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A Synchronization Protocol for Temporal Isolation of Software Components in Vehicular Systems
Nolte, T.,Insik Shin,Behnam, M.,Sjodin, M. IEEE 2009 IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS - Vol.5 No.4
<P>We present a method that allows for integration of individually developed functions of software components into a predictable real-time system. The method has been designed to provide a lightweight mechanism that gives temporal firewalls between functions, preventing unpredictable side effects during function integration. The method maps well to the AUTOSAR (automotive open system architecture) software component model and can thus be used to facilitate seamless and predictable integration and isolation of AUTOSAR components that have been developed by different manufacturers. Specifically, this paper presents a protocol for synchronization in a hierarchical real-time scheduling framework. Using our protocol, a software component does not need to know, and is not dependent on, the timing behavior of software components belonging to other functions; even though they share mutually exclusive resources. In this paper, we also prove the correctness of our approach and evaluate its efficiency and cost in terms of system load in a vehicular context.</P>
Michael T. Nolte,Elliot D.K. Cha,Conor P. Lynch,Kevin C. Jacob,Madhav R. Patel,Cara E. Geoghegan,Caroline N. Jadczak,Shruthi Mohan,Kern Singh 대한척추신경외과학회 2021 Neurospine Vol.18 No.4
Objective: To assess change in Patient-Reported Outcome Measures (PROM) as predictors for revision lumbar decompression (LD). Methods: Patients who underwent primary, single or multilevel LD were retrospectively reviewed. Patients were categorized according to whether or not they underwent revision LD within 2 years of the primary procedure. Visual analogue scale (VAS), Oswestry Disability Index (ODI), 12-item Short Form Health Survey and 12-item Veterans RAND physical component score (SF-12 PCS and VR-12 PCS), and Patient-Reported Outcome Measurement Information System physical function (PROMIS-PF) were recorded. Delta PROM scores were evaluated for differences between groups and as a risk factor for a revision LD. Results: The study included 135 patients, 91 undergoing a primary procedure only and 44 undergoing a primary and revision procedure. Matched patients did not demonstrate any significant differences in demographics or perioperative characteristics. Patients who underwent a revision had a mean time to revision of 7.4±5.7 months. Primary cohort significantly improved for all PROMs (all p<0.05), while the primary plus revision cohort significantly improved for VAS back, ODI, and PROMIS-PF (all p<0.05). However, cohorts differed in VAS back and PROMIS-PF (p<0.05). Delta PROMs were not a significant risk factor for revision except at 6 months for PROMIS-PF (p=0.024). Conclusion: LD has been associated with reliable outcomes, but early identification of patients at risk for revision is critical. This study suggests that tools such as PROMIS-PF may serve a role in predicting who is at risk and the 6-month follow-up period may be valuable for counseling patients who are not experiencing improvement.