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Gria:an efficient deterministic concurrency control protocol

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Frontiers of Computer Science 2024年第4期18卷 25-37页

作者： Xinyuan WANG Yun PENG Hejiao HUANG School of Computer Science and Technology Harbin Institute of TechnologyShenzhen 518055China Institute of artificial intelligence and Blockchain Guangzhou UniversityGuangzhou 510006China

Deterministic databases are able to reduce coordination costs in a *** property has fostered a significant interest in the design of efficient deterministic concurrency control ***,the state-of-the-art deterministic concurrency control protocol Aria has three ***,it is impractical to configure a suitable batch size when the read-write set is ***,Aria running in low-concurrency scenarios,e.g.,a single-thread scenario,suffers from the same conflicts as running in high-concurrency ***,the single-version schema brings write-after-write *** address these issues,we propose Gria,an efficient deterministic concurrency control *** has the following ***,the batch size of Gria is ***,Gria’s conflict probability in low-concurrency scenarios is lower than that in high-concurrency ***,Gria has no write-after-write conflicts by adopting a multi-version *** further reduce conflicts,we propose two optimizations:a reordering mechanism as well as a rechecking *** evaluation result on two popular benchmarks shows that Gria outperforms Aria by 13x.

关键词： deterministic concurrency control transaction processing

Linear-fitting-based recursive filtering for nonlinear systems under encoding-decoding mechanism

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Science China(Information Sciences) 2024年第5期67卷 183-196页

作者： Bo JIANG Hongli DONG Zhiwei GAO Yuxuan SHEN Fan YANG artificial intelligence Energy Research Institute Northeast Petroleum University Heilongjiang Provincial key laboratory of Networking and Intelligent Control Sanya Offshore Oil & Gas Research Institute Northeast Petroleum University School of Electrical & Information Engineering Northeast Petroleum University

This paper deals with a recursive filtering problem for a class of discrete time-varying nonlinear networked systems with the encoding-decoding mechanism. The linear fitting method is introduced to handle the nonlinearity. An encoding-decoding mechanism is constructed to describe the data transmission process in wireless communication networks(WCNs). To be specific, the measurement outputs are mapped by a quantizer to unique codewords for transmission in WCNs. Then, the codewords are decoded by the decoder to recover the measurement outputs which are sent to the filter. The processing/encoding delay and network delay have been considered. Firstly, on the premise that the upper bound of the filtering error covariance is minimum, the appropriate filtering gain is calculated. Then, the mean square exponential boundedness of the filtering error is analyzed. Finally, two simulation examples are presented to verify the effectiveness of the proposed algorithm.

关键词： encoding-decoding mechanism uniform quantizer linear fitting networked systems recursive filtering

Cognitive-emotional feasibility of the effect of visual quality of building form on promoting the sense of place attachment(Case study:Cultural iconic buildings of Iran’s contemporary architecture)

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Frontiers of Architectural Research 2024年第1期13卷 37-56页

作者： Narmin Ariannia Negar Naseri Mansour Yeganeh Digital Architecture and artificial intelligence lab Department of ArchitectureTarbiat Modares UniversityTehranIran Architectural Design Modeling and Fabrication LabDepartment of ArchitectureTarbiat Modares UniversityTehranIran

The present research studies the relationship between place attachment and the perception of form’s visual quality in fifteen outstanding contemporary Iranian architectural cultural *** study puts forward the hypothesis that there is a correlation between the quality of building form and the sense of place attachment,in the sense that creating high visual quality through enhancing the quality of building form increases citizens’initial satisfaction with and subsequent attachment to the *** visual quality influences people’s experience of the environment and improves the quality of *** attachment highlights how people,on a personal level,recreate a sense of place for *** present study adopts the descriptive-analytical method as its theoretical framework and the survey as the empirical *** were developed using the Likert scale and distributed among experts and ordinary *** analysis using SPSS and the adoption of descriptive-analytical statistics,correlation analysis,and regression showed the relationship among the characteristics of *** results show a positive correlation between form and place attachment mediated through visual quality,and they are causal conditions for one *** addition,only some of the buildings under study evoke the same level of place attachment.

