With the rapid development of intelligent cyber-physical systems(ICPS),diverse services with varying Quality of Service(QoS)requirements have brought great challenges to traditional network resource allocation.Further...With the rapid development of intelligent cyber-physical systems(ICPS),diverse services with varying Quality of Service(QoS)requirements have brought great challenges to traditional network resource allocation.Furthermore,given the open environment and a multitude of devices,enhancing the security of ICPS is an urgent concern.To address these issues,this paper proposes a novel trusted virtual network embedding(T-VNE)approach for ICPS based combining blockchain and edge computing technologies.Additionally,the proposed algorithm leverages a deep reinforcement learning(DRL)model to optimize decision-making processes.It employs the policygradient-based agent to compute candidate embedding nodes and utilizes a breadth-first search(BFS)algorithm to determine the optimal embedding paths.Finally,through simulation experiments,the efficacy of the proposed method was validated,demonstrating outstanding performance in terms of security,revenue generation,and virtual network request(VNR)acceptance rate.展开更多
Spam emails remain one of the most persistent threats to digital communication,necessitating effective detection solutions that safeguard both individuals and organisations.We propose a spam email classification frame...Spam emails remain one of the most persistent threats to digital communication,necessitating effective detection solutions that safeguard both individuals and organisations.We propose a spam email classification frame-work that uses Bidirectional Encoder Representations from Transformers(BERT)for contextual feature extraction and a multiple-window Convolutional Neural Network(CNN)for classification.To identify semantic nuances in email content,BERT embeddings are used,and CNN filters extract discriminative n-gram patterns at various levels of detail,enabling accurate spam identification.The proposed model outperformed Word2Vec-based baselines on a sample of 5728 labelled emails,achieving an accuracy of 98.69%,AUC of 0.9981,F1 Score of 0.9724,and MCC of 0.9639.With a medium kernel size of(6,9)and compact multi-window CNN architectures,it improves performance.Cross-validation illustrates stability and generalization across folds.By balancing high recall with minimal false positives,our method provides a reliable and scalable solution for current spam detection in advanced deep learning.By combining contextual embedding and a neural architecture,this study develops a security analysis method.展开更多
Message structure reconstruction is a critical task in protocol reverse engineering,aiming to recover protocol field structures without access to source code.It enables important applications in network security,inclu...Message structure reconstruction is a critical task in protocol reverse engineering,aiming to recover protocol field structures without access to source code.It enables important applications in network security,including malware analysis and protocol fuzzing.However,existing methods suffer from inaccurate field boundary delineation and lack hierarchical relationship recovery,resulting in imprecise and incomplete reconstructions.In this paper,we propose ProRE,a novel method for reconstructing protocol field structures based on program execution slice embedding.ProRE extracts code slices from protocol parsing at runtime,converts them into embedding vectors using a data flow-sensitive assembly language model,and performs hierarchical clustering to recover complete protocol field structures.Evaluation on two datasets containing 12 protocols shows that ProRE achieves an average F1 score of 0.85 and a cophenetic correlation coefficient of 0.189,improving by 19%and 0.126%respectively over state-of-the-art methods(including BinPRE,Tupni,Netlifter,and QwQ-32B-preview),demonstrating significant superiority in both accuracy and completeness of field structure recovery.Case studies further validate the effectiveness of ProRE in practical malware analysis scenarios.展开更多
In the context of the coordinated pursuit of"carbon peak and neutrality"objectives,alongside the strategy to establish a robust agricultural nation,the economic and social development of rural areas is under...In the context of the coordinated pursuit of"carbon peak and neutrality"objectives,alongside the strategy to establish a robust agricultural nation,the economic and social development of rural areas is undergoing a profound paradigm shift.The traditional rural division of labor pattern,which depends on tangible factors such as land,labor,and capital,has increasingly encountered developmental challenges characterized by diminishing marginal returns and a detrimental cycle of internal competition.The new quality productive force,centered on data,algorithms,green technologies,bioengineering,and clean energy,offers a potential pathway for the rural division of labor system to overcome the"low-level equilibrium".This force is characterized by attributes such as non-exclusivity,replicability,network collaboration,and ecological compatibility.This paper develops a three-dimensional collaborative analytical framework encompassing"technology,institution,and culture".It systematically elucidates the internal logic by which new quality productive forces drive the transformation of the rural division of labor from"quantitative factor matching"to"qualitative structural reorganization"through three principal mechanisms:technology embedding,institutional reconstruction,and cultural coupling.Furthermore,the study proposes corresponding policy recommendations,thereby offering theoretical insights to support the modernization of China s agriculture and rural areas,as well as the development of a strong agricultural country.展开更多
Temporal knowledge graph completion(TKGC),which merges temporal information into traditional static knowledge graph completion(SKGC),has garnered increasing attention recently.Among numerous emerging approaches,transl...Temporal knowledge graph completion(TKGC),which merges temporal information into traditional static knowledge graph completion(SKGC),has garnered increasing attention recently.Among numerous emerging approaches,translation-based embedding models constitute a prominent approach in TKGC research.However,existing translation-based methods typically incorporate timestamps into entities or relations,rather than utilizing them independently.This practice fails to fully exploit the rich semantics inherent in temporal information,thereby weakening the expressive capability of models.To address this limitation,we propose embedding timestamps,like entities and relations,in one or more dedicated semantic spaces.After projecting all embeddings into a shared space,we use the relation-timestamp pair instead of the conventional relation embedding as the translation vector between head and tail entities.Our method elevates timestamps to the same representational significance as entities and relations.Based on this strategy,we introduce two novel translation-based embedding models:TE-TransR and TE-TransT.With the independent representation of timestamps,our method not only enhances capabilities in link prediction but also facilitates a relatively underexplored task,namely time prediction.To further bolster the precision and reliability of time prediction,we introduce a granular,time unit-based timestamp setting and a relation-specific evaluation protocol.Extensive experiments demonstrate that our models achieve strong performance on link prediction benchmarks,with TE-TransR outperforming existing baselines in the time prediction task.展开更多
