– Partitioning clustering algorithms, construct non-overlapping clusters such that each item is assigned to exactly one cluster. Example: k-means – Agglomerative clustering algorithms construct a hierarchical set of nested clusters, indicating the relatedness between clusters. Example: hierarchical clustering • In classification, we partition data into known labels. For example, we might constr...

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...

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...

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...

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 parametrized by curve arc lengths. 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. ...

In this paper, we discuss interactively visualizing hierarchical clustering using multidimensional scaling (MDS) and the minimal spanning tree (MST). We can examine the sequential process leading to agglomerative or divisive hierarchical clustering, compare the di erent agglomerative methods, and detect in uential observations better than is possible with dendrograms.

MOTIVATION Sampling the conformational space is a fundamental step for both ligand- and structure-based drug design. However, the rational organization of different molecular conformations still remains a challenge. In fact, for drug design applications, the sampling process provides a redundant conformation set whose thorough analysis can be intensive, or even prohibitive. We propose a statist...

Corresponding Author Tb Ai Munandar Department of Informatics Engineering, Faculty of Information Technology, Universitas Serang Raya, Banten, Indonesia Email: [email protected] Abstract: The identification of regional development gaps is an effort to see how far the development conducted in every District in a Province. By seeing the gaps occurred, it is expected that the Policymakers are...