Abstract: A method, a system, and a computer program product for detecting and/or determining occurrence of a neurological event in a subject. Data corresponding to one or more symptoms, detected by one or more sensors, associated with a subject is received. The sensors include sensors positioned directly on the subject and/or sensors positioned away from the subject. One or more symptom values are assigned to one or more detected symptoms. A severity score for each of the symptoms is determined. The severity scores are determined using one or more machine learning models receiving the assigned symptom values as input. A prediction that the subject is experiencing at least one neurological event and at least a type of the neurological event is generated using a combination of the determined severity scores corresponding to the symptoms. A generation of one or more alerts is triggered based on the prediction. One or more user interfaces are generated for displaying the alerts.

Abstract: The present invention describes a system and method for scheduling jobs on a multiprocessor system. The invention includes schedulers for use in both work-sharing and work-stealing environments. Each system utilizes a task scheduler using historical usage information, in conjunction with a job scheduler to achieve its results. In one embodiment, the task scheduler measures the time spent on various activities, in conjunction with its previous processor allocation or previous desire, to determine an indication of its current processor desire. In another embodiment of the present invention, the task scheduler measures the resources used by the job on various activities. Based on these measurements, the task scheduler determines the efficiency of the job and an indication of its current processor desire. In another embodiment, the task scheduler measures the resources consumed executing the job and determines its efficiency and an indication of its current processor desire.

Abstract: The present invention describes a system and method for scheduling jobs on a multiprocessor system. The invention includes schedulers for use in both work-sharing and work-stealing environments. Each system utilizes a task scheduler using historical usage information, in conjunction with a job scheduler to achieve its results. In one embodiment, the task scheduler measures the time spent on various activities, in conjunction with its previous processor allocation or previous desire, to determine an indication of its current processor desire. In another embodiment of the present invention, the task scheduler measures the resources used by the job on various activities. Based on these measurements, the task scheduler determines the efficiency of the job and an indication of its current processor desire. In another embodiment, the task scheduler measures the resources consumed executing the job and determines its efficiency and an indication of its current processor desire.