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Big Data Access Control Mechanism Based on Two-Layer Permission Decision Structure

Computers, Materials & Continua 2024年第4期79卷 1705-1726页

作者： Aodi Liu Na Wang Xuehui Du Dibin Shan Xiangyu Wu Wenjuan Wang He’nan Province key laboratory of information Security Information Engineering UniversityZhengzhou450000China

Big data resources are characterized by large scale, wide sources, and strong dynamics. Existing access controlmechanisms based on manual policy formulation by security experts suffer from drawbacks such as low policymanagement efficiency and difficulty in accurately describing the access control policy. To overcome theseproblems, this paper proposes a big data access control mechanism based on a two-layer permission decisionstructure. This mechanism extends the attribute-based access control (ABAC) model. Business attributes areintroduced in the ABAC model as business constraints between entities. The proposed mechanism implementsa two-layer permission decision structure composed of the inherent attributes of access control entities and thebusiness attributes, which constitute the general permission decision algorithm based on logical calculation andthe business permission decision algorithm based on a bi-directional long short-term memory (BiLSTM) neuralnetwork, respectively. The general permission decision algorithm is used to implement accurate policy decisions,while the business permission decision algorithm implements fuzzy decisions based on the business *** BiLSTM neural network is used to calculate the similarity of the business attributes to realize intelligent,adaptive, and efficient access control permission decisions. Through the two-layer permission decision structure,the complex and diverse big data access control management requirements can be satisfied by considering thesecurity and availability of resources. Experimental results show that the proposed mechanism is effective andreliable. In summary, it can efficiently support the secure sharing of big data resources.

关键词： Big data access control data security BiLSTM

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Predicting Users’ Latent Suicidal Risk in Social Media: An Ensemble Model Based on Social Network Relationships

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Computers, Materials & Continua 2024年第6期79卷 4259-4281页

作者： Xiuyang Meng Chunling Wang Jingran Yang Mairui Li Yue Zhang Luo Wang School of information Science and Technology Beijing Forestry UniversityBeijing100083China Engineering Research Center for Forestry-Oriented intelligent information processing of National Forestry and Grassland Administration Beijing100083China

Suicide has become a critical concern,necessitating the development of effective preventative *** media platforms offer a valuable resource for identifying signs of suicidal *** progress in detecting suicidal ideation on social media,accurately identifying individuals who express suicidal thoughts less openly or infrequently poses a significant *** tackle this,we have developed a dataset focused on Chinese suicide narratives from Weibo’s Tree Hole feature and introduced an ensemble model named Text Convolutional Neural Network based on Social Network relationships(TCNN-SN).This model enhances predictive performance by leveraging social network relationship features and applying correction factors within a weighted linear fusion *** is specifically designed to identify key individuals who can help uncover hidden suicidal users and *** model,assessed using the bespoke dataset and benchmarked against alternative classification approaches,demonstrates superior accuracy,F1-score and AUC metrics,achieving 88.57%,88.75%and 94.25%,respectively,outperforming traditional TextCNN models by 12.18%,10.84%and 10.85%.We assert that our methodology offers a significant advancement in the predictive identification of individuals at risk,thereby contributing to the prevention and reduction of suicide incidences.

关键词： Suicide risk prediction social media social network relationships Weibo Tree Hole deep learning

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Empowerment of Precise Ideological and Political Education in Higher Education with Educational Digitalization

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Journal of Contemporary Educational Research 2024年第4期8卷 23-28页

作者： Yan Dong Yu Yu Ge Yao Ulanqab key laboratory of intelligent {3. processing and Security Jining Normal UniversityUlanqab 012000China

The study explores how educational digitalization enables the precise development of ideological and political education in colleges and *** transformation enables colleges and universities to accurately define educational objectives,content strategies,effect evaluation,and process management,and realize the precision and intelligence of ideological and political *** application of big data technology enhances the data-oriented thinking of teachers and students,promotes the accurate application of data,and improves the efficiency of ideological and political educa*** research also prospected a new vision of the digital construction of ideological and political courses and clarified the theoretical and practical path of the implementation and evaluation mode of ideological and political courses under digital *** digitalization enables precise ideological and political education,which is a key way to promote the innovative development of ideological and political education in colleges and universities and will strongly support the improvement of the overall quality of higher education and the training of excellent talents.

