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Transfer learning and neural networks in predicting quadrupole deformation

Chinese Physics C 2024年第6期48卷 162-168页

作者：原林李佳星张鸿飞 School of Science Xi'an Polytechnic UniversityXi'an 710048China Engineering Research Center of Flexible Radiation Protection Technology Universities of Shaanxi ProvinceXi'an 710048China Xi'an Key Laboratory of Nuclear Protection Textile Equipment Technology Xi'an 710048China School of Physics Xi'an Jiaotong UniversityXi'an 710049China School of Nuclear Science and Technology Lanzhou UniversityLanzhou 730000China

Accurately determining the quadrupole deformation parameters of atomic nuclei is crucial for understanding their structural and dynamic *** study introduces an innovative approach that combines transfer learning techniques with neural networks to predict the quadrupole deformation parameters of even-even *** the application of this innovative technique,the quadrupole deformation parameters of 2331 even-even nuclei are successfully predicted within the nuclear region defined by proton numbers 8≤Z≤134 and neutron numbers N≥***,we discuss the impact of nuclear quadrupole deformation parameters on the capture cross-sections in heavy-ion fusion reactions,reconstructing the capture cross-sections for the reactions ^(48)Ca+^(244)Pu and ^(48)Ca+^(248)*** research offers new insights into the application of neural networks in nuclear physics and highlights the potential of merging advanced machine learning techniques with both theoretical and experimental data,particularly in fields where experimental data are limited.

关键词： nuclear deformation neural networks transfer learning heavy-ion fusion reactions

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Facile synthesis of W-Mo bimetallic oxides with high adsorption properties from secondary resources

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Tungsten 2024年第4期6卷 806-820页

作者： Jia-Li Cheng Yang-Si Liu Xiao-Li Xi Zuo-Ren Nie Collaborative Innovation Center of Capital Resource-Recycling Material Technology College of Materials Science and EngineeringBeijing University of TechnologyBeijing100124China National Engineering Laboratory for Industrial Big-Data Application Technology Beijing University of TechnologyBeijing100124China Key Laboratory of Advanced Functional Materials Ministry of EducationBeijing University of TechnologyBeijing100124China

A simple solvothermal method was used to obtain W-Mo bimetallic oxides from W-Mo alloy scrap,and pure metal powders were also used as the raw materials to simulate *** products had a sea urchin-like structure with abundant oxygen vacancies and the products prepared at low temperatures forms a sosoloid resembling orthorhombic W_(0.4)Mo_(0.6)O_(3).The WMo bimetallic oxide prepared at the reaction temperature of 120℃exhibited excellent selective adsorption performance for methylene blue(MB),which the adsorption rate of MB reached 99%in 12 min and the adsorption rate reached 90%after6 adsorption *** the W-Mo molar ratio is 1:3,the maximum adsorption capacity of sample for MB can reach1148 mg·g^(-1).The adsorption process followed the Langmuir and pseudo-second-order models,which is surface-controlled monolayer *** experimental results show the feasibility of preparing W-Mo bimetal oxide products from pure materials and *** process is simple and effective,which offered a potential approach for secondary resource recycling and reusing.

关键词： W-Mo bimetallic oxide Oxygen vacancy Selective adsorption W-Mo alloy scrap Solvothermal

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An Innovative K-Anonymity Privacy-Preserving Algorithm to Improve data Availability in the Context of Big data

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Computers, Materials & Continua 2024年第4期79卷 1561-1579页

作者： Linlin Yuan Tiantian Zhang Yuling Chen Yuxiang Yang Huang Li State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang550025China College of Information Engineering Guizhou Open UniversityGuiyang550025China Guizhou Academy of Tobacco Science Guiyang550025China

