Abstract: There is provided a method for providing pricing information about a potential migration of a network computing task. The method includes the step of providing a provider availability set, identifying a price qualified set for each cloud service provider, and displaying the information about each cloud service provider and its pricing via a user interface. The price qualified set includes each cloud service provider: (a) whose price for performing the task complies with a price acceptability criteria or (b) that has a respective price proposal associated therewith reflecting a price for engaging the cloud service provider to perform the task in lieu of the task being performed by the network.

Abstract: A computer-implemented method includes receiving process information that specifies one or more process requirements and one or more potential causes of failures associated with processes for manufacturing a design, ii) control information that specifies one or more parameters and one or more values associated with the one or more parameters that facilitate determining whether the one or more process requirements specified in the process information that are associated with the processes are being met, and iii) sensor data associated with the one or more parameters from one or more sensors of a product development environment. Responsive to determining that sensor data associated with a particular parameter of the control information is outside of an associated range of values, a process requirement and a process associated with the parameter is determined based on the process information and the control information.

Abstract: Store a subscription dataset for each tenant of a multi-tenant system, each of the subscription datasets having a common data format native to the system, the subscription datasets including billing data and not behavioral data. Determine primary features from a particular subscription dataset. Derive secondary features from the primary features. Generate a churn prediction model based on the primary features and the secondary features. Obtain a second subscription dataset, the second subscription dataset comprising billing data that is more recent than the particular subscription dataset. Identify, using the particular churn prediction model and the second subscription dataset, one or more subscribers as a churn-risk. Report the one or more subscribers identified as a churn-risk.

Abstract: A system and method are disclosed for solving a supply chain planning problem modeled as a linear programming problem. Embodiments include receiving a matrix formulation of at least a portion of the linear programming problem representing a supply chain planning problem for a supply chain network, generating an image based on the matrix formulation to identify connected components, partitioning the matrix formulation based, at least in part, on the connected components constraint into at least two partitions, formulating an linear programming subproblem from each of the at least two partitions, and solving the linear programming subproblems to generate a global solution to the supply chain planning problem.

Abstract: A method, apparatus and computer program product are provided for providing resource adequacy intelligence information. A user may configure organizational data relating to various levels within an organizational hierarchy. Various assumption data, including quantifiable target developments of an organization, at any level of the hierarchy, may be configured. A monitoring engine monitors actual values of metrics provided by integrating systems, and/or predicted values predicted based on the actual values, relative to target values calculated according to assumption data. Alert conditions relating to metrics, and for any level of the hierarchy may be generated in response to the monitoring and provided via a user interface. Intelligence information relating to workforce needs, location optimization, and real estate needs is also provided.

Abstract: A method for obtaining credit card pricing for a merchant includes obtaining a merchant category classification (MCC) code. A sales volume, a number of credit card transactions, an average dollar amount of the credit card transactions and a percentage of credit card transactions that are keyed are obtained. The MCC code, the average dollar amount of the of credit card transactions processed and the percentage of credit card transactions that are keyed are compared with corresponding data from a database of merchant credit card transactions. A matched merchant is identified whose transaction profile closely matches a combination of the MCC code, the average dollar amount of the credit card transactions processed and the percentage of credit card transactions that are keyed. Credit card processing pricing information for the matched merchant is obtained from the database. The credit card processing pricing information is used to calculate credit card processing pricing for the matched merchant.

Abstract: An operation management apparatus includes: a plan generator that generates a travel plane for each of a plurality of vehicles which form a vehicle line and which travel autonomously along a prescribed travel path; a communication device that transmits the travel plan to a corresponding vehicle; and a judging unit that judges necessity of an addition of a vehicle to the vehicle line and an elimination of a vehicle from the vehicle line. When it is judged that the addition of the vehicle is necessary, the plan generator determines a position of addition of a new vehicle in the vehicle line based on at least one of travel information and passenger information transmitted from each of the plurality of vehicles, and generates a travel plan for adding the new vehicle at the position of addition.

Abstract: Embodiments of the invention are directed to systems, methods, and computer program products for utilizing machine learning to calculate product replacement cycle times and predict resource transfers associated with said product replacements. As such, the system allows for receipt of resource transfer datasets which are processed along with historical datasets via a machine learning engine. The system may then identify data trends and generate predictions of future resource transfers associated with product or service lifecycles. Furthermore, the system may also identify potential merchants or other third-party systems which may be associated with the predicted future transfers.

Abstract: This document describes techniques and apparatuses for enhancing data-analytic visualizations of a data analytics system. A computing device captures input data and output data associated with a data-analytic visualization generated by an advanced user using the data analytics system. The input data and output data are mapped together for defining the data-analytic visualization generated. A machine learning model is trained relative to the mapped input data and output data for generating the data-analytic visualization. During a normal usage of the data analytics system by a user, the trained model generates data-analytic visualizations to suggest to the user responsive to input data from the user. An optional threshold is set and applied relative to the data-analytic visualizations generated. If a data-analytic visualization meets the threshold, the data analytics system reports the data-analytic visualization.

