Abstract: A survey method may include presenting a participant with a training stimulus through a survey channel, wherein the survey channel is capable of measuring a reactive aspect of the participant's response to stimuli, measuring the reactive aspect of the participant's response to the training stimulus through the survey channel, presenting the participant with a survey stimulus through the survey channel, measuring the reactive aspect of the participant's response to the survey stimulus through the survey channel, and evaluating the reactive aspect of the participant's response to the survey stimulus based on the reactive aspect of the participant's response to the training stimulus.

Abstract: The present invention relates to a national forest resources continuous inventory cloud platform and sample plot monitoring method. The cloud platform includes a perception layer, a network layer, a platform layer, a data layer, an application layer, and a user layer.

Abstract: Techniques are generally described for onboarding optimization for new hires. In various examples, labor order data specifying a target number of new hires may be received. In some examples, a first machine learning model may predict a number of new hire appointments to offer based at least in part on the labor order data. In further examples, an optimization component may allocate the number of new hire appointments to respective time slots based at least in part on candidate preferences. In some additional examples, data may be sent to a first application effective to display a list of available new hire appointment time slots of the respective time slots.

Abstract: Data system for organising workflows, in which the cooperation of human beings and machines is controlled intra-logistically with optimum protection for the human beings involved, having the following features: g) an intra-logistically relevant work area is divided into production or storage areas (1) that are accessible, by means of transport areas (7), to the human beings and machines involved in the work process without obstacles, wherein the transport areas (7) are completely available to data systems by means of expediently distributed radio subscribers as transmitters and receivers (6), and an intra-logistical manager system undertakes the superordinate control, h) numerous DTSs (driverless transport systems) in various configurations and manufacturer-specific control subsystems are usable, besides transport drones (9), for handling the transport tasks that arise, i) robots in various configurations and manufacturer-specific control subsystems are used, besides people (2) equipped with radios, for carry

Abstract: A computer-based method, system, and computer program product for automatically identifying significant events for food traceability. The method may comprise receiving a series of events from an agriculture supply chain entity, automatically determining, at a machine learning model of an event analysis module, one or more events in the series having a significance for food traceability greater than a threshold, and automatically reporting the one or more events to a ledger.

Abstract: Apparatus and methods present a content item and question from an inquirer to a group of users in a first feedback session with a requirement for the users to provide predictions of how a member of a distinct target group will respond to the content item, receiving, during the first feedback session, the first group's prediction of the target group's responses, presenting, during a second feedback session, the same content item and the same question to the target group with a requirement for the target group to provide responses directed to their own responses, constructing a predictive model of the target group based on responses received from the target group during the second feedback session, measuring accuracy of the first group's predictions using the target group predictive model and providing the inquirer access to an ordered visual representation of the first group users arranged as a function of accuracy.

Abstract: Candidate function data can include data for multiple candidate functions that may indicate whether insurance claims are likely to involve certain issues, such as comparative negligence issues. A real-time claim identifier can use the candidate function data to determine, in near real-time, if claim data for a new insurance claim submitted to an insurance company satisfies at least one of the candidate functions. If the claim data satisfies at least one of the candidate functions, the insurance claim can be assigned to a corresponding destination in the insurance company, such as a department that processes comparative negligence claims, for further processing.

Abstract: In one embodiment, a scheduling system includes an interactive graphical user interface. Each cell has a position in a displayed first array of cells and has respective scheduling data associated with it. Each cell is visually translocatable out of the first array under a user navigation to another position within the interface. A second array of cells is displayed within the interface and some cells in the second array correspond to open time slots in a schedule.

Abstract: A collaboration platform for implicitly determining user collaborations in real time or near real time is disclosed. The collaboration platform monitors event records generated based on user interactions with various team-based tools/collaborative applications to generate collaboration scores that provide a real time picture of a user's interactions with other users, and a user's interactions with content/objects/projects in the tools/collaborative applications. The collaboration platform also monitors user interactions with specific sub-projects to determine at any given time the users actively involved in any given project or sub-project.

Abstract: A method, apparatus, system, and computer program product for generating a schedule for project. Modules are selected from a collection of modules. A module in the collection of modules has a group of milestones. A set of backoffs is selected for a set of the modules. A backoff in the set of modules for the module in the set of modules points to a milestone in another module in the modules. Dates are determined for the milestones based on time periods for the milestones, the set of backoffs, and a reference date for the project to form the schedule for the project.

Abstract: Techniques for improving packaging systems are described. In an example, a computer system receives item data from a workstation. The item data includes a description of an item. The workstation is configured to facilitate packaging of the item. Based at least in part on an input to the predictive model, the computer system generates a package decision indicating a package type associated with the packaging of the item. The input is based at least in part on the item data. The predictive model is trained based at least in part on damage data associated with packaging. The computer system sends the package decision to the workstation.

