We present a bi-directional Fano resonator, which is capable of spectral shape control by adjusting the continuum state. By addressing the reflection phase, we demonstrate sensitive-chromatic response for color contro...
详细信息
Reversible data hiding is widely utilized for secure communication and copyright protection. Recently, to improve embedding capacity and visual quality of stego-images, some Partial Reversible Data Hiding (PRDH) schem...
详细信息
This article reports two important mixed-signal building blocks using unipolar oxide thin-film transistors (TFTs) on a 30- μ m -thick polymide substrate, which find potential application in communication systems. The...
详细信息
The accuracy and timeliness tradeoff prevents Digital Twins (DTs) from realizing their full potential. High accuracy is crucial for decision-making, and timeliness is equally essential for responsiveness. Therefore, t...
详细信息
The paper presents an innovative approach for predicting breast cancer by employing fine-needle aspiration (FNA), the synthetic minority oversampling method (SMOTE), and a Cubic Support Vector Machine (c-SVM) to gener...
详细信息
This study explores the relationship between quiz question performance and preceding quiz activities, aiming to predict the former through the lens of diverse machine learning models. Our research explores four distin...
详细信息
This paper presents an indoor tracking algorithm model designed specifically for the unique scenario of supermarkets. Firstly, the UWB positioning technology is utilized to replace the RFID radio frequency positioning...
详细信息
Precision agriculture is a cutting-edge farming strategy that maximizes harvests by using cutting-edge technology and data-driven decision-making. Optical sensors and other Internet of Things (IoT) devices have great ...
详细信息
High-efficiency and low-cost knowledge sharing can improve the decision-making ability of autonomous vehicles by mining knowledge from the Internet of Vehicles(IoVs).However,it is challenging to ensure high efficiency...
详细信息
High-efficiency and low-cost knowledge sharing can improve the decision-making ability of autonomous vehicles by mining knowledge from the Internet of Vehicles(IoVs).However,it is challenging to ensure high efficiency of local data learning models while preventing privacy leakage in a high mobility *** order to protect data privacy and improve data learning efficiency in knowledge sharing,we propose an asynchronous federated broad learning(FBL)framework that integrates broad learning(BL)into federated learning(FL).In FBL,we design a broad fully connected model(BFCM)as a local model for training client *** enhance the wireless channel quality for knowledge sharing and reduce the communication and computation cost of participating clients,we construct a joint resource allocation and reconfigurable intelligent surface(RIS)configuration optimization framework for *** problem is decoupled into two convex *** to improve the resource scheduling efficiency in FBL,a double Davidon–Fletcher–Powell(DDFP)algorithm is presented to solve the time slot allocation and RIS configuration *** on the results of resource scheduling,we design a reward-allocation algorithm based on federated incentive learning(FIL)in FBL to compensate clients for their *** simulation results show that the proposed FBL framework achieves better performance than the comparison models in terms of efficiency,accuracy,and cost for knowledge sharing in the IoV.
Group-IV color centers in diamond (SiV–, GeV–, and SnV–) have emerged as leading solid-state spin-photon interfaces for quantum information processing applications. However, these qubits require cryogenic temperatu...
详细信息
Group-IV color centers in diamond (SiV–, GeV–, and SnV–) have emerged as leading solid-state spin-photon interfaces for quantum information processing applications. However, these qubits require cryogenic temperatures to achieve high fidelity operation due to interactions with the thermal phonon environment. In this paper, we (i) derive a detailed model of the decoherence from first-order acoustic phonon processes acting on the spin-orbit fine structure of these color centers, (ii) demonstrate agreement of the model's predicted coherence times with previous measurements, and (iii) identify regimes to suppress phonon-mediated decoherence by changing magnetic field and strain bias to allow higher temperature operation. This methodology enables prediction of decoherence processes in other color centers and solid-state qubit systems coupled to a thermal bath via a parasitic two-level system. By experiment-anchored decoherence models, we facilitate optimizing qubit coherence for specific applications and devices.
暂无评论