Prolog was a modern, promising and a very popular programming language thirty years ago and logic Programming acquired a firm place within Computer Science as well as in ICT programs curricula especially at European a...
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ISBN:
(纸本)9781538677117
Prolog was a modern, promising and a very popular programming language thirty years ago and logic Programming acquired a firm place within Computer Science as well as in ICT programs curricula especially at European and Asian Universities. However, the rapid development of new programming languages moved Prolog far away from the beginning of the list of the most widely utilized programming languages. Therefore the logical question is whether there are still some good and justified reasons to keep logic Programming in the present ICT specialists curricula. This paper outlines some general reasons for maintaining it on the list of the subjects taught and it brings out some basic examples showing the usefulness of the logic programming paradigm especially when explaining and teaching the efficient utilization of recursion.
The functional properties of living organisms have a complexity exceeding the human capacity for analysis. A basic conviction in computational biology is that it should be possible to develop computational tools allow...
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The functional properties of living organisms have a complexity exceeding the human capacity for analysis. A basic conviction in computational biology is that it should be possible to develop computational tools allowing us to considerably increase our understanding of such functional *** a fragment of reality is closely related to having a model of such a fragment. Hence, model construction is a high priority on the agenda of computational biology. Once available, a model can then be analyzed with different techniques. These two processes, however, are often intertwined, as analysis can guide the construction of a *** the models for biochemical and gene networks (de Jong, 2002; Fages and Soliman, 2008), ordinary differential equations are of prime importance. Stochastic models based on Gillespie’s method (identified with continuous-time Markov chains), represent perhaps a most concrete model. Discrete models (e.g., Petri nets) are prominent, as abstractions from stochastic techniques, where both the concentrations and time have been discretized. Finally, Boolean formalisms are abstractions of discrete models. Boolean models were initially studied with propositional logic (i.e., Boolean logic). Later, however, close connections with more expressive logics have been established, such as those underlying logic Programming (Kowalski, 2014) and Model Checking (Clarke et al., 1999).Analysis techniques vary in the direction of treatment of time. Simulators normally deal with time in a forward manner by reproducing in the model a single behavior among all possible behaviors from an initial state. Model checkers, by contrast, often proceed backwards by analyzing, in reverse, all possible behaviors ending in a given set of final ***-construction techniques, in turn, range from those completely performed by a human being to those entirely *** a living system through a model could be a goal per se. The model of a syste
About 90% of breast cancers do not cause or are capable of producing death if detected at an early stage and treated properly. Indeed, it is still not known a specific cause for the illness. It may be not only a begin...
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ISBN:
(纸本)9783319192222;9783319192215
About 90% of breast cancers do not cause or are capable of producing death if detected at an early stage and treated properly. Indeed, it is still not known a specific cause for the illness. It may be not only a beginning, but also a set of associations that will determine the onset of the disease. Undeniably, there are some factors that seem to be associated with the boosted risk of the malady. Pondering the present study, different breast cancer risk assessment models where considered. It is our intention to develop a hybrid decision support system under a formal framework based on logic Programming for knowledge representation and reasoning, complemented with an approach to computing centered on Artificial Neural Networks, to evaluate the risk of developing breast cancer and the respective Degree-of-Confidence that one has on such a happening.
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