The storage layer within the Moxizhuang Oilfield in the Junggar Basin develops various types of interlayer barriers with significant differences in morphology and scale of development. In response to the issues of int...The storage layer within the Moxizhuang Oilfield in the Junggar Basin develops various types of interlayer barriers with significant differences in morphology and scale of development. In response to the issues of interlayer barriers affecting the formation of oil and gas reservoirs and controlling oil-water distribution, this study proposes precise classification and quantitative identification of interlayer barriers in the study area based on a fully connected neural network combined with grey relational analysis. Taking the second member of the Sangonghe Formation (J1S22) in the Moxizhuang Oilfield as an example, combined with previous research, this study statistically analyzes the lithology and logging response characteristics of three types of interlayer barriers in the study area. Based on differences in composition, lithology, and genesis, interlayer barrier types are classified. Sensitive logging data such as natural gamma, acoustic time difference, and resistivity are selected through crossover plots. Grey relational analysis is used to calculate comprehensive discrimination indicators for interlayer barriers. Combined with the fully connected neural network method, an interlayer barrier identification model is established, and model training is conducted to verify the accuracy of interlayer barrier identification. The results indicate that the interlayer barrier identification model based on a fully connected neural network can rapidly and accurately identify interlayer barriers and their types. Its application in the second member of the Sangonghe Formation in the Moxizhuang Oilfield in the Junggar Basin has proven that the identification results of this method for interlayer barriers have a conformity rate exceeding 90% with core data, demonstrating excellent performance in interlayer barrier identification and proving the effectiveness of the model for interlayer barrier identification and prediction in this area. The research conclusions can provide theoretical guidance and technical reference for the identification and evaluation of interlayer barriers in the second member of the Sangonghe Formation in the Moxizhuang Oilfield in the Junggar Basin.展开更多
Green development is vital for bringing about high-quality development,which makes measuring and comparing provincial green development levels essential.This study calculates the comprehensive green development scores...Green development is vital for bringing about high-quality development,which makes measuring and comparing provincial green development levels essential.This study calculates the comprehensive green development scores using panel data from 30 Chinese provinces and autonomous regions(2013-2022)and a combined subjective-objective weighting method.It also innovatively establishes a grey relational degree matrix and a grey improvement sequence to analyze provincial similarities and identify benchmarks for improvement.The results indicate that ecological and environmental protection holds the highest weight among the primary indicators.Beijing,Shanghai,Tianjin,Zhejiang,and Jiangsu lead in green development,with Shanghai,Beijing,and Tianjin exhibiting distinct development trajectories,while Guizhou and Yunnan share a similar trend.Zhejiang and Shaanxi have prominent benchmarks for improvement,while some provinces dynamically adjust their targets.The results suggest that advanced regions should further refine their green development pathways to align with their specific contexts,while less-developed regions should adaptively learn from the appropriate benchmarks and periodically reassess their strategies.This study provides scientific guidance for regional green development planning,policymaking,and benchmarking,thus contributing to sustainable regional development.Furthermore,it lays a foundation for future research to expand into broader datasets,scales,influencing factors,and policy evaluations.展开更多
Anti-jamming performance evaluation has recently received significant attention. For Link-16, the anti-jamming performance evaluation and selection of the optimal anti-jamming technologies are urgent problems to be so...Anti-jamming performance evaluation has recently received significant attention. For Link-16, the anti-jamming performance evaluation and selection of the optimal anti-jamming technologies are urgent problems to be solved. A comprehensive evaluation method is proposed, which combines grey relational analysis (GRA) and cloud model, to evaluate the anti-jamming performances of Link-16. Firstly, on the basis of establishing the anti-jamming performance evaluation indicator system of Link-16, the linear combination of analytic hierarchy process(AHP) and entropy weight method (EWM) are used to calculate the combined weight. Secondly, the qualitative and quantitative concept transformation model, i.e., the cloud model, is introduced to evaluate the anti-jamming abilities of Link-16 under each jamming scheme. In addition, GRA calculates the correlation degree between evaluation indicators and the anti-jamming performance of Link-16, and assesses the best anti-jamming technology. Finally, simulation results prove that the proposed evaluation model can achieve the objective of feasible and practical evaluation, which opens up a novel way for the research of anti-jamming performance evaluations of Link-16.展开更多
Purpose–The deformation of the roadbed is easily influenced by the external environment to improve the accuracy of high-speed railway subgrade settlement prediction.Design/methodology/approach–A high-speed railway s...Purpose–The deformation of the roadbed is easily influenced by the external environment to improve the accuracy of high-speed railway subgrade settlement prediction.Design/methodology/approach–A high-speed railway subgrade settlement interval prediction method using the secretary bird optimization(SBOA)algorithm to optimize the BP neural network under the premise of gray relational analysis is proposed.Findings–Using the SBOA algorithm to optimize the BP neural network,the optimal weights and thresholds are obtained,and the best parameter prediction model is combined.The data were collected from the sensors deployed through the subgrade settlement monitoring system,and the gray relational analysis is used to verify that all four influencing factors had a great correlation to the subgrade settlement,and the collected data are verified using the model.Originality/value–The experimental results show that the SBOA-BP model has higher prediction accuracy than the BP model,and the SBOA-BP model has a wider range of prediction intervals for a given confidence level,which can provide higher guiding value for practical engineering applications.展开更多
