Two-dimensional(2D)transition-metal dichalcogenides(TMDs)materials have unique band structure as well as excellent electrical and optical properties,which exhibit great advantages in optoelectronic *** vapor depositio...
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Two-dimensional(2D)transition-metal dichalcogenides(TMDs)materials have unique band structure as well as excellent electrical and optical properties,which exhibit great advantages in optoelectronic *** vapor deposition(CVD),a method to realize the synthesis of large-scale 2D TMDs materials,will inevitably introduce defects in the growth process,thus decreasing the performance of 2D TMDs-based optoelectronic *** order to fundamentally address this issue,we proposed a method to gradually regulate the reaction concentration of precursor during *** a result,the suitable concentration of precursor can effectively enhance the probability of covalent binding of X-M(X:S,Se,etc.;M:Mo,W,etc.),thus suppressing the generation of vacancy ***,we explored sulfur vacancy(V_(S))on the performance of 2D molybdenum disulfide-based(MoS_(2)-based)self-powered devices through constructing p-type silicon/MoS_(2)(p-Si/MoS_(2))based p-n *** photodetector composed of optimized MoS_(2) nanosheets exhibited high responsivity(330.14 A·W^(-1)),fast response speed(40μs/133μs),and excellent photovoltage *** method of regulating the low temperature region during CVD growth can realize the preparation of high-quality TMDs films and be applied in high-performance optoelectronic devices.
Partial maximum satisfiability(PMS) is a significant generalization of Boolean satisfiability(SAT) and maximum satisfiability(MaxSAT), by introducing hard clauses and soft clauses. Compared with SAT and MaxSAT, the PM...
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Partial maximum satisfiability(PMS) is a significant generalization of Boolean satisfiability(SAT) and maximum satisfiability(MaxSAT), by introducing hard clauses and soft clauses. Compared with SAT and MaxSAT, the PMS problem has more real-world applications where both hard and soft constraints are involved. Local search is an effective incomplete method for solving PMS and is useful for important domains where good-quality solutions are desired within reasonable *** local search PMS solvers, the approach for initial assignment generation is crucial because its effectiveness significantly affects practical performance. In this study, we propose a novel initial assignment prediction approach, called InitPMS. When predicting an assignment for PMS, InitPMS considers the specific structure of PMS instances, i.e., distinguishing hard and soft clauses. Our experiments on extensive PMS instances from MaxSAT evaluations(MSEs) 2020 and 2021 show that InitPMS significantly boosts the performance of five state-of-the-art local search PMS solvers, demonstrating its generality. In addition,our results indicate that incorporating InitPMS could improve the performance of one of the best incomplete PMS solvers in MaxSAT Evaluation 2021, indicating that InitPMS might help advance the state of the art in PMS solving.
In this paper, Eu3+-Tb3+-Pr3+ triple-doped Gd2O3 phosphors based on solar-blind ultraviolet band response were successfully prepared by the hydrothermal method. All the phosphor samples exhibit excellent crystallinity...
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Implementing quantum wireless multi-hop network communication is essential to improve the global quantum network system. In this paper, we employ eight-level GHZ states as quantum channels to realize multi-hop quantum...
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Implementing quantum wireless multi-hop network communication is essential to improve the global quantum network system. In this paper, we employ eight-level GHZ states as quantum channels to realize multi-hop quantum communication, and utilize the logical relationship between the measurements of each node to derive the unitary operation performed by the end node. The hierarchical simultaneous entanglement switching(HSES) method is adopted, resulting in a significant reduction in the consumption of classical information compared to multi-hop quantum teleportation(QT)based on general simultaneous entanglement switching(SES). In addition, the proposed protocol is simulated on the IBM Quantum Experiment platform(IBM QE). Then, the data obtained from the experiment are analyzed using quantum state tomography, which verifies the protocol's good fidelity and accuracy. Finally, by calculating fidelity, we analyze the impact of four different types of noise(phase-damping, amplitude-damping, phase-flip and bit-flip) in this protocol.
The rapid development of ISAs has brought the issue of software compatibility to the forefront in the embedded *** address this challenge,one of the promising solutions is the adoption of a multiple-ISA processor that...
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The rapid development of ISAs has brought the issue of software compatibility to the forefront in the embedded *** address this challenge,one of the promising solutions is the adoption of a multiple-ISA processor that supports multiple different ***,due to constraints in cost and performance,the architecture of a multiple-ISA processor must be carefully optimized to meet the specific requirements of embedded *** exploring the RISC-V and ARM Thumb ISAs,this paper proposes RVAM16,which is an optimized multiple-ISA processor microarchitecture for embedded devices based on hardware binary translation *** results show that,when running non-native ARM Thumb programs,RVAM16 achieves a significant speedup of over 2.73×with less area and energy consumption compared to using hardware binary translation alone,reaching more than 70%of the performance of native RISC-V programs.
The coronavirus disease 2019(COVID-19)has severely disrupted both human life and the health care *** diagnosis and treatment have become increasingly important;however,the distribution and size of lesions vary widely ...
