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A Linear Homomorphic Proxy Signature Scheme Based on Blockchain for Internet of Things 认领 引用
1
作者 Caifen Wang Bin Wu 《Computer Modeling in Engineering & Sciences》 SCIE EI 2023年第8期1857-1878,共22页
The mushroom growth of IoT has been accompanied by the generation of massive amounts of data.Subject to the limited storage and computing capabilities ofmost IoT devices,a growing number of institutions and organizati... The mushroom growth of IoT has been accompanied by the generation of massive amounts of data.Subject to the limited storage and computing capabilities ofmost IoT devices,a growing number of institutions and organizations outsource their data computing tasks to cloud servers to obtain efficient and accurate computation while avoiding the cost of local data computing.One of the most important challenges facing outsourcing computing is how to ensure the correctness of computation results.Linearly homomorphic proxy signature(LHPS)is a desirable solution to ensure the reliability of outsourcing computing in the case of authorized signing right.Blockchain has the characteristics of tamper-proof and traceability,and is a new technology to solve data security.However,as far as we know,constructions of LHPS have been few and far between.In addition,the existing LHPS scheme does not focus on homomorphic unforgeability and does not use blockchain technology.Herein,we improve the security model of the LHPS scheme,and the usual existential forgery and homomorphic existential forgery of two types of adversaries are considered.Under the new model,we present a blockchain-based LHPS scheme.The security analysis shows that under the adaptive chosen message attack,the unforgeability of the proposed scheme can be reduced to the CDH hard assumption,while achieving the usual and homomorphic existential unforgeability.Moreover,comparedwith the previous LHPS scheme,the performance analysis shows that our scheme has the same key size and comparable computational overhead,but has higher security. 展开更多
关键词 Homomorphic signature proxy signature security model provable security unforgeability
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Decentralized Counterparty Matches and Automatic Settlement of Interest Rate Swap Through Blockchain’s Smart Contracts 认领 引用
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作者 Jian Zhao Jinjing Liu +2 位作者 Hua Wang Lin Lin Shaohua Xiang 《国际计算机前沿大会会议论文集》 2022年第2期437-447,共11页
Interest Rate Swap(IRS)is the most vivid application of the principle of comparative advantage in the financial field.The effectiveness of interest rate swap in managing interest rate risk has been widely recognized.H... Interest Rate Swap(IRS)is the most vivid application of the principle of comparative advantage in the financial field.The effectiveness of interest rate swap in managing interest rate risk has been widely recognized.However,the traditional interest rate swap transaction is complicated.Meanwhile,there usually existmarket risks and credit risks.To alleviate risks and cost,and improve liquidity of interest rate swap,this paper proposes a smart contract basedmatching platform for interest rate swap of real fiat currency.Smart contracts play a key role for sharing data among participants,which can not be forged or tampered with.In our design,an efficient peer-to-peer counterparty matching method on the chain is proposed.The whole trading process of interest rate swap is carried out on the blockchain,which has higher security.A prototype based on smart contracts running on Ethereum is implemented and validates our design. 展开更多
关键词 Ethereum Smart contract Interest rate swap DeFi
A deep convolutional neural network for diabetic retinopathy detection via mining local and long-range dependence 认领 引用 被引量：4
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作者 Xiaoling Luo Wei Wang +4 位作者 Yong Xu Zhihui Lai Xiaopeng Jin Bob Zhang David Zhang 《CAAI Transactions on Intelligence Technology》 SCIE EI 2024年第1期153-166,共14页
Diabetic retinopathy(DR),the main cause of irreversible blindness,is one of the most common complications of diabetes.At present,deep convolutional neural networks have achieved promising performance in automatic DR d... Diabetic retinopathy(DR),the main cause of irreversible blindness,is one of the most common complications of diabetes.At present,deep convolutional neural networks have achieved promising performance in automatic DR detection tasks.The convolution operation of methods is a local cross-correlation operation,whose receptive field de-termines the size of the local neighbourhood for processing.However,for retinal fundus photographs,there is not only the local information but also long-distance dependence between the lesion features(e.g.hemorrhages and exudates)scattered throughout the whole image.The proposed method incorporates correlations between long-range patches into the deep learning framework to improve DR detection.Patch-wise re-lationships are used to enhance the local patch features since lesions of DR usually appear as plaques.The Long-Range unit in the proposed network with a residual structure can be flexibly embedded into other trained networks.Extensive experimental results demon-strate that the proposed approach can achieve higher accuracy than existing state-of-the-art models on Messidor and EyePACS datasets. 展开更多
