Abstract: A mechanism is provided to proactively forecast gross margin for a business unit of an organization utilizing machine learning techniques. Embodiments provide a cascading-architecture machine-learning model to predict gross margin for a period (e.g., an upcoming quarter), utilizing metrics both internal and external to the organization. Internal metrics can include list price change, discounting change, cost impact, and the like. External metrics can include customer information such as propensity to purchase and purchase consumption.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to verify accuracy of a shipment. In some embodiments, items loaded to and/or unloaded from a delivery vehicle are scanned and compared to a delivery schedule, and a unique identifier is provided to confirm proper loading/unloading at a subsequent scheduled stop of the vehicle.

Abstract: There are provided systems and methods for application data integration for automatic data categorizations. A user associated with an organization, such as an employee of a company, may utilize a payment instrument or card affiliated with that company to make one or more purchases. In order to provide proper data allocation of transaction data resulting from that purchase, the company may utilize an expense management system to track data through one or more processes and databases. The expense management system may utilize application data integrations, such as a calendar application, in order to extract application data at a time of detection of electronic transaction processing to allocate that transaction data in real-time to particular actions taken by or engaged in by the user. Further, the application data integrations may allow for more precise data management by the expense management system.

Abstract: Systems, methods, and devices may enable management of a renewable power asset. A control device may generate a Day-Ahead (DA) pricing model, a Real-Time (RT) pricing model and a renewable generation model for the renewable power asset. Optimal DA commitments may be determined, and an optimal RT schedule estimated. A DA power delivery strategy and an RT power delivery strategy may be determined. The determined DA and RT power delivery strategies may be evaluated based on obtained real power prices. The DA and RT power delivery strategies may be redetermined, and the renewable power asset may be controlled to deliver power the DA and RT power delivery strategies. The value of the renewable power asset may be maximized while bounding financial risks and returns associated with scheduling the renewable power asset as tailored to risk preferences of the renewable power asset owner or operator.

Abstract: The present disclosure describes improvements in optimization systems. During an optimization loop, an advanced objective function is used to determine an objective value, a specification metric, and a rule coverage metric for a particular solution. The specification metric characterizes compliance of the solution with certain formal specifications. The rule coverage metric characterizes the degree to which all rules (or a particular rule) are tested during testing of the system. The objective value and metrics may influence future operation of the optimization loop.

Abstract: A method includes displaying on a graphic user interface (GUI) of a computing device of a user, a log of computing operations performed by the user at computing terminals of entity servers respectively managed by entities. The user uses a unique authorization identifier provided by the authorizing entity to authorize the computing operations at the computing terminals of the entity servers. The user provides a fraud indication through the GUI that at least one computing operation in the log is fraudulent. Memory jogging visual units are displayed on the GUI to the user that cause the user to recall performing the at least one computing operation identified as being fraudulent. An entry of the at least one computing operation in an operation database is marked as a valid operation authorized by the user when receiving a recognition indication and potentially fraudulent when no recognition indication by the user.

Abstract: Aspects of the invention include a computer-implemented method that receives, by a processor, an ensemble decision tree and generates, by the processor, native code from the ensemble decision tree. The method compiles, by the processor, the native code into machine language and scores, by the processor, the execution time of the native code. The method dynamically reoptimizes, by the processor, portions of the native code corresponding to the most traversed portion of the ensemble decision tree.

Abstract: A server device includes: an identification information storage configured to store identification information stored in identification tags; an identification information storage configured to store a baggage list where the items are listed for each activity; a schedule acquisition unit configured to acquire schedule information of the user; and a list generator configured to generate a baggage list according to an activity included in the schedule information of the user when the boarding of the user is identified. The list generator receives a plurality of schedule items that are set for a point of time after the boarding of the user is identified from the schedule acquisition unit and combines baggage lists that correspond to activities in the plurality of schedule items that have been received so as to generate a baggage list for checking in order to check whether there are enough baggage items.

Abstract: A system for solution architecture prediction may identify a previous solution from a data source and may create a historical solution evaluation matrix by mapping a plurality of concern categories with the previous solution. The system may identify a plurality of solution components preponderant to deriving a solution associated with the solution architecture prediction and create a potential solution evaluation matrix therefrom. The system may evaluate the historical solution evaluation matrix and the potential solution evaluation matrix to determine a credibility score for each solution comprised therein. Based on the evaluation, a solution prediction data may be generated including a previous solution, a potential solution, and the associated credibility score. A service solution may be selected from the solution prediction data to resolve the solution prediction requirement.

