University of Bedfordshire

About: University of Bedfordshire is a education organization based out in Luton, Bedford, United Kingdom. It is known for research contribution in the topics: Population & Social work. The organization has 3860 authors who have published 6079 publications receiving 143448 citations. The organization is also known as: University of Luton.

Mapping Potential Crop Management Zones within Fields: Use of Yield-map Series and Patterns of Soil Physical Properties Identified by Electromagnetic Induction Sensing

Abstract: Investment in precision farming technologies can be expensive and is not expected to be cost-effective for every farm. Previous research and farm experience has shown that the amount of soil variability across a farm and within a field is of key importance for determining potential benefits from the adoption of precision farming. The research reported here evaluates the analysis of yield map sequences and electromagnetic induction (EMI) soil sensing as potentially cost-effective methods for identifying and mapping soil-determined “management zones” within fields. Both methods are shown to provide useful information for the provisional delineation of soil type boundaries and crop management zones, though soil examination in the field is still necessary to confirm specific soil characteristics.

Cyclic volatile methylsiloxane bioaccumulation in flounder and ragworm in the Humber Estuary.

Abstract: Cyclic volatile methylsiloxanes are being subjected to regulatory scrutiny as possible PET chemicals. The investigation of bioaccumulation has yielded apparently contradictory results, with high la ...

Dynamic genetic algorithms for the dynamic load balanced clustering problem in mobile ad hoc networks

Abstract: Clustering can help aggregate the topology information and reduce the size of routing tables in a mobile ad hoc network (MANET). To achieve fairness and uniform energy consumption, each clusterhead should ideally support the same number of clustermembers. However, a MANET is a dynamic and complex system and its one important characteristic is the topology dynamics, that is, the network topology changes over time due to the factors such as energy conservation and node movement. Therefore, in a MANET, an effective clustering algorithm should efficiently adapt to each topology change and produce the new load balanced clusterhead set quickly. The maintenance of the cluster structure should aim to keep it as stable as possible to reduce overhead. To meet this requirement, the new solution should keep as many good parts in the previous solution as possible. In this paper, we first formulate the dynamic load balanced clustering problem (DLBCP) into a dynamic optimization problem. Then, we propose to use a series of dynamic genetic algorithms (GAs) to solve the DLBCP in MANETs. In these dynamic GAs, each individual represents a feasible clustering structure and its fitness is evaluated based on the load balance metric. Various dynamics handling techniques are introduced to help the population to deal with the topology changes and produce closely related solutions in good quality. The experimental results show that these GAs can work well for the DLBCP and outperform traditional GAs that do not consider dynamic network optimization requirements.

Developments in bioassay methods for toxicity testing in water treatment

Abstract: The presence of toxic substances in water and water treatment plants is a major environmental problem. Numerous test methods have been developed to assess the effect of chemical pollutants on the e ...