Design of an Agricultural Production Model for the Food Demand of the Mining Complex

The work＇s main purpose was to design and implement a model of agricultural production for the attention of food demand of the coal complex in the center of the department of Cesar, Colombia, by mounting Profitable Productive Units in rural areas of the zone with mining influence. The aforementioned rural communities are at a socioeconomic disadvantage concerning to the local economic development policies. It was taken a rural society with socio-economic conditions at a disadvantage, level 1 in the classification scale of 1 to 5 of Colombia, several associations were organized in each one of the affected municipalities with strong agricultural vocation to train them in profitable production strategies, authors performed technical and technological support for 12 months. In synthesis, there were meaningful differences among gross income per month of people who worked in the projects of the Young Rural Entrepreneurs, a fact confirmed by the P-value 0.00000005 （Prob. 〉 F） and the F-value 29.3, both denote the significance statistic for this case is best gross income per month of persons covered by the program, this implies that for a person of the rural community it is more meaningful economically linked to the SENA＇s Young Rural Entrepreneurs, in contrast to search for jobs in the informal sector, there is even an average value of 530.000 COP/month （about 265 US/month） higher than the statutory minimum wage for 2009, equivalent to 497.000 COP/month （about 245 US/month）.

Computational implementation of a GIS developed tool for prediction of dynamic ground movement and deformation due to underground extraction sequence

In the last century, there has been a significant development in the evaluation of methods to predict ground movement due to underground extraction. Some remarkable developments in three-dimensional computational methods have been supported in civil engineering, subsidence engineering and mining engineering practice. However, ground movement problem due to mining extraction sequence is effectively four dimensional （4D）. A rational prediction is getting more and more important for long-term underground mining planning. Hence, computer-based analytical methods that realistically simulate spatially distributed time-dependent ground movement process are needed for the reliable long-term underground mining planning to minimize the surface environmental damages. In this research, a new computational system is developed to simulate four-dimensional （4D） ground movement by combining a stochastic medium theory, Knothe time-delay model and geographic information system （GIS） technology. All the calculations are implemented by a computational program, in which the components of GIS are used to fulfill the spatial-temporal analysis model. In this paper a tight coupling strategy based on component object model of GIS technology is used to overcome the problems of complex three-dimensional extraction model and spatial data integration. Moreover, the implementation of computational of the interfaces of the developed tool is described. The GIS based developed tool is validated by two study cases. The developed computational tool and models are achieved within the GIS system so the effective and efficient calculation methodology can be obtained, so the simulation problems of 4D ground movement due to underground mining extraction sequence can be solved by implementation of the developed tool in GIS.

Fast Community Detection Based on Distance Dynamics

The distance dynamics model is excellent tool for uncovering the community structure of a complex network. However, one issue that must be addressed by this model is its very long computation time in large-scale networks. To identify the community structure of a large-scale network with high speed and high quality, in this paper, we propose a fast community detection algorithm, the F-Attractor, which is based on the distance dynamics model. The main contributions of the F-Attractor are as follows. First, we propose the use of two prejudgment rules from two different perspectives： node and edge. Based on these two rules, we develop a strategy of internal edge prejudgment for predicting the internal edges of the network. Internal edge prejudgment can reduce the number of edges and their neighbors that participate in the distance dynamics model. Second, we introduce a triangle distance to further enhance the speed of the interaction process in the distance dynamics model. This triangle distance uses two known distances to measure a third distance without any extra computation. We combine the above techniques to improve the distance dynamics model and then describe the community detection process of the F-Attractor. The results of an extensive series of experiments demonstrate that the F-Attractor offers high-speed community detection and high partition quality.