We solve the planar case of the urgent pursuit-evasion problem for players using various strategies of motion. The following options are considered: players perform piecewise-linear motions;the pursuer moves in a stra...
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Increased urbanization and climate change intensify urban heat islands and degrade air quality, making current mitigation strategies insufficient. Nature-based solutions (NBSs), such as parks, green walls, roofs, and ...
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We investigate the equilibrium stability and robustness in a class of moving target defense problems, in which players have both incomplete information and asymmetric cognition. We first establish a Bayesian Stackelbe...
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ISBN:
(数字)9798350316339
ISBN:
(纸本)9798350316346
We investigate the equilibrium stability and robustness in a class of moving target defense problems, in which players have both incomplete information and asymmetric cognition. We first establish a Bayesian Stackelberg game model for incomplete information and then employ a hypergame reformulation to address asymmetric cognition. With the core concept of the hyper Bayesian Nash equilibrium (HBNE), a condition for achieving both the strategic and cognitive stability in equilibria can be realized by solving linear equations. Moreover, to deal with players’ underlying perturbed knowledge, we study the equilibrium robustness by presenting a condition of robust HBNE under the given configuration. Experiments evaluate our theoretical results.
We investigate the equilibrium stability and robustness in a class of moving target defense problems, in which players have both incomplete information and asymmetric cognition. We first establish a Bayesian Stackelbe...
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Fog computing paradigm extends computing,communication,storage,and network resources to the network’s *** the fog layer is located between cloud and end-users,it can provide more convenience and timely services to **...
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Fog computing paradigm extends computing,communication,storage,and network resources to the network’s *** the fog layer is located between cloud and end-users,it can provide more convenience and timely services to ***,in fog computing(FC),attackers can behave as real fog nodes or end-users to provide malicious services in the *** attacker acts as an impersonator to impersonate other legitimate ***,in this work,we present a detection technique to secure the FC ***,we model a physical layer key generation based on wireless channel *** generate the secret keys between the legitimate users and avoid impersonators,we then consider a Double Sarsa technique to identify the impersonators at the receiver *** compare our proposed Double Sarsa technique with the other two methods to validate our work,i.e.,Sarsa and *** simulation results demonstrate that the method based on Double Sarsa outperforms Sarsa and Q-learning approaches in terms of false alarm rate(FAR),miss detection rate(MDR),and average error rate(AER).
In planar pursuit-evasion differential games considering a faster pursuer and slower evader, the interception points resulting from equilibrium strategies lie on the Apollonius circle. This property is instrumental fo...
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Mobile Edge Computing (MEC), an emerging computing paradigm, shifts computing and storage capabilities from the cloud to the network edge, aiming to meet the delay requirements of emerging applications and save backha...
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We present a generic framework for data augmentation via dependency subtree swapping that is applicable to machine translation. We extract corresponding subtrees from the dependency parse trees of the source and targe...
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As the fields of machine learning and computer vision are developing, facial recognition systems are becoming increasingly popular and are slowly being widely used in various fields like security, surveillance and med...
As the fields of machine learning and computer vision are developing, facial recognition systems are becoming increasingly popular and are slowly being widely used in various fields like security, surveillance and medicine. This paper presents the design and development of a facial recognition solution that works in a distributed context, given that the devices used for capturing the images do not have the ability to train models capable of achieving good enough accuracy on large amounts of data. Thus, a method is presented in which the detection of human faces and the characteristics extraction are done locally based on a pre-trained FaceNet model. These characteristics are sent to a strong processing unit where a global model is trained and then transferred back to the clients, where it can be used for recognition. Through experimental evaluation, we show that our solution is efficient and exhibits high accuracy values.
For a linear difference equation with the coefficients being computable sequences, we establish algorithmic undecidability of the problem of determining the dimension of the solution space including the case when some...
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