This paper presents a method for detecting and locating structural damages in local elements or regions of a structural
system by directly utilizing structural vibration measurements. A previously developed damage diagnosis technique is
enhanced by including a simplified lumped-mass model, which is equivalent to the complex frame structure. The
parameters derived from the simplified lumped-mass model are used in the damage diagnosis algorithm, while the actual
dynamic responses measured from the frame structure under seismic excitation are used as the inputs. The dynamic
responses measured from different floors can be decoupled by implementing the proposed damage diagnosis algorithm.
As a result, damages in the frame structure can be detected and located. Numerical examples of a three-story-one-bay
steel frame model and a benchmark-liked four-story-two-bay steel frame model are considered to demonstrate and
evaluate the effectiveness of the present method.
An automatic facial feature extraction algorithm is presented in this paper. The algorithm is composed of two main stages: the face region estimation stage and the feature extraction stage. In the face region estimation stage, a second-chance region growing method is adopted to estimate the face region of a target image. In the feature extraction stage, genetic search algorithms are applied to extract the facial feature points within the face region. It is shown by simulation results that the proposed algorithm can automatically and exactly extract facial features with limited computational complexity.
In this paper, a segmentation-based subband video coding algorithm is proposed. In this algorithm, each encoding frame is first compared with the associated prediction frame (outputed from a motion estimation based predictor) and the variant blocks (those blocks with variation larger than a given threshold) in the encoding frame are located. And the successive QMF decompositions and entropy coding are applied to encode each variant block. Simulations show that, by using the proposed coding scheme, the picture quality of the reconstructed frames is better than that of the other two well-known subband coding schemes while the resultant data rates are nearly the same. The computational complexities involved in the proposed approach are also shown to be less than that of the others. Moreover, the segmented nature of the proposed algorithm makes it more suitable for parallel implementation.
Full search block-matching algorithm (FBMA) was shown to be able to produce the best motion compensated images among various motion estimation algorithms. However, huge computational load inhibits its applicability in real applications. A lot of different methods, with lower complexity, have been proposed to speed up the process of motion compensation, but the resultant image quality cannot be as good as FBMA does. A new motion estimated algorithm, with less computational complexity and similar image quality while comparing to FBMA, will be presented in this paper. By considering the relation between neighboring blocks, the search area in the algorithm is adjustable. Due to the adaptation of the search area, the computation complexity can be largely reduced and the actual motion vectors can still be found. On the Sun SPARC-II workstation, the speed of the proposed algorithm can be 61 times faster than that of FBMA, maximally.