713 research outputs found

    Deep Attributes Driven Multi-Camera Person Re-identification

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    The visual appearance of a person is easily affected by many factors like pose variations, viewpoint changes and camera parameter differences. This makes person Re-Identification (ReID) among multiple cameras a very challenging task. This work is motivated to learn mid-level human attributes which are robust to such visual appearance variations. And we propose a semi-supervised attribute learning framework which progressively boosts the accuracy of attributes only using a limited number of labeled data. Specifically, this framework involves a three-stage training. A deep Convolutional Neural Network (dCNN) is first trained on an independent dataset labeled with attributes. Then it is fine-tuned on another dataset only labeled with person IDs using our defined triplet loss. Finally, the updated dCNN predicts attribute labels for the target dataset, which is combined with the independent dataset for the final round of fine-tuning. The predicted attributes, namely \emph{deep attributes} exhibit superior generalization ability across different datasets. By directly using the deep attributes with simple Cosine distance, we have obtained surprisingly good accuracy on four person ReID datasets. Experiments also show that a simple metric learning modular further boosts our method, making it significantly outperform many recent works.Comment: Person Re-identification; 17 pages; 5 figures; In IEEE ECCV 201

    Seismic Analysis of Saturated Sand Deposits with Silt Layers

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    Liquefaction of saturated sands during earthquakes is known to be the cause of significant earthquake related damages, including loss of bearing capacity, lateral flow and spreading, slope failures. In recent earthquakes including the1999 Marmara Earthquake in Turkey, field observations have indicated that silt inclusions or silt layers in the sandy deposits can have significant effects on development of liquefaction. The objective of this work is to analytically study the behavior of saturated sand deposits with silt layers. For this purpose, a hypothetical soil profile in which silt layers exist has been selected. The selected profile was then modeled and analyzed using the LASS-IV code that has nonlinear effective stress analysis capability. As base motion, rock site recordings of the mentioned earthquakes were utilized. Furthermore, as part of this study, a parametric study has been conducted to further understand the effects of silt layers within sand deposits on the onset of liquefaction. The results of the analyses of various parameters such as depth of silt layer, the relative density of sand layer and maximum base acceleration were tabulated to summarize the effect of silt layers on the onset of liquefaction

    Duration of Posttraumatic Amnesia Predicts Neuropsychological and Global Outcome in Complicated Mild Traumatic Brain Injury.

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    OBJECTIVES: Examine the effects of posttraumatic amnesia (PTA) duration on neuropsychological and global recovery from 1 to 6 months after complicated mild traumatic brain injury (cmTBI). PARTICIPANTS: A total of 330 persons with cmTBI defined as Glasgow Coma Scale score of 13 to 15 in emergency department, with well-defined abnormalities on neuroimaging. METHODS: Enrollment within 24 hours of injury with follow-up at 1, 3, and 6 months. MEASURES: Glasgow Outcome Scale-Extended, California Verbal Learning Test II, and Controlled Oral Word Association Test. Duration of PTA was retrospectively measured with structured interview at 30 days postinjury. RESULTS: Despite all having a Glasgow Coma Scale Score of 13 to 15, a quarter of the sample had a PTA duration of greater than 7 days; half had PTA duration of 1 of 7 days. Both cognitive performance and Extended Glasgow Outcome Scale outcomes were strongly associated with time since injury and PTA duration, with those with PTA duration of greater than 1 week showing residual moderate disability at 6-month assessment. CONCLUSIONS: Findings reinforce importance of careful measurement of duration of PTA to refine outcome prediction and allocation of resources to those with cmTBI. Future research would benefit from standardization in computed tomographic criteria and use of severity indices beyond Glasgow Coma Scale to characterize cmTBI

    The SLICK hair locus derived from Senepol cattle confers thermotolerance to intensively managed lactating Holstein cows

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    AbstractThe SLICK haplotype (http://omia.angis.org.au/OMIA001372/9913/) in cattle confers animals with a short and sleek hair coat. Originally identified in Senepol cattle, the gene has been introduced into Holsteins. The objectives of the current study were to determine (1) whether lactating Holsteins with the slick hair phenotype have superior ability for thermoregulation compared with wild-type cows or relatives not inheriting the SLICK haplotype, and (2) whether seasonal depression in milk yield would be reduced in SLICK cows. In experiment 1, diurnal variation in vaginal temperature in the summer was monitored for cows housed in a freestall barn with fans and sprinklers. Vaginal temperatures were lower in slick-haired cows than in relatives and wild-type cows. In experiment 2, acute responses to heat stress were monitored after cows were moved to a dry lot in which the only heat abatement was shade cloth. The increases in rectal temperature and respiration rate caused by heat stress during the day were lower for slick cows than for relatives or wild-type cows. Moreover, sweating rate was higher for slick cows than for cows of the other 2 types. In experiment 3, effects of season of calving (summer vs. winter) on milk yield and composition were determined. Compared with milk yield of cows calving in winter, milk yield during the first 90 d in milk was lower for cows calving in the summer. However, this reduction was less pronounced for slick cows than for wild-type cows. In conclusion, Holsteins with slick hair have superior thermoregulatory ability compared with non-slick animals and experience a less drastic depression in milk yield during the summer
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