25th week of 2019 patent applcation highlights part 56 |
Patent application number | Title | Published |
20190188550 | RFID TAG MANUFACTURING METHOD, RFID TAG MANUFACTURING DEVICE, AND TRANSFER SHEET MANUFACTURING METHOD - An RFID tag manufacturing method is provided that includes arranging a plurality of RFIC elements in a housing tool at a first arrangement density; and extracting an RFIC element group out of the plurality of RFIC elements arranged in the housing tool. Moreover, the extracted RFIC element group has a second arrangement density that is lower than the first arrangement density and that corresponds to an arrangement density of a plurality of antenna patterns arranged on an antenna substrate. The method includes disposing the RFIC element group onto the plurality of antenna patterns of the antenna substrate while maintaining the second arrangement density. | 2019-06-20 |
20190188551 | ESTIMATING AND VISUALIZING COLLABORATION TO FACILITATE AUTOMATED PLAN GENERATION - Techniques facilitating estimating and visualizing entity to agent collaboration to facilitate automated plan generation are provided. In one example, a computer-implemented method comprises generating, by a device operatively coupled to a processor, a plan based on receiving first input data associated with an instance model. The computer-implemented method also comprises generating, by the device, a revised plan based on receiving second input data, associated with a revised instance model, from an entity. Furthermore, the computer-implemented method comprises, tracking, by the device, a contribution of the entity as a function of a modification from the instance model to the revised instance model. | 2019-06-20 |
20190188552 | COMMUNICATION MODEL FOR COGNITIVE SYSTEMS - Systems and methods for a cognitive system to interact with a user are provide. Aspects include receiving a cognitive system profile and observational data associated with the user. Environmental data associated with the user is received and features are extracted from the observations data and the environmental data. The features are stored in the user profile and analyzed to determine a situational context for each of the features based on the cognitive system profile and the user profile. Trigger events are identified based on the situational context for each of the features. One or more proposed actions are determined based at least in part on the one or more trigger events. At least one action is initiated from the one or more proposed actions and are stored in the user profile along with the one or more trigger events and the one or more features. | 2019-06-20 |
20190188553 | SCALABLE PARAMETER ENCODING OF ARTIFICIAL NEURAL NETWORKS OBTAINED VIA AN EVOLUTIONARY PROCESS - A source system initializes, using an initialization seed, a first parameter vector representing weights of a neural network. The source system determines a second parameter vector by performing a sequence of mutations on the first parameter vector, the mutations each being based on a perturbation seed. The source system generates, and stores to memory, an encoded representation of the second parameter vector that comprises the initialization seed and a sequence of perturbation seeds corresponding to the sequence of mutations. The source system transmits the data structure to a target system, which processes a neural network based on the data structure. | 2019-06-20 |
20190188554 | CONVOLUTIONAL NEURAL NETWORK OPTIMIZATION MECHANISM - Embodiments provide systems and methods which facilitate optimization of a convolutional neural network (CNN). One embodiment provides for a non-transitory machine-readable medium storing instructions that cause one or more processors to perform operations comprising processing a trained convolutional neural network (CNN) to generate a processed CNN, the trained CNN having weights in a floating-point format. Processing the trained CNN includes quantizing the weights in the floating-point format to generate weights in an integer format. Quantizing the weights includes generating a quantization table to enable non-uniform quantization of the weights and quantizing the weights from the floating-point format to the integer format using the quantization table. The operations additionally comprise performing an inference operation utilizing the processed CNN with the integer format weights. | 2019-06-20 |
20190188555 | PARTIAL INFERENCE PATH TECHNOLOGY IN GENERAL OBJECT DETECTION NETWORKS FOR EFFICIENT VIDEO PROCESSING - Systems, apparatuses and methods may provide for technology that generates, by a full inference path of a neural network, a first detection result associated with one or more objects in a first video frame. The technology may also generate, by a partial inference path of the neural network, a second detection result based on the first detection result, wherein the second detection result corresponds to a second video frame that is subsequent to the first video frame. | 2019-06-20 |
20190188556 | Floating Gate for Neural Network Inference - A computer-implemented method, the method comprising: in an initial setup of weights for a floating gate including rows, columns, and a separate input line: comparing a current weight to a desired weight; performing a feedback to the input line to set a voltage to change the floating gate field effect transistor (FET) threshold voltage (VT) and the current weight; and checking that the current weight is within a predetermined tolerance of the desired weight; and performing a stochastic pulse update on the floating gate based on the checking. | 2019-06-20 |
20190188557 | ADAPTIVE QUANTIZATION FOR NEURAL NETWORKS - Methods, devices, systems, and instructions for adaptive quantization in an artificial neural network (ANN) calculate a distribution of ANN information; select a quantization function from a set of quantization functions based on the distribution; apply the quantization function to the ANN information to generate quantized ANN information; load the quantized ANN information into the ANN; and generate an output based on the quantized ANN information. Some examples recalculate the distribution of ANN information and reselect the quantization function from the set of quantization functions based on the resampled distribution if the output does not sufficiently correlate with a known correct output. In some examples, the ANN information includes a set of training data. In some examples, the ANN information includes a plurality of link weights. | 2019-06-20 |
20190188558 | MONITORING POTENTIAL OF NEURON CIRCUITS - A neuromorphic electric system includes a network of plural neuron circuits connected in series and in parallel to form plural layers. Each of the plural neuron circuits includes: a soma circuit that stores a charge supplied thereto and outputs a spike signal; and plural synapse circuits that supply a charge to the soma circuit according to a spike signal fed to the synapse circuits, a number of the plural synapse circuits being one more than a number of plural neuron circuits in a prior layer outputting the spike signal to the synapse circuits. One of the plural synapse circuits supplies a charge to the soma circuit in response to receiving a series of pulse signals, and the others of the plural synapse circuits supply a charge to the soma circuit in response to receiving a spike signal from corresponding neuron circuits in the prior layer. | 2019-06-20 |
20190188559 | SYSTEM, METHOD AND RECORDING MEDIUM FOR APPLYING DEEP LEARNING TO MOBILE APPLICATION TESTING - A Deep learning method, system, and computer program product, include collecting context information and a user input from an existing test case and training a recurrent neural network (RNN) model with the collected context information and the user input to map each of the context information to the user input. | 2019-06-20 |
20190188560 | MULTI-GPU DEEP LEARNING USING CPUS - A computer-implemented method, computer program product, and computer processing system are provided for accelerating neural network data parallel training in multiple graphics processing units (GPUs) using at least one central processing unit (CPU). The method includes forming a set of chunks. Each of the chunks includes a respective group of neural network layers other than a last layer. The method further includes performing one or more chunk-wise synchronization operations during a backward phase of the neural network data parallel training, by each of the multiple GPUs and the at least one CPU. | 2019-06-20 |
20190188561 | DEEP LEARNING BASED DISTRIBUTION OF CONTENT ITEMS DESCRIBING EVENTS TO USERS OF AN ONLINE SYSTEM - An online system distributes content items describing events to one or more users of the online system. The online system receives, an event from a third-party system, the event associated with one or more content items. The online system determines a vector representation of users based on a first neural network and a vector representation of an event based on a second neural network. The online system jointly trains the first neural network and second neural network based on labels describing user entity relationships. The online system determines a likelihood of attendance of an event by a user based on a distance between the vector representation of the user and the vector representation of the entity. The online system provides the content associated with the event to users of the online system based on the likelihood of attendance of the event by the users. | 2019-06-20 |
20190188562 | Deep Neural Network Hardening Framework - Mechanisms are provided to implement a hardened neural network framework. A data processing system is configured to implement a hardened neural network engine that operates on a neural network to harden the neural network against evasion attacks and generates a hardened neural network. The hardened neural network engine generates a reference training data set based on an original training data set. The neural network processes the original training data set and the reference training data set to generate first and second output data sets. The hardened neural network engine calculates a modified loss function of the neural network, where the modified loss function is a combination of an original loss function associated with the neural network and a function of the first and second output data sets. The hardened neural network engine trains the neural network based on the modified loss function to generate the hardened neural network. | 2019-06-20 |
20190188563 | SYSTEM - According to one embodiment, in nth (n is a natural number) processing, a first node calculates a first gradient to update a first weight and a second node calculates a second gradient to update the first weight. In mth (m is a natural number) processing, a third node calculates a third gradient to update a third weight and a fourth node calculates a fourth gradient to update the third weight. If the calculation by the first and second nodes is faster than the calculation by the third and fourth nodes, in n+1th processing, a second weight updated from the first weight is further updated using the first and second gradients, and, in m+1th processing, a fourth weight updated from the third weight is further updated using the first to fourth gradients. | 2019-06-20 |
