25th week of 2022 patent applcation highlights part 63 |
Patent application number | Title | Published |
20220198282 | DECISION TREE OF MODELS: USING DECISION TREE MODEL, AND REPLACING THE LEAVES OF THE TREE WITH OTHER MACHINE LEARNING MODELS - Described are techniques of generating and training a neural network that include training multiple models and constructing multiple decision trees with said models. Each decision tree may include additional decision trees at various levels of that decision tree. Each decision tree has a different accuracy indicator due to the unique structuring of each decision tree, and by testing each tree through a testing dataset, the tree with the highest accuracy can be determined. | 2022-06-23 |
20220198283 | DYNAMIC RECONSTRUCTION OF DECISION TREE STRUCTURES - Techniques are disclosed relating to dynamic construction of decision tree structures. In various embodiments, a server system may receive, from a client device, a request to perform a particular operation via an application hosted by the server system. In some such embodiments, the request (e.g., an API request) may specify data values for one or more parameters. Based on a first parameter specified in the request, the server system may dynamically generate a first decision tree structure for an authorization policy used to determine whether to authorize the particular operation. In some embodiments, the first decision tree structure may include a first plurality of interconnected nodes organized into a first hierarchy having multiple levels, where a highest of the levels includes a first subset of nodes that correspond to the first parameter. Based on this first decision tree structure, the server system may then determine whether to authorize the request. | 2022-06-23 |
20220198284 | SEARCH DEVICE, OPERATION METHOD OF SEARCH DEVICE, OPERATION PROGRAM OF SEARCH DEVICE, AND FLOW REACTION EQUIPMENT - A prediction-data-set-generation-unit generates a prediction-data-set composed of a plurality of prediction-data where an explanatory-variable for an unknown-value of a response-variable and a prediction-value of the response-variable are associated with each other by using a known-data-set. A first-actual-measurement-value-acquisition-unit acquires an actual-measurement-value of the response-variable included in the prediction-data where the prediction-value is closest to a target-value. An improvement-rate-calculation-unit calculates an improvement-rate representing a difference between a known-value of the response-variable closest to the target-value and the actual-measurement-value. A known-data-set-update-unit adds the actual-measurement-value and a value of the explanatory-variable corresponding to the actual-measurement-value to the known-data-set in a case where the improvement-rate is equal to or higher than a target improvement-rate. A second-actual-measurement-value-acquisition-unit acquires an actual-measurement-value of the response-variable for a value of the explanatory-variable included in the prediction-data, which is not used for acquiring the actual-measurement-value by the first-actual-measurement-value-acquisition-unit, in a case where the improvement-rate is lower than the target improvement-rate. | 2022-06-23 |
20220198285 | KNOWLEDGE MANAGEMENT SYSTEM - A knowledge management system includes a knowledge entry management configured to manage at least one knowledge entry in recording or managing knowledge, a knowledge entry attribute description management configured to record and manage an attribute description about the at least one knowledge entry. A term used in the attribute description is another knowledge entry or an attribute description of the other knowledge entry and a reference link to the other knowledge entry or the attribute description of the other knowledge entry is available, and a reference term-using document creation configured to create a document in which the knowledge entry is used as a term and that holds a reference link to the knowledge entry. | 2022-06-23 |
20220198286 | SYSTEM AND METHOD FOR MOLECULAR RECONSTRUCTION FROM MOLECULAR PROBABILITY DISTRIBUTIONS - A system and method comprising a transmoler that identifies common substructures of a given 3D conformer and predicts its structural information. First, based on contrastive learning, substructure embeddings are learned in an unsupervised manner. Secondly, a novel oriented 3D object regressor predicts the dimensions and directions of each substructure in a conformer as well as its fingerprint embedding which are used to create differentiable junction tree molecular graphs. Lastly, using the junction tree graphs, molecular representations such as DeepSMILES are generated which represent new and novel molecules. The system may also generate conformers directly from a pocket. A pocket may be input to the model and the model learns to generate structures which can fit that pocket by conditioning the generative system. Furthermore, structure-based contrastive embeddings generated for transmoler can be recycled in structure-based generative modelling. | 2022-06-23 |
20220198287 | CLASSIFICATION MODEL FOR CONTROLLING A MANUFACTURING PROCESS - Controlling a manufacturing process by a computer-generated classification model is provided. This is combined with a reward system based on a distributed ledger and smart contracts. The classification model is trained by: Providing data entities being indicative of a property of a manufacturing of a product. Acquiring labels for each of the data entities from an agent. Determining labeling metrics based on the acquiring of the agent. Training the classification model, wherein the training set includes the data entities and their labels. Validating the trained classification model yielding a classifier score. Training a labeling score model based on the data entities, the respective labels, the labeling metrics and the classifier score. Determining a labeling score for the agent based on the labeling score model, the labels and the set of labeling metrics. | 2022-06-23 |
20220198288 | Method And System For Unsupervised Learning Of Document Classifiers - A system and method for classifying unstructured text documents, without the need for pre-classified training examples. In general, the system and method provides for blending statistical, syntactic and semantic considerations to learn classifiers from an organization's unclassified internal and external unstructured text documents, as well as unclassified documents available via the Internet. In one form, for each class in a taxonomy the class name is expanded into semantically related words and phrases to build approximate classifiers. Each approximate classifier will almost certainly be erroneous but it can be used to identify an approximately correct set of documents. The process is recursive; e.g. the approximate classifier with the strongest evidence, is fed back into the system until a stale set of the strongest terms for each classifier has been selected. | 2022-06-23 |
20220198289 | RECOMMENDATION MODEL TRAINING METHOD, SELECTION PROBABILITY PREDICTION METHOD, AND APPARATUS - A recommendation model training method, a selection probability prediction method, and an apparatus are provided. The training method includes obtaining a training sample, where the training sample includes a sample user behavior log, position information of a sample recommended object, and a sample label. The training method further includes performing joint training on a position aware model and a recommendation model by the training sample, to obtain a trained recommendation model, where the position aware model predicts probabilities that a user pays attention to a target recommended object when the target recommended object is at different positions, and the recommendation model predicts, when the user pays attention to the target recommended object, a probability that the user selects the target recommended object. | 2022-06-23 |
20220198290 | Randomization-Based Network of Domain Specific Rule Bases - An artificial intelligence system and a method for its operation include rule bases established to maintain rules for respective knowledge domains. A network links the rule bases together. A first rule in every rule base references a second rule in another rule base via the network, and the network at least interconnects every first and second rule bases for which the first rule in the first rule base references the second rule in the second rule base. The artificial intelligence system is adapted to invoke a third one of the rules of a particular one of the rule bases in response to an input from a user of the artificial intelligence system, and this begins a chain invoking the rules of the rule bases via the network. The chain includes the first rule in one of the rule bases invoking the second rule in another one of the rule bases. | 2022-06-23 |
20220198291 | SYSTEMS AND METHODS FOR EVENT DETECTION - An event detection system includes a remote computing device comprising a processor configured to communicably couple to one or more sensors. The event detection system is configured to access a first model, a second model, and a third model, receive current data from the one or more of the sensors, determine that an event or possible emergency condition is present based on the first model, second model, third model, and current data, and cause a notification to be transmitted in response to determining the presence of the event or possible emergency condition. | 2022-06-23 |
20220198292 | AUTOMATION OF VIRTUAL ASSISTANT TRAINING - A question and answer pair is received from an external knowledge base. From the question, a set of intents is extracted. Whether the set of intents exceeds a match threshold with a subset of a plurality of intents within an internal knowledge base is determined. In response to determining a match threshold success, associating the question with the subset of intents within the plurality. A virtual assistant is trained to answer the question using the subset of intents. | 2022-06-23 |
20220198293 | SYSTEMS AND METHODS FOR EVALUATION OF INTERPERSONAL INTERACTIONS TO PREDICT REAL WORLD PERFORMANCE - Aspects of systems and methods for evaluation of interpersonal interactions to predict real world performance are disclosed. In an example, a system includes an input device, a memory storing instructions, and a processor communicatively coupled with the input device and the memory. The processor is configured to receive ratings data corresponding to a first user from the input device indicating an assessment of the first user during an interpersonal interaction. The processor is configured to evaluate the ratings data corresponding to the first user in comparison to ratings data corresponding to a plurality of rated users. The processor is configured to output a result of the evaluated ratings data indicating a performance of the first user during the interpersonal interaction. | 2022-06-23 |