关键词： Education digital empowerment Precise ideological and political education Improvement of efficiency

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Real-time tracking of fast-moving object in occlusion scene

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Journal of Systems Engineering and Electronics 2024年第3期35卷 741-752页

作者： LI Yuran LI Yichen ZHANG Monan YU Wenbin GUAN Xinping Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China key laboratory of Systems Control and information {3. Ministry of Education of ChinaShanghai 200240China

Tracking the fast-moving object in occlusion situations is an important research topic in computer vision. Despite numerous notable contributions have been made in this field,few of them simultaneously incorporate both object's extrinsic features and intrinsic motion patterns into their methodologies,thereby restricting the potential for tracking accuracy improvement. In this paper, on the basis of efficient convolution operators(ECO) model, a speed-accuracy-balanced model is put forward. This model uses the simple correlation filter to track the object in real-time, and adopts the sophisticated deep-learning neural network to extract high-level features to train a more complex filter correcting the tracking mistakes, when the tracking state is judged to be poor. Furthermore, in the context of scenarios involving regular fast-moving, a motion model based on Kalman filter is designed which greatly promotes the tracking stability, because this motion model could predict the object's future location from its previous movement pattern. Additionally,instead of periodically updating our tracking model and training samples, a constrained condition for updating is proposed,which effectively mitigates contamination to the tracker from the background and undesirable samples avoiding model degradation when occlusion happens. From comprehensive experiments, our tracking model obtains better performance than ECO on object tracking benchmark 2015(OTB100), and improves the area under curve(AUC) by about 8% and 3.% compared with ECO, in the scenarios of fast-moving and occlusion on our own collected dataset.

关键词： speed-accuracy balanced motion modeling constrained updater

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Sparse convolutional model with semantic expression for waste electrical appliances recognition

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Science China(Technological Sciences) 2024年第9期67卷 2881-2893页

作者： HAN HongGui LIU YiMing LI FangYu DU YongPing Faculty of information Technology Beijing University of TechnologyBeijing 100124China Beijing key laboratory of Computational Intelligence and intelligent System Beijing 100124China Engineering Research Center of Digital Community Ministry of EducationBeijing 100124China Beijing Artificial Intelligence Institute and Beijing laboratory for intelligent Environmental Protection Beijing 100124China

Deep neural networks play an important role in the recognition of waste electrical appliances. However, deep neural network components still lack reliability in decision-making features. To address this problem, a sparse convolutional model with semantic expression(SCMSE) is proposed. First, a low-rank sparse semantic expression component, combining the benefits of residual networks and sparse representation, is adapted to enhance sparse feature extraction and semantic expression. Second, a reliable network architecture is obtained by iterating the optimal sparse solution, enhancing semantic expression. Finally, the results of visualization experiments on the waste electrical appliances dataset demonstrate that the proposed SCMSE can obtain excellent semantic performance.

关键词： sparse convolutional model deep neural network semantic expression visualization computer vision

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Revealing the atomic mechanism of diamond–iron interfacial reaction

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Carbon Energy 2024年第3期6卷 255-263页

作者： Yalun Ku Kun Xu Longbin Yan Kuikui Zhang Dongsheng Song Xing Li Shunfang Li Shaobo Cheng Chongxin Shan Henan key laboratory of Diamond Optoelectronic Materials and Devices Key Laboratory of Material PhysicsMinistry of EducationSchool of Physics and MicroelectronicsZhengzhou UniversityZhengzhouChina Department of Mechanical Engineering Stanford UniversityStanfordCaliforniaUSA information Materials and intelligent Sensing laboratory of Anhui Province Key Laboratory of Structure and Functional Regulation of Hybrid Materials of Ministry of EducationInstitutes of Physical Science and Information TechnologyAnhui UniversityHefeiChina Institute of Quantum Materials and Physics Henan Academy of SciencesZhengzhouChina

Diamond,with ultrahigh hardness,high wear resistance,high thermal conductivity,and so forth,has attracted worldwide ***,researchers found emergent reactions at the interfaces between diamond and ferrous materials,which significantly affects the performance of diamond-based ***,combing experiments and theoretical calculations,taking diamond–iron(Fe)interface as a prototype,the counter-diffusion mechanism of Fe/carbon atoms has been ***,it is identified that Fe and diamond first form a coherent interface,and then Fe atoms diffuse into diamond and prefer the carbon vacancies ***,the relaxed carbon atoms diffuse into the Fe lattice,forming Fe_(3.***,graphite is observed at the Fe_(3.C surface when Fe_(3.C is over-saturated by carbon *** present findings are expected to offer new insights into the atomic mechanism for diamondferrous material's interfacial reactions,benefiting diamond-based device applications.

关键词： coherent interface counter-diffusion diamond iron phase transition

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Imaging a force field via an optically levitated nanoparticle array

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Chinese Physics B 2024年第9期33卷 179-184页

作者： Bihu Lv Jiandong Zhang Chuang Li Research Center for Novel Computing Sensing and intelligent processing Zhejiang LaboratoryHangzhou 311121China School of Mathematics and Physics Jiangsu University of TechnologyChangzhou 213001China

Levitated optomechanical systems represent an excellent candidate platform for force and acceleration *** propose a force-sensing protocol utilizing an optically levitated nanoparticle *** our scheme,N nanoparticles are trapped in an optical cavity using holographic optical *** external laser drives the cavity,exciting N cavity modes interacting simultaneously with the N *** optomechanical interaction encodes the information of the force acting on each nanoparticle onto the intracavity photons,which can be detected directly at the output ports of the ***,our protocol enables real-time imaging of a force field.