20190188564 | METHODS AND APPARATUS FOR ASYNCHRONOUS AND INTERACTIVE MACHINE LEARNING USING ATTENTION SELECTION TECHNIQUES - A non-transitory medium includes code representing processor-executable instructions; the code causes a processor to produce, via a machine learning model, a predicted value of a membership relationship between a data object and a target tag. The code causes the processor to display, via a user interface, the data object and the target tag and indicate a non-empty set of identified sections of one or more attributes of data object supporting the membership relationship between the data object and the target tag. The code also causes the processor to receive a tag signal, via the user interface, indicating one of an acceptance tag signal, a dismissal tag signal, or a corrective tag signal, and re-train the machine learning model based at least in part on the tag signal. | 2019-06-20 |
20190188565 | LEARNING AND DEPLOYMENT OF ADAPTIVE WIRELESS COMMUNICATIONS - Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training and deploying machine-learned communication over radio frequency (RF) channels. One method includes: determining an encoder and a decoder, at least one of which is configured to implement an encoding or decoding that is based on at least one of an encoder machine-learning network or a decoder machine-learning network that has been trained to encode or decode information over a communication channel; determining first information; using the encoder to process the first information and generate a first RF signal; transmitting, by at least one transmitter, the first RF signal through the communication channel; receiving, by at least one receiver, a second RF signal that represents the first RF signal altered by transmission through the communication channel; and using the decoder to process the second RF signal and generate second information as a reconstruction of the first information. | 2019-06-20 |
20190188566 | REWARD AUGMENTED MODEL TRAINING - A method includes obtaining data identifying a machine learning model to be trained to perform a machine learning task, the machine learning model being configured to receive an input example and to process the input example in accordance with current values of a plurality of model parameters to generate a model output for the input example; obtaining initial training data for training the machine learning model, the initial training data comprising a plurality of training examples and, for each training example, a ground truth output that should be generated by the machine learning model by processing the training example; generating modified training data from the initial training data; and training the machine learning model on the modified training data. | 2019-06-20 |
20190188567 | DYNAMIC NEURAL NETWORK SURGERY - Techniques related to compressing a pre-trained dense deep neural network to a sparsely connected deep neural network for efficient implementation are discussed. Such techniques may include iteratively pruning and splicing available connections between adjacent layers of the deep neural network and updating weights corresponding to both currently disconnected and currently connected connections between the adjacent layers. | 2019-06-20 |
20190188568 | HYBRID TRAINING OF DEEP NETWORKS - Hybrid training of deep networks includes a multi-layer neural network. The training includes setting a current learning algorithm for the multi-layer neural network to a first learning algorithm. The training further includes iteratively applying training data to the neural network, determining a gradient for parameters of the neural network based on the applying of the training data, updating the parameters based on the current learning algorithm, and determining whether the current learning algorithm should be switched to a second learning algorithm based on the updating. The training further includes, in response to the determining that the current learning algorithm should be switched to a second learning algorithm, changing the current learning algorithm to the second learning algorithm and initializing a learning rate of the second learning algorithm based on the gradient and a step used by the first learning algorithm to update the parameters of the neural network. | 2019-06-20 |
20190188569 | Parallel Forward and Backward Propagation - A neural network structure is separated into an odd neural network including only the odd layers and an even neural network including only the even layers. In order to allow for parallel execution, for forward propagation a second input is generated from the original input, while for backward propagation a second error gradient is generated. Parallel execution may accelerate the forward and backward propagation operations without significant change in accuracy of the model. Additionally, restructuring a single neural network into two or more parallel neural networks may reduce the total time needed for training. | 2019-06-20 |
20190188570 | METHODS AND APPARATUS FOR MODEL PARALLELISM IN ARTIFICIAL NEURAL NETWORKS - The method according to an embodiment comprises automatically controlling allocation, to memories of available hardware resources, of parameters defining computational operations required to calculate an output of at least one layer of neurons of an artificial neural network. The allocation is controlled on the basis of previously-defined allocation data specifying how the operations required to calculate the output of the one layer of neurons are to be allocated to hardware resources to perform the operations. The allocation data is pre-defined using, at least partly, an automatic computer-implemented process, which may include checking before each iteration of the network which of the hardware resources are available to execute that iteration of the network and, if necessary, re-defining the allocation data for that iteration accordingly | 2019-06-20 |
20190188571 | TRAINING NEURAL NETWORKS USING EVOLUTION BASED STRATEGIES AND NOVELTY SEARCH - Systems and methods are disclosed herein for selecting a parameter vector from a set of parameter vectors for a neural network and generating a plurality of copies of the parameter vector. The systems and methods generate a plurality of modified parameter vectors by perturbing each copy of the parameter vector with a different perturbation seed, and determine, for each respective modified parameter vector, a respective measure of novelty. The systems and methods determine an optimal new parameter vector based on each respective measure of novelty for each respective one of the plurality of modified parameter vectors, and determine behavior characteristics of the new parameter vector. The systems and methods store the behavior characteristics of the new parameter vector in an archive. | 2019-06-20 |
20190188572 | MEMORY-EFFICIENT BACKPROPAGATION THROUGH TIME - Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a recurrent neural network on training sequences using backpropagation through time. In one aspect, a method includes receiving a training sequence including a respective input at each of a number of time steps; obtaining data defining an amount of memory allocated to storing forward propagation information for use during backpropagation; determining, from the number of time steps in the training sequence and from the amount of memory allocated to storing the forward propagation information, a training policy for processing the training sequence, wherein the training policy defines when to store forward propagation information during forward propagation of the training sequence; and training the recurrent neural network on the training sequence in accordance with the training policy. | 2019-06-20 |
20190188573 | TRAINING OF ARTIFICIAL NEURAL NETWORKS USING SAFE MUTATIONS BASED ON OUTPUT GRADIENTS - Systems and methods are disclosed herein for ensuring a safe mutation of a neural network. A processor determines a threshold value representing a limit on an amount of divergence of response for the neural network. The processor identifies a set of weights for the neural network, the set of weights beginning as an initial set of weights. The processor trains the neural network by repeating steps including determining a safe mutation representing a perturbation that results in a response of the neural network that is within the threshold divergence, and modifying the set of weights of the neural network in accordance with the safe mutation. | 2019-06-20 |
20190188574 | GROUND TRUTH GENERATION FRAMEWORK FOR DETERMINATION OF ALGORITHM ACCURACY AT SCALE - The example embodiments are directed to a system and method for generating ground truth for determination of algorithm accuracy at scale. In one example, the method includes receiving raw data from at least one data source, performing pre-processing on the raw data, obtaining first information for generating ground truth data by applying a machine learning algorithm to the pre-processed raw data, obtaining second information for generating ground truth data by applying a signal processing algorithm to the pre-processed raw data, generating ground truth data based on matches between the first information and the second information, and determining accuracy of a source algorithm using the generated ground truth data. | 2019-06-20 |
20190188575 | COMPUTER-IMPLEMENTED SYSTEMS UTILIZING SENSOR NETWORKS FOR SENSING TEMPERATURE AND MOTION ENVIRONMENTAL PARAMETERS; AND METHODS OF USE THEREOF - Computer-implemented systems utilizing sensor networks for sensing temperature and motion environmental parameters, and performing at least operations of electronically establishing, based on pattern recognition criteria, correspondence of a plurality of representative features a plurality of characteristics of an occurrence, where a first instance of the occurrence occurred within a first time period of a plurality of time periods; electronically discovering, based on the correspondence, a second instance of the occurrence in an environment during a second time period of the plurality of time periods; and electronically causing, based on the discovery of the second instance of the occurrence, a change in the environment via an electronically-controlled device. | 2019-06-20 |
