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Microstructure evolution of extruded Mg-RE-Ag alloy during short-time heat treatment

Journal of Rare Earths 2024年第12期42卷 2350-2361,I0006页

作者： Zehua Li Jinghuai Zhang Shujuan Liu Jiaming Hao Liyuan Liu Yuying He Haodong Zhang Xingkai Jiao Xiaobo Zhang Ruizhi Wu Key Laboratory of Superlight Material and Surface Technology Ministry of EducationCollege of Material Science and Chemical EngineeringHarbin Engineering UniversityHarbin150001China School of Materials Science and Engineering Harbin Institute of TechnologyHarbin150001China Jiangsu Key Laboratory of Advanced Structural Materials and Application Technology Nanjing Institute of TechnologyNanjing211167China

Microstructure regulation via short-time heat treatment is conducive to the optimization in the microstructure and properties of precipitable magnesium(Mg)alloys,but there is currently a lack of relevant *** this work,the microstructure evolution of a Mg-RE-Ag alloy during different short-time heat treatments was characterized and *** results show that extreme short-time heat treatment(ESHT,e.g.,2 min)at 450-480℃can greatly increase solute concentration in Mg matrix through the rapid re-dissolution of the second-phase and simultaneously maintain fine grains,while the ESHT at a too high temperature(e.g.,510℃)is not suitable due to excessive grain growth and coarse second phase regenerated at grain *** is found that 480℃is the approximate critical temperature for appropriate ESHT,and further prolongation of the time will lead to excessive grain *** is suggested that in addition to grain boundary migration,grain rotation is activated,resulting in the annihilation of high-angle grain boundaries with relatively low misorientation,as well as the reduction in the ability of the residual second phase to pin grain *** addition,the reasons for the abnormal grain boundary segregation and grain boundary continuous phase were analyzed from the perspective of interfacial *** study provides a basis for effective microstructure regulation of Mg-RE alloys.

关键词： Magnesium alloy Rare earths Microstructure Heat treatment Precipitates

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RCCA-SM9: securing SM9 on corrupted machines

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science China(Information sciences) 2024年第11期67卷 106-120页

作者： Rongmao CHEN Jinrong CHEN Xinyi HUANG Yi WANG College of Computer National University of Defense Technology Artificial Intelligence Thrust Information Hub Hong Kong University of Science and Technology (Guangzhou)

The SM9 identity-based encryption(IBE) scheme is a cryptographic standard used in China, and has been incorporated into the ISO/IEC standard in 2021. This work primarily proposes a countermeasure to secure the SM9 IBE scheme if its implementation is tampered with or deviated from the standard *** attacks, known as subversion attacks, are feasible and powerful in real-world cryptographic application scenarios. Our goal is to design a subversion-resilient variant of the SM9 IBE scheme, primarily using the cryptographic reverse firewall(CRF) proposed by Mironov and Stephens-Davidowitz at EUROCRYPT 2015.A CRF can sanitize cryptographic transcripts to eliminate covert channels, necessitating that the underlying primitive be rerandomizable. Unfortunately, the rerandomizability of the SM9 IBE scheme is disabled for ensuring security against chosen ciphertext attack(CCA). Hence, we shift our focus to a relaxed version of CCA security called RCCA security, offering security guarantees comparable to CCA security while allowing for ciphertext rerandomization. For this purpose, we design an efficient and RCCA-secure variant of the SM9 IBE scheme with provable security that can integrate with CRFs to achieve subversion resilience.

关键词： SM9 subversion resilience subversion attack cryptographic reverse firewall RCCA

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Maximizing Overall Service Profit:Multi-Edge Service Pricing as a Stochastic Game Model

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Tsinghua science and technology 2024年第6期29卷 1872-1889页

作者： Shengye Pang Xinkui Zhao Jiayin Luo Jintao Chen Fan Wang Jianwei Yin College of Computer Science and Technology Zhejiang UniversityHangzhou 310058China School of Software Technology Zhejiang UniversityNingbo 315048China

The diversified development of the service ecosystem,particularly the rapid growth of services like cloud and edge computing,has propelled the flourishing expansion of the service trading ***,in the absence of appropriate pricing guidance,service providers often devise pricing strategies solely based on their own interests,potentially hindering the maximization of overall market *** challenge is even more severe in edge computing scenarios,as different edge service providers are dispersed across various regions and influenced by multiple factors,making it challenging to establish a unified pricing *** paper introduces a multi-participant stochastic game model to formalize the pricing problem of multiple edge ***,an incentive mechanism based on Pareto improvement is proposed to drive the game towards Pareto optimal direction,achieving optimal ***,an enhanced PSO algorithm was proposed by adaptively optimizing inertia factor across three *** optimization significantly improved the efficiency of solving the game model and analyzed equilibrium states under various evolutionary *** results demonstrate that the proposed pricing incentive mechanism promotes more effective and rational pricing allocations,while also demonstrating the effectiveness of our algorithm in resolving game problems.

