Freeze Prediction Model

Measurements of wind speed, net irradiation, and of air, soil, and dew point temperatures in an orchard at the Rock Springs Agricultural Research Center, as well as topographical and climatological data and a description of the major apple growing regions of Pennsylvania were supplied to the University of Florida for use in running the P-model, freeze prediction program. Results show that the P-model appears to have considerable applicability to conditions in Pennsylvania. Even though modifications may have to be made for use in the fruit growing regions, there are advantages for fruit growers with the model in its present form

Development of Moisture Prediction Model for Tea using Electrical Impedance Spectroscopy

Moisture is the most essential parameter for tea leaves for storage and consumption stage as it affects the physical and chemical aspects of tea leaves with which it relates the stability and freshness the tea leaves for a long time. The most essential parameter which affects the quality of tea leaves is moisture for post harvesting, processing, storage and transport. The main aim of this study is to development procedure for moisture content measurements of fresh tea leaves using measurement acquired by electrical properties. Method This relation is obtained the frequency range within between 100 kHz to 300 MHz and moisture content ranges between 2%-75%. A good relation between moisture content and correlate with variations in electrical properties viz. IZI, Ѳz, R, Cp, Cs has been observed by partial least square regression technique. Result Moisture prediction model was developed by applying electrical properties and that the new technique it was observed more accuracy obtained using a single parameter as compared with that moisture measurement. Conclusion the model which is developed can evaluated with in performance the moisture content a commercial moisture meter which is expected

Microbial burden prediction model program

Model supplements biological surveys of spacecraft by simulating microbial burden accumulation process during periods when surveys are not taken. Important application of model is to predict microbial loading on spacecraft landing capsule immediately prior to terminal heat sterilization

Reliability prediction in model driven development

Evaluating the implications of an architecture design early in the software development lifecycle is important in order to reduce costs of development. Reliability is an important concern with regard to the correct delivery of software system service. Recently, the UML Profile for Modeling Quality of Service has defined a set of UML extensions to represent dependability concerns (including reliability) and other non-functional requirements in early stages of the software development lifecycle. Our research has shown that these extensions are not comprehensive enough to support reliability analysis for model-driven software engineering, because the description of reliability characteristics in this profile lacks support for certain dynamic aspects that are essential in modeling reliability. In this work, we define a profile for reliability analysis by extending the UML 2.0 specification to support reliability prediction based on scenario specifications. A UML model specified using the profile is translated to a labelled transition system (LTS), which is used for automated reliability prediction and identification of implied scenarios; the results of this analysis are then fed back to the UML model. The result is a comprehensive framework for addressing software reliability modeling, including analysis and evolution of reliability predictions. We exemplify our approach using the Boiler System used in previous work and demonstrate how reliability analysis results can be integrated into UML models