Adaptation of Nonlinear Mathematical Models to Take into Consideration the Date of Conception of Animal Species
Issue:
Volume 4, Issue 2, June 2019
Pages:
18-23
Received:
23 August 2019
Accepted:
6 September 2019
Published:
21 September 2019
Abstract: Nonlinear functions are of great interest in the field of livestock, particularly through the modeling of the relationship between weight and age in animal species, which facilitates both the interpretation and the understanding of the growth phenomenon. Adjustments to growth data allow the information to be condensed into a few parameters that are used for selection purposes and to improve production forecasts. However, these functions do not take into consideration the fixed nature of the conception date which is specific for each animal species. In principle, all observations should be based on this date. The purpose of this study is to adapt the most frequently used mathematical models to take into consideration the conception dates of animal species. To do this, four functions were studied namely those of Logistic, Gompertz, Richards and Von Bertalanffy. Afterwards, modified models were developed to determine their derivatives and inflection points. An example of an initial model and its adaptations were adjusted to the data of moroccan sheep "sardi" to observe the effects of adaptations on the growth curves for males and females of this species. The results obtained show that among these functions, only Richards and Von Bertalanffy could be adapted according to two methods to meet the aforementioned objective because the logistic and Gompertz models are strictly positive and do not cancel each other out. In addition, the comparison example between Richards' Model and its adaptations to sheep data shows that for the initial model, the conception dates are -24.07 days and -23.6 days for males and females, respectively. while modified models, whose adjustment results show similar results, have -150 day conception dates for both sexes. In conclusion, the modified models of Richards and Von Bertalanffy seem to represent at best the biology of animal species and therefore, could replace the initial models for future studies of animal species growth modeling.
Abstract: Nonlinear functions are of great interest in the field of livestock, particularly through the modeling of the relationship between weight and age in animal species, which facilitates both the interpretation and the understanding of the growth phenomenon. Adjustments to growth data allow the information to be condensed into a few parameters that are...
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Decision-Making Framework Using a Growth Hacking Model for Computerized Decision Support
Okpala Izunna Udebuana,
Ikerionwu Charles
Issue:
Volume 4, Issue 2, June 2019
Pages:
24-30
Received:
21 August 2019
Accepted:
6 September 2019
Published:
24 September 2019
Abstract: Strategic decisions positively drive organizational performance and could have a measurable impact on any enterprise. Proper management and resource allocation are relevant to the growth of any organization, and there is an accelerated progression towards a complete overhaul of manual systems leading to the increased proliferation of digital systems. Businesses with less or no computerization create a bridge between users and data, in turn, causes poor decision making, loss of data on transit, time wastage in data extraction, poor data management, improper use of data and erroneous application of organizational data for decision making. This study utilizes information modeling method aimed at studying a decision-making framework and how growth hacking plays a critical role in the implementation of a decision support system for organizational growth. Supporting decision making in a traditional platform consumes time, taking note of the data collection phase, analysis and the choice of alternatives phases but a decision support system digitizes the whole process of data input or extraction, data processing, and the output mechanisms. The paper models the decision-making steps and also suggests that decision-making will take less time in contrast to the use of traditional methods using this growth hacking model. The end product of the implementation of the suggestions from the output stage of this model is growth.
Abstract: Strategic decisions positively drive organizational performance and could have a measurable impact on any enterprise. Proper management and resource allocation are relevant to the growth of any organization, and there is an accelerated progression towards a complete overhaul of manual systems leading to the increased proliferation of digital system...
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