Abstract: Methods and systems for controlling production resources in a supply chain are described. The system automatically generates predicted supply chain operational metrics across a nodes of a supply chain. The system automatically infers causal factors that impact the predicted supply chain operational metrics. The causal factors include a change to a utilization of the production resource. The system communicates a user interface including production runs being scheduled on the production resource including a user interface element representing the scheduling of the production run associated with a value at risk. The system receives input causing a change to the utilization of the production resource. The change to the utilization of the production resource impacts the predicted supply chain operational metrics including the value at risk associated with the scheduling of the production run.

Abstract: The present disclosure provides systems and methods that learn a loss function that, when (approximately) minimized over the training data, produces a model that performs well on test data according to some error metric. The error metric need not be differentiable and may be only loosely related to the loss function. In particular, the present disclosure presents a convex-programming-based algorithm that takes as input observed data from training a small number of models and produces as output a loss function. This algorithm can be used to tune loss function hyperparameters and/or to adjust the loss function on-the-fly during training.

Abstract: Embodiments of the invention are directed to techniques that include predicting, by a computer system, a number of predicted opportunities and signatures of the predicted opportunities expected in a time window. Based on the signatures of the predicted opportunities, the computer system generates a listing of entities ranked according to signatures of the predicted opportunities. The computer system selects the entities to be assigned to the predicted opportunities based, at least in part, on computing capacity related to sales while accounting for any current opportunities having been assigned to the entities.

Abstract: A computer-implemented method for managing a graphical user interface for a computer procurement application is disclosed. The graphical user interface is configured to show data related to key performance indicators (KPIs) for an entity and those for a peer group, show recommendations for improving values of the KPIs by adjusting values of configurations associated with the KPIs for the entity based on values of the KPIs and the associated configurations for the peer group in response to a first request, and implement the adjustment in response to a second request.

Abstract: A system and method are disclosed for solving a supply chain planning problem modeled as a linear programming (LP) problem. Embodiments include receiving a matrix formulation of at least a portion of the LP problem representing a supply chain planning problem for a supply chain network, generating an image based on the matrix formulation to identify connected components, partitioning the matrix formulation based, at least in part, on the connected components constraint into at least two partitions, formulating an LP subproblem from each of the at least two partitions, and solving the LP subproblems to generate a global solution to the supply chain planning problem.

Abstract: An apparatus for a license orchestrator to most efficiently distribute fee-based licenses includes a processor and a memory that stores code executable by the processor to determine that a workload is scheduled to be executed by a computing device. The computing device includes a licensable resource available for execution of the workload. The code is executable to compare a per-use licensing cost associated with using the licensable resource for execution of the workload with a cost of using existing capabilities of the computing device for execution of the workload and license and use the licensable resource for execution of the workload in response to determining that the per-use licensing cost of the licensable resource is less than using the existing capabilities of the computing device.

Abstract: Systems and methods for generating visual disposition data and identifying causal event are disclosed. An example system may include an electronic mobile device to generate visual disposition data from a plurality of items in a store. The example system may further include a server to generate processed disposition data via image processing the visual disposition data and determine disposition analysis data for an item of sale from the processed disposition data. The server may further transmit the disposition analysis data, where the disposition analysis data includes an indication of a causal event for the disposal of the item of sale.

Abstract: In an example embodiment, a series of machine learned models are trained and utilized in conjunction with each other to improve the reliability of predictions of fuel costs. One of these models is specifically trained to learn the “gap” time for a particular retail location, meaning the amount of time between when the futures contract market price on a trading exchange making up the fuel blend has the most correlation with the retail price of that fuel blend (for that particular location). This greatly enhances the reliability of the predictions of fuel costs, and, as described in detail herein, these predictions may be used in a number of different applications in unique ways.

Abstract: A method for improving performance of a computer procurement application includes using the procurement control system computer, determining a peer group associated with a first entity; using a procurement control system computer, obtaining, from client computers respectively associated with the entities, configurations that instruct a procurement application how to perform procurement tasks for the respective entities of the entities in the peer group; using a procurement control system computer, obtaining, from a first client computer associated with the first entity, a first configuration that instruct the procurement application how to perform procurement tasks for the first entity; obtaining a desired end result from the first entity; using the procurement control system computer, using a machine learning algorithm, determining configurations of the peer groups that have a causal relationship to the desired end result; providing a description of the configuration value to the client computer associated w

Abstract: Systems and methods of the present disclosure facilitate managing a business. In some embodiments, the system includes a product data module and a plurality of business process modules executing on at least one processor of a server. The product data module may be configured to store at least one product description. Responsive to a first user, the system may associate a product class with a first description. Responsive to a second user, the system may associate a first product description with a first of the business process modules. The system may be configured to select a second business process module based on the product class and update the second business process module with the first product description.

Abstract: An optimization apparatus for repeatedly obtaining a constraint violating solution, a constraint satisfying solution, and an approximate solution in a resource-constrained project scheduling problem performs setting an end time of a target optimization period at a point between a first finish time equal to a finish time of a latest version of the constraint violating solution and a second finish time equal to a finish time of a latest version of the constraint satisfying solution, followed by obtaining the approximate solution using a metaheuristic algorithm, making a determination as to whether the approximate solution violates constraint or satisfy the constraint, and performing, based on the determination, updating the first finish time with a finish time of the approximate solution when the approximate solution violates the constraint, and updating the second finish time with a finish time of the approximate solution when the approximate solution satisfies the constraint.