecting image triplets of first, second and third images; generating, by the image embedding function, a first, second and third representations of the features of the first, second and third images; determining, based on the first representation of features and the second representation of features, a first similarity measure for the first image to the second image; determining, based on the first representation of features and the third representation of features, a second similarity measure for the the first image to the third image; determining, based on the first and second similarity measures, a performance measure of the image embedding function for the image triplet; and adjusting the parameter weights of the image embedding function based on the performance measures for the image triplets. | 2019-04-04 |
20190102652 | INFORMATION PUSHING METHOD, STORAGE MEDIUM AND SERVER - A server acquires a feature label vector of each seed user and forms a first number of clusters corresponding different information categories according to the feature label vectors of the seed users. The server calculates a central vector of each cluster according to the feature label vectors of the seed users in the cluster. The server acquires a feature weight vector corresponding to the information categories. The server acquires a feature label vector of each potential user. The server calculates first distances from the potential users to the central vector of the information categories according to the feature label vectors of the potential users, feature weight vectors and central vectors corresponding to the information categories. The server selects a second number of potential users corresponding to the shortest first distances from the first distances and sends them information that is matched with corresponding information categories of the target users. | 2019-04-04 |
20190102653 | LOCAL CONNECTIVITY FEATURE TRANSFORM OF BINARY IMAGES CONTAINING TEXT CHARACTERS FOR OPTICAL CHARACTER/WORD RECOGNITION - A local connectivity feature transform (LCFT) is applied to binary document images containing text characters, to generate transformed document images which are then input into a bi-directional Long Short Term Memory (LSTM) neural network to perform character/word recognition. The LCFT transformed image is a gray scale image where the pixel values encode local pixel connectivity information of corresponding pixels in the original binary image. The transform is one that provides a unique transform score for every possible shape represented as a 3×3 block. In one example, the transform is computed using a 3×3 weight matrix that combines bit coding with a zigzag pattern to assign weights to each element of the 3×3 block, and by summing up the weights for the non-zero elements of the 3×3 block shape. | 2019-04-04 |
20190102654 | Generation of Training Data for Image Classification - A system and methods for generating training images. The system includes a data processing system that performs object recognition and differentiation of similar objects in a retail environment. A method includes generating training images for neural networks trained for the Stock Keeping Unit (SKU), angle and gesture elements that allow multiple overlapping predictions function. | 2019-04-04 |
20190102655 | TRAINING DATA ACQUISITION METHOD AND DEVICE, SERVER AND STORAGE MEDIUM - A training data acquisition method and device, a server and a storage medium are provided. The training data acquisition method is applied to a classifier and includes the following steps: obtaining an image search target according to an input of a user; providing images to the user according to the image search target, to display the images; and selecting at least one image from the displayed images, and determining a target-classification pair as training data according to the at least one image; where the target-classification pair includes the image search target and an entity-based classification of the at least one image. Thus, more high-quality training data can be obtained, improving the performance of a classifier. | 2019-04-04 |
20190102656 | METHOD, APPARATUS, AND SYSTEM FOR PROVIDING QUALITY ASSURANCE FOR TRAINING A FEATURE PREDICTION MODEL - An approach is provided for providing quality assurance for training a feature prediction model. The approach involves training the feature prediction model to label one or more features by using a training data set comprising a plurality of data items with manually marked feature labels. The approach also involves processing the training data set using the trained feature prediction model to generate automatically marked feature labels for the plurality of data items. The approach further involves computing precision data indicating a respective precision between the manually marked feature labels and the automatically marked feature labels for each of the plurality of data items in the training data set. The approach further involves initiating a quality assurance procedure on said each of the plurality of data items based on a determination that the precision data does not satisfy a quality assurance criterion. | 2019-04-04 |
20190102657 | CLASSIFICATION MODELING FOR MONITORING, DIAGNOSTICS OPTIMIZATION AND CONTROL - A modular analysis engine provided classification of variables and data in an industrial automation environment. The module may be instantiated upon receipt of an input data structure, such as containing annotated data for any desired variables related to the machine or process monitored and/or controlled. The data may be provided in a batch or the engine may operate on streaming data. The output of the module may be a data structure that can be used by other modules, such as for modeling, optimization, and control. The classification may allow for insightful analysis, such as for textual classification of alarms provided in the automation setting. | 2019-04-04 |
20190102658 | HIERARCHICAL IMAGE CLASSIFICATION METHOD AND SYSTEM - A hierarchical image classification method and system are provided. The hierarchical image classification method derives a coarse classification result of an image by analyzing the image according to a coarse classification model, derives at least one fine classification model by inquiring a classification relation table according to the coarse classification result, derives at least one level information by inquiring a level relation table according to the at least one fine classification model, retrieves at least one coarse feature descriptor from the coarse classification model according to the at least one level information, and decides at least one fine classification result according to the at least one fine classification model and the at least one coarse feature descriptor. The hierarchical image classification method may inquire the classification relation table and the level relation table repeatedly to continuously decide other fine classification result(s). | 2019-04-04 |
20190102659 | METHODS AND APPARATUS TO IMPROVE ACCURACY OF EDGE AND/OR A FOG-BASED CLASSIFICATION - Methods, apparatus, systems and articles of manufacture to improve accuracy of a fog/edge-based classifier system are disclosed. An example apparatus includes a transducer to mounted on a tracked object, the transducer to generate data samples corresponding to the tracked object; a discriminator to: generate a first classification using a first model based on a first calculated feature of the first data samples from the transducer, the first model corresponding to calculated features determined from second data samples, the second data samples obtained prior to the first data samples; generate an offset based on a difference between a first model feature the first model and a second model feature of a second model, the second model being different than the first model; and adjust the first calculated feature using the offset to generate an adjusted feature; a pattern matching engine to generate a second classification using vectors corresponding to the second model based on the adjusted feature; and a counter to, when the first classification matches the second classification, increment a count. | 2019-04-04 |
20190102660 | TRAINING DATA GENERATING DEVICE, METHOD, AND PROGRAM, AND CROWD STATE RECOGNITION DEVICE, METHOD, AND PROGRAM - At least one processor determines a person state of a crowd according to a people state control designation as designation information on a person state of people and an individual person state control designation as designation information on a state of an individual person in the people. The at least one processor generates a crowd state image as an image in which a person image corresponding to the person state determined is synthesized with previously-prepared image at a predetermined size, specifies a training label for the crowd state image, and outputs a pair of crowd state image and training label. | 2019-04-04 |