20220198294 | GENERALIZED PRODUCTION RULES - N-GRAM FEATURE EXTRACTION FROM ABSTRACT SYNTAX TREES (AST) FOR CODE VECTORIZATION - Herein is resource-constrained feature enrichment for analysis of parse trees such as suspicious database queries. In an embodiment, a computer receives a parse tree that contains many tree nodes. Each tree node is associated with a respective production rule that was used to generate the tree node. Extracted from the parse tree are many sequences of production rules having respective sequence lengths that satisfy a length constraint that accepts at least one fixed length that is greater than two. Each extracted sequence of production rules consists of respective production rules of a sequence of tree nodes in a respective directed tree path of the parse tree having a path length that satisfies that same length constraint. Based on the extracted sequences of production rules, a machine learning model generates an inference. In a bag of rules data structure, the extracted sequences of production rules are aggregated by distinct sequence and duplicates are counted. | 2022-06-23 |
20220198295 | COMPUTERIZED SYSTEM AND METHOD FOR IDENTIFYING AND APPLYING CLASS SPECIFIC FEATURES OF A MACHINE LEARNING MODEL IN A COMMUNICATION NETWORK - 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 machine learning framework that trains classifiers to identify specific features of input data. When implementing these trained classifiers in specific runtime environments, the important features of those specific environments can be identified and leveraged for directing the classifier to the vital information that is relevant to the environment. A customized classifier is thereby dynamically created and deployed which improves how data can be classified, thereby reducing false negatives and positives, and increasing confidence and reliance on how such classifiers can be implemented. | 2022-06-23 |
20220198296 | USER CONTEXT MIGRATION BASED ON COMPUTATION GRAPH IN ARTIFICIAL INTELLIGENCE APPLICATION EXECUTING IN EDGE COMPUTING ENVIRONMENT - In an information processing system with at least a first node and a second node separated from the first node, and each of the first node and the second node configured to execute an application in accordance with at least one entity that moves from a proximity of the first node to a proximity of the second node, a method maintains, as part of a context at the first node, a set of status indicators for a set of computations associated with a computation graph representing at least a portion of the execution of the application at the first node. Further, the method causes the transfer of the context from the first node to the second node to enable the second node to continue execution of the application using the transferred context from the first node. | 2022-06-23 |
20220198297 | SELF-MONITORING COGNITIVE BIAS MITIGATOR IN PREDICTIVE SYSTEMS - One or more embodiments described herein facilitate identification and mitigation of cognitive bias in data-driven models. In one embodiment, a deep-learning system can comprise a memory that stores computer executable components; and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise: an input component that receives data comprising primary task labels, secondary-identity attributes and a number of potential categories for one or more of the secondary-identity attributes; a machine-learning model that generates one or more predictions based on the received data; and a multi-objective learning component that trains the machine-learning model to mitigate bias from the one or more predictions. | 2022-06-23 |
20220198298 | CURATED MACHINE LEARNING WORKFLOW SUGGESTIONS AND CLUSTERING TECHNIQUES - Techniques for providing recommended attribute value pairs for clustering a set of users are disclosed. The system may provide an administrator with attributes and attribute values prior to executing the clustering. The administrator may select some combinations of attribute value pairs, which the system may then use for execution of the clustering. Other techniques are disclosed for enabling an administrator to apply administrator-defined constraints to a list of recommended actions generated by a machine learning model. In some cases, the recommended actions may be specific to a particular group of users identified by execution of the administrator-informed clustering process. | 2022-06-23 |
20220198299 | MEDIA ENHANCEMENT VIRTUAL ASSISTANT - Techniques and devices for enhancing media content and presence are discussed herein. An example technique may include aggregating social media data from a plurality of agent profiles and determining a composite score corresponding to each respective agent profile by applying a media enhancement model to the social media data. The example technique may further include cataloging each respective agent profile into an agent profile group of a plurality of agent profile groups based upon the composite score corresponding to the respective agent profile, and determining one or more top media posts by applying the media enhancement model to the plurality of agent profile groups and the social media data. The example technique may further include displaying the one or more top media posts on a virtual social media board for viewing by a respective agent associated with each respective agent profile. | 2022-06-23 |
20220198300 | QUESTION RECOMMENDATION METHOD, DEVICE AND SYSTEM, ELECTRONIC DEVICE, AND READABLE STORAGE MEDIUM - A question recommendation method, a device, a system, an electronic device, and a non-volatile readable storage medium are provided. The question recommendation method includes: obtaining a candidate question set of a user, the candidate question set including a plurality of candidate questions; obtaining user behavior data, and obtaining a user interest parameter based on the user behavior data; based on the user interest parameter and the plurality of candidate questions, obtaining at least one similarity feature between each candidate question of the plurality of candidate questions and the user interest parameter; based on basic user information, the plurality of candidate questions, and the at least one similarity feature, sorting the plurality of candidate questions to obtain a question sequence; and based on an order of the question sequence, recommending at least one candidate question in the question sequence to the user. | 2022-06-23 |
20220198301 | METHOD AND APPARATUS FOR UPDATE PROCESSING OF QUESTION ANSWERING SYSTEM - The present disclosure provides a method and apparatus for update processing of a question answering system, relates to the technical field of artificial intelligence and specifically to big data and natural language processing technologies. A specific implementation solution is: acquiring an updated question-answer set; comparing blocks of the updated question-answer set with blocks of an original question-answer set in terms of question-answer pairs to determine an unchanged block and a changed block; acquiring feature data of questions included in the changed block, and creating an index file corresponding to the block, and adding the feature data to an updated training output set; and retaining the index file and feature data corresponding to the unchanged block, and adding the feature data to the updated training output set. The present disclosure can reduce the time consumed in the updating process and occupation of resources. | 2022-06-23 |
20220198302 | DESTINATION PREDICTION DEVICE, METHOD, AND PROGRAM - A destination of a user is predicted with high accuracy while the user is moving regardless of whether past movement trajectory data of the user does not exist or the past movement trajectory data of the user exists. A destination prediction device according to the present disclosure includes: a first destination prediction unit that predicts a destination candidate of the user who is moving and a value that represents certainty of the destination candidate on the basis of the movement trajectory data that represents a movement trajectory of the user to the present point and movement history data of the user in the past; a second destination prediction unit that predicts a destination candidate of the user and a value that represents the certainty of the destination candidate on the basis of the movement trajectory data of the user and data that represents a movement tendency set in accordance with movement states of people; and an ensemble prediction unit that predicts a destination and a value that represents the certainty of the destination by combining the destination candidates and the values that represent the certainty of the destination candidates predicted by the first destination prediction unit and the second destination prediction unit. | 2022-06-23 |
20220198303 | DEVICE, METHOD AND PROGRAM FOR ENVIRONMENTAL FACTOR ESTIMATION, LEARNED MODEL AND RECORDING MEDIUM - Provided is an environmental factor prediction device that includes a predictor and predicting means. The predictor uses, as explanatory variables: water quality data in a plurality of layers in water, the data including a value corresponding to a biochrome level or a bioluminescence level (e.g. chlorophyll concentration), water temperature, salt concentration, dissolved oxygen, turbidity and flow rate; and meteorological data including atmospheric temperature, precipitation and sunshine duration, and outputs an estimated value of each item of the explanatory variables at a unit time later, based on time series data of the explanatory variables. The predicting means predicts the water quality data up to an N unit time later by repeating prediction using the estimated value acquired by the predictor as input of the predictor again. According to the present invention, the environmental factors that cause generation of red tide, blue tide or water bloom, diseases of fish, and the like, can be predicted, on a long term basis and at high accuracy. | 2022-06-23 |
