Decompressive hemicraniectomy improves survival in patients with malignant MCA infarction when compared with earlier reports of conservative treatment alone. Functional outcome and QOL remain markedly impaired, especially among elderly patients and in those with a severe neurological deficit at admission.

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Energy-efficiency is becoming one of the most critical issues in embedded system design. In Network-on-Chip (NoC) based heterogeneous Multiprocessor Systems, the energy consumption is influenced dramatically by task allocation schemes. Although various approaches are proposed to allocate tasks in an energy-efficient way, existing work does not well explore the tradeoff between the two major power consumers, namely the processors and network links, resulting in suboptimal mappings from a system point of view. In this paper, we first extend the existing Integer Linear Programming (ILP) formulation to take both processing and communication energy into account. Thereafter, we propose a Simulated Annealing with Timing Adjustment (SA-TA) heuristic to accelerate the optimization process. While the SA-TA algorithm achieves performance very close to the global optimum, significant improvement in computation speed is observed.

The Spiegelberg 3-PN sensor was reliable and simple to use. It can be recommended for routine intraparenchymal and subdural pressure measurement at a considerably lower price compared with other tip transducers and has the unique advantage of automated zeroing in vivo.

Reliability is a major requirement for most safety-related systems. To meet this requirement, fault-tolerant techniques such as hardware replication and software re-execution are often utilized. In this paper, we tackle the problem of analysis and optimization of fault-tolerant task scheduling for multiprocessor embedded systems. A set of existing faultand process-models are adopted and a Binary Tree Analysis (BTA) is proposed to compute the system-level reliability in the presence of software/hardware redundancy. The BTA is integrated into a multi-objective evolutionary algorithm via a two-step encoding to perform reliability-aware design optimization. The optimization results contain the mapping of tasks to processing elements, the exact task and message schedule and the fault-tolerance policy assignment. Based on the observation that permanent faults need to be considered together with transient faults to achieve optimal system design, we propose a virtual mapping technique to take both types of faults into account. To the best of our knowledge, this is the first approach in fault-tolerant task scheduling that considers permanent and transient faults in a unified manner. The effectiveness of our approach is illustrated using several case studies.