In recent years,ransomware attacks have become one of the most common and destructive types of cyberattacks.Their impact is significant on the operations,finances and reputation of affected companies.Despite the effor...In recent years,ransomware attacks have become one of the most common and destructive types of cyberattacks.Their impact is significant on the operations,finances and reputation of affected companies.Despite the efforts of researchers and security experts to protect information systems from these attacks,the threat persists and the proposed solutions are not able to significantly stop the spread of ransomware attacks.The latest remarkable achievements of large language models(LLMs)in NLP tasks have caught the attention of cybersecurity researchers to integrate thesemodels into security threat detection.Thesemodels offer high embedding capabilities,able to extract rich semantic representations and paving theway formore accurate and adaptive solutions.In this context,we propose a new approach for ransomware detection based on an ensemblemethod that leverages three distinctLLMembeddingmodels.This ensemble strategy takes advantage of the variety of embedding methods and the strengths of each model.In the proposed solution,each embedding model is associated with an independently trainedMLP classifier.The predictions obtained are then merged using a weighted voting technique,assigning each model an influence proportional to its performance.This approach makes it possible to exploit the complementarity of representations,improve detection accuracy and robustness,and offer a more reliable solution in the face of the growing diversity and complexity of modern ransomware.展开更多
Objective To systematically evaluate the effect of acupoint catgut embedding therapy （ACET） for simple obesity. Methods Computer retrieval was used for randomized controlled trials on the treatment effect of simple ...Objective To systematically evaluate the effect of acupoint catgut embedding therapy （ACET） for simple obesity. Methods Computer retrieval was used for randomized controlled trials on the treatment effect of simple obesity with ACET in databases of the China National Knowledge Infrastructure （CNKI）, Wanfang Data system, and the China Biology Medicine disc （CBMDisc）. The Jadad Quality Scale was used in the evaluation of included studies. The outcome indicators were analyzed with the Review Manage 5.1 software. Results A total of 16 randomized controlled trials were included finally. The meta-analysis result showed that compared with the control group, there was statistically significance on the total efficiency of using ACET for simple obesity [OR=2.51, 95% confidence interval （1.74, 3.63）, Z=4.91, P〈0.000 01]. The analysis on the literature quality showed that there was only 2 article marked as 3 points. The other 25 articles marked ≤2 points. The quality of published articles was generally low. There were publication biases and the blinding method was seldom used, the losses of follow-up / drop oup / withdraw were reported with less. There were 27 acupoints used in the treatment, which mainly included Tianshu （天枢ST 25）, Zhongwan （中脘 CV 12）, Fenglong （丰隆 ST 40）, Shufen （水分 CV 9）, Qihai （气海 CV 6）, Sanyinjiao （三阴交 SP 6）, Zusnli （足三里 ST 36）, Ashi point, Daheng （大横 SP 25）. The five kinds of catgut embedding needle were injection needles ＋ acupuncture needle, specialized catgut embedding needle, spinal needle, triangular needle, and skin suture needle. Conclusion There is definite efficiency of using ACET in the treatment of simple obesity. However, the clinical efficiency still lacks of sufficient evidences. Therefore, further clinical research should be conducted in the providing of reliable evidences in the clinical decision-making in the future.展开更多
Most of the commercially-available pot seedling nursery machines are incompatible with soft-pot-trays and are labor-intensive and low in productivity.A soft-pot-tray automatic embedding system was developed in this st...Most of the commercially-available pot seedling nursery machines are incompatible with soft-pot-trays and are labor-intensive and low in productivity.A soft-pot-tray automatic embedding system was developed in this study to achieve automatic embedding of the soft pot tray into the hard tray following sowing and covering with soil.A control system was constructed using the Arduino program development environment.An embedded-hard-tray automatic lowering mechanism and conveyor-belt-based pot-tray embedding system were designed.Dynamics analysis was conducted to derive an equation to describe the embedding process of the soft pot tray into the embedded hard tray.A prototype of the soft-pot-tray automatic embedding system was manufactured and tested.The analytical equation suggested that a minimum linear velocity of 0.86 m/s was required for a complete embedding process.The experimental results showed that the embedded-hard-tray automatic lowering mechanism was reliable and stable as the tray placement success rate was greater than 99%.The successful tray embedding rate was 100%and the seed exposure rate was less than 1%with a linear velocity of the conveyor belt of 0.92 m/s.The experiment findings agreed well with the analytical results.The proposed soft-pot-tray automatic embedding system satisfied the technical specifications for a light-economical pot seedling nursery machine.展开更多
Objective This review aimed to systematically evaluate the evidence on the effects of acupoint catgut embedding （ACE） therapy for patients with polycystic ovary syndrome （PCOS）. Methods Five databases （CBM, CNKI,...Objective This review aimed to systematically evaluate the evidence on the effects of acupoint catgut embedding （ACE） therapy for patients with polycystic ovary syndrome （PCOS）. Methods Five databases （CBM, CNKI, Wanfang Database, VlP Database, and PubMed） were searched to identify relevant studies published before June 2027. The outcomes were resumption of menstruation and serum levels of testosterone （T）. The methodological quality of the included studies was judged using the Cochrane risk of bias tool. The overall level of evidence was judged by the Grading of Recommendations Assessment, Development, and Evaluation （GRADE） criteria. Results Twenty- five randomized controlled trials were included. ACE therapy significantly lowered serum T levels, and patients receiving ACE treatment reported resumption of menstruation. However, these results should be interpreted with caution due to a high risk of randomization and blinding bias, and likely publication bias. The level of evidence for resumption of menstruation and serum T levels was assessed as ＂low＂ and ＂low＂, respectively, using GRADE. Conclusion The current evidence on ACE therapy for PCOS is insufficient to draw firm conclusions due to the poor methodological quality. Future well- designed trials are needed to validate the therapeutic efficacy, safety, and mechanisms of ACE in patients with PCOS.展开更多