20190188576 | DISTRIBUTED ACTIVITY CONTROL SYSTEMS AND METHODS - A dynamic, distributed directed activity network comprising a directed activity control program specifying tasks to be executed including required individual task inputs and outputs, the required order of task execution, and permitted parallelism in task execution; a plurality of task execution agents, individual of said agents having a set of dynamically changing agent attributes and capable of executing different required tasks in said activity control; a plurality of task execution controllers, each controller associated with one or more of the task execution agents with access to dynamically changing agent attributes; a directed activity controller for communicating with said task execution controllers for directing execution of said activity control program; a communications network capable of supporting communication between said directed activity controller and task execution controllers; and wherein said directed activity controller and task execution controllers communicate via said communication network to execute said directed activity control program using selected task execution agents. | 2019-06-20 |
20190188577 | DYNAMIC HARDWARE SELECTION FOR EXPERTS IN MIXTURE-OF-EXPERTS MODEL - A system assigns experts of a mixture-of-experts artificial intelligence model to processing devices in an automated manner. The system includes an orchestrator component that maintains priority data that stores, for each of a set of experts, and for each of a set of execution parameters, ranking information that ranks different processing devices for the particular execution parameter. In one example, for the execution parameter of execution speed, and for a first expert, the priority data indicates that a central processing unit (“CPU”) executes the first expert faster than a graphics processing unit (“GPU”). In this example, for the execution parameter of power consumption, and for the first expert, the priority data indicates that a GPU uses less power than a CPU. The priority data stores such information for one or more processing devices, one or more experts, and one or more execution characteristics. | 2019-06-20 |
20190188578 | AUTOMATIC DISCOVERY OF DATA REQUIRED BY A RULE ENGINE - Methods and systems for automatically discovering data types required by a computer-based rule engine for evaluating a transaction request are presented. Multiple potential paths for evaluating the transaction request according to the rule engine are determined. An abstract syntax tree may be generated based on the rule engine to determine the multiple potential paths. Based on an initial set of data extracted from the transaction request, one or more potential paths that are determined to be irrelevant to evaluating the transaction request are identified. Types of data required to evaluate the transaction request according to the remaining potential paths are determined. Only data that corresponds to the determined types of data is retrieved to evaluate the transaction request. | 2019-06-20 |
20190188579 | SELF LEARNING DATA LOADING OPTIMIZATION FOR A RULE ENGINE - Methods and systems for using machine learning to automatically determine a data loading configuration for a computer-based rule engine are presented. The computer-based rule engine is configured to use rules to evaluate incoming transaction requests. Data of various data types may be required by the rule engine when evaluating the incoming transaction requests. The data loading configuration specifies pre-loading data associated with at least a first data type and lazy-loading data associated with at least a second data type. Statistical data such as use rates and loading times associated with the various data types may be supplied to a machine learning module to determine a particular loading configuration for the various data types. The computer-based rule engine then loads data according to the data loading configuration when evaluating a subsequent transaction request. | 2019-06-20 |
20190188580 | SYSTEM AND METHOD FOR AUGMENTED MEDIA INTELLIGENCE - Aspects of the present disclosure involve systems, methods, devices, and the like for augmented media intelligence using data analytics, machine learning and data visualization. In one embodiment, a system is introduced that can retrieve real-time data from social media platforms to perform augmented media intelligence analytics. The augmented media system is designed to generate reports/actionable insights for user visualization on an interactive user interface, where the reports are based in part on the user social currency. | 2019-06-20 |
20190188581 | SWITCHING FROM CALENDAR-BASED TO PREDICTIVE MAINTENANCE: A LEANER AND FASTER SOFTWARE-BASED SOLUTION ORCHESTRATING DATA-DRIVEN FORECASTING MODELS - A computer-implemented method for performing predictive maintenance includes executing a fleet prediction process. During this fleet prediction process, a plurality of fleet data records is collected. Each fleet data record comprises sensor data from a particular physical component in a fleet of physical components. A plurality of component maintenance predictions related to the fleet of physical components is generated. Each component maintenance prediction corresponds to a particular physical component. The plurality of component predictions are merged into one or more fleet maintenance predictions and the fleet maintenance predictions are presented to one or more users. Following the fleet prediction process, a next execution of the fleet prediction process is scheduled based on the fleet maintenance predictions. | 2019-06-20 |
20190188582 | COLLECTIVE DECISION MAKING BY CONSENSUS IN COGNITIVE ENVIRONMENTS - Techniques are provided to automatically facilitate a decision process to enable a set of decision makers to reach a decision that represents consensus or near-consensus among the decision makers. The method comprises: obtaining input representing a set of decision alternatives and indicators of desirability corresponding to the decision alternatives; analyzing a degree of consensus among the decision makers in accordance with the desirability indicators obtained; in response to the degree of consensus being deemed sufficient, reporting the decision to the decision makers; otherwise, actively suggesting to the decision makers a set of one or more discussions in which they should engage, and for each of those discussions which decision alternatives should be discussed and which of the decision makers should participate in the discussion; and interacting with the decision makers to facilitate the discussion in order to obtain a degree of consensus that is deemed sufficient. | 2019-06-20 |
20190188583 | SYSTEM AND METHOD TO RECOMMEND MITIGATION ACTION USING CONVERSATIONAL AGENT - A mitigation action recommendation method, system, and computer program product, includes building a cognitive machine learning model for a conversational agent, querying a user, via the conversational agent, to create a profile of the user by comparing answers from the user to the cognitive machine learning model to determine missing data, and creating a new query, based on the cognitive machine learning model, to acquire, via the conversational agent, at least some of the missing data from the user to update the profile. | 2019-06-20 |
20190188584 | Computer System And Method For Building And Deploying Models Predicting Plant Asset Failure - A system that provides an improved approach for detecting and predicting failures in a plant or equipment process. The approach may facilitate failure-model building and deployment from historical plant data of a formidable number of measurements. The system implements methods that generate a dataset containing recorded measurements for variables of the process. The methods reduce the dataset by cleansing bad quality data segments and measurements for uninformative process variables from the dataset. The methods then enrich the dataset by applying nonlinear transforms, engineering calculations and statistical measurements. The methods identify highly correlated input by performing a cross-correlation analysis on the cleansed and enriched dataset, and reduce the dataset by removing less-contributing input using a two-step feature selection procedure. The methods use the reduced dataset to build and train a failure model, which is deployed online to detect and predict failures in real-time plant operations. | 2019-06-20 |
20190188585 | MULTI-ROUND QUESTIONING AND ANSWERING METHODS, METHODS FOR GENERATING A MULTI-ROUND QUESTIONING AND ANSWERING SYSTEM, AND METHODS FOR MODIFYING THE SYSTEM - The present invention provides a multi-round questioning and answering method, a method for generating a multi-round questioning and answering system and a method for modifying a multi-round questioning and answering system. The multi-round questioning and answering method includes: acquisition initial request information, and matching the initial request information with a knowledge point in a knowledge base; if it is determined that the initial request information matches with a thematic question in a thematic knowledge point, triggering a root node of a multi-round questioning and answering flow module corresponding to the thematic knowledge point; and, performing, according to a first interaction node to which the multi-round questioning and answering flow module is proceeded currently, one or more knowledge points corresponding to the first interaction node stored in the knowledge base and user interaction information input by an interactive user, questioning and answering interaction with the interactive user. | 2019-06-20 |
20190188586 | METHODS OF PROCESSING AND GENERATING IMAGE DATA IN A CONNECTIONIST NETWORK - A method of processing image data in a connectionist network comprises a plurality of units, wherein the method implements a multi-channel unit forming a respective one of the plurality of units, and wherein the method comprises: receiving, at the data input, a plurality of input picture elements representing an image acquired by means of a multi-channel image sensor, wherein the plurality of input picture elements comprise a first and at least a second portion of input picture elements, wherein the first portion of input picture elements represents a first channel of the image sensor and the second portion of input picture elements represents a second channel of the image sensor; processing of the first and at least second portion of input picture elements separately from each other; and outputting, at the data output, the processed first and second portions of input picture elements. | 2019-06-20 |
20190188587 | MODEL GUIDED DEEP LEARNING APPROACH TOWARDS PREDICTION OF PHYSICAL SYSTEM BEHAVIOR - Systems and methods are provided for controlling predictive medical monitoring. A non-linear-predictive-guide model estimates a patient parameter that is used as a guide in a deep neural network for improving accuracy of estimation by the deep neural network. The guide model generates a guiding first estimated patient parameter based on the guide model and patient input data. The deep neural network generates a second estimated patient parameter based on the deep neural network, the patient input data, and the guiding first estimated patient parameter. The deep neural network includes an input layer that receives the guiding first estimated patient parameter, and hidden layers including respective artificial neurons configured to perform a linear or nonlinear transformation on output of at least one artificial neuron from an adjacent layer in the deep neural network. An output layer receives at least one output from a hidden layer. | 2019-06-20 |