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The coronavirus disease 2019(COVID-19)has severely disrupted both human life and the health care *** diagnosis and treatment have become increasingly important;however,the distribution and size of lesions vary widely among individuals,making it challenging to accurately diagnose the *** study proposed a deep-learning disease diagnosismodel based onweakly supervised learning and clustering visualization(W_CVNet)that fused classification with ***,the data were *** optimizable weakly supervised segmentation preprocessing method(O-WSSPM)was used to remove redundant data and solve the category imbalance ***,a deep-learning fusion method was used for feature extraction and classification recognition.A dual asymmetric complementary bilinear feature extraction method(D-CBM)was used to fully extract complementary features,which solved the problem of insufficient feature extraction by a single deep learning ***,an unsupervised learning method based on Fuzzy C-Means(FCM)clustering was used to segment and visualize COVID-19 lesions enabling physicians to accurately assess lesion distribution and disease *** this study,5-fold cross-validation methods were used,and the results showed that the network had an average classification accuracy of 85.8%,outperforming six recent advanced classification models.W_CVNet can effectively help physicians with automated aid in diagnosis to determine if the disease is present and,in the case of COVID-19 patients,to further predict the area of the lesion.
Intelligent assembly of large-scale,complex structures using an intelligent manufacturing platform represents the future development direction for industrial *** large-scale structural assembly processes,several bottl...
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Intelligent assembly of large-scale,complex structures using an intelligent manufacturing platform represents the future development direction for industrial *** large-scale structural assembly processes,several bottleneck problems occur in the existing auxiliary assembly ***,the traditional LiDARbased assembly technology is often limited by the openness of the manufacturing environment,in which there are blind spots,and continuous online assembly adjustment thus cannot be ***,for assembly of large structures,a single-station LiDAR system cannot achieve complete coverage,which means that a multi-station combination method must be used to acquire the complete three-dimensional data;many more data errors are caused by the transfer between stations than by the measurement accuracy of a single station,which means that the overall system's measurement and adjustment errors are increased ***,because of the large numbers of structural components contained in a large assembly,the accumulated errors may lead to assembly interference,but the LiDAR-assisted assembly process does not have a feedback perception capability,and thus assembly component loss can easily be caused when assembly interference ***,this paper proposes to combine an optical fiber sensor network with digital twin technology,which will allow the test data from the assembly entity state in the real world to be applied to the"twin"model in the virtual world and thus solve the problems with test openness and data *** problem of station and perception feedback is also addressed and represents the main innovation of this *** system uses an optical fiber sensor network as a flexible sensing medium to monitor the strain field distribution within a complex area in real time,and then completes real-time parameter adjustment of the virtual assembly based on the distributed *** areas include areas that are laser-unreachable,areas wi
Motor imagery electroencephalography (MI-EEG) is widely used in the neural rehabilitation field, including for hybrid device control, such as robotic arms. However, it is difficult to apply large models with good perf...
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In a crowd density estimation dataset,the annotation of crowd locations is an extremely laborious task,and they are not taken into the evaluation *** this paper,we aim to reduce the annotation cost of crowd datasets,a...
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In a crowd density estimation dataset,the annotation of crowd locations is an extremely laborious task,and they are not taken into the evaluation *** this paper,we aim to reduce the annotation cost of crowd datasets,and propose a crowd density estimation method based on weakly-supervised learning,in the absence of crowd position supervision information,which directly reduces the number of crowds by using the number of pedestrians in the image as the supervised *** this purpose,we design a new training method,which exploits the correlation between global and local image features by incremental learning to train the ***,we design a parent-child network(PC-Net)focusing on the global and local image respectively,and propose a linear feature calibration structure to train the PC-Net simultaneously,and the child network learns feature transfer factors and feature bias weights,and uses the transfer factors and bias weights to linearly feature calibrate the features extracted from the Parent network,to improve the convergence of the network by using local features hidden in the crowd *** addition,we use the pyramid vision transformer as the backbone of the PC-Net to extract crowd features at different levels,and design a global-local feature loss function(L2).We combine it with a crowd counting loss(LC)to enhance the sensitivity of the network to crowd features during the training process,which effectively improves the accuracy of crowd density *** experimental results show that the PC-Net significantly reduces the gap between fullysupervised and weakly-supervised crowd density estimation,and outperforms the comparison methods on five datasets of Shanghai Tech Part A,ShanghaiTech Part B,UCF_CC_50,UCF_QNRF and JHU-CROWD++.
Thanks to its ubiquity,using radio frequency (RF) signals for sensing has found widespread *** traditional integrated sensing and communication systems,such as joint radar-communication systems,common sensing tasks in...
Thanks to its ubiquity,using radio frequency (RF) signals for sensing has found widespread *** traditional integrated sensing and communication systems,such as joint radar-communication systems,common sensing tasks include target localization and ***,increasingly intelligent systems,such as smart agriculture,lowaltitude economy,and smart healthcare,have demanded more comprehensive and continuous information sensing capabilities to support higher-level *** sensing has the potential to offer both spatial and temporal continuity,meeting the multi-dimensional sensing needs of these intelligent ***,numerous advanced systems have been proposed,expanding the application scope of RF sensing to be more pervasive,including discrete state ubiquitous sensing tasks (such as material identification [1]),and continuous state ubiquitous sensing tasks (such as health monitoring [2]).With the advent of the 6G era,it is anticipated that the sensing potential of RF systems will be further unleashed.
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