•The study focuses on the interaction between automated vehicles and human drivers.•Communicating via an eHMI increases the traffic efficiency and safety.•Traffic regulation is a key factor in ...determining the extent to which the eHMI is beneficial.•Experiencing an automation failure leads to less efficient driving behavior and lower ratings.
In the near future, automated vehicles (AVs) will enter the urban transport system. This fact will lead to mixed traffic consisting of AVs, human car drivers and vulnerable road users. Since the AV’s passenger no longer has to monitor the driving scene, conventional communication does not exist anymore, which is essential for traffic efficiency and safety. In research, there are plenty of studies focusing on how AVs could communicate with pedestrians. One approach is to use external human-machine interfaces (eHMIs) on the AV’s surface. In contrast to the studies dealing with AV-pedestrian communication, this paper focuses on communication strategies of AVs with drivers of regular vehicles in different road bottleneck scenarios. The eHMI development and design is building on previously defined requirements and on fundamentals of human visual perception. After designing several eHMI drafts, we conducted a user survey with 29 participants resulting in the final eHMI concept. The evaluation of the evolved eHMI was conducted in a driving simulator experiment with 43 participants investigating the AV-human driver interaction at road bottlenecks. The participants were assigned either to the experimental group being faced with the eHMI or to the baseline group without explicit communication. The results show significantly shorter passing times and fewer crashes among the human drivers in the group with the eHMI. Additionally, the paper researches the aftereffects of an automation failure, where the AV first yields the right of way and then changes its strategy and insisted on priority. Experiencing the automation failure is reflected in increased passing times, reduced acceptance ratings and a lower perceived usefulness. In conclusion, especially in unregulated bottleneck scenarios flawless communication via eHMIs increases traffic efficiency and safety.
•Probably because of the sudden emergence of the COVID-19 pandemic, at present, there are various facial recognition technology applied to people wearing masks. Detection of face masks is an ...extremely challenging task for the face detectors. This is because faces with masks have varied accommodations, various degrees of obstructions, and diversified mask types. Face Mask detection models have many variations. These can be divided into several categories like Boosting-based classification, Deformable Part Model-based classification and CNN base classification.•A model named as SSDMNV2 has been proposed in this paper for face mask detection using OpenCV Deep Neural Network (DNN), TensorFlow , Keras, and MobileNetV2 architecture which is used as an image classifier. OpenCV DNN used in SSDMNV2 contains SSD with ResNet-10 as backbone and is capable of detecting faces in most orientations. While MobileNetV2 used provides for lightweight and accurate predictions for classification based on whether a mask is worn or not. SSDMNV2 performs competently in differentiating images having frontal faces with masks from images having frontal faces without masks.•The SSDMNV2 model was also compared with different pre-existing models like LeNet-5, AlexNet, VGG-16, and ResNet-50 by training them on the same dataset, and the proposed model outperforms the other models in terms of accuracy, F1 score and FPS parameter. As a result SSDMNV2 model is easy to deploy on embedded devices which is not possible with heavy models and to do real-time detection using these models that requires good computational power and which is the sole purpose of the research.
Face mask detection had seen significant progress in the domains of Image processing and Computer vision, since the rise of the Covid-19 pandemic. Many face detection models have been created using several algorithms and techniques. The proposed approach in this paper uses deep learning, TensorFlow, Keras, and OpenCV to detect face masks. This model can be used for safety purposes since it is very resource efficient to deploy. The SSDMNV2 approach uses Single Shot Multibox Detector as a face detector and MobilenetV2 architecture as a framework for the classifier, which is very lightweight and can even be used in embedded devices (like NVIDIA Jetson Nano, Raspberry pi) to perform real-time mask detection. The technique deployed in this paper gives us an accuracy score of 0.9264 and an F1 score of 0.93. The dataset provided in this paper, was collected from various sources, can be used by other researchers for further advanced models such as those of face recognition, facial landmarks, and facial part detection process.
In this theory paper, we investigate training deep neural networks (DNNs) for classification via minimizing the information bottleneck (IB) functional. We show that the resulting optimization problem ...suffers from two severe issues: First, for deterministic DNNs, either the IB functional is infinite for almost all values of network parameters, making the optimization problem ill-posed, or it is piecewise constant, hence not admitting gradient-based optimization methods. Second, the invariance of the IB functional under bijections prevents it from capturing properties of the learned representation that are desirable for classification, such as robustness and simplicity. We argue that these issues are partly resolved for stochastic DNNs, DNNs that include a (hard or soft) decision rule, or by replacing the IB functional with related, but more well-behaved cost functions. We conclude that recent successes reported about training DNNs using the IB framework must be attributed to such solutions. As a side effect, our results indicate limitations of the IB framework for the analysis of DNNs. We also note that rather than trying to repair the inherent problems in the IB functional, a better approach may be to design regularizers on latent representation enforcing the desired properties directly.
Single necessary (but not sufficient) conditions are critically important for business theory and practice. Without them, the outcomes cannot occur, and other conditions cannot compensate for this ...absence. Currently two analytical approaches are available for identifying single necessary conditions: Necessary Condition Analysis (NCA), which was recently developed, and fuzzy-set qualitative comparative analysis (fsQCA), which is a more established approach. FsQCA normally focuses on sufficient but not necessary configurations, but can also identify necessary but not sufficient conditions. This study uses NCA to analyze two examples of empirical datasets published in the Journal of Business Research that use fsQCA to identify single necessary conditions. A comparison of the results of NCA and fsQCA shows that NCA can identify more necessary conditions than fsQCA and can specify the level of the condition that is required for a given level of the outcome.