OBJECTIVE: To evaluate the clinical effectiveness and safety of acupoint catgut embedding and acupuncture on simple obesity by Meta-analysis. METHODS: Studies on clinical randomized controlled trials of acupoint catgu...OBJECTIVE: To evaluate the clinical effectiveness and safety of acupoint catgut embedding and acupuncture on simple obesity by Meta-analysis. METHODS: Studies on clinical randomized controlled trials of acupoint catgut embedding for simple obesity which were published from January 2015 to November 2020 were searched in Cochrane Central Register of Control Trials(Central), Pub Med, China Science and Technology Journal Database, China National Knowledge Infrastructure Database and Wanfang databases. And those that met the inclusion criteria were screened. Rev Man5.3 was used for Meta-analysis. The “Risk of Bias” tool was used to evaluate the quality of included studies. R studio software was used for the measurement of publication bias. RESULTS: A total of 33 studies were included for Metaanalysis, including 2685 patients with simple obesity. Meta-analysis results showed the comparison of effectiveness rate was relative risk(RR) = 1.12, 95%CI(1.08, 1.16), body mass index(BMI) was mean difference(MD) =-1.12, 95%CI(-2.09,-0.14), waist circumference was MD =-2.14, 95%CI(-4.22,-0.06), and body mass was MD =-2.36, 95%CI(-3.99,-0.73). On the basis of diet and exercise intervention, the effectiveness rate [RR = 1.12, 95%CI(1.05, 1.19)], BMI [MD =-0.88, 95%CI(-1.35,-0.40)], waist circumference [MD =-1.10, 95%CI(-4.27, 2.07)], and body mass [MD =-0.68, 95%CI(-2.90, 1.54)]. The risk of bias of included literatures was low. CONCLUSIONS: Acupoint catgut embedding therapy was slightly better than acupuncture therapy in most of the outcomes. Moreover, the treatment frequency of acupoint catgut embedding is less with larger stimulation intensity, which is more conducive to clinical promotion.展开更多
OBJECTIVE:To assess the efficacy of acupoint catgut embedding(ACE)for simple obesity in preclinical animal experiments.METHODS:We searched the following 14 electronic databases:PubM ed,Cochrane Library,EMBASE,Oriental...OBJECTIVE:To assess the efficacy of acupoint catgut embedding(ACE)for simple obesity in preclinical animal experiments.METHODS:We searched the following 14 electronic databases:PubM ed,Cochrane Library,EMBASE,Oriental Medicine Advanced Searching Integrated System,KoreaMed,Korean Studies Information Service System,Science-on,Research Information Sharing Service,Korea Citation Index,Korea Traditional Knowledge Portal,China Network Knowledge Infrastructure Database,Wanfang Database,Chinese Science and Technology Journal Database,and Chinese Biology Medicine Database,from inception to November 2021 without language limitation.The assessment was performed according to the guidelines of Animal Research:Reporting of in vivo experiments;and Metaanalysis was performed using Reviewer Manager 5.4.1 software.RESULTS:Twenty-four studies involving 813 animals were selected.Meta-analysis showed that ACE was beneficial for weight control[n=40,MD=-50.63,95%CI(-57.59,-43.67),P<0.00001,I 2=0%]and reduced the Lee index[n=40,MD=-18.79,95%CI(-20.01,-17.57),P<0.00001,I 2=0%].However,when efficacy of ACE was compared with that of manual acupuncture,electroacupuncture,or oilistat therapy,statistical difference was not observed between the two groups.CONCLUSIONS:This systematic review suggests that ACE may be efficacious in treating obesity.Moreover,the analyses highlighted the necessity to perform welldesigned,higher-quality experiments.展开更多
OBJECTIVE:To systematically review and analyze the effect of acupuncture and acupoint catgut embedding in treatment of abdominal obesity to provide a more reasonable clinical treatment regimen.METHODS:Ten databases we...OBJECTIVE:To systematically review and analyze the effect of acupuncture and acupoint catgut embedding in treatment of abdominal obesity to provide a more reasonable clinical treatment regimen.METHODS:Ten databases were searched as of August 2022:the English databases Pub Med,Embase,Cochrane Library,Web of Science,Wiley,and Scopus and the Chinese databases China National Knowledge Infrastructure Database,China Science and Technology Journal Database,Wanfang,and Sino Med/Chinese Biomedical Literature Database.Randomized controlled trials(RCTs)of acupuncture and acupoint catgut embedding as the main interventions to treat abdominal obesity were extracted.The investigators imported the citations into End Note version X9.1 for deduplication,screening,extraction,and integration.The risk of bias in the included RCTs was assessed according to the Cochrane Handbook.Rev Man 5.4 software was used to conduct a Meta-analysis of RCTs that met the inclusion criteria.RESULTS:Thirteen RCTs(1069 patients)were included in this study,and the data of eleven RCTs(966 patients)were include in the Meta-analysis.The results showed that acupoint catgut embedding can significantly change the weight and waist circumference of patients with abdominal obesity when compared to sham acupuncture or no treatment[mean difference(MD)=2.32,95%confidence interval(CI)(1.88,2.76),P<0.00001],[MD=3.47,95%CI(1.99,4.94),P<0.00001].The change in hip circumference after acupuncture was also significant[MD=0.89,95%CI(0.12,1.66),P=0.02].CONCLUSION:This study found that acupuncture and acupoint catgut embedding can effectively treat abdominal obesity,therefore,these interventions can be used as clinical supplements and alternative therapies.The diagnostic criteria of the existing studies and the intervention measures of the control group are not unified.It will be necessary to improve the clinical study protocols and expand the sample size to further validate the reliability of the results obtained of this study.展开更多
The parameter embedding method is applied for numerically solving the perturbed conservative systems. By means of Newtonian iteration, a simple algorithm has been constructed. Finally, the convergence of the iteration...The parameter embedding method is applied for numerically solving the perturbed conservative systems. By means of Newtonian iteration, a simple algorithm has been constructed. Finally, the convergence of the iteration is proved.展开更多
News recommendation system is designed to deal with massive news and provide personalized recommendations for users.Accurately capturing user preferences and modeling news and users is the key to news recommendation.I...News recommendation system is designed to deal with massive news and provide personalized recommendations for users.Accurately capturing user preferences and modeling news and users is the key to news recommendation.In this paper,we propose a new framework,news recommendation system based on topic embedding and knowledge embedding(NRTK).NRTK handle news titles that users have clicked on from two perspectives to obtain news and user representation embedding:1)extracting explicit and latent topic features from news and mining users’preferences for them in historical behaviors;2)extracting entities and propagating users’potential preferences in the knowledge graph.Experiments in a real-world dataset validate the effectiveness and efficiency of our approach.展开更多
The substantial competition among the news industries puts editors under the pressure of posting news articleswhich are likely to gain more user attention. Anticipating the popularity of news articles can help the edi...The substantial competition among the news industries puts editors under the pressure of posting news articleswhich are likely to gain more user attention. Anticipating the popularity of news articles can help the editorial teamsin making decisions about posting a news article. Article similarity extracted from the articles posted within a smallperiod of time is found to be a useful feature in existing popularity prediction approaches. This work proposesa new approach to estimate the popularity of news articles by adding semantics in the article similarity basedapproach of popularity estimation. A semantically enriched model is proposed which estimates news popularity bymeasuring cosine similarity between document embeddings of the news articles. Word2vec model has been used togenerate distributed representations of the news content. In this work, we define popularity as the number of timesa news article is posted on different websites. We collect data from different websites that post news concerning thedomain of cybersecurity and estimate the popularity of cybersecurity news. The proposed approach is comparedwith different models and it is shown that it outperforms the other models.展开更多
