32nd week of 2022 patent applcation highlights part 52 |
Patent application number | Title | Published |
20220253703 | DATA COMPRESSION APPARATUS, DATA COMPRESSION METHOD, AND LEARNING APPARATUS - According to one embodiment, a data compression apparatus includes processing circuitry. The processing circuitry generates reconstructed data by performing reconstruction processing on data. The processing circuitry generates decompressed reconstructed data by performing the reconstruction processing on decompressed data obtained by decompressing compressed data that is generated by performing compression processing on the data. The processing circuitry determines a parameter relating to a compression ratio of the data based on comparison between the reconstructed data and the decompressed reconstructed data. | 2022-08-11 |
20220253704 | OPTIMIZATION USING LEARNED NEURAL NETWORK OPTIMIZERS - Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing optimization using an optimizer neural network. One of the methods includes for each optimizer network parameter, randomly sampling a perturbation value; generating a plurality of sets of candidate values for the optimizer network parameters, for each set of candidate values of the optimizer network parameters: determining a respective loss value representing a performance of the optimizer neural network in updating one or more sets of inner parameters in accordance with the set of candidate of values of the optimizer network parameters; and updating the current values of the optimizer network parameters based on the loss values for the plurality of sets of candidate values of the optimizer network parameters. | 2022-08-11 |
20220253705 | METHOD, DEVICE AND COMPUTER READABLE STORAGE MEDIUM FOR DATA PROCESSING - Embodiments of the present disclosure relate to methods, devices and computer readable storage media for data processing. The method comprises obtaining input data. The method further comprises generating, by using a neural network, a predicted label indicating a class of the input data. The neural network comprises a weighted layer that determines at least a weight applied to at least one candidate class to generate a predicted result. The input data is possibly belonging to the at least one candidate class. In this way, the predicted label may be generated more accurately. | 2022-08-11 |
20220253706 | DISTANCE TO OBSTACLE DETECTION IN AUTONOMOUS MACHINE APPLICATIONS - In various examples, a deep neural network (DNN) is trained to accurately predict, in deployment, distances to objects and obstacles using image data alone. The DNN may be trained with ground truth data that is generated and encoded using sensor data from any number of depth predicting sensors, such as, without limitation, RADAR sensors, LIDAR sensors, and/or SONAR sensors. Camera adaptation algorithms may be used in various embodiments to adapt the DNN for use with image data generated by cameras with varying parameters—such as varying fields of view. In some examples, a post-processing safety bounds operation may be executed on the predictions of the DNN to ensure that the predictions fall within a safety-permissible range. | 2022-08-11 |
20220253707 | Devices and Methods Using Machine Learning for Surveillance and Granting of Privileges - A method and system where a first subsystem makes observations and performs surveillance using sensors in a mode that conserves a resource such as power, data transmission band width or processing cycles. This is accomplished by reducing illumination, pixel count, sampling rate or other functions that result in a limited granularity or data collection rate. A machine model is applied to the limited data and, when it evaluates to a suitable result or a prediction of an interesting condition, another subsystem or the same subsystem in a different mode collects data at a finer granularity with a higher data collection size or rate and evaluates that data to determine the nature of the first evaluation. The machine model may be trained in stages on a large scale server and on a small field processor. Data from the sensor may be used for training to improve the second step. | 2022-08-11 |
20220253708 | DEEP NEURAL NETWORK COMPRESSION BASED ON FILTER IMPORTANCE - Techniques are provided for compressing deep neural networks using a structured filter pruning method that is extensible and effective. According to an embodiment, a computer-implemented method comprises determining, by a system operatively coupled to a processor, importance scores for filters of layers of a neural network model previously trained until convergence for an inferencing task on a training dataset. The method further comprises removing, by the system, a subset of the filters from one or more layers of the layers based on the importance scores associated with the subset failing to satisfy a threshold importance score value. The method further comprises converting, by the system, the neural network model into a compressed neural network model with the subset of the filters removed. | 2022-08-11 |
20220253709 | Compressing a Set of Coefficients for Subsequent Use in a Neural Network - A method of compressing a set of coefficients for subsequent use in a neural network, the method comprising: applying sparsity to a plurality of groups of the coefficients, each group comprising a predefined plurality of coefficients; and compressing the groups of coefficients according to a compression scheme aligned with the groups of coefficients so as to represent each group of coefficients by an integer number of one or more compressed values. | 2022-08-11 |
20220253710 | Human-Machine Multi-Turn Conversation Method and System for Human-Machine Interaction, and Intelligent Apparatus - The present disclosure relates to a human-machine multi-turn conversation method and system for human-machine interaction, and an intelligent apparatus. The method includes: S | 2022-08-11 |
20220253711 | PARSIMONIOUS INFERENCE ON CONVOLUTIONAL NEURAL NETWORKS - The disclosed system incorporates a new learning module, the Learning Kernel Activation Module (LKAM), at least serving the purpose of enforcing the utilization of less convolutional kernels by learning kernel activation rules and by actually controlling the engagement of various computing elements: The exemplary module activates/deactivates a sub-set of filtering kernels, groups of kernels, or groups of full connected neurons, during the inference phase, on-the-fly for every input image depending on the input image content and the learned activation rules. | 2022-08-11 |
20220253712 | NEURAL COMMAND LINE INTERFACE EXAMPLE GENERATION - An example generator tool generates an example illustrating correct usage of a command of a command line interface. A command may include a command name, zero or more subcommands, and one or more parameters with a corresponding parameter value. A template containing the correct syntax of the command is obtained from a template database. Parameter values for the template are generated from a neural transformer with attention given the command template. | 2022-08-11 |
20220253713 | TRAINING NEURAL NETWORKS USING LAYER-WISE LOSSES - Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a neural network using local layer-wise losses. | 2022-08-11 |
20220253714 | GENERATING UNSUPERVISED ADVERSARIAL EXAMPLES FOR MACHINE LEARNING - A trained machine learning model and a training dataset used to train the trained machine learning model can be received. Based on the training dataset, unsupervised adversarial examples can be generated. Robustness of the trained machine learning model can be determined using the generated unsupervised adversarial examples. The training dataset can be augmented with the generated unsupervised adversarial examples. The trained machine learning model can be retrained using the augmented training dataset. | 2022-08-11 |
20220253715 | NARRATIVE-BASED CONTENT DISCOVERY EMPLOYING ARTIFICAL INTELLIGENCE - Processor-based systems and/or methods of operation may generate queries and suggest legacy narrative content (e.g., video content, script content) for a narrative under development. An artificial neural network (ANN, e.g., autoencoder) is trained on pairs of video and text vectors to capture attributes or nuances beyond those typical of keyword searching. Query vector representations generated using an instance of the ANN may be matched against candidate vector representations, for instance generated using an instance of the ANN from legacy narratives. Such may query for missing video and/or text for a narrative under development. Matches may be returned, including scores or ranks. Feature vectors may be shared without jeopardizing source narrative content. Legacy source narrative content may remain secure behind a controlling entity's network security wall. | 2022-08-11 |
20220253716 | NEURAL NETWORK COMPRISING MATRIX MULTIPLICATION - A method and data processing system implement a neural network containing at least one matrix multiplication operation. The matrix multiplication operation is mapped to a graph of neural network operations including at least one transformation and at least one convolution. The at least one convolution is implemented in fixed-function hardware of a neural network accelerator. | 2022-08-11 |
20220253717 | SYSTEM AND METHOD FOR BRINGING INANIMATE CHARACTERS TO LIFE - A method and system for bringing inanimate characters to life as an interactive chatbot. The method transforms a static character to a dynamic chatbot through bringing to life to the character, letting the character evolve, learn, and grow, and thereby be able to engage with, and by extension, cull from human users via a text user interface. | 2022-08-11 |
20220253718 | AUTOMATICALLY VALIDATING DECISION TABLES - Decision tables can be automatically validated on a computer according to some examples. In one example, a system can determine a first set of values associated with a first column of a decision table and a second set of values associated with a second column of the decision table. The system can then determine that each respective value in the first set of values has a one-to-one relationship with a corresponding value in the second set of values. Based on determining that each respective value in the first set of values has the one-to-one relationship, the system determines that the first column and second column violate a third normal form (3NF) constraint. The system may then automatically rearrange the first and second columns into separate decision tables that comply with the 3NF constraint. | 2022-08-11 |
