outliers

SME investment best strategies. Outliers for assessing how to optimize performance

Any research on strategies for reaching business excellence aims at revealing the appropriate course of actions any executive should consider. Thus, discussions take place on how effective a performance measurement system can be estimated, or/and validated. Relevant questions can be raised, like: can one find an adequate measure (i) on the performance result due to whatever level of investment, and (ii) on the timing of such investments? We argue that extreme value statistics provide the answer.

Deep L1-PCA of time-variant data with application to brain connectivity measurements

L1-Principal Component Analysis (L1-PCA) is a powerful computational tool to identify relevant components in data affected by noise, outliers, partial disruption and so on. Relevant efforts have been made to adapt its powerful summarization capacity to time variant data, e.g. in tracking the evolution of L1-PCA components. Here, we analyze a layered version of L1-PCA, to which we refer to as Deep L1-PCA. Deep L1-PCA is obtained by recursive application of two stages: estimation of L1-PCA basis and extraction of the first rank projector.

Extraction of main levels of a building from a large point cloud

Horizontal levels are references entities, the base of man-made environments. Their creation is the first step for various applications including the BIM (Building Information Modelling). BIM is an emerging methodology, widely used for new constructions, and increasingly applied to existing buildings (scan-to-BIM). The as-built BIM process is still mainly manual or semi-automatic and therefore is highly time-consuming. The automation of the as-built BIM is a challenging topic among the research community.

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