20220198304 | PROVIDING EXPLAINABLE MACHINE LEARNING MODEL RESULTS USING DISTRIBUTED LEDGERS - Providing reproducible machine learning model results by receiving input data for a machine learning (ML) model, processing the input data using the ML model, yielding an initial result, adding a first block to a distributed ledger, the block comprising the input data, the initial result, an ML model data structure, and a link to training data for the ML model, wherein the training data resides in previous distributed ledger blocks, and providing an output including the initial result. | 2022-06-23 |
20220198305 | METHOD FOR DETECTING ANOMALIES - Disclosed is a computing platform including a memory assembly having encoded thereon executable control-logic instructions configured to be executable by the computing platform, and also configured to urge the computing platform to carry out a method comprising receiving data; and detecting at least one anomaly contained in the data that was received. | 2022-06-23 |
20220198306 | Baum-Welch Accelerator - A processor package comprises at least one Baum-Welch core. The Baum-Welch core comprises a likelihood-value generator, an emission-probability generator, and a transition-probability generator. The likelihood-value generator generates forward values and backward values for a set of observations. The emission-probability generator generates emission probabilities for the set of observations. The transition-probability generator generates transition probabilities for the set of observations. Furthermore, the BW core is to generate, in parallel, at least two types of probability values from the group consisting of forward values, backward values, emission probabilities, and transition probabilities. Other embodiments are described and claimed. | 2022-06-23 |
20220198307 | Baum-Welch Accelerator - A processor package comprises at least one Baum-Welch core. The Baum-Welch core comprises a likelihood-value generator, an emission-probability generator, and a transition-probability generator. The likelihood-value generator generates forward values and backward values for a set of observations. The emission-probability generator generates emission probabilities for the set of observations. The transition-probability generator generates transition probabilities for the set of observations. Furthermore, the BW core comprises a look-up table comprising preconfigured transition*emission values to be used by the LV generator when generating FVs and BVs. Other embodiments are described and claimed. | 2022-06-23 |
20220198308 | CLOSED LOOP ADAPTIVE PARTICLE FORECASTING - Forecasting is built around an adaptive particle approach, which may be classified under the broad umbrella of Monte Carlo methods. Performance can be self-monitoring, and an ensemble can be adaptively modified to maintain performance within prescribed bounds. If underperforming, additional particles can be added until performance is again within the prescribed bounds. If overperforming, particles can optionally be removed until performance is within the prescribed bounds. | 2022-06-23 |
20220198309 | MEASUREMENT AGGREGATION IN QUANTUM PROGRAMS - Systems and techniques that facilitate measurement aggregation in quantum programs are provided. In various embodiments, a system can comprise an input component that can access a quantum program. In various instances, the system can further comprise an aggregation component that can aggregate quantum measurement instructions that are listed in the quantum program. In various embodiments, the aggregation component can aggregate the quantum measurement instructions by: identifying a first quantum measurement instruction in the quantum program; identifying another quantum instruction in the quantum program that is adjacent to the first quantum measurement instruction; and swapping and/or merging the first quantum measurement instruction with the another quantum instruction based on determining whether the first quantum measurement instruction and the another quantum instruction share qubits and based on determining whether the another quantum instruction is a quantum measurement instruction. | 2022-06-23 |
20220198310 | SEMI-ACTIVE MAGNETIC SHIELDING FOR QUBIT UNIT COMPONENTS OF QUANTUM COMPUTING APPARATUSES - A computer-implemented method of reducing an impact of stray magnetic fields on components of a quantum computing chip is disclosed. The computer implemented method includes applying a first current signal to a first component of a quantum computing chip, whereby the first component generates a stray magnetic field impacting an operation of a second component of the quantum computing chip. The computer implemented method further includes applying a compensation current signal to a shielding circuit of the quantum computing chip, the compensation current signal generated according to a predetermined function of the first signal, to magnetically shield the second component from the stray magnetic field generated by the first component. | 2022-06-23 |
20220198311 | SHORT-DEPTH SYNDROME EXTRACTION CIRCUITS IN 2D QUANTUM ARCHITECTURES FOR HYPERGRAPH PRODUCT CODES - A quantum measurement circuit implements a hypergraph product code (HPG). A syndrome can be extracted from the circuit by preparing a readout qubit of the quantum measurement circuit in a known state, preparing a row-based measurement gadget, and preparing a column-based measurement gadget in the quantum measurement circuit. The row-based measurement gadget entangles the readout qubit with a first subset of the target set of data qubits in a same row of the quantum measurement circuit as the readout qubit, and the column based gadget entangles the readout qubit with a second subset of the target set of data qubits in a same column of the quantum measurement circuit as the readout qubit. The syndrome is extracted by measuring the readout qubit to extract the parity of the target set of data qubits. | 2022-06-23 |
20220198312 | SHORT-DEPTH SYNDROME EXTRACTION CIRCUITS FOR CALDERBANK SHOR STEANE (CSS) STABILIZER CODES - A disclosed methodology for syndrome extraction in a quantum measurement circuit includes generating a graph representing a code implemented by the quantum measurement circuit. The graph includes bit nodes corresponding to data qubits in the quantum measurement circuit, check nodes corresponding to syndrome qubits in the quantum measurement circuit, and edges between the bit nodes and check nodes that are each associated with a stabilizer measurement provided by the code. The methodology provides for assigning each of the different edges in the graph to a select one of “G” number of different edge types and performing at least G-number of temporally-separated rounds of qubit operations that each enact concurrent multi-qubit operations on endpoints of a subset of the edges assigned to a same one of the G different edge types. | 2022-06-23 |
20220198313 | CONTROL AND READOUT TOPOLOGY FOR SPIN QUBITS - An integrated system for quantum computation is provided, In one aspect, the system includes at least one semiconductor spin quantum bit (qubit); a feedline configured to act as an electron spin resonance (ESR) antenna for control of the at least one qubit; at least one resonator; and a ground plane common to both the feedline and the at least one resonator. The at least one resonator is capacitively coupled to the feedline, and configured for readout of the at least one qubit via the feedline. The feedline and the at least one resonator are arranged in adjacent layers separated by at least a dielectric. A corresponding method of performing quantum computation using such an integrated system is also provided. | 2022-06-23 |
20220198314 | METHOD FOR READING THE SPIN STATE OF A SYSTEM AND ASSOCIATED METHOD FOR DETERMINING THE FIDELITY - A method of measuring the spin state of two charged particles able to adopt a first, second, third, and fourth spin state S, T+, T0 and T, the two charged particles being contained in a system, including first and second quantum dots characterised by a first parameter Γ relative to the potential barrier separating the two quantum dots and a second parameter ε corresponding to the difference in energy between the fundamental states of the first and second quantum dots, the couple formed by the values of these two parameters defining an operating point of the system as a function of which the system adopts a first charge state noted (1,1) wherein each quantum dot contains a charged particle, a second charge state noted (2,0) wherein the first quantum dot contains two charged particles or a third charge state noted (0,2) wherein the second quantum dot contains two charged particles. | 2022-06-23 |
20220198315 | METHOD FOR DENOISING QUANTUM DEVICE, ELECTRONIC DEVICE, AND COMPUTER-READABLE MEDIUM - The present disclosure provides a method for denoising a quantum device, and relates to the technical fields, such as quantum circuits, quantum algorithms, and quantum calibration. A specific implementation includes: acquiring a noise channel of an actual quantum device; determining a truncation coefficient based on the noise channel; running the actual quantum device to generate an intermediate quantum state; performing a first iteration of applying the noise channel to the intermediate quantum state for the number of times, the number being equal to a value of the truncation coefficient, each applying stage of the first iteration being performed based on a result of a previous applying stage of the first iteration; and computing a zero-noise expected value of an ideal quantum device corresponding to the actual quantum device based on the intermediate quantum state and a resultant quantum state obtained through each applying stage of the first iteration. | 2022-06-23 |
20220198316 | Systems and Methods for Automatic Extraction of Classification Training Data - A method for training a multi-class classification model includes receiving training data corresponding to a plurality of classes. For each class in the plurality of classes, the method includes training a binary classification model configured to determine whether or not an observation of training data belongs to the class and for each observation of training data identified as belonging to the class, extracting one or more class identification features from the observation of training data based on activations of an intermediate attention layer in the binary classification model. A multi-class classification model is trained using the class identification features extracted for each of the plurality of classes. | 2022-06-23 |
