Development of a Bio-inspired GNS methodology in the dark environment

The current research explores the connection between gazing and locomotion of acoustic guided animals and the application of this in autonomous vehicles guidance and navigation strategies. Research groups worldwide are currently investigating different technologies and autonomous guidance algorithm-based strategies. The use of nature-inspired innovations ensures both the efficiency and the robustness of guidance strategies. The current research looks to fill the lack of research of those methodologies using bio-inspired techniques for acoustic guided animals as only visual-based methodologies have been implemented for a variety of tasks. Also, to connect the results from bat¿s flight experiments of Moss et al. with the Tau Theory of David Lee. The connection between the Tau Theory and flight dynamics and manoeuvring is another interesting topic not only for autonomous navigation but also for handling qualities and safety improvement. After carrying out a data analysis of Bat¿s flight experiments through the cluttering of the environment and connecting the flight behaviour with the extensive research done upon environmental cues perception guiding locomotion action for visual and acoustic cues. This concept is in an early phase of development and therefore, the aim is to set the baseline for further research on the topic. Results showed that bats perform a controlled braking manoeuvre when closing gaps, which is coined the term ¿Energised Approach¿. However, biased errors were found in some cases hence the results were negatively impacted, causing the results to be inaccurate in certain phases of the analysis. Despite the error found post-analysis, the results found in this research can still be considered insightful however artificial intelligence algorithms should be incorporated in future studies in order to achieve a more accurate result and finding.Outgoin

A study of the Mexican sugar industry and the impact of the new suspension agreement under different market structures

The aim of this thesis is to investigate the possibility of sugar industry collusion in Mexico, given government policy, and to assess the economic impact of the new trade restrictions on Mexican sugar exports under different market structures. Government ownership of sugar mills and other policies have led people to believe that there is collusion in the Mexican sugar market. For this reason, the author decided to test for market concentration and the impact of the new trade policy under different market structures. This thesis first examines the possibility of non-competitive behavior in the sugar industry in Mexico by testing for market integration and pass-through prices. A second analysis uses partial equilibrium models with different market structures, competitive and non-competitive exports. Time series estimation results support the hypothesis that Mexican sugar market is integrated with international and domestic markets, so these results do not support the hypothesis of collusion. However, evidence is mixed given the different estimates of price penetration among markets and the delays in adjustments to price shocks. Partial equilibrium models show that the effect of the agreement has stronger implications in prices if there is collusion among exporters, leading to larger impacts on sugarcane area, sugar production and consumption in Mexico if there is collusion relative to the competitive market case

Subset simulation for probabilistic computer models

Reliability analysis can be performed efficiently through subset simulation. Through Markov chain Monte Carlo, subset simulation progressively samples from the input domain of a performance function (typically a computer model) to find the failure domain, that is, the set of input configurations that result in an output higher than a prescribed threshold. Recently, a probabilistic framework for numerical analysis was proposed, whereby computation is treated as a statistical inference problem. The framework, called probabilistic numerics, treats the output of a computer code as a random variable. This paper presents a generalisation of subset simulation, which enables reliability analysis for probabilistic numerical models. The advantages and challenges of the method are discussed, and an example with industrial application is presented

Experimental Investigation and Gaussian Process Emulation of Steel Skeleton Reinforced Concrete Behaviors in Split Hopkinson Pressure Bar Tests

This paper conducts split Hopkinson pressure bar (SHPB) experiments to investigate the dynamic compressive properties of steel skeleton reinforced concrete (SSRC) materials. The SSRC specimens with the different volume fraction of steel range from 0 to 2.94% are investigated by conducting quasi-static and SHPB compression tests, respectively. In SHPB tests, the strain rate achieves from 30 s-1 to 100 s-1. The concrete matrix for all SSRC specimens is mixed to obtain a compressive strength of 45 MPa. The influences of different steel skeleton arrangements on the compressive strength, energy absorption, dynamic strain-stress relations, and failure modes are discussed and compared. The most important indicator, dynamic increase factor (DIF) relations of SSRC for compressive strength and Young’s modulus are modelled probabilistically using Gaussian process (GP) emulation under the Bayesian framework. The corresponding performances are validated by individual prediction errors (IPE) diagnostics. The experimental results demonstrate that by adding certain types of steel skeleton into plain concrete, which gives a general better bonding property to concrete materials and increases the capacities of dynamic compressive strength, dynamic resistance and energy absorption

Calculation of threshold Olsen P values for fertilizer response from soil properties

Phosphorus (P), a non-renewable resource, needs to be used more efficiently in agriculture. This requires using soil P tests. However, the P test threshold values for fertilizer response depend on many soil properties, some of which may be useful to estimate these threshold values, others not. Therefore, we searched here which soil properties are useful to estimate P threshold values. We calculated the threshold values for Olsen P and 0.01 M CaCl2 extractable P of 18 representative agricultural soils of the Mediterranean region of Spain. For that, we performed a P starvation experiment in which wheat and sunflower were alternatively pot-cropped. Results show that Olsen P threshold values are negatively correlated to P buffer capacity (r of −0.74, P lower than 0.001), clay content (−0.82, 0.001), pH (−0.76, 0.001), and Fe oxide content (−0.55, 0.05). Multiple regression models involving clay, pH or soil organic C, and phosphatase activity or organic hydrolysable P accounted for as much as 87 % of the variance in calculated Olsen P threshold values. In particular, there is a major effect of organic P on Olsen P threshold values. Single models based on routinely measured soil properties such as clay content and pH made accurate predictions of Olsen P threshold values with r 2 of 0.81 and P lower than 0.001