Efficient data management in healthcare is essential for providing timely and accurate patient care, yet traditional partitioning methods in relational databases often struggle with the high volume, heterogeneity, and...Efficient data management in healthcare is essential for providing timely and accurate patient care, yet traditional partitioning methods in relational databases often struggle with the high volume, heterogeneity, and regulatory complexity of healthcare data. This research introduces a tailored partitioning strategy leveraging the MD5 hashing algorithm to enhance data insertion, query performance, and load balancing in healthcare systems. By applying a consistent hash function to patient IDs, our approach achieves uniform distribution of records across partitions, optimizing retrieval paths and reducing access latency while ensuring data integrity and compliance. We evaluated the method through experiments focusing on partitioning efficiency, scalability, and fault tolerance. The partitioning efficiency analysis compared our MD5-based approach with standard round-robin methods, measuring insertion times, query latency, and data distribution balance. Scalability tests assessed system performance across increasing dataset sizes and varying partition counts, while fault tolerance experiments examined data integrity and retrieval performance under simulated partition failures. The experimental results demonstrate that the MD5-based partitioning strategy significantly reduces query retrieval times by optimizing data access patterns, achieving up to X% better performance compared to round-robin methods. It also scales effectively with larger datasets, maintaining low latency and ensuring robust resilience under failure scenarios. This novel approach offers a scalable, efficient, and fault-tolerant solution for healthcare systems, facilitating faster clinical decision-making and improved patient care in complex data environments.展开更多
We theoretically investigate the propagation characteristics of spin waves in skyrmion-based magnonic crystals. It is found that the dispersion relation can be manipulated by strains through magneto-elastic coupling. ...We theoretically investigate the propagation characteristics of spin waves in skyrmion-based magnonic crystals. It is found that the dispersion relation can be manipulated by strains through magneto-elastic coupling. Especially, the allowed bands and forbidden bands in dispersion relations shift to higher frequency with strain changing from compressive to tensile,while shifting to lower frequency with strain changing from tensile to compressive. We also confirm that the spin wave with specific frequency can pass the magnonic crystal or be blocked by tuning the strains. The result provides an advanced platform for studying the tunable skyrmion-based spin wave devices.展开更多
Objective This study aimed to explore the association between humidity exposure and the risk of cardiovascular disease(CVD),utilizing follow-up data and relative humidity(RH)metric assessments.Methods We extracted the...Objective This study aimed to explore the association between humidity exposure and the risk of cardiovascular disease(CVD),utilizing follow-up data and relative humidity(RH)metric assessments.Methods We extracted the baseline data from the China Hypertension Survey(CHS)of 24,510 enrolled participants aged≥35 years without a history of CVD between 2012 and 2015 and followed them up from 2018 to 2019.The National Meteorological Information Center(NMIC)of the China Meteorological Administration(CMA)provided the quality-controlled relative humidity(RH)datasets.Cox proportional hazards models were used to estimate hazard ratios(HRs)for CVD in relation to RH.Results During the follow-up period(2018-2019),973 patients with CVD were identified.The HR of CVD risk was 1.17(95%CI:1.04-1.31)per 10%increase in summer mean RH.Compared with participants in the 3rd quintile group,those in the 1st and 5th quintiles of RH had a higher risk of CVD.For summer mean RH,the HRs(95%CIs)for the 1st and 5th quintiles were 1.34(1.04-1.71)and 1.44(1.14-1.83),respectively.The relationship(“U”shape)between summer mean RH and the risk of CVD was nonlinear.Stratified analyses indicated that the risk of CVD was substantially influenced by the summer mean RH in female,older individuals,and those in southern China.Conclusion Unsuitable(too high or low)humidity environments affect the risk of CVD.Our study highlights those future policies for adapting to climate change should consider the humidity-CVD relationship.展开更多
How to use a few defect samples to complete the defect classification is a key challenge in the production of mobile phone screens.An attention-relation network for the mobile phone screen defect classification is pro...How to use a few defect samples to complete the defect classification is a key challenge in the production of mobile phone screens.An attention-relation network for the mobile phone screen defect classification is proposed in this paper.The architecture of the attention-relation network contains two modules:a feature extract module and a feature metric module.Different from other few-shot models,an attention mechanism is applied to metric learning in our model to measure the distance between features,so as to pay attention to the correlation between features and suppress unwanted information.Besides,we combine dilated convolution and skip connection to extract more feature information for follow-up processing.We validate attention-relation network on the mobile phone screen defect dataset.The experimental results show that the classification accuracy of the attentionrelation network is 0.9486 under the 5-way 1-shot training strategy and 0.9039 under the 5-way 5-shot setting.It achieves the excellent effect of classification for mobile phone screen defects and outperforms with dominant advantages.展开更多
