With the development of modern sensor technology, the automatic movement of robot has become a reality, and improving the path planning performance of robot in dynamic and complex environment is an important development direction of mobile robot intelligence. In this research, based on the idea of hybrid path planning, whale optimization algorithm is introduced combined with computer perception te...
This paper dealt with the evaluation reliability, availability, maintainability, dependability, mean time between failures, and mean time to failure of series-parallel system. The system under investigation has four subsystems, namely subsystem A containing two units in cold standby, subsystem B and C possess one unit each, and subsystem D has two units in cold standby. Through the transition diag...
Leave-One-Outscores provide estimates of feature importance in neural networks for adversarial attacks. In this work, we present context-free word scores as a query-efficient alternative. Experiments show that these approximations are quite effective for black-box attacks on neural networks trained for text classification, particularly for CNNs. The model query count for this method scales as O(vo...
In contrast to a standard closed-set domain adaptation task, partial domain adaptation setup caters to a realistic scenario by relaxing the identical label set assumption. The fact of source label set subsuming the target label set, however, introduces few additional obstacles as training on private source category samples thwart relevant knowledge transfer and mislead the classification process. ...
Recent advances in deep learning techniques such as convolutional neural networks, recurrent neural network, and generative adversarial networks have achieved breakthroughs in many fields or in many real-world applications. For the problem of semantic image inpainting, the task of reconstructing meaningful missing pixels also demonstrates that deep neural networks can play an effective role. While...
In this paper, we study the robustness of graph convolutional networks (GCNs). Previous works have shown that GCNs are vulnerable to adversarial perturbation on adjacency or feature matrices of existing nodes; however, such attacks are usually unrealistic in real applications. For instance, in social network applications, the attacker will need to hack into either the client or server to change ex...
Recent study of adversarial attacks has revealed the vulnerability of modern deep learning models. That is, subtly crafted perturbations of the input can make a trained network with high accuracy and produce arbitrary incorrect predictions, while maintaining imperceptible to human vision system. In this paper, we introduce Block Switching (BS), a defense strategy against adversarial attacks based ...
Among different adversarial attacks on deep learning models for image classification, physical attacks have been considered easier to implement without assuming access to victims’ devices. In this paper, we propose a practical new pipeline for launching multiview robust physical-world attacks, by creating printable adversarial stickers for arbitrary objects. In particular, a 3D model is used to es...
Municipal solid waste management in developing countries like Nigeria did not consider benefits from reuse/recycling recovered
waste materials during solid waste evacuation and disposal. The benefits from recovered waste materials mostly go to informal waste vendors and scavengers. This study developed a multiobjective mathematical programming model for waste evacuation and disposal, considering ...
Compared to previous extensions, the q-rung orthopair fuzzy sets are superior to intuitionistic ones and Pythagorean ones because they allow decision-makers to use a more extensive domain to present judgment arguments. The purpose of this study is to explore the multicriteria group decision-making (MCGDM) problem with the q-rung orthopair trapezoidal fuzzy (q-ROTrF) context by employing Einstein t...