关键词 image classification medical image processing pattern recognition
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Untangling the association between urban mobility and urban elements 认领 引用 被引量：1
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作者 Jinzhou Cao Wei Tu +3 位作者 Rui Cao Qili Gao Guanzhou Chen Qingquan Li 《Geo-Spatial Information Science》 SCIE EI CSCD 2024年第4期1071-1089,共19页
Understanding complex urban systems necessitates untangling the relationships between diverse urban elements such as population,infrastructure,and socioeconomic activities.Scaling laws are basic but effective rules fo... Understanding complex urban systems necessitates untangling the relationships between diverse urban elements such as population,infrastructure,and socioeconomic activities.Scaling laws are basic but effective rules for evaluating a city’s internal growth logic and assessing its efficiency by investigating whether urban indicators scale with population.To date,only limited research has empirically explored the scaling relations between variables of urban mobility in mega-cities at an intra-urban scale of a few meters.Using multiple urban-sensed and human-sensed data,this study proposes a thorough framework for quantifying the scaling laws in a city.To begin,urban mobility networks are built by aggregating population flows using large-scale mobile phone tracking data.To demonstrate the spatiotemporal variability of urban mobility,various network-based mobility measures are proposed.Following that,three different features of urban mobility laws are exposed,explaining spatial agglomeration,spatial hierarchical structures,and the temporal growth process.The scaling correlations between urban indicators pertaining to socioeconomic features and infrastructure and a mobility-population measure are then quantified using multi-sourced urban-sensed data.Applying this framework to the case study of Shenzhen,China revealed(a)spatial travel heterogeneity,hierarchical spatial structures,and mobility growth,and(b)not only a robust sub-linear relationship between infrastructure volume and population,but also a sub-linear relationship for socioeconomic activity.The identified scaling laws,both in terms of mobility measures and urban indicators,provide a multi-faceted portrait of the spatio-temporal variations of urban settings,allowing us to better understand intra-urban developments and,consequently,provide critical policy evaluations and suggestions for improving intra-urban efficiency in the future. 展开更多
关键词 Scaling law urban scaling urban mobility intra-urban system mobile phone data
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Electricity Carbon Quota Trading Scheme based on Certificateless Signature and Blockchain 认领 引用 被引量：1
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作者 Xiaodong Yang Runze Diao +2 位作者 Tao Liu Haoqi Wen Caifen Wang 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第2期1695-1712,共18页
The carbon tradingmarket can promote“carbon peaking”and“carbon neutrality”at low cost,but carbon emission quotas face attacks such as data forgery,tampering,counterfeiting,and replay in the electricity trading mar... The carbon tradingmarket can promote“carbon peaking”and“carbon neutrality”at low cost,but carbon emission quotas face attacks such as data forgery,tampering,counterfeiting,and replay in the electricity trading market.Certificateless signatures are a new cryptographic technology that can address traditional cryptography’s general essential certificate requirements and avoid the problem of crucial escrowbased on identity cryptography.However,most certificateless signatures still suffer fromvarious security flaws.We present a secure and efficient certificateless signing scheme by examining the security of existing certificateless signature schemes.To ensure the integrity and verifiability of electricity carbon quota trading,we propose an electricity carbon quota trading scheme based on a certificateless signature and blockchain.Our scheme utilizes certificateless signatures to ensure the validity and nonrepudiation of transactions and adopts blockchain technology to achieve immutability and traceability in electricity carbon quota transactions.In addition,validating electricity carbon quota transactions does not require time-consuming bilinear pairing operations.The results of the analysis indicate that our scheme meets existential unforgeability under adaptive selective message attacks,offers conditional identity privacy protection,resists replay attacks,and demonstrates high computing and communication performance. 展开更多