The joint entity relation extraction model which integrates the semantic information of relation is favored by relevant researchers because of its effectiveness in solving the overlapping of entities,and the method of...The joint entity relation extraction model which integrates the semantic information of relation is favored by relevant researchers because of its effectiveness in solving the overlapping of entities,and the method of defining the semantic template of relation manually is particularly prominent in the extraction effect because it can obtain the deep semantic information of relation.However,this method has some problems,such as relying on expert experience and poor portability.Inspired by the rule-based entity relation extraction method,this paper proposes a joint entity relation extraction model based on a relation semantic template automatically constructed,which is abbreviated as RSTAC.This model refines the extraction rules of relation semantic templates from relation corpus through dependency parsing and realizes the automatic construction of relation semantic templates.Based on the relation semantic template,the process of relation classification and triplet extraction is constrained,and finally,the entity relation triplet is obtained.The experimental results on the three major Chinese datasets of DuIE,SanWen,and FinRE showthat the RSTAC model successfully obtains rich deep semantics of relation,improves the extraction effect of entity relation triples,and the F1 scores are increased by an average of 0.96% compared with classical joint extraction models such as CasRel,TPLinker,and RFBFN.展开更多
In this article, we study generating sets of the complete semigroups of binary relations defined by X-semilattices of unions of the class Σ<sub>8</sub>(X, 5). Found uniquely irreducible generating set for...In this article, we study generating sets of the complete semigroups of binary relations defined by X-semilattices of unions of the class Σ<sub>8</sub>(X, 5). Found uniquely irreducible generating set for the given semigroups and when X is finite set formulas for calculating the number of elements in generating sets are derived.展开更多
We explore the properties of the bottom-quark on-shell mass(M_(b))by using its relation to the MS mass(m_(b)).At present,this MS-on-shell relation has been known up to four-loop QCD corrections,which however still has...We explore the properties of the bottom-quark on-shell mass(M_(b))by using its relation to the MS mass(m_(b)).At present,this MS-on-shell relation has been known up to four-loop QCD corrections,which however still has a~2%scale uncertainty by taking the renormalization scale as m_(b)(m_(b))and varying it within the usual range of [m_(b)(m_(b))/2,2m_(b)(m_(b))].展开更多
In agreement with Titchmarsh’s theorem, we prove that dispersion relations are just the Fourier-transform of the identity, g(x′)=±Sgn(x′)g(x′), which defines the property of being a truncated functions at the...In agreement with Titchmarsh’s theorem, we prove that dispersion relations are just the Fourier-transform of the identity, g(x′)=±Sgn(x′)g(x′), which defines the property of being a truncated functions at the origin. On the other hand, we prove that the wave-function of a generalized diffraction in time problem is just the Fourier-transform of a truncated function. Consequently, the existence of dispersion relations for the diffraction in time wave-function follows. We derive these explicit dispersion relations.展开更多
Objectives:The arrival of cancer in adolescents and young adults(aged 15 to 24 years)-Adolescents and young adults(AJA)-corresponds to a fragile period during which the adulthood of the young person and the evolution ...Objectives:The arrival of cancer in adolescents and young adults(aged 15 to 24 years)-Adolescents and young adults(AJA)-corresponds to a fragile period during which the adulthood of the young person and the evolution of family ties mobilize the family as a whole.Therefore,cancer,beyond its individual traumatic dimension,affects the whole family,which can modify family ties and family functioning.Our objective is to evaluate family functioning from the complex model evaluating cohesion and adaptability when an adolescent or young adult has cancer.Methods:Adolescents and young adults with cancer(n=41),mothers(n=41),and fathers(n=13)participated in this study.They completed the Family Adaptation and Cohesion Scales(FACES Ⅲ)questionnaire.Family functioning when an aya is ill has been compared to that of families without any disease.Results:a comparison of the mean scores of perceived cohesion and adaptability of face Ⅲ indicates no significant difference for cohesion.In contrast,the averages of the adaptability scores of our sample with those of the general population indicate that families with cancer hais generally feel more“adaptable”than the non-clinical population.These results are statistically significant for AJA,but also for mothers and fathers.Regarding the mean scores of ideal cohesion and ideal adaptability,there are no significant differences between fathers in our sample and fathers in the general population.In contrast,mothers in our sample had less ideal adaptability than those in the general population.In aya patients with cancer,the scores of both adaptability and cohesion were significantly different from those of non-diseased adolescents.Conclusion:Cancer leads to many changes in family relationships,making it difficult to empower the young patient and latent the evolution of the relationship.展开更多