20190188588 | FEATURE CONTRIBUTORS AND INFLUENCERS IN MACHINE LEARNED PREDICTIVE MODELS - In an example, for each feature of one or more features of a target sample data, feature values for one or more pseudo-samples are generated using, localized stratified sampling. The one or more pseudo-samples are fed into the trained machine learned model to obtain their prediction values. A piecewise linear regression model is trained using the one or more pseudo-samples and their prediction values, the piecewise linear regression model having two coefficients for each feature, a first coefficient describing prediction change when a corresponding feature value is increased and a second coefficient describing prediction change when a corresponding feature value is decreased. A top positive feature influencer is identified based on a feature of the one or more features of the target sample having a greatest magnitude of positive first coefficient or greatest magnitude of negative second coefficient. A top negative feature influencer is identified based on a feature of the one or more features of the target sample having a greatest magnitude of negative first coefficient or greatest magnitude of positive second coefficient. A top feature contributor is identified based on a feature of the one or more features of the target sample having a greatest magnitude of a combination of second coefficient and feature value in the target sample data. | 2019-06-20 |
20190188589 | SYSTEMS AND METHODS FOR PREDICTING PERSISTENT MEMORY DEVICE DEGRADATION BASED ON OPERATIONAL PARAMETERS - In accordance with embodiments of the present disclosure, an information handling system may include a processor, a memory system communicatively coupled to the processor, the memory system comprising one or more persistent memory modules, each of the one or more persistent memory modules comprising a volatile memory and a non-volatile memory, and a management controller communicatively coupled to the processor and the memory system. The management controller may be configured to correlate temperature sensor information with one or more other operational parameters associated with the one or more persistent memory modules and predict a likelihood of degradation of the one or more persistent memory modules based on correlation of the temperature sensor information with the one or more other operational parameters. | 2019-06-20 |
20190188590 | Chatbot Integrating Derived User Intent - A method provides information to a user as a function of derived user intent. The method includes receiving input from a user, generating an intent vector by processing the received input though an artificial intelligence model that has been trained with data representative of the user's intention, wherein the intent vector comprises a probability for each intent in a known set of possible intents, executing a trigger control model to determine whether to respond to the user as a function of the input from the user and the intent vector, utilizing the trigger control model, received input, and intent vector input to generate a response via a trained chatbot, and providing the response via an output device. | 2019-06-20 |
20190188591 | NEARLINE UPDATES TO PERSONALIZED MODELS AND FEATURES - The disclosed embodiments provide a system for processing data. During operation, the system obtains events reflecting responses by a user to job recommendations outputted to the user. Next, the system updates a set of features for the user from the events. The system then includes the updated set of features in a feature repository for use by a statistical model in generating a ranking of jobs for the user. Finally, the system retrains the statistical model using the events prior to using the statistical model to update the outputted job recommendations using the ranking. | 2019-06-20 |
20190188592 | Model-Based Control Under Uncertainty - An apparatus for controlling a system includes a memory to store a model of the system including a motion model of the system subject to process noise and a measurement model of the system subject to measurement noise, such that one or combination of the process noise and the measurement noise forms an uncertainty of the model of the system with unknown probabilistic parameters, wherein the uncertainty of the model of the system causes a state uncertainty of the system with unknown probabilistic parameters. The apparatus also includes a sensor to measure a signal to produce a sequence of measurements indicative of a state of the system, a processor to estimate a Gaussian distribution representing the state uncertainty, and a controller to determine a control input to the system using the model of the system with state uncertainty represented by the Gaussian distribution and control the system according to the control input. The processor is configured to estimate, using at least one or combination of the motion model, the measurement model, and the measurements of the state of the system, a first Student-t distribution representing the uncertainties of the model and a second Student-t distribution representing the state uncertainty of the system, the estimation is performed iteratively until a termination condition is met, and fit a Gaussian distribution representing the state uncertainty into the second Student-t distribution. | 2019-06-20 |
20190188593 | METHOD AND SYSTEM FOR REDUCING RISK VALUES DISCREPANCIES BETWEEN CATEGORIES - The present teaching generally relates to removing perturbations from predictive scoring. In one embodiment, data representing a plurality of events detected by a content provider may be received, the data indicating a time that a corresponding event occurred and whether the corresponding event was fraudulent. First category data may be generated by grouping each event into one of a number of categories, each category being associated with a range of times. A first measure of risk for each category may be determined, where the first measure of risk indicates a likelihood that a future event occurring at a future time is fraudulent. Second category data may be generated by processing the first category data and a second measure of risk for each category may be determined. Measure data representing the second measure of risk for each category and the range of times associated with that category may be stored. | 2019-06-20 |
20190188594 | PREDICTING SITE VISIT BASED ON INTERVENTION - A method can include determining a first probability that a first member of members of a website will visit the website within a specified time window if the first member is provided an intervention at a specified time, determining a second probability that the first member will visit the website within the specified time window without being provided the intervention, determining a difference between the first and second probability, and in response to determining the difference is greater than a first specified threshold, providing the intervention at the specified time. | 2019-06-20 |
20190188595 | Method for Preloading Application, Storage Medium, and Terminal Device - A method for preloading an application, a storage medium, and a terminal device are provided. The method includes the following. Current state feature information of the terminal device is acquired, when an application preloading prediction event is detected to be triggered. The current state feature information is input into a plurality of CART prediction models each corresponding to an application in a preset application set, where each of the CART prediction models is generated based on a usage regularity of an associated application corresponding to historical state feature information of the terminal device. A target application to be initiated is predicted according to output results of the CART prediction models, and then the target application is preloaded. | 2019-06-20 |
20190188596 | SUPERCONDUCTING SYSTEM ARCHITECTURE FOR HIGH-PERFORMANCE ENERGY-EFFICIENT CRYOGENIC COMPUTING - An energy efficient rapid single flux quantum (ERSFQ) logic register wheel includes a circular shift register having a plurality of destructive read out (DRO) cells. Each entry of the circular shift register includes a data block, a tag, and a valid bit. A compare and control logic is coupled to the circular shift register to compare a source specifier or a destination register specifier against a register tag stored in the wheel following each cycle of the register wheel. At least one or more read ports and at least one or more write ports are coupled to the circular shift register to write to or to read from a different entry each in the register wheel following each cycle of the register wheel. A RSFQ clearable FIFO with flushing and a crosspoint memory topology for integrating MRAM devices with ERSFQ circuits are also described. | 2019-06-20 |
20190188597 | Magnetic Flux Control in Superconducting Device - A device includes: a first qubit including a first co-planar waveguide; a second qubit including a second co-planar waveguide, in which the second co-planar waveguide crosses the first co-planar waveguide; and a qubit coupler including a loop having a first lobe and a second lobe, in which a first portion of the first lobe extends parallel to the first co-planar waveguide, a second portion of the first lobe extends parallel to the second co-planar waveguide, a first portion of the second lobe extends parallel to the first co-planar waveguide, and a second portion of the second lobe extends parallel to the second co-planar waveguide. | 2019-06-20 |
20190188598 | LEARNING METHOD, PREDICTION METHOD, LEARNING DEVICE, PREDICTING DEVICE, AND STORAGE MEDIUM - A non-transitory computer-readable storage medium storing a program that causes a computer to execute a process, the process includes learning a learning model using a first training data group obtained by excluding a test data group from a plurality of training data items; calculating prediction accuracy of the learning model using the test data group; and when the prediction accuracy satisfies the predetermined requirement, learning an error prediction model for determining whether an error of a value predicted by the learning model satisfies a predetermined requirement, by using a second training data group obtained by excluding the test data group and the first training data group from the plurality of training data items. | 2019-06-20 |
20190188599 | INFORMATION PROCESSING METHOD, INFORMATION PROCESSING APPARATUS, AND PROGRAM - Provided are an information processing method, an information processing apparatus, and a program that can increase a diversity of learning data for configurations or techniques of unspecified devices. The information processing method includes: obtaining sensor data obtained by a sensor installed in a vehicle, and at least one type of traveling data of the vehicle; associating the sensor data and the at least one type of traveling data with each other; determining a degree of difference of the at least one type of traveling data from the at least one type of one or more traveling data associated with one or more sensor data; and selecting the sensor data as learning data according to the degree of difference. | 2019-06-20 |
