Multiscale modeling of combined deterministic and stochastic fabric non-uniformity for realistic resin injection simulation

The local fiber arrangement in a bi-directional fabric formed to a complex shape was modeled considering the stochastic arrangement of filaments within yarns, which determines axial and transverse yarn permeabilities, and the stochastic arrangement of yarns in a fabric, which determines the dimensions of interyarn gap spaces locally. To mimic the uncertainty in fabric forming, drape simulation was randomized in terms of start point and yarn start orientations. From yarn permeabilities and simulated local yarn spacing distributions, local fiber volume fractions and fabric permeabilities were approximated. This allowed resin injection into a deformed fabric to be simulated for different drape scenarios with different probabilities and different degrees of fabric randomness. The results indicate that variability in fabric properties and the forming process affects flow front shapes and times for complete impregnation of the reinforcement

Ectopic expression of a vesicle trafficking gene, OsRab7, from Oryza sativa, confers tolerance to several abiotic stresses in Escherichia coli

Rab7 is a small GTP-binding protein involved in intracellular vesicle trafficking from late endosome to the vacuole. In this study, the gene OsRab7 was isolated from Oryza sativa. Over-expression of OsRab7 gene in Escherichia coli increased the resistance to heat, cold and salt stress. In addition, subcellular localization of OsRab7 protein in E. coli and onion cells all revealed that OsRab7 protein is specifically present in the cytoplasm. These results showed that OsRab7 plays an important role in stress tolerance and probably develop abiotic stress tolerance in E. coli and planta with similar mechanism.Key words: Vesicle trafficking, rice, OsRab7, Escherichia coli, abiotic stresses

Finite dimensional integrable Hamiltonian systems associated with DSI equation by Bargmann constraints

The Davey-Stewartson I equation is a typical integrable equation in 2+1 dimensions. Its Lax system being essentially in 1+1 dimensional form has been found through nonlinearization from 2+1 dimensions to 1+1 dimensions. In the present paper, this essentially 1+1 dimensional Lax system is further nonlinearized into 1+0 dimensional Hamiltonian systems by taking the Bargmann constraints. It is shown that the resulting 1+0 dimensional Hamiltonian systems are completely integrable in Liouville sense by finding a full set of integrals of motion and proving their functional independence.Comment: 10 pages, in LaTeX, to be published in J. Phys. Soc. Jpn. 70 (2001

Bulk and interfacial properties of quadrupolar fluids

We extend Teixeira and Telo da Gama’s density-functional approach [J. Phys.: Condens. Matter 3, 111 (1991)] to study the vapor–liquid phase equilibria and planar interfacial properties of quadrupolar fluids. The density profile, surface ordering, surface polarization, and surface tension of quadrupolar fluids are evaluated. Particular attention is given to the temperature and quadrupole-strength dependence. It is found that the interfacial molecular ordering can arise entirely due to the quadrupole–quadrupole interaction. It is also found that the bulk-phase properties of the quadrupolar fluids satisfy the law of correspondence states. The reduced surface potential and surface tension can be well correlated by power laws of the scaled temperature τ ≡1-T/Tc , where Tc is the critical temperature of the fluids

People Detection and Pose Classification Inside a Moving Train Using Computer Vision

This paper has been presented at : 5th International Visual Informatics Conference (IVIC 2017)Also part of the Image Processing, Computer Vision, Pattern Recognition, and Graphics book sub series (LNIP, volume 10645)The use of surveillance video cameras in public transport is increasingly regarded as a solution to control vandalism and emergency situations. The widespread use of cameras brings in the problem of managing high volumes of data, resulting in pressure on people and resources. We illustrate a possible step to automate the monitoring task in the context of a moving train (where popular background removal algorithms will struggle with rapidly changing illumination). We looked at the detection of people in three possible postures: Sat down (on a train seat), Standing and Sitting (half way between sat down and standing). We then use the popular Histogram of Oriented Gradients (HOG) descriptor to train Support Vector Machines to detect people in any of the predefined postures. As a case study, we use the public BOSS dataset. We show different ways of training and combining the classifiers obtaining a sensitivity performance improvement of about 12% when using a combination of three SVM classifiers instead of a global (all classes) classifier, at the expense of an increase of 6% in false positive rate. We believe this is the first set of public results on people detection using the BOSS dataset so that future researchers can use our results as a baseline to improve upon.The work described here was carried out as part of the OBSERVE project funded by the Fondecyt Regular Program of Conicyt (Chilean Research Council for Science and Technology) under grant no. 1140209. S.A. Velastin is grateful to funding received from the Universidad Carlos III de Madrid, the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no. 600371, el Ministerio de Economía y Competitividad (COFUND2013-51509) and Banco Santander

Adaptive obstacle detection for mobile robots in urban environments using downward-looking 2D LiDAR

Environment perception is important for collision-free motion planning of outdoor mobile robots. This paper presents an adaptive obstacle detection method for outdoor mobile robots using a single downward-looking LiDAR sensor. The method begins by extracting line segments from the raw sensor data, and then estimates the height and the vector of the scanned road surface at each moment. Subsequently, the segments are divided into either road ground or obstacles based on the average height of each line segment and the deviation between the line segment and the road vector estimated from the previous measurements. A series of experiments have been conducted in several scenarios, including normal scenes and complex scenes. The experimental results show that the proposed approach can accurately detect obstacles on roads and could effectively deal with the different heights of obstacles in urban road environments