To solve the problem of long response time when users obtain suitable cutting parameters through the Internet based platform,a case-based reasoning framework is proposed.Specifically,a Hamming distance and Euclidean d...To solve the problem of long response time when users obtain suitable cutting parameters through the Internet based platform,a case-based reasoning framework is proposed.Specifically,a Hamming distance and Euclidean distance combined method is designed to measure the similarity of case features which have both numeric and category properties.In addition,AHP(Analytic Hierarchy Process)and entropy weight method are integrated to provide features weight,where both user preferences and comprehensive impact of the index have been concerned.Grey relation analysis is used to obtain the similarity of a new problem and alternative cases.Finally,a platform is also developed on Visual Studio 2015,and a case study is demonstrated to verify the practicality and efficiency of the proposed method.This method can obtain cutting parameters which is suitable without iterative calculation.Compared with the traditional PSO(Particle swarm optimization algorithm)and GA(Genetic algorithm),it can obtain faster response speed.This method can provide ideas for selecting processing parameters in industrial production.While guaranteeing the characteristic information is similar,this approach can select processing parameters which is the most appropriate for the production process and a lot of time can be saved.展开更多
Effective data communication is a crucial aspect of the Social Internet of Things(SIoT)and continues to be a significant research focus.This paper proposes a data forwarding algorithm based on Multidimensional Social ...Effective data communication is a crucial aspect of the Social Internet of Things(SIoT)and continues to be a significant research focus.This paper proposes a data forwarding algorithm based on Multidimensional Social Relations(MSRR)in SIoT to solve this problem.The proposed algorithm separates message forwarding into intra-and cross-community forwarding by analyzing interest traits and social connections among nodes.Three new metrics are defined:the intensity of node social relationships,node activity,and community connectivity.Within the community,messages are sent by determining which node is most similar to the sender by weighing the strength of social connections and node activity.When a node performs cross-community forwarding,the message is forwarded to the most reasonable relay community by measuring the node activity and the connection between communities.The proposed algorithm was compared to three existing routing algorithms in simulation experiments.Results indicate that the proposed algorithmsubstantially improves message delivery efficiency while lessening network overhead and enhancing connectivity and coordination in the SIoT context.展开更多
We-map is an interactive mobile map that can be easily communicated and applied on personal electronic devices,such as personal computers and mobile phones.Therefore,the study of direction systems and coordinate syste...We-map is an interactive mobile map that can be easily communicated and applied on personal electronic devices,such as personal computers and mobile phones.Therefore,the study of direction systems and coordinate systems is critical,and exploring reference frames is essential in direction and coordinate systems.Despite its significance,existing research on We-map lacks specific solutions for the exploration of reference frames is indispensable for the establishment of accurate direction and coordinate systems.In this paper,we endeavor to address this gap by elucidating the significance of We-map reference frames,defining them with mathematical constraints,summarizing their nature and characteristics,deriving their transformation relationships and representing them through mathematical formulars and equations.Our work contributes to the fundamental theory of We-map and provides valuable systems and support for the mathematical foundation of We-map,map production,and platform development.Ultimately,this research serves to advance the development of We-map.展开更多
Currently,all quantum private comparison protocols based on two-dimensional quantum states can only compare equality,via using high-dimensional quantum states that it is possible to compare the size relation in existi...Currently,all quantum private comparison protocols based on two-dimensional quantum states can only compare equality,via using high-dimensional quantum states that it is possible to compare the size relation in existing work.In addition,it is difficult to manipulate high-dimensional quantum states under the existing conditions of quantum information processing,leading to low practicality and engineering feasibility of protocols for comparing size relation.Considering this situation,we propose an innovative protocol.The proposed protocol can make size comparison by exploiting more manageable two-dimensional Bell states,which significantly enhances its feasibility with current quantum technologies.Simultaneously,the proposed protocol enables multiple participants to compare their privacies with the semi-quantum model.The communication process of the protocol is simulated on the IBM Quantum Experience platform to verify its effectiveness.Security analysis shows that the proposed protocol can withstand common attacks while preserving the privacies of all participants.Thus,the devised protocol may provide an important reference for implementation of quantum private size comparison protocols.展开更多
Text classification,by automatically categorizing texts,is one of the foundational elements of natural language processing applications.This study investigates how text classification performance can be improved throu...Text classification,by automatically categorizing texts,is one of the foundational elements of natural language processing applications.This study investigates how text classification performance can be improved through the integration of entity-relation information obtained from the Wikidata(Wikipedia database)database and BERTbased pre-trained Named Entity Recognition(NER)models.Focusing on a significant challenge in the field of natural language processing(NLP),the research evaluates the potential of using entity and relational information to extract deeper meaning from texts.The adopted methodology encompasses a comprehensive approach that includes text preprocessing,entity detection,and the integration of relational information.Experiments conducted on text datasets in both Turkish and English assess the performance of various classification algorithms,such as Support Vector Machine,Logistic Regression,Deep Neural Network,and Convolutional Neural Network.The results indicate that the integration of entity-relation information can significantly enhance algorithmperformance in text classification tasks and offer new perspectives for information extraction and semantic analysis in NLP applications.Contributions of this work include the utilization of distant supervised entity-relation information in Turkish text classification,the development of a Turkish relational text classification approach,and the creation of a relational database.By demonstrating potential performance improvements through the integration of distant supervised entity-relation information into Turkish text classification,this research aims to support the effectiveness of text-based artificial intelligence(AI)tools.Additionally,it makes significant contributions to the development ofmultilingual text classification systems by adding deeper meaning to text content,thereby providing a valuable addition to current NLP studies and setting an important reference point for future research.展开更多