20220253719 | SCHEMA AUGMENTATION SYSTEM FOR EXPLORATORY RESEARCH - In examples, a schema augmentation system for exploratory research leverages intelligence from a machine learning model to augment such tasks by leveraging intelligence derived from machine learning capabilities. Augmenting tasks include schematization of content, such as information units and groupings of information units. Based on the schematization of such content, semantic proximities for information units are determined. The semantic proximities may be used to identify and present potentially relevant information units, for example to accelerate the exploratory research task at hand. As such, users engaged in consumption of heterogeneous content (e.g., across client applications and/or content sources), may receive machine-augmented support to find potential information units. To optimize machine training, user input may be received, such that the system may intelligently augment the user's exploratory research task based on the semantic coherence of the content processed from information units and associated user behavior. | 2022-08-11 |
20220253720 | BESPOKE DETECTION MODEL - The present invention relates to a method of classifying behaviour patterns. The method comprises configuring a simulation environment based on an operational arena, configuring an artificial agent to carry out a chosen activity within the simulation environment, generating training data from the agent's activity, and training a detection model using the training data. | 2022-08-11 |
20220253721 | GENERATING RECOMMENDATIONS USING ADVERSARIAL COUNTERFACTUAL LEARNING AND EVALUATION - A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, perform certain acts. The acts can include obtaining training data. The acts also can include training candidate recommendation models and an adversarial exposure model using the training data. The acts additionally can include generating recommendations based on a selected recommendation model of the candidate recommendation models. Other embodiments are described. | 2022-08-11 |
20220253722 | RECOMMENDATION SYSTEM WITH ADAPTIVE THRESHOLDS FOR NEIGHBORHOOD SELECTION - A recommendation system (RS) for processing an input dataset that identifies a set of users, a set of items, and user-item interaction data about historic interactions between users in the set of users and items in the set of items. The RS is configured to: generate, based on a user-item interaction dataset, a user-user similarity dataset and an item-item similarity dataset, filter the user-user similarity dataset based on a user similarity threshold vector that includes a respective user similarity threshold value for each user, filter the item-item similarity dataset based on an item similarity threshold vector including a respective item similarity threshold value for each item generate a set of user neighbour embeddings based on the filtered user-user similarity dataset, and generating a set of item neighbour embeddings based on the filtered item-item similarity dataset. The RS is also configured to generate a set of relevance scores based on the user neighbour embeddings and the item neighbour embeddings and generating a list of one or more recommended items for each user. | 2022-08-11 |
20220253723 | AMPLIFYING SOURCE CODE SIGNALS FOR MACHINE LEARNING - Embodiments are disclosed for a method. The method includes identifying one or more source code signals in a source code. The method also include generating an amplified code based on the identified signals and the source code. The amplified code is functionally equivalent to the source code. Further, the amplified code includes one or more amplified signals. The method additionally includes providing the amplified code for a machine learning model that is trained to perform a source code relevant task. | 2022-08-11 |
20220253724 | VARIANCE OF GRADIENT BASED ACTIVE LEARNING FRAMEWORK FOR TRAINING PERCEPTION ALGORITHMS - Neural networks and learning algorithms can use a variance of gradients to provide a heuristic understanding of the model. The variance of gradients can be used in active learning techniques to train a neural network. Techniques include receiving a dataset with a vector. The dataset can be annotated and a loss calculated. The loss value can be used to update the neural network through backpropagation. An updated dataset can be used to calculate additional losses. The loss values can be added to a pool of gradients. A variance of gradients can be calculated from the pool of gradient vectors. The variance of gradients can be used to update a neural network. | 2022-08-11 |
20220253725 | MACHINE LEARNING MODEL FOR ENTITY RESOLUTION - In some implementations, a system may define common attributes of a first dataset and a second dataset. The system may generate a candidate set of mappings between one or more entities in the first dataset and one or more entities in the second dataset based on candidate generation criteria associated with a related pair of common attributes. The system may generate feature sets for the candidate set of mappings based on the common attributes and a featurization configuration. The system may train a machine learning model for performing entity resolution between the first dataset and the second dataset. The system may perform entity resolution between the first dataset and the second dataset based on the feature sets for the candidate set of mappings using the trained machine learning model. | 2022-08-11 |
20220253726 | HYDROCARBON OIL FRACTION PREDICTION WHILE DRILLING - A method includes building a mud-gas hydrocarbon oil fraction database comprising historical data, training a machine learning model using the historical data in the mud-gas hydrocarbon oil fraction database, drilling a new wellbore, processing drilling mud returns, from the new wellbore, through a gas sampler comprising a gas chromatograph and a gas mass spectrometer, retrieving real-time mud-gas data from the gas sampler, and generating a real-time hydrocarbon oil fraction log for the new wellbore by processing the real-time mud-gas data through the trained machine learning model and producing estimated hydrocarbon oil fraction data. | 2022-08-11 |
20220253727 | OPERATIONAL FORECASTING SYSTEM BASED ON ANOMALOUS BEHAVIORS IN COMPLEX SYSTEMS - A general-purpose approach to solving the core problems of detecting and predicting the actions of invisible actors, and the consequential challenges of intervention and prevention. The operational forecasting system is applied to data gathered from complex systems. The operational forecasting system uses novel early-warning signals that are based on anomalous behaviors of actors/agents that are observed, as they respond to those unobserved actors that are the source of systemic change. The operational forecasting system targets predicting when an event will occur, before it does, based on the anomalous behaviors of observed actors responding to those invisible actors that are creating the perturbation (i.e. the murmuration). | 2022-08-11 |
20220253728 | Method and System for Determining and Reclassifying Valuable Words - Method and system for determining and reclassifying valuable words, wherein a large amount of text and valuable words are pre-inputted into a word processing server for machine learning. Moreover, the word processing server is trained on the valuable words and many labels associated with the valuable words such that it can learn and determines the valuable words in the text that meet the definition of the valuable word. The valuable word is further extracted from the text and re-classified after extraction. In addition, each valuable word is provided with various relevance labels to facilitate the subsequent application of the valuable words. | 2022-08-11 |
20220253729 | SCALABLE KNOWLEDGE DATABASE GENERATION AND TRANSACTIONS PROCESSING - Systems and methods are described for a scalable approach to build a knowledge database of clinical trial data by extracting, aligning, and synthesizing information from a variety of sources including clinical trial registries, abstracts of papers, and full-text medical journal articles, as well as external gazetteers, dictionaries, and lexicons. For examples, a system may implement a flexible and repeatable workflow that extracts both structured and semi-structured elements from unstructured data such as journal articles using a ‘back off strategy’ in which specialized rules are used to extract structured, clinical trial design parameters as well as information retrieval techniques that exploit regularities in language used in the medical literature to discover semi-structured trial outcomes. This workflow also aligned structured elements with data from structured data sources and augmented the base structured information with additional searchable trial features or characteristics and sentiment or polarity scores derived from the unstructured data. | 2022-08-11 |
20220253730 | CASE-BASED REASONING AS A CLOUD SERVICE - The disclosure generally describes methods, software, and systems for providing solution descriptions. A problem description of a problem is received, from a client, at a cloud-based reasoning service. A solution description for a solution to the problem is received. Case metadata for a case defining the problem and solution are generated by the cloud-based reasoning service. The case metadata, including the problem description and solution description, are stored by the cloud-based reasoning service in a cases repository associating solutions with problems. A new problem is received at the cloud-based reasoning service. An automated analysis of the new problem is performed, and a comparison is made of the new problem with existing solutions in the cases repository to identify solutions matching the new problem. A new solution description is provided that is based on a match between the new problem description and the problem description and using the problem solution. | 2022-08-11 |
