Radiation guided along a cylindrical symmetry system according to the refractive index profile.

We aim at finding, from a purely theoretical analysis, the behavior that the refractive index should have within a cylindrical waveguide so that the radiation entering the system in a definite way is guided through it. Based on the criterion we have set in a previous article applying the Fermat's extremal principle in the framework of the geometrical optics, we depict the radiation confinement regions for refractive index profiles often used in the construction of waveguides, one step, multi-step and parabolic, by drawing upon the Legendre transform space as an intermediate resource in the process. We have also studied the possibility of performing the reverse path: for a wanted confinement region, to find the parameters defining the refractive index profile of the waveguide to be built. We conclude that such a process is possible as long as we know the shape of the profile. Under such restriction, our analysis allows us to deduce the characteristics that the guide should have so that the radiation entering with a given angle and at a certain distance from its axis remains confined. The technique can be used in design processes as a resource to limit the parameters that characterize the system.

Incidental news exposure via social media and political participation: Evidence of reciprocal effects

The aim of this study is to investigate the causal direction of the relationship between incidental news exposure via social media and political participation. Unlike prior studies, which have relied on cross-sectional data to examine this link, we used two panel data sets to better identify causal relationships. Specifically, we evaluate two unidirectional models (i.e. mobilization and reinforcement) and a reciprocal causal model using both cross-lagged and autoregressive path models. The findings reveal a more complex relationship than most previous studies have suggested. The relationship between incidental news exposure via social media and political participation appears to be reciprocal, with incidental news exposure and political participation indirectly influencing each other through social media use for political purposes. Furthermore, while the relationship between incidental news exposure and political participation is reciprocal, the participation-to-incidental news exposure path exerted a stronger effect than the reverse path in both studies.

Reverse Path Nearby Cluster (Rpnc) Query Optimization using Trajectory Clustering With Ensemble Learning (Tcel) In Spatial Networks

In spatial network, optimal path planning in real time is an open problem. For complex queries, Query optimization is intensively used. From given locations, most accessible locations can be found by Reverse Path nearby Cluster (R-PNC) query. This facility maximizes the commercial value. Distribution Clustering with Support Vector Machine is used to form a R-PNC clusters in the existing works. Trajectories with low positioning accuracy are used by this method. Trajectory Clustering with Ensemble Learning (TCEL) is proposed to overcome this problem. In this, Reverse Path nearby Cluster (R-PNC) query is used for effective path selection. Spatial datasets are handled using a two step process. Set of micro-clusters are maintained in the first step. Based on the input data, this micro clusters are continuously updated. Infinite data sources are compressed into a finite data set using Micro-clusters. More trajectory information can be stored using this finite dataset. In the second stage, ensemble learning is used to convert this micro-cluster into a macro-clusters of trajectories. Reverse the top k –RPNC. Based on their highest distribution they are stored and they are scanned to minimum from maximum. Improved Weight based Grey Wolf Optimization Algorithm (IWGWOA) is used to compute these values. The proposed system is implemented in MATLAB. The evaluation parameters like Normalized Mutual Information (NMI) and Rand Index (RI) are utilized for performance evaluation of proposed model.

Mobility Support in Vehicular Named-Data Networking

In this thesis, Vehicular Named-Data Networking (VNDN) refers tothe use of the Named-Data Networking communication model over VehicularAd-hoc Networks. With the aim of addressing the problems caused by mobility to efficiently support VNDN communications in highly mobile traffic scenarios, various contributions were proposed in the scope of this thesis. These contributions include a routing protocol, able to address VNDN problems such as broadcast storms and message redundancy, as well as solutions to enable content advertisements and for addressing the problems caused by reverse path partitioning, network partitioning, and source mobility. Finally, all the proposed solutions are integrated into a single framework called MobiVNDN. The evaluation results show that the proposed solutions are efficient and scalable, providing high VNDN application performance even in complex traffic scenarios.