20190102661 | TRAINING DATA GENERATING DEVICE, METHOD, AND PROGRAM, AND CROWD STATE RECOGNITION DEVICE, METHOD, AND PROGRAM - At least one storage stores a dictionary of a discriminator acquired by machine learning by use of a plurality of pairs of crowd state image as an image which expresses a crowd state at a predetermined size and includes a person whose reference site is expressed as large as the size of the reference site of a person defined for the predetermined size, and training label for the crowd state image. At least one processor extracts regions from a given image and recognizes states of the crowds shot in the extracted regions based on the dictionary. | 2019-04-04 |
20190102662 | METHOD OF MANUFACTURING A SMARTCARD - A method of manufacturing a smartcard may include providing a flexible smartcard circuit, forming conductive extension members on and extend away from the flexible circuit from a high melting point solder material, and laminating the flexible circuit to form a smartcard body. A cavity is then milled in the smartcard body to expose the ends of the extension members, and a contact pad is inserted into the cavity and electrically connected to extension members using a low melting temperature tin-bismuth solder using ultrasonically soldering, so as to avoid heat damage to the card body. | 2019-04-04 |
20190102663 | FINGER-CONTROLLED CONTACTLESS CHIP CARD - The invention relates to a contactless chip card intended to communicate with a chip card reader operating at a resonant frequency F | 2019-04-04 |
20190102664 | METHOD AND A SYSTEM FOR MONITORING A QUANTITY RELATED TO AN ASSET - A method for automatically electronically associating vessel identity information of a vessel with an unassociated telemetric device, the unassociated telemetric device comprising a processor and being configured to detect and transmit quantity or usage data and being configured with a location sensing device, wherein the unassociated telemetric device is configured to communicate with a remote server, the method comprising the steps of: the remote server receiving the vessel identity information comprising a deployment location for the unassociated telemetric device; the unassociated telemetric device operating in accordance with an automatic action rule; in response to the unassociated telemetric device operating in accordance with the automatic action rule, the processor receiving location information of the unassociated telemetric device from the location sensing device; the unassociated telemetric device transmitting the location information; the remote server receiving the location information; the remote server correlating the location information with the vessel identity information when resolving that the location information represents that the unassociated telemetric device is within a proximity to the deployment location, and the remote server automatically electronically associating the unassociated telemetric device with the vessel identity information, resulting in the unassociated telemetric device becoming an associated telemetric device, so that when the associated telemetric device generates quantity or usage information, the quantity or usage information transmitted by the associated telemetric device is applied to a data store of the remote server related to the vessel identity information. | 2019-04-04 |
20190102665 | METHOD OF MANUFACTURING A SMARTCARD - A method of manufacturing a smartcard includes providing a flexible circuit having contacts for connection to a contact pad, wherein a secure element is electrically connected to the flexible circuit, electrically connecting contacts on the contact pad to the contacts on a flexible circuit via conductive paths through an extension block. A lamination process is applied to the flexible circuit to provide a card body enclosing the flexible circuit. | 2019-04-04 |
20190102666 | STRAP MOUNTING TECHNIQUES FOR WIRE FORMAT ANTENNAS - An RFID device includes an antenna defining a gap, with an RFID chip electrically coupled to the antenna across the gap. The RFID chip may be incorporated into an RFID strap, in which a pair of connection pads is connected to the RFID chip, with the connection pads connected to the antenna on opposite sides of the gap. Alternatively, the antenna may be connected to bond pads of the RFID chip. At least a portion of the antenna has a cross section with an at least partially curved perimeter. The cross section of the antenna may be differently shaped at different locations, such as having a flattened oval shape at one location and a substantially circular shape at another location. A portion of the cross section of the antenna may have a non-curved, relatively sharp edge, which may break through an outer oxide layer of a connection pad. | 2019-04-04 |
20190102667 | MODULAR HIERARCHICAL VISION SYSTEM OF AN AUTONOMOUS PERSONAL COMPANION - An autonomous personal companion utilizing a method of object identification that relies on a hierarchy of object classifiers for categorizing one or more objects in a scene. The classifier hierarchy is composed of a set of root classifiers trained to recognize objects based on separate generic classes. Each root acts as the parent of a tree of child nodes, where each child node contains a more specific variant of its parent object classifier. The method covers walking the tree in order to classify an object based on more and more specific object features. The system is further comprised of an algorithm designed to minimize the number of object comparisons while allowing the system to concurrently categorize multiple objects in a scene. | 2019-04-04 |
20190102668 | METHOD OF PREDICTION OF A STATE OF AN OBJECT IN THE ENVIRONMENT USING AN ACTION MODEL OF A NEURAL NETWORK - A method, device and system of prediction of a state of an object in the environment using an action model of a neural network. In accordance with one aspect, a control system for a object comprises a processor, a plurality of sensors coupled to the processor for sensing a current state of the object and an environment in which the object is located, and a first neural network coupled to the processor. One or more predicted subsequent states of the object in the environment are determined using an action model of the neural network and a current state of the object in the environment and an plurality of action sequences. The action model comprises a mapping of states of the object in the environment and actions performed by the object for each state to predicted subsequent states of the object in the environment. | 2019-04-04 |
20190102669 | GLOBAL AND LOCAL TIME-STEP DETERMINATION SCHEMES FOR NEURAL NETWORKS - In one embodiment, a processor comprises a first neuromorphic core to implement a plurality of neural units of a neural network, the first neuromorphic core comprising a memory to store a current time-step of the first neuromorphic core; and a controller to track current time-steps of neighboring neuromorphic cores that receive spikes from or provide spikes to the first neuromorphic core; and control the current time-step of the first neuromorphic core based on the current time-steps of the neighboring neuromorphic cores. | 2019-04-04 |
20190102670 | Secure Broker-Mediated Data Analysis and Prediction - The present disclosure relates to secure broker-mediated data analysis and prediction. One example embodiment includes a method. The method includes receiving, by a managing computing device, a plurality of datasets from client computing devices. The method also includes computing, by the managing computing device, a shared representation based on a shared function having one or more shared parameters. Further, the method includes transmitting, by the managing computing device, the shared representation and other data to the client computing devices. In addition, the method includes, based on the shared representation and the other data, the client computing devices update partial representations and individual functions with one or more individual parameters. Still further, the method includes determining, by the client computing devices, feedback values to provide to the managing computing device. Additionally, the method includes updating, by the managing computing device, the one or more shared parameters based on the feedback values. | 2019-04-04 |
