Abstract: There is provided a method of training a machine learning model adapted for guiding subjects to an instructional goal, the method comprising: a) executing, by a guidance system of a subject, a guidance behavior; and b) training the machine learning model, by a processor, with a training input comprising, at least, data indicative of a time of the execution of the guidance behaviour, data indicative of a degree of completion of the instructional goal for the subject—at a given time, and data indicative of subject-specific information; wherein the machine learning model is adapted to enable calculating a ranking derivative of an estimated likelihood of satisfaction of an instructional goal completion criterion, for subject-specific information, subsequent to execution of a given guidance behaviour, thereby facilitating executing, by a guidance system of a given subject, a guidance behavior selected according to the ranking.

Abstract: An integrated circuit arrangement clocked by a single clock having variable delays to different regions of said arrangement such that said regions are partially synchronized to each other, the arrangement comprising: a data transfer buffer for buffering a data stream for transfer between respective first and second ones of said regions, and a data transfer controller, associated with said data transfer buffer and said respective regions, configured to control transfer of said data stream by: initially synchronizing between said respective regions at a start of said data stream, receiving data, in said buffer, from said first region, at a predetermined rate, and outputting said data stream to said second region at said predetermined rate in accordance with said initial synchronization. The arrangement allows deterministic data patterns to arrive at the receiving domain at minimal hardware cost.