The relation is a semantic expression relevant to two named entities in a sentence.Since a sentence usually contains several named entities,it is essential to learn a structured sentence representation that encodes de...The relation is a semantic expression relevant to two named entities in a sentence.Since a sentence usually contains several named entities,it is essential to learn a structured sentence representation that encodes dependency information specific to the two named entities.In related work,graph convolutional neural networks are widely adopted to learn semantic dependencies,where a dependency tree initializes the adjacency matrix.However,this approach has two main issues.First,parsing a sentence heavily relies on external toolkits,which can be errorprone.Second,the dependency tree only encodes the syntactical structure of a sentence,which may not align with the relational semantic expression.In this paper,we propose an automatic graph learningmethod to autonomously learn a sentence’s structural information.Instead of using a fixed adjacency matrix initialized by a dependency tree,we introduce an Adaptive Adjacency Matrix to encode the semantic dependency between tokens.The elements of thismatrix are dynamically learned during the training process and optimized by task-relevant learning objectives,enabling the construction of task-relevant semantic dependencies within a sentence.Our model demonstrates superior performance on the TACRED and SemEval 2010 datasets,surpassing previous works by 1.3%and 0.8%,respectively.These experimental results show that our model excels in the relation extraction task,outperforming prior models.展开更多
This study explored the construction of power relations in the cognitive assessment of older adults within the Chinese clinical context.Data is derived from audio and video recordings that nine older adults produced i...This study explored the construction of power relations in the cognitive assessment of older adults within the Chinese clinical context.Data is derived from audio and video recordings that nine older adults produced in the cognitive assessment of the Chinese version of the Montreal Cognitive Assessment-Basic(MoCA-B),which were then annotated and analyzed from a multimodal pragmatic perspective.The study reveals that examiners and older adults employed various speech acts to achieve distinct communicative goals,with power relations between them being reflected through these speech acts.Examiners tend to claim high power,utilizing discourse strategies such as request,interruption,evaluation,rhetorical questions,and directive speech acts.In contrast,older adults assert high power through directive speech acts,rhetorical questions,and interruptions.Both parties also exhibit low power by using confirming questions and explanations.Additionally,gestures,smiles,prosody features,and other non-verbal communicative resources are synergistically employed to exercise power.The interactive mechanism of constructing power relations reveals that age affects older adults’power relations construction even in a professional setting of the Chinese context.The negotiation between the advanced age of older adults and the expertise of examiners jointly shapes power relations in their interactions.展开更多
文摘The storage layer within the Moxizhuang Oilfield in the Junggar Basin develops various types of interlayer barriers with significant differences in morphology and scale of development. In response to the issues of interlayer barriers affecting the formation of oil and gas reservoirs and controlling oil-water distribution, this study proposes precise classification and quantitative identification of interlayer barriers in the study area based on a fully connected neural network combined with grey relational analysis. Taking the second member of the Sangonghe Formation (J1S22) in the Moxizhuang Oilfield as an example, combined with previous research, this study statistically analyzes the lithology and logging response characteristics of three types of interlayer barriers in the study area. Based on differences in composition, lithology, and genesis, interlayer barrier types are classified. Sensitive logging data such as natural gamma, acoustic time difference, and resistivity are selected through crossover plots. Grey relational analysis is used to calculate comprehensive discrimination indicators for interlayer barriers. Combined with the fully connected neural network method, an interlayer barrier identification model is established, and model training is conducted to verify the accuracy of interlayer barrier identification. The results indicate that the interlayer barrier identification model based on a fully connected neural network can rapidly and accurately identify interlayer barriers and their types. Its application in the second member of the Sangonghe Formation in the Moxizhuang Oilfield in the Junggar Basin has proven that the identification results of this method for interlayer barriers have a conformity rate exceeding 90% with core data, demonstrating excellent performance in interlayer barrier identification and proving the effectiveness of the model for interlayer barrier identification and prediction in this area. The research conclusions can provide theoretical guidance and technical reference for the identification and evaluation of interlayer barriers in the second member of the Sangonghe Formation in the Moxizhuang Oilfield in the Junggar Basin.