Objective:To evaluate the effectiveness and safety of acupoint catgut embedding(ACE)in combination with Chinese herbal medicine(CHM)in treating chronic urticaria(CU).Methods:We thoroughly searched Embase,PubMed,Cochra...Objective:To evaluate the effectiveness and safety of acupoint catgut embedding(ACE)in combination with Chinese herbal medicine(CHM)in treating chronic urticaria(CU).Methods:We thoroughly searched Embase,PubMed,Cochrane Library,Web of Science,China National Knowledge Infrastructure(CNKI),Wangfang database,Chinese Scientific Journal Database(VIP),and Chinese biomedical literature database(SinoMed)for relevant studies from inception until May 2022.Randomized controlled trials(RCTs)on ACE combined with CHM for CU were included.Literature search,data extraction,and risk of bias assessment were independently conducted by two authors.Results:A total of 15 RCTs with 1065 participants were included in this review.Five trials reported that the combined therapy showed a higher total effective rate,and four trials reported that the combined therapy was associated with a lower level of serum immunoglobulin E.Furthermore,two,four,and four trials reported that the combined therapy was more effective in reducing itching degree,size,and number of wheals,respectively.The combined therapy was reported to be associated with a lower recurrence rate in three trials,and with a fewer adverse reaction rate in two trials.Conclusions:ACE in combination with CHM appears to be a safe and effective therapy for patients with CU.Given the relatively low quality of the included trials,these findings should be interpreted cautiously.Further high-quality RCTs are needed to confirm our findings.展开更多
Throughout scientific research, the state space reconstruction that embeds a non-linear time series is the first and necessary step for characterizing and predicting the behavior of a complex system. This requires to ...Throughout scientific research, the state space reconstruction that embeds a non-linear time series is the first and necessary step for characterizing and predicting the behavior of a complex system. This requires to choose appropriate values of time delay T and embedding dimension dE. Three methods are applied and discussed on nonlinear time series provided by the Rössler attractor equations set: Cao’s method, the C-C method developed by Kim et al. and the C-C-1 method developed by Cai et al. A way to fix a parameter necessary to implement the last method is given. Focus has been put on small size and/or noisy time series. The reconstruction quality is measured by using a criterion based on the transformation smoothness.展开更多
Let G be a group.The family of all sets which are closed in every Hausdorf group topology of G form the family of closed sets of a T_(1) topology M_(G) on G called the Markov topology.Similarly,the family of all algeb...Let G be a group.The family of all sets which are closed in every Hausdorf group topology of G form the family of closed sets of a T_(1) topology M_(G) on G called the Markov topology.Similarly,the family of all algebraic subsets of G forms a family of closed sets for another T_(1)topology Z_(G) on G called the Zarski topology.A subgroup H of G is said to be Markov(resp.Zarski)embedded if the equality M_(G|H)=M_(H)(resp.Z_(G|H)=Z_(H))holds.I's proved that an abirary subgroup of a free group is both Zariski and Markov embedded in it.展开更多
Digital watermarking must balance imperceptibility,robustness,complexity,and security.To address the challenge of computational efficiency in trellis-based informed embedding,we propose a modified watermarking framewo...Digital watermarking must balance imperceptibility,robustness,complexity,and security.To address the challenge of computational efficiency in trellis-based informed embedding,we propose a modified watermarking framework that integrates fuzzy c-means(FCM)clustering into the generation off block codewords for labeling trellis arcs.The system incorporates a parallel trellis structure,controllable embedding parameters,and a novel informed embedding algorithm with reduced complexity.Two types of embedding schemes—memoryless and memory-based—are designed to flexibly trade-off between imperceptibility and robustness.Experimental results demonstrate that the proposed method outperforms existing approaches in bit error rate(BER)and computational complexity under various attacks,including additive noise,filtering,JPEG compression,cropping,and rotation.The integration of FCM enhances robustness by increasing the codeword distance,while preserving perceptual quality.Overall,the proposed framework is suitable for real-time and secure watermarking applications.展开更多
Tibetan medical named entity recognition(Tibetan MNER)involves extracting specific types of medical entities from unstructured Tibetan medical texts.Tibetan MNER provide important data support for the work related to ...Tibetan medical named entity recognition(Tibetan MNER)involves extracting specific types of medical entities from unstructured Tibetan medical texts.Tibetan MNER provide important data support for the work related to Tibetan medicine.However,existing Tibetan MNER methods often struggle to comprehensively capture multi-level semantic information,failing to sufficiently extract multi-granularity features and effectively filter out irrelevant information,which ultimately impacts the accuracy of entity recognition.This paper proposes an improved embedding representation method called syllable-word-sentence embedding.By leveraging features at different granularities and using un-scaled dot-product attention to focus on key features for feature fusion,the syllable-word-sentence embedding is integrated into the transformer,enhancing the specificity and diversity of feature representations.The model leverages multi-level and multi-granularity semantic information,thereby improving the performance of Tibetan MNER.We evaluate our proposed model on datasets from various domains.The results indicate that the model effectively identified three types of entities in the Tibetan news dataset we constructed,achieving an F1 score of 93.59%,which represents an improvement of 1.24%compared to the vanilla FLAT.Additionally,results from the Tibetan medical dataset we developed show that it is effective in identifying five kinds of medical entities,with an F1 score of 71.39%,which is a 1.34%improvement over the vanilla FLAT.展开更多
基金supported by the National Natural Science Foundation of China under Grant 62471493supported by the Natural Science Foundation of Shandong Province under Grant ZR2023LZH017,ZR2024MF066。
文摘With the rapid development of intelligent cyber-physical systems(ICPS),diverse services with varying Quality of Service(QoS)requirements have brought great challenges to traditional network resource allocation.Furthermore,given the open environment and a multitude of devices,enhancing the security of ICPS is an urgent concern.To address these issues,this paper proposes a novel trusted virtual network embedding(T-VNE)approach for ICPS based combining blockchain and edge computing technologies.Additionally,the proposed algorithm leverages a deep reinforcement learning(DRL)model to optimize decision-making processes.It employs the policygradient-based agent to compute candidate embedding nodes and utilizes a breadth-first search(BFS)algorithm to determine the optimal embedding paths.Finally,through simulation experiments,the efficacy of the proposed method was validated,demonstrating outstanding performance in terms of security,revenue generation,and virtual network request(VNR)acceptance rate.
