The rapid development of mobile network brings opportunities for researchers to analyze user behaviors based on largescale network traffic data. It is important for Internet Service Providers(ISP) to optimize resource...The rapid development of mobile network brings opportunities for researchers to analyze user behaviors based on largescale network traffic data. It is important for Internet Service Providers(ISP) to optimize resource allocation and provide customized services to users. The first step of analyzing user behaviors is to extract information of user actions from HTTP traffic data by multi-pattern URL matching. However, the efficiency is a huge problem when performing this work on massive network traffic data. To solve this problem, we propose a novel and accurate algorithm named Multi-Pattern Parallel Matching(MPPM) that takes advantage of HashMap in data searching for extracting user behaviors from big network data more effectively. Extensive experiments based on real-world traffic data prove the ability of MPPM algorithm to deal with massive HTTP traffic with better performance on accuracy, concurrency and efficiency. We expect the proposed algorithm and it parallelized implementation would be a solid base to build a high-performance analysis engine of user behavior based on massive HTTP traffic data processing.展开更多
The traditional multiple pattern matching algorithm, deterministic finite state automata, is implemented by tree structure. A new algorithm is proposed by substituting sequential binary tree for traditional tree. It i...The traditional multiple pattern matching algorithm, deterministic finite state automata, is implemented by tree structure. A new algorithm is proposed by substituting sequential binary tree for traditional tree. It is proved by experiment that the algorithm has three features, its construction process is quick, its cost of memory is small. At the same time, its searching process is as quick as the traditional algorithm. The algorithm is suitable for the application which requires preprocessing the patterns dynamically.展开更多
Multi-pattern matching with wildcards is a problem of finding the occurrence of all patterns in a pattern set {p^1,… ,p^k} in a given text t. If the percentage of wildcards in pattern set is not high, this problem ca...Multi-pattern matching with wildcards is a problem of finding the occurrence of all patterns in a pattern set {p^1,… ,p^k} in a given text t. If the percentage of wildcards in pattern set is not high, this problem can be solved using finite automata. We introduce a multi-pattern matching algorithm with a fixed number of wildcards to overcome the high percentage of the occurrence of wildcards in patterns. In our proposed method, patterns are matched as bit patterns using a sliding window approach. The window is a bit window that slides along the given text, matching against stored bit patterns. Matching process is executed using bit wise operations. The experimental results demonstrate that the percentage of wildcard occurrence does not affect the proposed algorithm＇s performance and the proposed algorithm is more efficient than the algorithms based on the fast Fourier transform. The proposed algorithm is simple to implement and runs efficiently in O（n ＋ d（n/σ ）（m/w）） time, where n is text length, d is symbol distribution over k patterns, m is pattern length, and σ is alphabet size.展开更多
Pattern matching is a fundamental approach to detect malicious behaviors and information over Internet, which has been gradually used in high-speed network traffic analysis. However, there is a performance bottleneck ...Pattern matching is a fundamental approach to detect malicious behaviors and information over Internet, which has been gradually used in high-speed network traffic analysis. However, there is a performance bottleneck for multi-pattern matching on online compressed network traffic(CNT), this is because malicious and intrusion codes are often embedded into compressed network traffic. In this paper, we propose an online fast and multi-pattern matching algorithm on compressed network traffic(FMMCN). FMMCN employs two types of jumping, i.e. jumping during sliding window and a string jump scanning strategy to skip unnecessary compressed bytes. Moreover, FMMCN has the ability to efficiently process multiple large volume of networks such as HTTP traffic, vehicles traffic, and other Internet-based services. The experimental results show that FMMCN can ignore more than 89.5% of bytes, and its maximum speed reaches 176.470MB/s in a midrange switches device, which is faster than the current fastest algorithm ACCH by almost 73.15 MB/s.展开更多
Most existing multi-pattern matching algorithms are designed for single English texts leading to issues such as missed matches and space expansion when applied to Chinese-English mixed-text environments.The Hash Trie-...Most existing multi-pattern matching algorithms are designed for single English texts leading to issues such as missed matches and space expansion when applied to Chinese-English mixed-text environments.The Hash Trie-based matching machine demonstrates strong compatibility with both Chinese and English,ensuring high accuracy in text processing and subtree positioning.In this study,a novel functional framework based on the HashTrie structure is proposed and mechanically verified using Isabelle/HOL.This framework is applied to design Functional Multi-Pattern Matching(FMPM),the first functional multi-pattern matching algorithm for Chinese-English mixed texts.FMPM constructs the HashTrie matching machine using character codes and threads the machine according to the associations between pattern strings.The experimental results show that as the stored string information increases,the proposed algorithm demonstrates more significant optimization in retrieval efficiency.FMPM simplifies the implementation of the Threaded Hash Trie(THT)for Chinese-English mixed texts,effectively reducing the uncertainties in the transition from the algorithm description to code implementation.FMPM addresses the problem of space explosion Chinese-English mixed texts and avoids issues such as bound variable iteration errors.The functional framework of the HashTrie structure serves as a reference for the formal verification of future HashTrie-based algorithms.展开更多
The increased demand for personalized customization calls for new production modes to enhance collaborations among a wide range of manufacturing practitioners who unnecessarily trust each other.In this article,a block...The increased demand for personalized customization calls for new production modes to enhance collaborations among a wide range of manufacturing practitioners who unnecessarily trust each other.In this article,a blockchain-enabled manufacturing collaboration framework is proposed,with a focus on the production capacity matching problem for blockchainbased peer-to-peer(P2P)collaboration.First,a digital model of production capacity description is built for trustworthy and transparent sharing over the blockchain.Second,an optimization problem is formulated for P2P production capacity matching with objectives to maximize both social welfare and individual benefits of all participants.Third,a feasible solution based on an iterative double auction mechanism is designed to determine the optimal price and quantity for production capacity matching with a lack of personal information.It facilitates automation of the matching process while protecting users'privacy via blockchainbased smart contracts.Finally,simulation results from the Hyperledger Fabric-based prototype show that the proposed approach increases social welfare by 1.4%compared to the Bayesian game-based approach,makes all participants profitable,and achieves 90%fairness of enterprises.展开更多
