PURPOSE In this article, the authors report reliability and validity evidence for the Dynamic Evaluation of Motor Speech Skill (DEMSS), a new test that uses dynamic assessment to aid in the differential diagnosis of childhood apraxia of speech (CAS). METHOD Participants were 81 children between 36 and 79 months of age who were referred to the Mayo Clinic for diagnosis of speech sound disorder...

A new energy efficient clustering algorithm based on the highest residual energy is proposed to improve the lifetime of wireless sensor network (WSN). In each cycle, a fixed number of cluster heads are selected based on maximum residual energy of the nodes. Each cluster head is associated with a group of nodes based on the minimum distance among them. In such scheduling, all the nodes dissipate...

The article examines the innovative trends in renewable power generation, taking into account impact of crises, as well energy on air pollution world (environmental change). Hierarchical agglomerative and iterative methods cluster analysis, econometric models were used to test hypotheses. Carbon dioxide emissions generation for 78 countries during 2000-2020 are taken database study. results sho...

Hierarchical clustering constructs a hierarchy of clusters by either repeatedly merging two smaller clusters into a larger one or splitting a larger cluster into smaller ones. The crucial step is how to best select the next cluster(s) to split or merge. Here we provide a comprehensive analysis of selection methods and propose several new methods. We perform extensive clustering experiments to t...

In this paper we introduce a general framework for hierarchical clustering that deals with both static and dynamic data sets. From this framework, different hierarchical agglomerative algorithms can be obtained, by specifying an inter-cluster similarity measure, a subgraph of the β-similarity graph, and a cover algorithm. A new clustering algorithm called Hierarchical Compact Algorithm and its ...

BACKGROUND High-dimensional biomedical data are frequently clustered to identify subgroup structures pointing at distinct disease subtypes. It is crucial that the used cluster algorithm works correctly. However, by imposing a predefined shape on the clusters, classical algorithms occasionally suggest a cluster structure in homogenously distributed data or assign data points to incorrect cluster...

We present a slicing-based coherence measure for clusters of DTI integral curves. For a given cluster, we probe samples from the cluster by “slicing” it with a plane at regularly spaced locations parameterized by curve arclengths. Then we compute a stability measure based on the spatial relations between the projections of the curve points in individual slices and their change across the slices...