14,772 research outputs found
Modeling, Synthesis, and Validation of Heterogeneous Biomedical Embedded Systems
Abstract-The increasing performance and availability of embedded systems increases their attractiveness for biomedical applications. With advances in sensor processing and classification algorithms, real-time decision support in patient monitoring becomes feasible. However, the gap between algorithm design and their embedded realization is growing. This paper overviews an approach for development of biomedical devices at an abstract algorithm level with automatic generation of an embedded implementation. Based on a case study of a Brain Computer Interface (BCI), this paper demonstrates capturing, modeling and synthesis of such applications
DeSyRe: on-Demand System Reliability
The DeSyRe project builds on-demand adaptive and reliable Systems-on-Chips (SoCs). As fabrication technology scales down, chips are becoming less reliable, thereby incurring increased power and performance costs for fault tolerance. To make matters worse, power density is becoming a significant limiting factor in SoC design, in general. In the face of such changes in the technological landscape, current solutions for fault tolerance are expected to introduce excessive overheads in future systems. Moreover, attempting to design and manufacture a totally defect and fault-free system, would impact heavily, even prohibitively, the design, manufacturing, and testing costs, as well as the system performance and power consumption. In this context, DeSyRe delivers a new generation of systems that are reliable by design at well-balanced power, performance, and design costs. In our attempt to reduce the overheads of fault-tolerance, only a small fraction of the chip is built to be fault-free. This fault-free part is then employed to manage the remaining fault-prone resources of the SoC. The DeSyRe framework is applied to two medical systems with high safety requirements (measured using the IEC 61508 functional safety standard) and tight power and performance constraints
Mechanical and Systems Biology of Cancer
Mechanics and biochemical signaling are both often deregulated in cancer,
leading to cancer cell phenotypes that exhibit increased invasiveness,
proliferation, and survival. The dynamics and interactions of cytoskeletal
components control basic mechanical properties, such as cell tension,
stiffness, and engagement with the extracellular environment, which can lead to
extracellular matrix remodeling. Intracellular mechanics can alter signaling
and transcription factors, impacting cell decision making. Additionally,
signaling from soluble and mechanical factors in the extracellular environment,
such as substrate stiffness and ligand density, can modulate cytoskeletal
dynamics. Computational models closely integrated with experimental support,
incorporating cancer-specific parameters, can provide quantitative assessments
and serve as predictive tools toward dissecting the feedback between signaling
and mechanics and across multiple scales and domains in tumor progression.Comment: 18 pages, 3 figure
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