Urban and extra-urban hybrid vehicles: a technological review

Pollution derived from transportation systems is a worldwide, timelier issue than ever. The abatement actions of harmful substances in the air are on the agenda and they are necessary today to safeguard our welfare and that of the planet. Environmental pollution in large cities is approximately 20% due to the transportation system. In addition, private traffic contributes greatly to city pollution. Further, “vehicle operating life” is most often exceeded and vehicle emissions do not comply with European antipollution standards. It becomes mandatory to find a solution that respects the environment and, realize an appropriate transportation service to the customers. New technologies related to hybrid –electric engines are making great strides in reducing emissions, and the funds allocated by public authorities should be addressed. In addition, the use (implementation) of new technologies is also convenient from an economic point of view. In fact, by implementing the use of hybrid vehicles, fuel consumption can be reduced. The different hybrid configurations presented refer to such a series architecture, developed by the researchers and Research and Development groups. Regarding energy flows, different strategy logic or vehicle management units have been illustrated. Various configurations and vehicles were studied by simulating different driving cycles, both European approval and homologation and customer ones (typically municipal and university). The simulations have provided guidance on the optimal proposed configuration and information on the component to be used

A survey of machine learning techniques applied to self organizing cellular networks

In this paper, a survey of the literature of the past fifteen years involving Machine Learning (ML) algorithms applied to self organizing cellular networks is performed. In order for future networks to overcome the current limitations and address the issues of current cellular systems, it is clear that more intelligence needs to be deployed, so that a fully autonomous and flexible network can be enabled. This paper focuses on the learning perspective of Self Organizing Networks (SON) solutions and provides, not only an overview of the most common ML techniques encountered in cellular networks, but also manages to classify each paper in terms of its learning solution, while also giving some examples. The authors also classify each paper in terms of its self-organizing use-case and discuss how each proposed solution performed. In addition, a comparison between the most commonly found ML algorithms in terms of certain SON metrics is performed and general guidelines on when to choose each ML algorithm for each SON function are proposed. Lastly, this work also provides future research directions and new paradigms that the use of more robust and intelligent algorithms, together with data gathered by operators, can bring to the cellular networks domain and fully enable the concept of SON in the near future

The wicked and complex in education: developing a transdisciplinary perspective for policy formulation, implementation and professional practice

The concept of 'wicked issues', originally developed in the field of urban planning, has been taken up by design educators, architects and public health academics where the means for handling 'wicked issues' has been developed through 'reflective practice'. In the education of teachers, whilst reflective practice has been a significant feature of professional education, the problems to which this has been applied are principally 'tame' ones. In this paper, the authors argue that there has been a lack of crossover between two parallel literatures. The literature on 'wicked issues' does not fully recognise the difficulties with reflective practice and that in education which extols reflective practice, is not aware of the 'wicked' nature of the problems which confront teachers and schools. The paper argues for a fresh understanding of the underlying nature of problems in education so that more appropriate approaches can be devised for their resolution. This is particularly important at a time when the government in England is planning to make teaching a masters level profession, briefly defined by the Quality Assurance Agency for Higher Education (QAA) benchmark statement as 'Decision-making in complex and unpredictable situations'. The paper begins by locating the argument and analysis of 'wicked problems' within the nature of social complexity and chaos. The second part of the paper explores implications for those involved in policy formation, implementation and service provision. Given the range of stakeholders in education, the paper argues for a trans-disciplinary approach recognising the multiple perspectives and methodologies leading to the acquisition of reticulist skills and knowledge necessary to boundary cross. © 2009 Taylor & Francis

How to Attract the Right Economic Activities in a Certain Spatial Environment?

During the past few years, our research has examined and described the spatial patterns and organisation of economic activities. In order to link these findings to policy, we introduced the concepts of demand and supply segments, and applied them on the scale of an area or a certain spatial environment. Considering the business needs of companies on a certain location, we identified 16 demand parameters of companies, that are spatially relevant on the scale of an area: the size of good flows, the alternative freight transport, the nearness to the market,... Literature, interviews and observations offer supporting evidence for the parameters. We linked them to 24 other parameters that reflect the characteristics of the area where a company is located. These include amongst others mobility, level of foot fall, the presence of green infrastructure, other companies (or mix of companies), density, parking possibilities,... The combination of this information with our typology of economic area’s (Giaretta, Pennincx, De Mulder, Zaman, 2019) resulted into 24 main segments, that show the relation between demand of companies and supply of spatial characteristics on the scale of an area. The segments are ideally grouped according to the characteristics, and in this sense they differ from typology of economic areas, that is based on the observed location preferences of companies. This way of grouping into segments generates new questions, that enable us to spatially differentiate economic environments, and to make decisions regarding the location of economic activities. We aim at getting concrete answers to three main questions: (1) Is my company located in the right place? Does this area spatially deliver what my company needs? (2) Does the area deliver the right services, that the companies in this area need? (3) If we want to transform an area, which area characteristics do we need to change in order to attract the wanted companies? We subdivide these three main questions into sub questions. The first question considers the demand side and uses the micro-economic considerations, made by a company, in order to choice a certain segment. Several questions succeed each other and deal with the demand of companies regarding the effects of agglomeration, economic and environmental spatial use, freight transport, price per square meter,... The second question can lead to the segment that is the closest to the actual situation, based on the typology of economic areas. Indeed, there is usually a gap between the actual situation and the best fitting segment. Using the typology and the segments on an actual situation uncovers information about visibility, land price value, good flows, land use plan. The third and last question deals with areas that are in a process of transformation. After finding out the desirable segment, it is possible to evaluate which companies belong to this segment, which need to adapt or to disappear. In addition, the transition in terms of services that the area delivers (which is implied when transforming from one segment to another), can be determined

Simplified Energy Landscape for Modularity Using Total Variation

Networks capture pairwise interactions between entities and are frequently used in applications such as social networks, food networks, and protein interaction networks, to name a few. Communities, cohesive groups of nodes, often form in these applications, and identifying them gives insight into the overall organization of the network. One common quality function used to identify community structure is modularity. In Hu et al. [SIAM J. App. Math., 73(6), 2013], it was shown that modularity optimization is equivalent to minimizing a particular nonconvex total variation (TV) based functional over a discrete domain. They solve this problem, assuming the number of communities is known, using a Merriman, Bence, Osher (MBO) scheme. We show that modularity optimization is equivalent to minimizing a convex TV-based functional over a discrete domain, again, assuming the number of communities is known. Furthermore, we show that modularity has no convex relaxation satisfying certain natural conditions. We therefore, find a manageable non-convex approximation using a Ginzburg Landau functional, which provably converges to the correct energy in the limit of a certain parameter. We then derive an MBO algorithm with fewer hand-tuned parameters than in Hu et al. and which is 7 times faster at solving the associated diffusion equation due to the fact that the underlying discretization is unconditionally stable. Our numerical tests include a hyperspectral video whose associated graph has 2.9x10^7 edges, which is roughly 37 times larger than was handled in the paper of Hu et al.Comment: 25 pages, 3 figures, 3 tables, submitted to SIAM J. App. Mat