20190188600 | Secure Voice Communications System - Disclosed herein are system and method embodiments for establishing secure communication with a remote artificial intelligent device. An embodiment operates by capturing an auditory signal from an auditory source. The embodiment coverts the auditory signal into a plurality of pulses having a spatio-temporal distribution. The embodiment identifies an acoustic signature in the auditory signal based on the plurality of pulses using a spatio-temporal neural network. The embodiment modifies synaptic strengths in the spatio-temporal neural network in response to the identifying thereby causing the spatio-temporal neural network to learn to respond to the acoustic signature in the acoustic signal. The embodiment transmits the plurality of pulses to the remote artificial intelligent device over a communications channel thereby causing the remote artificial intelligent device to learn to respond to the acoustic signature, and thereby allowing secure communication to be established with the remote artificial intelligent device based on the auditory signature. | 2019-06-20 |
20190188601 | PRESENTING ANTICIPATED USER SEARCH QUERY RESULTS PROMPTED BY A TRIGGER - A method for presenting search query results is provided. The method may include detecting an occurrence of the trigger event. The method may include determining a category of information based on data associated with the trigger event. The method may include identifying at least one constraint based on the determined category of information. The method may include appending to the identified at least one constraint to the determined category of information. The method may include generating at least one search query. The method may include selecting at least one candidate website based on the category of information. The method may include performing the at least one search query on the at least one candidate website. The method may include filtering each search query result within the search query results. The method may include sending each filtered search query result within the search query results to a user. | 2019-06-20 |
20190188602 | METHOD, APPARATUS, AND SYSTEM FOR PROVIDING A LOCATION-AWARE EVALUATION OF A MACHINE LEARNING MODEL - An approach is provided for a location-aware evaluation of a machine learning model. The approach, for example, involves designating a geographic area for creating an evaluation dataset for the machine learning model. The approach also involves separating a plurality of observation data records into the evaluation dataset and a training dataset based on a comparison of a respective data collection location of each of the plurality of observation data records to the geographic area. The training dataset is then used to train the machine learning model, and the evaluation dataset is used to evaluate the trained machine learning model. | 2019-06-20 |
20190188603 | WEAKLY-SUPERVISED FRAUD DETECTION FOR TRANSPORTATION SYSTEMS VIA MACHINE LEARNING - Example methods and systems disclosed herein train an accurate machine-learned model that detects fraud within an electronic transportation system. A first model is trained on a first (comparatively small) set of trip data items representing trips taken, or requested, in the electronic transportation system. The first set of trip data items have been manually labeled by human analysts to determine whether the trips were or were not fraudulent. The first model is used to generate weak labels for a second (comparatively larger) set of trip data items that lack manual labels. The weak labels are used along with the second set of trip data items to train a second model that is more accurate than the first model for detecting fraud. | 2019-06-20 |
20190188604 | MACHINE LEARNING SYSTEM FOR PREDICTING OPTIMAL INTERRUPTIONS BASED ON BIOMETRIC DATA COLLLECTED USING WEARABLE DEVICES - Method and apparatus for using machine learning to monitor biometric data to provide intelligent alerts are provided. At a first moment in time, first biometric data for a plurality of users are received from a plurality of sensor devices. A group metric is generated by processing the first biometric data using at least one trained machine learning model, and it is determined that the group metric does not satisfy one or more predefined criteria. At a second moment in time, second biometric data for the plurality of users is received from the plurality of sensor devices, and an updated group metric is generated by processing the second biometric data using the at least one trained machine learning model. Upon determining that the updated group metric satisfies the one or more predefined criteria, an indication is provided that the one or more predefined criteria have been satisfied. | 2019-06-20 |
20190188605 | Machine Learning Model Understanding As-A-Service - Concepts and technologies disclosed herein are directed to machine learning model understanding as-a-service. According to one aspect of the concepts and technologies disclosed herein, a model understanding as-a-service system can receive, from a user system, a service request that includes a machine learning model created for a user associated with the user system. The model understanding as-a-service system can conduct an analysis of the machine learning model in accordance with the service request. The model understanding as-a-service system can compile, for the user, results of the analysis of the machine learning model in accordance with the service request. The model understanding as-a-service system can create a service response that includes the results of the analysis. The model understanding as-a-service system can provide the service response to the user system. | 2019-06-20 |
20190188606 | SYSTEM AND METHOD FOR CLINICAL INTELLIGENT AGENTS IMPLEMENTING AN INTEGRATED INTELLIGENT MONITORING AND NOTIFICATION SYSTEM - A method includes: receiving, at a clinical intelligent agent, patient specific data comprising a room location of a patient within a healthcare facility and information regarding the condition of the patient in the room; comparing, using a monitor of the clinical intelligent agent, patient specific data with historical reference data to detect clinical patterns; producing, using an alerting agent of the clinical intelligent agent, one or more alerts when a processor identifies a clinical pattern indicating an alert situation; sending, using the alerting agent, the one or more alerts to a patient screen located in the room occupied by the patient; scoring, using the clinical intelligent agent, the one or more alerts; and prioritizing, using the clinical intelligent agent, care provider tasks displayed on the patient screen based on the score of the one or more alerts. Other aspects are described and claimed. | 2019-06-20 |
20190188607 | MOBILE COMMERCIAL SYSTEMS AND METHODS - Methods, systems, and machine-readable media are disclosed for utilizing mobile electronic devices in various types of financial transactions. According to one embodiment, a method of providing a plurality of mobile commerce functions can comprise receiving a communication related to a function of a mobile wallet application of a mobile device. One or more of a plurality of acquirer systems for handling of the communication can be identified based on the function of the mobile wallet application to which the communication relates. The communication can be routed to the identified one or more acquirer systems for handling of the communication. In some cases, a reply to the communication can be received from at least one of the identified one or more acquirer systems and the reply can be sent to a recipient. | 2019-06-20 |
20190188608 | SYSTEMS, DEVICES, AND METHODS FOR SEARCHING AND BOOKING RIDE-SHARED TRIPS - Embodiments relate to systems and methods for electronically booking ride share trips. The systems and methods can involve a data storage device storing ride sharing records with itineraries including a plurality of legs. The systems and methods can involve at least one processor configured to receive a trip booking request for a passenger, the trip booking request defining passenger constraints including a desired pickup time or drop off time. | 2019-06-20 |
20190188609 | SYSTEM WITH SEAT MAP CACHE - An apparatus includes a cache and a hardware processor. The cache stores first and second seat maps for a first flight leg and a second flight leg, respectively. The apparatus determines a flight segment from a first location and a second location included in a request from a user. The flight segment includes the first flight leg and the second flight leg. The first and second seat maps are retrieved from the cache. The apparatus communicates the flight segment and the first and second seat maps to the user. The user selects the flight segment. The apparatus obtains updated first and second seat maps from one or more airline computer reservations systems (CRS) and updates the cache. The updated seat maps are presented to the user. Seat selections from each seat map are received from the user. The apparatus reserves the seat selections in the respective CRS(s). | 2019-06-20 |
20190188610 | Multi-Modal Directions with a Ride Service Segment in a Navigation Application - To provide ride services within a mapping application in a client computing device without directing the user to a separate ride service application, the mapping application invokes one or several ride service APIs to access ride service data from various ride service providers. For example, the mapping application receives a request for travel directions to a destination and generates multi-modal travel directions which include a route segment where the mode of transportation is a ride service. The mapping application invokes one or several ride service APIs to retrieve a price estimate, estimated wait time, or any other suitable information regarding the ride service route segment. Accordingly, the mapping application provides the multi-modal travel directions to a user including information regarding the ride service route segment. | 2019-06-20 |
20190188611 | MULTI-STEP TIME SERIES FORECASTING WITH RESIDUAL LEARNING - A method includes receiving training data including sequential data, determining a plurality of future time points, generating a first prediction by applying a first forecasting algorithm to the training data, generating a second prediction by applying a second forecasting algorithm to the training data, extracting predicted values from the first prediction and the second prediction that corresponds to a future time point of the plurality of future time points, applying a regression model in sequence on each of the plurality of future time points to generate a final predicted value of each of the plurality of future time points, and outputting the final predicted values of the plurality of future time points. | 2019-06-20 |
