Abstract: There is disclosed a method and system for combining datasets. Study results may be retrieved. Each study result may include datapoints. Each datapoint may include attributes. Study questions may be extracted from the study results. The questions may be converted into a standardized format. Categories may be assigned to the questions. The questions may be grouped together into groups. A response scale may be determined for each of the groups. The responses may be rescaled using the corresponding response scale. A final dataset may be generated by combining the study results. Features may be selected using the final dataset. A machine learning algorithm may be trained using the features of the final dataset.

Abstract: A method for producing cannabinoid cooking oil and budder uses a mixture of cannabinoid material and natural oils to produce a consumable spread. The method used a quantity of cannabinoid substance, and a quantity of foaming substance. The foaming substance is a natural oil that can absorb and blend with the cannabinoid substance. The method begins by continuously agitating the cannabinoid substance with the foaming substance until a paste mixture is formed. The method continues by cooling the paste mixture until a solidified mixture is formed. The method concludes by thawing the solidified mixture to yield a tetrahydrocannabinol (THC) infused spreadable paste. Thus, an edible mixture is produced. Some versions of the method feature a flavoring substance that is added to the cannabinoid and foaming substance mixture. Thus, improving flavor.

Abstract: A method is provided for enterprise management and bundling of inventory to maximize revenue on perishable products. An electronic data-mart collects factors for the probability and price sensitivity of a buyer. The data-mart also collects rules for inventory scaling, available inventory to sell, budget (goal) information, advertiser payment history, and station performance data to feed to a scenario planner. Once three or more variables exist, algorithms create scenario plans to present the most profitable bundle of offerings. The scenarios are typically pre-approved although presented to local business units for an abnormality failsafe. Once processed by local business units, the scenarios are presented to the buyer. Negotiations typically cause the process to restart.

Abstract: A method is provided for enterprise management and bundling of inventory to maximize revenue on perishable products. An electronic data-mart collects factors for the probability and price sensitivity of a buyer. The data-mart also collects rules for inventory scaling, available inventory to sell, budget (goal) information, advertiser payment history, and station performance data to feed to a scenario planner. Once three or more variables exist, algorithms create scenario plans to present the most profitable bundle of offerings. The scenarios are typically pre-approved although presented to local business units for an abnormality failsafe. Once processed by local business units, the scenarios are presented to the buyer. Negotiations typically cause the process to restart.

Abstract: A method is provided for enterprise management and bundling of inventory to maximize revenue on perishable products. An electronic data-mart collects factors for the probability and price sensitivity of a buyer. The data-mart also collects rules for inventory scaling, available inventory to sell, budget (goal) information, advertiser payment history, and station performance data to feed to a scenario planner. Once three or more variables exist, algorithms create scenario plans to present the most profitable bundle of offerings. The scenarios are typically pre-approved although presented to local business units for an abnormality failsafe. Once processed by local business units, the scenarios are presented to the buyer. Negotiations typically cause the process to restart.

Abstract: A method is provided for enterprise management and bundling of radio, outdoor and entertainment inventory to achieve maximum revenue on perishable products. An electronic data-mart 110 or central information storage and data processing system is established to collect influencing factors for the probability and price sensitivity of a particular advertising buyer 120. The data-mart 110 also collects business rules for inventory scaling, available inventory to sell, budget (goal) information, advertiser payment history, and station performance data to feed to a scenario planner 130. Once three or more variables exist, inventory and pricing fuzzy logic algorithms create scenario plans to present the most profitable bundle of offerings. The scenarios are typically pre-approved although presented to the local business units 150 for an abnormality failsafe. Once processed by the local business units 150, the scenarios are presented to the advertising buyer 120.

Abstract: A method is provided for enterprise management and bundling of radio, outdoor and entertainment inventory to achieve maximum revenue on perishable products. An electronic data-mart 110 or central information storage and data processing system is established to collect influencing factors for the probability and price sensitivity of a particular advertising buyer 120. The data-mart 110 also collects business rules for inventory scaling, available inventory to sell, budget (goal) information, advertiser payment history, and station performance data to feed to a scenario planner 130. Once three or more variables exist, inventory and pricing fuzzy logic algorithms create scenario plans to present the most profitable bundle of offerings. The scenarios are typically pre-approved although presented to the local business units 150 for an abnormality failsafe. Once processed by the local business units 150, the scenarios are presented to the advertising buyer 120.

Abstract: A method is provided for enterprise management and bundling of radio, outdoor and entertainment inventory to achieve maximum revenue on perishable products. An electronic data-mart 110 or central information storage and data processing system is established to collect influencing factors for the probability and price sensitivity of a particular advertising buyer 120. The data-mart 110 also collects business rules for inventory scaling, available inventory to sell, budget (goal) information, advertiser payment history, and station performance data to feed to a scenario planner 130. Once three or more variables exist, inventory and pricing fuzzy logic algorithms create scenario plans to present the most profitable bundle of offerings. The scenarios are typically pre-approved although presented to the local business units 150 for an abnormality failsafe. Once processed by the local business units 150, the scenarios are presented to the advertising buyer 120.

Abstract: A method is provided for enterprise management and bundling of radio, outdoor and entertainment inventory to achieve maximum revenue on perishable products. An electronic data-mart 110 or central information storage and data processing system is established to collect influencing factors for the probability and price sensitivity of a particular advertising buyer 120. The data-mart 110 also collects business rules for inventory scaling, available inventory to sell, budget (goal) information, advertiser payment history, and station performance data to feed to a scenario planner 130. Once three or more variables exist, inventory and pricing fuzzy logic algorithms create scenario plans to present the most profitable bundle of offerings. The scenarios are typically pre-approved although presented to the local business units 150 for an abnormality failsafe. Once processed by the local business units 150, the scenarios are presented to the advertising buyer 120.