关键词： Visual preferences Environmental quality Environmental psychology Mental schemas Contemporary architecture

A Privacy Preservation Method for Attributed Social Network Based on Negative Representation of Information

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Computer Modeling in Engineering & Sciences 2024年第7期140卷 1045-1075页

作者： Hao Jiang Yuerong Liao Dongdong Zhao Wenjian Luo Xingyi Zhang key laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and TechnologyAnhui UniversityHefei230601China Chongqing Research Institute School of Computer Science and Artificial IntelligenceWuhan University of TechnologyWuhan430070China Guangdong Provincial key laboratory of Novel Security intelligence Technologies School of Computer Science and TechnologyHarbin Institute of TechnologyShenzhen518055China

Due to the presence of a large amount of personal sensitive information in social networks,privacy preservation issues in social networks have attracted the attention of many *** by the self-nonself discrimination paradigmin the biological immune system,the negative representation of information indicates features such as simplicity and efficiency,which is very suitable for preserving social network ***,we suggest a method to preserve the topology privacy and node attribute privacy of attribute social networks,called ***,a negative survey-based method is developed to disturb the relationship between nodes in the social network so that the topology structure can be kept ***,a negative database-based method is proposed to hide node attributes,so that the privacy of node attributes can be preserved while supporting the similarity estimation between different node attributes,which is crucial to the analysis of social *** evaluate the performance of the AttNetNRI,empirical studies have been conducted on various attribute social networks and compared with several state-of-the-art methods tailored to preserve the privacy of social *** experimental results show the superiority of the developed method in preserving the privacy of attribute social networks and demonstrate the effectiveness of the topology disturbing and attribute hiding *** experimental results show the superiority of the developed methods in preserving the privacy of attribute social networks and demonstrate the effectiveness of the topological interference and attribute-hiding components.

关键词： Attributed social network topology privacy node attribute privacy negative representation of information negative survey negative database

3D hand pose and shape estimation from monocular RGB via efficient 2D cues

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Computational Visual Media 2024年第1期10卷 79-96页

作者： Fenghao Zhang Lin Zhao Shengling Li Wanjuan Su Liman Liu Wenbing Tao Hubei key laboratory of Medical Information Analysis and Tumor Diagnosis&Treatment School of Biomedical EngineeringSouth Central Minzu UniversityWuhan430074China National key laboratory of Science and Technology of Multi-spectral Information Processing School of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan430074China

Estimating 3D hand shape from a single-view RGB image is important for many ***,the diversity of hand shapes and postures,depth ambiguity,and occlusion may result in pose errors and noisy hand *** full use of 2D cues such as 2D pose can effectively improve the quality of 3D human hand shape *** this paper,we use 2D joint heatmaps to obtain spatial details for robust pose *** also introduce a depth-independent 2D mesh to avoid depth ambiguity in mesh regression for efficient hand-image *** method has four cascaded stages:2D cue extraction,pose feature encoding,initial reconstruction,and reconstruction ***,we first encode the image to determine semantic features during 2D cue extraction;this is also used to predict hand joints and for ***,during the pose feature encoding stage,we use a hand joints encoder to learn spatial information from the joint ***,a coarse 3D hand mesh and 2D mesh are obtained in the initial reconstruction step;a mesh squeeze-and-excitation block is used to fuse different hand features to enhance perception of 3D hand ***,a global mesh refinement stage learns non-local relations between vertices of the hand mesh from the predicted 2D mesh,to predict an offset hand mesh to fine-tune the reconstruction *** and qualitative results on the FreiHAND benchmark dataset demonstrate that our approach achieves state-of-the-art performance.

关键词： hand 3D reconstruction deep learning image features 3D mesh

A Knowledge-enhanced Two-stage Generative Framework for Medical Dialogue Information Extraction

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Machine intelligence Research 2024年第1期21卷 153-168页

作者： Zefa Hu Ziyi Ni Jing Shi Shuang Xu Bo Xu School of artificial intelligence University of Chinese Academy of SciencesBeijing 100049China Institute of Automation Chinese Academy of SciencesBeijing 100190China

This paper focuses on term-status pair extraction from medical dialogues(MD-TSPE),which is essential in diagnosis dia-logue systems and the automatic scribe of electronic medical records(EMRs).In the past few years,works on MD-TSPE have attracted increasing research attention,especially after the remarkable progress made by generative ***,these generative methods output a whole sequence consisting of term-status pairs in one stage and ignore integrating prior knowledge,which demands a deeper un-derstanding to model the relationship between terms and infer the status of each *** paper presents a knowledge-enhanced two-stage generative framework(KTGF)to address the above *** task-specific prompts,we employ a single model to com-plete the MD-TSPE through two phases in a unified generative form:We generate all terms the first and then generate the status of each generated *** this way,the relationship between terms can be learned more effectively from the sequence containing only terms in the first phase,and our designed knowledge-enhanced prompt in the second phase can leverage the category and status candidates of the generated term for status ***,our proposed special status"not mentioned"makes more terms available and en-riches the training data in the second phase,which is critical in the low-resource *** experiments on the Chunyu and CMDD datasets show that the proposed method achieves superior results compared to the state-of-the-art models in the full training and low-re-sourcesettings.