20190188612 | SYSTEMS AND METHODS FOR BUSINESS ANALYTICS MANAGEMENT AND MODELING - The present invention relates to systems and methods for model generation. The model is generated by selecting indicators that are relevant to the model, determining a strength score for each of the indicators, ranking the indicators by their strength scores, and bucketizing the indicators. Different permutations of the indicators are then selected for modeling in parallel. The model results are compared, and the ‘best’ model (most historically accurate) is selected for display within a report | 2019-06-20 |
20190188613 | METHODS AND APPARATUS TO MONITOR WORK VEHICLES AND TO GENERATE WORKLISTS TO ORDER THE REPAIR OF SUCH WORK VEHICLES SHOULD A MACHINE FAILURE BE IDENTIFIED - Methods and apparatus to monitor work vehicles and to generate worklists to order the repair of such work vehicles should a machine failure be identified are disclosed. An apparatus includes a model generator to generate a model by collating warranty data, parts and associated maintenance data, and reference alert and measurement data for work vehicles, the reference alert and measurement data including a first alert from a first work vehicle and a second alert from a second work vehicle; associate the first and second alerts with at least one of a first classification, a second classification, or a third classification based on work vehicle operating parameters; determine a first weighting factor for the first alert and a second weighting factor for the second alert within the model based on information from at least one of a weighting factor database, owner/operator input, work order data, or worklist data to prioritize the first alert or the second alert within the model; and update the model based on associating the first and second weighting factors with the first and second alerts; and a processor to generate a display including worklist and work order information. | 2019-06-20 |
20190188614 | DEVIATION ANALYTICS IN RISK RATING SYSTEMS - A set of operational risk rating algorithms is received. A set of operational risk rating weight factors is applied to the set of operational risk rating algorithms. An initial operational risk rating score of an entity associated with the selected domain category is generated based on the set of operational risk rating algorithms applied with the set of operational risk rating weight factors. A baseline operational risk rating score is retrieved based on the selected domain category. A deviation value is determined based on comparing the retrieved baseline operational risk rating score and the initial operational risk rating score. | 2019-06-20 |
20190188615 | UNIVERSAL MODEL SCORING ENGINE - Methods and systems for generating a universal computer model for assessing a risk in an electronic transaction based on one or more risk assessment models are presented. The one or more risk assessment models may be incompatible with each other. Different portions of a risk assessment models may be extracted from the risk assessment models. A node structure is generated for each risk assessment model based on the portions extracted from a corresponding risk assessment model. The node structures generated based on the risk assessment models are merged to produce a merged node structure. The universal computer model is generated based on the merged node structure. | 2019-06-20 |
20190188616 | RISK SIMULATION AND ASSESSMENT TOOL - A risk simulation and assessment tool may enable a user to select scenarios and risk factors associated with a selected scenario. The risk factors may be defined by risk factor characteristics along with links that define connectivity or interconnectedness to other risk factors. The risk factor characteristics may also include impact, velocity, and likelihood. The tool may provide for a simplified way to create a computerized network map that includes the nodes of risk factors associated with each of the scenarios. The computerized network map may be displayed and dynamic adjustment may be available to the user. A simulation using the computerized network map may also be executed as defined by the risk factor characteristics, thereby enabling a user to determine how operations of an organization may be impacted by changing events that may occur in regions in which physical operations of an organization of the user exist. | 2019-06-20 |
20190188617 | DYNAMIC LEAD GENERATION - A system for electronic lead generation including a semantic graph database including a knowledge graph and a dynamic profiling module comprising automated computing machinery configured to identify a near-term surge in product interest for a number of companies of a particular size in a particular industry in a particular region of the world in dependence upon the knowledge graph and create a company profile in dependence upon the size of the identified companies, the industry of the identified companies, and the region of the world of the identified companies associated with the near-term surge. Embodiments also include a lead purchase module comprising automated computing machinery configured to generate an electronic lead purchase order in dependence upon the company profile; transmit the lead purchase order to a lead generation engine; and receive, from the lead generation engine, a plurality of leads in dependence upon the lead purchase order. | 2019-06-20 |
20190188618 | Automatic Wellbore Activity Schedule Adjustment Method and System - A method for scheduling wellbore construction activities includes entering a well plan into a computer. The well plan includes estimated start and stop times for a plurality of activities in a predetermined sequence. Progress of selected ones of the plurality of activities is measured during their performance. In the computer, expected ending time of at least one of the plurality of activities is recalculated based on progress thereof during that activity. In the computer, expected start and stop times are recalculated for each activity subsequent to the activity in progress based on the recalculated expected ending time. The recalculated start and stop times for each subsequent activity are displayed. | 2019-06-20 |
20190188619 | COLLABORATIVE ENTERPRISE SHARED RESOURCE STATUS SYSTEM - A status system suitable for monitoring and maintaining status for shared resources is provided. The status system obtains status for a shared resource from a plurality of users of the shared resource, the status indicating an observed status of the shared resource received via a device of each of the plurality of users. Based on the obtained status from the plurality of users, the status system determines a current status for the shared resource. A central database in a central data storage is updated with the current status for the shared resource. In response to a request for the status of the shared resource, the status system retrieves the current status of the shared resource and causes display of the current status in a user interface. | 2019-06-20 |
20190188620 | SYSTEM AND METHOD FOR LOCATION SENSOR ASSOCIATION - A method includes receiving, with a controller of a paving plant, a first signal from a location sensor associated with a haul truck, the first signal including information indicating a first location of the haul truck. The method also includes generating a paving material ticket with the controller, the paving material ticket including a first identifier unique to the haul truck. The method further includes determining, with the controller, whether the first location is within a first geofence disposed within a perimeter of the paving plant. The controller is also configured to associate the first identifier with the location sensor in a memory connected to the controller. | 2019-06-20 |
20190188621 | PRODUCT NARROWING DOWN SUPPORT SYSTEM AND METHOD - A product narrowing down support system in an enterprise dealing with various kinds of goods, includes a processing unit and a storage unit, in which the storage unit stores, a product master table storing various kinds of goods, a management index database storing a management index of the enterprise and data thereof for each product, and a factor index database storing a factor index for each department affected by multiple products and data thereof for each product, and the processing unit narrows down a product which greatly influences deterioration in the management index for each management index by VC crossing to specify a product of a target for which a measure is to be implemented. | 2019-06-20 |
20190188622 | SYSTEMS AND METHODS TO PROVIDE CUSTOMIZED PRODUCT INFORMATION - The disclosed embodiments include systems and methods to provide customized product information for display. In one embodiment, the system includes a sensor positioned proximate a production line, where the production line is operable to transport an optical product and a product label along the production line, and where the sensor is operable to obtain identification information of the optical product from the product label. The system also includes a storage medium containing product information of the optical product and business rules for providing the product information of the optical product for display. The system further includes a processor operable to determine the identification of the optical product, obtain business rules based on the identification of the optical product, dynamically customize the product information of the optical product based on the business rules, and provide the customized product information for display on an electronic display positioned along the production line. | 2019-06-20 |
20190188623 | COGNITIVE AND DYNAMIC BUSINESS PROCESS GENERATION - In an approach for providing a cognitive and dynamic business process, based on a user's natural language input, a processor receives information from a user, wherein the information includes natural language input. A processor analyzes the information from the user, using natural language processing. A processor generates a cognitive and dynamic business process, wherein the cognitive and dynamic business process assists the user to determine a solution to a problem. A processor delivers the cognitive and dynamic business process, wherein the delivered cognitive and dynamic business process includes a request for feedback. A processor analyzes the feedback, wherein the cognitive and dynamic business process is tagged with the feedback and stored, and wherein the feedback is based on feedback from the user and a subject matter expert. | 2019-06-20 |
