Clemson University

About: Clemson University is a education organization based out in Clemson, South Carolina, United States. It is known for research contribution in the topics: Population & Control theory. The organization has 20556 authors who have published 42518 publications receiving 1170779 citations. The organization is also known as: Clemson Agricultural College of South Carolina.

The Ecological Significance of Behavioral Dominance

Abstract: In a discussion of the evolution of gene flow, Wilson (1975, p. 103) pointed out that a tendency for different sexes and age groups to migrate differentially can exert a profound influence on social structure. In this paper, I suggest that the reverse is equally true: a basic social structure—namely, the dominance hierarchy—can strongly influence the differential dispersal and migration of different sexes and age groups and thereby serve an important function in population dynamics.

Conceptualizing models using multidimensional constructs: a review and guidelines for their use

Abstract: While information on multidimensional constructs and empirical methods has become more accessible, there remain substantial challenges to theorizing about their form and implications. There are at ...

Automated fault location and diagnosis on electric power distribution feeders

Abstract: This paper presents new techniques for locating and diagnosing faults on electric power distribution feeders. The proposed fault location and diagnosis scheme is capable of accurately identifying the location of a fault upon its occurrence, based on the integration of information available from disturbance recording devices with knowledge contained in a distribution feeder database. The developed fault location and diagnosis system can also be applied to the investigation of temporary faults that may not result in a blown fuse. The proposed fault location algorithm is based on the steady-state analysis of the faulted distribution network. To deal with the uncertainties inherent in the system modeling and the phasor estimation, the fault location algorithm has been adapted to estimate fault regions based on probabilistic modeling and analysis. Since the distribution feeder is a radial network, multiple possibilities of fault locations could be computed with measurements available only at the substation. To identify the actual fault location, a fault diagnosis algorithm has been developed to prune down and rank the possible fault locations by integrating the available pieces of evidence. Testing of the developed fault location and diagnosis system using field data has demonstrated its potential for practical use.