20190102671 | INNER PRODUCT CONVOLUTIONAL NEURAL NETWORK ACCELERATOR - A convolutional neural network (CNN) accelerator, including: a CNN circuit for performing a multiple-layer CNN computation, wherein the multiple layers are to receive an input feature according to an input feature map (IFM) and a weight matrix per output feature, wherein an output of a first layer provides an input for a next layer; and a mapping circuit to access a three-dimensional input matrix stored as a Z-major matrix; wherein the CNN circuit is to perform an inner-product direct convolution on the Z-major matrix, wherein the direct convolution lacks a lowering operation. | 2019-04-04 |
20190102672 | USING PROGRAMMABLE SWITCHING CHIPS AS ARTIFICIAL NEURAL NETWORKS ENGINES - A method for executing a binarized neural network (BNN) using a switching chip includes describing an artificial neural network application in a binarized form to provide the BNN; configuring a parser of the switching chip to encode an input vector of the BNN in a packet header; configuring a plurality of match-action tables (MATs) of the switching chip to execute, on the input vector encoded in the packet header, one or more of the operations including XNOR, bit counting, and sign operations such that the plurality of MATs are configured to: implement a bitwise XNOR operation between the input vector and a weights matrix to produce a plurality of first stage vectors, implement an algorithm for counting a number of bits set to 1 in the plurality of first stage vectors to produce a plurality of second stage vectors, and implement a sign operation on the second stage vectors. | 2019-04-04 |
20190102673 | ONLINE ACTIVATION COMPRESSION WITH K-MEANS - Methods and apparatus relating to online activation compression with K-means are described. In one embodiment, logic (e.g., in a processor) compresses one or more activation functions for a convolutional network based on non-uniform quantization. The non-uniform quantization for each layer of the convolutional network is performed offline, and an activation function for a specific layer of the convolutional network is quantized during runtime. Other embodiments are also disclosed and claimed. | 2019-04-04 |
20190102674 | METHOD, APPARATUS, AND SYSTEM FOR SELECTING TRAINING OBSERVATIONS FOR MACHINE LEARNING MODELS - An approach is provided for selecting training observations for machine learning models. The approach involves determining a first distribution of a plurality of features observed in the training data set, and a second distribution of the plurality of features observed in the candidate pool of observations. The approach further involves selecting one or more observations in the candidate pool of observations for annotation based on the first distribution and the second distribution. The approach further involves adding the one or more observations to the training data set after annotation. The training data set is used for training the machine learning model. | 2019-04-04 |
20190102675 | GENERATING AND TRAINING MACHINE LEARNING SYSTEMS USING STORED TRAINING DATASETS - Systems and methods for generating and training machine learning systems using stored training datasets are disclosed. In an embodiment, a machine learning server computer stores a plurality of machine learning training datasets, each machine learning training dataset of the plurality of machine learning training datasets comprising input data and output data. The machine learning server computer displays, through a graphical user interface, a plurality of selectable options, each selectable option of the plurality of selectable options identifying a machine learning training dataset of the plurality of machine learning training datasets. The machine learning server computer receives a particular input dataset and a selection of a particular selectable option identifying a particular machine learning training dataset. The machine learning server computer trains a particular machine learning system using the particular machine learning training dataset. The machine learning server computer uses the particular input dataset as input into the particular machine learning system to compute a particular output dataset. | 2019-04-04 |
20190102676 | METHODS AND SYSTEMS FOR REINFORCEMENT LEARNING - Exemplary embodiments can maximize long-term value in a machine learning system. The system may employ an offline training process and an online training process. In the offline training process, an initial policy is learned to provide a warm start to the online training process. In the online training process, the system applies concurrent reinforcement learning across multiple environments, with the goal of learning efficient policies in real time from in-flight user data in one environment, and applying the learned policies to other environments. With the combination of offline training and online training, the system is able to improve initial performance through the warm start, while adapting to a changing context through concurrent reinforcement learning. | 2019-04-04 |
20190102677 | METHOD FOR ACQUIRING A PSEUDO-3D BOX FROM A 2D BOUNDING BOX BY REGRESSION ANALYSIS AND LEARNING DEVICE AND TESTING DEVICE USING THE SAME - A method for acquiring a pseudo-3D box from a 2D bounding box in a training image is provided. The method includes steps of: (a) a computing device acquiring the training image including an object bounded by the 2D bounding box; (b) the computing device performing (i) a process of classifying a pseudo-3D orientation of the object, by referring to information on probabilities corresponding to respective patterns of pseudo-3D orientation and (ii) a process of acquiring 2D coordinates of vertices of the pseudo-3D box by using regression analysis; and (c) the computing device adjusting parameters thereof by backpropagating loss information determined by referring to at least one of (i) differences between the acquired 2D coordinates of the vertices of the pseudo-3D box and 2D coordinates of ground truth corresponding to the pseudo-3D box, and (ii) differences between the classified pseudo-3D orientation and ground truth corresponding to the pseudo-3D orientation. | 2019-04-04 |
20190102678 | NEURAL NETWORK RECOGNTION AND TRAINING METHOD AND APPARATUS - Disclosed is a recognition and training method and apparatus. The apparatus may include a processor configured to input data to a neural network, determine corresponding to a multiclass output a mapping function of a first class and a mapping function of a second class, acquire a result of a loss function including a first probability component that changes correspondingly to a function value of the mapping function of the first class and a second probability component that changes contrastingly to a function value of the mapping function of the second class, determine a gradient of loss corresponding to the input data based on the result of the loss function, update a parameter of the neural network based on the determined gradient of loss for generating a trained neural network based on the updated parameter. The apparatus may input other data to the trained neural network, and indicate a recognition result. | 2019-04-04 |
20190102679 | DIRECTED TRAJECTORIES THROUGH COMMUNICATION DECISION TREE USING ITERATIVE ARTIFICIAL INTELLIGENCE - Embodiments relate to configuring artificial-intelligence (AI) decision nodes throughout a communication decision tree. The decision nodes can support successive iteration of AI models to dynamically define iteration data that corresponds to a trajectory through the tree | 2019-04-04 |
20190102680 | METHOD, DEVICE AND SYSTEM FOR ESTIMATING CAUSALITY AMONG OBSERVED VARIABLES - A method, device and system for estimating causality among observed variables are provided. In response to receiving observation data of a plurality of observed variables, a causality objective function is determined, based on fitting inconsistencies when fitting is performed using the observed variables and a sparse constraint for a causal network structure. The fitting inconsistencies are adjusted based on weighting factors of the observed variables, wherein a weighting factor of an observed variable indicates a minimum underestimate value of cost required for fitting a target variable using all other observed variables than the above observed variable. Then, the causality among the plurality of observed variables is estimated by using the observations data to optimally solve the causality objective function through sparse causal reasoning under a directed acyclic graph constraint. | 2019-04-04 |
20190102681 | DIRECTED TRAJECTORIES THROUGH COMMUNICATION DECISION TREE USING ITERATIVE ARTIFICIAL INTELLIGENCE - Embodiments relate to configuring artificial-intelligence (AI) decision nodes throughout a communication decision tree. The decision nodes can support successive iteration of AI models to dynamically define iteration data that corresponds to a trajectory through the tree. | 2019-04-04 |
