Robust and Fast 3D Scan Alignment using Mutual Information

This paper presents a mutual information (MI) based algorithm for the estimation of full 6-degree-of-freedom (DOF) rigid body transformation between two overlapping point clouds. We first divide the scene into a 3D voxel grid and define simple to compute features for each voxel in the scan. The two scans that need to be aligned are considered as a collection of these features and the MI between these voxelized features is maximized to obtain the correct alignment of scans. We have implemented our method with various simple point cloud features (such as number of points in voxel, variance of z-height in voxel) and compared the performance of the proposed method with existing point-to-point and point-to- distribution registration methods. We show that our approach has an efficient and fast parallel implementation on GPU, and evaluate the robustness and speed of the proposed algorithm on two real-world datasets which have variety of dynamic scenes from different environments

Brillouin Cooling

We analyze how to exploit Brillouin scattering for the purpose of cooling opto-mechanical devices and present a quantum-mechanical theory for Brillouin cooling. Our analysis shows that significant cooling ratios can be obtained with standard experimental parameters. A further improvement of cooling efficiency is possible by increasing the dissipation of the optical anti-Stokes resonance.Comment: 4 pages 3 figure

VIDEO FRAME REDUCTION IN AUTONOMOUS VEHICLES

Camera sensors are emerging in many applications such as Smart Buildings and autonomous driving. The Data generated by multiple cameras in a smart building and autonomous driving applications is usually transmitted through an edge box to a cloud terminal. This transmitted information requires a considerable channel bandwidth, which is not available through current communication standards. The report proposes a Camera Sensor Frame Reduction method to decrease the required channel bandwidth for applications such as autonomous driving. Here, we propose a method that incorporates cross frame similarity measurement method to reduce the redundant frames and decrease the data rate of each camera. This approach adds processing to the camera sensor, which maps each camera to a smart one. In order to calculate cross frame correlation, each smart camera converts frames into blocks of sub-images. Next, we incorporate consecutive blocks to compute the overall cross frame correlation. The report studies block size selection and its impact on processing complexity and performance. We used real vehicle videos in different driving speed and scenarios to study the complexity and performance of the proposed method. We have investigated frame reduction rate as a function of vehicle traffic and driving environment

Rebuilding after war: micro-level determinants of poverty reduction in Mozambique

"Rather than looking at the association between poverty and various household and individual characteristics on a one-to-one basis (bivariate analysis), which often oversimplifies complex relationships and can lead to erroneous conclusions, this report uses multiple regression to analyze poverty and living standards econometrically. As methodological choices can have a strong influence on the results,much of the report is given over to a detailed discussion of the methodology used to conduct the analysis and sensitivity analysis to assess the robustness of the findings to alternative methodological choices. These include the construction of region-specific poverty linesand the empirical model of poverty determinants used. Estimates of poverty levels and the results of the model are presented, followed by simulations that indicate the impact on poverty of specific policy interventions." from Text of AbstractConflict, Poverty alleviation, Living standards Mozambique,