Georgia College & State University

About: Georgia College & State University is a education organization based out in Milledgeville, Georgia, United States. It is known for research contribution in the topics: Population & Context (language use). The organization has 950 authors who have published 1591 publications receiving 37027 citations.

Efficient algorithms for computing the nearest polynomial with a real root and related problems

Abstract: We present three new algorithms in the general area of input-sensitivity analysis: a problem formulation, possibly with floating point coefficients, lacks an expected property because the inputs are slightly perturbed. A task is to efficiently compute the nearest problem that has the desired property. Nearness to the desired property can lead to problems for numerical algorithms: for example, an almost singular linear system cannot be solved by classical numerical techniques. In such case one can approach the problem of locating the nearest problem with the desired property by symbolic computation techniques, for instance, by exact arithmetic. Our three properties are:

A multiobjective module-order model for software quality enhancement

Abstract: The knowledge, prior to system operations, of which program modules are problematic is valuable to a software quality assurance team, especially when there is a constraint on software quality enhancement resources. A cost-effective approach for allocating such resources is to obtain a prediction in the form of a quality-based ranking of program modules. Subsequently, a module-order model (MOM) is used to gauge the performance of the predicted rankings. From a practical software engineering point of view, multiple software quality objectives may be desired by a MOM for the system under consideration: e.g., the desired rankings may be such that 100% of the faults should be detected if the top 50% of modules with highest number of faults are subjected to quality improvements. Moreover, the management team for the same system may also desire that 80% of the faults should be accounted if the top 20% of the modules are targeted for improvement. Existing work related to MOM(s) use a quantitative prediction model to obtain the predicted rankings of program modules, implying that only the fault prediction error measures such as the average, relative, or mean square errors are minimized. Such an approach does not provide a direct insight into the performance behavior of a MOM. For a given percentage of modules enhanced, the performance of a MOM is gauged by how many faults are accounted for by the predicted ranking as compared with the perfect ranking. We propose an approach for calibrating a multiobjective MOM using genetic programming. Other estimation techniques, e.g., multiple linear regression and neural networks cannot achieve multiobjective optimization for MOM(s). The proposed methodology facilitates the simultaneous optimization of multiple performance objectives for a MOM. Case studies of two industrial software systems are presented, the empirical results of which demonstrate a new promise for goal-oriented software quality modeling.

MEDTOUR: a scale for measuring medical tourism intentions

Abstract: Purpose – The purpose of this paper is to use a theoretical model to create a scale to predict medical tourism (MT) intentions.Design/methodology/approach – The theory of planned behavior (TPB) model was applied to MT by creating a 49‐item questionnaire and collecting data from a convenience sample of 453 undergraduate students enrolled in a university located in the USA. Factor analysis was used to evaluate the results, and yielded a MEDTOUR scale containing 29 items.Findings – A regression of the three variables on an intentions scale of participation in MT had an R‐value of 0.587. The model was able to explain around 35 percent of the variance in intentions. Given the general nature of the model and the first attempt at predicting MT, the results are positive.Research limitations/implications – This research is limited due to the use of a convenience sample of undergraduate students. Further research utilizing additional samples is needed to verify the MEDTOUR scale. In addition, future research can fo...

Behavioral parasitology and perspectives on miracidial host-finding

Abstract: This paper proposes and outlines a new interdiscipline, ‘behavioral parasitology,’ and presents some interpretations in one of the leading themes of this field, miracidial chemosensitivity to snails. Controversies over miracidial attraction and species-specificity are considered from the standpoints of the distinction between taxis and kinesis, the need for a stimulus gradient, and the possibility of an early phase in a miracidium's behavior adapted for dispersal rather than host-finding. Some of the many possible organic stimulants are discussed with regard to quantitative production by snails, sensory thresholds of the parasites, and possible interaction with inorganic ions. Organic and inorganic stimulants are considered to possibly from qualitative as well as quantitative gradients. A thermodynamic interpretation of miracidial klinokinesis as a function of stimulant concentration suggests the existence of two or more separate types of receptors for the same stimulant, one with a higher affinity for the stimulant and mediating a weaker klinokinesis (possibly a long-range receptor as compared to the other).