Ground source heat pump systems demonstrate significant potential for northern rural heating applications;however,the effectiveness of these systems is often limited by challenging geological conditions.For instance,i...Ground source heat pump systems demonstrate significant potential for northern rural heating applications;however,the effectiveness of these systems is often limited by challenging geological conditions.For instance,in certain regions,the installation of buried pipes for heat exchangers may be complicated,and these pipes may not always serve as efficient low-temperature heat sources for the heat pumps of the system.To address this issue,the current study explored the use of solar-energy-collecting equipment to supplement buried pipes.In this design,both solar energy and geothermal energy provide low-temperature heat to the heat pump.First,a simulation model of a solar‒ground source heat pump coupling system was established using TRNSYS.The accuracy of this model was validated through experiments and simulations on various system configurations,including varying numbers of buried pipes,different areas of solar collectors,and varying volumes of water tanks.The simulations examined the coupling characteristics of these components and their influence on system performance.The results revealed that the operating parameters of the system remained consistent across the following configurations:three buried pipes,burial depth of 20 m,collector area of 6 m^(2),and water tank volume of 0.5 m^(3);four buried pipes,burial depth of 20 m,collector area of 3 m^(2),and water tank volume of 0.5 m^(3);and five buried pipes with a burial depth of 20 m.Furthermore,the heat collection capacity of the solar collectors spanning an area of 3 m^(2)was found to be equivalent to that of one buried pipe.Moreover,the findings revealed that the solar‒ground source heat pump coupling system demonstrated a lower annual cumulative energy consumption compared to the ground source heat pump system,presenting a reduction of 5.31%compared to the energy consumption of the latter.展开更多
The concept of matching energy was proposed by Gutman and Wagner firstly in 2012. Let G be a simple graph of order n and λ1, λ2, . . . , λn be the zeros of its matching polynomial. The matching energy of a graph G ...The concept of matching energy was proposed by Gutman and Wagner firstly in 2012. Let G be a simple graph of order n and λ1, λ2, . . . , λn be the zeros of its matching polynomial. The matching energy of a graph G is defined as ME(G) = Pni=1 |λi|. By the famous Coulson’s formula, matching energies can also be calculated by an improper integral depending on a parameter. A k-claw attaching graph Gu(k) refers to the graph obtained by attaching k pendent edges to the graph G at the vertex u, where u is called the root of Gu(k). In this paper, we use some theories of mathematical analysis to obtain a new technique to compare the matching energies of two k-claw attaching graphs Gu(k) and Hv(k) with the same order, that is, limk→∞[ME(Gu(k)) − ME(Hv(k))] = ME(G − u) − ME(H − v). By the technique, we finally determine unicyclic graphs of order n with the 9th to 13th minimal matching energies for all n ≥ 58.展开更多
With the rapid development of online education,the impact of interface design on learning experience has become increasingly prominent.Reasonable color matching can effectively improve learning efficiency,enhance user...With the rapid development of online education,the impact of interface design on learning experience has become increasingly prominent.Reasonable color matching can effectively improve learning efficiency,enhance user engagement,and improve visual experience.This paper analyzes the application of color matching in interface design,discusses the principle of color matching in online course interfaces,and puts forward some design strategies.It provides a practical reference for the interface design of an online education platform.展开更多
Session-based recommendation systems(SBR)are pivotal in suggesting items by analyzing anonymized sequences of user interactions.Traditional methods,while competent,often fall short in two critical areas:they fail to a...Session-based recommendation systems(SBR)are pivotal in suggesting items by analyzing anonymized sequences of user interactions.Traditional methods,while competent,often fall short in two critical areas:they fail to address potential inter-session item transitions,which are behavioral dependencies that extend beyond individual session boundaries,and they rely on monolithic item aggregation to construct session representations.This approach does not capture the multi-scale and heterogeneous nature of user intent,leading to a decrease in modeling accuracy.To overcome these limitations,a novel approach called HMGS has been introduced.This system incorporates dual graph architectures to enhance the recommendation process.A global transition graph captures latent cross-session item dependencies,while a heterogeneous intra-session graph encodesmulti-scale item embeddings through localized feature propagation.Additionally,amulti-tier graphmatchingmechanism aligns user preference signals across different granularities,significantly improving interest localization accuracy.Empirical validation on benchmark datasets(Tmall and Diginetica)confirms HMGS’s efficacy against state-of-the-art baselines.Quantitative analysis reveals performance gains of 20.54%and 12.63%in Precision@10 on Tmall and Diginetica,respectively.Consistent improvements are observed across auxiliary metrics,with MRR@10,Precision@20,and MRR@20 exhibiting enhancements between 4.00%and 21.36%,underscoring the framework’s robustness in multi-faceted recommendation scenarios.展开更多
After the design of aerospace products is completed,a manufacturability assessment needs to be conducted based on 3D model's features in terms of modeling quality and process design,otherwise the cost of design ch...After the design of aerospace products is completed,a manufacturability assessment needs to be conducted based on 3D model's features in terms of modeling quality and process design,otherwise the cost of design changes will increase.Due to the poor structure and low reusability of product manufacturing feature information and assessment knowledge in the current aerospace product manufacturability assessment process,it is difficult to realize automated manufacturability assessment.To address these issues,a domain ontology model is established for aerospace product manufacturability assessment in this paper.On this basis,a structured representation method of manufacturability assessment knowledge and a knowledge graph data layer construction method are proposed.Based on the semantic information and association information expressed by the knowledge graph,a rule matching method based on subgraph matching is proposed to improve the precision and recall.Finally,applications and experiments based on the software platform verify the effectiveness of the proposed knowledge graph construction and rule matching method.展开更多
The effects of micro-ridge-furrow planting(MR)on yield and the efficiency of light,water,and thermal resource use in rapeseed were tested in a three-year field experiment comparing MR to conventional flat planting.MR ...The effects of micro-ridge-furrow planting(MR)on yield and the efficiency of light,water,and thermal resource use in rapeseed were tested in a three-year field experiment comparing MR to conventional flat planting.MR enhanced canopy heterogeneity by altering the leaf angle between plants on ridges and furrows.The heterogeneous canopy environment increased intercepted photosynthetic active radiation,alleviated canopy temperature stress,and optimized canopy humidity,leading to improvements in light-nitrogen matching and net photosynthetic rate.Consequently,dry matter and yield increased by 13.0%and 11.0%,respectively,while radiation,thermal,and precipitation utilization efficiency increased by 12.3%-16.2%.The corresponding improvements in yield and resource use efficiency were attributed to a heterogeneous canopy environment that improved microclimatic conditions.展开更多