The development of technologies such as big data and blockchain has brought convenience to life,but at the same time,privacy and security issues are becoming more and more *** K-anonymity algorithm is an effective and low computational complexity privacy-preserving algorithm that can safeguard users’privacy by anonymizing big ***,the algorithm currently suffers from the problem of focusing only on improving user privacy while ignoring data *** addition,ignoring the impact of quasi-identified attributes on sensitive attributes causes the usability of the processed data on statistical analysis to be *** on this,we propose a new K-anonymity algorithm to solve the privacy security problem in the context of big data,while guaranteeing improved data ***,we construct a new information loss function based on the information quantity *** that different quasi-identification attributes have different impacts on sensitive attributes,we set weights for each quasi-identification attribute when designing the information loss *** addition,to reduce information loss,we improve K-anonymity in two ***,we make the loss of information smaller than in the original table while guaranteeing privacy based on common artificial intelligence algorithms,i.e.,greedy algorithm and 2-means clustering *** addition,we improve the 2-means clustering algorithm by designing a mean-center method to select the initial center of ***,we design the K-anonymity algorithm of this scheme based on the constructed information loss function,the improved 2-means clustering algorithm,and the greedy algorithm,which reduces the information ***,we experimentally demonstrate the effectiveness of the algorithm in improving the effect of 2-means clustering and reducing information loss.

关键词： Blockchain big data K-anonymity 2-means clustering greedy algorithm mean-center method

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Face Forgery Detection Based on Fine-Grained Clues and Noise Inconsistency

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2025年第1期6卷 144-158页

作者： Zhang, Dengyong He, Ruiyi Liao, Xin Li, Feng Chen, Jiaxin Yang, Gaobo Changsha University of Science and Technology Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation the School of Computer and Communication Engineering Changsha410114 China Hunan University Changsha410082 China

Deepfake detection has gained increasing research attention in media forensics, and a variety of works have been produced. However, subtle artifacts might be eliminated by compression, and the convolutional neural networks (CNNs)-based detectors are invalidated for fake face images with compression. In this work, we propose a two-stream network for deepfake detection. We observed that high-frequency noise features and spatial features are inherently complementary to each other. Thus, both spatial features and high-frequency noise features are exploited for face forgery detection. Specifically, we design a double-frequency transformer module (DFTM) to guide the learning of spatial features from local artifact regions. To effectively fuse spatial features and high-frequency noise features, a dual-domain attention fusion module (DDAFM) is designed. We also introduce a local relationship constraint loss, which requires only image-level labels, for model training. We evaluate the proposed approach on five large-scale benchmark datasets, and extensive experimental results demonstrate the proposed approach outperforms most SOTA works. © 2024 IEEE.

关键词： Frequency domain analysis

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AMHF-TP:Multifunctional therapeutic peptides prediction based on multi-granularity hierarchical features

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Quantitative Biology 2025年第1期13卷 127-141页

作者： Shouheng Tuo YanLing Zhu Jiangkun Lin Jiewei Jiang School of Computer Science and Technology Xi’an University of Posts and TelecommunicationsXi’anChina Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Xi’anChina Xi’an Key Laboratory of Big Data and Intelligent Computing Xi’anChina School of Electronic Engineering Xi’an University of Posts and TelecommunicationsXi’anChina

Multifunctional therapeutic peptides(MFTP)hold immense potential in diverse therapeutic contexts,yet their prediction and identification remain challenging due to the limitations of traditional methodologies,such as extensive training durations,limited sample sizes,and inadequate generalization *** address these issues,we present AMHF-TP,an advanced method for MFTP recognition that utilizes attention mechanisms and multi-granularity hierarchical features to enhance *** AMHF-TP is composed of four key components:a migration learning module that leverages pretrained models to extract atomic compositional features of MFTP sequences;a convolutional neural network and selfattention module that refine feature extraction from amino acid sequences and their secondary structures;a hypergraph module that constructs a hypergraph for complex similarity representation between MFTP sequences;and a hierarchical feature extraction module that integrates multimodal peptide sequence *** with leading methods,the proposed AMHF-TP demonstrates superior precision,accuracy,and coverage,underscoring its effectiveness and robustness in MFTP *** comparative analysis of separate hierarchical models and the combined model,as well as with five contemporary models,reveals AMHFTP’s exceptional performance and stability in recognition tasks.

