Competition for shortest paths on sparse graphs

Optimal paths connecting randomly selected network nodes and fixed routers are studied analytically in the presence of a nonlinear overlap cost that penalizes congestion. Routing becomes more difficult as the number of selected nodes increases and exhibits ergodicity breaking in the case of multiple routers. The ground state of such systems reveals nonmonotonic complex behaviors in average path length and algorithmic convergence, depending on the network topology, and densities of communicating nodes and routers. A distributed linearly scalable routing algorithm is also devised. © 2012 American Physical Society.

Shortest node-disjoint paths on random graphs

A localized method to distribute paths on random graphs is devised, aimed at finding the shortest paths between given source/destination pairs while avoiding path overlaps at nodes. We propose a method based on message-passing techniques to process global information and distribute paths optimally. Statistical properties such as scaling with system size and number of paths, average path-length and the transition to the frustrated regime are analyzed. The performance of the suggested algorithm is evaluated through a comparison against a greedy algorithm. © 2014 IOP Publishing Ltd and SISSA Medialab srl.

The temperature dependence of the electro-optic kerr effect in solutions

A novel Kerr cell of greater optical path length and temperature stability has been designed and built. The Kerr effect experimental has been substantially automated using an Apple IIe computer. Software has been written allowing the computer to partially control the Kerr effect equipment and to acquire and analyse the relevant data.The temperature dependent electro-optic Kerr effect of 2-methyl-4-nitroaniline, p-nitroaniline, nitrobenzene, aniline, and toluene as solutions in 1, 4-dioxane has been studied. The Kerr effect measurements combined with dipole moment, depolarisation ratio, dielectric, and electronic polarisation measurements have been used to calculate the first hyperpolarisability of the solute.Although first hyperpolarisabilities for the compounds studied have been measured in various physical states using a variety of experimental techniques, it is gratifying to find that the values presented in this thesis have a linear relationship with values reported by other workers.

Flow patterns on sieve trays

Studies into gas-liquid flow patterns were carried out on commercial scale sieve trays where the ratio of froth depth to flow path length is typical of that found in practice. Experiments were conducted on a 2.44 m diameter air-water distillation simulator, in which flow patterns were investigated by direct observation, using directional flow pointers; by water cooling, to simulate mass transfer; and by height of clear liquid measurements across the tray. The flow rates used are typical of those found in practice. The approach adopted was to investigate the effect of the gas flow on the liquid flow by comparing water only flow patterns across an unperforated tray with air-water flow patterns on perforated trays. Initial gas-liquid contacting experiments on the 6.35 mm hole tray showed that, under certain conditions, the gas flow pattern beneath the test tray can have a significant effect on the tray liquid flow pattern such that gas-driven liquid circulation was produced. This was found to be a function of this particular air-water simulator design, and as far as is known this is the first time that this phenomenon has been observed. Consequently non-uniform gas flow effects were removed by modification of the gas distribution system. By eliminating gas circulation effects, the effect of the gas flow on the separation of liquid flow was similar to that obtained on the 1.0 mm hole tray (Hine, 1990). That is, flow separation occurred at the ends of the inlet downcomer which produced large circulating zones along the tray segments both on the non-perforated and perforated trays. The air when forced through the liquid, inhibited circulating flow such that it only occurred at high water inlet velocities. With the 6.35 mm hole tray, the growth and velocity of circulating flow was reduced at high superficial air velocities, and in the experiments to simulate distillation, liquid was in forward flow over most of the tray.

Comparing transport emissions and impacts for energy recovery from domestic waste (EfW): centralised and distributed disposal options for two UK Counties

Many local authorities (LAs) are currently working to reduce both greenhouse gas emissions and the amount of municipal solid waste (MSW) sent to landfill. The recovery of energy from waste (EfW) can assist in meeting both of these objectives. The choice of an EfW policy combines spatial and non-spatial decisions which may be handled using Multi-Criteria Analysis (MCA) and Geographic Information Systems (GIS). This paper addresses the impact of transporting MSW to EfW facilities, analysed as part of a larger decision support system designed to make an overall policy assessment of centralised (large-scale) and distributed (local-scale) approaches. Custom-written ArcMap extensions are used to compare centralised versus distributed approaches, using shortest-path routing based on expected road speed. Results are intersected with 1-kilometre grids and census geographies for meaningful maps of cumulative impact. Case studies are described for two counties in the United Kingdom (UK); Cornwall and Warwickshire. For both case study areas, centralised scenarios generate more traffic, fuel costs and emitted carbon per tonne of MSW processed.