关键词 Electricity carbon trading certificateless signature blockchain forgery attack carbon quota
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Multi‐task framework of precipitation nowcasting 认领 引用 被引量：1
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作者 Zheng Zhang Chuyao Luo +2 位作者 Baoquan Zhang Hao Jiang Bowen Zhang 《CAAI Transactions on Intelligence Technology》 SCIE EI 2023年第4期1350-1363,共14页
Precipitation forecasting plays an important role in disaster warning,agricultural production,and other fields.To solve this issue,some deep learning methods are proposed to forecast future radar echo images and conve... Precipitation forecasting plays an important role in disaster warning,agricultural production,and other fields.To solve this issue,some deep learning methods are proposed to forecast future radar echo images and convert them into rainfall distributions.Prevailing spatiotemporal sequence prediction methods are usually based on a ConvRNN structure that combines a Convolutional Neural Network and Recurrent Neural Network.However,these existing methods ignore the image change prediction,which causes the coherence of the predicted image has deteriorated.Moreover,these approaches mainly focus on complicating model structure to exploit more historical spatiotemporal representations.Nevertheless,they ignore introducing other valuable information to improve predictions.To tackle these two issues,we propose GCMT‐ConvRNN,a multi‐ask framework of ConvRNN.Except for precipitation nowcasting as the main task,it combines the motion field estimation and sub‐regression as auxiliary tasks.In this framework,the motion field estimation task can provide motion information,and the sub‐regression task offers future information.Besides,to reduce the negative transfer between the auxiliary tasks and the main task,we propose a new loss function based on the correlation of gradients in different tasks.The experiments show that all models applied in our framework achieve stable and effective improvement. 展开更多
关键词 deep neural networks motion estimation
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Message Verification Protocol Based on Bilinear Pairings and Elliptic Curves for Enhanced Security in Vehicular Ad Hoc Networks 认领 引用
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作者 Vincent Omollo Nyangaresi Arkan A.Ghaib +6 位作者 Hend Muslim Jasim Zaid Ameen Abduljabbar Junchao Ma Mustafa A.Al Sibahee Abdulla J.Y.Aldarwish Ali Hasan Ali Husam A.Neamah 《Computers, Materials & Continua》 SCIE EI 2024年第10期1029-1057,共29页
Vehicular ad hoc networks(VANETs)provide intelligent navigation and efficient route management,resulting in time savings and cost reductions in the transportation sector.However,the exchange of beacons and messages ov... Vehicular ad hoc networks(VANETs)provide intelligent navigation and efficient route management,resulting in time savings and cost reductions in the transportation sector.However,the exchange of beacons and messages over public channels among vehicles and roadside units renders these networks vulnerable to numerous attacks and privacy violations.To address these challenges,several privacy and security preservation protocols based on blockchain and public key cryptography have been proposed recently.However,most of these schemes are limited by a long execution time and massive communication costs,which make them inefficient for on-board units(OBUs).Additionally,some of them are still susceptible to many attacks.As such,this study presents a novel protocol based on the fusion of elliptic curve cryptography(ECC)and bilinear pairing(BP)operations.The formal security analysis is accomplished using the Burrows–Abadi–Needham(BAN)logic,demonstrating that our scheme is verifiably secure.The proposed scheme’s informal security assessment also shows that it provides salient security features,such as non-repudiation,anonymity,and unlinkability.Moreover,the scheme is shown to be resilient against attacks,such as packet replays,forgeries,message falsifications,and impersonations.From the performance perspective,this protocol yields a 37.88%reduction in communication overheads and a 44.44%improvement in the supported security features.Therefore,the proposed scheme can be deployed in VANETs to provide robust security at low overheads. 展开更多
关键词 Attacks bilinear elliptic curve cryptography(ECC) privacy security vehicular ad hoc network(VANET)
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Partial Time-Varying Coefficient Regression and Autoregressive Mixed Model 认领 引用
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作者 Hui Li Zhiqiang Cao 《Open Journal of Endocrine and Metabolic Diseases》 2023年第4期514-533,共20页