20220253731 | DYNAMIC BLOCKCHAIN-BASED PROCESS ENABLEMENT SYSTEM (PES) - A dynamic Innovation Enablement System (IES) that utilizes a novel n-dimensional vector-based data management system, in combination with a novel user interface and novel expert system, to speed up the efficiency of computer processing and real-time user application of data for selecting user interventions that optimize outcomes within the IES. The IES is a computer-implemented system for facilitating users to develop, practice and apply competency in innovation-conducive behaviors and techniques. The system has a user system and coupled to the user system, a server system, a data store and an innovation enablement system (IES). IES has a first module that includes information to guide users through a first set of tasks directed to developing competencies in innovation. IES also has a second module that includes information to guide users through a second set of predetermined tasks, including at least two tasks that together form an innovation process that directs a user towards producing an innovation. IES also has a third module that integrates the first module and the second module, wherein information about the users, generated utilizing one of the two modules, can inform and facilitate what the users input as information when utilizing the other of the two modules. In a further aspect, the IES employs vector matrix algebra to arrive at an ideal vector correlated to an innovation outcome, which can use blockchain as a fundamental, integral enhancement of the software architecture for a Dynamic Blockchain-Enhanced Process Enablement System (PES). This PES utilizes the same n-dimensional compound vector architecture that has already been previously shown herein to improve computer performance without blockchain software. | 2022-08-11 |
20220253732 | SELECTING A WINDOW TREATMENT FABRIC - A fabric selection tool provides an automated procedure for recommending and/or selecting a fabric for a window treatment to be installed in a building. The recommendation may be made to optimize the performance of the window treatment in which the fabric may be installed. The recommended fabric may be selected based on performance metrics associated with each fabric in an environment. The fabrics may be ranked based upon the performance metrics of one or more of the fabrics. One or more of the fabrics, and/or their corresponding ranks, may be displayed to a user for selection. The recommended fabrics may be determined based on combinations of fabrics that provide performance metrics for various façades of the building. Using the ranking system provided by the fabric selection tool, the user may obtain a fabric sample and/or order one or more of the recommended fabrics. | 2022-08-11 |
20220253733 | ABNORMALITY DETECTION BASED ON CAUSAL GRAPHS REPRESENTING CAUSAL RELATIONSHIPS OF ABNORMALITIES - An example method for abnormality detection based on causal graphs representing causal relationships of abnormalities includes detecting an abnormality in a test data set and generating a counterfactual data set for the test data set. The method further includes determining a quantitative feature dependence between the test data set and the counterfactual data set and determining a causal relationship of the abnormality based on the quantitative feature dependence. The method also includes generating a causal graph that represents the causal relationship of the abnormality. The method may also implement an action to mitigate the abnormality based on the causal graph. | 2022-08-11 |
20220253734 | MACHINE LEARNING METHODS TO OPTIMIZE CONCRETE APPLICATIONS AND FORMULATIONS - A method comprising: pulling a set of customer data and augment it with data sets designed to optimized machine learning operations; Selecting specified machine learning techniques from a specified machine learning database; taking into account a set of worksite context parameters; and optimizing and adjusting a concrete mix in real time to be able to deliver concrete products that meet requirements of project. | 2022-08-11 |
20220253735 | METHOD FOR SIMULATION ASSISTED DATA GENERATION AND DEEP LEARNING INTELLIGENCE CREATION IN NON-DESTRUCTIVE EVALUATION SYSTEMS - Method and system for detecting one or more anomalies in an object are provided. The system receives experimental data of the object and applies a probability density function (PDF) upon one or more variables associated with the experimental data to determine corresponding one or more PDF estimates. The system further generates simulated data associated with the object based on at least one of the one or more PDF estimates and priori data associated with the testing of the object. The simulated data comprises one or more new anomalies unknown in the experimental data along with the one or more anomalies of the experimental data. Furthermore, the system trains a learning model based on the one or more new anomalies and the one or more anomalies of the experimental data. The learning model is applied for detecting any anomaly in an object. | 2022-08-11 |
20220253736 | AGGREGATED DATA RESOLUTION ENHANCEMENT DEVICE, AGGREGATED DATA RESOLUTION ENHANCEMENT METHOD, AND AGGREGATED DATA RESOLUTION ENHANCEMENT PROGRAM - A parameter estimation section | 2022-08-11 |
20220253737 | HARDWARE-EFFICIENT CALIBRATION FRAMEWORK FOR QUANTUM COMPUTING DEVICES - Techniques facilitating hardware-efficient calibration protocols for quantum computing devices. In one example, a system can comprise a process that executes computer executable components stored in memory. The computer executable components can comprise an echo pattern component and a pulse component. The echo pattern component can generate an echo sequence based on a Pauli term. The echo sequence can amplify the Pauli term. The pulse component can generate a pulse sequence to calibrate a multi-qubit gate using the echo sequence. | 2022-08-11 |
20220253738 | INFORMATION PROCESSING DEVICE AND INFORMATION PROCESSING METHOD - According to one embodiment, an information processing device includes a qubit pair structure body including a plurality of qubit pairs. The qubit pairs are arranged in m rows and n columns. The qubit pairs include first, and second qubit pairs, and first to sixth adjacent qubit pairs. The qubit pair structure body includes first to eighth spin chains. The first and fifth spin chains include a first eigenenergy, and not include the second, third, and fourth eigenenergies. The second and sixth spin chains include a second eigenenergy, and not include the first, third, and fourth eigenenergies. The third and seventh spin chains include a third eigenenergy, and not include the first, second, and fourth eigenenergies. The fourth spin chain and the eighth spin chain include a fourth eigenenergy, not include the first, second, and third eigenenergies. The first to fourth eigenenergies are different from each other. | 2022-08-11 |
20220253739 | QUANTUM COMPUTER ARCHITECTURE BASED ON MULTI-QUBIT GATES - The disclosure describes various aspects of a practical implementation of multi-qubit gate architecture. A method is described that includes enabling ions in the ion trap having three energy levels, enabling a low-heating rate motional mode (e.g., zig-zag mode) at a ground state of motion with the ions in the ion trap; and performing a Cirac and Zoller (CZ) protocol using the low-heating rate motional mode as a motional state of the CZ protocol and one of the energy levels as an auxiliary state of the CZ protocol, where performing the CZ protocol includes implementing the multi-qubit gate. The method also includes performing one or more algorithms using the multi-qubit gate, including Grover's algorithm, Shor's factoring algorithm, quantum approximation optimization algorithm (QAOA), error correction algorithms, and quantum and Hamiltonian simulations. A corresponding system that supports the implementation of a multi-qubit gate architecture is also described. | 2022-08-11 |
20220253740 | SYSTEMS AND METHODS FOR SIMULATING A QUANTUM PROCESSOR - A digital processor simulates a quantum computing system by implementing a QPU model including a set of representation models and a device connectivity representation to simulate a quantum processor design or a physical quantum processor. The digital processor receives an analog waveform and generates a digital waveform representation comprising a set of waveform values that correspond to biases applied to programmable devices in a quantum processor. The digital processor selects a subset of waveform values based on channels in the device connectivity representation. The digital processor implements a representation model to compute a response based on the waveform values and a plurality of physical parameter values, the physical parameters characterizing a programmable device in a quantum processor. The device connectivity representation can be generated from a design implementation, validated against a set of rules, and adjusted to change the device connectivity representation until all of the rules are passed. | 2022-08-11 |
20220253741 | QUANTUM PROCESSING OF PROBABILISTIC NUMERIC CONVOLUTIONAL NEURAL NETWORKS - Certain aspects of the present disclosure provide techniques for performing probabilistic convolution operation with a quantum and non-quantum processing systems. | 2022-08-11 |
20220253742 | QUANTUM ERROR CORRECTION DECODING SYSTEM AND METHOD, FAULT-TOLERANT QUANTUM ERROR CORRECTION SYSTEM, AND CHIP - A quantum error correction (QEC) decoding system includes an error correction chip. The error correction chip is configured to: obtain error syndrome information of a quantum circuit; and decode the error syndrome information by running neural network decoders, to obtain error result information, a core operation of the neural network decoders being a multiply accumulate (MA) operation of unsigned fixed-point numbers obtained through numerical quantization. According to the present disclosure, for the system that uses the neural network decoders for QEC decoding, the core operation of the neural network decoders is the MA operation of unsigned fixed-point numbers obtained through numerical quantization, thereby minimizing the data volume and the calculation amount desirable by the neural network decoders, so as to better meet the requirement of real-time error correction. | 2022-08-11 |
