Abstract
In our previous work, we proposed to use a vehicle network for data gathering, i.e. as an urban sensor. In this paper, we aim at understanding the theoretical limits of data gathering in a time slotted wireless network in terms of maximum service rate per node and end to end packet delivery ratio. The capacity of wireless networks has been widely studied and boundaries for that capacity expressed in Bachmann-Landau notation [ 1]. But these asymptotic limits do not clarify the numeric limits on data packets that can be carried by a wireless network. In this paper, we calculate the maximum data that each node can generate before saturating the network. The expected number of collision and its effect of the PDR% and service rate are investigated. The results quantify the trade off between packet delivery rate and service rate. Finally, we verify our analytical results by simulating the same scenario.

Abstract
For optimal control problems involving ordinary differential equations and functional inequality state constraints, the maximum principle may degenerate, producing no useful information about minimizers. This is known as the degeneracy phenomenon. Several non-degenerate forms of the maximum principle, valid under different constraint qualifications, have been proposed in the literature. In this paper we propose a new constraint qualification under which a nondegenerate maximum principle is validated. In contrast with existing results, our constraint qualification is of an integral type. An advantage of the proposed constraint qualification is that it is verified on a larger class of problems with nonsmooth data and convex velocity sets.

Abstract
The smart city is a sustainable and efficient urban center that provides high quality of life to its inhabitants with an optimal management of its resources, where clean and cost effective energy generation is a key issue. Under this setting, distributed generation can provide an adequate tool to deal with energy reliability and to successfully implement renewable sources; nevertheless, selection and scaling of energy systems, considering location, is not a trivial task. Frequently, the stakeholders analyze only one or two 'popular' generation systems, and then calculate the output and return of investment in a simplified and approximated approach. This practice could lead the stakeholder to an inadequate technology mix. To tackle this problem, this paper reviews and models most common energy sources for distributed generation in a smart city context. Then, a technical economic analysis is developed for 2 cases, a household and a district, considering not only renewable sources but also efficient non-renewable technologies. The results of the numerical analysis help to assess the more adequate generation systems for a given application, energetic demand, and geographical characteristics. A well-developed analysis is essential for a better understanding of the available technologies and their synergies; as a result, the investors can choose the appropriate solutions, maximizing overall benefits. © 2013 IEEE.

Abstract
This paper studies the Facility Layout Problem (FLP) of a first tier supplier in the automotive industry. This complex manufacturing system involves multiple facilities, complex products, and layout reconfiguration constraints. One of the key requirements of this particular system is the need for high levels of flexibility in the reconfiguration of the layouts. This problem is formulated as a mixed-integer programming (MIP), based on a FLP model with multiple objectives and unequal areas. The model allows for two reconfiguration types: small and large changes. We explore the application of optimization methodologies to produce efficient and flexible layouts.

Abstract
In our living, we often have a sense of being tired due to a mental or physical work, plus a feeling of performance degradation even in the accomplishment of simple tasks. However, these mental states are often not consciously felt or are ignored, an attitude that may result in human failures, errors and even in the occurrence of health problems or on a decrease in the quality of life. States of fatigue may be detected with a close monitoring of some indicators, such as productivity, performance or even the health states. In this work it is proposed a model and a prototype to detect and monitor fatigue based on some of these items. We focus specifically on mental fatigue, a key factor in an individual's performance. With this approach we aim to develop leisure and work context-aware environments that may improve the quality of life and the individual performance of any human being.

Abstract
There has been a longstanding interest in deriving conditions under which dynamic optimization problems are normal, that is, the necessary conditions of optimality (NCO) can be written with a nonzero multiplier associated with the objective function. This paper builds upon previous results on nondegenerate NCO for trajectory constrained optimal control problems to provide even stronger, normal forms of the conditions. The NCO developed may address problems with nonsmooth, less regular data. The particular case of calculus of variations problems is here explored to show a favorable comparison with existent results.