关键词： optomechanics levitated nanoparticles force field detection

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Spatiotemporal evolution laws of sector-shaped dielectric-barrier-discharge plasma actuator

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Plasma Science and Technology 2024年第10期26卷 108-115页

作者： Borui ZHENG Jianbo ZHANG Shaojie QI Jianghua XU Yiche LI Yuanzhong JIN Dongliang BIAN School of Automation and information Engineering Xi’an University of TechnologyXi’an 710048People’s Republic of China Shaanxi key laboratory of Complex System Control and intelligent {3. processing Xi’an 710048People’s Republic of China School of Mechanical and Precision Instrument Engineering Xi’an University of TechnologyXi’an 710048People’s Republic of China Science and Technology on Plasma Dynamics laboratory Air Force Engineering UniversityXi’an 710038People’s Republic of China

Dielectric barrier discharge(DBD)plasma actuators are widely used in active flow control due to their simple design and rapid ***,they need more effectiveness and discharge *** overcome these limitations,a sector-shaped dielectric barrier discharge(SS-DBD)plasma actuator with an adjustable jet angle was developed to enhance flow control *** flow field dynamics induced by the SS-DBD plasma actuator were quantitatively analyzed using particle image velocimetry(PIV).Experimental investigations showed that precise adjustments to the actuation voltage can modulate the maximum velocity of the induced ***,a quasi-linear relationship between the sector-shaped angles of the SS-DBD and the deflected jet angles was established,indicating that changes in the sector-shaped angles directly influence the direction of the deflected *** correlation enables precise control over jet angles,significantly enhancing flow control by adjusting the SS-DBD-PA's sector-shaped angle.

关键词： plasma flow control plasma actuator particle image velocimetry

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Co-salient object detection with iterative purification and predictive optimization

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虚拟现实与智能硬件（中英文） 2024年第5期6卷 396-407页

作者： Yang WEN Yuhuan WANG Hao WANG Wuzhen SHI Wenming CAO Guangdong Provincial key laboratory of intelligent {3. processing College of Electronics and Information EngineeringShenzhen UniversityShenzhen 518060China

Background Co-salient object detection(Co-SOD)aims to identify and segment commonly salient objects in a set of related ***,most current Co-SOD methods encounter issues with the inclusion of irrelevant information in the *** issues hamper their ability to locate co-salient objects and significantly restrict the accuracy of *** To address this issue,this study introduces a novel Co-SOD method with iterative purification and predictive optimization(IPPO)comprising a common salient purification module(CSPM),predictive optimizing module(POM),and diminishing mixed enhancement block(DMEB).Results These components are designed to explore noise-free joint representations,assist the model in enhancing the quality of the final prediction results,and significantly improve the performance of the Co-SOD ***,through a comprehensive evaluation of IPPO and state-of-the-art algorithms focusing on the roles of CSPM,POM,and DMEB,our experiments confirmed that these components are pivotal in enhancing the performance of the model,substantiating the significant advancements of our method over existing *** on several challenging benchmark co-saliency datasets demonstrate that the proposed IPPO achieves state-of-the-art performance.

关键词： Co-salient object detection Saliency detection Iterative method Predictive optimization

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Integer multiple quantum image scaling based on NEQR and bicubic interpolation

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Chinese Physics B 2024年第4期33卷 259-273页

作者：蔡硕周日贵罗佳陈思哲 College of information Engineering Shanghai Maritime UniversityShanghai 201306China Research Center of intelligent information processing and Quantum intelligent Computing Shanghai 201306China College of Merchant Marine Shanghai Maritime UniversityShanghai 201306China School of Mathematics and Computational Science Shangrao Normal UniversityShangrao 334001China

As a branch of quantum image processing,quantum image scaling has been widely ***,most of the existing quantum image scaling algorithms are based on nearest-neighbor interpolation and bilinear interpolation,the quantum version of bicubic interpolation has not yet been *** this work,we present the first quantum image scaling scheme for bicubic interpolation based on the novel enhanced quantum representation(NEQR).Our scheme can realize synchronous enlargement and reduction of the image with the size of 2^(n)×2^(n) by integral ***,the image is represented by NEQR and the original image coordinates are obtained through multiple CNOT ***,16 neighborhood pixels are obtained by quantum operation circuits,and the corresponding weights of these pixels are calculated by quantum arithmetic ***,a quantum matrix operation,instead of a classical convolution operation,is used to realize the sum of convolution of these *** simulation experiments and complexity analysis,we demonstrate that our scheme achieves exponential speedup over the classical bicubic interpolation algorithm,and has better effect than the quantum version of bilinear interpolation.

关键词： quantum image processing image scaling bicubic interpolation quantum circuit

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