Regression and autoregressive mixed models are classical models used to analyze the relationship between time series response variable and other covariates. The coefficients in traditional regression and autoregressiv... Regression and autoregressive mixed models are classical models used to analyze the relationship between time series response variable and other covariates. The coefficients in traditional regression and autoregressive mixed models are constants. However, for complicated data, the coefficients of covariates may change with time. In this article, we propose a kind of partial time-varying coefficient regression and autoregressive mixed model and obtain the local weighted least-square estimators of coefficient functions by the local polynomial technique. The asymptotic normality properties of estimators are derived under regularity conditions, and simulation studies are conducted to empirically examine the finite-sample performances of the proposed estimators. Finally, we use real data about Lake Shasta inflow to illustrate the application of the proposed model. 展开更多
关键词 Regression and Autoregressive Time Series Partial Time-Varying Coefficient Local Polynomial
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Partial Time-Varying Coefficient Regression and Autoregressive Mixed Model 认领 引用
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作者 Hui Li Zhiqiang Cao 《Open Journal of Statistics》 2023年第4期514-533,共20页
Regression and autoregressive mixed models are classical models used to analyze the relationship between time series response variable and other covariates. The coefficients in traditional regression and autoregressiv... Regression and autoregressive mixed models are classical models used to analyze the relationship between time series response variable and other covariates. The coefficients in traditional regression and autoregressive mixed models are constants. However, for complicated data, the coefficients of covariates may change with time. In this article, we propose a kind of partial time-varying coefficient regression and autoregressive mixed model and obtain the local weighted least-square estimators of coefficient functions by the local polynomial technique. The asymptotic normality properties of estimators are derived under regularity conditions, and simulation studies are conducted to empirically examine the finite-sample performances of the proposed estimators. Finally, we use real data about Lake Shasta inflow to illustrate the application of the proposed model. 展开更多
关键词 Regression and Autoregressive Time Series Partial Time-Varying Coefficient Local Polynomial
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Blockchain smart contracts for decentralized matching of counterparties and automatic settlement of financial derivatives 认领 引用
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作者 Hua Wang Jinjing Liu Jian Zhao 《Blockchain(Research and Applications)》 EI CSCD 2025年第4期80-85,共6页
Financial derivatives are widely recognized for their effectiveness in managing interest rate risk,demonstrating the principle of comparative advantage in finance.However,traditional financial derivative transactions ... Financial derivatives are widely recognized for their effectiveness in managing interest rate risk,demonstrating the principle of comparative advantage in finance.However,traditional financial derivative transactions are often complex and can expose participants to market and credit risks.To mitigate these risks,reduce transaction costs,and enhance liquidity,this paper proposes a blockchain-based matching mechanism for financial derivatives that uses smart contracts for decentralized counterparty matching and settlement.Smart contracts facilitate secure data sharing among participants,ensuring the integrity and immutability of transaction data.We design a transaction pool mechanism-based smart contracts for counterparty matching and automatic settlement of financial derivatives involving real fiat currencies and introduce an efficient peer-to-peer counterparty matching method,where the entire trading process is conducted on a decentralized blockchain,ensuring greater security and transparency.A prototype implementation based on Ethereum smart contracts validates the effectiveness of our proposed model,demonstrating its potential to streamline and secure financial derivative transactions. 展开更多
关键词 Blockchain Decentralized finance Smart contract Financial derivatives
SFNIC:Hybrid Spatial-Frequency Information for Lightweight Neural Image Compression 认领 引用 被引量：1
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作者 Youneng Bao Wen Tan +3 位作者 Mu Li Jiacong Chen Qingyu Mao Yongsheng Liang 《CAAI Transactions on Intelligence Technology》 SCIE EI CSCD 2025年第6期1717-1730,共14页