20190102682 | Machine Learning Classification with Confidence Thresholds - A machine learning classifier may classify observations into one or more of i categories, and may be configured to: receive test data that includes j observations, each associated with a respective ground truth category, and produce output that provides, for each particular observation of the j observations, a set of i probabilities, one probability for each of the i categories. For each particular confidence threshold in k confidence thresholds, a computing device may: reclassify, into a null category, any of the j observations for which all of the set of i probabilities are less than the particular confidence threshold, and determine a respective precision value and a respective coverage value for a particular category of the i categories. A specific confidence threshold in the k confidence thresholds may be selected, and further observations may be reclassified into the null category in accordance with the specific confidence threshold. | 2019-04-04 |
20190102683 | Machine Learning Classification with Confidence Thresholds - A machine learning classifier may classify observations into one or more of i categories, and may be configured to: receive test data that includes j observations, each associated with a respective ground truth category, and produce output that provides, for each particular observation of the j observations, a set of i probabilities, one probability for each of the i categories. For each particular confidence threshold in k confidence thresholds, a computing device may: reclassify, into a null category, any of the j observations for which all of the set of i probabilities are less than the particular confidence threshold, and determine a respective precision value and a respective coverage value for a particular category of the i categories. A specific confidence threshold in the k confidence thresholds may be selected, and further observations may be reclassified into the null category in accordance with the specific confidence threshold. | 2019-04-04 |
20190102684 | MOBILE AND AUTONOMOUS PERSONAL COMPANION BASED ON AN ARTIFICIAL INTELLIGENCE (AI) MODEL FOR A USER - A method for building an artificial intelligence (AI) model. The method includes accessing data related to monitored behavior of a user. The data is classified, wherein the classes include an objective data class identifying data relevant to a group of users including the user, and a subjective data class identifying data that is specific to the user. Objective data is accessed and relates to monitored behavior of a plurality of users including the user. The method includes providing as a first set of inputs into a deep learning engine performing AI the objective data and the subjective data of the user, and a plurality of objective data of the plurality of users. The method includes determining a plurality of learned patterns predicting user behavior when responding to the first set of inputs. The method includes building a local AI model of the user including the plurality of learned patterns. | 2019-04-04 |
20190102685 | GENERATING SOLUTIONS FROM AURAL INPUTS - Techniques for generating solutions from aural inputs include identifying, with one or more machine learning engines, a plurality of aural signals provided by two or more human speakers, at least some of the plurality of aural signals associated with a human-perceived problem; parsing, with the one or more machine learning engines, the plurality of aural signals to generate a plurality of terms, each of the terms associated with the human-perceived problem; deriving, with the one or more machine learning engines, a plurality of solution sentiments and a plurality of solution constraints from the plurality of terms; generating, with the one or more machine learning engines, at least one solution to the human-perceived problem based on the derived solution sentiments and solution constraints; and presenting the at least one solution of the human-perceived problem to the two or more human speakers through at least one of a graphical interface or an auditory interface. | 2019-04-04 |
20190102686 | SELF-LEARNING FOR AUTOMATED PLANOGRAM COMPLIANCE - A system includes a self-learning module for creating a self-learned planogram based on images of shelving units at a location and shelving unit tracking. The self-learned planogram includes shelving unit locations for the shelving units. The system also includes a training module for training the merchandise tracking model based on merchandise-shelving unit clustering. The merchandise-shelving unit clustering is based on the self-learned planogram and sensor readings received from sensors at the location. The sensor readings are associated with items at the location. The system further includes a tracking module for tracking and storing locations of the items based on the sensor readings and the merchandise tracking model. The system also includes a planogram compliance module for determining planogram compliance based on comparing the self-learned planogram to the item locations. The system identities actionable insights based on the planogram compliance and additionally includes a display device to present the actionable insights. | 2019-04-04 |
20190102687 | Event Recommendation System - An event recommendation system recommends events for a candidate attendee. The system recommends an event based on characteristics of the candidate attendee and characteristics of prior attendees that attended a prior occurrence of the event. A prior attendee may have a positive or negative experience with the prior occurrence of the event. A positive experience may be defined, for example, as enjoying the event, completing the event, or performing well in the event. A negative experience may be defined, for example, as not enjoying the event, not completing the event, or not performing well in the event. An event is recommended to a candidate attendee if the candidate attendee has similar characteristics to a prior attendee that had a positive experience. An event is not recommended to a candidate attendee if the candidate attendee has similar characteristics as a prior attendee that had a negative experience. | 2019-04-04 |
20190102688 | METHOD, DEVICE AND SYSTEM FOR ESTIMATING CAUSALITY AMONG OBSERVED VARIABLES - A method, device and system for estimating causality among observed variables are provided. The method for estimating causality among observed variables may include: in response to receiving expert knowledge for at least part of a plurality of observed variables, converting the expert knowledge into a constraint that needs to be satisfied by a causality objective function for the plurality of observed variables; and estimating the causality among the observed variables, by using observed data of the observed variables to optimally solve, through sparse causal reasoning, the causality objective function under a constraint of a directed acyclic graph and the constraint that needs to be satisfied and converted from the expert knowledge. With embodiments of the present disclosure, it is possible to incorporate the expert knowledge into the causal reasoning process in a simple manner to sufficiently utilize the expert knowledge and obtain a more precise causality. | 2019-04-04 |
20190102689 | MONITORING VEHICULAR OPERATION RISK USING SENSING DEVICES - Embodiments for monitoring risk associated with operating a vehicle by a processor. One or more behavior parameters of an operator of a vehicle may be learned in relation to the vehicle, one or more alternative vehicles, or a combination thereof using one or more sensing devices for a journey. A risk associated with the one or more learned behavior parameters for the journey may be assessed. | 2019-04-04 |
20190102690 | DEBUGGING QUANTUM CIRCUITS BY CIRCUIT REWRITING - Techniques for automating quantum circuit debugging are provided that simulate standard debugging behaviors. The technology includes rewriting a source quantum circuit into instrumented circuits based on instrumentation instruction information inserted into software code that corresponds to the source quantum circuit. The instrumented circuits can executed to obtain measurement data corresponding to different state data of qubits within the source quantum circuit. The measurement data can be processed to output generated information corresponding to one or more internal states or processes of a quantum computer associated with the source quantum circuit. | 2019-04-04 |
