Many complex systems display a surprising degree of tolerance against errors. For example, relatively simple organisms grow, persist and reproduce despite drastic pharmaceutical or environmental interventions, an error tolerance attributed to the robustness of the underlying metabolic network [1

those for samples with d positive clones to samples with at most d − 1 positive clones, the error-tolerant property will have an interesting improvement. We also make a remark on decoding method for k-error-correcting d-disjunct matrix. © 2006 Elsevier B.V. All rights reserved.

This paper presents an efficient algorithm for retrieving from a database of trees, all trees that match a given query tree approximately, that is, within a cer- tain error tolerance. It has natural lan- guage processing applications in searching or matches in example-based translation systems

is one such efficient adder which speeds up binary addition. ETA is the Error Tolerant Adder which consumes less power and delay. Design of ETA is done using backend tool under real time simulation conditions. This paper compares the performance of the ETA in terms of accuracy, delay and power

generalize this concept by introducing error-tolerant combiners, which in addition to protection against insecure implementations provide tolerance to functionality failures: an error-tolerant combiner guarantees a secure and correct implementation of the output primitive even if some of the candidates

Abstract. Gradient-domain compositing is an essential tool in computer vision and its applications, e.g., seamless cloning, panorama stitching, shadow removal, scene completion and reshuffling. While easy to implement, these gradient-domain techniques often generate bleeding artifacts where the composited image regions do not match. One option is to modify the region boundary to minimize such mismatches. However, this option may not always be sufficient or applicable, e.g., the user or algorithm may not allow the selection to be altered. We propose a new approach to gradient-domain compositing that is robust to inaccuracies and prevents color bleeding without changing the boundary location. Our approach improves standard gradient-domain compositing in two ways. First, we define the boundary gradients such that the produced gradient field is nearly integrable. Second, we control the integration process to concentrate residuals where they are less conspicuous. We show that our approach can be formulated as a standard least-squares problem that can be solved with a sparse linear system akin to the classical Poisson equation. We demonstrate results on a variety of scenes. The visual quality and run-time complexity compares favorably to other approaches. Key words: gradient-domain compositing, visual masking 1

Abstract The use of agents in today’s Internet world is expanding rapidly. Yet, agent developers proceed largely under the optimistic assumption that agents will be error-free. Errors may arise in agents for numerous reasons — agents may share a workspace with other agents or humans and updates

Abstract not found

Gradient-domain compositing is an essential tool in computer vision and its applications, e.g., seamless cloning, panorama stitching, shadow removal, scene completion and reshuffling. While easy to implement, these gradient-domain techniques often generate bleeding artifacts where the composited image regions do not match. One option is to modify the region boundary to minimize such mismatches. However, this option may not always be sufficient or applicable, e.g., the user or algorithm may not allow the selection to be altered. We propose a new approach to gradient-domain compositing that is robust to inaccuracies and prevents color bleeding without changing the boundary location. Our approach improves standard gradient-domain compositing in two ways. First, we define the boundary gradients such that the produced gradient field is nearly integrable. Second, we control the integration process to concentrate residuals where they are less conspicuous. We show that our approach can be formulated as a standard leastsquares problem that can be solved with a sparse linear system akin to the classical Poisson equation. We demonstrate results on a variety of scenes. The visual quality and run-time complexity compares favorably to other approaches.

. The use of agents in today's Internet world is expanding rapidly. Yet, agent developers