The Comparison of Some Soil Quality Indexes in Different Land uses of Ghareh Aghaj Watershed of Semirom, Isfahan, Iran

Land use change, if not based on proper scientific investigation affects other physical, chemical, and biological properties of soil and leading to increased destruction and erosion. It was imperative to study the effects of changing rangelands to farmlands on some Soil quality indexes. Undisturbed soil samples were collected from the depths of 0-10 and 10-30 centimeter in pasture with good vegetation cover(GP), pasture with medium vegetation cover(MP), abandoned dry land farming(ADF) and degraded dry land farming(DDF) land uses in Ghareh Aghaj watershed of Isfahan province. The results revealed that organic matter(OM), cation exchange capacity(CEC) and available potassium(AK) decreasing in the depth of 0-10 centimeter were 66.6, 38.8 and 70 percent and in the depth of 10-30 centimeter were 58, 61.4 and 83.5 percent respectively in DDF comparison with GP. Concerning to the results, it seems that land use change can decrease soil quality and increase soil degradation and lead in undesirable consequences.

Evaluating Refactoring with a Quality Index

The aim of every software product is to achieve an appropriate level of software quality. Developers and designers are trying to produce readable, reliable, maintainable, reusable and testable code. To help achieve these goals, several approaches have been utilized. In this paper, refactoring technique was used to evaluate software quality with a quality index. It is composed of different metric sets which describes various quality aspects.

A Similarity Metric for Assessment of Image Fusion Algorithms

In this paper, we present a novel objective nonreference performance assessment algorithm for image fusion. It takes into account local measurements to estimate how well the important information in the source images is represented by the fused image. The metric is based on the Universal Image Quality Index and uses the similarity between blocks of pixels in the input images and the fused image as the weighting factors for the metrics. Experimental results confirm that the values of the proposed metrics correlate well with the subjective quality of the fused images, giving a significant improvement over standard measures based on mean squared error and mutual information.