Strain and temperature sensitivity of a singlemode polymer optical fibre

We report experimental measurements of the strain and temperature sensitivity of the optical phase in a singlemode polymer optical fibre. These values were obtained by measuring optical path length change using a Mach-Zender interferometer.

Unfolding kernel embeddings of graphs:enhancing class separation through manifold learning

In this paper, we investigate the use of manifold learning techniques to enhance the separation properties of standard graph kernels. The idea stems from the observation that when we perform multidimensional scaling on the distance matrices extracted from the kernels, the resulting data tends to be clustered along a curve that wraps around the embedding space, a behavior that suggests that long range distances are not estimated accurately, resulting in an increased curvature of the embedding space. Hence, we propose to use a number of manifold learning techniques to compute a low-dimensional embedding of the graphs in an attempt to unfold the embedding manifold, and increase the class separation. We perform an extensive experimental evaluation on a number of standard graph datasets using the shortest-path (Borgwardt and Kriegel, 2005), graphlet (Shervashidze et al., 2009), random walk (Kashima et al., 2003) and Weisfeiler-Lehman (Shervashidze et al., 2011) kernels. We observe the most significant improvement in the case of the graphlet kernel, which fits with the observation that neglecting the locational information of the substructures leads to a stronger curvature of the embedding manifold. On the other hand, the Weisfeiler-Lehman kernel partially mitigates the locality problem by using the node labels information, and thus does not clearly benefit from the manifold learning. Interestingly, our experiments also show that the unfolding of the space seems to reduce the performance gap between the examined kernels.

Enabling long journeys in electric vehicles:design and demonstration of an infrastructure location model

This research develops a methodology and model formulation which suggests locations for rapid chargers to help assist infrastructure development and enable greater battery electric vehicle (BEV) usage. The model considers the likely travel patterns of BEVs and their subsequent charging demands across a large road network, where no prior candidate site information is required. Using a GIS-based methodology, polygons are constructed which represent the charging demand zones for particular routes across a real-world road network. The use of polygons allows the maximum number of charging combinations to be considered whilst limiting the input intensity needed for the model. Further polygons are added to represent deviation possibilities, meaning that placement of charge points away from the shortest path is possible, given a penalty function. A validation of the model is carried out by assessing the expected demand at current rapid charging locations and comparing to recorded empirical usage data. Results suggest that the developed model provides a good approximation to real world observations, and that for the provision of charging, location matters. The model is also implemented where no prior candidate site information is required. As such, locations are chosen based on the weighted overlay between several different routes where BEV journeys may be expected. In doing so many locations, or types of locations, could be compared against one another and then analysed in relation to siting practicalities, such as cost, land permission and infrastructure availability. Results show that efficient facility location, given numerous siting possibilities across a large road network can be achieved. Slight improvements to the standard greedy adding technique are made by adding combination weightings which aim to reward important long distance routes that require more than one charge to complete.

Effectively positioning water loss event in smart water networks

With the eye-catching advances in sensing technologies, smart water networks have been attracting immense research interest in recent years. One of the most overarching tasks in smart water network management is the reduction of water loss (such as leaks and bursts in a pipe network). In this paper, we propose an efficient scheme to position water loss event based on water network topology. The state-of-the-art approach to this problem, however, utilizes the limited topology information of the water network, that is, only one single shortest path between two sensor locations. Consequently, the accuracy of positioning water loss events is still less desirable. To resolve this problem, our scheme consists of two key ingredients: First, we design a novel graph topology-based measure, which can recursively quantify the "average distances" for all pairs of senor locations simultaneously in a water network. This measure will substantially improve the accuracy of our positioning strategy, by capturing the entire water network topology information between every two sensor locations, yet without any sacrifice of computational efficiency. Then, we devise an efficient search algorithm that combines the "average distances" with the difference in the arrival times of the pressure variations detected at sensor locations. The viable experimental evaluations on real-world test bed (WaterWiSe@SG) demonstrate that our proposed positioning scheme can identify water loss event more accurately than the best-known competitor.