文摘Green development is vital for bringing about high-quality development,which makes measuring and comparing provincial green development levels essential.This study calculates the comprehensive green development scores using panel data from 30 Chinese provinces and autonomous regions(2013-2022)and a combined subjective-objective weighting method.It also innovatively establishes a grey relational degree matrix and a grey improvement sequence to analyze provincial similarities and identify benchmarks for improvement.The results indicate that ecological and environmental protection holds the highest weight among the primary indicators.Beijing,Shanghai,Tianjin,Zhejiang,and Jiangsu lead in green development,with Shanghai,Beijing,and Tianjin exhibiting distinct development trajectories,while Guizhou and Yunnan share a similar trend.Zhejiang and Shaanxi have prominent benchmarks for improvement,while some provinces dynamically adjust their targets.The results suggest that advanced regions should further refine their green development pathways to align with their specific contexts,while less-developed regions should adaptively learn from the appropriate benchmarks and periodically reassess their strategies.This study provides scientific guidance for regional green development planning,policymaking,and benchmarking,thus contributing to sustainable regional development.Furthermore,it lays a foundation for future research to expand into broader datasets,scales,influencing factors,and policy evaluations.
基金Heilongjiang Provincial Natural Science Foundation of China (LH2021F009)。
文摘Anti-jamming performance evaluation has recently received significant attention. For Link-16, the anti-jamming performance evaluation and selection of the optimal anti-jamming technologies are urgent problems to be solved. A comprehensive evaluation method is proposed, which combines grey relational analysis (GRA) and cloud model, to evaluate the anti-jamming performances of Link-16. Firstly, on the basis of establishing the anti-jamming performance evaluation indicator system of Link-16, the linear combination of analytic hierarchy process(AHP) and entropy weight method (EWM) are used to calculate the combined weight. Secondly, the qualitative and quantitative concept transformation model, i.e., the cloud model, is introduced to evaluate the anti-jamming abilities of Link-16 under each jamming scheme. In addition, GRA calculates the correlation degree between evaluation indicators and the anti-jamming performance of Link-16, and assesses the best anti-jamming technology. Finally, simulation results prove that the proposed evaluation model can achieve the objective of feasible and practical evaluation, which opens up a novel way for the research of anti-jamming performance evaluations of Link-16.
文摘Purpose–The deformation of the roadbed is easily influenced by the external environment to improve the accuracy of high-speed railway subgrade settlement prediction.Design/methodology/approach–A high-speed railway subgrade settlement interval prediction method using the secretary bird optimization(SBOA)algorithm to optimize the BP neural network under the premise of gray relational analysis is proposed.Findings–Using the SBOA algorithm to optimize the BP neural network,the optimal weights and thresholds are obtained,and the best parameter prediction model is combined.The data were collected from the sensors deployed through the subgrade settlement monitoring system,and the gray relational analysis is used to verify that all four influencing factors had a great correlation to the subgrade settlement,and the collected data are verified using the model.Originality/value–The experimental results show that the SBOA-BP model has higher prediction accuracy than the BP model,and the SBOA-BP model has a wider range of prediction intervals for a given confidence level,which can provide higher guiding value for practical engineering applications.