关键词： Medical dialogue understanding information extraction text generation knowledge-enhanced prompt low-resource setting dataaugmentation

Weakly Supervised Object Localization with Background Suppression Erasing for Art Authentication and Copyright Protection

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Machine intelligence Research 2024年第1期21卷 89-103页

作者： Chaojie Wu Mingyang Li Ying Gao Xinyan Xie Wing W.Y.Ng Ahmad Musyafa School of Computer Science and Engineering South China University of TechnologyGuangzhou 511442China Guangdong Provincial key laboratory of artificial intelligence in Medical Image Analysis and Application Guangdong Provincial People's HospitalGuangzhou 510180China

The problem of art forgery and infringement is becoming increasingly prominent,since diverse self-media contents with all kinds of art pieces are released on the Internet every *** art paintings,object detection and localization provide an efficient and ef-fective means of art authentication and copyright ***,the acquisition of a precise detector requires large amounts of ex-pensive pixel-level *** alleviate this,we propose a novel weakly supervised object localization(WSOL)with background su-perposition erasing(BSE),which recognizes objects with inexpensive image-level ***,integrated adversarial erasing(IAE)for vanilla convolutional neural network(CNN)dropouts the most discriminative region by leveraging high-level semantic ***,a background suppression module(BSM)limits the activation area of the IAE to the object region through a self-guidance ***,in the inference phase,we utilize the refined importance map(RIM)of middle features to obtain class-agnostic loc-alization *** experiments are conducted on paintings,CUB-200-2011 and ILSVRC to validate the effectiveness of our BSE.

关键词： Weakly supervised object localization erasing method deep learning computer vision art authentication and copyright protection

Dynamic SLAM Visual Odometry Based on Instance Segmentation:A Comprehensive Review

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Computers, Materials & Continua 2024年第1期78卷 167-196页

作者： Jiansheng Peng Qing Yang Dunhua Chen Chengjun Yang Yong Xu Yong Qin College of Automation Guangxi University of Science and TechnologyLiuzhou545000China Department of artificial intelligence and Manufacturing Hechi UniversityHechi547000China

Dynamic Simultaneous Localization and Mapping(SLAM)in visual scenes is currently a major research area in fields such as robot navigation and autonomous ***,in the face of complex real-world envi-ronments,current dynamic SLAM systems struggle to achieve precise localization and map *** the advancement of deep learning,there has been increasing interest in the development of deep learning-based dynamic SLAM visual odometry in recent years,and more researchers are turning to deep learning techniques to address the challenges of dynamic *** to dynamic SLAM systems based on deep learning methods such as object detection and semantic segmentation,dynamic SLAM systems based on instance segmentation can not only detect dynamic objects in the scene but also distinguish different instances of the same type of object,thereby reducing the impact of dynamic objects on the SLAM system’s *** article not only introduces traditional dynamic SLAM systems based on mathematical models but also provides a comprehensive analysis of existing instance segmentation algorithms and dynamic SLAM systems based on instance segmentation,comparing and summarizing their advantages and *** comparisons on datasets,it is found that instance segmentation-based methods have significant advantages in accuracy and robustness in dynamic ***,the real-time performance of instance segmentation algorithms hinders the widespread application of dynamic SLAM *** recent years,the rapid development of single-stage instance segmentationmethods has brought hope for the widespread application of dynamic SLAM systems based on instance ***,possible future research directions and improvementmeasures are discussed for reference by relevant professionals.

关键词： Dynamic SLAM instance segmentation visual odometry

DCFNet:Discriminant Correlation Filters Network for Visual Tracking

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Journal of Computer Science & Technology 2024年第3期39卷 691-714页

作者：胡卫明王强高晋李兵 Stephen Maybank State key laboratory of Multimodal artificial intelligence Systems Institute of AutomationChinese Academy of Sciences Beijing 100190China Department of Computer Science and Information Systems Birkbeck CollegeLondon WC1E 7HXU.K.

CNN(convolutional neural network)based real time trackers usually do not carry out online network update in order to maintain rapid tracking *** inevitably influences the adaptability to changes in object *** filter based trackers can update the model parameters online in real *** this paper,we present an end-to-end lightweight network architecture,namely Discriminant Correlation Filter Network(DCFNet).A differentiable DCF(discriminant correlation filter)layer is incorporated into a Siamese network architecture in order to learn the convolutional features and the correlation filter *** correlation filter can be efficiently updated *** previous work,we introduced a joint scale-position space to the DCFNet,forming a scale DCFNet which carries out the predictions of object scale and position *** combine the scale DCFNet with the convolutional-deconvolutional network,learning both the high-level embedding space representations and the low-level fine-grained representations for *** adaptability of the fine-grained correlation analysis and the generalization capability of the semantic embedding are complementary for visual *** back-propagation is derived in the Fourier frequency domain throughout the entire work,preserving the efficiency of the *** evaluations on the OTB(Object Tracking Benchmark)and VOT(Visual Object Tracking Challenge)datasets demonstrate that the proposed trackers have fast speeds,while maintaining tracking accuracy.

关键词： correlation filter convolutional neural network(CNN) visual tracking