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Yayın Precursors of instability in a natural slope due to rainfall: a full-scale experiment(Springer Heidelberg, 2018-09) Askarinejad, Amin; Akça, Mehmet Devrim; Springman, Sarah MarcellaA full-scale landslide-triggering experiment was conducted on a natural sandy slope subjected to an artificial rainfall event, which resulted in mobilisation of 130m(3) of soil mass. Novel slope deformation sensors (SDSs) were applied to monitor the subsurface pre-failure movements and the precursors of the artificially triggered landslide. These fully automated sensors are more flexible than the conventional inclinometers by several orders of magnitude and therefore are able to detect fine movements (<1mm) of the soil mass reliably. Data from high-frequency measurements of the external bending work, indicating the transmitted energy from the surrounding soil to these sensors, pore water pressure at various depths, horizontal soil pressure and advanced surface monitoring techniques, contributed to an integrated analysis of the processes that led to triggering of the landslide. Precursors of movements were detected before the failure using the horizontal earth pressure measurements, as well as surface and subsurface movement records. The measurements showed accelerating increases of the horizontal earth pressure in the compression zone of the unstable area and external bending work applied to the slope deformation sensors. These data are compared to the pore water pressure and volumetric water content changes leading to failure.Yayın Predictive vector quantization of 3-D mesh geometry by representation of vertices in local coordinate systems(Elsevier Inc, 2007-08) Bayazıt, Uluğ; Orcay, Özgür; Konur, Umut; Gürgen, Sadık FikretIn predictive 3-D mesh geometry coding, the position of each vertex is predicted from the previously coded neighboring vertices and the resultant prediction error vectors are coded. In this work, the prediction error vectors are represented in a local coordinate system in order to cluster them around a subset of a 2-D planar subspace and thereby increase block coding efficiency. Alphabet entropy constrained vector quantization (AECVQ) of Rao and Pearlman is preferred to the previously employed minimum distortion vector quatitization (MDVQ) for block coding the prediction error vectors with high coding efficiency and low implementation complexity. Estimation and compensation of the bias in the parallelogram prediction rule and partial adaptation of the AECVQ codebook to the encoded vector source by normalization using source statistics, are the other salient features of the proposed coding system. Experimental results verify the advantage of the use of the local coordinate system over the global one. The visual error of the proposed coding system is lower than the predictive coding method of Touma and Gotsman especially at low rates, and lower than the spectral coding method of Karni and Gotsman at medium-to-high rates.