20190102691 | CROSS-RESONANCE FAN-OUT FOR EFFICIENCY AND HARDWARE REDUCTION - A signal generating system is provided. The signal generating system provides a microwave signal to a plurality of qubits. The signal generating system includes a generator, an oscillator, a mixer, and a splitter. The oscillator generates an oscillator signal including a constant frequency. The generator generates a generator signal including an initial frequency. The mixer is electrically coupled to the generator and the oscillator. The mixer combines the generator and oscillator signals to produce the microwave signal. The splitter is electrically coupled to the mixer. The splitter fans-out the microwave signal to a plurality of physical lines. Each of the plurality of physical lines is electrically connected to a corresponding one of the plurality of qubits. | 2019-04-04 |
20190102692 | METHOD, APPARATUS, AND SYSTEM FOR QUANTIFYING A DIVERSITY IN A MACHINE LEARNING TRAINING DATA SET - An approach is provided for quantifying a diversity of a machine learning training data set. The approach involves creating a matrix data structure storing a plurality of feature data records describing the observations in the training data set. The approach also involves computing a covariance of the matrix data structure. For example, in one embodiment, the covariance is based on a stable rank of a covariance matrix. The approach further involves determining the diversity value of the observations based on the computed covariance. | 2019-04-04 |
20190102693 | OPTIMIZING PARAMETERS FOR MACHINE LEARNING MODELS - An online system determines candidate parameter values to be used by a machine learning algorithm to train a machine learning model by saving historical datasets that include historical parameter searches and the performance of prior machine learning models that were trained on the historical parameters. Using the historical datasets, the online system identifies parameter predictors associated with a relation between candidate parameter values and properties of the training dataset that will be used to train the machine learning model. The online system trains the machine learning models according to the candidate parameter values and validates that the machine learning model is performing as expected. If the online system detects that the machine learning model is performing outside of an acceptable range, the online system determines new candidate parameter values and re-trains the machine learning model. | 2019-04-04 |
20190102694 | CONTENT DELIVERY BASED ON CORRECTIVE MODELING TECHNIQUES - An online system uses multiple machine learning models to select content for providing to a user of the online system. Specifically, the online system trains a general model that intakes a first set of features and outputs predictions at a general level. The online system further trains a residual model that intakes a second set of features. The residual model predicts a residual (e.g., an error) of the predictions outputted by the general model. Therefore, the predicted residual from the residual model is combined with the prediction from the general model in order to correct for the over-generality of the general model. The online system may use the combined prediction to send content to users. | 2019-04-04 |
20190102695 | GENERATING MACHINE LEARNING SYSTEMS USING SLAVE SERVER COMPUTERS - Systems and methods for generating machine learning systems using slave server computers are disclosed. In an embodiment, a first server computer stores one or more machine learning training datasets, each of the datasets comprising input data and verified output data. The first server computer receives a particular input dataset and a request to run a machine learning system with the particular input dataset. The first server computer sends the particular input dataset, a particular machine learning training dataset of the one or more machine learning training datasets, and one or more configuration files for building a machine learning system to a second server computer. The second server computer processes the particular input dataset with a particular machine learning system by configuring the particular machine learning system using the one or more particular configuration files, training the particular machine learning system using the particular machine learning training dataset, and, using the particular input dataset as input into the particular machine learning system, computing a particular output dataset. The second server computer then sends the particular output dataset to the first server computer. | 2019-04-04 |
20190102696 | EMPATHY FOSTERING BASED ON BEHAVIORAL PATTERN MISMATCH - A cognitive system collects online behaviors of a user and an affinity group of users who are related (e.g. by relationship, or behavioral similarities) to the user. A knowledge base of behavior and sentiment patterns is produced and maintained. If real-time data for the user shifts in behavior and/or sentiment and significantly deviates from established patterns, the system looks for a similar behavior and/or sentiment pattern shift among members of the affinity group. If the affinity group patterns shift in a manner similar to the first user's pattern shift, the cognitive system, in response, updates the knowledge base with information related to the shift, thereby adding knowledge to the long-term patterns. If the cognitive system finds that the user's behavior and/or sentiment pattern shift differs significantly from the affinity group, the system generates an empathy fostering alert message and sends it to one or more recipients. | 2019-04-04 |
20190102697 | CREATING MACHINE LEARNING MODELS FROM STRUCTURED INTELLIGENCE DATABASES - An approach for creating an artificial intelligence machine learning model is provided. In an embodiment, a set of unstructured documents stored in an intelligence database is selected. Attributes associated with entities contained in the selected unstructured documents are retrieved from structured data that is also stored within the intelligence database. In addition, a natural language scan of the unstructured documents is performed to identify relationships between the entities. These relationships and the attributes are used to annotate the originally selected documents. Then the machine learning model is automatically created based on the annotated documents. This machine learning model can be used to train an AI to perform a specific set of problem solving tasks. | 2019-04-04 |
20190102698 | METHODS AND SYSTEMS FOR CONFIGURING COMMUNICATION DECISION TREES BASED ON CONNECTED POSITIONABLE ELEMENTS ON CANVAS - Embodiments relate to configuring artificial-intelligence (AI) decision nodes throughout a communication decision tree. The decision nodes can support successive iteration of AI models to dynamically define iteration data that corresponds to a trajectory through the tree. | 2019-04-04 |
20190102699 | LEARNING PROGRAM, LEARNING APPARATUS, AND LEARNING METHOD - A non-transitory computer-readable storage medium storing therein a learning program that causes a computer to execute a process includes: determining whether or not there is a discontinuity point at which a variation in a learning time relative to a variation in a learning parameter is discontinuous; specifying, when the discontinuity point is present, ranges of the learning parameter in which the variation in the learning time relative to the variation in the learning parameter is continuous, based on the discontinuity point; calculating, for each of the specified ranges, an estimated value of performance of trials using a trial parameter learned by machine learning per a learning time of machine learning using a learning parameter included in the range; and specifying a learning parameter which enables any of the estimated values selected in accordance with a magnitude of the estimated value among the calculated estimated values. | 2019-04-04 |
20190102700 | MACHINE LEARNING PLATFORM - The present disclosure relates generally to an integrated machine learning platform. The machine learning platform can convert machine learning models with different schemas into machine learning models that share a common schema, organize the machine learning models into model groups based on certain criteria, and perform pre-deployment evaluation of the machine learning models. The machine learning models in a model group can be evaluated or used individually or as a group. The machine learning platform can be used to deploy a model group and a selector in a production environment, and the selector may learn to dynamically select the model(s) from the model group in the production environment in different contexts or for different input data, based on a score determined using certain scoring metrics, such as certain business goals. | 2019-04-04 |
