Abstract: Techniques for agriculture action recommendation are provided. Agricultural information from a plurality of data sources is used to generate a general agriculture data profile and user specific agricultural information is used to generate a user data profile. The general and user specific agricultural information is utilized by an agriculture optimization model to provide an action recommendation and the justification summary for an agriculture product. The action recommendation and the justification summary are based on a plurality of sell and storage options for the at least one agriculture product generated using the agriculture optimization model, where an optimal recommendation is selected by the agriculture optimization model for the agricultural product.

Abstract: Guiding agribusiness producer prescriptive decisions is provided. A first risk coefficient and a first profit coefficient corresponding to selling a commodity via a traditional market and a second risk coefficient and a second profit coefficient corresponding to selling the commodity via a futures market are calculated. A minimized level of risk is calculated based on the first and second risk coefficient and information in a profile received from a producer of the commodity. A maximized level of profit is calculated based on the first and second profit coefficient and information in the profile received from the producer of the commodity. A recommendation is sent to a dashboard with a justification including calculations of the minimized level of risk and the maximized level of profit, a first percentage of the commodity to sell via the futures market and a second percentage of the commodity to sell via the traditional market.

Abstract: Identifying malicious code execution of executing subject code of a software enclave of a processing system follows a process that includes monitoring performance characteristics of the processing system attributed to execution of the subject code of the software enclave. The monitoring produces performance data, which is stored to a relational database. The process applies a classification model to the stored performance data to obtain an output, and, based on the output of the classification model, identifies anomalous behavior in the execution of the subject code and determines a confidence level that the anomalous behavior exhibits malicious activity. Based on the confidence level exceeding a threshold, the process determines that the executing subject code is malicious and initiates halting of the execution of the subject code.

Abstract: A method, a computer system, and a computer program product for an artificial intelligence (AI) based agribusiness logistics advisor is provided. Embodiments of the present invention may include receiving a first user data. Embodiments of the present invention may include collecting a second user data and external data. Embodiments of the present invention may include preparing and transforming the second user data and the external data. Embodiments of the present invention may include conducting a hypothesis on the transformed data. Embodiments of the present invention may include validating the transformed data. Embodiments of the present invention may include training an artificial intelligence (AI) model based on the transformed data. Embodiments of the present invention may include matching the first user data with the artificial intelligence (AI) model. Embodiments of the present invention may include ranking results based on the matching the first user data with the artificial intelligence (AI) model.

Abstract: A method, computer system, and a computer program product for verifying the consistency of a current medical product is provided. The present invention may include generating a quantity associated with each of one or more active principles in the current medical product based on a plurality of current medical product data and a plurality of information from the data domains. The present invention may then include comparing the generated quantity associated with each of the one or more active principles in the current medical product with one or more constraints associated with a feasible solution associated with the current medical product. The present invention may further include determining a level of counterfeit risk based on the compared quantity associated with each of the one or more active principles in the current medical product with the one or more constraints from the feasible solution for the current medical product.

Abstract: Identifying malicious code execution of executing subject code of a software enclave of a processing system follows a process that includes monitoring performance characteristics of the processing system attributed to execution of the subject code of the software enclave. The monitoring produces performance data, which is stored to a relational database. The process applies a classification model to the stored performance data to obtain an output, and, based on the output of the classification model, identifies anomalous behavior in the execution of the subject code and determines a confidence level that the anomalous behavior exhibits malicious activity. Based on the confidence level exceeding a threshold, the process determines that the executing subject code is malicious and initiates halting of the execution of the subject code.