Herding is the process of bringing individuals (e.g. animals) together into a group. More specifically, we consider self– organized herding as the process of moving a set of individuals to a given number of locations (cluster centers) without any external control. We formally describe the relation between herding and clustering and show that any clustering model can be used to control herding p...

The extensive use of Internet Things (IoT) appliances has greatly contributed in the growth smart cities. Moreover, city deploys IoT-enabled applications, communications, and technologies to improve quality life, people’s wellbeing, services for service providers increase operational efficiency. Nevertheless, expansion network become utmost hazard due increased cyber security attacks threats. C...

Abstract: In order to solve the cooperation of autonomous agent systems,an artificial immune network cooperation algorithm is proposed,which is based on Jerne’s idiotypic immune network hypothesis. A sheepdog herding problem is taken as an example. The relative position information of dogs with the sheep and sheep pen is taken as an antigen. Dogs’ action is taken as an antibody. We calculate an...

Windows Vista Enterprise and Ultimate editions use Bitlocker Drive Encryption as its disk encryption algorithm, and at its heart is the AES-CBC + Elephant diffuser encryption algorithm (ELEPHANT). In this paper we present our analysis of ELEPHANT using statistical tests. Our analysis has explored some weaknesses in its diffusers, thus we propose new diffusers to replace them. The new diffusers ...

In recent years, Wireless Sensor Networks (WSNs) have received increased international attention due to advancements in the communication, electronics, and information fields. These sensor networks integrate a huge number of nodes track rapidly changing physical events. The key improvement is that these can be easily positioned any environment their small size. Therefore, maintaining network co...

Recently, the Frank-Wolfe optimization algorithm was suggested as a procedure to obtain adaptive quadrature rules for integrals of functions in a reproducing kernel Hilbert space (RKHS) with a potentially faster rate of convergence than Monte Carlo integration (and “kernel herding” was shown to be a special case of this procedure). In this paper, we propose to replace the random sampling step i...

We study the usefulness of conditional gradient like methods for determining projections onto convex sets, in particular, projections onto naturally arising convex sets in reproducing kernel Hilbert spaces. Our work is motivated by the recently introduced kernel herding algorithm which is closely related to the Conditional Gradient Method (CGM). It is known that the herding algorithm converges ...

This paper aims to study the effect of herding on buy and hold, momentum and contrarian strategy. In this research, the cross-sectional absolute deviation is used to identify herding behavior in twenty industries in Tehran stock market. It is observed that the down and boom periods had more industries with herding. Moreover, the weak herding is more common than the strong herding in this market...

We show that the algorithm to extract diverse M -solutions from a Conditional Random Field (called divMbest [1]) takes exactly the form of a Herding procedure [2], i.e. a deterministic dynamical system that produces a sequence of hypotheses that respect a set of observed moment constraints. This generalization enables us to invoke properties of Herding that show that divMbest enforces implausib...