20190102701 | TECHNIQUES FOR GENERATING A HIERARCHICAL MODEL TO IDENTIFY A CLASS AMONG A PLURALITY OF CLASSES - Techniques disclosed herein relate to generating a hierarchical classification model that includes a plurality of classification models. The hierarchical classification model is configured to classify an input into a class in a plurality of classes and includes a tree structure. The tree structure includes leaf nodes and non-leaf nodes. Each non-leaf node has two child nodes associated with two respective sets of classes in the plurality of classes, where a difference between numbers of classes in the two sets of classes is zero or one. Each leaf node is associated with at least two but fewer than a first threshold number of classes. Each of the leaf nodes and non-leaf nodes is associated with a classification model in the plurality of classification models of the hierarchical classification model. The classification model associated with each respective node in the tree structure can be trained independently. | 2019-04-04 |
20190102702 | SYSTEM AND METHOD FOR DATA VISUALIZATION USING MACHINE LEARNING AND AUTOMATIC INSIGHT OF FACTS ASSOCIATED WITH A SET OF DATA - In accordance with various embodiments, described herein are systems and methods for use of computer-implemented machine learning to automatically determine insights of facts, segments, outliers, or other information associated with a set of data, for use in generating visualizations of the data. In accordance with an embodiment, the system can receive a data set that includes data points having data values and attributes, and a target attribute, and use a machine learning process to automatically determine one or more other attributes as driving factors for the target attribute, based on, for example, the use of a decision tree and a comparison of information gain, Gini, or other indices associated with attributes in the data set. Information describing facts associated with the data set can be graphically displayed at a user interface, as visualizations, and used as a starting point for further analysis of the data set. | 2019-04-04 |
20190102703 | SYSTEM AND METHOD FOR DATA VISUALIZATION USING MACHINE LEARNING AND AUTOMATIC INSIGHT OF SEGMENTS ASSOCIATED WITH A SET OF DATA - In accordance with various embodiments, described herein are systems and methods for use of computer-implemented machine learning to automatically determine insights of facts, segments, outliers, or other information associated with a set of data, for use in generating visualizations of the data. In accordance with an embodiment, the system can use a machine learning process to automatically determine one or more segments within a data set, associated with a target attribute value, based on, for example, the use of a classification and regression tree and a combination of different driving factors, or same driving factors with different values. Information describing segments associated with the data set can be graphically displayed at a user interface, as text, graphs, charts, or other types of visualizations, and used as a starting point for further analysis of the data set. | 2019-04-04 |
20190102704 | MACHINE LEARNING SYSTEMS FOR RANKING JOB CANDIDATE RESUMES - A machine learning system for ranking job candidates' resumes based on a predictive system comprising machine learning from a large number of resume profile data sets, job opening requirements data sets, and relevant employer HR data. The machine learning system includes a resume data training engine that receives a plurality of resume profile data, job opening requirements data, and relevant employer HR data. The received data is used to determine a plurality of features and generate a predictive model. The system also includes a resume ranking runtime engine that utilizes the predictive model to generate ranking data regarding a plurality of resume records data using the predictive model based on received job description data and resume records data. | 2019-04-04 |
20190102705 | Determining Preferential Device Behavior - Systems, methods and computer program products are disclosed for machine learning to determine preferential device behavior. In some implementations, a server receives inputs, including attributes from a client device, crowd-sourced data from a number of other devices and a priori knowledge. The server includes a concept engine that applies machine-learning process to the inputs. The output of the machine learning process is transported to the client device. At the client device, a client engine associates attributes observed at the device to the machine learning output to determine a user profile. Applications may access the user profile to determine preferential device behavior, such as provide targeted information to the user or take action on the device that is personalized to the user of the device. | 2019-04-04 |
20190102706 | Affective response based recommendations - Described herein are embodiments of systems, method, and computer programs for recommending an experience to a user. In one embodiment, a sensor takes measurements of affective response of the user while the user is exposed to token instances that are instantiations of visual tokens. An eye tracker measures the gaze of the user while the user is exposed to the token instances. A computer calculates, based on the measurements of affective response and measurements of the gaze, values of expected affective response of the user to exposure to instantiations of the visual tokens. These values are utilized to select an experience for the user, such that based on the values, an expected affective response of the user to exposure to token instances corresponding to the selected experience is more positive than an expected affective response of the user to exposure to token instances corresponding to other experiences. | 2019-04-04 |
20190102707 | APPLICATION PROGRAMMING INTERFACE FOR A LEARNING CONCIERGE SYSTEM AND METHOD - The described system and method reviews past receipts from purchases and past purchase patterns and, in response to a request, returns a recommendation about future scheduling or future purchases. | 2019-04-04 |
20190102708 | Reservation Processing Device, Reservation Processing Method, and Reservation Processing Program - An event suitable for the preference of a user is provided at a vacant time in a schedule. Reservable event information regarding an event which is provided by each of providers of different industry types or different business types and is a target of a reservation is stored. Schedule information regarding a schedule of a user is acquired from a reservation applicant terminal. The vacant time of the schedule and preference information regarding the preference of the user are specified based on the acquired schedule information. One or more events capable of being reserved in the vacant time are specified at least by using the vacant time and the preference information which have been specified, from the reservable event information. The specified event is provided to the reservation applicant terminal as an acquisition source of the schedule information used for specifying the event. | 2019-04-04 |
20190102709 | SYSTEMS AND METHODS FOR COORDINATING VENUE SYSTEMS AND MESSAGING CONTROL - Systems and methods for managing and coordinating data objects encoding events. The method comprises accepting definition of a group event and a venue for the event; defining a private communication channel for use by participants invited to the event; establishing communication with one or more venue fulfillment systems; triggering execution of participant requested functionality on the one or more venue fulfillment systems; accessing fulfilment information on the one or more venue fulfillment systems; and enabling at least one user device associated with at least one member of a participant group to access and execute functionality on the one or more venue fulfillment systems. | 2019-04-04 |
20190102710 | EMPLOYER RANKING FOR INTER-COMPANY EMPLOYEE FLOW - Methods, systems, and computer programs are presented for generating company-comparison reports based on a company ranking for hiring and retaining employees. One method includes an operation for determining transitions of users of a social network based on their profiles. Each transition comprises a change of employment from a source to a destination company. A transition graph is created, for a group of companies, including a node for each company and links between the nodes. Each link comprises a number of employees that transitioned from the source to the destination company. A weight, calculated for each link in the transition graph, is based on a number of employees of the destination company and a number of users transitioning between companies (both directions). A company score is calculated for each company based on the transition graph and the weights of the links. A report based on the company scores is then presented. | 2019-04-04 |