The cross-modal person re-identification task aims to match visible and infrared images of the same individual.The main challenges in this field arise from significant modality differences between individuals and the ...The cross-modal person re-identification task aims to match visible and infrared images of the same individual.The main challenges in this field arise from significant modality differences between individuals and the lack of high-quality cross-modal correspondence methods.Existing approaches often attempt to establish modality correspondence by extracting shared features across different modalities.However,these methods tend to focus on local information extraction and fail to fully leverage the global identity information in the cross-modal features,resulting in limited correspondence accuracy and suboptimal matching performance.To address this issue,we propose a quadratic graph matching method designed to overcome the challenges posed by modality differences through precise cross-modal relationship alignment.This method transforms the cross-modal correspondence problem into a graph matching task and minimizes the matching cost using a center search mechanism.Building on this approach,we further design a block reasoning module to uncover latent relationships between person identities and optimize the modality correspondence results.The block strategy not only improves the efficiency of updating gallery images but also enhances matching accuracy while reducing computational load.Experimental results demonstrate that our proposed method outperforms the state-of-the-art methods on the SYSU-MM01,RegDB,and RGBNT201 datasets,achieving excellent matching accuracy and robustness,thereby validating its effectiveness in cross-modal person re-identification.展开更多
To enhance the resistance of honeycomb sandwich panel against local impact,this study delved into the matching relationship between face sheets and core.An integrated approach,combining experiment,simulation,and theor...To enhance the resistance of honeycomb sandwich panel against local impact,this study delved into the matching relationship between face sheets and core.An integrated approach,combining experiment,simulation,and theoretical methods,was used.Local loading experiments were conducted to validate the accuracy of the finite element model.Furthermore,a control equation was formulated to correlate structural parameters with response modes,and a matching coefficientλ(representing the ratio of core thickness to face sheet thickness)was introduced to establish a link between these parameters and impact characteristics.A demand-driven reverse design methodology for structural parameters was developed,with numerical simulations employed to assess its effectiveness.The results indicate that the proposed theory can accurately predict response modes and key indicators.An increase in theλbolsters the structural indentation resistance while concurrently heightens the likelihood of penetration.Conversely,a decrease in theλimproves the resistance to penetration,albeit potentially leading to significant deformations in the rear face sheet.Numerical simulations demonstrate that the reverse design methodology significantly enhances the structural penetration resistance.Comparative analyses indicate that appropriate matching reduces indentation depth by 27.4% and indentation radius by 41.8%of the proposed structure.展开更多
BACKGROUND Recently,Olympus Corporation released new scopes(XZ1200/EZ1500).However,there have been few reports on this topic,although improvement in adenoma detection rate(ADR)by texture and color enhancement imaging(...BACKGROUND Recently,Olympus Corporation released new scopes(XZ1200/EZ1500).However,there have been few reports on this topic,although improvement in adenoma detection rate(ADR)by texture and color enhancement imaging(TXI)or computer-aided detection system(CAD)has been reported.AIM To investigate the effects of the scope on the detection of adenomas and sessile serrated lesions(SSLs).METHODS The subjects were patients who underwent pancolonic chromoendoscopy using the EVIS X1 video system center between May 2023 and October 2024.The patients were divided into the new(CF-XZ1200/CF-EZ1500)and 290 series(CF-HQ290Z/PCF-H290Z)groups.Propensity score matching was performed for age,sex,examination purpose,endoscopist,preparation,TXI use,and CAD use.The effects of the scope were analyzed in terms of the ADR,SSL detection rate(SDR),and mean number of adenomas per colonoscopy(APC).RESULTS Of the 7014 patients enrolled,2138 pairs were extracted by propensity score matching(mean age 55.4 years,45.5%male).The new scopes group had a significantly higher ADR than the 290 series group[51.5%vs 45.5%,odds ratio(OR)=1.27,95%CI:1.13-1.43,P<0.001].Similarly,the new scopes group had significantly higher SDR(7.8%vs 5.7%,OR=1.41,95%CI:1.11-1.80,P=0.005)and APC(0.90 vs 0.76,OR=1.11,95%CI:1.05-1.17,P<0.001)than the 290 series group.CONCLUSION In conclusion,the new scope(CF-XZ1200/CF-EZ1500)enhanced the detection of adenomas and SSLs compared to the old ones(290 series).展开更多
The impact of location services on people’s lives has grown significantly in the era of widespread smart device usage.Due to global navigation satellite system(GNSS)signal rejection,weak signal strength in indoor env...The impact of location services on people’s lives has grown significantly in the era of widespread smart device usage.Due to global navigation satellite system(GNSS)signal rejection,weak signal strength in indoor environments and radio signal interference caused by multiwall environments,which collectively lead to significant positioning errors,vision-based positioning has emerged as a crucial method in indoor positioning research.This paper introduces a scale hierarchical matching model to tackle challenges associated with large visual databases and high scene similarity,both of which will compromise matching accuracy and lead to prolonged positioning delays.The proposed model establishes an image feature database using GIST features and speeded up robust feature(SURF)in the offline stage.In the online stage,a positioning navigating algorithm is constructed based on Dijkstra’s path planning.Additionally,a corresponding Android application has been developed to facilitate visual positioning and navigation in indoor environments.Experimental results obtained in real indoor environments demonstrate that the proposed method significantly enhances positioning accuracy compared with similar algorithms,while effectively reducing time overhead.This improvement caters to the requirements for indoor positioning and navigation,thereby meeting user needs.展开更多
