In complex networks such as computer and information networks, social networks or biological networks a community structure is a common and important property. Community detection in complex networks has attracted a lot of attention in recent years. Community detection is the problem of finding closely related groups within a network. Modularity optimisation is a widely accepted method for community detection. It has been shown that the modularity optimisation has a resolution limit because it is unable to detect communities with sizes smaller than a certain number of vertices defined with network size. In this paper we propose a metric for describing community structures that enables community detection better than other metrics. We present a fast local expansion algorithm for community detection. The proposed algorithm provides online multiresolution community detection from a source vertex. Experimental results show that the proposed algorithm is efficient in both real-world and synthetic networks.
COBISS.SI-ID: 20912904
The forest soil can act as an important sink for CO2 and in that respect also appears in the national Kyoto reports, where a distinction is made between carbon accumulated in litter and organic soil horizons and carbon accumulated in mineral soil layers. There is a multitude of dynamic models of Corg change in the soil particularly due to different environmental and anthropogenic factors. The purpose of this paper is the Yasso07 model application on the “Brdo” plot, which is part of the ICP Forest Level II plots of Slovenia. The Yasso07 model describes the decomposition of organic matter in the forest soil by dividing litter inputs into different components with varying decomposition rates. Here, the temporal change of soil Corg in various scenarios of future climate change (increase in air temperature, change in precipitation) was predicted. The difference between the measured amount and the model-predicted amount of Corg in the soil for the current climate on the Brdo plot is 6.4 tC/ha (88.6 tC/ha measured vs. 95.0 tC/ha predicted). Taking into consideration the climate change scenarios for Slovenia, Corg stock is expected to decrease in the future according to Yasso07 projections in all scenarios of climate change. The estimate of 100-year decrease of Corg is the largest for scenario, when large increase of both temperature and precipitation is expected (18.2%) and smallest when small temperature increase and precipitation decrease are predicted (9.3%). Assuming stable litter input, larger influence on Corg decrease was predicted for the temperature change compared to precipitation change. However, many uncertainties are included in model estimates ranging from litter input estimates, climate change uncertainties, climate-litter production feedbacks, starting value estimates, etc. The determination of the uncertainty of model calculations is a requirement for conducting simulations and their interpretation.
COBISS.SI-ID: 3918246