关键词： service pricing game theory incentive mechanism Pareto improvement equilibrium solution

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Maternal supplementation with konjac glucomannan and κ-carrageenan promotes sow performance and benefits the gut barrier in offspring

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Animal Nutrition 2024年第4期19卷 272-286页

作者： Feng Gao Yongqing Du Haiyang Liu Hongwei Ding Wentao Zhang Zhongyu Li Baoming Shi College of Animal Science and Technology Northeast Agricultural UniversityHarbin 150030Heilongjiang ProvinceChina

This research aims to investigate the effects of dietary konjac glucomannan and κ-carrageenan(SF) on sow performance and suckling piglet gut barrier. Thirty-four sows in late gestation(parity 2-5) were selected at random and grouped into two treatments. The control group(Con group;n = 17) was fed the basal diet;the SF group was fed the same diet supplemented with 0.25% konjac glucomannan + 0.25% κ-carrageenan(SF group;n = 17). The results showed that sows fed the SF diet had a higher feed intake during lactation than the Con group(P < 0.05), and the levels of neuropeptide tyrosine(NPY)(P = 0.006)and acetylcholine enzyme(AChE)(P < 0.05) significantly increased. The fecal microbial analysis indicated that the SF diet had a higher abundance of Subdoligranulum, Holdemanella, and Succinivibrio at the genus level, and the acetate level was significantly increased(P < 0.05). Moreover, SF lowered the level of interleukin-6(IL-6) in milk(P < 0.05). Regarding suckling piglets, maternal supplementation with SF reduced jejunal IL-6 protein levels in suckling piglets(P < 0.05). In the colon of the piglet, the SF group up-regulated protein levels of occludin(P < 0.05), and the nuclear factor erythroid 2-related factor 2(Nrf2)(0.05 ≤ P < 0.10), and claudin 4(CLDN4)(0.05 ≤ P < 0.10) protein levels tended to be ***, supplementation of SF in sow diets positively affects lactation feed intake and maternal microflora. Furthermore, the maternal effect improves the jejunum and colon barriers of suckling piglets.

关键词： Konjac glucomannan Kappa-carrageenan Sow Suckling piglet Gut barrier

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Deep learning-based software engineering: progress,challenges, and opportunities

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science China(Information sciences) 2025年第1期68卷 57-144页

作者： Xiangping CHEN Xing HU Yuan HUANG He JIANG Weixing JI Yanjie JIANG Yanyan JIANG Bo LIU Hui LIU Xiaochen LI Xiaoli LIAN Guozhu MENG Xin PENG Hailong SUN Lin SHI Bo WANG Chong WANG Jiayi WANG Tiantian WANG Jifeng XUAN Xin XIA Yibiao YANG Yixin YANG Li ZHANG Yuming ZHOU Lu ZHANG School of Journalism and Communication Sun Yat-sen University School of Software Technology Zhejiang University School of Software Engineering Sun Yat-sen University School of Software Dalian University of Technology School of Computer Science and Technology Beijing Institute of Technology Key Laboratory of High Confidence Software Technologies (Peking University) Ministry of EducationSchool of Computer Science Peking University State Key Laboratory for Novel Software Technology Nanjing University School of Computer Science and Engineering Beihang University Institute of Information Engineering Chinese Academy of Sciences School of Computer Science Fudan University State Key Laboratory of Complex & Critical Software Environment (CCSE) School of Software Beihang University School of Computer and Information Technology Beijing Jiaotong University School of Computer Science and Technology Harbin Institute of Technology School of Computer Science Wuhan University Huawei Technologies