20190102711 | APPROACH FOR GENERATING BUILDING SYSTEMS IMPROVEMENT PLANS - Capabilities of the building automation system are assessed with assessments that are used to generate plans and justification for upgrading or servicing the building automation system. | 2019-04-04 |
20190102712 | CONTAINER HANDLING EQUIPMENT CONTROLLER ARRANGEMENT - A CHE controller arrangement comprises: an execution controller in operative connection with one or more engines of the CHE and configured to control movement of the CHE; a communication controller having a memory to at least store a job to be executed by said CHE, the communication controller further comprising a first interface to retrieve instructions from an external instance, and particular from a terminal operating system related to a plurality of jobs to be executed by said CHE and a second interface to communicate with at least a second CHE; a control interface between the execution controller and the communication controller being adapted to provide instructions to the execution controller responsive to an execution of said job, and the second inter face being adapted to forward at least one job of the plurality of jobs in response to a respective request by said at least one second CHE. | 2019-04-04 |
20190102713 | SPLIT ENTERPRISE/PROVIDER WORKFLOWS - A provider system (e.g., a cloud based provider system) receives a workflow. For example, the workflow may be for handling a voice communication session in a contact center. The workflow comprises a plurality of workflow tasks. The workflow tasks comprise enterprise workflow tasks and provider workflow tasks. The identified provider workflow tasks are executed on the provider system according the workflow. The provider system initiates execution of the identified enterprise workflow tasks on the enterprise system according to the workflow. By allowing a split workflow between the provider system and the enterprise, exposure to sensitive information used by the provider system may be limited. | 2019-04-04 |
20190102714 | SYSTEMS AND METHODS FOR IDENTIFYING, PROFILING AND GENERATING A GRAPHICAL USER INTERFACE DISPLAYING CYBER, OPERATIONAL, AND GEOGRAPHIC RISK - Methods and apparatus consistent with the invention provide the ability to combine data from multiple different sources of risk data, to create a weighted risk model using Bayesian networks and Monte-Carlo simulation to advance a quantified risk outlook. Based on the client risk configuration file, a risk user interface (UI) template is selected and the modelled risk is generated into a graphical user interface (GUI) using the selected risk template to display the GUI at multiple summary levels starting at a high-level overview which will include cyber, economic, legal, brand, operational and geographic risks. The GUI of modelled risk is displayed on the client device using the selected UI template. The system enables the user to drill down into the GUI for any of the categories available in the selected UI template to further examine risk characteristics as well as the actual sources of the risk in the modelled risk. | 2019-04-04 |
20190102715 | METHODS AND DEVICES FOR MANAGING RESOURCE REALLOCATION - A computer system and computer-implemented method for proactively enabling reallocation of resources among two or more data records. The data records include a first data record to which resources are allocated. The system includes determining that the resources allocated to the first data record include surplus resources and sending a notification to a manager application on a remote device, the notification including a proposed reallocation of at least a portion of the surplus resources to a second data record. The manager application is associated with both the first data record and the second data record. A response is received from the remote device confirming the proposed reallocation and, in response, the at least a portion of the surplus resources are reallocated from the first data record to the second data record. | 2019-04-04 |
20190102716 | CROWD SOURCED RESOURCES AS SELECTABLE WORKING UNITS - The global proliferation of high speed communication networks has created unprecedented opportunities for geographically distributed resource interaction. A crowd sourced project management synthesizer provides crowd sourced project management features, as well as resource performance tracking features, to provide efficiencies to the project's implementation. | 2019-04-04 |
20190102717 | MICROSERVICE AUTO-SCALING FOR ACHIEVING SERVICE LEVEL AGREEMENTS - Methods and systems associated with a microservice based predictive service level agreement (SLA) impact analytics system that may run on standardized container based virtual computing platform to enable capacity auto-scaling for on-demand, near-real-time resource allocation automatically supporting user data packet forwarding when SLA is potentially impacted to ensure SLA compliance. | 2019-04-04 |
20190102718 | TECHNIQUES FOR AUTOMATED SIGNAL AND ANOMALY DETECTION - Predictive analysis techniques are described herein as applied to business variables. In some embodiments, a dynamic dependency model may be generated using a time-series data from a first time period. The model may define relationships between business variables during the first time period. A prediction of values of a variable (e.g., a business variable such as sales, revenue, attrition, or the like) can be generated based on the dynamic dependency model. The prediction of values may be for a second time period after the first time period. The actual values of the variable over the second time period can be obtained and compared to the predicted values to generate a statistical deviation. The statistical deviation may exceed a threshold and, a notification of the statistical deviation may be transmitted to a user device. The notification may alert the user that the variable is likely to miss the targeted/predicted value. | 2019-04-04 |
20190102719 | Graphical User Interfaces for Dynamic Information Technology Performance Analytics and Recommendations - An embodiment may involve receiving respective information technology performance data related to managed networks. The embodiment may further involve transmitting a web-based representation of a first graphical user interface. The first graphical user interface may be configurable to display a plurality of performance metrics related to the managed network. The embodiment may further involve receiving an indication to display a detailed representation of a particular performance metric of the plurality of performance metrics. The embodiment may further involve transmitting a web-based representation of a second graphical user interface. The second graphical user interface may be configured to display (i) a textual description of the particular performance metric, (ii) the value of the particular performance metric, (iii) an ordered ranking, (iv) a graph-based representation of the particular performance metric as measured over a time period, and (v) a recommendation of operational modifications to improve the particular performance metric. | 2019-04-04 |
20190102720 | JOB-TRANSITION ANALYSIS AND REPORT SYSTEM - Methods, systems, and computer programs are presented for analyzing and generating employee-mobility information. One method includes an operation for determining transitions of users of a social network based on user profiles. Each transition includes a change of employment. Further, the method includes creating a member table based on the determined transitions and the user profiles. The member table includes fields for a company identifier and a previous company identifier, where the previous company identifier indicates a transition from the source company that is associated with the previous company identifier to the destination company that is associated with the company identifier. The method further includes operations for providing a user interface for receiving user input to create a report based on the determined transitions, accessing the member table to generate report data based on the received user input, and for causing presentation of the report based on the report data. | 2019-04-04 |