20220198317 | CONTEXT-AWARE AND STATELESS DEEP LEARNING AUTOTUNING FRAMEWORK - Systems and methods are provided for improving autotuning procedures using stateless processing with a remote key-value store. For example, the system can implement a task launcher, a scheduler, and an agent to launch, schedule, and execute decomposed autotuning stages, respectively. The scheduling policy implemented by the scheduler may perform operations beyond a simple scheduling policy (e.g., a FIFO-based scheduling policy), which produces a high queuing delay. Compared to the traditional systems, by leveraging autotuning specific domain knowledge, queueing delay is reduced and resource utilization is improved. | 2022-06-23 |
20220198318 | INSTRUCTION STREAMING FOR A MACHINE LEARNING ACCELERATOR - A machine learning network is implemented by executing a computer program of instructions on a machine learning accelerator (MLA) comprising a plurality of interconnected storage elements (SEs) and processing elements (PEs. The instructions are partitioned into blocks, which are retrieved from off-chip memory. The block includes a set of deterministic instructions to be executed by on-chip storage elements and/or processing elements according to a static schedule. The block also includes the number of non-deterministic instructions to be executed prior to executing the set of deterministic instructions in this block. These non-deterministic instructions may be instructions for storage elements to retrieve data from off-chip memory and are contained in one or more prior blocks. The execution of these non-deterministic instructions is counted, for example through the use of tokens. The set of deterministic instructions in the current block is not executed until the count reaches the number provided in the block. | 2022-06-23 |
20220198319 | Machine Learning Feature Stability Alerts - A method for creating machine learning model performance alerts showing the drifting of functions is described herein. The method starts by creating the initial machine learning model using a training data set. This initial machine learning model is then used in production, and the model is updated to account for the production data. To assure the quality of the updated machine learning model, test data results from the initial machine learning model is compared to the results from the updated machine learning model. Each feature is checked to see if the difference is within a p-value and whether the confidence intervals overlap. If not, an alert is generated to take action on the model. | 2022-06-23 |
20220198320 | MINIMIZING PROCESSING MACHINE LEARNING PIPELINING - One or more computer processors determine a plurality of models to incorporate a plurality of determined features from a received dataset. The one or more computer processors generate an aggregated prediction utilizing each model, in parallel, in the determined plurality of models subject to stop criteria, wherein stop criteria includes a prediction duration threshold. The one or more computer processors calculate a confidence value for the aggregated prediction. | 2022-06-23 |
20220198321 | Data Validation Systems and Methods - A computer-implemented method is provided for validating input data from a third-party vendor. The method includes receiving, by a computing device, a plurality of prospectuses from a plurality of third-party entities and generating, by the computing device, a trained machine learning model using the plurality of prospectuses. The method also includes applying, by the computing device, the trained machine learning model on the input data to predict a classification label for the input data and generate a confidence level for the prediction. | 2022-06-23 |
20220198322 | TECHNIQUES FOR AUTO-REMEDIATING SECURITY ISSUES WITH ARTIFICIAL INTELLIGENCE - Techniques for auto-remediating security issues with artificial intelligence. One technique includes obtaining a problem detected within a signal from an emitter associated with a user, inferring a first response, using a global model having a global set of model parameters learned from mappings between problems and responses globally with respect to preferences of all users using a security architecture, inferring a second response, using a local model having a local set of model parameters learned from mappings between problems and responses locally with respect to preferences of the user; evaluating the first response and the second response using criteria, determining a final response for the problem based on the evaluation of the first response and the second response, and selecting a responder from a set of responders based on the final response. The responder is adapted to take one or more actions to respond to the problem. | 2022-06-23 |
20220198323 | SYSTEM FOR PREPARING MACHINE LEARNING TRAINING DATA FOR USE IN EVALUATION OF TERM DEFINITION QUALITY - A system for preparing machine learning training data for use in evaluation of term definition quality. The system can include a server having at least one server processor and at least one server memory for storing a plurality of terms with corresponding definitions, and a plurality of client devices each having at least one client memory device and at least one client processor. The client processor programmed to receive at least one of the plurality of terms and its corresponding definition from the server, display the term and its corresponding definition, and receive an indication of whether the definition satisfies one or more definition quality guidelines. The server memory includes instructions for causing the at least one server processor to receive the indications from the plurality of client devices and label each definition as satisfying each of the definition quality guidelines or not based on the received indications. | 2022-06-23 |
20220198324 | SYMBOLIC MODEL TRAINING WITH ACTIVE LEARNING - Techniques regarding generating and/or training one or more symbolic models are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise a training component that can train a symbolic model via active machine learning. The symbolic model can characterize a formal planning language for a planning domain as a plurality of digital image sequences. | 2022-06-23 |
20220198325 | METHOD, APPARATUS, AND COMPUTER PROGRAM PRODUCT FOR PREDICTING A SPLIT LANE TRAFFIC PATTERN - A method, apparatus and computer program product are provided for predicting a split lane traffic pattern for a road segment. In this regard, first traffic data for an upstream road segment of the road segment is aggregated based on a distribution of speeds associated with location probe points representative of travel of vehicles along the road segment. Furthermore, second traffic data for a first downstream road segment of the road segment is aggregated based on the distribution of speeds associated with the location probe points for the vehicles. Third traffic data for a second downstream road segment of the road segment is also aggregated based on the distribution of speeds associated with the location probe points for the vehicles. Additionally, a machine learning model that predicts a traffic pattern is trained based on the first traffic data, the second traffic data and the third traffic data. | 2022-06-23 |
20220198326 | SPECTRAL DATA PROCESSING FOR CHEMICAL ANALYSIS - A method for operating a spectral data processing system. The method includes receiving a user input associated with processing of a spectral data of a chemical sample at least partly using a machine learning processing model. The machine learning processing model is arranged in a machine learning controller of the spectral data processing system. The method also includes training the machine learning processing model based on the received user input. | 2022-06-23 |
20220198327 | METHOD, APPARATUS, DEVICE AND STORAGE MEDIUM FOR TRAINING DIALOGUE UNDERSTANDING MODEL - The present disclosure provides a method, apparatus, device and storage medium for training a dialogue understanding model, and relates to technical field of computers, and specifically to the technical field of artificial intelligence such as natural language processing and deep learning. The method for training a dialogue understanding model includes: obtaining dialogue understanding training data; performing joint training for a dialogue understanding pre-training task and a general pre-training task by using the dialogue understanding training data, to obtain a dialogue understanding model. According to the present disclosure, a model specially adapted for a dialogue understanding task may be obtained by training. | 2022-06-23 |
20220198328 | INFORMATION PROCESSING METHOD, INFORMATION PROCESSING DEVICE, AND PROGRAM - An information processing method includes: acquiring behavioral history information on an inference target user; acquiring an inferred value of a characteristic relating to the consumption behavior of the inference target user as an output in response to an input of the behavioral history information on the inference target user into a first learned model that has been learned using first learning data about a plurality of learning target users, the first learning data having, as an input, behavioral history information on each learning target user and, as an output, a characteristic relating to the consumption behavior of the learning target user based on answers to a questionnaire given by the learning target user; and based on the inferred value of the characteristic relating to the consumption behavior of the inference target user, outputting an action that is inferred to be effective for the inference target user. | 2022-06-23 |
20220198329 | INFORMATION PROCESSING APPARATUS, INFORMATION PROCESSING METHOD, AND INFORMATION PROCESSING PROGRAM - An information processing apparatus according to the application concerned includes an obtaining unit that obtains a dataset of training data to be used for the training of a model; and a generating unit that uses the dataset and generates a model in such a way that there is a decrease in the variability in the weight. | 2022-06-23 |
20220198330 | METHOD AND SYSTEM FOR GENERATING MOLECULAR STRUCTURE OF CHEMICAL COMPOUND - Generation of a molecular structure of a chemical compound is disclosed. A target agent is trained based on a first reward and a second reward, the first reward being a reward determined by a model likelihood of a target neural network model, the second reward being a reward self-defined based on target requirements, and the target agent being used to determine a molecular compound structure. A target molecular structure of a chemical compound is generated using the target agent. | 2022-06-23 |
