5 results about "Activity factor" patented technology

A computer-implemented method for treating a patient suffering from Type I Diabetes (T1D). The method can include quantifying physical activity (PA) of the patient; calculating an accumulated PA periodically based on the quantified PA, the accumulated PA indicating an aggregate of the PA; and generating an activity informed insulin bolus by adjusting a prevalent functional insulin therapy bolus with a previous activity component, wherein the previous activity component is based on the accumulated daily PA, an activity profile, and an activity factor of the patient. The method can include determining an additional glucose uptake within a time period, the additional glucose uptake being caused by a PA; translating the additional glucose uptake into a number of insulin units with a same BG lowering impact; and generating an activity informed insulin bolus by adjusting a prevalent functional insulin therapy bolus with the insulin units.

The application belongs to the technical field of Internet, and relates to a marriage and dating method and system based on relationship management and independent life cycle constraint, which comprises the following steps: unified state coding and initialization, many-to-many relationship establishment and seat allocation, independent life cycle timing and dynamic constraint management, two-way threshold automatic confirmation and state migration, dynamic seat supplement and system closed-loop management, when the relationship is terminated due to expiration or active termination, the seats of both parties are released through an atomic transaction and the global state is updated, a mixed recommendation formula containing a cosine similarity, a Pearson correlation coefficient and an activity factor is used to generate and push new matching objects for the released seat users, and system parameters are dynamically adjusted through monitoring indicators to realize adaptive optimization. The matching efficiency can be significantly improved, the psychological pressure of users can be reduced, the fairness and timeliness of relationship development can be ensured, high automation and low manual intervention can be realized, and high scalability and adaptability are achieved.

The invention relates to the field of electronic commerce calculation, in particular to dynamic adjustment of probability weight. The invention provides a probability weight adjustment method based on user interaction, and the method comprises the steps: setting a user activity conversion rule which is used for converting a user behavior into a user activity factor; collecting a user behavior, and obtaining a user activity factor according to the user behavior and the user activity conversion rule; and taking the adjustment probability value as a final probability weight output value. The invention aims to provide a probability weight adjustment method and device based on user interaction, equipment and a medium, and the probability weight is different from a constant static design, but is a dynamic design based on user behaviors. The method is driven by user data activeness data and can be adaptively adjusted, and fairness and efficiency are comprehensively improved.

This invention relates to an information push method and system based on smart healthcare big data. The method includes: calculating the activation rate of single-category projects for each user category and project category combination; calculating a comprehensive project activation rate by using a weighted average method for multiple single-category project activation rates; setting a project activity factor based on the value of the single-category project activation rate; setting a user activity factor based on the number of project types involved in a single user; and generating an optimization scheme based on the single-category project activation rate, combined with the project activity factor and the user activity factor. By calculating the single-category project activation rate, it is possible to more accurately match users with smart healthcare projects, taking into account user interests and needs, combining project characteristics and target user groups, and better meeting the characteristics and preferences of different user groups, thereby improving the accuracy of push notifications and user experience.

A computer-implemented method for treating a patient suffering from Type I Diabetes (T1D). The method can include quantifying physical activity (PA) of the patient; calculating an accumulated PA periodically based on the quantified PA, the accumulated PA indicating an aggregate of the PA; and generating an activity informed insulin bolus by adjusting a prevalent functional insulin therapy bolus with a previous activity component, wherein the previous activity component is based on the accumulated daily PA, an activity profile, and an activity factor of the patient. The method can include determining an additional glucose uptake within a time period, the additional glucose uptake being caused by a PA; translating the additional glucose uptake into a number of insulin units with a same BG lowering impact; and generating an activity informed insulin bolus by adjusting a prevalent functional insulin therapy bolus with the insulin units.