Neural image compression(NIC)has shown remarkable rate-distortion(R-D)efficiency.However,the considerable computational and spatial complexity of most NIC methods presents deployment challenges on resource-constrained... Neural image compression(NIC)has shown remarkable rate-distortion(R-D)efficiency.However,the considerable computational and spatial complexity of most NIC methods presents deployment challenges on resource-constrained devices.We introduce a lightweight neural image compression framework designed to efficiently process both local and global information.In this framework,the convolutional branch extracts local information,whereas the frequency domain branch extracts global information.To capture global information without the high computational costs of dense pixel operations,such as attention mechanisms,Fourier transform is employed.This approach allows for the manipulation of global information in the frequency domain.Additionally,we employ feature shift operations as a strategy to acquire large receptive fields without any computational cost,thus circumventing the need for large kernel convolution.Our framework achieves a superior balance between ratedistortion performance and complexity.On varying resolution sets,our method not only achieves rate-distortion(R-D)performance on par with versatile video coding(VVC)intra and other state-of-the-art(SOTA)NIC methods but also exhibits the lowest computational requirements,with approximately 200 KMACs/pixel.The code will be available at http://gffzz188fe103f8f1460aswx05cfco9k9x69o6.ffgz.tsg.suse.edu.cn/baoyu2020/SFNIC. 展开更多
关键词 deep learning image coding neural network video coding
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Exploring High Dimensional Feature Space With Channel-Spatial Nonlinear Transforms for Learned Image Compression 认领 引用 被引量：1
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作者 Wen Tan Fanyang Meng +2 位作者 Chao Li Youneng Bao Yongsheng Liang 《CAAI Transactions on Intelligence Technology》 SCIE EI CSCD 2025年第4期1235-1253,共19页
Nonlinear transforms have significantly advanced learned image compression(LIC),particularly using residual blocks.This transform enhances the nonlinear expression ability and obtain compact feature representation by ... Nonlinear transforms have significantly advanced learned image compression(LIC),particularly using residual blocks.This transform enhances the nonlinear expression ability and obtain compact feature representation by enlarging the receptive field,which indicates how the convolution process extracts features in a high dimensional feature space.However,its functionality is restricted to the spatial dimension and network depth,limiting further improvements in network performance due to insufficient information interaction and representation.Crucially,the potential of high dimensional feature space in the channel dimension and the exploration of network widthesolution remain largely untapped.In this paper,we consider nonlinear transforms from the perspective of feature space,defining high-dimensional feature spaces in different dimensions and investigating the specific effects.Firstly,we introduce the dimension increasing and decreasing transforms in both channel and spatial dimensions to obtain high dimensional feature space and achieve better feature extraction.Secondly,we design a channel-spatial fusion residual transform(CSR),which incorporates multi-dimensional transforms for a more effective representation.Furthermore,we simplify the proposed fusion transform to obtain a slim architecture(CSR-sm),balancing network complexity and compression performance.Finally,we build the overall network with stacked CSR transforms to achieve better compression and reconstruction.Experimental results demonstrate that the proposed method can achieve superior ratedistortion performance compared to the existing LIC methods and traditional codecs.Specifically,our proposed method achieves 9.38%BD-rate reduction over VVC on Kodak dataset. 展开更多
关键词 high dimensional feature space learned image compression nonlinear transform the dimension increase and decrease
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SFFSlib:A Python library for optimizing attribute layouts from micro to macro scales in network visualization 认领 引用
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作者 Ke-Chao Zhang Sheng-Yue Jiang Jing Xiao 《Chinese Physics B》 SCIE EI CAS CSCD 2025年第5期124-138,共15页
Complex network modeling characterizes system relationships and structures,while network visualization enables intuitive analysis and interpretation of these patterns.However,existing network visualization tools exhib... Complex network modeling characterizes system relationships and structures,while network visualization enables intuitive analysis and interpretation of these patterns.However,existing network visualization tools exhibit significant limitations in representing attributes of complex networks at various scales,particularly failing to provide advanced visual representations of specific nodes and edges,community affiliation attribution,and global scalability.These limitations substantially impede the intuitive analysis and interpretation of complex network patterns through visual representation.To address these limitations,we propose SFFSlib,a multi-scale network visualization framework incorporating novel methods to highlight attribute representation in diverse network scenarios and optimize structural feature visualization.Notably,we have enhanced the visualization of pivotal details at different scales across diverse network scenarios.The visualization algorithms proposed within SFFSlib were applied to real-world datasets and benchmarked against conventional layout algorithms.The experimental results reveal that SFFSlib significantly enhances the clarity of visualizations across different scales,offering a practical solution for the advancement of network attribute representation and the overall enhancement of visualization quality. 展开更多