20220198331 | MACHINE MODEL UPDATE METHOD AND APPARATUS, MEDIUM, AND DEVICE - Disclosed are a machine model update method and apparatus, a medium, and a device. The method includes: obtaining first hard example samples of a machine model and attribute information of the first hard example samples; determining category-based data distribution information of the first hard example samples according to the attribute information of the first hard example samples; determining second hard example samples of the machine model in current machine learning according to learning requirement information of the machine model for categories of the first hard example samples and the data distribution information; performing, according to learning operation information corresponding to the machine model, a learning operation on the machine model by using the second hard example samples; and updating the machine model based on a learning result of the machine model. The present disclosure helps efficiently implement a machine learning lifecycle, and reduce the cost of machine learning lifecycle. | 2022-06-23 |
20220198332 | SYSTEMS AND METHODS FOR DECENTRALIZED ATTRIBUTION OF GENERATIVE MODELS - A system and associated methods for decentralized attribution of GAN models is disclosed. Given a group of models derived from the same dataset and published by different users, attributability is achieved when a public verification service associated with each model (a linear classifier) returns positive only for outputs of that model. Each model is parameterized by keys distributed by a registry. The keys are computed from first-order sufficient conditions for decentralized attribution. The keys are orthogonal or opposite to each other and belong to a subspace dependent on the data distribution and the architecture of the generative model. | 2022-06-23 |
20220198333 | RECIPE OPTIMIZATION THROUGH MACHINE LEARNING - A method includes training a machine learning model with data input including one or more sets of historical recipe parameters associated with producing one or more substrates with substrate processing equipment and target data including historical performance data of the one or more substrates to generate a trained machine learning model. The method further includes identifying one or more sets of additional recipe parameters associated with a level of uncertainty of the trained machine learning model. The method further includes further training the machine learning model with additional data input including the one or more sets of additional recipe parameters and additional target data including additional performance data of one or more additional substrates produced based on the one or more sets of additional recipe parameters to update the trained machine learning model. | 2022-06-23 |
20220198334 | METHOD AND SYSTEM FOR ACTIVE LEARNING AND FOR AUTOMATIC ANALYSIS OF DOCUMENTS - An active learning and automatic analysis system executes a learning mode and a production mode in parallel. In production mode, it responds to requests for the automatic analysis of documents using a machine learning model trained with annotated documents. In learning mode, it receives and stores non-annotated documents, and updates a descriptor with information about the automatic analysis prediction for the non-annotated documents. It samples the stored non-annotated documents whose descriptor has been updated, and determines an order of the sampled non-annotated documents for annotation by an oracle. It distributes the annotated documents between documents to be used in either training mode or validation mode. It trains at least one randomly structured candidate machine learning model which, in the event of better performance in terms of validation, replaces the model used in production mode. New training is then performed while updating the descriptor in accordance with the replacement model. | 2022-06-23 |
20220198335 | METHOD AND APPARATUS FOR COLLECTING DATA OF ARTIFICIAL INTELLIGENCE SYSTEM - A method and an AI system for collecting data on demand by starting data collection based on a predetermined data configuration of data required for development of AI model when design of the AI model starts on the AI system; storing raw data collected through the data collection and generating data processed for AI model learning or machine learning (ML) by pre-processing the raw data; and completing the development of the AI model by learning and validating the AI model designed based on the raw data and/or pre-processed data are provided. | 2022-06-23 |
20220198336 | Technique for Facilitating Use of Machine Learning Models - A technique for facilitating use of machine learning models in a system comprising a plurality of machine learning model providers ( | 2022-06-23 |
20220198337 | INFORMATION PROCESSING SYSTEM, INFORMATION PROCESSING METHOD AND INFORMATION PROCESSING DEVICE - An information processing system obtains a training data set including input data and a label, which is ground truth data for the input data, training a machine learning model on the training data set, inputs test data to the machine learning model trained on the training data set, evaluates whether performance of the machine learning model satisfies a predetermined condition based on an output of the machine learning model to which the test data is entered, updates the training data set when the performance of the machine learning model is evaluated not to satisfy the predetermined condition, and retrains the machine learning model on the updated training data set. The information processing system repeats updating, retraining, and evaluating the data set in response to the evaluation. | 2022-06-23 |
20220198338 | METHOD FOR AND SYSTEM FOR PREDICTING ALIMENTARY ELEMENT ORDERING BASED ON BIOLOGICAL EXTRACTION - A system for predicting alimentary element ordering based on biological extraction includes a computing device configured to identify an alimentary profile, wherein identifying further comprises obtaining a biological extraction of a user, determining an alimentary element order chronicle of a user, and identifying the alimentary profile as a function of the biological extraction and the alimentary element order chronicle, determine an edible of interest, wherein determining the edible further comprises receiving a datum as a function of an edible database, and determining the edible of interest as a function of the alimentary profile and the datum, obtain a nourishment information associated to the edible of interest, and generate a nourishment score as a function of the edible of interest and the nourishment information. | 2022-06-23 |
20220198339 | SYSTEMS AND METHODS FOR TRAINING MACHINE LEARNING MODEL BASED ON CROSS-DOMAIN DATA - Systems and methods for training an initial machine learning model is provided. The system may train an initial machine learning model using source domain training data with sample labels and target domain training data without sample labels. The initial machine learning model may include a feature extraction unit, a first processing unit, and an adversarial unit, wherein the first processing unit is associated with a first loss function, and the adversarial unit is associated with a second loss function. In some embodiments, the initial machine learning model may also include a second processing unit. A third loss function that reflects the consistency of the first processing unit and the second processing unit may be determined. The initial machine learning model may be trained based on the feature extraction unit, the first processing unit, the adversarial unit, and the second processing unit. | 2022-06-23 |
20220198340 | AUTOMATED MACHINE LEARNING TEST SYSTEM - A computing device selects new test configurations for testing software. Software under test is executed with first test configurations to generate a test result for each test configuration. Each test configuration includes a value for each test parameter where each test parameter is an input to the software under test. A predictive model is trained using each test configuration of the first test configurations in association with the test result generated for each test configuration based on an objective function value. The predictive model is executed with second test configurations to predict the test result for each test configuration of the second test configurations. Test configurations are selected from the second test configurations based on the predicted test results to define third test configurations. The software under test is executed with the defined third test configurations to generate the test result for each test configuration of the third test configurations. | 2022-06-23 |
20220198341 | STATE ESTIMATION DEVICE, STATE ESTIMATION PROGRAM, ESTIMATION MODEL, AND STATE ESTIMATION METHOD - A state estimation device includes a sensor information acquisition unit that acquires time-series sensor data, a state allocation unit that provisionally allocates a state label to sensor data, a first model learning unit that calculates a feature parameter of sensor data to which the same state label is allocated and performs learning of a state estimation model that classifies the sensor data at each time into any one of states, a second model learning unit that performs learning of a state transition model whose input is transition of state labels before a transition reference time and whose output is a state label at a time subsequent to the transition reference time, a state allocation update unit that updates a state label allocated to each time based on the state at each time estimated, and an output unit that outputs the state estimation model and the state transition model. | 2022-06-23 |
20220198342 | METHOD AND DEVICE FOR DETECTING MOORING AND MONITORING OF A NAVIGABLE AREA - The device for detecting mooring in a navigable area comprises:
| 2022-06-23 |
20220198343 | INFORMATION PROPOSING DEVICE AND INFORMATION PROPOSING METHOD - An information proposing device includes: an obtaining unit that obtains service provider information including information related to a service that a service provider is able to provide, and condition information related to a condition for a service that a user desires to receive; and a calculating unit that calculates information related to the service provider and the service to be selected by the user on the basis of a result of the matching processing. | 2022-06-23 |
