The objective of this paper is to propose an adjustment to the three methods of calculating the probability that regularities in a sample data represent a systemic influence in the population data. The method proposed is called data profiling. It consists of calculating vertical and horizontal correlation coefficients in a sample data. The two correlation coefficients indicate the internal dynamic or inter dependency among observation points, and thus add new information. This information is incorporated in the already established methods and the consequence of this integration is that one can conclude with certainty that the probability calculated is indeed a valid indication of systemic influence in the population data.
The intent of this paper is to show that for the capitalist system to survive some specific form of economic activities have to be practiced. These economic activities are introduced in this paper in the form of economic theorems. Their existence and credibility are exhibited through structured proofs. Six economic theorems are introduced in total. In theorem 1 it is stated that for a capitalistic system to survive the domestic and international market share of territorial manufacturing and businesses should be kept limited. In theorem 2, it is stated that both manufacturing and businesses should have a limited life span. In theorem 3, it is stated that growth should be based on production and creation of real values. In theorem 4, it is stated that the relationship between (manufacturing, businesses) and banks should be based on wealth collected out of production activities and creation of real values in manufacturing and services. In theorem 5, it is stated that monopolistic and oligopolistic based economic activities are in conflict with small manufacturing and service activities. In theorem 6, it is stated that the capitalist system should evolve into a Parallel-Multi-Layer Capitalism (PMLC) where small and large economic activities can work on parallel levels with no interference.
The objective of this paper is to study the impact of a vehicular network on a physical (road) network consisting of several intersections controlled by traffic lights. The vehicular network is considered to be a random graph superimposed on a regular Hamiltonian graph. The two graphs are connected by hyperlinks. The evolution of traffic at intersections given the existence of vehicular networks is measured by the method of reflective triangles.
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