关键词 complex network visualization layout algorithm signed network fuzzy community structure social bot network
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An introduction and review on innovative silicon implementations of implantable/scalp EEG chips for data acquisition, seizure/behavior detection, and brain stimulation 认领 引用 被引量：2
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作者 Weiwei Shi Jinyong Zhang +2 位作者 Zhiguo Zhang Lizhi Hu Yongqian Su 《Brain Science Advances》 2020年第3期242-254,共13页
Technological advances in the semiconductor industry and the increasing demand and development of wearable medical systems have enabled the development of dedicated chips for complex electroencephalogram(EEG)signal pr... Technological advances in the semiconductor industry and the increasing demand and development of wearable medical systems have enabled the development of dedicated chips for complex electroencephalogram(EEG)signal processing with smart functions and artificial intelligence-based detections/classifications.Around 10 million transistors are integrated into a 1 mm2 silicon wafer surface in the dedicated chip,making wearable EEG systems a powerful dedicated processor instead of a wireless raw data transceiver.The reduction of amplifiers and analog-digital converters on the silicon surface makes it possible to place the analog front-end circuits within a tiny packaged chip;therefore,enabling high-count EEG acquisition channels.This article introduces and reviews the state-of-the-art dedicated chip designs for EEG processing,particularly for wearable systems.Furthermore,the analog circuits and digital platforms are included,and the technical details of circuit topology and logic architecture are presented in detail. 展开更多
关键词 biomedical chip wearable EEG system digital system chip energy-efficient circuit EEG signal acquisition
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PediaBench:a comprehensive Chinese pediatric dataset for benchmarking large language models 认领 引用
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作者 Qian ZHANG Panfeng CHEN +6 位作者 Linkun FENG Shuyu LIU Jiali LI Heng ZHAO Mei CHEN Hui LI Yanhao WANG 《Frontiers of Computer Science》 SCIE EI CAS CSCD 2026年第3期177-179,共3页
1 Introduction.Recently,Large Language Models(LLMs),with their remarkable language understanding,reasoning,and generation capabilities,have shown exceptional performance in question-answering(QA)tasks.With this trend,... 1 Introduction.Recently,Large Language Models(LLMs),with their remarkable language understanding,reasoning,and generation capabilities,have shown exceptional performance in question-answering(QA)tasks.With this trend,there is an increasing interest in applying LLMs to QA in the medical domain[1]. 展开更多
关键词 pediatric large language models medical domain language models llms question answering
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Zero-inflated non-central negative binomial distribution 认领 引用
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作者 TIAN Wei-zhong LIU Ting-ting YANG Yao-ting 《Applied Mathematics(A Journal of Chinese Universities)》 SCIE CSCD 2022年第2期187-198,共12页
In this article, the zero-inflated non-central negative binomial(ZINNB) distribution is introduced. Some of its basic properties are obtained. In addition, we use the maximum likelihood estimation method to estimate t... In this article, the zero-inflated non-central negative binomial(ZINNB) distribution is introduced. Some of its basic properties are obtained. In addition, we use the maximum likelihood estimation method to estimate the parameters of the ZINNB distribution, and illustrate its application by fitting the actual data sets. 展开更多
关键词 zero-in ated non-central negative binomial distribution maximum likelihood estimation good-ness of fit
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Shock Wave Structure of One-Dimensional Hydro-Elastoplastic Riemann Problem with Elastic-Plastic-Fluid Phase Transition 认领 引用
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作者 Xiao Li Zhijun Shen +1 位作者 Hongping Zhang Gang Xu 《Advances in Applied Mathematics and Mechanics》 SCIE CSCD 2025年第2期580-598,共19页
In this work,the types of shock wave structure for hydro-elastoplastic model under compression are researched.The emphasis focuses on the theory of shock transition in the presence of elastic-plastic-fluid phase trans... In this work,the types of shock wave structure for hydro-elastoplastic model under compression are researched.The emphasis focuses on the theory of shock transition in the presence of elastic-plastic-fluid phase transition.As a result,in addition to the classical three-wave structure,two new shock wave patterns are found with the increase of loading strength.Several numerical tests are presented to verify the existence of the three types of wave structure. 展开更多
