Abstract: A computerized-method for recommending activities for an agent, in a contact center is provided herein. The computerized-method includes operating an activities-recommendation module, for agents in a contact center, during a work-shift of an agent.

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: 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: 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: 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: 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: 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 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.

Abstract: A method and system are described for generating a quantified perception profile of a predetermined stimulus. The method may be used in colorimetry or flavor quantization. Flavor descriptors are selected from database for the particular product and presented pairwise in all possible pair combinations to each of a plurality of tasters via user-devices. For each flavor descriptor pair, users select one of the descriptors which is perceived to be more intense than the other. The results of the selections are captured at host and mapped by normalizing means as intensity values into a flavor descriptor space in database to create a quantized flavor profile. Normalizing means performs a weighting on each descriptor selection result. Filtering means detects anomalous or inconsistent selection responses and issues adaptive control instructions.

Abstract: Features related to a system and method for scheduling a resources to perform discrete tasks are described. The scheduling features include generating schedules predicted to appeal to the tasked resource (e.g., delivery partner) such as by time, day of the week, location, item types, etc. Using machine learning, the schedule and terms thereof can be dynamically generated to suit the tastes of each tasked resource and the overall demand for services. Using historical data, the modeling also accounts for likelihood an offer will be accepted and risk of cancellation for a given resource. The machine learning may be based on a mixed integer problem as constrained by partner and system capacity parameters.

Abstract: Techniques for automatically manufacturing mechanical parts are described. A first estimate of manufacturing cost for a first mechanical part is generated using a first machine learning model. In response to determining that the first estimate of manufacturing cost for the first mechanical part falls within a range of effectivity for the first machine learning model, a second estimate of manufacturing cost for the first mechanical part is generated using a second machine learning model. An expected cost error in the second estimate of manufacturing cost for the first mechanical part is determined, and upon determining that the expected cost error falls within a pre-determined acceptable range, automatic manufacturing of the first mechanical part is facilitated.

Abstract: Conventional resource management systems often merely assign resource data to accounts determined on a yearly basis, which does not provide an efficient means of planning for changes at a more granular level, or for making adjustments if an allocation needs to be modified during a budget period. An embodiment of the invention provides a method for managing modifications to an allocation. Modifications to an allocation may be represented as deltas, and the deltas may be evaluated against a set of rules to determine a precedence for selectively applying the deltas. The deltas may be selectively applied to the allocation according to the precedence to generate an allocation instance, and the allocation instance may be adapted into a location of a user interface.

Abstract: A computer system for performing automated market research using an electronic survey is provided herein. The computer system includes a communications subsystem for receiving survey content data. The communications subsystem also receives survey response data from at least one respondent device. The computer system includes a memory for storing the survey content data and the survey response data. The computer system includes a processor configured to execute a survey programming application. The survey programming application includes a survey design application for creating a survey program from the survey content data. The survey program provisions the electronic survey to respondents via the at least one respondent device and collects the survey response data from the respondents. The survey programming application also includes at least one survey program quality assurance tool.

Abstract: Presenting a content item and a 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 in the future, receiving, during the first feedback session, the first group's prediction of the target group's future 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 prediction using the target group predictive model, and providing inquirer access to the predictive model of the target group and the most accurate prediction.

Abstract: 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.

Abstract: Methods, systems and apparatus for implementing a security awareness program are provided which allow a device of a security awareness system to receive attributes of an implementation of a security awareness program from an entity, such as a company. Responsive to the attributes, the device determines a configuration for each of a baseline simulated phishing campaign, electronic based training of users of the entity for security awareness and one or more subsequent simulated phishing campaigns. The device initiates execution of the baseline simulated phishing campaign to identify a percentage of users of the entity that are phish-prone.

Abstract: This specification generally discloses technology for optimizing the loading of pallets on trucks and other sorts of vehicles. A pallet loading technique includes receiving pallet information for a shipment, the pallet information describing pallets to be included in the shipment, receiving vehicle constraint information for a vehicle, the vehicle constraint information describing rules for loading pallets on the vehicle, and determining candidate solutions for loading the pallets on the vehicle, each candidate solution (i) satisfying the rules for loading pallets on the vehicle, and (ii) defining, for each pallet to be included in the shipment, a respective position and orientation of the pallet on the vehicle. At least some of the candidate solutions are evaluated, one of the candidate solutions is selected, and the vehicle is loaded according to the selected candidate solution.

Abstract: Systems, devices, methods, and computer-readable media are disclosed for utilizing group theoretic techniques to enable data exchange between a supervisory central processing unit (CPU) and a group of graphical processing units (GPUs). The CPU may be configured to utilize a tabu search metaheuristic to explore a solution space to determine an optimal solution to an optimization problem. More specifically, the CPU may determine a fragmentation of a solution space that yields multiple partitions of the solution space and may assign each partition to a respective GPU configured to calculate a computational result. The CPU may then determine a new fragmentation of the solution space based on the computational results received from the GPUs that yields new partitions of the solution space and may assign each new partition to a respective GPU configured to again generate a computational result based on its assigned new partition.