Objectives This study aimed to analyze the prevalence of long-term central line-associated bloodstream infections(CLABSI)among hospitalized adults with cancer in Italy and compare the characteristics of patients who r...Objectives This study aimed to analyze the prevalence of long-term central line-associated bloodstream infections(CLABSI)among hospitalized adults with cancer in Italy and compare the characteristics of patients who required long-term central venous access device(LCVAD)substitution due to prior CLABSI with those who had never experienced CLABSI.Methods The study was conducted in hospitals across northern and central Italy using a multicenter,observational,cross-sectional design from March to September 2021.A total of 174 adults with cancer were included.Data were collected through electronic case report forms,including demographic,clinical,treatment-related,and catheter-related variables.Propensity score matching(PSM)was used to compare the characteristics of patients who underwent LCVAD substitution due to previous CLABSI with those who never experienced CLABSI.Multiple correspondence analysis(MCA)was conducted to explore the patterns within matched subgroups.Results The prevalence of CLABSI was 3%,and 5.2%of patients required LCVAD substitution due to prior CLABSI.After applying PSM,the groups were successfully balanced for sex,age,presence of metastases,comorbidities,BMI,received treatments,corticosteroid therapy,ongoing antibiotics,hormone therapy,type of LCVAD,lumens,and utilization frequency.Hematologic cancer was more frequent in the CLABSI group(44.4%)compared to the non-infective group(0),with a statistically significant difference(P=0.045).MCA revealed potential patterns among matched subgroups but did not identify statistically significant associations:patients with previous LCVAD substitution were more frequently associated with a history of prior infections,ongoing antibiotic therapy,and unspecified primary lesion locations;conversely,patients who never experienced CLABSI tended to cluster around characteristics such as hormone therapy and corticosteroid therapy.Conclusions These findings emphasize the importance of continuous monitoring,individualized infection prevention strategies in oncology nursing practice.Future research with larger datasets is needed to validate these findings and develop tailored interventions to reduce CLABSI risks.展开更多
To enhance network security,this study employs a deep graph matching model for vulnerability similarity detection.The model utilizes a Word Embedding layer to vectorize data words,an Image Embedding layer to vectorize...To enhance network security,this study employs a deep graph matching model for vulnerability similarity detection.The model utilizes a Word Embedding layer to vectorize data words,an Image Embedding layer to vectorize data graphs,and an LSTM layer to extract the associations between word and graph vectors.A Dropout layer is applied to randomly deactivate neurons in the LSTM layer,while a Softmax layer maps the LSTM analysis results.Finally,a fully connected layer outputs the detection results with a dimension of 1.Experimental results demonstrate that the AUC of the deep graph matching vulnerability similarity detection model is 0.9721,indicating good stability.The similarity scores for vulnerabilities such as memory leaks,buffer overflows,and targeted attacks are close to 1,showing significant similarity.In contrast,the similarity scores for vulnerabilities like out-of-bounds memory access and logical design flaws are less than 0.4,indicating good similarity detection performance.The model’s evaluation metrics are all above 97%,with high detection accuracy,which is beneficial for improving network security.展开更多
BACKGROUND The relationship between low physical activity and cognitive impairment in type 2 diabetes mellitus(T2DM)patients remains unclear.AIM To explore this association and identify risk factors for cognitive impa...BACKGROUND The relationship between low physical activity and cognitive impairment in type 2 diabetes mellitus(T2DM)patients remains unclear.AIM To explore this association and identify risk factors for cognitive impairment in elderly T2DM patients.METHODS A retrospective analysis was conducted on 245 elderly T2DM patients treated at Xuanwu Hospital,Beijing,in 2023.Patients were categorized into low physical activity(n=126)and non-low physical activity(n=119)groups.After propensity score matching(PSM)of 100 pairs,univariate and binary logistic regression analyses identified risk factors for cognitive impairment.A predictive model was constructed and evaluated using receiver operating characteristic curve analysis.RESULTS Before PSM,the percentage of cognitive impairment was higher in the low physical activity group(P<0.05),but after PSM,this difference was not signi-ficant(P>0.05).Additionally,on regression analyses after PSM,age,occupation type,history of stroke,malnutrition,and frailty remained independent factors associated with cognitive impairment,while low physical activity did not.The constructed risk prediction model for cognitive impairment in elderly T2DM patients exhibited an area under the curve of 0.77.CONCLUSION Low physical activity was not associated with cognitive impairment in our study population.Some results differed before and after PSM analysis,indicating that PSM supports objective assessment of risk factors by controlling for selection bias and confounding factors related to population characteristics.The constructed cognitive risk model insight for the development of a clinical tool for early prevention of cognitive impairment in elderly patients.展开更多
With the development of the Semantic Web,the number of ontologies grows exponentially and the semantic relationships between ontologies become more and more complex,understanding the true semantics of specific terms o...With the development of the Semantic Web,the number of ontologies grows exponentially and the semantic relationships between ontologies become more and more complex,understanding the true semantics of specific terms or concepts in an ontology is crucial for the matching task.At present,the main challenges facing ontology matching tasks based on representation learning methods are how to improve the embedding quality of ontology knowledge and how to integrate multiple features of ontology efficiently.Therefore,we propose an Ontology Matching Method Based on the Gated Graph Attention Model(OM-GGAT).Firstly,the semantic knowledge related to concepts in the ontology is encoded into vectors using the OWL2Vec^(*)method,and the relevant path information from the root node to the concept is embedded to understand better the true meaning of the concept itself and the relationship between concepts.Secondly,the ontology is transformed into the corresponding graph structure according to the semantic relation.Then,when extracting the features of the ontology graph nodes,different attention weights are assigned to each adjacent node of the central concept with the help of the attention mechanism idea.Finally,gated networks are designed to further fuse semantic and structural embedding representations efficiently.To verify the effectiveness of the proposed method,comparative experiments on matching tasks were carried out on public datasets.The results show that the OM-GGAT model can effectively improve the efficiency of ontology matching.展开更多
基金supported in part by National Natural Science Foundation of China(61671078)the Director Funds of Beijing Key Laboratory of Network System Architecture and Convergence(2017BKL-NSACZJ-06)
文摘The rapid development of mobile network brings opportunities for researchers to analyze user behaviors based on largescale network traffic data. It is important for Internet Service Providers(ISP) to optimize resource allocation and provide customized services to users. The first step of analyzing user behaviors is to extract information of user actions from HTTP traffic data by multi-pattern URL matching. However, the efficiency is a huge problem when performing this work on massive network traffic data. To solve this problem, we propose a novel and accurate algorithm named Multi-Pattern Parallel Matching(MPPM) that takes advantage of HashMap in data searching for extracting user behaviors from big network data more effectively. Extensive experiments based on real-world traffic data prove the ability of MPPM algorithm to deal with massive HTTP traffic with better performance on accuracy, concurrency and efficiency. We expect the proposed algorithm and it parallelized implementation would be a solid base to build a high-performance analysis engine of user behavior based on massive HTTP traffic data processing.