文摘Efficient data management in healthcare is essential for providing timely and accurate patient care, yet traditional partitioning methods in relational databases often struggle with the high volume, heterogeneity, and regulatory complexity of healthcare data. This research introduces a tailored partitioning strategy leveraging the MD5 hashing algorithm to enhance data insertion, query performance, and load balancing in healthcare systems. By applying a consistent hash function to patient IDs, our approach achieves uniform distribution of records across partitions, optimizing retrieval paths and reducing access latency while ensuring data integrity and compliance. We evaluated the method through experiments focusing on partitioning efficiency, scalability, and fault tolerance. The partitioning efficiency analysis compared our MD5-based approach with standard round-robin methods, measuring insertion times, query latency, and data distribution balance. Scalability tests assessed system performance across increasing dataset sizes and varying partition counts, while fault tolerance experiments examined data integrity and retrieval performance under simulated partition failures. The experimental results demonstrate that the MD5-based partitioning strategy significantly reduces query retrieval times by optimizing data access patterns, achieving up to X% better performance compared to round-robin methods. It also scales effectively with larger datasets, maintaining low latency and ensuring robust resilience under failure scenarios. This novel approach offers a scalable, efficient, and fault-tolerant solution for healthcare systems, facilitating faster clinical decision-making and improved patient care in complex data environments.
文摘We theoretically investigate the propagation characteristics of spin waves in skyrmion-based magnonic crystals. It is found that the dispersion relation can be manipulated by strains through magneto-elastic coupling. Especially, the allowed bands and forbidden bands in dispersion relations shift to higher frequency with strain changing from compressive to tensile,while shifting to lower frequency with strain changing from tensile to compressive. We also confirm that the spin wave with specific frequency can pass the magnonic crystal or be blocked by tuning the strains. The result provides an advanced platform for studying the tunable skyrmion-based spin wave devices.
基金supported by the National High Level Hospital Clinical Research Funding[grant number No.2023-GSPRC-18]the National Key R&D Program of China during the Thirteen Five-Year Plan Period[grant number No.2018YFC1315303]+1 种基金the Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences[grant number No.2017-I2M-1-004]the Projects in the Chinese National Science&Technology Pillar Program during the Twelfth Fiveyear Plan Period[grant number No.2011BAI11B01].
文摘Objective This study aimed to explore the association between humidity exposure and the risk of cardiovascular disease(CVD),utilizing follow-up data and relative humidity(RH)metric assessments.Methods We extracted the baseline data from the China Hypertension Survey(CHS)of 24,510 enrolled participants aged≥35 years without a history of CVD between 2012 and 2015 and followed them up from 2018 to 2019.The National Meteorological Information Center(NMIC)of the China Meteorological Administration(CMA)provided the quality-controlled relative humidity(RH)datasets.Cox proportional hazards models were used to estimate hazard ratios(HRs)for CVD in relation to RH.Results During the follow-up period(2018-2019),973 patients with CVD were identified.The HR of CVD risk was 1.17(95%CI:1.04-1.31)per 10%increase in summer mean RH.Compared with participants in the 3rd quintile group,those in the 1st and 5th quintiles of RH had a higher risk of CVD.For summer mean RH,the HRs(95%CIs)for the 1st and 5th quintiles were 1.34(1.04-1.71)and 1.44(1.14-1.83),respectively.The relationship(“U”shape)between summer mean RH and the risk of CVD was nonlinear.Stratified analyses indicated that the risk of CVD was substantially influenced by the summer mean RH in female,older individuals,and those in southern China.Conclusion Unsuitable(too high or low)humidity environments affect the risk of CVD.Our study highlights those future policies for adapting to climate change should consider the humidity-CVD relationship.
文摘How to use a few defect samples to complete the defect classification is a key challenge in the production of mobile phone screens.An attention-relation network for the mobile phone screen defect classification is proposed in this paper.The architecture of the attention-relation network contains two modules:a feature extract module and a feature metric module.Different from other few-shot models,an attention mechanism is applied to metric learning in our model to measure the distance between features,so as to pay attention to the correlation between features and suppress unwanted information.Besides,we combine dilated convolution and skip connection to extract more feature information for follow-up processing.We validate attention-relation network on the mobile phone screen defect dataset.The experimental results show that the classification accuracy of the attentionrelation network is 0.9486 under the 5-way 1-shot training strategy and 0.9039 under the 5-way 5-shot setting.It achieves the excellent effect of classification for mobile phone screen defects and outperforms with dominant advantages.
基金supported by the National Natural Science Foundation of China(Nos.U1804263,U1736214,62172435)the Zhongyuan Science and Technology Innovation Leading Talent Project(No.214200510019).
文摘The joint entity relation extraction model which integrates the semantic information of relation is favored by relevant researchers because of its effectiveness in solving the overlapping of entities,and the method of defining the semantic template of relation manually is particularly prominent in the extraction effect because it can obtain the deep semantic information of relation.However,this method has some problems,such as relying on expert experience and poor portability.Inspired by the rule-based entity relation extraction method,this paper proposes a joint entity relation extraction model based on a relation semantic template automatically constructed,which is abbreviated as RSTAC.This model refines the extraction rules of relation semantic templates from relation corpus through dependency parsing and realizes the automatic construction of relation semantic templates.Based on the relation semantic template,the process of relation classification and triplet extraction is constrained,and finally,the entity relation triplet is obtained.The experimental results on the three major Chinese datasets of DuIE,SanWen,and FinRE showthat the RSTAC model successfully obtains rich deep semantics of relation,improves the extraction effect of entity relation triples,and the F1 scores are increased by an average of 0.96% compared with classical joint extraction models such as CasRel,TPLinker,and RFBFN.
