In this survey, the issues of urban routing are analyzed, and critical considerations for smart and cost-effective delivery services are highlighted. Smart cities require intelligent services and solutions to address their routing issues. This article gives a brief description of current services that either apply classical methods or services that employ machine learning approaches. Furthermore, a comparison of the most promising research options in regard to VRP is provided. Finally, an initial design of a holistic scheme that would optimally combine several tools and approaches to serve the needs of different users with regard to the VRP is presented.
In this paper the dynamic behavior of the cells of the immune system is studied through the use of a mathematical and physical model developed using artificial neural networks. Simulations were obtained by solving the equation for the appropriate neuron models, in particular a two cell module. By calculating the equilibrium point of the system and taking into account the bioimpedance of the linearized model, we can determine whether the system is stable or not and whether a self immune disease is developing.
Safety-critical systems embedding concurrent on-line testing techniques are vulnerable to design issues causing the degradation of totally self-checking (TSC) property, which is proved to be fatal for further operations (e.g., space electronics, medical devices). In addition to the exploration of the degradation of TSC property over time, a concurrent on-line testing architecture is offered that adjusts the input activity, addressing the absence of input values or the low frequency of their appearance (e.g., during sleep mode). During concurrent on-line testing, the inputs of the circuit under test (CUT) are, at the same time, its test vectors. This architecture tolerates possible degradation of the terms that contribute to the calculation of the totally self-checking goal (TSCG(t)) . An adaptive built-in self-test (BIST) unit is proposed that dynamically applies test vector subsets when permitted, based on the frequency of appearance of the input values. The clustering of the inputs is based on the k-means algorithm and, in combination with the ordering of the test vectors to minimize the subsets, results in partitioning the test procedure in a significantly shorter time. The comparison to other solutions used for concurrent on-line testing showed that the proposed adaptive BIST has significant advantages. It can cope with rare occurrences, or even no occurrence, of input values by enabling the BIST mechanism appropriately. The results showed that it may increase the TSCG(t) up to almost 90% when applied during a low-power mode and present better concurrent test latency (CTL) when assumptions regarding the availability of all input values and the probability of occurrence are not realistic.
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