Techniques to Enhance the Quality of Service of Multi Hop Relay Networks

AbstractBroadband internet access through the user equipment has become the hot research topic. The shadowing and multipath issues restrict the high performance nature of 4G cells. In Multi hop Relay (MHR) networks, Relay Stations (RS) are introduced to improve coverage and capacity of the system. There exist some issues like path selection and RSs deployment, which severely affects the Quality of Service (QoS) of the system. In this paper, to improve the QoS of MHR networks, Load Aware Routing Metric (LARM) based path selection and a low complex Burst Profile (BP) based RS deployment schemes are discussed

Gapped Excitations in the High-Pressure Antiferromagnetic Phase of URu2_2Si2_2

We report a neutron scattering study of the magnetic excitation spectrum in each of the three temperature and pressure driven phases of URu$_2$Si$_2$. We find qualitatively similar excitations throughout the (H0L) scattering plane in the hidden order and large moment phases, with no changes in the $\hbar\omega$-widths of the excitations at the $\Sigma$ = (1.407,0,0) and $Z$ = (1,0,0) points, within our experimental resolution. There is, however, an increase in the gap at the $\Sigma$ point from 4.2(2) meV to 5.5(3) meV, consistent with other indicators of enhanced antiferromagnetism under pressure.Comment: 5 pages, 3 figures, 1 tabl

Relative Pose from Deep Learned Depth and a Single Affine Correspondence

We propose a new approach for combining deep-learned non-metric monocular depth with affine correspondences (ACs) to estimate the relative pose of two calibrated cameras from a single correspondence. Considering the depth information and affine features, two new constraints on the camera pose are derived. The proposed solver is usable within 1-point RANSAC approaches. Thus, the processing time of the robust estimation is linear in the number of correspondences and, therefore, orders of magnitude faster than by using traditional approaches. The proposed 1AC+D solver is tested both on synthetic data and on 110395 publicly available real image pairs where we used an off-the-shelf monocular depth network to provide up-to-scale depth per pixel. The proposed 1AC+D leads to similar accuracy as traditional approaches while being significantly faster. When solving large-scale problems, e.g., pose-graph initialization for Structure-from-Motion (SfM) pipelines, the overhead of obtaining ACs and monocular depth is negligible compared to the speed-up gained in the pairwise geometric verification, i.e., relative pose estimation. This is demonstrated on scenes from the 1DSfM dataset using a state-of-the-art global SfM algorithm. Source code: https://github.com/eivan/one-ac-pos

Venus - Preliminary science objectives and experiments for use in advanced mission studies

Mission planning and experiment design for future Mariner-type Venus space probe

Radio Astronomy

Contains reports on five research projects.National Aeronautics and Space Administration (Grant NGL 22-009-016)National Aeronautics and Space Administration (Grant NGL 22-009-421)National Science Foundation (Grant GP-13056)California Institute of Technology Contract 95256