Researchers have recently achieved significant advances in deep learning techniques, which in turn has substantially advanced other research disciplines, such as natural language processing, image processing, speech recognition, and software engineering. Various deep learning techniques have been successfully employed to facilitate software engineering tasks, including code generation, software refactoring, and fault localization. Many studies have also been presented in top conferences and journals, demonstrating the applications of deep learning techniques in resolving various software engineering tasks. However,although several surveys have provided overall pictures of the application of deep learning techniques in software engineering,they focus more on learning techniques, that is, what kind of deep learning techniques are employed and how deep models are trained or fine-tuned for software engineering tasks. We still lack surveys explaining the advances of subareas in software engineering driven by deep learning techniques, as well as challenges and opportunities in each subarea. To this end, in this study, we present the first task-oriented survey on deep learning-based software engineering. It covers twelve major software engineering subareas significantly impacted by deep learning techniques. Such subareas spread out through the whole lifecycle of software development and maintenance, including requirements engineering, software development, testing, maintenance, and developer collaboration. As we believe that deep learning may provide an opportunity to revolutionize the whole discipline of software engineering, providing one survey covering as many subareas as possible in software engineering can help future research push forward the frontier of deep learning-based software engineering more systematically. For each of the selected subareas,we highlight the major advances achieved by applying deep learning techniques with pointers to the available datasets i

关键词： deep learning software engineering software benchmark software artifact representation survey

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Improved quantum(t,n)threshold group signature

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Chinese Physics B 2023年第9期32卷 184-191页

作者：张耀东刘锋左海新 College of Computer Science and Technology Shandong Technology and Business UniversityYantai 264005China College of Mathematic and Information Science Shandong Technology and Business UniversityYantai 264005China

Threshold signature is an important branch of the digital signature scheme,which can distribute signature rights and avoid the abuse of signature *** the continuous development of quantum computation and quantum information,quantum threshold signatures are gradually becoming more ***,a quantum(t,n)threshold group signature scheme was analyzed that uses techniques such as quantum-controlled-not operation and quantum ***,this scheme cannot resist forgery attack and does not conform to the design of a threshold signature in the signing *** on the original scheme,we propose an improved quantum(t,n)threshold signature scheme using quantum(t,n)threshold secret sharing *** analysis proves that the improved scheme can resist forgery attack and collusion attack,and it is *** the same time,this scheme reduces the level of trust in the arbitrator during the signature phase.

关键词： quantum(t n)threshold signature quantum(t n)threshold secret sharing forgery attack collusion attack

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A Sentence Retrieval Generation Network Guided Video Captioning

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computers, Materials & Continua 2023年第6期75卷 5675-5696页

作者： Ou Ye Mimi Wang Zhenhua Yu Yan Fu Shun Yi Jun Deng College of Computer Science and Technology Xi’an University of Science and TechnologyXi’an710054China College of Safety and Engineering Xi’an University of Science and TechnologyXi’an710054China

Currently,the video captioning models based on an encoder-decoder mainly rely on a single video input *** contents of video captioning are limited since few studies employed external corpus information to guide the generation of video captioning,which is not conducive to the accurate descrip-tion and understanding of video *** address this issue,a novel video captioning method guided by a sentence retrieval generation network(ED-SRG)is proposed in this ***,a ResNeXt network model,an efficient convolutional network for online video understanding(ECO)model,and a long short-term memory(LSTM)network model are integrated to construct an encoder-decoder,which is utilized to extract the 2D features,3D features,and object features of video data *** features are decoded to generate textual sentences that conform to video content for sentence ***,a sentence-transformer network model is employed to retrieve different sentences in an external corpus that are semantically similar to the above textual *** candidate sentences are screened out through similarity ***,a novel GPT-2 network model is constructed based on GPT-2 network *** model introduces a designed random selector to randomly select predicted words with a high probability in the corpus,which is used to guide and generate textual sentences that are more in line with human natural language *** proposed method in this paper is compared with several existing works by *** results show that the indicators BLEU-4,CIDEr,ROUGE_L,and METEOR are improved by 3.1%,1.3%,0.3%,and 1.5%on a public dataset MSVD and 1.3%,0.5%,0.2%,1.9%on a public dataset MSR-VTT *** can be seen that the proposed method in this paper can generate video captioning with richer semantics than several state-of-the-art approaches.

关键词： Video captioning encoder-decoder sentence retrieval external corpus RS GPT-2 network model

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Evolutions of Microstructure and Mechanical Properties in Mg-5Li-1Zn-0.5Ag-0.5Zr-xGd Alloy

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Acta Metallurgica Sinica(English Letters) 2023年第2期36卷 215-228页

作者： Bing-Yu Qian Rui-Zhi Wu Jian-Feng Sun Jing-Huai Zhang Le-Gan Hou Xiao-Chun Ma Jia-Hao Wang Hai-Ting Hu Key Laboratory of Superlight Materials&Surface Technology Ministry of EducationHarbin Engineering UniversityHarbin150001China College of Materials Science and Engineering Heilongjiang University of Science and TechnologyHarbin150022China

