3,713 research outputs found
Online Human-Bot Interactions: Detection, Estimation, and Characterization
Increasing evidence suggests that a growing amount of social media content is
generated by autonomous entities known as social bots. In this work we present
a framework to detect such entities on Twitter. We leverage more than a
thousand features extracted from public data and meta-data about users:
friends, tweet content and sentiment, network patterns, and activity time
series. We benchmark the classification framework by using a publicly available
dataset of Twitter bots. This training data is enriched by a manually annotated
collection of active Twitter users that include both humans and bots of varying
sophistication. Our models yield high accuracy and agreement with each other
and can detect bots of different nature. Our estimates suggest that between 9%
and 15% of active Twitter accounts are bots. Characterizing ties among
accounts, we observe that simple bots tend to interact with bots that exhibit
more human-like behaviors. Analysis of content flows reveals retweet and
mention strategies adopted by bots to interact with different target groups.
Using clustering analysis, we characterize several subclasses of accounts,
including spammers, self promoters, and accounts that post content from
connected applications.Comment: Accepted paper for ICWSM'17, 10 pages, 8 figures, 1 tabl
Hollywood in Homes: Crowdsourcing Data Collection for Activity Understanding
Computer vision has a great potential to help our daily lives by searching
for lost keys, watering flowers or reminding us to take a pill. To succeed with
such tasks, computer vision methods need to be trained from real and diverse
examples of our daily dynamic scenes. While most of such scenes are not
particularly exciting, they typically do not appear on YouTube, in movies or TV
broadcasts. So how do we collect sufficiently many diverse but boring samples
representing our lives? We propose a novel Hollywood in Homes approach to
collect such data. Instead of shooting videos in the lab, we ensure diversity
by distributing and crowdsourcing the whole process of video creation from
script writing to video recording and annotation. Following this procedure we
collect a new dataset, Charades, with hundreds of people recording videos in
their own homes, acting out casual everyday activities. The dataset is composed
of 9,848 annotated videos with an average length of 30 seconds, showing
activities of 267 people from three continents. Each video is annotated by
multiple free-text descriptions, action labels, action intervals and classes of
interacted objects. In total, Charades provides 27,847 video descriptions,
66,500 temporally localized intervals for 157 action classes and 41,104 labels
for 46 object classes. Using this rich data, we evaluate and provide baseline
results for several tasks including action recognition and automatic
description generation. We believe that the realism, diversity, and casual
nature of this dataset will present unique challenges and new opportunities for
computer vision community
Nazarbayev University multigrasp hand with bidirectional tendon actuation
Robotic hands are being used in various areas such as industrial automation, medical
robotics, and defense. In this work, we are presenting the Nazarbayev University Multigrasp Robot Hand
with an integrated RGB-Depth camera for intelligent object manipulation. The novelty ofthe project is seen
in the creation of an end effector system which obtains higher level autonomy from the base manipulator,
being able to recognize target objects, generate approach trajectories and apply corresponding grasping
patterns to capture the object
Numerical Simulation of Nano Scanning in Intermittent-Contact Mode AFM under Q control
We investigate nano scanning in tapping mode atomic force microscopy (AFM)
under quality (Q) control via numerical simulations performed in SIMULINK. We
focus on the simulation of whole scan process rather than the simulation of
cantilever dynamics and the force interactions between the probe tip and the
surface alone, as in most of the earlier numerical studies. This enables us to
quantify the scan performance under Q control for different scan settings.
Using the numerical simulations, we first investigate the effect of elastic
modulus of sample (relative to the substrate surface) and probe stiffness on
the scan results. Our numerical simulations show that scanning in attractive
regime using soft cantilevers with high Qeff results in a better image quality.