基金funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2026R234)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Spam emails remain one of the most persistent threats to digital communication,necessitating effective detection solutions that safeguard both individuals and organisations.We propose a spam email classification frame-work that uses Bidirectional Encoder Representations from Transformers(BERT)for contextual feature extraction and a multiple-window Convolutional Neural Network(CNN)for classification.To identify semantic nuances in email content,BERT embeddings are used,and CNN filters extract discriminative n-gram patterns at various levels of detail,enabling accurate spam identification.The proposed model outperformed Word2Vec-based baselines on a sample of 5728 labelled emails,achieving an accuracy of 98.69%,AUC of 0.9981,F1 Score of 0.9724,and MCC of 0.9639.With a medium kernel size of(6,9)and compact multi-window CNN architectures,it improves performance.Cross-validation illustrates stability and generalization across folds.By balancing high recall with minimal false positives,our method provides a reliable and scalable solution for current spam detection in advanced deep learning.By combining contextual embedding and a neural architecture,this study develops a security analysis method.
文摘Message structure reconstruction is a critical task in protocol reverse engineering,aiming to recover protocol field structures without access to source code.It enables important applications in network security,including malware analysis and protocol fuzzing.However,existing methods suffer from inaccurate field boundary delineation and lack hierarchical relationship recovery,resulting in imprecise and incomplete reconstructions.In this paper,we propose ProRE,a novel method for reconstructing protocol field structures based on program execution slice embedding.ProRE extracts code slices from protocol parsing at runtime,converts them into embedding vectors using a data flow-sensitive assembly language model,and performs hierarchical clustering to recover complete protocol field structures.Evaluation on two datasets containing 12 protocols shows that ProRE achieves an average F1 score of 0.85 and a cophenetic correlation coefficient of 0.189,improving by 19%and 0.126%respectively over state-of-the-art methods(including BinPRE,Tupni,Netlifter,and QwQ-32B-preview),demonstrating significant superiority in both accuracy and completeness of field structure recovery.Case studies further validate the effectiveness of ProRE in practical malware analysis scenarios.
基金Supported by Key Project of Jiangsu Education Science Planning"Research on the Structural Adjustment of Higher Education in Jiangsu in the Context of High-Quality Economic Development"(B/2021/01/67).
文摘In the context of the coordinated pursuit of"carbon peak and neutrality"objectives,alongside the strategy to establish a robust agricultural nation,the economic and social development of rural areas is undergoing a profound paradigm shift.The traditional rural division of labor pattern,which depends on tangible factors such as land,labor,and capital,has increasingly encountered developmental challenges characterized by diminishing marginal returns and a detrimental cycle of internal competition.The new quality productive force,centered on data,algorithms,green technologies,bioengineering,and clean energy,offers a potential pathway for the rural division of labor system to overcome the"low-level equilibrium".This force is characterized by attributes such as non-exclusivity,replicability,network collaboration,and ecological compatibility.This paper develops a three-dimensional collaborative analytical framework encompassing"technology,institution,and culture".It systematically elucidates the internal logic by which new quality productive forces drive the transformation of the rural division of labor from"quantitative factor matching"to"qualitative structural reorganization"through three principal mechanisms:technology embedding,institutional reconstruction,and cultural coupling.Furthermore,the study proposes corresponding policy recommendations,thereby offering theoretical insights to support the modernization of China s agriculture and rural areas,as well as the development of a strong agricultural country.
基金supported by the National Natural Science Foundation of China under Grant No.72293575.
文摘Temporal knowledge graph completion(TKGC),which merges temporal information into traditional static knowledge graph completion(SKGC),has garnered increasing attention recently.Among numerous emerging approaches,translation-based embedding models constitute a prominent approach in TKGC research.However,existing translation-based methods typically incorporate timestamps into entities or relations,rather than utilizing them independently.This practice fails to fully exploit the rich semantics inherent in temporal information,thereby weakening the expressive capability of models.To address this limitation,we propose embedding timestamps,like entities and relations,in one or more dedicated semantic spaces.After projecting all embeddings into a shared space,we use the relation-timestamp pair instead of the conventional relation embedding as the translation vector between head and tail entities.Our method elevates timestamps to the same representational significance as entities and relations.Based on this strategy,we introduce two novel translation-based embedding models:TE-TransR and TE-TransT.With the independent representation of timestamps,our method not only enhances capabilities in link prediction but also facilitates a relatively underexplored task,namely time prediction.To further bolster the precision and reliability of time prediction,we introduce a granular,time unit-based timestamp setting and a relation-specific evaluation protocol.Extensive experiments demonstrate that our models achieve strong performance on link prediction benchmarks,with TE-TransR outperforming existing baselines in the time prediction task.
基金funded by the Deanship of Graduate Studies and Scientific Research at Jouf University under grant No.(DGSSR-2024-02-01176).