20220198344 | SYSTEM AND METHOD FOR PROVIDING HEALTH STATUS WITH AN EVENT TICKET - A computer-implemented method comprises obtaining data associated with an event ticket and data associated with a digital health certificate of a user; generating a scannable code that includes the data associated with the event ticket and the data associated with the digital health certificate of the user, the scannable code configured to be scanned by a relying party device and causing the relying party device to display at least a notification indicating a ticket status and information associated with the user; and provide the scannable code to memory of a user device. | 2022-06-23 |
20220198345 | SYSTEM AND METHOD FOR REAL-TIME GEO-PHYSICAL SOCIAL GROUP MATCHING AND GENERATION - A system and method for real-time geophysical social grouping comprising customer profiles and venue profiles, wherein the profiles comprise expressed and inferred attributes, and a social grouping and recommendation server which utilizes machine learning algorithms on the profiles to generate recommendations for social group pairing, venues, and activities. Attribute matching provides optimized grouping between customers who share certain commonalities while also providing venues a system for locating and attracting ideal customers. Machine learning algorithms may be used to analyze profile attributes and identify patterns of commonality that would riot otherwise be recognized. This system allows patrons to meet, dine, and socialize with one or more matched individuals at a venue that satisfies all participants preferences and attributes. | 2022-06-23 |
20220198346 | DETERMINING COMPLEMENTARY BUSINESS CYCLES FOR SMALL BUSINESSES - Systems and methods for identifying businesses having complementary business cycles are disclosed. An example method may include receiving financial information for each business of a plurality of businesses, the financial information including a plurality of values of a financial indicator with respect to time, training a machine learning model to determine a preference metric for a pair of businesses based at least in part on respective values of the businesses' financial indicators, for each given business in the plurality of businesses, determining corresponding values of the preference metric, using the training machine learning model, for at least a respective subset of the plurality of businesses, and determining an optimal pairing for each business in the plurality of businesses based at least in part on the determined values of the preference metric. | 2022-06-23 |
20220198347 | PRODUCING EXTRACT-TRANSFORM-LOAD (ETL) ADAPTERS FOR PROGRAMMED MODELS DESIGNED TO PREDICT PERFORMANCE IN ECONOMIC SCENARIOS - Introduced here are risk management platforms able to implement an automated framework designed to manage, parse, and analyze data for purposes of facilitating compliance with relevant policies in a distributed computer environment. By implementing the technology described herein, an entity can ensure that it complies with the latest regulatory policies, recognizes emerging risks, and conducts more efficient operational planning. A risk management platform can generate interfaces through which an individual (also referred to as a “user”) can interact with the risk management platform. Through these interfaces, the user can apply programmed models to financial data associated with an entity to predict the performance of the entity under various economic scenarios. | 2022-06-23 |
20220198348 | Farming Data Collection and Exchange System - Embodiments of the present invention provide a passive relay device for farming vehicles and implements, as well as an online farming data exchange, which together enable capturing, processing and sharing farming operation data generated during combined use of the farming vehicle and farming implement at a farming business. The farming operation data includes detailed information about individual farming operations, including without limitation the type of farming operation, the location of the farming operation, the travel path for the farming operation, as well as operating parameters and operating events occurring while the farming operation is performed. | 2022-06-23 |
20220198349 | ADAPTIVE SYSTEMS, APPARATUS AND METHODS FOR ALIGNING ORGANIZATIONAL WORKFLOWS WITH ORGANIZATIONAL PURPOSE - A processor-implemented method includes defining, via a processor, a user purpose profile for each user from a plurality of users within an organization having an organizational purpose. The method also includes tracking, automatically via the processor and for each user from the plurality of users, an alignment among: (1) a representation of at least one work-related parameter such as strategy, a goal, or a associated with that user of a computer network of the organization, (2) activity data associated with that user and occurring with the computer network of the organization, and (3) at least one of (i) a representation of the organizational purpose, or (ii) and the user purpose profile associated with that user, to produce tracked data. The method also includes identifying at least one recommended action based on the tracked data. | 2022-06-23 |
20220198350 | COGNITIVE ANALYSIS FOR ENTERPRISE DECISION META MODEL - A computer implemented method is provided that includes creating an industry force graph meta model; and establishing a relationship for each maturity dimension to determine most relevant content. The most relevant content is graphed using a chromatic polynomial to map strongest industry trends in an industry force. The method continues with building traversal logic to determine most relevant technologies for the strongest industry trends in the industry force. Most relevant components of an component business model are identified, and linkages between the strongest industry trends in the industry force are made to the most relevant components of the component business model. | 2022-06-23 |
20220198351 | CONTEXTUALLY DEFINING AN INTEREST INDEX FOR SHARED AND AUTONOMOUS VEHICLES - System and methods are provided that contextually define interest index requirements for shared and autonomous vehicles. An interest index is computed based on detected contextual behavioral patterns of pedestrians such as the trajectory a candidate passenger is walking given a locational context. The use of the interest index allows users of shared vehicles to benefit from an enhanced user experience that seamlessly unlocks and/or provides access to features for autonomous vehicles based on the interest index. | 2022-06-23 |
20220198352 | System and Method for Vehicle Relocation - A method for relocating one or more vehicles of a fleet of shared vehicles in an operating area is provided. The operating area includes a plurality of zones, each zone of the plurality of zones being configured to designate a portion of the operating area. The method includes determining, for each zone of the plurality of zones, a relocation requirement for the one or more vehicles based on a predicted demand, the predicted demand including, for each zone of the plurality of zones, a respective demand indicative of a demand for vehicles in the respective zone; determining, based on the respective relocation requirement, the one or more vehicles to be relocated; and providing the one or more vehicles to be relocated with a relocation instruction. | 2022-06-23 |
20220198353 | SYSTEM AND METHOD FOR SHIFT SCHEDULE MANAGEMENT - Implementations relate to methods and systems to identify problem shifts. In some implementations, a method includes obtaining a plurality of published shift schedules, each published shift schedule associated with a respective shift of a respective employer of one or more employers, wherein each published shift schedule includes a location attribute, industry code attribute, and week indicator attribute; for each published shift schedule, obtaining a corresponding time and attendance record; programmatically analyzing the published shift schedule and the corresponding time and attendance record to determine unscheduled shifts; and adding unscheduled shift data associated with one or more unscheduled shifts to a training corpus, wherein the unscheduled shift data includes two or more of an employer identifier, a location identifier, a shift identifier, an industry identifier, an employee identifier, a job type identifier; and applying a machine learning algorithm to the training corpus to determine a plurality of problem shifts. | 2022-06-23 |
20220198354 | AUTOMATIC WELLBORE ACTIVITY SCHEDULE ADJUSTMENT METHOD AND SYSTEM - A method can include determining an ideal activity speed profile of an activity for a well, where the ideal activity speed profile of the activity for the well corresponds to a length of the well; forecasting a start time and a stop time using the ideal activity speed profile of the activity; generating a drilling plan using the start time and the stop time where another activity commences after the stop time; during performance of the activity for the well, receiving data indicative of an actual activity speed of the activity for the well for a corresponding length of the well; during the performance of the activity, deciding to make an adjustment to the performance of the activity for the well using the ideal activity speed profile and the actual activity speed of the activity for the well; and adjusting the stop time of the drilling plan. | 2022-06-23 |
20220198355 | OPTIMIZED DELIVERY SCHEME - A method, a system and a computer program product for providing efficient food delivery services. The method comprises determining based on a predicted demand within the delivery area, a food plan comprising predefined meals and generic meals associated with a plurality of concrete meals to be prepared and a delivery scheme for delivering food by delivery vehicles in accordance with the food delivery plan. After the determined quantity of the predefined meals is available for delivery, clients in the delivery area are enabled to order from the predefined meals. In response to a client making an order from the list, a respective meal is selected for delivery and the delivery scheme is automatically updated to enable fulfillment of the order. | 2022-06-23 |