We, then demonstrate the trade-off in setting the effective Q factor (Qeff) of
the probe in Q control: low values of Qeff cause an increase in tapping forces
while higher ones limit the maximum achievable scan speed due to the slow
response of the cantilever to the rapid changes in surface profile. Finally, we
show that it is possible to achieve higher scan speeds without causing an
increase in the tapping forces using adaptive Q control (AQC), in which the Q
factor of the probe is changed instantaneously depending on the magnitude of
the error signal in oscillation amplitude. The scan performance of AQC is
quantitatively compared to that of standard Q control using iso-error curves
obtained from numerical simulations first and then the results are validated
through scan experiments performed using a physical set-up
Locomotion strategy selection for a legged wheeled hybrid quadruped using depth images
Three fundamental locomotion configurations recognized commonly are legged, wheeled,
and articulated mechanisms using which a mobile robot can navigate terrains. Hybrid configurations
enable execution of different locomotion types separately and in combinations. Such advantage usually
implies complexity and necessity in a robust supervisory controller capable of terrain recognition and
locomotion strategy selection. We developed the Nazarbayev University (NU) Hybrid Quadruped (Fig. 1)
- mobile robot with four legs and wheels. Project's major novelty is the implementation of the supervisory
controller which selects a locomotion mode associated with particular terrain types based on its terrain
recognizer input data
A survey of Australian midwives’ knowledge, experience, and training needs in relation to female genital mutilation
© 2017 Australian College of Midwives Background: Female genital mutilation (FGM) involves partial or total removal of the external female genitalia or any other injury for non-medical reasons. Due to international migration patterns, health professionals in high income countries are increasingly caring for women with FGM. Few studies explored the knowledge and skills of midwives in high income countries. Aim: To explore the knowledge, experience and needs of midwives in relation to the care of women with FGM. Methods: An online self-administered descriptive survey was designed and advertised through the Australian College of Midwives’ website. Results: Of the 198 midwives (24%) did not know the correct classification of FGM. Almost half of the respondents (48%) reported they had not received FGM training during their midwifery education. Midwives (8%) had been asked, or knew of others who had been asked to perform FGM in Australia. Many midwives were not clear about the law or health data related to FGM and were not aware of referral paths for affected women. Conclusion: As frontline providers, midwives must have appropriate up-to-date clinical skills and knowledge to ensure they are able to provide women with FGM the care they need and deserve. Midwives have a critical role to play in the collection of FGM related data to assist with health service planning and to prevent FGM by working closely with women and communities they serve to educate and advocate for its abandonment. Therefore, addressing educational gaps and training needs are key strategies to deliver optimal quality of care
Inertial motion capture based teleoperation of a mobile robot manipulator with a multigrasp hand
Autonomous mobile robots are still not reliable enough for performing complex tasks
such as search and rescue, space or undersea exploration and explosive ordnance disposal. Human
intelligence is frequently employed for high-level robot decision making and control. Moreover, for most
of the cases low-weight and dexterous end-effectors are required for performing delicate tasks efficiently
Inertial motion capture based teleoperation of a mobile robot manipulator with a multigrasp hand
Autonomous mobile robots are still not reliable enough for performing complex tasks
such as search and rescue, space or undersea exploration and explosive ordnance disposal. Human
intelligence is frequently employed for high-level robot decision making and control. Moreover, for most
of the cases low-weight and dexterous end-effectors are required for performing delicate tasks efficiently
Effects of irrigation applied at different growth stages on chickpea yield
ArticleThis study was conducted over the experimental fields of Erciyes University in 2016
to investigate the effects of irrigations applied at different growth stages on chickpea yields. Experiments were conducted in randomized blocks design with 3 replications. There were 7 irrigation treatments as of I1: rainfed, I2: pre-bloom single irrigation, I3: single irrigation at the
beginning of blooming, I4: single irrigation at 50% pod set, I5: two irrigations at 50% bloom and 50% pod-set, I6: two irrigations at pre-bloom and 50% pod-set, I7: full irrigation. The amount of applied irrigation water varied between 85.6–323 mm. Plant water
consumptions varied between 262
– 569 mm. The greatest yield was obtained from I4 treatment with 273 kg da-1 and the lowest yield was obtained from I1
treatments with 146 kg da-1. It was
concluded for chickpea cultivation under deficit water resources conditions that water deficits may be applied at different growth
stages except for 50% pod-set period
Preventing female genital mutilation in high income countries: A systematic review of the evidence
© 2019 The Author(s). Background: Female genital mutilation (FGM) is prevalent in communities of migration. Given the harmful effects of the practice and its illegal status in many countries, there have been concerted primary, secondary and tertiary prevention efforts to protect girls from FGM. However, there is paucity of evidence concerning useful strategies and approaches to prevent FGM and improve the health and social outcomes of affected women and girls. Methods: We analysed peer-reviewed and grey literature to extract the evidence for FGM prevention interventions from a public health perspective in high income countries by a systematic search of bibliographic databases and websites using appropriate keywords. Identified publications were screened against selection criteria, following the PRISMA guidelines. We examined the characteristics of prevention interventions, including their programmatic approaches and strategies, target audiences and evaluation findings using an apriori template. Findings: Eleven documents included in this review described primary and secondary prevention activities. High income countries have given attention to legislative action, bureaucratic interventions to address social injustice and protect those at risk of FGM, alongside prevention activities that favour health persuasion, foster engagement with the local community through outreach and the involvement of community champions, healthcare professional training and capacity strengthening. Study types are largely process evaluations that include measures of short-term outcomes (pre- and post-changes in attitude, knowledge and confidence or audits of practices). There is a dearth of evaluative research focused on empowerment-oriented preventative activities that involve individual women and girls who are affected by FGM. Beattie's framework provides a useful way of articulating negotiated and authoritative prevention actions required to address FGM at national and local levels. Conclusion: FGM is a complex and deeply rooted sociocultural issue that requires a multifaceted response that encompasses socio-economic, physical and environmental factors, education and learning, health services and facilities, and community mobilisation activities. Investment in the rigorous longitudinal evaluation of FGM health prevention efforts are needed to provide strong evidence of impact to guide future decision making. A national evidence-based framework would bring logic, clarity, comprehension, evidence and economically more effective response for current and future prevention interventions addressing FGM in high income countries
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