关键词 Shock wave structure Hydro-elastoplastic model shock transition
A survey on sequential recommendation 认领 引用 被引量：2
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作者 Li-Wei PAN Wei-Ke PAN +2 位作者 Mei-Yan WEI Hong-Zhi YIN Zhong MING 《Frontiers of Computer Science》 SCIE EI CAS CSCD 2026年第3期83-114,共32页
Different from most conventional recommendation problems,sequential recommendation(SR)focuses on learning users’preferences by exploiting the internal order and dependency among the interacted items,which has receive... Different from most conventional recommendation problems,sequential recommendation(SR)focuses on learning users’preferences by exploiting the internal order and dependency among the interacted items,which has received significant attention from both researchers and practitioners.In recent years,we have witnessed great progress and achievements in this field,necessitating a new survey.In this survey,we study the SR problem from a new perspective(i.e.,the construction of an item’s properties),and summarize the most recent techniques used in sequential recommendation such as multi-modal SR,generative SR,LLM-powered SR,ultra-long SR,and data-augmented SR.Moreover,we introduce some frontier research topics in SR,e.g.,open-domain SR,data-centric SR,cloud-edge collaborative SR,continuous SR,SR for good,and explainable SR.We believe that our survey could be served as a valuable roadmap for readers in this field. 展开更多
关键词 sequential recommendation ID-based side information recent advancements new problems
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Tunable and scalable broadband metamaterial absorber involving VO2-based phase transition 认领 引用 被引量：11
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作者 Lei Lei Fei Lou +3 位作者 Keyu Tao Haixuan Huang Xin Cheng Ping Xu 《Photonics Research》 SCIE EI CAS CSCD 2019年第7期49-56,共8页
Optical absorbers with dynamic tuning features are able to flexibly control the absorption performance, which offers a good platform for realizing optical switching, filtering, modulating, etc. Here, we propose a ther... Optical absorbers with dynamic tuning features are able to flexibly control the absorption performance, which offers a good platform for realizing optical switching, filtering, modulating, etc. Here, we propose a thermally tunable broadband absorber applying a patterned plasmonic metasurface with thermo-chromic vanadium dioxide (VO2) spacers. An actively tunable absorption bandwidth and peak resonant wavelength in the region from the near-to mid-infrared (NMIR) are simultaneously achieved with the insulating.metallic phase transition ofVO2·Moreover, the scalable unit cell,which is composed of multi-width sub-cells, provides a new freedom to further manipulate (i.e., broaden or narrow) the absorption bandwidth while maintaining a high relative absorption bandwidth and efficient absorbance at the same time. For both transverse-electric and transverse-magnetic polarizations, the proposed nanostructure exhibits a high absorption over a wide angular range up to 60°.This method holds a promising potential for versatile utilizations in optical integrated devices,NMIR photodetection, thermal emitters, smart temperature control systems,and so fbrth. 展开更多
关键词 Tunable scalable transition
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A CELL-CENTERED GODUNOV METHOD BASED ON STAGGERED DATA DISTRIBUTION,PART Ⅰ:ONE-DIMENSIONAL CASE 认领 引用
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作者 Jiayin Zhai Xiao Li Zhijun Shen 《Journal of Computational Mathematics》 SCIE CSCD 2024年第4期1172-1196,共25页
This paper presents a cell-centered Godunov method based on staggered data distribu-tion in Eulerian framework.The motivation is to reduce the intrinsic entropy dissipation of classical Godunov methods in the calculat... This paper presents a cell-centered Godunov method based on staggered data distribu-tion in Eulerian framework.The motivation is to reduce the intrinsic entropy dissipation of classical Godunov methods in the calculation of an isentropic or rarefaction flow.At the same time,the property of accurate shock capturing is also retained.By analyzing the factors that cause nonphysical entropy in the conventional Godunov methods,we introduce two velocities rather than a single velocity in a cell to reduce kinetic energy dissipation.A series of redistribution strategies are adopted to update subcell quantities in order to improve accuracy.Numerical examples validate that the present method can dramatically reduce nonphysical entropy increase.Mathematics subject classification:35Q35,76N15,76M12. 展开更多
关键词 Godunov method Riemann solver Rarefaction wave Nonphysical entropy increase.
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