A LiDAR-Based Recommendation System to Improve Sitting Posture Respecting Privacy.

Poor posture is becoming more widespread due to the rising number of jobs that require workers to sit for extended hours. Maintaining proper leg positioning is essential for good overall posture and long-term health. However, current monitoring methods involve multiple sensors and cameras, leading to discomfort and privacy concerns.

Approaching the Ocean Color problem using fuzzy rules.

In this paper, we propose a fuzzy logic-based approach which exploits remotely sensed multispectral measurements of the reflected sunlight to estimate the concentration of optically active constituents of the sea water. The relation between the concentrations of interest and the subsurface reflectances is modeled by a set of fuzzy rules extracted automatically from the data through a two-step procedure. First, a compact initial rule base is generated by projecting onto the input variables the clusters produced by a fuzzy clustering algorithm.

A fuzzy relational clustering algorithm based on a dissimilarity measure extracted from data.

One of the critical aspects of clustering algorithms is the correct identification of the dissimilarity measure used to drive the partitioning of the data set. The dissimilarity measure induces the cluster shape and therefore determines the success of clustering algorithms. As cluster shapes change from a data set to another, dissimilarity measures should be extracted from data.