文摘In recent years,ransomware attacks have become one of the most common and destructive types of cyberattacks.Their impact is significant on the operations,finances and reputation of affected companies.Despite the efforts of researchers and security experts to protect information systems from these attacks,the threat persists and the proposed solutions are not able to significantly stop the spread of ransomware attacks.The latest remarkable achievements of large language models(LLMs)in NLP tasks have caught the attention of cybersecurity researchers to integrate thesemodels into security threat detection.Thesemodels offer high embedding capabilities,able to extract rich semantic representations and paving theway formore accurate and adaptive solutions.In this context,we propose a new approach for ransomware detection based on an ensemblemethod that leverages three distinctLLMembeddingmodels.This ensemble strategy takes advantage of the variety of embedding methods and the strengths of each model.In the proposed solution,each embedding model is associated with an independently trainedMLP classifier.The predictions obtained are then merged using a weighted voting technique,assigning each model an influence proportional to its performance.This approach makes it possible to exploit the complementarity of representations,improve detection accuracy and robustness,and offer a more reliable solution in the face of the growing diversity and complexity of modern ransomware.
基金Supported by the Naional Natural Science Fund Project of China:81072883,81173342
文摘Objective To systematically evaluate the effect of acupoint catgut embedding therapy （ACET） for simple obesity. Methods Computer retrieval was used for randomized controlled trials on the treatment effect of simple obesity with ACET in databases of the China National Knowledge Infrastructure （CNKI）, Wanfang Data system, and the China Biology Medicine disc （CBMDisc）. The Jadad Quality Scale was used in the evaluation of included studies. The outcome indicators were analyzed with the Review Manage 5.1 software. Results A total of 16 randomized controlled trials were included finally. The meta-analysis result showed that compared with the control group, there was statistically significance on the total efficiency of using ACET for simple obesity [OR=2.51, 95% confidence interval （1.74, 3.63）, Z=4.91, P〈0.000 01]. The analysis on the literature quality showed that there was only 2 article marked as 3 points. The other 25 articles marked ≤2 points. The quality of published articles was generally low. There were publication biases and the blinding method was seldom used, the losses of follow-up / drop oup / withdraw were reported with less. There were 27 acupoints used in the treatment, which mainly included Tianshu （天枢ST 25）, Zhongwan （中脘 CV 12）, Fenglong （丰隆 ST 40）, Shufen （水分 CV 9）, Qihai （气海 CV 6）, Sanyinjiao （三阴交 SP 6）, Zusnli （足三里 ST 36）, Ashi point, Daheng （大横 SP 25）. The five kinds of catgut embedding needle were injection needles ＋ acupuncture needle, specialized catgut embedding needle, spinal needle, triangular needle, and skin suture needle. Conclusion There is definite efficiency of using ACET in the treatment of simple obesity. However, the clinical efficiency still lacks of sufficient evidences. Therefore, further clinical research should be conducted in the providing of reliable evidences in the clinical decision-making in the future.
基金The authors gratefully acknowledge the financial support from the National Key Research and Development Program of China(Grant No.2018YFD0700703)National Natural Science Foundation of China(Grant No.51675188)and the Earmarked Fund for Modern Agro-industry Technology Research System(Grant No.CARS-01-43).
文摘Most of the commercially-available pot seedling nursery machines are incompatible with soft-pot-trays and are labor-intensive and low in productivity.A soft-pot-tray automatic embedding system was developed in this study to achieve automatic embedding of the soft pot tray into the hard tray following sowing and covering with soil.A control system was constructed using the Arduino program development environment.An embedded-hard-tray automatic lowering mechanism and conveyor-belt-based pot-tray embedding system were designed.Dynamics analysis was conducted to derive an equation to describe the embedding process of the soft pot tray into the embedded hard tray.A prototype of the soft-pot-tray automatic embedding system was manufactured and tested.The analytical equation suggested that a minimum linear velocity of 0.86 m/s was required for a complete embedding process.The experimental results showed that the embedded-hard-tray automatic lowering mechanism was reliable and stable as the tray placement success rate was greater than 99%.The successful tray embedding rate was 100%and the seed exposure rate was less than 1%with a linear velocity of the conveyor belt of 0.92 m/s.The experiment findings agreed well with the analytical results.The proposed soft-pot-tray automatic embedding system satisfied the technical specifications for a light-economical pot seedling nursery machine.
文摘Objective This review aimed to systematically evaluate the evidence on the effects of acupoint catgut embedding （ACE） therapy for patients with polycystic ovary syndrome （PCOS）. Methods Five databases （CBM, CNKI, Wanfang Database, VlP Database, and PubMed） were searched to identify relevant studies published before June 2027. The outcomes were resumption of menstruation and serum levels of testosterone （T）. The methodological quality of the included studies was judged using the Cochrane risk of bias tool. The overall level of evidence was judged by the Grading of Recommendations Assessment, Development, and Evaluation （GRADE） criteria. Results Twenty- five randomized controlled trials were included. ACE therapy significantly lowered serum T levels, and patients receiving ACE treatment reported resumption of menstruation. However, these results should be interpreted with caution due to a high risk of randomization and blinding bias, and likely publication bias. The level of evidence for resumption of menstruation and serum T levels was assessed as ＂low＂ and ＂low＂, respectively, using GRADE. Conclusion The current evidence on ACE therapy for PCOS is insufficient to draw firm conclusions due to the poor methodological quality. Future well- designed trials are needed to validate the therapeutic efficacy, safety, and mechanisms of ACE in patients with PCOS.