20220198356 | SYSTEM AND METHOD FOR PRODUCT REARRANGEMENT IN RETAIL ENVIRONMENT BASED ON POSITION ADJACENCY AWARENESS PLAN - A system for recognizing a plurality of assets in an environment, determining a distribution of the plurality of assets, computing a position adjacency constraint for the distribution of the plurality of assets and a rearrangement plan based on position adjacency constraints for the plurality of assets in the environment is provided. The system (i) determines a distribution of a plurality of assets and type of each of the plurality of assets within the media content, (ii) determines a brand and at least one object from the brand associated with each of the plurality of assets, (iii) determines at least one attribute of the at least one determined object associated with the brand, (iv) computes a position adjacency constraints for the distribution of the plurality of assets and (v) computes a rearrangement plan for the plurality of assets within the environment based on the computed position adjacency constraint and compliance rules. | 2022-06-23 |
20220198357 | APPARATUSES, METHODS, AND COMPUTER PROGRAM PRODUCTS FOR MONITORING ASSET REMAINING USEFUL LIFETIME - Embodiments of the present disclosure provide for asset lifetime monitoring. Estimated values for factors representing root causes of operational anomalies of an asset may be generated utilizing one or more models. Estimated remaining lifetime values for one or more root cause variables may be generated that indicate a time until the value for a root cause variable is estimated to reach a particular limit threshold corresponding to the root cause variable, and/or an estimated second remaining lifetime value for an asset health index representing a combination of one or more root cause variables. The second remaining lifetime value for the asset health index may be provided to enable processing of the second remaining lifetime value as the remaining useful lifetime of the asset based on overall root cause variables. The first remaining lifetime value for one or more individual root cause variables may be provided to enable more detailed insight into individual root causes of operational degradation of an asset. | 2022-06-23 |
20220198358 | METHOD FOR GENERATING USER INTEREST PROFILE, ELECTRONIC DEVICE AND STORAGE MEDIUM - A method for generating a user interest profile includes: generating at least one keyword by extracting information from input information of a user; generating interest tags corresponding to the at least one keyword by matching the at least one keyword with tags corresponding to nodes of a knowledge graph; sorting the interest tags corresponding to the at least one keyword; and generating a user interest profile based on the sorted interest tags corresponding to the at least one keyword. | 2022-06-23 |
20220198359 | METHOD FOR AUGMENTING PROCEDURES OF A LOCKED, REGULATED DOCUMENT - A method for augmenting procedures at production equipment includes: linking a first description of a first step in a procedure and a capture type to a first capture field; generating a digital draft procedure comprising descriptions of steps extracted from the procedure and the first capture field specifying data capture of the first capture type from an equipment unit; generating augmented guidance for the first step in the procedure based on visual content recorded by a mobile device—assigned to an exemplary operator—during completion of the first step in the digital draft procedure; linking the augmented guidance to a location proximal the equipment unit based on locations of the first mobile device during completion of the first step in the digital draft procedure; and generating an augmented digital procedure based on steps in the procedure, the augmented guidance, and definitions for data capture according to the first capture field. | 2022-06-23 |
20220198360 | METHOD OF PREDICTING SOYBEAN YIELD - To provide a method for predicting a soybean yield at an early stage with high accuracy. | 2022-06-23 |
20220198361 | SYSTEMS AND METHODS FOR AUTOMATED EVALUATION OF DIGITAL SERVICES - A digital service evaluation system evaluates services and user sessions provided by a service, to provide an overall score of the service. The digital service evaluation system detects client sessions associated with one or more devices. The digital service evaluation system obtains a first plurality of scores associated with performance metrics of the client session, and calculates an overall score for the client session. The digital service evaluation system obtains a second plurality of scores and calculates a second overall score. The digital service evaluation system determines a weight for each performance metric based on the first and second plurality of scores and the overall scores. The digital service evaluation system uses the weights to determine which performance metric caused a change in the overall scores. The digital service evaluation system takes an action based on the determination that a performance metric caused a change in the overall scores. | 2022-06-23 |
20220198362 | GENERATION OF DASHBOARD TEMPLATES FOR OPERATIONS MANAGEMENT - A computer-implemented method for generation of dashboard templates for operations management is disclosed. The computer-implemented method includes monitoring a user interactions with an editable dashboard user interface when handling issue instances to gather chart selections, wherein a chart is a graphical visualization of one or more parameters of a data source. The computer-implemented method further includes identifying an issue type to chart pairs from the gathered chart selections and, for each pair, generalizing the one or more data source parameters. The computer-implemented method further includes identifying from the gathered chart selections common associations between the issue type and a chart visualization type. The computer-implemented method further includes storing dashboard information for an issue type including one or more likely chart visualization types for one or more generalized data source parameters, wherein the dashboard information is available to generate a dashboard template for a new issue instance of the issue type. | 2022-06-23 |
20220198363 | COMPATIBILITY VERIFICATION OF DATA STANDARDS - A set of standards to be used in a compatibility verification of one or more digital twin resources is received. A first digital twin resource added to a digital twin marketplace is analyzed. In response to determining that the first digital twin resource is not compatible with at least one standard in the set of standards based on the analysis, a non-compatibility badge associated with the first digital twin resource is displayed in a generated user interface associated with the digital twin marketplace. | 2022-06-23 |
20220198364 | SYSTEM AND METHOD FOR DETERMINING AND UTILIZING AFTER-CALL-WORK FACTOR IN CONTACT CENTER QUALITY PROCESSES - A computerized-method for calculating an After-Call-Work (ACW) factor of an interaction in a contact center, by which a related recording may be filtered for evaluation is provided herein. The method includes an After-Call-Work (ACW) factor calculation module. The operating of the ACW factor calculation module includes: (i) receiving agent recording of the interaction; (ii) aggregating data fields associated with: (a) the interaction; and (b) the customer; (iii) retrieving ACW time of the interaction; (iv) forwarding the aggregated data fields to a machine learning model; (v) operating the machine learning model to calculate a predicted ACW time, based on the aggregated data fields; (vi) calculating an ACW factor based on the received time of ACW and the calculated predicted ACW time; and (vii) sending the calculated ACW factor to a platform by which the platform is preconfigured to distribute the interaction for evaluation, based on the ACW factor. | 2022-06-23 |
20220198365 | SYSTEM AND METHOD FOR MANAGEMENT OF A TALENT NETWORK - A system and method for management of a talent network are disclosed. The system includes an expert ranking measurement subsystem configured to compute a quantitative score of an expert for a user query based on a talent metric and a trust metric, a qualitative score measurement subsystem configured to compute a qualitative score of the expert based on a content score and an activity score, wherein the content score is computed based on a content provided by the expert and the activity score is computed based on an activity occurring on a profile of the expert, an overall expert rank calculation subsystem configured to calculate an overall rank of the expert, wherein the overall expert rank is calculated based on the quantitative score, the qualitative score, predefined weightages assigned to the connection relationship, the plurality of professional achievements, the content score, the activity score, and user preferences. | 2022-06-23 |
20220198366 | SYSTEM AND METHOD FOR MANAGEMENT OF A TALENT NETWORK - A system and method for management of a talent network are disclosed. The system includes an expert ranking measurement subsystem configured to compute a quantitative score of an expert for a user query based on a talent metric and a trust metric, a qualitative score measurement subsystem configured to compute a qualitative score of the expert based on a content score and an activity score, wherein the content score is computed based on a content provided by the expert and the activity score is computed based on an activity occurring on a profile of the expert, an overall expert rank calculation subsystem configured to calculate an overall rank of the expert, wherein the overall expert rank is calculated based on the quantitative score, the qualitative score, predefined weightages assigned to the connection relationship, the plurality of professional achievements, the content score, the activity score, and user preferences. | 2022-06-23 |
20220198367 | EXPERT MATCHING THROUGH WORKLOAD INTELLIGENCE - Aspects of the present disclosure provide techniques for expert matching though workload intelligence. Embodiments include receiving a request for a support engagement. Embodiments include receiving workload data of a plurality of experts. Embodiments include determining a workload capacity of each respective expert based on the respective workload data for the respective expert. Embodiments include determining a respective estimated completion time for the support engagement for each of the plurality of experts using a machine learning model. Embodiments include determining match scores for the support engagement and each of the plurality of experts based on the estimated completion times and the workload capacities. Embodiments include selecting a given expert of the plurality of experts to handle the support engagement based on the match scores. | 2022-06-23 |