20220253743 | REINFORCEMENT LEARNING WITH QUANTUM ORACLE - A computing device is provided, including a processor configured to transmit, to a quantum coprocessor, instructions to encode a Markov decision process (MDP) model as a quantum oracle. The processor may be further configured to train a reinforcement learning model at least in part by transmitting a plurality of superposition queries to the quantum oracle encoded at the quantum coprocessor. Training the reinforcement learning model may further include receiving, from the quantum coprocessor, one or more measurement results in response to the plurality of superposition queries. Training the reinforcement learning model may further include updating a policy function of the reinforcement learning model based at least in part on the one or more measurement results. | 2022-08-11 |
20220253744 | SYSTEM FOR IMPLEMENTING DYNAMIC DATA OBFUSCATION USING PATTERN RECOGNITION TECHNIQUES - Systems, computer program products, and methods are described herein for implementing dynamic data obfuscation using pattern recognition techniques. The present invention is configured to electronically receive one or more data artifacts; electronically receive one or more masked data artifacts; initiate one or more machine learning algorithms on the one or more data artifacts and the one or more masked data artifacts; determine, using the one or more machine learning algorithms, a first set of patterns associated with the one or more data artifacts and a second set of patterns associated with the one or more masked data artifacts; determine a similarity index between the first set of patterns and the second set of patterns; and compare the similarity index with a predetermined threshold; determine one or more alternate data obfuscation algorithms; and implement the one or more alternate data obfuscation algorithms on the one or more data artifacts. | 2022-08-11 |
20220253745 | METHODS AND SYSTEMS FOR MULTIPLE TIME-SERIES DATA FORECASTING - This disclosure relates generally to methods and systems for multiple time-series data forecasting using recurrent neural networks (RNNs). Conventional techniques in the art for the time-series prediction are limited to deal with one long data sequence and a single forecasting model may not be sufficient and efficient to cover the multiple short data sequences. The present disclosure makes use of greedy recursive procedure to build a set of multi-step forecasting models that covers the multiple data sequences, using the recurrent neural network (RNN) models. The one or more multi-step residual error forecasting models makes the forecasting resulting from the set of multi-step forecasting models, accurate and efficient. The set of multi-step forecasting models are useful for various forecasting applications such as prediction of the sales for retail industries, prediction of power consumption for households, the prediction of traffic occupancy across roads, and so on. | 2022-08-11 |
20220253746 | Systems and Methods for Managing, Distributing and Deploying a Recursive Decisioning System Based on Continuously Updating Machine Learning Models - The present disclosure relates generally to the generation and deployment of a machine learning-enabled decision engine (MLDE). The MLDE includes decision options that are composed of a discrete list of selectable options. Further, the MLDE includes data inputs that can be used to influence decisions made by the machine learning models of the MLDE. Controls are applied to the MLDE to overlay and bound the decisioning within guidelines established by an operator of the MLDE. Once the MLDE is established, the MLDE is validated and deployed for use by software applications to make decisions. | 2022-08-11 |
20220253747 | Likelihood Ratios for Out-of-Distribution Detection - The present disclosure is directed to systems and method to perform improved detection of out-of-distribution (OOD) inputs. In particular, current deep generative model-based approaches for OOD detection are significantly negatively affected by and struggle to distinguish population level background statistics from semantic content relevant to the in-distribution examples. In fact, such approaches have even been experimentally observed to assign higher likelihood to OOD inputs, which is opposite to the desired behavior. To resolve this problem, the present disclosure proposes a likelihood ratio method for deep generative models which effectively corrects for these confounding background statistics. | 2022-08-11 |
20220253748 | Techniques for Training Systems for Autonomous Vehicle Navigation - Techniques are disclosed for the implementation of machine learning model training utilities to generate models for advanced driving assistance system (ADAS), driving assistance, and/or automated vehicle (AV) systems. The techniques described herein may be implemented in conjunction with the utilization of open source and cloud-based machine learning training utilities to generate machine learning trained models. One example of such an open source solution includes TensorFlow, which is a free and open-source software library for dataflow and differentiable programming across a range of tasks. TensorFlow may be used in conjunction with many different types of machine learning utilities, such as Amazon's cloud-based SageMaker utility for instance, which is a fully-managed service that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. | 2022-08-11 |
20220253749 | METHODS OF PREDICTING RELIABILITY INFORMATION OF STORAGE DEVICES AND METHODS OF OPERATING STORAGE DEVICES - In a method of operating a storage device including a plurality of nonvolatile memories, reliability information of the storage device is predicted. A read operation on the storage device is performed based on a result of predicting the reliability information. In the predicting the reliability information of the storage device, a model request signal is outputted by selecting one of a plurality of machine learning models as an optimal machine learning model based on deterioration characteristic information and deterioration phase information. The model request signal corresponds to the optimal machine learning model. The plurality of machine learning models are used to generate first reliability information related to the plurality of nonvolatile memories. First parameters of the optimal machine learning model may be received based on the model request signal. The first reliability information is generated based on the deterioration characteristic information and the first parameters. | 2022-08-11 |
20220253750 | COMPUTER-READABLE RECORDING MEDIUM STORING MODEL GENERATION PROGRAM, METHOD OF GENERATING MODEL, AND MODEL GENERATION APPARATUS - A non-transitory computer-readable recording medium stores a model generation program for causing a computer to execute a process including: obtaining a plurality of pieces of data; inputting the plurality of pieces of data to a first model and obtaining a plurality of prediction results; determining importance of each of the plurality of pieces of data based on the plurality of prediction results; and generating a second model based on the determined importance and the plurality of pieces of data. | 2022-08-11 |
20220253751 | HUMAN IDENTIFICATION METHOD BASED ON EXPERT FEEDBACK MECHANISM - The disclosure provides an identification method based on an expert feedback mechanism, in which the expert properly give a feedback to results of a static model, the model is dynamically adjusted and updated according to the feedback of the expert each time, so that identifications for similar objects can be changed from a wrong identification to a correct identification. The model can adapt to dynamic changes of the environment, so that an identification accuracy and robustness of the model under the dynamic environment are improved with an expertise. The accuracy of the identification model is improved without repeated training, which solves a problem that the accuracy of the static model decreases in the dynamic environment, raising an adaptability of the identification model to environmental changes, shortening updating time of the model and improving working efficiency of the identification application system. | 2022-08-11 |
20220253752 | LEARNING OPERATING METHOD BASED ON FEDERATED DISTILLATION, LEARNING OPERATING SERVER, AND LEARNING OPERATING TERMINAL - According to the present disclosure, disclosed are a learning operating method based on a federated distillation, a learning operating server, and a learning operating terminal which calculate a local average logit by collecting data samples by the terminal, transmit the local average logit and seed samples to an uplink of a server, perform distillation of a global model based on the seed sample and the local average logit by the server to solve the problems of the privacy and communication overhead generated in the distributed network. | 2022-08-11 |
20220253753 | METHOD FOR VEHICLE TO COMMUNICATE WITH NETWORK IN WIRELESS COMMUNICATION SYSTEM, AND VEHICLE THEREFOR - Disclosed is a method for a vehicle to communicate with a network in a wireless communication system. The method may comprise: receiving a message related to a parking lot from the network; transmitting, to the network, a message for requesting a reservation for a specific parking space from among at least one parking space in the parking lot; and receiving a message including the spatial coordinates of the specific parking space. In particular, the message for reservation includes type information of the vehicle, and the spatial coordinates of the specific parking space may be dynamically determined on the basis of the type information of the vehicle and type information of the at least one parking space. | 2022-08-11 |
