361 research outputs found
Unsupervised Object-Centric Voxelization for Dynamic Scene Understanding
Understanding the compositional dynamics of multiple objects in unsupervised
visual environments is challenging, and existing object-centric representation
learning methods often ignore 3D consistency in scene decomposition. We propose
DynaVol, an inverse graphics approach that learns object-centric volumetric
representations in a neural rendering framework. DynaVol maintains time-varying
3D voxel grids that explicitly represent the probability of each spatial
location belonging to different objects, and decouple temporal dynamics and
spatial information by learning a canonical-space deformation field. To
optimize the volumetric features, we embed them into a fully differentiable
neural network, binding them to object-centric global features and then driving
a compositional NeRF for scene reconstruction. DynaVol outperforms existing
methods in novel view synthesis and unsupervised scene decomposition and allows
for the editing of dynamic scenes, such as adding, deleting, replacing objects,
and modifying their trajectories
Draining the Water Hole: Mitigating Social Engineering Attacks with CyberTWEAK
Cyber adversaries have increasingly leveraged social engineering attacks to
breach large organizations and threaten the well-being of today's online users.
One clever technique, the "watering hole" attack, compromises a legitimate
website to execute drive-by download attacks by redirecting users to another
malicious domain. We introduce a game-theoretic model that captures the salient
aspects for an organization protecting itself from a watering hole attack by
altering the environment information in web traffic so as to deceive the
attackers. Our main contributions are (1) a novel Social Engineering Deception
(SED) game model that features a continuous action set for the attacker, (2) an
in-depth analysis of the SED model to identify computationally feasible
real-world cases, and (3) the CyberTWEAK algorithm which solves for the optimal
protection policy. To illustrate the potential use of our framework, we built a
browser extension based on our algorithms which is now publicly available
online. The CyberTWEAK extension will be vital to the continued development and
deployment of countermeasures for social engineering.Comment: IAAI-20, AICS-2020 Worksho
Robot Protection in the Hazardous Environments
Rescue missions for chemical, biological, radiological, nuclear, and explosive (CBRNE) incidents are highly risky and sometimes it is impossible for rescuers to perform, while these accidents vary dramatically in features and protection requirements. The purpose of this chapter is to present several protection approaches for rescue robots in the hazardous conditions. And four types of rescue robots are presented, respectively. First, design factors and challenges of the rescue robots are analyzed and indicated for these accidents. Then the rescue robots with protective modification are presented, respectively, meeting individual hazardous requirements. And finally several tests are conducted to validate the effectiveness of these modified robots. It is clear that these well-designed robots can work efficiently for the CBRNE response activities
Explaining Income-Related Inequalities in Dietary Knowledge: Evidence from the China Health and Nutrition Survey
Lack of adequate dietary knowledge may result in poor health conditions. This study aims to measure income-related inequality in dietary knowledge, and to explain the sources of the inequality. Data were from the China Health and Nutrition Survey (CHNS) conducted in 2015. A summary of the dietary knowledge score and dietary guideline awareness was used to measure the dietary knowledge of respondents. The concentration index was employed as a measure of socioeconomic inequality and was decomposed into its determining factors. The study found that the proportion of respondents who correctly answered questions on dietary knowledge was significantly low for some questions. Compared to rural residents, urban residents had a higher proportion of correctly answered dietary knowledge questions. In addition, there are pro-rich inequalities in dietary knowledge. This observed inequality is determined not only by individual factors but also high-level area factors. Our study recommends that future dietary education programs could take different strategies for individuals with different educational levels and focus more on disadvantaged people. It would be beneficial to consider local dietary habits in developing education materials
- …