基金Supported by National Administration of Traditional Chinese Medicine Project:Innovation Team and Talents Cultivation Program of National Administration of Traditional Chinese Medicine (No. ZYYCXTD-C-202006)。
文摘OBJECTIVE: To evaluate the clinical effectiveness and safety of acupoint catgut embedding and acupuncture on simple obesity by Meta-analysis. METHODS: Studies on clinical randomized controlled trials of acupoint catgut embedding for simple obesity which were published from January 2015 to November 2020 were searched in Cochrane Central Register of Control Trials(Central), Pub Med, China Science and Technology Journal Database, China National Knowledge Infrastructure Database and Wanfang databases. And those that met the inclusion criteria were screened. Rev Man5.3 was used for Meta-analysis. The “Risk of Bias” tool was used to evaluate the quality of included studies. R studio software was used for the measurement of publication bias. RESULTS: A total of 33 studies were included for Metaanalysis, including 2685 patients with simple obesity. Meta-analysis results showed the comparison of effectiveness rate was relative risk(RR) = 1.12, 95%CI(1.08, 1.16), body mass index(BMI) was mean difference(MD) =-1.12, 95%CI(-2.09,-0.14), waist circumference was MD =-2.14, 95%CI(-4.22,-0.06), and body mass was MD =-2.36, 95%CI(-3.99,-0.73). On the basis of diet and exercise intervention, the effectiveness rate [RR = 1.12, 95%CI(1.05, 1.19)], BMI [MD =-0.88, 95%CI(-1.35,-0.40)], waist circumference [MD =-1.10, 95%CI(-4.27, 2.07)], and body mass [MD =-0.68, 95%CI(-2.90, 1.54)]. The risk of bias of included literatures was low. CONCLUSIONS: Acupoint catgut embedding therapy was slightly better than acupuncture therapy in most of the outcomes. Moreover, the treatment frequency of acupoint catgut embedding is less with larger stimulation intensity, which is more conducive to clinical promotion.
基金the Korea Institute of Oriental Medicine(Grant No.KSN1823211 and KSN20234115)。
文摘OBJECTIVE:To assess the efficacy of acupoint catgut embedding(ACE)for simple obesity in preclinical animal experiments.METHODS:We searched the following 14 electronic databases:PubM ed,Cochrane Library,EMBASE,Oriental Medicine Advanced Searching Integrated System,KoreaMed,Korean Studies Information Service System,Science-on,Research Information Sharing Service,Korea Citation Index,Korea Traditional Knowledge Portal,China Network Knowledge Infrastructure Database,Wanfang Database,Chinese Science and Technology Journal Database,and Chinese Biology Medicine Database,from inception to November 2021 without language limitation.The assessment was performed according to the guidelines of Animal Research:Reporting of in vivo experiments;and Metaanalysis was performed using Reviewer Manager 5.4.1 software.RESULTS:Twenty-four studies involving 813 animals were selected.Meta-analysis showed that ACE was beneficial for weight control[n=40,MD=-50.63,95%CI(-57.59,-43.67),P<0.00001,I 2=0%]and reduced the Lee index[n=40,MD=-18.79,95%CI(-20.01,-17.57),P<0.00001,I 2=0%].However,when efficacy of ACE was compared with that of manual acupuncture,electroacupuncture,or oilistat therapy,statistical difference was not observed between the two groups.CONCLUSIONS:This systematic review suggests that ACE may be efficacious in treating obesity.Moreover,the analyses highlighted the necessity to perform welldesigned,higher-quality experiments.
基金Supported by National Key Research and Development Project:Clinical Evaluation of the Interventional Techniques for Abdominal Obesity(No.2019YFC1710102)。
文摘OBJECTIVE:To systematically review and analyze the effect of acupuncture and acupoint catgut embedding in treatment of abdominal obesity to provide a more reasonable clinical treatment regimen.METHODS:Ten databases were searched as of August 2022:the English databases Pub Med,Embase,Cochrane Library,Web of Science,Wiley,and Scopus and the Chinese databases China National Knowledge Infrastructure Database,China Science and Technology Journal Database,Wanfang,and Sino Med/Chinese Biomedical Literature Database.Randomized controlled trials(RCTs)of acupuncture and acupoint catgut embedding as the main interventions to treat abdominal obesity were extracted.The investigators imported the citations into End Note version X9.1 for deduplication,screening,extraction,and integration.The risk of bias in the included RCTs was assessed according to the Cochrane Handbook.Rev Man 5.4 software was used to conduct a Meta-analysis of RCTs that met the inclusion criteria.RESULTS:Thirteen RCTs(1069 patients)were included in this study,and the data of eleven RCTs(966 patients)were include in the Meta-analysis.The results showed that acupoint catgut embedding can significantly change the weight and waist circumference of patients with abdominal obesity when compared to sham acupuncture or no treatment[mean difference(MD)=2.32,95%confidence interval(CI)(1.88,2.76),P<0.00001],[MD=3.47,95%CI(1.99,4.94),P<0.00001].The change in hip circumference after acupuncture was also significant[MD=0.89,95%CI(0.12,1.66),P=0.02].CONCLUSION:This study found that acupuncture and acupoint catgut embedding can effectively treat abdominal obesity,therefore,these interventions can be used as clinical supplements and alternative therapies.The diagnostic criteria of the existing studies and the intervention measures of the control group are not unified.It will be necessary to improve the clinical study protocols and expand the sample size to further validate the reliability of the results obtained of this study.
文摘The parameter embedding method is applied for numerically solving the perturbed conservative systems. By means of Newtonian iteration, a simple algorithm has been constructed. Finally, the convergence of the iteration is proved.
基金Supported by the Key Research&Development Projects in Hubei Province(2022BAA041 and 2021BCA124)the Open Foundation of Engineering Research Center of Cyberspace(KJAQ202112002)。
文摘News recommendation system is designed to deal with massive news and provide personalized recommendations for users.Accurately capturing user preferences and modeling news and users is the key to news recommendation.In this paper,we propose a new framework,news recommendation system based on topic embedding and knowledge embedding(NRTK).NRTK handle news titles that users have clicked on from two perspectives to obtain news and user representation embedding:1)extracting explicit and latent topic features from news and mining users’preferences for them in historical behaviors;2)extracting entities and propagating users’potential preferences in the knowledge graph.Experiments in a real-world dataset validate the effectiveness and efficiency of our approach.
基金This research was supported by Korea Institute for Advancement of Technology(KIAT)grant funded by the Korea Government(MOTIE)(P0012724,The Competency Development Program for Industry Specialist)and the Soonchunhyang University Research Fund.
