Contextual Attention for Hand Detection in the Wild

We present Hand-CNN, a novel convolutional network architecture for detecting hand masks and predicting hand orientations in unconstrained images. Hand-CNN extends MaskRCNN with a novel attention mechanism to incorporate contextual cues in the detection process. This attention mechanism can be implemented as an efficient network module that captures non-local dependencies between features. This network module can be inserted at different stages of an object detection network, and the entire detector can be trained end-to-end. We also introduce a large-scale annotated hand dataset containing hands in unconstrained images for training and evaluation. We show that Hand-CNN outperforms existing methods on several datasets, including our hand detection benchmark and the publicly available PASCAL VOC human layout challenge. We also conduct ablation studies on hand detection to show the effectiveness of the proposed contextual attention module.Comment: 9 pages, 9 figure

Contextual Attention for Hand Detection in the Wild

We present Hand-CNN, a novel convolutional network architecture for detecting hand masks and predicting hand orientations in unconstrained images. Hand-CNN extends MaskRCNN with a novel attention mechanism to incorporate contextual cues in the detection process. This attention mechanism can be implemented as an efficient network module that captures non-local dependencies between features. This network module can be inserted at different stages of an object detection network, and the entire detector can be trained end-to-end. We also introduce large-scale annotated hand datasets containing hands in unconstrained images for training and evaluation. We show that Hand-CNN outperforms existing methods on the newly collected datasets and the publicly available PASCAL VOC human layout dataset. Data and code: https://www3.cs.stonybrook.edu/~cvl/projects/hand_det_attention

From lifelog to diary: a timeline view for memory reminiscence

As digital recording sensors and lifelogging devices become more prevalent, the suitability of lifelogging tools to act as a reminiscence supporting tool has become an important research challenge. This paper aims to describe a rst- generation memory reminiscence tool that utilises lifelog- ging sensors to record a digital diary of user activities and presents it as a narrative description of user activities. The automatically recognised daily activities are shown chronologically in the timeline view

Investing with Fast Thinking

Using data from a major online peer-to-peer lending market, we document that investors follow a simple rule of thumb under time pressure: they rush to invest in loans with high interest rates without sufficiently examining credit ratings, which are freely available on the trading interface. Our experiments show that making credit rating information more salient “nudges” investors into better decisions. Firsthand experience matters for learning for non-informational reasons: An investor responds differently when observing a default of her own loan, relative to observing a default of another investor’s loan

Antimikrobna rezistencija i svojstva virulencije bakterije Enterococcus faecium izolirane u goveda s kliničkim mastitisom iz pokrajine Ningxia, Kina

This study was conducted to determine the antimicrobial resistance and virulence traits of 32 Enterococcus faecium isolates from clinical bovine mastitis cases in Ningxia Province, China. In total, 32 E. faecium isolates were taken from subclinical bovine mastitis on the basis of morphological characterization and biochemical testing, and screened for antimicrobial susceptibility. The virulence genes of the isolates were studied using polymerase chain reaction (PCR). The disc diffusion assay revealed a high occurrence of resistance against tetracycline (78.1%) and erythromycin (68.8%) in the E. faecium isolates. However, all tested E. faecium were susceptible to linezolid and vancomycin. Moreover, all E. faecium isolates harbored the erythromycin-resistant genes ermA, ermB and ermC, as well as the tetracycline-resistant genes tetK, tetL and tetM. Furthermore, all E. faecium isolates carried more than 3 of the tested virulence genes. The presence of agg (100%), cpd (100%), efaA (100%), gelE (93.4%), and esp (75.0%) was found most frequently in all the tested isolates. These findings are useful for making appropriate antimicrobial choices and developing antivirulence therapies for subclinical bovine mastitis caused by E. faecium in Ningxia Province, China.Istraživanje je provedeno kako bi se odredila antimikrobina rezistencija i svojstva virulencije izolata bakterije Enterococcus faecium uzetih u goveda s kliničkim mastitisom. U ukupno 32 izolata goveda iz pokrajine Ningxia u Kini, procijenjena je antimikrobna osjetljivost na temelju morfološke karakterizacije i biokemijskih pretraga. Geni virulencije izolata istraženi su polimeraznom lančanom reakcijom (PCR). Disk-difuzijski test je u izolatu bakterije E. faecium pokazao visoku pojavnost rezistencije na tetraciklin (78,1 %) i eritromicin (68,8 %). Svi su pretraženi izolati bili osjetljivi na linezolid i vankomicin i imali gene rezisentne na eritromicin ermA, ermB i ermC, kao i na tetraciklin, tetK, tetL i tetM. Osim toga svi izolati E. faecium nosili su više od tri istraživana gena virulencije. Najčešći geni bili agg (100 %), cpd (100 %), efaA (100 %), gelE (93,4 %) i esp (75,0 %). Ovi rezultati mogu u pokrajini Ningxia u Kini pridonijeti pravilnom izboru antimikrobnog lijeka i razvoju uspješne terapije za supklinički goveđi mastitis uzrokovan bakterijom E. faecium

Experimental investigations on effects of axial clearance on high-speed turbine expansion generator rotor response

Bearing-rotor system dynamic characteristic is the key influence on high-speed power equipment stability. The experimental investigations focus on the dynamic characteristics of high-speed turbine expansion generator rotor, which was supported by gas aerostatic bearings. Nonlinear dynamic behavior of high-speed turbine expansion generator rotor, including gas film whipping and gas film half-speed whirling, were analyzed in the experiments. Static characteristic tests for effects of bearing supply gas pressure on the bearing axial clearance are carried out to provide the rotor axial position under different bearing supply gas pressure groups, which showed that the bearing thrust performance changed with bearing supply gas pressure. The experimental results of rotor dynamic characteristics under different bearing supply gas pressure groups show that gas film whirling and whipping occurred in the mentioned bearing-rotor system during the speed up process when the axial clearance for two ends were different. The shafting stability under the same axial clearance for two ends is better than the condition under the different bearing axial clearance. The paper gives some measures to improve the high-speed bearing-rotor system stability

Hawkeye: Change-targeted Testing for Android Apps based on Deep Reinforcement Learning

Android Apps are frequently updated to keep up with changing user, hardware, and business demands. Ensuring the correctness of App updates through extensive testing is crucial to avoid potential bugs reaching the end user. Existing Android testing tools generate GUI events focussing on improving the test coverage of the entire App rather than prioritising updates and its impacted elements. Recent research has proposed change-focused testing but relies on random exploration to exercise the updates and impacted GUI elements that is ineffective and slow for large complex Apps with a huge input exploration space. We propose directed testing of App updates with Hawkeye that is able to prioritise executing GUI actions associated with code changes based on deep reinforcement learning from historical exploration data. Our empirical evaluation compares Hawkeye with state-of-the-art model-based and reinforcement learning-based testing tools FastBot2 and ARES using 10 popular open-source and 1 commercial App. We find that Hawkeye is able to generate GUI event sequences targeting changed functions more reliably than FastBot2 and ARES for the open source Apps and the large commercial App. Hawkeye achieves comparable performance on smaller open source Apps with a more tractable exploration space. The industrial deployment of Hawkeye in the development pipeline also shows that Hawkeye is ideal to perform smoke testing for merge requests of a complicated commercial App