20220253754 | ONLINE PARKING LOT RESERVATION METHOD AND DEVICE, AND COMPUTER-READABLE STORAGE MEDIUM - A method performed by a system for providing a parking lot reservation service according to an embodiment of the present disclosure includes a process of receiving point of departure information and destination information from a user device, a process of identifying, based on the received destination information, real-time parking space information of each of at least one parking lot located within a reference distance from a location of the destination information, a process of determining at least one candidate parking lot from among the at least one parking lot, a process of transmitting the point of departure information and the destination information to a traffic information system and receiving an estimated time of arrival which has been calculated by the traffic information system based on the point of departure information and the destination information, a process of calculating, based on big data stored in a database, an estimated available parking space of each of the at least one candidate parking lot at the estimated time of arrival, and a process of transmitting, to the user device, information about the at least one candidate parking lot and the estimated available parking space of each candidate parking lot. Various other embodiments are also possible. | 2022-08-11 |
20220253755 | SYSTEM AND METHOD FOR EXCHANGING TICKETS VIA A MACHINE-READABLE CODE - A system for exchanging tickets comprising: a server system comprising a computer processor, a server, and a database; a user device comprising a unique ID; and a tag comprising a tag ID; and wherein upon scanning the tag by the user device, the system performs the following method: scanning, via a user device, a tag comprising a tag ID, said tag comprising a tag ID identifying a seat; verifying a unique ID on said user device by confirming a matching unique ID within a database or generating a unique ID if one is not present; verifying ownership of a first ticket on said user device, said first ticket comprising a unique identifying ticket code and matching the seat defined by said tag ID; directing the user device to a ticket exchange portal; selecting a second ticket for exchange; confirming the exchange; and exchanging the first and second tickets. | 2022-08-11 |
20220253756 | AGRICULTURAL OR INDUSTRIAL SUPPLY CHAIN DISTRIBUTED NETWORK USING MULTI-INPUT DECISION ALGORITHM - There is described a method and distributed network for managing a supply chain. At least one local production system is fed with an algorithm for producing a good or service (such as agricultural produce) over a production duration. An edge computing device, receives and treats data originating from the at least one local production system. A server periodically receives, from remote data sources, data relative to a market for the good or service, after a time period which is less than the production duration, and receives data treated by the edge computing device to perform comparisons with the data relative to the market to make a diagnostic. The diagnostic is transmitted to a machine learning module for updating the algorithm for production after the time period which is less than the production duration and feeding the algorithm as updated to the at least one local production system. | 2022-08-11 |
20220253757 | METAHEURISTICS OPTIMIZER FOR CONTROLLED ENVIRONMENT AGRICULTURE - A system for achieving optimized crop growth. A growth chamber is provided, as is environmental monitoring means for acquiring and monitoring data regarding environmental conditions within the growth chamber. Resource control means controls resources applied to the growth chamber. A metaheuristics based optimizer system is coupled to the environmental monitoring means for analyzing and evaluating crop growth conditions within the growth chamber, structuring data associated with the crop growth conditions, learning from the structured data using a routine to learn from the output of different machine learning strategies, and generating metaheuristic recommendations to optimize crop growing inputs. Optimized crop growth means to achieve crop growth with minimum consumption of energy and nutrients while improving yield and quality. The metaheuristics based optimizer system recommends and controls resources in response to the crop growth information to achieve optimized plant growth, maximum yield, and minimized power consumption. | 2022-08-11 |
20220253758 | METHOD AND SYSTEM FOR INSPECTING RAILWAY TRACKS - The invention provides a graphical user interface implemented on a computer including an information area for displaying to a user at the computer inspection status information in connection with one or more components of a linear asset infrastructure. The graphical user interface also includes a control component operable by the user at the computer to cause the graphical user interface to display additional information on the one or more components of the linear asset infrastructure. | 2022-08-11 |
20220253759 | SYSTEMS AND METHODS FOR ALTERING DISPLAY OF VIRTUAL CONTENT BASED ON MOBILITY STATUS CHANGE - Systems, methods, and non-transitory computer readable media for coordinating virtual content display with mobility status are disclosed. A non-transitory computer readable medium contains instructions that cause a processor to: access rules associating user mobility statuses with display modes; receive first sensor data reflecting a mobility status of a user during a first time period; based on the first sensor data, determine that during the first time period the user is associated with a first mobility status; implement a first accessed rule to generate a first display of virtual content; receive second sensor data reflecting the mobility status of the user during a second time period; based on the second sensor data, determine that during the second time period the user is associated with a second mobility status; and implement a second accessed rule to generate a second display of the virtual content different from the first display. | 2022-08-11 |
20220253760 | INTEGRATED MODEL FOR CONTROLLING A TECHNICAL SYSTEM - A method for controlling a technical system, wherein at least one milestone step and a plurality of intermediate steps are scheduled at respective points in time is provided. Time deviations for the intermediate steps are obtained, wherein a time deviation denotes a difference from an initial planning of a step. For the milestone step, a time deviation is determined using the time deviations of the intermediate steps. A cost function is obtained for the milestone step, wherein the cost function defines a cost value for the technical system dependent on the time deviation of the milestone step using a domain-specific language, e.g., based on a contractual requirement for the technical system. A cost value is determined for the technical system using the time deviation of the milestone step and the cost function. The technical system is controlled based on the cost value. | 2022-08-11 |
20220253761 | SYSTEMS AND METHODS OF ITERATIVE WELL PLANNING FOR OPTIMIZED RESULTS - Systems and methods of surface steering control of drilling may be used together with systems and methods for planning one or more wells before drilling, planning a well path during drilling and/or updating that well plan and/or other well plans during the drilling of a well. The methods and systems may include planning a field, comprising a plurality of wells to be drilled and/or a plurality of pads from which a plurality of wells are to be drilled, planning a pad from which a plurality of wells are to be drilled, and planning a well both before and during drilling of the well. | 2022-08-11 |
20220253762 | ISSUE TRACKING SYSTEMS AND METHODS - Described herein is a computer-implemented method. The method comprises receiving an operation notification in respect of a gated operation from a change requesting system, determining an issue type associated with the gated operation, and creating an issue of the determined issue type. The method further comprises determining that the issue has transitioned state from a pending workflow state to a particular operation resolution workflow state and, in response, generating an operation resolution message which is communicated to the change requesting system. | 2022-08-11 |
20220253763 | SYSTEM AND METHOD FOR VESSEL RISK ASSESSMENT - Provided are systems and methods for vessel risk assessment. This includes determining a risk assessment associated with a vessel, including receiving vessel data from at least one source, generating at least one vessel profile based on the vessel data, wherein each vessel profile provides indication of expected behavior events for one vessel and abnormal behavior events for one vessel, determining at least one abnormal behavior event of the vessel based on the at least one vessel profile, each event in the at least one abnormal behavior event having a time of occurrence, determining at least one frequency of occurrence of abnormal behavior events of the vessel based on the time of occurrence of each event, using at least one model to determine a risk assessment associated with the vessel based on the at least one frequency of occurrence of abnormal behavior events of the vessel. | 2022-08-11 |
20220253764 | SYSTEMS AND METHODS FOR DISTRIBUTED RISK ANALYSIS - Systems and methods for distributed risk analysis are discussed. | 2022-08-11 |
20220253765 | Regularized Spatiotemporal Dispatching Value Estimation - A system for evaluating order dispatching policy includes a first computing device, at least one processor, and a memory. The first computing device is configured to generate historical driver data associated with a driver. The at least one processor is configured to store instructions. When executed by the at least one processor, the instructions cause the at least one processor to perform operations. The operations performed by the at least one processor includes obtaining the generated historical driver data associated with the driver. Based at least in part on the obtained historical driver data, a value function is estimated. The value function is associated with a plurality of order dispatching policies. An optimal order dispatching policy is then determined. The optimal order dispatching policy is associated with an estimated maximum value of the value function. The estimation of the value function applies a feed-forward neutral network | 2022-08-11 |
