Due to their biological interpretability,memristors are widely used to simulate synapses between artificial neural *** a type of neural network whose dynamic behavior can be explained,the coupling of resonant tunnelin...
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Due to their biological interpretability,memristors are widely used to simulate synapses between artificial neural *** a type of neural network whose dynamic behavior can be explained,the coupling of resonant tunneling diode-based cellular neural networks(RTD-CNNs)with memristors has rarely been reported in the ***,this paper designs a coupled RTD-CNN model with memristors(RTD-MCNN),investigating and analyzing the dynamic behavior of the *** on this model,a simple encryption scheme for the protection of digital images in police forensic applications is *** results show that the RTD-MCNN can have two positive Lyapunov exponents,and its output is influenced by the initial values,exhibiting ***,a set of amplitudes in its output sequence is affected by the internal parameters of the memristor,leading to nonlinear ***,the rich dynamic behaviors described above make the RTD-MCNN highly suitable for the design of chaos-based encryption schemes in the field of privacy *** tests and security analyses validate the effectiveness of this scheme.
Against the backdrop of electromagnetic space integration,the radio system of equipment platforms,such as next-generation aircraft,must possess multifunctional integration and electromagnetic stealth ***,the equipment...
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Against the backdrop of electromagnetic space integration,the radio system of equipment platforms,such as next-generation aircraft,must possess multifunctional integration and electromagnetic stealth ***,the equipment platforms need to evolve towards flat *** requirements pose significant technical challenges for antenna system *** antenna must possess ultra-wideband to facilitate multi-function integration through the use of continuous radio frequency synthetic *** order to ensure good aerodynamics of the flat airborne platform,it is required to implement conformal design,while the ultra-low profile is the greatest challenge in conformal *** this background,this work proposes a novel airborne tightly coupled antenna with ultra-low profile,ultra-wideband,and vertical-polarized omnidirectional *** antenna unit utilizes a long slot structure and implements circular conformal design,where the resistive frequency selection surface is used to expand the operating *** antenna has a profile height of only 0.047 times the low-frequency *** and measurement results show that it achieves an impedance bandwidth of nearly 12∶1 with omnidirectional beam coverage,which meets the requirements of multifunctional future airborne antennas.
Unmanned and aerial systems as interactors among different system components for communications,have opened up great opportunities for truth data discovery in Mobile Crowd Sensing(MCS)which has not been properly solve...
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Unmanned and aerial systems as interactors among different system components for communications,have opened up great opportunities for truth data discovery in Mobile Crowd Sensing(MCS)which has not been properly solved in the *** this paper,an Unmanned Aerial Vehicles-supported Intelligent Truth Discovery(UAV-ITD)scheme is proposed to obtain truth data at low-cost communications for *** main innovations of the UAV-ITD scheme are as follows:(1)UAV-ITD scheme takes the first step in employing UAV joint Deep Matrix Factorization(DMF)to discover truth data based on the trust mechanism for an Information Elicitation Without Verification(IEWV)problem in MCS.(2)This paper introduces a truth data discovery scheme for the first time that only needs to collect a part of n data samples to infer the data of the entire network with high accuracy,which saves more communication costs than most previous data collection schemes,where they collect n or kn data ***,we conducted extensive experiments to evaluate the UAV-ITD *** results show that compared with previous schemes,our scheme can reduce estimated truth error by 52.25%–96.09%,increase the accuracy of workers’trust evaluation by 0.68–61.82 times,and save recruitment costs by 24.08%–54.15%in truth data discovery.
This paper proposes a support vector machine (SVM) classification model based on the grey wolf optimizer (GWO) to solve high-dimensional nonlinear classification problems in industrial production and daily life. To ad...
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WiFi-based indoor positioning has emerged as a crucial technology for enabling smart consumer electronic applications, particularly in large-scale buildings. The construction of WiFi fingerprint databases using receiv...
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The Internet of Things(loT)has grown rapidly due to artificial intelligence driven edge *** enabling many new functions,edge computing devices expand the vulnerability surface and have become the target of malware ***...
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The Internet of Things(loT)has grown rapidly due to artificial intelligence driven edge *** enabling many new functions,edge computing devices expand the vulnerability surface and have become the target of malware ***,attackers have used advanced techniques to evade defenses by transforming their malware into functionality-preserving *** systematically analyze such evasion attacks and conduct a large-scale empirical study in this paper to evaluate their impact on *** specifically,we focus on two forms of evasion attacks:obfuscation and adversarial *** the best of our knowledge,this paper is the first to investigate and contrast the two families of evasion attacks *** apply 10 obfuscation attacks and 9 adversarial attacks to 2870 malware *** obtained findings are as follows.(1)Commercial Off-The-Shelf(COTS)malware detectors are vulnerable to evasion attacks.(2)Adversarial attacks affect COTS malware detectors slightly more effectively than obfuscated malware examples.(3)Code similarity detection approaches can be affected by obfuscated examples and are barely affected by adversarial attacks.(4)These attacks can preserve the functionality of original malware examples.
Model updates are exchanged between server(s) and participants in Federated Learning (FL), which can result in excessive delay, especially for large models. Existing communication-efficient FL approaches such as quant...
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Model updates are exchanged between server(s) and participants in Federated Learning (FL), which can result in excessive delay, especially for large models. Existing communication-efficient FL approaches such as quantization and top-k sampling apply compression to gradients assuming that gradients are sparse and can tolerate small deviations. This can hardly be applied to down-link transmission. In this work, we employ compressive sensing on model parameters instead of gradients and propose a two-way adaptive compression scheme, Cepe-FL, which exploits dictionary learning to project non-sparse model parameters into sparse representations to ensure reconstruction accuracy. Cepe-FL supports joint model reconstruction with drastic reduction in computational complexity from $O(n)$ to $O(1)$. Cepe-FL adjusts the compression ratio adaptively according to the training loss, achieving the best trade-off between communication and model precision. Furthermore, it demonstrates efficacy in defending against membership inference attacks since only compressed models are exchanged. We conduct extensive experiments on three image classification tasks and compare with three communication-efficient approaches including FedPAQ, FedAvg and T-FedAvg. Cepe-FL presents the best performance in all tasks under IID and non-IID scenarios. We also implement white-box membership inference attacks, and the results show Cepe-FL can significantly suppress success ratio of inference in comparison with other approaches. IEEE
Data sparsity poses a significant challenge for recommendation systems, prompting the research of Cross-Domain Recommendation (CDR). CDR aims to leverage more user-item interaction information from source domains to i...
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In recent years, deep learning has significantly advanced skin lesion segmentation. However, annotating medical image data is specialized and costly, while obtaining unlabeled medical data is easier. To address this c...
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Recent strides in the combination of Artificial Intelligence(AI),edge computing,and Internet of Things(IoT)technology have shown great potential to unlock the Edge Artificial Intelligence(Edge AI)era for various *** A...
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Recent strides in the combination of Artificial Intelligence(AI),edge computing,and Internet of Things(IoT)technology have shown great potential to unlock the Edge Artificial Intelligence(Edge AI)era for various *** AI systems have opened new opportunities for many areas,such as smart cities,Intelligent transportation systems,the digital economy,and so *** technological innovations in multiple dimensions blur the lines between the physical and digital worlds and provide more convenient smart living solutions for human society.
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