文摘The substantial competition among the news industries puts editors under the pressure of posting news articleswhich are likely to gain more user attention. Anticipating the popularity of news articles can help the editorial teamsin making decisions about posting a news article. Article similarity extracted from the articles posted within a smallperiod of time is found to be a useful feature in existing popularity prediction approaches. This work proposesa new approach to estimate the popularity of news articles by adding semantics in the article similarity basedapproach of popularity estimation. A semantically enriched model is proposed which estimates news popularity bymeasuring cosine similarity between document embeddings of the news articles. Word2vec model has been used togenerate distributed representations of the news content. In this work, we define popularity as the number of timesa news article is posted on different websites. We collect data from different websites that post news concerning thedomain of cybersecurity and estimate the popularity of cybersecurity news. The proposed approach is comparedwith different models and it is shown that it outperforms the other models.
基金This research was supported by Key Research Program of the Chinese Academy of Sciences(ZDRW-ZS-2021-1-2).
文摘Objective:To evaluate the effectiveness and safety of acupoint catgut embedding(ACE)in combination with Chinese herbal medicine(CHM)in treating chronic urticaria(CU).Methods:We thoroughly searched Embase,PubMed,Cochrane Library,Web of Science,China National Knowledge Infrastructure(CNKI),Wangfang database,Chinese Scientific Journal Database(VIP),and Chinese biomedical literature database(SinoMed)for relevant studies from inception until May 2022.Randomized controlled trials(RCTs)on ACE combined with CHM for CU were included.Literature search,data extraction,and risk of bias assessment were independently conducted by two authors.Results:A total of 15 RCTs with 1065 participants were included in this review.Five trials reported that the combined therapy showed a higher total effective rate,and four trials reported that the combined therapy was associated with a lower level of serum immunoglobulin E.Furthermore,two,four,and four trials reported that the combined therapy was more effective in reducing itching degree,size,and number of wheals,respectively.The combined therapy was reported to be associated with a lower recurrence rate in three trials,and with a fewer adverse reaction rate in two trials.Conclusions:ACE in combination with CHM appears to be a safe and effective therapy for patients with CU.Given the relatively low quality of the included trials,these findings should be interpreted cautiously.Further high-quality RCTs are needed to confirm our findings.
文摘Throughout scientific research, the state space reconstruction that embeds a non-linear time series is the first and necessary step for characterizing and predicting the behavior of a complex system. This requires to choose appropriate values of time delay T and embedding dimension dE. Three methods are applied and discussed on nonlinear time series provided by the Rössler attractor equations set: Cao’s method, the C-C method developed by Kim et al. and the C-C-1 method developed by Cai et al. A way to fix a parameter necessary to implement the last method is given. Focus has been put on small size and/or noisy time series. The reconstruction quality is measured by using a criterion based on the transformation smoothness.
基金Supported by the Grant-in-Aid for Scientific Research(C)by the Japan Society for the Promotion of Science(20K03615)。
文摘Let G be a group.The family of all sets which are closed in every Hausdorf group topology of G form the family of closed sets of a T_(1) topology M_(G) on G called the Markov topology.Similarly,the family of all algebraic subsets of G forms a family of closed sets for another T_(1)topology Z_(G) on G called the Zarski topology.A subgroup H of G is said to be Markov(resp.Zarski)embedded if the equality M_(G|H)=M_(H)(resp.Z_(G|H)=Z_(H))holds.I's proved that an abirary subgroup of a free group is both Zariski and Markov embedded in it.
基金funded by the National Science and Technology Council,Taiwan,under grant number NSTC 114-2221-E-167-005-MY3,and NSTC 113-2221-E-167-006-.
文摘Digital watermarking must balance imperceptibility,robustness,complexity,and security.To address the challenge of computational efficiency in trellis-based informed embedding,we propose a modified watermarking framework that integrates fuzzy c-means(FCM)clustering into the generation off block codewords for labeling trellis arcs.The system incorporates a parallel trellis structure,controllable embedding parameters,and a novel informed embedding algorithm with reduced complexity.Two types of embedding schemes—memoryless and memory-based—are designed to flexibly trade-off between imperceptibility and robustness.Experimental results demonstrate that the proposed method outperforms existing approaches in bit error rate(BER)and computational complexity under various attacks,including additive noise,filtering,JPEG compression,cropping,and rotation.The integration of FCM enhances robustness by increasing the codeword distance,while preserving perceptual quality.Overall,the proposed framework is suitable for real-time and secure watermarking applications.
基金supported in part by the National Science and Technology Major Project under(Grant 2022ZD0116100)in part by the National Natural Science Foundation Key Project under(Grant 62436006)+4 种基金in part by the National Natural Science Foundation Youth Fund under(Grant 62406257)in part by the Xizang Autonomous Region Natural Science Foundation General Project under(Grant XZ202401ZR0031)in part by the National Natural Science Foundation of China under(Grant 62276055)in part by the Sichuan Science and Technology Program under(Grant 23ZDYF0755)in part by the Xizang University‘High-Level Talent Training Program’Project under(Grant 2022-GSP-S098).
文摘Tibetan medical named entity recognition(Tibetan MNER)involves extracting specific types of medical entities from unstructured Tibetan medical texts.Tibetan MNER provide important data support for the work related to Tibetan medicine.However,existing Tibetan MNER methods often struggle to comprehensively capture multi-level semantic information,failing to sufficiently extract multi-granularity features and effectively filter out irrelevant information,which ultimately impacts the accuracy of entity recognition.This paper proposes an improved embedding representation method called syllable-word-sentence embedding.By leveraging features at different granularities and using un-scaled dot-product attention to focus on key features for feature fusion,the syllable-word-sentence embedding is integrated into the transformer,enhancing the specificity and diversity of feature representations.The model leverages multi-level and multi-granularity semantic information,thereby improving the performance of Tibetan MNER.We evaluate our proposed model on datasets from various domains.The results indicate that the model effectively identified three types of entities in the Tibetan news dataset we constructed,achieving an F1 score of 93.59%,which represents an improvement of 1.24%compared to the vanilla FLAT.Additionally,results from the Tibetan medical dataset we developed show that it is effective in identifying five kinds of medical entities,with an F1 score of 71.39%,which is a 1.34%improvement over the vanilla FLAT.
