Two-layer particle filter for multiple target detection and tracking

This paper deals with the detection and tracking of an unknown number of targets using a Bayesian hierarchical model with target labels. To approximate the posterior probability density function, we develop a two-layer particle filter. One deals with track initiation, and the other with track maintenance. In addition, the parallel partition method is proposed to sample the states of the surviving targets.

Emissions and economic costs of cycling compact fluorescent lamps with integrated ballasts

This paper proposes a way to quantify the emissions of mercury (Hg) and CO2 associated with the manufacture and operation of compact fluorescent lamps with integrated ballasts (CFLis), as well as the economic cost of using them under different operating cycles. The main purpose of this paper is to find simple criteria for reducing the polluting emissions under consideration and the economic cost of CFLi to a minimum. A lifetime model is proposed that allows the emissions and costs to be described as a function of degradation from turning CFLi on and their continuous operation. An idealized model of a CFLi is defined that combines characteristics stated by different manufacturers. In addition, two CFLi models representing poor-quality products are analyzed. It was found that the emissions and costs per unit of time of operation of the CFLi depend linearly on the number of times per unit of time it is turned on and the time of continuous operation. The optimal conditions (lowest emissions and costs) depend on the place of manufacture, the place of operation and the quality of the components of the lamp/ballast. Finally, it was also found that for each lamp, there are intervals when it is turned off during which emissions of pollutants and costs are identical regardless of how often the lamp is turned on or the time it remains on. For CO2 emissions, the lamp must be off up to 5 minutes; for the cost, up to 7 minutes and for Hg emissions, up to 43 minutes. It is advisable not to turn on a CFLi sooner than 43 minutes from the last time it was turned off.

Development of a methodology and tool to evaluate the impact of ICT measures on road transport emissions

The paper presents the main elements of a project entitled ICT-Emissions that aims at developing a novel methodology to evaluate the impact of ICT-related measures on mobility, vehicle energy consumption and CO2 emissions of vehicle fleets at the local scale, in order to promote the wider application of the most appropriate ICT measures. The proposed methodology combines traffic and emission modelling at micro and macro scales. These will be linked with interfaces and submodules which will be specifically designed and developed. A number of sources are available to the consortium to obtain the necessary input data. Also, experimental campaigns are offered to fill in gaps of information in traffic and emission patterns. The application of the methodology will be demonstrated using commercially available software. However, the methodology is developed in such a way as to enable its implementation by a variety of emission and traffic models. Particular emphasis is given to (a) the correct estimation of driver behaviour, as a result of traffic-related ICT measures, (b) the coverage of a large number of current vehicle technologies, including ICT systems, and (c) near future technologies such as hybrid, plug-in hybrids, and electric vehicles. The innovative combination of traffic, driver, and emission models produces a versatile toolbox that can simulate the impact on energy and CO2 of infrastructure measures (traffic management, dynamic traffic signs, etc.), driver assistance systems and ecosolutions (speed/cruise control, start/stop systems, etc.) or a combination of measures (cooperative systems).The methodology is validated by application in the Turin area and its capacity is further demonstrated by application in real world conditions in Madrid and Rome.

Ranking factors affecting emissions of GHG from incubated agricultural soils

Agriculture significantly contributes to global greenhouse gas (GHG) missions and there is a need to develop effective mitigation strategies. The efficacy of methods to reduce GHG fluxes from agricultural soils can be affected by a range of interacting management and environmental factors. Uniquely, we used the Taguchi experimental design methodology to rank the relative importance of six factors known to affect the emission of GHG from soil: nitrate (NO3?) addition, carbon quality (labile and non-labile C), soil temperature, water-filled pore space (WFPS) and extent of soil compaction. Grassland soil was incubated in jars where selected factors, considered at two or three amounts within the experimental range, were combined in an orthogonal array to determine the importance and interactions between factors with a L16 design, comprising 16 experimental units. Within this L16 design, 216 combinations of the full factorial experimental design were represented. Headspace nitrous oxide (N2O), methane (CH4) and carbon dioxide (CO2) concentrations were measured and used to calculate fluxes. Results found for the relative influence of factors (WFPS and NO3? addition were the main factors affecting N2O fluxes, whilst glucose, NO3? and soil temperature were the main factors affecting CO2 and CH4 fluxes) were consistent with those already well documented. Interactions between factors were also studied and results showed that factors with Little individual influence became more influential in combination. The proposed methodology offers new possibilities for GHG researchers to study interactions between influential factors and address the optimized sets of conditions to reduce GHG emissions in agro-ecosystems, while reducing the number of experimental units required compared with conventional experimental procedures that adjust one variable at a time.