In this article,we investigate the dependence of nuclear temperature on emitting source neutron-proton(N/Z)asymmetry with light charged particles(LCPs)and intermediate mass fragments(IMFs)generated from intermediate-v...
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In this article,we investigate the dependence of nuclear temperature on emitting source neutron-proton(N/Z)asymmetry with light charged particles(LCPs)and intermediate mass fragments(IMFs)generated from intermediate-velocity sources in thirteen reaction systems with different N/Z asymmetries,^(64)Zn on^(112)Sn,and^(70)Zn,^(64)Ni on^(112,124)Sn,^(58,64)Ni,^(197)Au,and^(232)Th at 40 MeV/*** apparent temperature values of LCPs and IMFs from different systems are deduced from the measured yields using two helium-related and eight carbon-related double isotope ratio thermometers,***,the sequential decay effect on the experimental apparent temperature deduction with the double isotope ratio thermometers is quantitatively corrected explicitly with the aid of the quantum statistical *** present treatment is an improvement compared to our previous studies in which an indirect method was adopted to qualitatively consider the sequential decay effect.A negligible N/Z asymmetry dependence of the real temperature after the correction is quantitatively addressed in heavy-ion reactions at the present intermediate energy,where a change of o.1 units in source N/Z asymmetry corresponds to an absolute change in temperature of an order of 0.03 to 0.29 MeV on average for LCPs and *** conclusion is in close agreement with that inferred qualitatively via the indirect method in our previous studies.
Infrared and visible image fusion is a process whereby infrared and visible spectral images are combined to enhance the visual quality of the resulting image and to retain more detailed information. Traditional infrar...
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Currently,the challenge lies in the traditional intelligent algorithm’s ability to effectively address the e-hailing repositioning *** identifying the underlying characteristics in extensive traffic data within a lim...
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Currently,the challenge lies in the traditional intelligent algorithm’s ability to effectively address the e-hailing repositioning *** identifying the underlying characteristics in extensive traffic data within a limited timeframe is difficult,ultimately preventing the achievement of the most optimal *** paper suggests a hybrid computing architecture involving reinforcement learning and quantum annealing based on intuitive *** reasoning aims to enhance performance in scenarios with poor system robustness,complex tasks,and diverse goals.A deep learning model is constructed,trained to extract scene features,and combined with expert knowledge,then transformed into a quantum annealable *** final strategy is obtained using a D-wave quantum computer with quantum tunneling effect,which helps in finding optimal solutions by jumping out of local suboptimal *** on 400000 real data,four algorithms are compared:minimum-cost flow,sequential markov decision process,hot-dot strategy,and driver-prefer *** average total revenue increases by about 10%and vehicle utilization by about 15%in various *** summary,the proposed architecture effectively solves the e-hailing reposition problem,offering new directions for robust artificial intelligence in big data decision problems.
The reduced-order spectral-element time-domain method based on the proper orthogonal decomposition method is proposed to solve the electromagnetic scattering problem based on wave equation. The spectral-element time-d...
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- COPEC's educational research team designed the engineering Program Freshmen Motivation Week for 2023. It was specially designed to provide first-year engineering students with time to receive guidance and be mot...
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Aiming at the problem that precise equalization can not be carried out due to the poor consistency of the single battery, an active equalization method based on frequent item statistics and transfer power is proposed....
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A single Visible (VIS) image or Infrared (IR) image cannot clearly present the texture details and heat source information of the scene. The fusion task of IR images and VIS can combine the respective characteristics ...
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The data in the blockchain cannot be tampered with and the users are anonymous,which enables the blockchain to be a natural carrier for covert ***,the existing methods of covert communication in blockchain suffer from...
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The data in the blockchain cannot be tampered with and the users are anonymous,which enables the blockchain to be a natural carrier for covert ***,the existing methods of covert communication in blockchain suffer from the predefined channel structure,the capacity of a single transaction is not high,and the fixed transaction behaviors will lower the concealment of the communication ***,this paper proposes a derivation matrix-based covert communication method in *** uses dual-key to derive two types of blockchain addresses and then constructs an address matrix by dividing addresses into multiple layers to make full use of the redundancy of ***,to solve the problem of the lack of concealment caused by the fixed transaction behaviors,divide the rectangular matrix into square blocks with overlapping regions and then encrypt different blocks sequentially to make the transaction behaviors of the channel addresses match better with those of the real ***,the linear congruence algorithm is used to generate random sequence,which provides a random order for blocks encryption,and thus enhances the security of the encryption *** results show that this method can effectively reduce the abnormal transaction behaviors of addresses while ensuring the channel transmission efficiency.
An action recognition network that combines multi-level spatiotemporal feature fusion with an attention mechanism is proposed as a solution to the issues of single spatiotemporal feature scale extraction,information r...
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An action recognition network that combines multi-level spatiotemporal feature fusion with an attention mechanism is proposed as a solution to the issues of single spatiotemporal feature scale extraction,information redundancy,and insufficient extraction of frequency domain information in channels in 3D convolutional neural ***,based on 3D CNN,this paper designs a new multilevel spatiotemporal feature fusion(MSF)structure,which is embedded in the network model,mainly through multilevel spatiotemporal feature separation,splicing and fusion,to achieve the fusion of spatial perceptual fields and short-medium-long time series information at different scales with reduced network parameters;In the second step,a multi-frequency channel and spatiotemporal attention module(FSAM)is introduced to assign different frequency features and spatiotemporal features in the channels are assigned corresponding weights to reduce the information redundancy of the feature ***,we embed the proposed method into the R3D model,which replaced the 2D convolutional filters in the 2D Resnet with 3D convolutional filters and conduct extensive experimental validation on the small and medium-sized dataset UCF101 and the largesized dataset *** findings revealed that our model increased the recognition accuracy on both *** on the UCF101 dataset,in particular,demonstrate that our model outperforms R3D in terms of a maximum recognition accuracy improvement of 7.2%while using 34.2%fewer *** MSF and FSAM are migrated to another traditional 3D action recognition model named C3D for application *** test results based on UCF101 show that the recognition accuracy is improved by 8.9%,proving the strong generalization ability and universality of the method in this paper.
An anti-interference network of CNN-BiGRU for pipeline corrosion recognition assisted with fiber optic DAS system is proposed. For the recognition of seven corrosion degrees in high-interference environment, the propo...
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