关键词： deep learning hypergraph multifunctional therapeutic peptides multi-granularity hierarchical features

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Cross-Chain Asset Trading Scheme Without Trusted Third-Party 2nd

Cross-Chain Asset Trading Scheme Without Trusted Third-Party

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2nd International Conference on data Security and Privacy Protection, DSPP 2024

作者： Li, Bo Chen, Yuling Huang, Siyuan Yang, Yuxiang State Key Laboratory of Public Big Data College of Computer Science and Technology Guizhou University Guizhou Guiyang550025 China

ISBN: (纸本)9789819785391

The development of blockchain technology is influenced by user diversity and application scenarios, resulting in limitations on the applicability of assets. Although cloud computing is renowned for facilitating cross-chain token transfers, it lacks a robust trust mechanism. Existing cross-chain transaction solutions are typically confined to interactions between two blockchains or within established networks. Hence, constructing a trustless cross-chain transaction protocol remains a significant challenge. This study proposes a trustless third-party cross-chain asset trading solution, Vchain, based on a Blockchain of Blockchains architecture and driven by a relay chain. This solution supports various blockchain ecosystem accounts and leverages cloud computing to integrate external data sources and API calls to obtain the latest token exchange rates, ensuring transaction accuracy and real-time performance. Simulation results demonstrate that Vchain’s cross-chain transaction costs are 69.25% lower than those of existing models. The research indicates that Vchain offers significant advantages in enhancing transaction efficiency and reducing costs, effectively addressing current challenges in cross-chain transactions. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Asset transactions Cross-chain Relay chain

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A DE/WD/VM Hybrid Algorithm for Multiple-Constraint Synthesis of Concentric Ring Arrays

A DE/WD/VM Hybrid Algorithm for Multiple-Constraint Synthesi...

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2023 IEEE MTT-S International Wireless Symposium, IWS 2023

作者： Xie, Shaoyi Deng, Guangjian Guo, Letian Northwest Institution of Nuclear Technology Key Laboratory of Advanced Science and Technology on High Power Microwave China

ISBN: (纸本)9798350336535

a hybrid synthesis algorithm is proposed by combining differential evolutionary (DE) algorithm with weighting density (WD) method and vector mapping (VM) method to synthesize the radiation pattern of concentric ring arrays (CRAs) with multiple constraints. The constraints in the optimization process mainly include the total number of elements, the size of the array and the minimum spacing between the elements. Both numerical example and full wave simulation are presented to verify the effectiveness and stability of the proposed DE/WD/VM hybrid algorithm. © 2023 IEEE.

关键词： Directional patterns (antenna)

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Edge Computing Task Scheduling with Joint Blockchain and Task Caching in Industrial Internet

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Computers, Materials & Continua 2023年第4期75卷 2101-2117页

作者： Yanping Chen Xuyang Bai Xiaomin Jin Zhongmin Wang Fengwei Wang Li Ling School of Computer Science and Technology Xi’an University of Posts and TelecommunicationsXi’an710121China Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Xi’an710121China Xi’an Key Laboratory of Big Data and Intelligent Computing Xi’anShaanxi710121China ZTE Corporation Shenzhen51805China

