In recent years, social networks have surged in popularity as one of the main applications of the Internet. This has generated great interest in researching these networks by various fields in the scientific community. One key aspect of social network research is identifying important missing information which is not explicitly represented in the network, or is not visible to all. To date, this...

Theories of information that attempt to sort out problems concerning the status and effi cacy of its content – as it is understood in thoughts, meanings, signs, intended actions, and so forth – have so far failed to resolve a crucial dilemma: how what is represented could possibly have physical consequences. The legacy of this has been played out in various skeptical paradigms that either concl...

We present a method for the evaluation of the interaction potential of an equilibrium classical system starting from the (partial) knowledge of its structure factor. The procedure is divided into two phases, both of which are based on the maximum entropy principle of information theory. First we determine the maximum entropy estimate of the radial distribution function constrained by the inform...

The classical uncertainty principle of harmonic analysis states that a nontrivial function and its Fourier transform cannot both be sharply localized. It plays an important role in signal processing and physics. This paper generalizes the uncertainty principle for measurable sets from complex domain to hypercomplex domain using quaternion algebras, associated with the Quaternion Fourier transfo...

Context information other than faces, such as clothes, picturetaken-time and some logical constraints, can provide rich cues for recognizing people. This aim of this work is to automatically cluster pictures according to person’s identity by exploiting as much context information as possible in addition to faces. Toward that end, a clothes recognition algorithm is first developed, which uses co...