In this talk I will describe the first sub-quadratic sampling algorithm for the Multiplicative Attribute Graph Model (MAGM, Kim and Leskove 2010). To design our algorithm, we first define a stochastic ball-dropping process (BDP). Although a special case of this process was introduced as an efficient approximate sampling algorithm for the Kronecker Product Graph Model (KPGM, Leskovec et al 2010)...

The modelling concept is well accepted in software engineering discipline. Some software models are built either to control the development stages, to measure program quality or to serve as a medium that gives better understanding of the actual software systems. Software process modelling nowadays has reached a level that allow software designs to be transformed into programming languages, such...

Classification is an important technology in data mining, while clonal selection algorithm (CSA) is a very effective classification method. Although CSA brings a new effective tool for solving complex problems, we can not completely say that it over-performs to other algorithms especially in the classification field. A main problem of CSA classifier is that it does not carry attribute imbalance...

Cognitive biases affect decision making in systems engineering (SE). Daniel Kahneman, 2002 Nobel laureate for his pioneering studies of cognitive biases in economic decision making, describes many disparate cognitive biases as abstractly belonging to one higher-level bias, that of attribute substitution. Attribute substitution occurs when an answer about a target attribute is unconscientiously ...

the subject of divine will is discussed in three views of imammieh, moatazeleh, and ashaereh scholars. in views of them, god has will, however, there are differences between their beliefs: is divine will a substance attribute or an attribute surplus to substance is divine will an ancient or created attribute is divine will an affirmative or privative attribute is divine will a real or unreal at...

Aiming at combining the good characteristics of a differential scale in representing human cognition and the favorable properties of interval judgments in expressing decision-makers’ uncertainty, this paper proposes the interval cognitive network process (I-CNP) to extend the primitive cognition network process (P-CNP) to handle interval judgments. The key points of I-CNP include a consistency ...