Fractional Super-Resolution of Voxelized Point Clouds

<div>We present a method to super-resolve voxelized point clouds down-sampled by a fractional factor, using look-up-tables (LUT) constructed from self-similarities from its own down-sampled neighborhoods. Given a down-sampled point cloud geometry Vd, and its corresponding fractional down-sampling factor s, the proposed method determines the set of positions that may have generated Vd, and estimates which of these positions were indeed occupied (super-resolution). Assuming that the geometry of a point cloud is approximately self-similar at different scales, LUTs relating down-sampled neighborhood configurations with children occupancy configurations can be estimated by further down-sampling the input point cloud to Vd2 , and by taking into account the irregular children distribution derived from fractional down-sampling. For completeness, we also interpolate texture by averaging colors from adjacent neighbors. We present extensive test results over different point clouds, showing the effectiveness of the proposed method against baseline methods.</div>

Fractional Super-Resolution of Voxelized Point Clouds

<div>We present a method to super-resolve voxelized point clouds down-sampled by a fractional factor, using look-up-tables (LUT) constructed from self-similarities from its own down-sampled neighborhoods. Given a down-sampled point cloud geometry Vd, and its corresponding fractional down-sampling factor s, the proposed method determines the set of positions that may have generated Vd, and estimates which of these positions were indeed occupied (super-resolution). Assuming that the geometry of a point cloud is approximately self-similar at different scales, LUTs relating down-sampled neighborhood configurations with children occupancy configurations can be estimated by further down-sampling the input point cloud to Vd2 , and by taking into account the irregular children distribution derived from fractional down-sampling. For completeness, we also interpolate texture by averaging colors from adjacent neighbors. We present extensive test results over different point clouds, showing the effectiveness of the proposed method against baseline methods.</div>

Design of an enhanced fractional order PID controller for a class of second-order system

Purpose This paper aims to design a modified fractional order proportional integral derivative (PID) (FO[PI]λDµ) controller based on the principle of fractional calculus and investigate its performance for a class of a second-order plant model under different operating conditions. The effectiveness of the proposed controller is compared with the classical controllers. Design/methodology/approach The fractional factor related to the integral term of the standard FO[PI]λDµ controller is applied as a common fractional factor term for the proportional plus integral coefficients in the proposed controller structure. The controller design is developed using the regular closed-loop system design specifications such as gain crossover frequency, phase margin, robustness to gain change and two more specifications, namely, noise reduction and disturbance elimination functions. Findings The study results of the designed controller using matrix laboratory software are analyzed and compared with an integer order PID and a classical FOPIλDµ controller, the proposed FO[PI]λDµ controller exhibit a high degree of performance in terms of settling time, fast response and no overshoot. Originality/value This paper proposes a methodology for the FO[PI]λDµ controller design for a second-order plant model using the closed-loop system design specifications. The effectiveness of the proposed control scheme is demonstrated under different operating conditions such as external load disturbances and input parameter change.

Analysis of fractional factor system for data transmission in SDN

In software definition networks, we allow transmission paths to be selected based on real-time data traffic monitoring to avoid congested channels. Correspondingly, this motivates us to study the existence of fractional factors in different settings. In this paper, we present several extend sufficient conditions for a graph admits ID-Hamiltonian fractional (g, f )factor. These results improve the conclusions originally published in the study by Gong et al. [2].

Neighborhood condition for all fractional (g, f, n′, m)-critical deleted graphs

In data transmission networks, the availability of data transmission is equivalent to the existence of the fractional factor of the corresponding graph which is generated by the network. Research on the existence of fractional factors under specific network structures can help scientists design and construct networks with high data transmission rates. A graph G is named as an all fractional (g, f, n′, m)-critical deleted graph if the remaining subgraph keeps being an all fractional (g, f, m)-critical graph, despite experiencing the removal of arbitrary n′ vertices of G. In this paper, we study the relationship between neighborhood conditions and a graph to be all fractional (g, f, n′, m)-critical deleted. Two sufficient neighborhood conditions are determined, and furthermore we show that the conditions stated in the main results are sharp.