基金This project was supported by the National "863" High Technology Research and Development Program of China(2003AA142160) and the National Natural Science Foundation of China (60402019)
文摘The traditional multiple pattern matching algorithm, deterministic finite state automata, is implemented by tree structure. A new algorithm is proposed by substituting sequential binary tree for traditional tree. It is proved by experiment that the algorithm has three features, its construction process is quick, its cost of memory is small. At the same time, its searching process is as quick as the traditional algorithm. The algorithm is suitable for the application which requires preprocessing the patterns dynamically.
基金Supported by the European Framework Program(FP7)(FP7-PEOPLE-2011-IRSES)the National Sci-Tech Support Plan of China(2014BAH02F03)
文摘Multi-pattern matching with wildcards is a problem of finding the occurrence of all patterns in a pattern set {p^1,… ,p^k} in a given text t. If the percentage of wildcards in pattern set is not high, this problem can be solved using finite automata. We introduce a multi-pattern matching algorithm with a fixed number of wildcards to overcome the high percentage of the occurrence of wildcards in patterns. In our proposed method, patterns are matched as bit patterns using a sliding window approach. The window is a bit window that slides along the given text, matching against stored bit patterns. Matching process is executed using bit wise operations. The experimental results demonstrate that the percentage of wildcard occurrence does not affect the proposed algorithm＇s performance and the proposed algorithm is more efficient than the algorithms based on the fast Fourier transform. The proposed algorithm is simple to implement and runs efficiently in O（n ＋ d（n/σ ）（m/w）） time, where n is text length, d is symbol distribution over k patterns, m is pattern length, and σ is alphabet size.
基金supported by China MOST project (No.2012BAH46B04)
文摘Pattern matching is a fundamental approach to detect malicious behaviors and information over Internet, which has been gradually used in high-speed network traffic analysis. However, there is a performance bottleneck for multi-pattern matching on online compressed network traffic(CNT), this is because malicious and intrusion codes are often embedded into compressed network traffic. In this paper, we propose an online fast and multi-pattern matching algorithm on compressed network traffic(FMMCN). FMMCN employs two types of jumping, i.e. jumping during sliding window and a string jump scanning strategy to skip unnecessary compressed bytes. Moreover, FMMCN has the ability to efficiently process multiple large volume of networks such as HTTP traffic, vehicles traffic, and other Internet-based services. The experimental results show that FMMCN can ignore more than 89.5% of bytes, and its maximum speed reaches 176.470MB/s in a midrange switches device, which is faster than the current fastest algorithm ACCH by almost 73.15 MB/s.
基金Supported by the National Natural Science Foundation of China(62462036,62462037)Jiangxi Provincial Natural Science Foundation(20242BAB26017,20232BAB202010)+1 种基金Cultivation Project for Academic and Technical Leader in Major Disciplines in Jiangxi Province(20232BCJ22013)the Jiangxi Province Graduate Innovation Found Project(YC2024-S214)。
文摘Most existing multi-pattern matching algorithms are designed for single English texts leading to issues such as missed matches and space expansion when applied to Chinese-English mixed-text environments.The Hash Trie-based matching machine demonstrates strong compatibility with both Chinese and English,ensuring high accuracy in text processing and subtree positioning.In this study,a novel functional framework based on the HashTrie structure is proposed and mechanically verified using Isabelle/HOL.This framework is applied to design Functional Multi-Pattern Matching(FMPM),the first functional multi-pattern matching algorithm for Chinese-English mixed texts.FMPM constructs the HashTrie matching machine using character codes and threads the machine according to the associations between pattern strings.The experimental results show that as the stored string information increases,the proposed algorithm demonstrates more significant optimization in retrieval efficiency.FMPM simplifies the implementation of the Threaded Hash Trie(THT)for Chinese-English mixed texts,effectively reducing the uncertainties in the transition from the algorithm description to code implementation.FMPM addresses the problem of space explosion Chinese-English mixed texts and avoids issues such as bound variable iteration errors.The functional framework of the HashTrie structure serves as a reference for the formal verification of future HashTrie-based algorithms.
基金supported in part by the National Natural Science Foundation of China(62273310)the Natural Science Foundation of Zhejiang Province of China(LY22F030006,LZ24F030009)
文摘The increased demand for personalized customization calls for new production modes to enhance collaborations among a wide range of manufacturing practitioners who unnecessarily trust each other.In this article,a blockchain-enabled manufacturing collaboration framework is proposed,with a focus on the production capacity matching problem for blockchainbased peer-to-peer(P2P)collaboration.First,a digital model of production capacity description is built for trustworthy and transparent sharing over the blockchain.Second,an optimization problem is formulated for P2P production capacity matching with objectives to maximize both social welfare and individual benefits of all participants.Third,a feasible solution based on an iterative double auction mechanism is designed to determine the optimal price and quantity for production capacity matching with a lack of personal information.It facilitates automation of the matching process while protecting users'privacy via blockchainbased smart contracts.Finally,simulation results from the Hyperledger Fabric-based prototype show that the proposed approach increases social welfare by 1.4%compared to the Bayesian game-based approach,makes all participants profitable,and achieves 90%fairness of enterprises.
