Reduction of the size of datasets by using evolutionary feature selection: the case of noise in a modern city

Smart city initiatives have emerged to mitigate the negative effects of a very fast growth of urban areas. Most of the population in our cities are exposed to high levels of noise that generate discomfort and different health problems. These issues may be mitigated by applying different smart cities solutions, some of them require high accurate noise information to provide the best quality of serve possible. In this study, we have designed a machine learning approach based on genetic algorithms to analyze noise data captured in the university campus. This method reduces the amount of data required to classify the noise by addressing a feature selection optimization problem. The experimental results have shown that our approach improved the accuracy in 20% (achieving an accuracy of 87% with a reduction of up to 85% on the original dataset).Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. This research has been partially funded by the Spanish MINECO and FEDER projects TIN2016-81766-REDT (http://cirti.es), and TIN2017-88213-R (http://6city.lcc.uma.es)

Incorporating conceptual site models into national-scale environmental risk assessments for legacy waste in the coastal zone

Solid wastes deposited in the coastal zone that date from an era of lax environmental regulations continue to pose significant challenges for regulators and coastal managers worldwide. The increasing risk of contaminant release from these legacy disposal sites, due to a range of factors including rising sea levels, associated saline intrusion, and greater hydrological extremes, have been highlighted by many researchers. Given this widespread challenge, and the often-limited remedial funds available, there is a pressing need for the development of new advanced site prioritization protocols to limit potential pollution risks to sensitive ecological or human receptors. This paper presents a multi-criteria decision analysis that integrates the principles of Conceptual Site Models (Source-Pathway-Receptor) at a national scale in England and Wales to identify legacy waste sites where occurrence of pollutant linkages are most likely. A suite of spatial data has been integrated in order to score potential risks associated with waste type (Source), likelihood of pollutant release relating to current and future flood and erosion climate projections, alongside current management infrastructure (Pathway), and proximity to sensitive ecological features or proxies of human use in coastal areas (Receptors). Of the 30,281 legacy waste deposits identified in England and Wales, 3,219 were located within the coastal zone, with coastal areas containing a density of legacy wastes (by area) 10.5 times higher than inland areas. Of these, 669 were identified as priority sites in locations without existing coastal defences or flood management infrastructure, with 2550 sites identified in protected areas where contaminant transfer risks could still be apparent. The majority (63%) of the priority sites have either undefined source terms, or are classified as mixed wastes. Mining and industrial wastes were also notable waste categories, and displayed strong regional distributions in the former mining areas of north-east and south-west of England, south Wales, and post-industrial estuaries. The large-scale screening process presented here could be used by environmental managers as a foundation to direct more high-resolution site assessment and remedial work at priority sites, and can be used as a tool by governments for directing funding to problematic sites. List of Acronyms

Incorporating conceptual site models into national-scale environmental risk assessments for legacy waste in the coastal zone

Solid wastes deposited in the coastal zone that date from an era of lax environmental regulations continue to pose significant challenges for regulators and coastal managers worldwide. The increasing risk of contaminant release from these legacy disposal sites, due to a range of factors including rising sea levels, associated saline intrusion, and greater hydrological extremes, have been highlighted by many researchers. Given this widespread challenge, and the often-limited remedial funds available, there is a pressing need for the development of new advanced site prioritization protocols to limit potential pollution risks to sensitive ecological or human receptors. This paper presents a multi-criteria decision analysis that integrates the principles of Conceptual Site Models (Source-Pathway-Receptor) at a national scale in England and Wales to identify legacy waste sites where occurrence of pollutant linkages are most likely. A suite of spatial data has been integrated in order to score potential risks associated with waste type (Source), likelihood of pollutant release relating to current and future flood and erosion climate projections, alongside current management infrastructure (Pathway), and proximity to sensitive ecological features or proxies of human use in coastal areas (Receptors). Of the 30,281 legacy waste deposits identified in England and Wales, 3,219 were located within the coastal zone, with coastal areas containing a density of legacy wastes (by area) 10.5 times higher than inland areas. Of these, 669 were identified as priority sites in locations without existing coastal defences or flood management infrastructure, with 2550 sites identified in protected areas where contaminant transfer risks could still be apparent. The majority (63 %) of the priority sites have either undefined source terms, or are classified as mixed wastes. Mining and industrial wastes were also notable waste categories, and displayed strong regional distributions in the former mining areas of north-east and south-west of England, south Wales, and post-industrial estuaries. The large-scale screening process presented here could be used by environmental managers as a foundation to direct more high-resolution site assessment and remedial work at priority sites, and can be used as a tool by governments for directing funding to problematic sites

Royal Road Encodings and Schema Propagation in Selective Crossover

Recombination operators with high positional bias are less disruptive against adjacent genes. Therefore, it is ideal for the encoding to position epistatic genes adjacent to each other and aid GA search through genetic linkage. To produce an encoding that facilitates genetic linkage is problematic. This study focuses on selective crossover, which is an adaptive recombination operator. We propose three alternative encodings for the Royal Road problem. We use these encodings to analyse the performance of selective crossover with respect to different encodings. This study shows that the performance of selective crossover is consistent and is not affected by alternative encodings of a problem, unlike two-point crossover. The encodings are also used to understand the behaviour of selective crossover in terms of schema propagation. Experimental results indicate that selective crossover provides a better balance between exploration and exploitation than conventional recombination operators. ..

Improving the Performance of Challenged Networks with Controlled Mobility

International audienceIn this work, we investigate the application of an adapted controlled mobility strategy on self-propelling nodes, which could efficiently provide network resource to users scattered on a designated area. We design a virtual force-based controlled mobility scheme, named VFPc, and evaluate its ability to be jointly used with a dual packet-forwarding and epidemic routing protocol. In particular, we study the possibility for end-users to achieve synchronous communications at given times of the considered scenarios. On this basis, we study the delay distribution for such user traffic and show the advantages of VFPc compared to other packet-forwarding and packet-replication schemes, and highlight that VFPc-enabled applications could take benefit of both schemes to yield a better user experience, despite challenging network conditions

TCC Power Point Presentation : Animation Principles Flash Module

Power Point PresentationThis Presentation was delivered as part of th TCC Online Conference 2010. It is in Power Point format. The presentation is the cullmination of an istructional design project to teach animation principles using an interactive Flash module