Abstract: A method for tracking containers. The method includes manufacturing containers, including forming the containers and serializing them with machine-readable codes. The method further includes using the machine-readable codes to store data associated with the containers, and supplying the containers to a customer. The method still further comprises receiving from the customer, data obtained from customer-readings of the machine-readable codes; and receiving from one or more other locations in a distribution chain in which the containers travel, data obtained from readings of the machine-readable codes at those locations. The method still further comprises comparing the data from the customer-readings and other readings of the machine-readable codes across product brands, product distribution channels, and/or container types, and providing the data to the customer.

Abstract: Systems and methods for features engineering, in which internal and external signals are received and fused. The fusing is based on meta-data of each of the one or more internal signals and each of the one or more external signals. A set of features is generated based on one or more valid combinations that match a transformation input, the transformation forming part of library of transformations. Finally, a set of one or more features is selected from the plurality of features, based on a predictive strength of each feature. The set of selected features can be used to train and select a machine learning model.

Abstract: Systems and methods for dynamic demand sensing in a supply chain in which constantly-updated data is used to select a machine learning model or retrain a pre-selected machine learning model, for forecasting sales of a product at a specific location. The updated data includes product information and geographic information.

Abstract: The present invention belongs to the field of information technology, involving the techniques of fuzzy modeling, reinforcement learning, parallel computing, etc. It is a method combining granular computing and reinforcement learning for construction of long-term prediction interval and determination of its structure. Adopting real industrial data, the present invention constructs multi-layer structure for assigning information granularity in unequal length and establishes corresponding optimization model at first. Then considering the importance of the structure on prediction accuracy, Monte-Carlo method is deployed to learn the structural parameters. Based on the optimal multi-layer granular computing structure along with implementing parallel computing strategy, the long-term prediction intervals of gaseous generation and consumption are finally obtained. The proposed method exhibits superiority on accuracy and computing efficiency which satisfies the demand of real-world application.

Abstract: A method and system for allocating displays to a plurality of stores grouped into a plurality of store configurations is presented. It includes receiving a plurality of counts, that specifies spaces available in the store configuration for one of a plurality of types of displays, a ranking of a plurality of displays, wherein the ranking is based on a benefit of each of the plurality of displays for the store configuration, and when the plurality of displays are to be allocated to the plurality of stores; determining a subset of the plurality of displays that meet one or more conditions related to at least one of a forecasted sell through or forecasted margin of the plurality of displays for the store, allocating at least some of the displays based on the ranking of the displays, and generating an indication of the allocated displays for output to a user.

Abstract: Systems and methods for generating an event occurrence feedback report after receipt of an event occurrence completion indicator, the event occurrence completion indicator associated with an event occurrence identifier and received from a third party event scheduling resource, and to present the event occurrence feedback report to a client device associated with an event occurrence creator identifier are provided herein.

Abstract: A method of analyzing one or more asset repositories to determine a developer's competency and ability to collaborate in a team environment. The method includes obtaining metadata artifacts as documents from one or more asset repositories. The documents are represented using a tree structure that has nodes to form a knowledge graph that is suitable for input vectorization. Each node is configured in the tree structure to represent a content region within the one or more documents, with a root node representing the entire document and each node representing an aggregation of all its children nodes. One or more computing devices are used to receive an input vector that includes a set of descriptive statistics about data in asset repositories and a vectorized form of one or more concepts. The developer's competency and ability to collaborate in a team environment is automatically estimated using output values of a trained neural network.

Abstract: Method, apparatus and computer program product for facilitating event creation and modification in a group-based communication platform are described herein.

Abstract: A system and method may determine the carbon emissions risk to an institution through its lending and investment activities to a plurality of counterparties by, for example, determining carbon emissions data for a number of counterparties and, for each counterparty, determining the carbon emissions risk to the institution. A system and method may determine the proportion of total capital of a counterparty that is being financed by a bank, and multiply this by a carbon emissions measure for the counterparty. Embodiments may be applied to determine optimal investment strategies for managing an institution's exposures to carbon risk over time.

Abstract: Provided are methods and apparatuses configured to programmatically generate and provide calendar digests of relevant group-based communication content to a client device associated with one or more event occurrence data structures.

Abstract: A system to provide an automated data driven risk relationship review tool via a back-end application computer server of an enterprise. A resource allocation data store may contain electronic records representing requested resource allocations between the enterprise and a plurality of entities. The server may receive an indication of a selected requested resource allocation and retrieve, from the resource allocation data store, the electronic record associated with the selected requested resource allocation. The server may automatically calculate a first and second review date for the selected requested resource allocation and automatically establish a communication link based on the first review date for the selected requested resource allocation. The system may then support a graphical interactive user interface display via a distributed communication network, the interactive user interface display providing resource allocation data in connection with the second review date.