基金supported by 2024 Central Guidance Local Science and Technology Development Fund Project"Study on the mechanism and evaluation method of thermal pollution in water bodies,as well as research on thermal carrying capacity".(Grant 246Z4506G)Key Research and Development Project in Hebei Province:"Key Technologies and Equipment Research and Demonstration of Multiple Energy Complementary(Electricity,Heat,Cold System)for Solar Energy,Geothermal Energy,Phase Change Energy"(Grant 236Z4310G)the Hebei Academy of Sciences Key Research and Development Program"Research on Heat Transfer Mechanisms and Efficient Applications of Intermediate and Deep Geothermal Energy"(22702)。
文摘Ground source heat pump systems demonstrate significant potential for northern rural heating applications;however,the effectiveness of these systems is often limited by challenging geological conditions.For instance,in certain regions,the installation of buried pipes for heat exchangers may be complicated,and these pipes may not always serve as efficient low-temperature heat sources for the heat pumps of the system.To address this issue,the current study explored the use of solar-energy-collecting equipment to supplement buried pipes.In this design,both solar energy and geothermal energy provide low-temperature heat to the heat pump.First,a simulation model of a solar‒ground source heat pump coupling system was established using TRNSYS.The accuracy of this model was validated through experiments and simulations on various system configurations,including varying numbers of buried pipes,different areas of solar collectors,and varying volumes of water tanks.The simulations examined the coupling characteristics of these components and their influence on system performance.The results revealed that the operating parameters of the system remained consistent across the following configurations:three buried pipes,burial depth of 20 m,collector area of 6 m^(2),and water tank volume of 0.5 m^(3);four buried pipes,burial depth of 20 m,collector area of 3 m^(2),and water tank volume of 0.5 m^(3);and five buried pipes with a burial depth of 20 m.Furthermore,the heat collection capacity of the solar collectors spanning an area of 3 m^(2)was found to be equivalent to that of one buried pipe.Moreover,the findings revealed that the solar‒ground source heat pump coupling system demonstrated a lower annual cumulative energy consumption compared to the ground source heat pump system,presenting a reduction of 5.31%compared to the energy consumption of the latter.
基金Supported by the National Natural Science Foundation of China(Nos.12271439,11871398)the National College Students Innovation and Entrepreneurship Training Program(No.201910699173)。
文摘The concept of matching energy was proposed by Gutman and Wagner firstly in 2012. Let G be a simple graph of order n and λ1, λ2, . . . , λn be the zeros of its matching polynomial. The matching energy of a graph G is defined as ME(G) = Pni=1 |λi|. By the famous Coulson’s formula, matching energies can also be calculated by an improper integral depending on a parameter. A k-claw attaching graph Gu(k) refers to the graph obtained by attaching k pendent edges to the graph G at the vertex u, where u is called the root of Gu(k). In this paper, we use some theories of mathematical analysis to obtain a new technique to compare the matching energies of two k-claw attaching graphs Gu(k) and Hv(k) with the same order, that is, limk→∞[ME(Gu(k)) − ME(Hv(k))] = ME(G − u) − ME(H − v). By the technique, we finally determine unicyclic graphs of order n with the 9th to 13th minimal matching energies for all n ≥ 58.
文摘With the rapid development of online education,the impact of interface design on learning experience has become increasingly prominent.Reasonable color matching can effectively improve learning efficiency,enhance user engagement,and improve visual experience.This paper analyzes the application of color matching in interface design,discusses the principle of color matching in online course interfaces,and puts forward some design strategies.It provides a practical reference for the interface design of an online education platform.
基金funded by the State Grid Hebei Electric Power Company(Project Number:KJ2023-093).
文摘Session-based recommendation systems(SBR)are pivotal in suggesting items by analyzing anonymized sequences of user interactions.Traditional methods,while competent,often fall short in two critical areas:they fail to address potential inter-session item transitions,which are behavioral dependencies that extend beyond individual session boundaries,and they rely on monolithic item aggregation to construct session representations.This approach does not capture the multi-scale and heterogeneous nature of user intent,leading to a decrease in modeling accuracy.To overcome these limitations,a novel approach called HMGS has been introduced.This system incorporates dual graph architectures to enhance the recommendation process.A global transition graph captures latent cross-session item dependencies,while a heterogeneous intra-session graph encodesmulti-scale item embeddings through localized feature propagation.Additionally,amulti-tier graphmatchingmechanism aligns user preference signals across different granularities,significantly improving interest localization accuracy.Empirical validation on benchmark datasets(Tmall and Diginetica)confirms HMGS’s efficacy against state-of-the-art baselines.Quantitative analysis reveals performance gains of 20.54%and 12.63%in Precision@10 on Tmall and Diginetica,respectively.Consistent improvements are observed across auxiliary metrics,with MRR@10,Precision@20,and MRR@20 exhibiting enhancements between 4.00%and 21.36%,underscoring the framework’s robustness in multi-faceted recommendation scenarios.
基金Sponsored by the National Key Research and Development Program from Ministry of Science and Technology of the People's Republic of China (Grant No.2020YFB1711403)。
文摘After the design of aerospace products is completed,a manufacturability assessment needs to be conducted based on 3D model's features in terms of modeling quality and process design,otherwise the cost of design changes will increase.Due to the poor structure and low reusability of product manufacturing feature information and assessment knowledge in the current aerospace product manufacturability assessment process,it is difficult to realize automated manufacturability assessment.To address these issues,a domain ontology model is established for aerospace product manufacturability assessment in this paper.On this basis,a structured representation method of manufacturability assessment knowledge and a knowledge graph data layer construction method are proposed.Based on the semantic information and association information expressed by the knowledge graph,a rule matching method based on subgraph matching is proposed to improve the precision and recall.Finally,applications and experiments based on the software platform verify the effectiveness of the proposed knowledge graph construction and rule matching method.
基金supported by the National Key Research and Development Program of China (2021YFD1901200)the Key Research and Development Program of Hubei Province of China (2023BBB028)+1 种基金the Earmarked Fund of Hubei province of Chinathe Fundamental Research Funds for the Central Universities (2662024ZKQD005)
文摘The effects of micro-ridge-furrow planting(MR)on yield and the efficiency of light,water,and thermal resource use in rapeseed were tested in a three-year field experiment comparing MR to conventional flat planting.MR enhanced canopy heterogeneity by altering the leaf angle between plants on ridges and furrows.The heterogeneous canopy environment increased intercepted photosynthetic active radiation,alleviated canopy temperature stress,and optimized canopy humidity,leading to improvements in light-nitrogen matching and net photosynthetic rate.Consequently,dry matter and yield increased by 13.0%and 11.0%,respectively,while radiation,thermal,and precipitation utilization efficiency increased by 12.3%-16.2%.The corresponding improvements in yield and resource use efficiency were attributed to a heterogeneous canopy environment that improved microclimatic conditions.
