Stress Urinary Incontinence (SUI), defined as involuntary urine leakage caused by physical activity and/or efforts, is a frequently found pathology among women that significantly affects their quality of life. SUI treatments are often less effective than expected because they require a conscious effort by the patient to follow them correctly and usually have drawbacks, such as their high cost, time, and/or schedule requirements. ICT-mediated Physical Therapy treatment programs can be useful to improve Stress Urinary Incontinence symptoms and pelvic floor function in women while maintaining total confidentiality, with an at home treatment, accomplishing a higher adherence to the treatment, keeping a low budget for the patients, and saving the health systems' economic resources.
Predicting the performance of parallel scientific applications is becoming increasingly complex. Our goal was to characterize the behavior of message-passing applications on different target machines. To achieve this goal, we developed a method called parallel application signature for performance prediction (PAS2P), which strives to describe an application based on its behavior. Based on the application's message-passing activity, we identified and extracted representative phases, with which we created a parallel application signature that enabled us to predict the application's performance. We experimented with using different scientific applications on different clusters. We were able to predict execution times with an average accuracy greater than 97 percent.
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