20190188624 | AUTOMATED ONE-TO-MANY SCHEDULING OF INTERVIEWS WITH CANDIDATES - The disclosed embodiments provide a system for processing data. During operation, the system obtains, for a set of interviews with a candidate, a set of constraints that includes availabilities of a set of interviewers, a set of available time slots, and a time period spanned by the set of interviews. Next, the system generates, using the set of constraints, an interview schedule that includes an assignment of the set of interviewers to a subset of the available time slots in the time period by sequentially matching each time slot in the subset of the available time slots to the availabilities of the set of interviewers. The system then schedules the set of interviews according to the interview schedule. | 2019-06-20 |
20190188625 | METHOD AND SYSTEM FOR COMMUNICATING JOB ASSIGNMENT INFORMATION TO A USER - A method for execution by a computing apparatus comprising identifying a job to be assigned to an employee, the job requiring a given job qualification, wherein the given job qualification is associated with at least one requirement for maintaining the job qualification and a time-frame during which the at least one requirement should be satisfied. Completion of the job by an employee at least partially completes the at least one requirement for maintaining the job qualification. The method further comprises assigning the job to a selected employee from a set of employees, wherein each employee in the set of employees has the given job qualification. The selected employee is selected at least in part on a basis of a probability of the selected employee losing the job qualification relative to other employees in the set of employees. | 2019-06-20 |
20190188626 | Intermediated communication in a crowdsourced environment - Techniques for improving communication and expectation setting between various parties/communities of a crowdsourced platform are disclosed. The platform is used for reporting issues in a target system, program or product. A customer/subscriber entity enters a target brief in the platform. In response, a researcher enters a submission in the system. If the submission is valid, it is presented to the customer and a response-time or service level agreement (SLA) timer is started. If the customer agrees with the submission, it is marked as complete and the researcher is paid. If the customer disputes the submission, a third-party intervenes and the timer is paused until dispute resolution. If the submission requires more information the researcher is requested accordingly and the timer is reset. If at any point, the timer expires, the parties are notified and the submission is closed. | 2019-06-20 |
20190188627 | SYSTEM FOR CREATING COLLABORATIVE PROJECT DATA - A platform system for creating collaborative project data where a project collaborators create projects and content by inputting project information on a platform and recording the project information on a public or private blockchain. A plurality of data researchers collect data from various entities based upon the project information and then record the collected data on the blockchain. Collected data is selected based on criteria and payment made to the data researcher. | 2019-06-20 |
20190188628 | Measuring Video-Asset Viewing - A computer-implemented method of using channel tuning data from a video asset viewing device connected to a network to measure video asset viewing at a second-by-second level during one or more user defined lead-in periods, and then correlating that with video asset viewing during a user defined target period, for the purpose of analyzing how viewing activity during the lead-in period(s) correlates with viewing activity during the target period, thus producing longitudinal viewing metrics; all while maintaining viewer anonymity. Additionally, viewing metrics can be categorized based on user defined demographic, geographic, and histogram groupings representing the percentage of video asset viewing with the result that the analyst is able to gain detailed insight into customer viewing behavior. The lead-in video asset may be any video asset or assets. The target may be any subsequent video asset. The metrics produced are useful to service providers, advertisers, and content producers. | 2019-06-20 |
20190188629 | GOODS SHIPMENT MANAGEMENT SYSTEM AND METHOD - A goods shipment management system includes a management server. The management server includes a front end for performing an electronic transaction in response to an order from a customer terminal in a customer residence. The goods shipment management system performs control and management such that certain items of the goods that can be delivered from the nearby base to the customer residence when an order of any item of the goods is placed from the customer terminal are managed as stock goods and a predetermined number of items of the stock goods are stocked in the nearby base, remaining items of the goods other than the stock goods are managed as non-stock goods, and any item of the non-stock goods is delivered from the distribution center to the customer residence via the nearby base when an order of the item of non-stock goods is placed from the customer terminal. | 2019-06-20 |
20190188630 | SYSTEM AND METHOD OF ORDER PROCESSING WITH SMART COOL-DOWN - An order processing system includes a computing device, which includes a processor and a storage device storing computer executable code. The computer executable code, when executed at the processor, is configured to: receive an order, determine a cool-down period of the order based on a cost function, and dispatch the order to a warehouse platform when the cool-down period expires. The cost function takes into account at least a waste cost due to process by the warehouse platform according to the order in case of possible cancellation of the order after the cool-down period and a delay cost due to delayed dispatching of the order to the warehouse platform by the cool-down period. The cool-down period is determined as one that minimizes the cost function in a prescribed range. | 2019-06-20 |
20190188631 | SYSTEMS AND METHODS FOR MULTI-SENSOR TAG SALE OPTIMIZATION - Systems and methods for multi-sensor tag sale optimization. The methods comprise: analyzing sensor data generated by sensors internal to a tag, coupled to an item of an item set that is being handled by a first individual, to determine if the item was carried to a checkout lane of a retail store; and determining whether a sale conversion for the item occurred. If a sale conversion for the item occurred, performing the following operations: analyzing historical sale transaction information to determine a total number of sales of items in the item set over a first given period of time; comparing the total number of sales to a first threshold value; and causing content displayed on the tag's electronic visual display to be dynamically changed so as to include a sale price for the item, when the total number of sales is less than or equal to the first threshold value. | 2019-06-20 |
20190188632 | SYSTEM AND METHOD FOR PIECE PICKING OR PUT-AWAY WITH A MOBILE MANIPULATION ROBOT - A method and system for piece-picking or piece put-away within a logistics facility. The system includes a central server and at least one mobile manipulation robot. The central server is configured to communicate with the robots to send and receive piece-picking data which includes a unique identification for each piece to be picked, a location within the logistics facility of the pieces to be picked, and a route for the robot to take within the logistics facility. The robots can then autonomously navigate and position themselves within the logistics facility by recognition of landmarks by at least one of a plurality of sensors. The sensors also provide signals related to detection, identification, and location of a piece to be picked or put-away, and processors on the robots analyze the sensor information to generate movements of a unique articulated arm and end effector on the robot to pick or put-away the piece. | 2019-06-20 |
20190188633 | METHOD FOR MONITORING AND TRACKING IDENTIFIED MATERIALS IN FILLABLE RECEPTACLES - A method for monitoring and tracking identified material in at least one fillable receptacle in at least one facility using a moveable vehicle with GPS indicator. The method includes installing at least one sensor with an ultrasonic transducer or a laser or both in one of the fillable receptacles, creating a customer profile with a fillable receptacle location, a quantity of fillable receptacles and a preset height limit for each fillable receptacle, and activating the sensor to repeatedly transmit an ultrasonic signal or light pulse into the receptacles and calculate remaining empty space then comparing remaining empty space to the preset height limits to determine whether the fillable receptacle is full. Fillable receptacle locations are aggregated into a route and a driver is alerted to download the route, enabling drivers to pick up filled fillable receptacles and remove identified material at the fillable receptacle locations using the route. | 2019-06-20 |
20190188634 | STOCK MANAGEMENT DEVICE, ITEM SALES SYSTEM AND STOCK MANAGEMENT METHOD - Provide a stock management device capable of providing both a benefit of online shopping and a benefit by using a mobile sales vehicle, and also being capable of delivering, to a customer doing online shopping, an item which the customer wants, even when the item is purchased at a mobile sales vehicle. This stock management device is provided with: management means for managing stock information about stock of an item held by each of a plurality of mobile sales vehicles; first reception means for receiving sales information; second reception means for receiving order information; transmission means for transmitting the order information to the mobile sales vehicle; and detection means for detecting the item included in the order information becoming out-of-stock, wherein, when the item becoming out-of-stock is detected, the transmission means transmits the order information to another mobile sales vehicle. | 2019-06-20 |
20190188635 | AUTOMATED VEHICLE AND METHOD FOR SERVICING DISABLED VEHICLES - An economic priority of a cargo is determined based upon the financial information and delivery restrictions. Based upon sensed readings, the condition of the disabled delivery vehicle is determined and one or more proposed actions performable by the automated autonomous repair vehicle that would remedy the operational problems of the disabled delivery vehicle are identified. One (or more) of the proposed actions is selected based upon the economic priority of the cargo. The automated autonomous repair vehicle is caused to perform the selected action. | 2019-06-20 |
20190188636 | INFORMATION PROCESSING DEVICE, INFORMATION PROCESSING METHOD, AND NON-TRANSITORY STORAGE MEDIUM STORING INFORMATION PROCESSING PROGRAM - An information processing device includes: a target vehicle extracting unit configured to extract an available vehicle which is available as a delivery destination of luggage from a plurality of vehicles, the vehicles being rented as an accommodation place of an object, when a user of a delivery service in which an interior space including a trunk of the vehicles is able to be designated as the delivery destination of the luggage issues a delivery request of the luggage to a provider of the delivery service; and a target vehicle notifying unit configured to notify the user of the available vehicle. | 2019-06-20 |