文摘The cross-modal person re-identification task aims to match visible and infrared images of the same individual.The main challenges in this field arise from significant modality differences between individuals and the lack of high-quality cross-modal correspondence methods.Existing approaches often attempt to establish modality correspondence by extracting shared features across different modalities.However,these methods tend to focus on local information extraction and fail to fully leverage the global identity information in the cross-modal features,resulting in limited correspondence accuracy and suboptimal matching performance.To address this issue,we propose a quadratic graph matching method designed to overcome the challenges posed by modality differences through precise cross-modal relationship alignment.This method transforms the cross-modal correspondence problem into a graph matching task and minimizes the matching cost using a center search mechanism.Building on this approach,we further design a block reasoning module to uncover latent relationships between person identities and optimize the modality correspondence results.The block strategy not only improves the efficiency of updating gallery images but also enhances matching accuracy while reducing computational load.Experimental results demonstrate that our proposed method outperforms the state-of-the-art methods on the SYSU-MM01,RegDB,and RGBNT201 datasets,achieving excellent matching accuracy and robustness,thereby validating its effectiveness in cross-modal person re-identification.
基金Project(2022A02480004)supported by the Major Project of China Railway Design CorporationProject(2023RC1011)supported by the Science and Technology Innovation Program of Hunan Province,China+2 种基金Project(2024JJ6515)supported by the Hunan Provincial Natural Science Foundation,ChinaProject(kq2402220)supported by the Natural Science Foundation of Changsha City,ChinaProject(52402438)supported by the National Natural Science Foundation of China。
文摘To enhance the resistance of honeycomb sandwich panel against local impact,this study delved into the matching relationship between face sheets and core.An integrated approach,combining experiment,simulation,and theoretical methods,was used.Local loading experiments were conducted to validate the accuracy of the finite element model.Furthermore,a control equation was formulated to correlate structural parameters with response modes,and a matching coefficientλ(representing the ratio of core thickness to face sheet thickness)was introduced to establish a link between these parameters and impact characteristics.A demand-driven reverse design methodology for structural parameters was developed,with numerical simulations employed to assess its effectiveness.The results indicate that the proposed theory can accurately predict response modes and key indicators.An increase in theλbolsters the structural indentation resistance while concurrently heightens the likelihood of penetration.Conversely,a decrease in theλimproves the resistance to penetration,albeit potentially leading to significant deformations in the rear face sheet.Numerical simulations demonstrate that the reverse design methodology significantly enhances the structural penetration resistance.Comparative analyses indicate that appropriate matching reduces indentation depth by 27.4% and indentation radius by 41.8%of the proposed structure.
基金Ethics Committee of the Certified Institutional Review Board of the Yoyogi Mental Clinic(No.RKK227).
文摘BACKGROUND Recently,Olympus Corporation released new scopes(XZ1200/EZ1500).However,there have been few reports on this topic,although improvement in adenoma detection rate(ADR)by texture and color enhancement imaging(TXI)or computer-aided detection system(CAD)has been reported.AIM To investigate the effects of the scope on the detection of adenomas and sessile serrated lesions(SSLs).METHODS The subjects were patients who underwent pancolonic chromoendoscopy using the EVIS X1 video system center between May 2023 and October 2024.The patients were divided into the new(CF-XZ1200/CF-EZ1500)and 290 series(CF-HQ290Z/PCF-H290Z)groups.Propensity score matching was performed for age,sex,examination purpose,endoscopist,preparation,TXI use,and CAD use.The effects of the scope were analyzed in terms of the ADR,SSL detection rate(SDR),and mean number of adenomas per colonoscopy(APC).RESULTS Of the 7014 patients enrolled,2138 pairs were extracted by propensity score matching(mean age 55.4 years,45.5%male).The new scopes group had a significantly higher ADR than the 290 series group[51.5%vs 45.5%,odds ratio(OR)=1.27,95%CI:1.13-1.43,P<0.001].Similarly,the new scopes group had significantly higher SDR(7.8%vs 5.7%,OR=1.41,95%CI:1.11-1.80,P=0.005)and APC(0.90 vs 0.76,OR=1.11,95%CI:1.05-1.17,P<0.001)than the 290 series group.CONCLUSION In conclusion,the new scope(CF-XZ1200/CF-EZ1500)enhanced the detection of adenomas and SSLs compared to the old ones(290 series).
基金Supported by the National Natural Science Foundation of China(No.61971162,61771186)the Natural Science Foundation of Heilongjiang Province(No.PL2024F025)+1 种基金the Open Research Fund of National Mobile Communications Research Laboratory in Southeast University(No.2023D07)the Fundamental Scientific Research Funds of Heilongjiang Province(No.2022-KYYWF-1050).
文摘The impact of location services on people’s lives has grown significantly in the era of widespread smart device usage.Due to global navigation satellite system(GNSS)signal rejection,weak signal strength in indoor environments and radio signal interference caused by multiwall environments,which collectively lead to significant positioning errors,vision-based positioning has emerged as a crucial method in indoor positioning research.This paper introduces a scale hierarchical matching model to tackle challenges associated with large visual databases and high scene similarity,both of which will compromise matching accuracy and lead to prolonged positioning delays.The proposed model establishes an image feature database using GIST features and speeded up robust feature(SURF)in the offline stage.In the online stage,a positioning navigating algorithm is constructed based on Dijkstra’s path planning.Additionally,a corresponding Android application has been developed to facilitate visual positioning and navigation in indoor environments.Experimental results obtained in real indoor environments demonstrate that the proposed method significantly enhances positioning accuracy compared with similar algorithms,while effectively reducing time overhead.This improvement caters to the requirements for indoor positioning and navigation,thereby meeting user needs.