Inheritance of the mitochondrial genome does not follow the rules of conventional Mendelian genetics. The mitochondrial DNA (mtDNA) is present in many copies per cell and is inherited through the ...maternal germline. In addition, mutations in the mtDNA will give rise to heteroplasmy, the coexistence of different mtDNA variants within a single cell, whose levels can vary considerably between cells, organs or organisms. The inheritance and subsequent accumulation of deleterious variants are the cause of severe progressive mitochondrial disorders and play a role in many other conditions, including aging, cancer and neurodegenerative disorders. Here, we discuss the processes that give rise to cell-to-cell variability in mtDNA composition, focussing on somatic mtDNA segregation and on less conventional sources of heteroplasmy: non-maternal inheritance and mtDNA recombination. Understanding how mtDNA variants and mutations emerge and evolve within an organism is of crucial importance to prevent and cure mitochondrial disease and can potentially impact more common aging-associated conditions.
Communication systems to date primarily aim at reliably communicating bit sequences. Such an approach provides efficient engineering designs that are agnostic to the meanings of the messages or to ...the goal that the message exchange aims to achieve. Next generation systems, however, can be potentially enriched by folding message semantics and goals of communication into their design. Further, these systems can be made cognizant of the context in which communication exchange takes place, thereby providing avenues for novel design insights. This tutorial summarizes the efforts to date, starting from its early adaptations, semantic-aware and task-oriented communications, covering the foundations, algorithms and potential implementations. The focus is on approaches that utilize information theory to provide the foundations, as well as the significant role of learning in semantics and task-aware communications.
Two recently published analyses make cases for severe bottlenecking of human populations occurring in the late Early Pleistocene, one case at about 0.9 Mya based on a genomic analysis of modern human ...populations and the low number of hominin sites of this age in Africa and the other at about 1.1 Mya based on an age inventory of sites of hominin presence in Eurasia. Both models point to climate change as the bottleneck trigger, albeit manifested at very different times, and have implications for human migrations as a mechanism to elude extinction at bottlenecking. Here, we assess the climatic and chronologic components of these models and suggest that the several hundred-thousand-year difference is largely an artifact of biases in the chronostratigraphic record of Eurasian hominin sites. We suggest that the best available data are consistent with the Galerian hypothesis expanded from Europe to Eurasia as a major migration pulse of fauna including hominins in the late Early Pleistocene as a consequence of the opening of land routes from Africa facilitated by a large sea level drop associated with the first major ice age of the Pleistocene and concurrent with widespread aridity across Africa that occurred during marine isotope stage 22 at ~0.9 Mya. This timing agrees with the independently dated bottleneck from genomic analysis of modern human populations and allows speculations about the relative roles of climate forcing on the survival of hominins.
We target the problem named unsupervised domain adaptive semantic segmentation. A key in this campaign consists in reducing the domain shift, so that a classifier based on labeled data from one ...domain can generalize well to other domains. With the advancement of adversarial learning method, recent works prefer the strategy of aligning the marginal distribution in the feature spaces for minimizing the domain discrepancy. However, based on the observance in experiments, only focusing on aligning global marginal distribution but ignoring the local joint distribution alignment fails to be the optimal choice. Other than that, the noisy factors existing in the feature spaces, which are not relevant to the target task, entangle with the domain invariant factors improperly and make the domain distribution alignment more difficult. To address those problems, we introduce two new modules, Significance-aware Information Bottleneck (SIB) and Category-level alignment (CLA), to construct a purified embedding-based category-level adversarial network. As the name suggests, our designed network, CLAN, can not only disentangle the noisy factors and suppress their influences for target tasks but also utilize those purified features to conduct a more delicate level domain calibration, i.e., global marginal distribution and local joint distribution alignment simultaneously. In three domain adaptation tasks, i.e., GTA5 <inline-formula><tex-math notation="LaTeX">\rightarrow</tex-math> <mml:math><mml:mo>→</mml:mo></mml:math><inline-graphic xlink:href="luo-ieq1-3064379.gif"/> </inline-formula> Cityscapes, SYNTHIA <inline-formula><tex-math notation="LaTeX">\rightarrow</tex-math> <mml:math><mml:mo>→</mml:mo></mml:math><inline-graphic xlink:href="luo-ieq2-3064379.gif"/> </inline-formula> Cityscapes and Cross Season, we validate that our proposed method matches the state of the art in segmentation accuracy.
A successful reintroduction of Phengaris teleius performed in the Netherlands by translocating 86 individuals from a Polish metapopulation in 1990 represents a unique opportunity to study changes in ...butterflies from a source and reintroduced metapopulation after such a common conservation practice. Using multilevel comparisons, we tested morphological and genetic changes that occurred after 30 generations since the reintroduction. We also assessed the climatic and connectivity changes that occurred over time in both metapopulation networks. Unexpectedly, we found more significant morphological changes in the current individuals from the source metapopulation, where both sexes had bigger hindwings with different shapes in comparison to the individuals from the original metapopulation in the year of the reintroduction and the ones from the current reintroduced metapopulation. The butterflies from the Dutch metapopulation also had smaller thorax width compared to the ones from the current source metapopulation. The observed morphological changes can be shaped by various factors like changes in climatic conditions and habitat connectivity. Additionally, the genetic analysis revealed a differentiation between the source and reintroduced metapopulation. We found a loss of half of the allelic richness and a bottleneck effect in the reintroduced metapopulation compared to the current Polish one. Our results show that Phengaris butterflies have the potential to adapt to new habitats and respond to climatic changes despite their complex life cycle. A proper long-term habitat management in reintroduced butterfly metapopulations and habitat restoration are key factors influencing the success of reintroduction.
•The morphology of the reintroduced butterflies is more stable than the non-translocated ones.•The habitat connectivity decreased in the source and increased in the reintroduced population.•The reintroduction reduced the genetic richness of the translocated population.•The genetic structure of the reintroduced population changed over 30 generations.
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