20220253766 | CHANGE MANAGEMENT LOGIC - A system and method for managing and scheduling changes across an organization. A change management computer system can receive a request to implement a proposed change for a facility of the organization, determine a change score for the proposed change that quantifies a magnitude of impact for the proposed change on the facility, access, from a database, data records identifying other changes currently scheduled to be performed by the facility over a plurality of time periods, determine scheduled change scores for the facility for the plurality of time periods based on other changes scores for other scheduled changes, identify time periods from the plurality of time periods as suitable for scheduling the proposed change based on the scheduled change scores and change score for the proposed change, and output identification of the time periods as suitable for scheduling the proposed change for the facility. | 2022-08-11 |
20220253767 | COMPUTERIZED SYSTEM AND METHOD FOR DYNAMIC TASK MANAGEMENT AND EXECUTION - Disclosed are systems and methods for improving interactions with and between computers in content providing, streaming and/or hosting systems supported by or configured with devices, servers and/or platforms. The disclosed systems and methods provide a novel framework that automatically and dynamically determines and prioritizes, and updates tasks at a scale incapable of being performed without machine learning or modern technology. The framework provides systems and methods for the management of a work flow whereby tasks, subtasks and the behavior and interactions of entities performing those operations are monitored to determine which tasks are in progress, which are completed, which are safe and which are to be rescheduled. | 2022-08-11 |
20220253768 | METHOD FOR IMPROVING THE OPERATIONAL AVAILABILITY OF AN AIRCRAFT FLEET - A method including identifying a plurality of maintenance schedules for a plurality of aircraft of a fleet of aircrafts each of which satisfy a minimum maintenance free operating period, monitoring and measuring a health of each of the aircrafts, utilizing the measured heath of the aircrafts within a degradation model in order to produce a plurality possible maintenance events for each of the aircrafts, each of the possible maintenance events associated with a different maintenance time, identifying at least one maintenance event for each aircraft in the fleet of aircraft using the set of possible maintenance events found for each aircraft from the plurality of maintenance schedules resulting in number of aircraft down for maintenance below a predetermined threshold, and executing the at least one maintenance event based on the at least one identified maintenance event. | 2022-08-11 |
20220253769 | CONSTRAINED OPTIMIZATION AND POST-PROCESSING HEURISTICS FOR OPTIMAL PRODUCTION SCHEDULING FOR PROCESS MANUFACTURING - A method includes obtaining information identifying (i) multiple processing units in a facility, (ii) multiple interconnections between the processing units, and (iii) constraints associated with the processing units and the interconnections. The method also includes identifying an optimization problem associated with production of multiple products by the processing units in the facility, where the optimization problem is associated with a cost function. The method further includes removing one or more terms from the optimization problem to generate a relaxed optimization problem. In addition, the method includes generating one or more solutions to the relaxed optimization problem, where each solution represents a proposed production schedule. | 2022-08-11 |
20220253770 | SYSTEM AND METHOD FOR CALIBRATING A WFM SCHEDULING MODULE - System and method for calibration of WFM system modeling parameters. A first mode M[D,S] of a modeler computes demand-shrinkage controlled service levels and an error metric e(M[D,S]) between the controlled and actual service levels. A user device iteratively adjusts each core parameter. When the user is satisfied that e(M[D,S]) is sufficiently small, calibration of the core parameters is complete. The same is done for calibrating the modeling factor, and then a final e(M[D,S]) | 2022-08-11 |
20220253771 | SYSTEM AND METHOD OF PROCESSING DATA FROM MULTIPLE SOURCES TO PROJECT FUTURE RESOURCE ALLOCATION - Processing system for evaluating a customer opportunity based on multiple metrics, including automated tracking of communications activities with a customer, to determine when the customer opportunity has reached a defined milestone. | 2022-08-11 |
20220253772 | METHOD AND SYSTEM FOR PROVIDING PLATFORM TO MANAGE PRODUCED VISUAL CONTENTS - A method for providing a platform to manage produced visual contents includes (a) providing a main interface for a project by a server to a first terminal when the first terminal requests to generate the project for managing visual contents; (b) transmitting a project invitation message by the server to a second terminal when the first terminal inputs a project member request including identification information of the second terminal, and providing the main interface to the second terminal; (c) providing an upload area by the server, uploading visual contents in relation to the project by the first or the second terminal to the upload area, and providing a review interface displaying the visual contents by the server; and (d) displaying a text or a drawing image for evaluation or review overlapped with the visual contents by an input of the first or the second terminal through the review interface. | 2022-08-11 |
20220253773 | INFORMATION MANAGEMENT SYSTEM, SERVER, AND USER TERMINAL - A server is connected with a plurality of user terminals via a communication network. The server provides a user terminal with user screens capable of displaying both of a form (category) defining a data structure and an entity (schedule) being a data set created on the basis of a form. The server registers association of a second form with a first form when the second form is associated with the first form on a user screen by a user, and creates an entity when a form is specified and an entity based on the specified form is created on a user screen by a user. When displaying a first entity created on the basis of the first form on a user screen, the server displays, as a related entity of the first entity, a second entity created on the basis of the second form. | 2022-08-11 |
20220253774 | IMPLEMENTING BIG DATA AND ARTIFICIAL INTELLIGENCE TO DETERMINE LIKELIHOOD OF POST-ACCEPTANCE FACILITY OR SERVICE RENUNCIATION - Big data searches, statistical computation and artificial intelligence are leveraged to determine the likelihood that a user will renounce a facility or service post-acceptance. Specifically, the present invention relies on facility/service data and/or user data to key a plurality of data mining searches of big data sources. In response to extracted responsive data from the big data sources, the present invention implements statistical computing along with machine learning/Artificial Intelligence techniques to determine a go/no-go indicator that indicates either (i) the user is unlikely to renounce (i.e., abandon, fail to use and/or return) the facility or service post-acceptance/acquisition, or (ii) the user is likely to renounce the facility/service. | 2022-08-11 |
20220253775 | Automated Lead Generation - A evaluation server | 2022-08-11 |
20220253776 | AUTOMATICALLY DISCOVERING DATA TRENDS USING ANONYMIZED DATA - A computer-implemented method of executing a programmed spend management computer system. The computer system comprises a data pre-processor that is communicatively coupled to a plurality of the application instances and accesses historic transaction data from any of the instances and thereby has access to a large community of data across all tenants. The data pre-processor is programmed to normalize transaction descriptions and determine line spend values, unit price values, quantity values, and buyer country data for a plurality of commodities, and to store the data in item sets in digital storage. A statistical processor is coupled to the digital storage to access the item sets and executes statistical calculation on the item sets to generate pricing insight data. Pricing insights and/or prescriptions are generated automatically under stored program control and provided to a presentation processor for output to and/or rendering to an end-user device. | 2022-08-11 |
20220253777 | Dynamically Influencing Interactions Based On Learned Data And On An Adaptive Quantitative Indicator - Techniques are disclosed for generating and dynamically updating an experience score for a client, where the experience score operates as a quantitative indicator describing a relationship between the client and an entity. The experience score is used to modify subsequent interactions the client has with the entity. Sentiment data detailing the relationship between the client and the entity is acquired. The sentiment data is received from different types of interactions the client had relative to the entity. NLP is used to provide structure to the sentiment data, resulting in an initial set of scoring data being made available. That scoring data is normalized. After normalizing the scoring data, weighting factors are applied to the scoring data to generate weighted scores. The experience score is then generated by aggregating the weighted scores. The experience score is used to then modify a subsequent interaction the client has with the entity. | 2022-08-11 |
20220253778 | System and Method of a Supply Chain Retail Process Manager - A system and method are disclosed for analyzing the maturity of one or more supply chain entities according to competencies of an omni-channel retailer. The one or more supply chain entities including a retail manager that assesses the one or more supply chain entities according to one or more competencies and determines one or more maturity gaps associated with the one or more competencies. The retail manger further identifies one or more transition projects that fill the one or more maturity gaps and roadmaps one or more transition activities that generate the one or more identified transition projects. The one or more supply chain entities further adjusts an inventory of one or more products at least partially based on the one or more roadmapped transition activities. | 2022-08-11 |