20220198368 | ASSESSMENT AND AUGMENTATION SYSTEM FOR OPEN MOTOR SKILLS - A system adapted to augment movement behavior of participants in an open motor task or activity includes one or more movement sensors configured to generate output characterizing movements of participants, including relevant interactions with elements and features of the environment and task or activity objects within the environment. A processor is configured to extract and segment a sequence of movement behavior elements from the output, register the movement elements with respect to operating environment, including the task or activity objects, recognize activity state, and determine cues to enhance performance and/or learning. Augmentations include verbal, visual, or haptic or audible signal-based cues that are designed to target critical aspects of movement skills in open motor tasks, including planning sequence of movements toward task goals; coordinating and executing movement elements in the sequence in relationship to relevant task activity events and elements. | 2022-06-23 |
20220198369 | MANAGEMENT DEVICE, CONTROL METHOD AND STORAGE MEDIUM - The acquisition unit | 2022-06-23 |
20220198370 | EVENT TRANSCRIPT PRESENTATION - A computer system receives data that includes indications of a plurality of agenda items that correspond to the group event. During the group event, the system captures, by a media recording device, media data, converts the captured media data to a searchable version of the media data and searches the searchable version of the media data to determine a first time frame of the media data that corresponds to a first agenda item of the plurality of agenda items. The system displays, in a user interface that is accessible to at least one user associated with the group event, the representation of the media data. A first portion of the representation of the media data that corresponds to the first time frame is visually distinguished from at least a portion of the representation of the media data that does not correspond to the first time frame. | 2022-06-23 |
20220198371 | ACTION MANAGEMENT METHOD, PROGRAM, AND ACTION MANAGEMENT SYSTEM - An action management method includes generation processing and acquisition processing. The generation processing includes generating a schedule in accordance with an arrangement order of a plurality of action modules. The plurality of action modules represent respective actions to be performed by a target person. The schedule indicates an order in which the target person is supposed to perform the actions. The acquisition processing includes acquiring an action log indicating an execution status in which the target person is following the schedule. | 2022-06-23 |
20220198372 | TIME-SERIES MACHINE LEARNING MODEL-BASED RESOURCE DEMAND PREDICTION - In one example, a non-transitory machine-readable storage medium encoded with instructions that, when executed by a processor, may cause the processor to obtain historical recruitment data associated with an enterprise for a period, pre-process the historical recruitment data, filter the pre-processed historical recruitment data based on a set of recruitment parameters, build a timeseries machine learning model with the filtered historical recruitment data associated with a portion of the period, test the time-series machine learning model with the filtered historical recruitment data associated with a remaining portion of the period, and predict a resource demand for an upcoming period using the timeseries machine learning model based on successful testing. | 2022-06-23 |
20220198373 | AERIAL VEHICLE AND COMPUTING DEVICE INTERACTION FOR VALIDATING AERIAL VEHICLE ACTIVITY - One or more processors obtain a first radio environment signature associated with an aerial vehicle (AV) and a second radio environment signature associated with a computing device. Responsive to determining that the first radio environment signature and the second radio environment signature satisfy a similarity criteria, the one or more processors generate a validation data object verifying one or more of (i) that a location of the AV substantially corresponds to a location of the computing device at a time associated with at least one of the first radio environment signature or the second radio environment signature, (ii) a AV delivery associated with the AV and the computing device, or (iii) a AV pickup associated with the AV and the computing device. The one or more processors store or provide validation information based on the validation data object. | 2022-06-23 |
20220198374 | OPTIMIZING SERVICE REQUESTS IN TRANSPORT SUPPLY-CONSTRAINED SUB-REGIONS - A system can implement a delivery service for a service region by monitoring, for each respective sub-region of the service region, supply conditions corresponding to transport providers available to deliver menu items from menu item suppliers to requesting users. When the supply conditions have dropped below the equilibrium threshold for a respective sub-region, the system can initiate a supply-constrained mode for the respective sub-region in which the system inputs each respective menu item request received, corresponding to a delivery location within the respective sub-region, into a queue, and dynamically determines a fulfillment probability for the respective menu item request. When the fulfillment probability of the respective menu item request exceeds a fulfillment threshold, the system can transmit the respective menu item request to a corresponding menu item supplier for preparation of a corresponding menu item and coordinate delivery of the corresponding menu item to the requesting user. | 2022-06-23 |
20220198375 | COORDINATION OF GOODS DELIVERY - A system includes one or more processing devices and at least one memory on which are stored instructions that, when executed by the one or more processing devices, enable the one or more processing devices to perform a method of facilitating delivery of an item from a source destination to a target destination. The method includes the steps of receiving a delivery-route assignment request from a first user device associated with a producer, transmitting the request to one or more vehicle drivers, receiving an acceptance of the request from a second user device associated with a vehicle driver, receiving a first signal indicating that the vehicle driver is a predetermined first distance from the source destination, receiving a second signal indicating that the vehicle driver is a predetermined distance from the target destination, and in response to receiving the second signal, authorizing a payment to the vehicle driver. | 2022-06-23 |
20220198376 | DYNAMIC UPDATE OF CHARGEBACKS FOR SPACE ALLOCATION - An average usage of floorspace by one or more organizations utilizing the floorspace is determined. In response to determining that for at least one organization of the one or more organizations a usage delta between the average usage of floorspace and an allocated floorspace amount associated with the at least one organization exceeds a threshold, an adjusted cost associated with the at least one organization is calculated. | 2022-06-23 |
20220198377 | SYSTEMS AND METHODS FOR AUTOMATED INFORMATION COLLECTION AND PROCESSING - A computer-implemented database system for processing a returned item may include a memory storing instructions and at least one processor configured to execute the instructions to perform a process. The process may include receiving information relating to a returned item and selecting a first terminal among a first group of terminals. The process may also include receiving, via a first user interface, a first response to one or more first queries. The process may further include determining, based on the first response, a first condition category of the returned item. The process may further include transmitting the information relating to the returned item to the second terminal. The process may also include causing a second display associated with the second terminal to display in a second user interface one or more second queries. | 2022-06-23 |
20220198378 | INFORMATION PROCESSING DEVICE, INFORMATION PROCESSING METHOD, AND SYSTEM - An information processing device includes a controller configured to execute acquiring a detection value obtained by detecting an amount of a product stored in a storage location corresponding to the product by a sensor, and transmitting a notification regarding a storage error of the product to a user terminal in a case where a decrease amount of the product based on the detection value of the sensor in a predetermined period is larger than a threshold value. | 2022-06-23 |
20220198379 | INFORMATION PROCESSING APPARATUS AND INFORMATION PROCESSING METHOD - An information processing apparatus including a processor, the processor being configured to execute acquiring a quantity of stock of a first product stored at a storage place based on a measured value indicating a weight of a load at the storage place by a weight sensor installed at the storage place. The processor executes: acquiring a weight per one article of the first product; and determining, when there is an increase or decrease from a last measured value to the current measured value of the weight sensor, whether or not the increase or decrease in the measurement value is due to addition or reduction of the first product, based on the weight per one article. The processor executes updating the quantity of stock of the first product when it is determined that the increase or decrease in the measured value is due to addition or reduction of the first product. | 2022-06-23 |
20220198380 | SYSTEMS AND METHODS FOR ELECTRONIC PLATFORM FOR TRANSACTIONS OF WEARABLE ITEMS - Disclosed are methods, systems, and non-transitory computer-readable medium for dynamically managing data associated with transactions of wearable items. For example, a method may include receiving wearable item data from one or more electronic tenant interfaces, hosting an electronic warehouse operations portal and/or an electronic administrative portal, receiving one or more electronic user transactions initiated at one or more user platforms, updating one or more transaction databases and one or more analytics databases, based on the one or more electronic user transactions, receiving one or more wearable item operations requests, initiating one or more microservices to fulfill the one or more wearable item operations requests, and updating at least one of the one or more transaction databases and one or more analytics databases based on completion of the one or more wearable item operations requests. | 2022-06-23 |
20220198381 | SECURITY SYSTEM - A security system for monitoring cargo in motion during transport, comprising means for:
| 2022-06-23 |