20190188637 | INFORMATION PROCESSING DEVICE, INFORMATION PROCESSING METHOD, IMAGE ACQUISITION METHOD, AND NON-TRANSITORY COMPUTER-READABLE STORAGE MEDIUM - An information processing device is configured to perform an operation of a delivery service in which an inside of a vehicle, a building, or a facility used by a user is designated as a delivery destination of a package, or perform a support of the operation. The information processing device includes an information acquisition unit configured to acquire information on an accommodation situation of an object accommodated inside the vehicle, the building, or the facility, and an accommodation situation notification unit configured to notify the user of the accommodation situation based on the information acquired by the information acquisition unit. | 2019-06-20 |
20190188638 | METHODS AND SYSTEMS FOR IMPROVING VEHICLE SEARCHES - An example method can comprise receiving an indication of a scheduled delivery at a remote computing device and from a first device. The indication of the scheduled delivery can comprise one or more delivery parameters. A delivery schedule comprising the indication of the scheduled delivery can be transmitted from the remote computing device to a second device. A delivery update adjusting one or more of the delivery parameters can be received from a third device, and the delivery schedule can be updated based on the received delivery update. The updated delivery schedule can be transmitted to the second device. One or more security actions can be performed on a delivery vehicle based at least in part on the updated delivery schedule. | 2019-06-20 |
20190188639 | ON-DEMAND PURCHASING AND DELIVERY ECOSYSTEM - An on-demand ecosystem (ODE) computing device for integrating on-demand delivery services with purchase transactions is provided. The ODE computing device receives item data from a registered merchant, and receives availability data from at least one registered carrier. The ODE computing device further provides a searchable interface that enables a user to search for item data from the registered merchant, and receives a selected item from the user via the searchable interface. The selected item is offered for sale by the registered merchant and includes a selected pick-up location. The selected item is to be delivered to the user from the selected pick-up location. The ODE computing device also allows either the registered merchant or the user to select one of the at least one registered carriers, and processes a payment transaction for the selected item including an item price and a delivery fee. | 2019-06-20 |
20190188640 | STOCK MANAGEMENT DEVICE, CUSTOMER TERMINAL, AND STOCK MANAGEMENT METHOD - Provide a stock management device capable of bringing both a benefit of online shopping and a benefit by using a mobile sales vehicle to a customer purchasing an item by online shopping. This stock management device is provided with: management means for managing stock information about stock of an item held by each of a plurality of mobile sales vehicles performing mobile sale; first reception means for receiving sales information indicating and current position information; second reception means for receiving order information and desired delivery time information and delivery address information; first specification means for specifying a mobile sales vehicle capable of delivering the item by the desired delivery time; first transmission means for transmitting the stock information and transmitting the stock information; and second transmission means for transmitting the order information, wherein the management means updates the stock information. | 2019-06-20 |
20190188641 | ORDER ASSISTANCE SYSTEM - Provided is an order assistance system with which even an inexperienced person can readily determine an order quantity while taking a long-term view. This order assistance system is configured from a server computer installed in a manufacturing factory, a client computer installed in a store, and a network connecting the server computer and the client computer. The server computer stores a code master file and a sales result data file. The client computer stores an item data file and an order contact table file, and a variable data file is temporarily stored in an internal storage device. | 2019-06-20 |
20190188642 | METHOD AND APPARATUS FOR DETERMINING SOCIAL NETWORKING RELATIONSHIPS - An approach is provided for recognizing one or more people from media content and determining if the one or more people are associated with a social networking service. A request is received from a user equipment specifying a media content. Electronically processing of the media content to recognize one or more people is initiated. It is determined whether the one or more people are associated with a member account of a social networking service. A prompting of the user is initiated with an option based on the determination. | 2019-06-20 |
20190188643 | METHOD AND SYSTEM OF SHARING PRODUCT DATA IN A COLLABORATIVE ENVIRONMENT - A method and system for sharing product data in a collaborative environment is disclosed. In one embodiment, the method includes establishing a session for sharing product data between a source device and a target device. The method includes adaptively generating one or more payload files corresponding to the product data based on payload processing information. The payload processing information includes number of payload files waiting to be processed at the target device. Moreover, the method includes sending the one or more payload files to the target device over the product data sharing session such that the product data is reproduced at the target device using the payload files. | 2019-06-20 |
20190188644 | SYSTEMS AND METHODS FOR PROVIDING CONTEXTUAL CALENDAR REMINDERS - Systems and methods for providing contextual calendar reminders are provided. A host can receive a calendar reminder notifying the host that a calendar for a property listing maintained by the host may need to be updated. The system can provide the host with a reminder to update the calendar for the property listing based on criteria related to the expected number of times the host will view the calendar within a designated time period and the timing of the host's last interaction with the calendar. If the designated criteria are satisfied, the system can generate a reminder for the host to update the calendar for the property listing. Before sending the reminder to the host, the system confirms that the host did not recently interact with the calendar and if the host did interact with the calendar, the system cancels the sending of the reminder. | 2019-06-20 |
20190188645 | GENERATION OF AUTOMATED JOB INTERVIEW QUESTIONNAIRES ADAPTED TO CANDIDATE EXPERIENCE - According to embodiments of the present invention, a system is provided that will evaluate a candidate's experience (e.g., curriculum vitae (CV), resume, application, etc.) in view of job description requirements, and based on this combined information, will automatically generate a customized interview including questions tailored to each candidate related to his or her experience as described on the application and in view of the job description requirements. | 2019-06-20 |
20190188646 | CANDIDATE SELECTION USING A GAMING FRAMEWORK - One embodiment provides a method, including: receiving a requisition for a job position, the requisition having a plurality of recruiters, each having influence in selecting a candidate; generating a profile for an ideal candidate comprising (i) a plurality of attributes and (ii) weights corresponding to each of the attributes; receiving, for a plurality of candidates, profiles for each the candidates; comparing the profile of each of the plurality of candidates against the ideal candidate, using a distance method computation to determine the distance between the plurality of candidates and the ideal candidate based upon the weights; ranking the plurality of candidates and providing the ranking to each of the plurality of recruiters; receiving input from each of the plurality of recruiters that modifies the ranking, recalculating the weights of the attributes based upon the modified ranking, and modifying the ranking; and providing a final ranking of the plurality of candidates. | 2019-06-20 |
20190188647 | MULTIPLE ELEMENT JOB CLASSIFICATION - Multiple element job classification data objects include values for multiple elements related to a job. The multiple element job classification data object may be generated automatically from a job listing or search query. A database of multiple element job classification data objects may be created using scraping. Scraping job listing data from multiple job listing sites allows for the creation of a centralized database that includes all job listings from the multiple sites. Converting the job listings from a typical title-and-description format into multiple element job classification data objects permits more accurate searching of the data. The database of multiple element job classification data objects may be searched for relevant job listings by a user who provides a text string. The text string is converted into a multiple element job classification data object and used to find job listings that correspond to the user's search. | 2019-06-20 |
20190188648 | RECRUITMENT AND NETWORKING MOBILE APPLICATION - A matchmaking and geolocation mobile software application is designed for recruiting and professional networking. The software application allows users to have jobs and resumes attached to their public profiles, which are displayed on a map for others to see, pursue and engage. The software application can include three primary screens for user information, a map view, a user view and a list view. Users can see who is around them and the application can prioritize showing other users who have something in common. People will be able to know information about who is around them at a coffee shop, conference, or networking event prior to engaging with them in real time. Users will be able to broadcast jobs they represent to those around them and will be able to represent that job anywhere they go within the map view. | 2019-06-20 |
20190188649 | FILL-IN NOTIFICATIONS - Disclosed are various embodiments for providing fill-in notifications to end users. A cancellation event is identified for an appointment corresponding to a timeslot. Then, an eligible user for a new appointment corresponding to the timeslot is identified. A notification is then sent to the eligible user. The notification can include a request for the eligible user to schedule the new appointment for the timeslot. | 2019-06-20 |