20220253779 | CONSTRUCTION PROJECT MANAGEMENT APPLICATION - A management system for tracking a progress of a construction project comprises a server, a database, and one or more devices. The database comprises information on a predicted schedule for completion of the tasks on each floor. Each device comprises a graphical user interface to perform the following: accept a first input regarding a current status of one or more of the tasks; display a timeline depicting a range of future dates, wherein the future dates are selectable; and transmit the future dates selected to the server. The server determines a predicted progress for each task in order for the construction project to remain on the predicted schedule. The server further determines an indication as to whether the current status of the tasks is ahead or behind the predicted schedule and causes the graphical user interface to display the indication. | 2022-08-11 |
20220253780 | ANALYTICAL TOOL FOR COLLABORATIVE COMPETITIVE PURSUIT ANALYSIS AND CREATION OFENTERPRISE VALUE - A collaborative analytical pursuit system includes a data repository and server with memory and processor. The system includes opportunity assessment, capture, and proposal planning modules. The processor collects and assesses data on issues and decision factors associated with a bid and competitiveness, identifies discriminators; identifies partners, a leadership team, staffing solution, facilities, tools, certifications, and techniques; develops bid technical and management approaches and a pricing strategy; calculates and stores a value associated with the data; and produces a report including a temporal graph of the value. The data repository stores a data lake of competitive intelligence, intellectual capital, and proprietary data. The system runs a method identifying a customer's vision, mission, and evaluation factors; collecting data on individuals and enterprises; assessing their relationship status; identifying competitiveness gaps; developing a win strategy; automatically generating proposal strategy lists and strengths lists; preparing value statements from a structured template; and producing the report. | 2022-08-11 |
20220253781 | METHOD, DEVICE AND COMPUTER READABLE STORAGE MEDIUM FOR DATA PROCESSING - Embodiments of the present disclosure relate to a method, apparatus and computer readable storage medium for data processing. The method may include obtaining a causal result determined based on reference data of a plurality of reference factors. The plurality of reference factors may include a reference satisfaction degree and other reference factors, and the causal result may include a causal relationship between the reference satisfaction degree and the other reference factors and a causal relationship between the other reference factors. The method may further include obtaining sample data of a plurality of user factors associated with a user, the plurality of user factors at least partially overlapping the other reference factors. The method may further include determining a first satisfaction degree of the user based on the sampled data and the causal result. The technical solution of the present disclosure can predict the user's satisfaction degree timely and accurately and automatically make an optimization policy and improve the user's experience. | 2022-08-11 |
20220253782 | System and Method for Automatic Parameter Tuning of Campaign Planning with Hierarchical Linear Programming Objectives - A system and method are disclosed for campaign planning and include modeling the use of campaign operations and campaignable resources of a supply chain network including a production line to produce products using campaign operations and campaignable resources as campaign planning problems, defining an evaluation function comprising a weighted sum of features evaluated from the campaign planning problem, initializing weights to build a consumption profile and evaluation function, determining fitness values that indicate a level of variability, evaluating reward values based on the fitness values, selecting a sub-sample of the top fitness values having the best associated objective function, repeating the generating, the evaluating and the selecting steps to adjust the weights until a stopping criterion is met indicating an optimal solution has been reached, and determining a campaign plan for the use of the campaign operations and campaignable resource. | 2022-08-11 |
20220253783 | SYSTEMS AND METHODS FOR ENTERPRISE METADATA MANAGEMENT - Various methods, apparatuses/systems, and media for managing metadata are disclosed. A processor extracts technical metadata corresponding to enterprise applications from a plurality of databases; builds a metadata repository in a graph database; builds a web-based metadata application based on developing a normalized representation for data flows corresponding to the extracted technical metadata by utilizing the graph database. The extracted technical metadata is stored onto the metadata repository in the graph database. The processor authenticates and authorizes a user to utilize the web-based metadata application; receives search criteria from the user; accesses the metadata repository in the graph database to retrieve the technical metadata and/or data lineage within the enterprise applications from the metadata repository based on received search criteria; and displays the technical metadata and/or the data lineage within the enterprise applications onto a user interface. | 2022-08-11 |
20220253784 | INTERACTIVE AND PREDICTIVE TOOL FOR MONITORING PERFORMANCE METRICS - The present disclosure provides a method, system, and computer-readable medium for using a predictive analytics engine to dynamically modify an interactive tool. To illustrate, a method includes compiling candidate data. The method includes initializing a predictive analytics engine based on at least a portion of the compiled candidate data and a conceptual performance model representative of an expected performance over a period of time. The method includes processing, by the predictive analytics engine, a plurality of performance metrics to produce one or more predictive performance metrics. The method further includes dynamically modifying an interactive tool based on the conceptual performance model and the plurality of performance metrics. | 2022-08-11 |
20220253785 | MOBILE MEASUREMENT-ASSESSMENT SYSTEM - A mobile measurement assessment system including an application, assignment, placement and result announcement system (BAYS) containing fundamental systems to provide organization of information needed for receiving details of learners to take a test, processing thereof and administering the test, a question preparation system (SHS) providing assignment of subjects and questions to learners, a test application system (SUS) providing administration of prepared tests via mobile devices. The system contains at least one main computer system-containing mobile devices and applications required for performance of test process and providing encrypted wireless communication, at least one mobile tablets and carrying system-providing communication with the main computer system and containing procedures required for learners' login into the test, and a mobile test application containing security systems. | 2022-08-11 |
20220253786 | SYSTEM AND METHOD FOR PROVIDING ATTRIBUTIVE FACTORS, PREDICTIONS, AND PRESCRIPTIVE MEASURES FOR EMPLOYEE PERFORMANCE - A system and method for attributing the performance of an organization employee or team to events in the employees' career record and predicting future performance. The system acquires historical career record data comprising data of an employee or team of employees, including key performance indexes (KPIs) of the employee/team; finds at least one signpost—an individual data point or group of data points in the career record data having a comparatively high correlation with one of the KPIs of the employee/team or with increases/decreases of the KPI; monitors the career record for new occurrences of the signposts; predicts the KPI or whether the KPI will increase/decrease as a function of the occurrence of the signpost, and transmits the predicted KPI or increase/decrease thereof and its attribution to the occurrence of the signpost to a data consumer. In some embodiments, the system provides prescriptive measures for improving future performance. | 2022-08-11 |
20220253787 | ASSESSING PROJECT QUALITY USING CONFIDENCE ANALYSIS OF PROJECT COMMUNICATIONS - An embodiment trains a machine-learning model using a first training corpus of general items indicative of varying levels of confidence. The embodiment also prepares a second training corpus that includes domain-specific items indicative of varying levels of confidence extracted from communications from members of a project group associated with a project. The embodiment retrains the machine-learning model using the second training corpus and generates a confidence score for the project based on confidence values assigned by the machine-learning model to each of a plurality of project-related communication items from members of the project group. The embodiment also detects that the confidence score is below a predetermined threshold confidence level and, in response, initiates a communication to members of the project group conveying information regarding an automated remedial action for the project. | 2022-08-11 |
20220253788 | CROSS-TENANT DATA PROCESSING FOR AGENT DATA COMPARISON IN CLOUD COMPUTING ENVIRONMENTS - A system is provided for a cloud computing environment that is adapted to perform data processing and tracking of agent data between cloud computing tenants. The system includes a processor and a computer readable medium operably coupled thereto, to perform operations which include determining a unique identifier (ID) for an agent of the cloud computing tenants, accumulating, over a time period, agent data for the agent, refining the agent data to curated data views for the agent data based on a plurality of aggregate reports for each of a plurality of KPIs in the agent data, determining a batch processing job for the refined agent data, calculating, using the batch processing job, a base asset value (BAV) score for the agent, and updating a profile for the agent associated with the unique ID based on the calculated BAV score. | 2022-08-11 |