The evolution of the microstructure and mechanical properties of alloy system with nominally composition Mg-5Li-1Zn-0.5Ag-0.5Zr-xGd(x=0,1.2,2.4,3.6,4.8,6)is evaluated based on computational phase diagram and corresponding experimental *** results show that grains are significantly refined with the increase of Gd *** main phases of as-cast alloys areα-Mg,β-Li,AgLi_(2)Mg,and Mg_(3)*** the increase of Gd content,the amounts of Mg_(3)Gd phase andβ-Li phase have been *** the Gd content exceeds 3.6 wt%,Mg_(3)Gd phase precipitates in a form of the network at the grain *** precipitation ofβ-Li can be attributed to the competitive dissolution of Zn,Gd,and Li in ***,γ″is formed after the addition of Gd,which grows and transforms intoγ′with the increase of Gd *** solidification process,stacking faults are formed by solid transformation of partialα-Mg and Mg_(3)***,with the synergistic effect of Mg_(3)Gd,β-Li,andγ″(orγ′),as the Gd content increasing,the tensile strength of the alloy first increases,then decreases,and the elongation *** the content of Gd is 4.8 wt%,the ultimate tensile strength and yield strength reach the maximum values of 227 MPa and 139 MPa,and the elongation is 18.1%,respectively.

关键词： Mg-Li-Zn-Gd alloy Phase diagram Microstructure evolution Mechanical properties

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FedQT: A Federated Learning Model Compression Algorithm Based on Quicksort and Top Avg Pruning

Journal of Network Intelligence

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Journal of Network Intelligence 2024年第1期9卷 225-238页

作者： Zhang, Jin-Quan Xu, Hui-Xin Ma, Yun-Shen Ni, Li-Na College of Computer Science and Engineering Shandong University of Science and Technology Qingdao266590 China

With the advent of the fourth industrial revolution, data ushered in explosive growth. Federated learning can protect users’ privacy and raw data from being known by third parties. Its client data is only trained locally and will not be uploaded to the server. However, the need to continuously transmit between the server and the client in federated learning increases communication overhead and communication delay, and the consumption of resources is very large. In order to improve the communication efficiency of the federation, we proposed an FedQT federated learning model compression algorithm based on pruning and quantization. Firstly, the fast sorting is used to preprocess the trained parameters. Secondly, the middle part of the processed parameters is averaged to obtain the pruning threshold avg(ω). Then, according to the obtained new threshold standard, the model performs Top Avg pruning based on median comparison. Finally, the k − means algorithm is used to cluster the parameters for further compression. In the simulation experiment, FedQT is compared with uncompressed and other compression algorithms, and the time complexity is analyzed. It is proved that FedQT can compress the trained model parameters to improve its communication efficiency while reducing the time overhead. The model can be compressed by more than one thousand times, and the model accuracy can be maintained above 97%, which is enough to prove that FedQT algorithm has good performance in the compression framework of federated learning. © 2024.

关键词： Efficiency

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CMDCF: an effective cross-modal dense cooperative fusion network for RGB-D SOD

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Neural Computing and Applications 2024年第23期36卷 14361-14378页

作者： Jia, XingZhao Zhao, WenXiu Wang, YuMei DongYe, ChangLei Peng, YanJun College of Computer Science and Engineering Shandong University of Science and Technology Qingdao266590 China

The success of vision transformer demonstrates that the transformer structure is also suitable for various vision tasks, including high-level classification tasks and low-level dense prediction tasks. Salient object detection (SOD) is a pixel-level dense prediction task that simulates the most salient objects in human visual recognition scenarios. In recent years, depth images have been widely used for salient object detection. Compared with RGB SOD, the key point of RGB-D SOD is the effective fusion of depth information. As RGB-D SOD requires extracting depth features and fusing cross-modal information, additional computation is involved. However, except for lightweight models, most RGB-D SOD methods tend to obtain better prediction maps by consuming more computational resources. We propose a cross-modal dense cooperative fusion net, which provides state-of-the-art performance with less computation and parameters. We take advantage of the ability of the transformer structure to model long sequence dependencies to extract saliency features from RGB images. Since there is less information in the depth image than in the RGB image, it is not necessary to use the same structure in the depth stream. For the sake of reducing parameters and computation, we consider the asymmetric architecture. It is enough to meet our needs that deep features extracted by lightweight MobileV2Net. Our decoder can perform dense cooperative fusion of cross-modal information while decoding features. It can both effectively fuse cross-modal information and save computation. Comprehensive experiments on multiple benchmark datasets for RGB-D SOD show that compared with SOTA methods, our method performs much better with less computation and parameters. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Object detection

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