20190102721 | METHOD AND SYSTEM FOR TRACKING HEALTH STATISTICS IN CONSOLIDATED MARKETS - A computer program product for modeling a quality of healthcare based on a level of consolidation of a healthcare region is disclosed. The program causes a processor to identify a plurality of healthcare regions comprising healthcare providers and access healthcare statistics of a plurality of patients in the plurality of healthcare regions. The processor accesses a consolidation index for each of the healthcare regions and calculates a correlation of at least one care factor of the healthcare statistics to the consolidation index. The processor generates a consolidation influence model for the at least one care factor based on the correlation. | 2019-04-04 |
20190102722 | SYSTEM AND METHOD ENABLING DYNAMIC TEACHER SUPPORT CAPABILITIES - Systems and methods are provided for monitoring and improving teacher effectiveness. The systems and methods scrutinize various aspects of teacher performance, formulate appropriate recommendations for improving such performance, and provide digital interlinkages among teachers in order to effectively distribute content and improve teacher efficiency. | 2019-04-04 |
20190102723 | SYSTEMS FOR AUTOMATED PROFILE BUILDING, SKILLSET IDENTIFICATION, AND SERVICE TICKET ROUTING - A system includes a non-transitory memory and one or more hardware processors configured to read instructions from the non-transitory memory to perform operations. The operations include maintaining a list of agent profiles, wherein each of the agent profiles comprises a plurality of skills toward which points are awarded based on completed activities, receiving a service request, identifying one or more skills associated with the service request, referencing the list of agent profiles to identify one of the agent profiles possessing the one or more skills associated with the service request, and assigning the service request to the agent profile possessing the one or more skills associated with the service request. | 2019-04-04 |
20190102724 | HIRING DEMAND INDEX - Methods, systems, and computer programs are presented for generating custom hiring metrics based on configurable filters to assist in a company's recruiting efforts. One method includes an operation for determining job metrics, for a global pool of users, that are based on job-post communications received by the global pool. The method further includes operations for receiving filters for generating a report, and for identifying a talent pool based on the filters, which are applied to the global pool based on user profile data. A talent-pool metric is determined based on the job-post communications received by the talent pool, and a hiring demand index (HDI) is determined based on the talent-pool metric and the job metrics for the global pool of users, where the HDI provides a degree of difficulty for hiring users from the talent pool. Further, the report including the HDI for the talent pool is presented. | 2019-04-04 |
20190102725 | DETERMINATION OF EMPLOYMENT START DATE - Methods, systems, and computer programs are presented for determining employment start dates for members of a social network that have not indicated their employment start date in their profiles to generate employment market reports. One method includes an operation for receiving a request to infer a member start date for a member with an unknown member start date at a company. A distribution over time of known member start dates is determined for members of the social network with a known employment start date at the company, and a time interval is identified defining the boundaries for the member start date. A cohort group is selected from several cohort groups, that include members with known member start dates having a same cohort feature value as the member. A start-date probability distribution is determined based on the distribution of the known member start dates, the cohort group, and the time interval. | 2019-04-04 |
20190102726 | CONTROL METHOD AND INFORMATION PROCESSING DEVICE - Provided is a program causing a computer to execute a process including: storing schedule information including an execution order of activities; obtaining geofence information including positional information indicating a departure place of each activity and time information indicating time to transmit an advance notice regarding expectation of arrival at a first departure place of a first activity next to a second activity to a device of a business operator providing the first activity, specifying a next activity based on the schedule information; generating, based on time information in the geofence information corresponding to the next activity and speed information indicating user's moving speed, distance information corresponding to the time information; and transmitting, to another device of another business operator providing the next activity, the advance notice regarding expectation of arrival at a next departure place of the next activity based on user's entering into a geofence and the distance information. | 2019-04-04 |
20190102727 | SYSTEMS AND METHODS FOR DETERMINING INVENTORY USING TIME-SLOTTED TAG COMMUNICATIONS - Systems and methods for determining an inventory. The methods comprise: placing an RFID tag in a first operational mode in which at least one communication operation or device of the RFID tag is disabled or bypassed; performing first operations by the RFID tag to determine when it is time to begin communications in accordance with the time slotted communications scheme; transitioning an operational mode of the RFID tag from the first operational mode to a second operational mode in which the communication operation(s) or device of the RFID tag is enabled or no longer bypassed, in response to a determination that it is time for the RFID tag to begin communications; and transitioning the operational mode of the RFID tag back into the first operational mode when the RFID tag's communications with a remote tag reader for inventory determination purposes are complete or a time slot has expired. | 2019-04-04 |
20190102728 | PARCEL DELIVERY SYSTEM AND METHOD - A parcel delivery system and method for the delivery of a parcel into a vehicle within a parking location. The system and method uses communicative devices coupled to a vehicle and capable of providing a position of the vehicle within the parking location to a controller for the direction of a delivery of a given parcel. The system assigns a given parking location with an address for use by a user to direct a delivery into a vehicle parked within the parking location. | 2019-04-04 |
20190102729 | MEDICAL CABINET COMMUNICATION SYSTEM AND METHODS - Described is an RFID-enabled medical item storage, organization, and/or tracking device, such as a cabinet or shelf, that includes a limited-range wireless network communication capability, such as low-energy Bluetooth or Zigbee, to communicate with nearby cabinets, shelves or mobile devices, any of which may serve as a communication aggregator to coordinate the communication of multiple cabinets, shelves and other devices with an inventory management system or other back-end computer system or other device via back haul wireless or wired networks (e.g., the Internet). | 2019-04-04 |
20190102730 | DRONE DELIVERY AND LANDING - Techniques that facilitate drone delivery and landing, particularly with respect to home and commercial package delivery, are provided. In one example, a computer-implemented method comprises: detecting, by a system comprising a processor, presence of a drone device within a defined vicinity of a protected area, wherein the protected area is accessible via an opening that is blocked by a physical barrier. The method further comprises controlling, by the system, access by the drone device to the protected area to drop off or pick up a package by controlling removal of the physical barrier based in part on detection of the drone device within the defined vicinity of the protected area. | 2019-04-04 |
20190102731 | DEVICES, SYSTEMS, AND METHODS FOR SECURE AND ADAPTABLE TRANSPORTATION OF GOODS AND/OR PERSONS - A method includes receiving, by a first device of a transportation provider, a device ID of a particular device of a user and purchase information regarding a purchase, by the user, of one or more goods or services. The method includes sending, by the first device, the device ID of the particular user device to a central server. The method includes receiving, by the first device from the central server, information regarding the particular user device. The method includes determining, by the first device, a selected transportation vehicle based on the purchase information and the information regarding the particular user device. The method includes sending, by the first device, a vehicle ID of the selected transportation vehicle to the central server. The method includes providing a transportation service to the user using the particular user device and the selected transportation vehicle. | 2019-04-04 |