Fault interactions and reactivation within a normal-fault network at Milne Point, Alaska

A generalized ABFT technique using a fault tolerant neural network

In this paper we first show that standard BP algorithm cannot yeild to a uniform information distribution over the neural network architecture. A measure of sensitivity is defined to evaluate fault tolerance of neural network and then we show that the sensitivity of a link is closely related to the amount of information passes through it. Based on this assumption, we prove that the distribu...

Evidence for fault weakness and ̄ uid ̄ ow within an active low - angle normal fault

Determining the composition and physical properties of shallowdipping, active normal faults (dips , 358 with respect to the horizontal) is important for understanding how such faults slip under low resolved shear stress and accommodate signi®cant extension of the crust and lithosphere. Seismic re ̄ection images and earthquake source parameters show that a magnitude 6.2 earthquake occurred at abo...

Repeating deep earthquakes: evidence for fault reactivation at great depth.

We have identified three groups of deep earthquakes showing nearly identical waveforms in the Tonga slab. Relocation with a cross-correlation method shows that each cluster is composed of 10 to 30 earthquakes along a plane 10 to 30 kilometers in length. Some of the earthquakes are colocated, demonstrating repeated rupture of the same fault, and one pair of events shows identical rupture complex...

No-Fault Laws and At-Fault People

presenting a fault tolerant mechanism for buffering fault in network on chips

as technology scales deep into the nanometer regime, on-chip communication becomes more susceptible to transient noise sources, such as crosstalk, external radiation, and spurious voltage spikes. the network on chip s modularity and reusability has brought about the use of error control methods to address transient errors in network on chip links.in this work, we design a fault tolerance router...