Deploying task caching at edge servers has become an effectiveway to handle compute-intensive and latency-sensitive tasks on the industrialinternet. However, how to select the task scheduling location to reduce taskdelay and cost while ensuring the data security and reliable communicationof edge computing remains a challenge. To solve this problem, this paperestablishes a task scheduling model with joint blockchain and task cachingin the industrial internet and designs a novel blockchain-assisted cachingmechanism to enhance system security. In this paper, the task schedulingproblem, which couples the task scheduling decision, task caching decision,and blockchain reward, is formulated as the minimum weighted cost problemunder delay constraints. This is a mixed integer nonlinear problem, which isproved to be nonconvex and NP-hard. To solve the optimal solution, thispaper proposes a task scheduling strategy algorithm based on an improvedgenetic algorithm (IGA-TSPA) by improving the genetic algorithm initializationand mutation operations to reduce the size of the initial solutionspace and enhance the optimal solution convergence speed. In addition,an Improved Least Frequently Used algorithm is proposed to improve thecontent hit rate. Simulation results show that IGA-TSPA has a faster optimalsolution-solving ability and shorter running time compared with the existingedge computing scheduling algorithms. The established task scheduling modelnot only saves 62.19% of system overhead consumption in comparison withlocal computing but also has great significance in protecting data security,reducing task processing delay, and reducing system cost.

关键词： Edge computing task scheduling blockchain task caching industrial security

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data Aggregation Point Placement and Subnetwork Optimization for Smart Grids

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Computers, Materials & Continua 2025年第4期83卷 407-434页

作者： Tien-Wen Sung Wei Li Chao-Yang Lee Yuzhen Chen Qingjun Fang Fujian Provincial Key Laboratory of Big Data Mining and Applications College of Computer Science and MathematicsFujian University of TechnologyFuzhou350118China Department of Computer Science and Information Engineering National Yunlin University of Science and TechnologyYunlin640301TaiwanChina

To transmit customer power data collected by smart meters(SMs)to utility companies,data must first be transmitted to the corresponding data aggregation point(DAP)of the *** number of DAPs installed and the installation location greatly impact the whole *** the traditional DAP placement algorithm,the number of DAPs must be set in advance,but determining the best number of DAPs is difficult,which undoubtedly reduces the overall performance of the ***,the excessive gap between the loads of different DAPs is also an important factor affecting the quality of the *** address the above problems,this paper proposes a DAP placement algorithm,APSSA,based on the improved affinity propagation(AP)algorithm and sparrow search(SSA)algorithm,which can select the appropriate number of DAPs to be installed and the corresponding installation locations according to the number of SMs and their distribution locations in different *** algorithm adds an allocation mechanism to optimize the subnetwork in the *** is evaluated under three different areas and compared with other DAP placement *** experimental results validated that the method in this paper can reduce the network cost,shorten the average transmission distance,and reduce the load gap.

关键词： Smart grid data aggregation point placement network cost average transmission distance load gap

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Revisiting the island of hexadecapoledeformation nuclei in the A≈150 mass region:focusing on the model application to nuclear shapes and masses

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Communications in Theoretical Physics 2024年第2期76卷 74-88页

作者： Xiao-Yang Wei Hua-Lei Wang Zhen-Zhen Zhang Min-Liang Liu School of Physics and Microelectronics Zhengzhou UniversityZhengzhou 450001China Key Laboratory of High Precision Nuclear Spectroscopy Institute of Modern PhysicsChinese Academy of SciencesLanzhou 730000China School of Nuclear Science and Technology University of Chinese Academy of SciencesBeijing 100049China

Based on the potential-energy-surface calculation,the impact of different deformation degrees of freedom on a single-particle structure and binding energies in nuclei around^(152)Nd,located on one of the hexadecapole-deformation islands,is analyzed in a multi-dimensional deformation *** energy maps,curves and tables are presented to indicate nuclear *** calculated equilibrium deformations and binding energies with different potential parameters are compared with experimental data and other *** is found that the inclusion of the hexadecapole deformations,especially the axial one,can improve the theoretical description of both nuclear shapes and *** addition,our calculated potential-energy curve shows that a critical deformation-point,β_(2)≈0.4,exists—the triaxial(hexadecapole)deformation effect can be neglectable but the hexadecapole(triaxial)one plays an important role before(after)such a critical point.

关键词： hexadecapole deformation binding energy potential-energy-surface calculation nuclear property

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