Dynamic simulation for closed loops in heating systems with decision-making support

Nowadays utilising the proper HVAC system is essential both in extreme weather conditions and dense buildings design. Hydraulic loops are the most common parts in all air conditioning systems. This article aims to investigate the performance of different hydraulic loop arrangements in variable flow systems. Technical, economic and environmental assessments have been considered in this process. A dynamic system simulation is generated to evaluate the system performance and an economic evaluation is conducted by whole life cost assessment. Moreover, environmental impacts have been studied by considering the whole life energy consumption, CO2 emission, the embodied energy and embodied CO2 of the system components. Finally, decision-making in choosing the most suitable hydraulic system among five well-known alternatives has been proposed.

Economic analysis of integrated weed management in field bean (Phaseolus vulgaris L.)

Field experiments were conducted in field bean in the north-eastern part of the Republic of Croatia to compare weed control and crop response under different management practices within the critical period of field bean production. The practices consisted in broadcast application of labelled rate of preemergence herbicide (PRE) and postemergence herbicide application: (POST) broadcast, band application over the rows, and band application combined with mechanical cultivation using of different herbicide doses recommended by the manufacturer (2x, 1x, 1/2x, 1/4x, 1/8x). In 1999, weed control with PRE application of pendimethalin was superior to POST bentazone application due to late emergence of weeds and lack of residual herbicide control. In 2000 bentazone combined with cycloxydim controlled weeds in field bean better than PRE herbicide application. Based on the results of this research, single PRE or POST application of herbicide did not control a broad spectrum of weeds and did not provide the commercially acceptable full season control. Reduced rates of herbicide are not advisable tinder high weed pressure.

Understanding lake and catchment history as a tool for integrated lake management

Sustainable lake management for nutrient-enriched lakes must be underpinned by an understanding of both the functioning of the lake, and the origins of changes in nutrient loading from the catchment. To date, limnologists have tended to focus on studying the impact of nutrient enrichment on the lake biota, and the dynamics of nutrient cycling between the water column, biota and sediments within the lake. Relatively less attention has been paid to understanding the specific origins of nutrient loading from the catchment and nutrient transport pathways linking the lake to its catchment. As such, when devising catchment management strategies to reduce nutrient loading on enriched lakes, assumptions have been made regarding the relative significance of non-point versus point sources in the catchment. These are not always supported by research conducted on catchment nutrient dynamics in other fields of freshwater science. Studies on nutrient enrichment in lakes need to take account of the history of catchment use and management specific to each lake in order to devise targeted and sustainable management strategies to reduce nutrient loading to enriched lakes. Here a modelling approach which allows quantification of the relative contribution of nutrients from each specific point and non-point catchment source over the course of catchment history is presented. The approach has been applied to three contrasting catchments in the U.K. for the period 1931 to present. These are the catchment of Slapton Ley in south Devon, the River Esk in Cumbria and the Deben Estuary in Suffolk. Each catchment showed marked variations in the nature and intensity of land use and management. The model output quantifies the relative importance of point source versus non-point livestock and land use sources in each of the catchments, and demonstrates the necessity for an understanding of site-specific catchment history in devising suitable management strategies for the reduction of nutrient loading on enriched lakes.

An approximate dynamic programming approach for improving accuracy of lossy data compression by Bloom filters

Bloom filters are a data structure for storing data in a compressed form. They offer excellent space and time efficiency at the cost of some loss of accuracy (so-called lossy compression). This work presents a yes-no Bloom filter, which as a data structure consisting of two parts: the yes-filter which is a standard Bloom filter and the no-filter which is another Bloom filter whose purpose is to represent those objects that were recognised incorrectly by the yes-filter (that is, to recognise the false positives of the yes-filter). By querying the no-filter after an object has been recognised by the yes-filter, we get a chance of rejecting it, which improves the accuracy of data recognition in comparison with the standard Bloom filter of the same total length. A further increase in accuracy is possible if one chooses objects to include in the no-filter so that the no-filter recognises as many as possible false positives but no true positives, thus producing the most accurate yes-no Bloom filter among all yes-no Bloom filters. This paper studies how optimization techniques can be used to maximize the number of false positives recognised by the no-filter, with the constraint being that it should recognise no true positives. To achieve this aim, an Integer Linear Program (ILP) is proposed for the optimal selection of false positives. In practice the problem size is normally large leading to intractable optimal solution. Considering the similarity of the ILP with the Multidimensional Knapsack Problem, an Approximate Dynamic Programming (ADP) model is developed making use of a reduced ILP for the value function approximation. Numerical results show the ADP model works best comparing with a number of heuristics as well as the CPLEX built-in solver (B&B), and this is what can be recommended for use in yes-no Bloom filters. In a wider context of the study of lossy compression algorithms, our researchis an example showing how the arsenal of optimization methods can be applied to improving the accuracy of compressed data.