With the advancement of technology, data visualization has become one of the research hotspots. In big data analysis, data visualization is a very important means, and through visualization software, data related to s...
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There has been an increase in attacks on mobile devices,such as smartphones and tablets,due to their growing *** malware is one of the most dangerous threats,causing both security breaches and financial *** malware is...
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There has been an increase in attacks on mobile devices,such as smartphones and tablets,due to their growing *** malware is one of the most dangerous threats,causing both security breaches and financial *** malware is likely to continue to evolve and proliferate to carry out a variety of cybercrimes on mobile *** malware specifically targets Android operating system as it has grown in *** rapid proliferation of Android malware apps poses a significant security risk to users,making static and manual analysis of malicious files ***,efficient identification and classification of Androidmalicious files is *** ConvolutionalNeuralNetwork(CNN)basedmethods have been proposed in this regard;however,there is still room for performance *** this work,we propose a transfer learning and stacking approach to efficiently detect the Android malware files by utilizing two wellknown machine learning models,ResNet-50 and Support Vector Machine(SVM).The proposed model is trained on the DREBIN dataset by transforming malicious APK files into grayscale *** model yields higher performance measures than state-of-the-art works on the DREBIN dataset,where the reported measures are accuracy,recall,precision,and F1 measures of 97.8%,95.8%,95.7%,and 95.7%,respectively.
Regarding delay-induced predator-prey models, much research has been done on delayed destabilization, but whether delays are stabilizing or destabilizing is a subtle issue. In this study, we investigate predator-prey ...
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Regarding delay-induced predator-prey models, much research has been done on delayed destabilization, but whether delays are stabilizing or destabilizing is a subtle issue. In this study, we investigate predator-prey dynamics affected by both delays and the Allee effect. We analyze the consequences of delays in different feedback mechanisms. The existence of a Hopf bifurcation is studied, and we calculate the value of the delay that leads to the Hopf bifurcation. Furthermore, applying the normal form theory and a center manifold theorem, we consider the direction and stability of the Hopf bifurcation. Finally, we present numerical experiments that validate our theoretical analysis. Interestingly, depending on the chosen delay mechanism, we find that delays are not necessarily destabilizing. The Allee effect generally increases the stability of the equilibrium, and when the Allee effect involves a delay term, the stabilization effect is more pronounced.
Latent confounding bias and collider bias are two key challenges of causal inference in observational studies. Latent confounding bias occurs when failing to control the unmeasured covariates that are common causes of...
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Latent confounding bias and collider bias are two key challenges of causal inference in observational studies. Latent confounding bias occurs when failing to control the unmeasured covariates that are common causes of treatments and outcomes, which can be addressed by using the Instrumental Variable (IV) approach. Collider bias comes from non-random sample selection caused by both treatments and outcomes, which can be addressed by using a different type of instruments, i.e., shadow variables. However, in most scenarios, these two biases simultaneously exist in observational data, and the previous methods focusing on either one are inadequate. To the best of our knowledge, no approach has been developed for causal inference when both biases exist. In this paper, we propose a novel IV approach, Two-Stage Shadow Inclusion (2SSI), which can simultaneously address latent confounding bias and collider bias by utilizing the residual of the treatment as a shadow variable. Extensive experimental results on benchmark synthetic datasets and a real-world dataset show that 2SSI achieves noticeable performance improvement when both biases exist compared to existing methods. Copyright 2024 by the author(s)
This article deals with questions of organization online schoolchildren training using interactive posters as multidimensional didactic tools for a computerscience teacher. The concept of 'interactive posters'...
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The focus of this paper is the integration of artificial intelligence (AI) within the educational field including but not limited to, adaptive learning, teaching evaluation, online learning environments, and individua...
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The inclusion-exclusion principle together with Legendre type theorems for number of distinct restricted partitions weighted by the parity of their length are used to give several recurrence relations for restricted p...
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To give shift in safety protocols, we have employed advanced deep learning algorithms and frameworks (Shrestha and Mahmood in IEEE Access 7:53,040–53,065, 2019 [25]) to construct an innovative AI model. The designed ...
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This study introduces a novel control framework for human-drone interaction (HDI) in industrial warehouses, targeting pick-and-delivery operations. The goals are to enhance operator safety as well as well-being and, a...
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This study introduces a novel control framework for human-drone interaction (HDI) in industrial warehouses, targeting pick-and-delivery operations. The goals are to enhance operator safety as well as well-being and, at the same time, to improve efficiency and reduce production costs. To these aims, the speed and separation monitoring (SSM) operation method is employed for the first time in HDI, drawing an analogy to the safety requirements outlined in collaborative robots' ISO standards. The so-called protective separation distance is used to ensure the safety of operators engaged in collaborative tasks with drones. In addition, we employ the rapid upper limb assessment (RULA) method to evaluate the ergonomic posture of operators during interactions with drones. To validate the proposed approach in a realistic industrial setting, a quadrotor is deployed for pick-and-delivery tasks along a predefined trajectory from the picking bay to the palletizing area, where the interaction between the drone and a moving operator takes place. The drone navigates toward the interaction space while avoiding collisions with shelves and other drones in motion. The control strategy for the drone cruise navigation integrates simultaneously the time-variant artificial potential field (APF) technique for trajectory planning and the iterative linear quadratic regulator (LQR) controller for trajectory tracking. Differently, in the descent phase, the receding horizon LQR algorithm is employed to follow a trajectory planned in accordance with the SSM, which starts from the approach point at the border of the interaction space and ends in the volume with the operator's minimum RULA. The presented control strategy facilitates drone management by adapting the drone's position to changes in the operator's position while satisfying HDI safety requirements. The results of the proposed HDI framework simulations for the case study demonstrate the effectiveness of the method in ensuring a safe and er
We analyze an aggregated dynamic model for the development of gas fields. The same company consistently drills all fields. We pose and solve the problem of maximizing accumulated gas production over a predetermined pe...
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