基金part of a project that has received funding from the 5x1000 Humanitas funds。
文摘Objectives This study aimed to analyze the prevalence of long-term central line-associated bloodstream infections(CLABSI)among hospitalized adults with cancer in Italy and compare the characteristics of patients who required long-term central venous access device(LCVAD)substitution due to prior CLABSI with those who had never experienced CLABSI.Methods The study was conducted in hospitals across northern and central Italy using a multicenter,observational,cross-sectional design from March to September 2021.A total of 174 adults with cancer were included.Data were collected through electronic case report forms,including demographic,clinical,treatment-related,and catheter-related variables.Propensity score matching(PSM)was used to compare the characteristics of patients who underwent LCVAD substitution due to previous CLABSI with those who never experienced CLABSI.Multiple correspondence analysis(MCA)was conducted to explore the patterns within matched subgroups.Results The prevalence of CLABSI was 3%,and 5.2%of patients required LCVAD substitution due to prior CLABSI.After applying PSM,the groups were successfully balanced for sex,age,presence of metastases,comorbidities,BMI,received treatments,corticosteroid therapy,ongoing antibiotics,hormone therapy,type of LCVAD,lumens,and utilization frequency.Hematologic cancer was more frequent in the CLABSI group(44.4%)compared to the non-infective group(0),with a statistically significant difference(P=0.045).MCA revealed potential patterns among matched subgroups but did not identify statistically significant associations:patients with previous LCVAD substitution were more frequently associated with a history of prior infections,ongoing antibiotic therapy,and unspecified primary lesion locations;conversely,patients who never experienced CLABSI tended to cluster around characteristics such as hormone therapy and corticosteroid therapy.Conclusions These findings emphasize the importance of continuous monitoring,individualized infection prevention strategies in oncology nursing practice.Future research with larger datasets is needed to validate these findings and develop tailored interventions to reduce CLABSI risks.
基金Special Project Funded by Tsinghua University Press:“Engineering Drawing and CAD”Course Construction and Textbook Development。
文摘To enhance network security,this study employs a deep graph matching model for vulnerability similarity detection.The model utilizes a Word Embedding layer to vectorize data words,an Image Embedding layer to vectorize data graphs,and an LSTM layer to extract the associations between word and graph vectors.A Dropout layer is applied to randomly deactivate neurons in the LSTM layer,while a Softmax layer maps the LSTM analysis results.Finally,a fully connected layer outputs the detection results with a dimension of 1.Experimental results demonstrate that the AUC of the deep graph matching vulnerability similarity detection model is 0.9721,indicating good stability.The similarity scores for vulnerabilities such as memory leaks,buffer overflows,and targeted attacks are close to 1,showing significant similarity.In contrast,the similarity scores for vulnerabilities like out-of-bounds memory access and logical design flaws are less than 0.4,indicating good similarity detection performance.The model’s evaluation metrics are all above 97%,with high detection accuracy,which is beneficial for improving network security.
基金Supported by The Capital Funds for Health Improvement and Research,No.2024-2-1033The Beijing Municipal Administration of Hospitals Incubating Program,No.PX2022032+1 种基金Post-subsidy Fund from the National Clinical Research Center,the Ministry of Science and Technology of China,No.303-01-001-0272-08The Beijing Municipal Public Welfare Development and Reform Pilot Project for Medical Research Institutes,No.JYY2023-13.
文摘BACKGROUND The relationship between low physical activity and cognitive impairment in type 2 diabetes mellitus(T2DM)patients remains unclear.AIM To explore this association and identify risk factors for cognitive impairment in elderly T2DM patients.METHODS A retrospective analysis was conducted on 245 elderly T2DM patients treated at Xuanwu Hospital,Beijing,in 2023.Patients were categorized into low physical activity(n=126)and non-low physical activity(n=119)groups.After propensity score matching(PSM)of 100 pairs,univariate and binary logistic regression analyses identified risk factors for cognitive impairment.A predictive model was constructed and evaluated using receiver operating characteristic curve analysis.RESULTS Before PSM,the percentage of cognitive impairment was higher in the low physical activity group(P<0.05),but after PSM,this difference was not signi-ficant(P>0.05).Additionally,on regression analyses after PSM,age,occupation type,history of stroke,malnutrition,and frailty remained independent factors associated with cognitive impairment,while low physical activity did not.The constructed risk prediction model for cognitive impairment in elderly T2DM patients exhibited an area under the curve of 0.77.CONCLUSION Low physical activity was not associated with cognitive impairment in our study population.Some results differed before and after PSM analysis,indicating that PSM supports objective assessment of risk factors by controlling for selection bias and confounding factors related to population characteristics.The constructed cognitive risk model insight for the development of a clinical tool for early prevention of cognitive impairment in elderly patients.
基金supported by the National Natural Science Foundation of China(grant numbers 62267005 and 42365008)the Guangxi Collaborative Innovation Center of Multi-Source Information Integration and Intelligent Processing.
文摘With the development of the Semantic Web,the number of ontologies grows exponentially and the semantic relationships between ontologies become more and more complex,understanding the true semantics of specific terms or concepts in an ontology is crucial for the matching task.At present,the main challenges facing ontology matching tasks based on representation learning methods are how to improve the embedding quality of ontology knowledge and how to integrate multiple features of ontology efficiently.Therefore,we propose an Ontology Matching Method Based on the Gated Graph Attention Model(OM-GGAT).Firstly,the semantic knowledge related to concepts in the ontology is encoded into vectors using the OWL2Vec^(*)method,and the relevant path information from the root node to the concept is embedded to understand better the true meaning of the concept itself and the relationship between concepts.Secondly,the ontology is transformed into the corresponding graph structure according to the semantic relation.Then,when extracting the features of the ontology graph nodes,different attention weights are assigned to each adjacent node of the central concept with the help of the attention mechanism idea.Finally,gated networks are designed to further fuse semantic and structural embedding representations efficiently.To verify the effectiveness of the proposed method,comparative experiments on matching tasks were carried out on public datasets.The results show that the OM-GGAT model can effectively improve the efficiency of ontology matching.
