Financial transaction systems have become the critical backbone of modern society, and the sharp increase in fraudulent transactions has become an unavoidable significant topic. Their presence poses a severe threat to...
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The main question this work aims at answering is: "can morphing attack detection (MAD) solutions be successfully developed based on synthetic data?". Towards that, this work introduces the first synthetic-ba...
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ISBN:
(数字)9781665487399
ISBN:
(纸本)9781665487405
The main question this work aims at answering is: "can morphing attack detection (MAD) solutions be successfully developed based on synthetic data?". Towards that, this work introduces the first synthetic-based MAD development dataset, namely the Synthetic Morphing Attack Detection Development dataset (SMDD). This dataset is utilized successfully to train three MAD backbones where it proved to lead to high MAD performance, even on completely unknown attack types. Additionally, an essential aspect of this work is the detailed legal analyses of the challenges of using and sharing real biometric data, rendering our proposed SMDD dataset extremely essential. The SMDD dataset, consisting of 30,000 attack and 50,000 bona fide samples, is publicly available for research purposes 1 .
In this paper, we propose a multi-functional reconfigurable intelligent surface (MF-RIS) assisted rate-splitting multiple access (RSMA) scheme to improve the spectral efficiency in the downlink communications. With th...
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Recently, federated learning (FL) has gained momentum because of its capability in preserving data privacy. To conduct model training by FL, multiple clients exchange model updates with a parameter server via Internet...
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ISBN:
(数字)9798350383508
ISBN:
(纸本)9798350383515
Recently, federated learning (FL) has gained momentum because of its capability in preserving data privacy. To conduct model training by FL, multiple clients exchange model updates with a parameter server via Internet. To accelerate the communication speed, it has been explored to deploy a programmable switch (PS) in lieu of the parameter server to coordinate clients. The challenge to deploy the PS in FL lies in its scarce memory space, prohibiting running memory consuming aggregation algorithms on the PS. To overcome this challenge, we propose Federated Learning in-network Aggregation with Compression (FediAC) algorithm, consisting of two phases: client voting and model aggregating. In the former phase, clients report their significant model update indices to the PS to estimate global significant model updates. In the latter phase, clients upload global significant model updates to the PS for aggregation. FediAC consumes much less memory space and communication traffic than existing works because the first phase can guarantee consensus compression across clients. The PS easily aligns model update indices to swiftly complete aggregation in the second phase. Finally, we conduct extensive experiments by using public datasets to demonstrate that FediAC remarkably surpasses the state-of-the-art baselines in terms of model accuracy and communication traffic.
Peridigm is a meshfree peridynamics code written in C++ for use on large-scale parallel computers. It was originally developed at Sandia National Laboratories and is currently managed as an open-source, community driv...
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This work develops a novel approach to exploit synthesized, approximate circuits for the ansatz of variational quantum algorithms (VQA) and demonstrates its effectiveness for NchooseK, a domain-specific language suppo...
This work develops a novel approach to exploit synthesized, approximate circuits for the ansatz of variational quantum algorithms (VQA) and demonstrates its effectiveness for NchooseK, a domain-specific language supporting quantum-based solving of constraint-based problems. Synthesis is generalized to produce parametric circuits of short depth in close approximation of the original circuit offline. This removes syn-thesis from the critical path (online) between repeated quantum circuit executions of VQA while reducing circuit depth, thereby resulting in higher fidelity results than the baseline without synthesis. Simulation experiments indicate improvements of 98% on average. Further, experiments indicate that this approach can obtain viable solutions when the baseline could not. All of this is achieved with an average variation in circuit depth of less than 10%.
Generalized structures capable of implementing both fractional-order and power-law controllers are presented in this work. The first one is an active-RC scheme, realized using one active element, while the second one ...
Generalized structures capable of implementing both fractional-order and power-law controllers are presented in this work. The first one is an active-RC scheme, realized using one active element, while the second one is a Field Programmable Analog Array implementation offering digital programming of the realized controller functions. The derivation of the rational integer-order approximation functions is achieved, in both cases, through the employment of a curve fitting based algorithm. The behavior of the presented structures is evaluated through simulation and experimental results.
In federated learning (FL), the servers are generally seen as omnipotent to distribute the full models to all clients. This is not the case in wireless systems. The broadcast of models inevitably excludes some users w...
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ISBN:
(数字)9798350351255
ISBN:
(纸本)9798350351262
In federated learning (FL), the servers are generally seen as omnipotent to distribute the full models to all clients. This is not the case in wireless systems. The broadcast of models inevitably excludes some users with poor channel gain but valuable computation power and diverse local data. In this paper, taking the various computation and communication capabilities of users into account, we propose a federated learning scheme incorporating unstructured model pruning and non-orthogonal transmission. The pruning process divides the model into the core and the extended parts, with the ratio adaptive to the users’ achievable working rates. With non-orthogonal transmission, the strong users get both parts of the model while the weak get only the core part. Simulation results show that the proposed scheme involves more users than traditional wireless FL and improves the accuracy of tasks within the given communication rounds.
The standard power-law filter functions of order less than one, as well as their inverse counterparts, are implemented using only one active element in this work. The corresponding transfer functions are realized as i...
The standard power-law filter functions of order less than one, as well as their inverse counterparts, are implemented using only one active element in this work. The corresponding transfer functions are realized as impedances ratio, and the associated non-integer-order impedances are approximated using a suitable approximation technique, for fitting their magnitude and phase frequency responses. The employment of the Current Feedback Operational Amplifier as active element also offers the capability of interconnecting the filter stages without the requirement of extra buffer stages. The behavior of the presented schemes is validated through simulation results, obtained using the OrCAD PSpice simulator.
Alzheimer's disease is the primary cause of dementia. Due to the sluggish rate of progression of Alzheimer's disease, individuals have the opportunity to start receiving therapy early through routine testing. ...
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