REFINE: Reachability-based Trajectory Design using Robust Feedback Linearization and Zonotopes

Performing real-time receding horizon motion planning for autonomous vehicles while providing safety guarantees remains difficult. This is because existing methods to accurately predict ego vehicle behavior under a chosen controller use online numerical integration that requires a fine time discretization and thereby adversely affects real-time performance. To address this limitation, several recent papers have proposed to apply offline reachability analysis to conservatively predict the behavior of the ego vehicle. This reachable set can be constructed by utilizing a simplified model whose behavior is assumed a priori to conservatively bound the dynamics of a full-order model. However, guaranteeing that one satisfies this assumption is challenging. This paper proposes a framework named REFINE to overcome the limitations of these existing approaches. REFINE utilizes a parameterized robust controller that partially linearizes the vehicle dynamics even in the presence of modeling error. Zonotope-based reachability analysis is then performed on the closed-loop, full-order vehicle dynamics to compute the corresponding control-parameterized, over-approximate Forward Reachable Sets (FRS). Because reachability analysis is applied to the full-order model, the potential conservativeness introduced by using a simplified model is avoided. The pre-computed, control-parameterized FRS is then used online in an optimization framework to ensure safety. The proposed method is compared to several state of the art methods during a simulation-based evaluation on a full-size vehicle model and is evaluated on a 1/10th race car robot in real hardware testing. In contrast to existing methods, REFINE is shown to enable the vehicle to safely navigate itself through complex environments

VL-InterpreT: An Interactive Visualization Tool for Interpreting Vision-Language Transformers

Breakthroughs in transformer-based models have revolutionized not only the NLP field, but also vision and multimodal systems. However, although visualization and interpretability tools have become available for NLP models, internal mechanisms of vision and multimodal transformers remain largely opaque. With the success of these transformers, it is increasingly critical to understand their inner workings, as unraveling these black-boxes will lead to more capable and trustworthy models. To contribute to this quest, we propose VL-InterpreT, which provides novel interactive visualizations for interpreting the attentions and hidden representations in multimodal transformers. VL-InterpreT is a task agnostic and integrated tool that (1) tracks a variety of statistics in attention heads throughout all layers for both vision and language components, (2) visualizes cross-modal and intra-modal attentions through easily readable heatmaps, and (3) plots the hidden representations of vision and language tokens as they pass through the transformer layers. In this paper, we demonstrate the functionalities of VL-InterpreT through the analysis of KD-VLP, an end-to-end pretraining vision-language multimodal transformer-based model, in the tasks of Visual Commonsense Reasoning (VCR) and WebQA, two visual question answering benchmarks. Furthermore, we also present a few interesting findings about multimodal transformer behaviors that were learned through our tool.Comment: CVPR 2022 demo trac

Look, the World is Watching How We Treat Migrants! The Making of the Anti-Trafficking Legislation during the Ma Administration

Employing the spiral model, this research analyses how anti-human trafficking legislation was promulgated during the Ma Ying-jeou (Ma Yingjiu) presidency. This research found that the gov- ernment of Taiwan was just as accountable for the violation of mi- grants’ human rights as the exploitive placement agencies and abusive employers. This research argues that, given its reliance on the United States for political and security support, Taiwan has made great ef- forts to improve its human rights records and meet US standards for protecting human rights. The reform was a result of multilevel inputs, including US pressure and collaboration between transnational and domestic advocacy groups. A major contribution of this research is to challenge the belief that human rights protection is intrinsic to dem- ocracy. In the same light, this research also cautions against Taiwan’s subscription to US norms since the reform was achieved at the cost of stereotyping trafficking victimhood, legitimising state surveillance, and further marginalising sex workers

The Hypoglycemic Effect of the Kelp on Diabetes Mellitus Model Induced by Alloxan in Rats

Hypoglycemic effects and the use of kelp in diabetes mellitus (DM) model rats induced by alloxan were investigated. Sixty healthy male rats were used to establish DM models by injecting alloxan intraperitoneally. Kelp powder was added to the general forage for the rats. The levels of fasting blood glucose (FBG) were determined by an automatic blood glucose device. Electrochemiluminescence immunoassay was applied to determine the serum levels of insulin. The serum levels of malondialdehyde (MDA) were measured by thiobarbituric acid assay and nitric oxide (NO) by nitrate reductase assay. The activities of superoxide dismutase (SOD) were determined by xanthinoxidase assay and glutathione peroxidase (GSH-Px) by chemical colorimetry. The shape and structure of islet cells were observed with Hematine-Eosin staining, and the expression of superoxide dismutase (SOD) and inducible nitric oxide synthase (iNOS) in islet cells were detected by immunohistochemical assay. The results showed that the serum levels of insulin after treatment with kelp powder increased significantly compared to those in the DM-model group, while the FBG in the medium-high dose treated groups decreased significantly compared to those in the DM-model group (P < 0.05). The levels of MDA and NO in the kelp powder groups were lower than those in the DM-model group, while the activities of SOD and GSH-Px were higher than those in the DM-model group, of which a significant difference existed between the medium-high dose treated groups and the DM-model group (P < 0.05). The shape and structure of islet cells improved with the up-expressing SOD and down-expressing iNOS in the medium-high dose treated groups compared to those in the DM-model group (P < 0.05). There were no significant differences between the medium and high dose treated groups, all above indexes (P > 0.05). It is suggested that kelp might aid recovery of the the islet cell secreting function and reduce the level of FBG by an antioxidant effect

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