Using accelerometer, high sample rate GPS and magnetometer data to develop a cattle movement and behaviour model

The study described in this paper developed a model of animal movement, which explicitly recognised each individual as the central unit of measure. The model was developed by learning from a real dataset that measured and calculated, for individual cows in a herd, their linear and angular positions and directional and angular speeds. Two learning algorithms were implemented: a Hidden Markov model (HMM) and a long-term prediction algorithm. It is shown that a HMM can be used to describe the animal's movement and state transition behaviour within several “stay” areas where cows remained for long periods. Model parameters were estimated for hidden behaviour states such as relocating, foraging and bedding. For cows’ movement between the “stay” areas a long-term prediction algorithm was implemented. By combining these two algorithms it was possible to develop a successful model, which achieved similar results to the animal behaviour data collected. This modelling methodology could easily be applied to interactions of other animal specie

A Co-evolutionary Algorithm-based Enhanced Grey Wolf Optimizer for the Routing of Wireless Sensor Networks

Wireless networks are frequently installed in arduous environments, heightening the importance of their consistent operation. To achieve this, effective strategies must be implemented to extend the lifespan of nodes. Energy-conserving routing protocols have emerged as the most prevalent methodology, as they strive to elongate the network\u27s lifetime while guaranteeing reliable data routing with minimal latency. In this paper, a plethora of studies have been done with the purpose of improving network routing, such as the integration of clustering techniques, heterogeneity, and swarm intelligence-inspired approaches. A comparative investigation was conducted on a variety of swarm-based protocols, including a new coevolutionary binary grey wolf optimizer (Co-BGWO), a BGWO, a binary whale optimization, and a binary Salp swarm algorithm. The objective was to optimize cluster heads (CHs) positions and their number during the initial stage of both two-level and three-level heterogeneous networks. The study concluded that these newly developed protocols are more reliable, stable, and energy-efficient than the standard SEP and EDEEC heterogeneous protocols. Specifically, in 150 m2 area of interest, the Co-BGWO and BGWO protocols of two levels were found the most efficient, with over than 33% increase in remaining energy percentage compared to SEP, and over 24% more than EDEEC in three-level networks

bifurcation analysis of a delayed worm propagation model with saturated incidence

This paper is concerned with a delayed SVEIR worm propagation model with saturated incidence. The main objective is to investigate the effect of the time delay on the model. Sufficient conditions for local stability of the positive equilibrium and existence of a Hopf bifurcation are obtained by choosing the time delay as the bifurcation parameter. Particularly, explicit formulas determining direction of the Hopf bifurcation and stability of the bifurcating periodic solutions are derived by using the normal form theory and the center manifold theorem. Numerical simulations for a set of parameter values are carried out to illustrate the analytical results

An information diffusion model in social networks with carrier compartment and delay

With the wide applications of the communication networks, the topic of information networks security is getting more and more attention from governments and individuals. This paper is devoted to investigating a malware propagation model with carrier compartment and delay to describe the process of malware propagation in mobile wireless sensor networks. Based on matrix theory for characteristic values, the local stability criterion of equilibrium points is established. Applying the linear approximation method of nonlinear systems, we study the existence of Hopf bifurcation at the equilibrium points. At the same time, we identify some sensitive parameters in the process of malware propagation. Finally, numerical simulations are performed to illustrate the theoretical results