20220253789 | AGENT COACHING SYSTEM - Method starts with processing, by a processor, audio signal to generate audio caller utterance. Processor generates an agent action ranking score associated with the audio caller utterance and determines whether the agent action ranking score is below a minimum threshold. In response to determining that the agent action ranking score is below the minimum threshold, processor generates a transcribed caller utterance using a speech-to-text processor and generates an identified task based on the transcribed caller utterance. Using the transcribed caller utterance and a task-specific agent coaching neural network associated with the identified task, processor generates an ideal response. Processor generates a feedback result and causes the feedback result to be displayed on a display device of the agent client device. Other embodiments are disclosed herein. | 2022-08-11 |
20220253790 | AUTOMATED RECOMMENDATIONS FOR TASK AUTOMATION - In one embodiment, a method for providing recommendations for workflow alteration is disclosed. Task results for completion of a first set of iterations of a workflow are received. Training data may be extracted from the task results. The training data may be used to build a machine learning model for altering at least a portion of the workflow. An automation forecast that assesses the effects of altering the workflow for a second set of the iterations of the task may be generated, and a workflow alteration recommendation may be provided. Based on automation parameters, such as a minimum required level of accuracy, and the automation forecast, a recommendation regarding whether to automate the task may be included in the workflow alteration recommendation. Finally, based on the recommendation, an automated process may be generated to handle at least a portion of the task. | 2022-08-11 |
20220253791 | SYSTEM AND METHOD FOR PRIVATIZED PARCEL DELIVERY - A system and method for secure parcel delivery and/or privatizing personal identifiable information that includes: recording an association between user information and a user information code, the user information including at least shipping address information; at an online marketplace, establishing an association of a user information code with a delivery order, the user information code used in place of a delivery address and/or personal identifiable information; and servicing an information request that includes the user information code, the servicing the information request comprising generating a packing label of a product using the shipping address information accessed with the user information code. | 2022-08-11 |
20220253792 | SYSTEMS AND METHODS FOR RUSH ORDER FULFILLMENT OPTIMIZATION - A system for rush order fulfilment optimization is discussed. The system includes mobile devices that are each associated with a worker and a rush fulfillment engine executed by a computing system which dynamically updates a task queue of each worker upon receipt of a new rush order according to a task completion rate difference between an estimated task completion rate and the current task completion rate of the worker. | 2022-08-11 |
20220253793 | INVENTORY MANAGEMENT SYSTEM - Various embodiments of systems and methods allow a tool inventory device and associated system. A user can retrieve and return tools and such interactions can be monitored by the system. The inventory device can be an add-on to a standalone tool cabinet and can provide this extra functionality. The inventory device can have a camera looking at the drawers and can use computer vision to determine when tools are retrieved and/or replaced. | 2022-08-11 |
20220253794 | APPARATUS AND METHOD FOR SENSING FULLNESS OF STORAGE BIN - An apparatus, storage bin and method for determining fullness of the bin. The bin ( | 2022-08-11 |
20220253795 | METHOD FOR VERIFYING THE FIELD DEVICE INVENTORY ENTERED IN AN ASSET MANAGEMENT SYSTEM - A method for verifying field device inventory includes connecting a processing unit to a network; reading the address space of the network using the processing unit to generate a list of field devices contained in the address space; establishing communication between the processing unit and a field device contained in the list; reading out identification information of the field device using the processing unit, the identification and a characteristic parameter of the field device; carrying out a consistency check, a negative result being achieved if a field device is already entered under the serial number that has been read out; checking, if a negative result, whether a characteristic parameter of the field device corresponds with the characteristic parameter that has been read out; and outputting a notification using the processing unit that a characteristic parameter assigned to the field device deviates from the parameter that has been read out. | 2022-08-11 |
20220253796 | SYSTEM AND METHODS FOR MODULAR INVENTORY MANAGEMENT - A modular inventory management system ( | 2022-08-11 |
20220253797 | Methods, Systems, and Non-transitory Storage Media for Monitoring Progression of Medicinal Plants - Information identifying a specific patient and disposal information associated with a specific medicinal plant is obtained, and the information identifying the specific patient is encrypted. Progression of the specific medicinal plant through multiple stages including planting, growth, application of an additive, harvesting, finishing, assembling into at least one product, packaging, and delivery is monitored in association with the specific patient. Disposal of at least a portion of the raw form of the specific medicinal plant and at least a portion of the product resulting from assembling the specific medicinal plant is tracked in association with the specific patient. Inventory of the specific medicinal plant is updated based on the disposal. The encrypted information identifying the specific patient is transmitted with the updated inventory information to a central server via a wireless network for maintenance in accordance with government regulations. | 2022-08-11 |
20220253798 | DOCKING STATION ACCESSORY DEVICE FOR CONNECTING ELECTRONIC MODULE DEVICES TO A PACKAGE - An accessory device as a positioning device configured for use in connection with a package in-process of being delivered, or being prepared for, staged for or in-transit of delivery are herein described. The accessory device comprises a docking station including a receptacle used to receive, carry or apply one or more small electronic communication device module(s) to monitor package location(s) or condition(s) by securing electronic module(s) within the accessory device as a docking station to then be added and associated by computer-implemented systems with a package for wireless location and condition monitoring. The accessory device may include one or more retaining compartment features designed to hold or carry short-range radio module(s), serving as positioning device with monitoring module(s), coupled into the retaining feature receptacle(s). | 2022-08-11 |
20220253799 | SYSTEM AND METHOD FOR PROCESSING SHIPMENT REQUESTS USING A MULTI-SERVICE SHIPPING PLATFORM - Systems and methods for processing shipment request by using a multi-carrier shipping services platform. | 2022-08-11 |
20220253800 | USING CUSTOM HYPERLINKS TO IMPLEMENT PRODUCT RETURNS IN A PRODUCT BASED MLM SYSTEM - The present disclosure is directed to methods for returning funds that were paid as commissions to users of a multi-level marketing (MLM) organization that were part of a product tree of related users. These funds may be recovered after a previously purchased product has been returned. This tree of related users may have been created by a first user purchasing a product and then promoting the sale of that product to a second user that purchased the product and that promoted sale of the product to a third user who also purchased the product. Commissions may have been paid to users within the product tree when users that they sponsored or users that their sponsors sponsored purchased the product. In an instance when a user returns a product, commissions paid based on the sale of that returned product will be returned using methods and apparatus consistent with the present disclosure. | 2022-08-11 |
20220253801 | PIECE VERSUS MULTI-PIECE CARRIER OPTIMIZATION - Examples provide a system and method for optimizing single piece versus multi-piece shipment for source-carrier combinations. A manager component calculates an estimated shipping cost for all possible combinations of source-carrier associated with delivery of items from the source to a destination. The system iteratively calculates a cost for shipping the item with every combination of carriers and sources as a single piece only packaging, as well as a multi-piece packaging where applicable based on rate cards for the carriers. The combination of source-carrier and boxing method providing the lowest estimated shipping cost in a plurality of calculated shipping costs is selected for order fulfillment. The selected carrier is assigned to deliver the ordered items from the source location to the destination location. A notification can be sent to the user identifying the selected carrier and estimated date of delivery of the items. | 2022-08-11 |
20220253802 | SYSTEM AND METHODS FOR ENABLING EFFICIENT SHIPPING AND DELIVERY - A method for recipient-initiated shipping includes receiving, at an internet connected server, recipient data (including a first shipping address) from a shipping recipient; providing delivery options to the shipping recipient based on a set of delivery option criteria and the recipient data; receiving a delivery choice from the shipping recipient; and notifying at least one of a shipping sender and a shipping carrier of the delivery choice. | 2022-08-11 |