Abstract: An object of the present invention is to manage not only a delivery schedule of an article but also a collection schedule of a container to be collected appropriately and efficiently. Provided is an order receiving management device including an order receiving management server 11 that receives use date data 29 by distributing user-specific calendar screen data 23 from a user-specific calendar generation part 21 to a client terminal 3, and controls a schedule calculation part 31 so as to generate order receiving data 37 based on the use date data 29 with respect to an order-receiving data generation part 35.

Abstract: Aspects of the present disclosure generally relates to a method including receiving group data and identifying at least a domain target for the at least a domain as a function of the domain-specific data. Also, the method may include generating a plurality of candidate schedules. Further, the method may include selecting one or more recommendations from the plurality of candidate schedules. Moreover, the method may include presenting, at a remote device, the one or more recommendations to a group, and tracking, by the computing device, a group's progress with regard to the optimal group schedule.

Abstract: The present disclosure involves systems, software, and computer implemented methods for proactively predicting demand based on sparse transaction data. One example method includes receiving a request to predict transaction quantities for a plurality of transaction entities for a future time period. Historical transaction data for the transaction entities is identified for a plurality of categories of transacted items. The plurality of categories are organized using a hierarchy of levels. Multiple levels of the hierarchy are iterated over starting at a lowest level. For each current level in the iteration, features to include in a quantity forecasting model for the current level are identified. The quantity forecasting model is trained using the identified features. Predicted transaction dates are predicted for the current level by a transaction date prediction model. The quantity forecasting model is used to generate predicted quantity information for the current level for the predicted transaction dates.

Abstract: A computer executed process for mimicking human dialog, referred to herein as a “humanoid” or “humanoid system,” can be configured to provide automated customer support. The humanoid can identify a support issue for a customer, as well as a customer support campaign corresponding to the support issue. The humanoid can identify at least one machine learning model associated with the customer support campaign and can communicate with the customer using the at least one machine learning model. The humanoid can execute a support action to resolve the support issue.

Abstract: Systems and methods include determination of a plurality of call map clusters, each call map cluster associated with a respective type of external call, two or more of a plurality of services, and a service call model modelling, for each of the two or more of the plurality of services, the issuance of outgoing service calls in response to received service calls. A bot is deployed proximate to each of the plurality of services, and each deployed bot is associated with a respective configuration to issue outgoing service calls in response to received service calls as modelled by the service call models for each of one or more services proximate to the deployed bot.

Abstract: Techniques to generate a digitally optimized schedule for a construction activity to meet a construction objective(s) of a construction project are disclosed. An artificial intelligence system receives a plurality of input data sets that impact the construction project. Each of the plurality of input data sets is processed to achieve the construction objective(s). The artificial intelligence system processes the plurality of input data sets using a respective ensemble of machine learning models. The artificial intelligence system generates machine learning validated intermediate output data sets corresponding to each of the plurality of input data sets. The artificial intelligence system implements a supervisory machine learning model to generate an optimized schedule for the construction activity based on the machine learning validated intermediate output data sets and the construction objective(s).

Abstract: Systems, methods, and computer programming products for self-learning order dressing rules applied to manufacturing products in accordance with received product specifications. The translation from commercial characteristics to manufacturing characteristics of the product being manufactured are learned and adjusted to meet the specifications for quality required by the provided commercial characteristics. Reinforcement learning models learn from the quality characteristics of produced products by applying positive scores when the commercial to manufacturing characteristic translation is on-specification, otherwise a penalty is applied when an off-spec product is produced. Digital twins of manufacturing equipment, simulated in real time, provide insight and recommendations for achieving correct quality characteristics. Sensors in each device or within the surrounding environment help digital twins to measure operational performance and lifecycle of the manufacturing equipment against historical baselines.

Abstract: A system for third party email parsing comprises an input interface and a processor. The input interface is configured to receive an email. The processor is configured to: 1) determine whether the email is from a lead generating system; and 2) in the event that the email is from a lead generating system: a) extract real estate lead information from the email based at least in part on the lead generating system; b) determine whether the real estate lead information is sufficient for a real estate related customer relations management database entry; and c) in the event that the real estate lead information is sufficient for a real estate related customer relations management database entry, add the real estate lead information to a real estate related customer relations management database.

Abstract: A facility for estimating a subject home's value is described. For each of one or more direct home attributes, the facility determines the value of the direct home attribute for the subject home. For each of a plurality of arbitrary geographic regions of different sizes containing the subject home, the facility determines information relating to the geographic region as a whole. The facility then subjects the determined values and information to a statistical home valuation model to obtain an estimated value of the subject home.