Pop-up SLAM: Semantic Monocular Plane SLAM for Low-texture Environments

Existing simultaneous localization and mapping (SLAM) algorithms are not robust in challenging low-texture environments because there are only few salient features. The resulting sparse or semi-dense map also conveys little information for motion planning. Though some work utilize plane or scene layout for dense map regularization, they require decent state estimation from other sources. In this paper, we propose real-time monocular plane SLAM to demonstrate that scene understanding could improve both state estimation and dense mapping especially in low-texture environments. The plane measurements come from a pop-up 3D plane model applied to each single image. We also combine planes with point based SLAM to improve robustness. On a public TUM dataset, our algorithm generates a dense semantic 3D model with pixel depth error of 6.2 cm while existing SLAM algorithms fail. On a 60 m long dataset with loops, our method creates a much better 3D model with state estimation error of 0.67%.Comment: International Conference on Intelligent Robots and Systems (IROS) 201

A Simulation Study of Patient Accrual Patterns in Clinical Trials and Data Analysis of Histone 3 Lysine 36 Trimethylation ChIP-seq in Human Kidney Cancer

University of Minnesota M.S. thesis.July 2017. Major: Biomedical Informatics and Computational Biology. Advisors: Karla Ballman, Huihuang Yan. 1 computer file (PDF); viii, 49 pages.In part one, we simulated a successive of two-armed randomized clinical trial with the time-to-event outcome over 15 years. We used three different accrual pattern representing slow, medium and fast accrual, which is in fact related to the number of trials for the sequential trials interested in the 15-year period. We used a historical survival distribution to explore the treatment effects and analyzed by the Cox proportional hazard ratio model and log-rank test. We computed the mean and median overall hazard ratio (year 15 versus year 0), and the probability of detrimental effect to find the optimal design parameters. Finally, we carried out a sensitivity analysis to study the effect of an additional 6 month turnaround time. In Part two, we have described a general workflow for the normalization of ChIP-seq data by estimating the normalization factor from peak-less regions. Using publicly available histone 3 lysine 36 trimethylation (H3K36me3) data from human kidney cancer, we demonstrated the better performance of our method over the existing approach

Influence of fiber hollowness on the local thermo-electro-elastic field in a thermoelectric composite

The fiber geometry is one of the important parameters in the effective conversion performance and local strength of thermoelectric composites. In this study, the plane problem of a hollow fiber embedded within a non-linear thermoelectric medium in the presence of a uniform remote in-plane electric current and a uniform remote energy flux is investigated based on the complex variable method. Closed-form expressions for all the potential functions characterizing the thermoelectric field and the associated thermal stress field in both the matrix and fiber are obtained by solving the corresponding boundary value problem. Numerical examples are presented to illustrate the effect of hollowness ratio of the fiber on the local energy conversion efficiency and interfacial thermal stress concentration. It is found that a higher conversion efficiency and a lower amount of thermal stress concentration around a hollow fiber than that around a solid fiber could be achieved simultaneously by appropriate selection of the hollowness ratio of the fiber. The results can be directly used for performance optimization and reliability evaluation in design of thermoelectric composites in engineering

Comparison of multi-field coupling numerical simulation in hot dry rock thermal exploitation of enhanced geothermal systems

 In order to alleviate the environmental crisis and improve energy structure, countries from all over the world have focused on the hot dry rock geothermal resources with great potential and with little pollution. The geothermal heat production from Enhanced Geothermal System (EGS) comes with complex multi-field coupling process, and it is of great significance to study the temporal and spatial evolution of geothermal reservoir. In this work, a practical numerical model is established to simulate the heat production process in EGS, and the comparison of thermal-hydraulic (TH), thermal-hydraulic-mechanical (THM) and thermal-hydraulic-mechanical-chemical (THMC) coupling in geothermal reservoir is analyzed. The results show that the stable production stage of the three cases is approximately 5 years; however, compared with TH and THMC coupling, the service-life for THM coupling decreased by 1140 days and 332 days, respectively. The mechanical enhanced effects are offset by the chemical precipitation, and the precipitation from SiO2 is much larger than the dissolution of calcite.Cited as: Chen, S., Ding, B., Gong, L., Huang, Z., Yu, B., Sun, S. Comparison of multi-field coupling numerical simulation in hot dry rock thermal exploitation of enhanced geothermal systems. Advances in Geo-Energy Research, 2019, 3(4): 396-409, doi: 10.26804/ager.2019.04.0

Cascaded deep monocular 3D human pose estimation with evolutionary training data

End-to-end deep representation learning has achieved remarkable accuracy for monocular 3D human pose estimation, yet these models may fail for unseen poses with limited and fixed training data. This paper proposes a novel data augmentation method that: (1) is scalable for synthesizing massive amount of training data (over 8 million valid 3D human poses with corresponding 2D projections) for training 2D-to-3D networks, (2) can effectively reduce dataset bias. Our method evolves a limited dataset to synthesize unseen 3D human skeletons based on a hierarchical human representation and heuristics inspired by prior knowledge. Extensive experiments show that our approach not only achieves state-of-the-art accuracy on the largest public benchmark, but also generalizes significantly better to unseen and rare poses. Code, pre-trained models and tools are available at this HTTPS URL.Comment: Accepted to CVPR 2020 as Oral Presentatio