文摘In this article, we study generating sets of the complete semigroups of binary relations defined by X-semilattices of unions of the class Σ<sub>8</sub>(X, 5). Found uniquely irreducible generating set for the given semigroups and when X is finite set formulas for calculating the number of elements in generating sets are derived.
基金supported in part by the National Natural Science Foundation of China(Grant Nos.12175025,12247129,and 12347101)the Graduate Research and Innovation Foundation of Chongqing,China(Grant No.ydstd1912)the Foundation of Chongqing Normal University(Grant No.24XLB015)。
文摘We explore the properties of the bottom-quark on-shell mass(M_(b))by using its relation to the MS mass(m_(b)).At present,this MS-on-shell relation has been known up to four-loop QCD corrections,which however still has a~2%scale uncertainty by taking the renormalization scale as m_(b)(m_(b))and varying it within the usual range of [m_(b)(m_(b))/2,2m_(b)(m_(b))].
文摘In agreement with Titchmarsh’s theorem, we prove that dispersion relations are just the Fourier-transform of the identity, g(x′)=±Sgn(x′)g(x′), which defines the property of being a truncated functions at the origin. On the other hand, we prove that the wave-function of a generalized diffraction in time problem is just the Fourier-transform of a truncated function. Consequently, the existence of dispersion relations for the diffraction in time wave-function follows. We derive these explicit dispersion relations.
文摘Objectives:The arrival of cancer in adolescents and young adults(aged 15 to 24 years)-Adolescents and young adults(AJA)-corresponds to a fragile period during which the adulthood of the young person and the evolution of family ties mobilize the family as a whole.Therefore,cancer,beyond its individual traumatic dimension,affects the whole family,which can modify family ties and family functioning.Our objective is to evaluate family functioning from the complex model evaluating cohesion and adaptability when an adolescent or young adult has cancer.Methods:Adolescents and young adults with cancer(n=41),mothers(n=41),and fathers(n=13)participated in this study.They completed the Family Adaptation and Cohesion Scales(FACES Ⅲ)questionnaire.Family functioning when an aya is ill has been compared to that of families without any disease.Results:a comparison of the mean scores of perceived cohesion and adaptability of face Ⅲ indicates no significant difference for cohesion.In contrast,the averages of the adaptability scores of our sample with those of the general population indicate that families with cancer hais generally feel more“adaptable”than the non-clinical population.These results are statistically significant for AJA,but also for mothers and fathers.Regarding the mean scores of ideal cohesion and ideal adaptability,there are no significant differences between fathers in our sample and fathers in the general population.In contrast,mothers in our sample had less ideal adaptability than those in the general population.In aya patients with cancer,the scores of both adaptability and cohesion were significantly different from those of non-diseased adolescents.Conclusion:Cancer leads to many changes in family relationships,making it difficult to empower the young patient and latent the evolution of the relationship.
基金the Sichuan Science and Technology Program(Nos.23ZHCG0049,2023YFG0078,23ZHCG0030,2021ZDZX0007)SCU-SUINING Project(2022CDSN-14).
文摘To solve the problem of long response time when users obtain suitable cutting parameters through the Internet based platform,a case-based reasoning framework is proposed.Specifically,a Hamming distance and Euclidean distance combined method is designed to measure the similarity of case features which have both numeric and category properties.In addition,AHP(Analytic Hierarchy Process)and entropy weight method are integrated to provide features weight,where both user preferences and comprehensive impact of the index have been concerned.Grey relation analysis is used to obtain the similarity of a new problem and alternative cases.Finally,a platform is also developed on Visual Studio 2015,and a case study is demonstrated to verify the practicality and efficiency of the proposed method.This method can obtain cutting parameters which is suitable without iterative calculation.Compared with the traditional PSO(Particle swarm optimization algorithm)and GA(Genetic algorithm),it can obtain faster response speed.This method can provide ideas for selecting processing parameters in industrial production.While guaranteeing the characteristic information is similar,this approach can select processing parameters which is the most appropriate for the production process and a lot of time can be saved.
基金supported by the NationalNatural Science Foundation of China(61972136)the Hubei Provincial Department of Education Outstanding Youth Scientific Innovation Team Support Foundation(T201410,T2020017)+1 种基金the Natural Science Foundation of Xiaogan City(XGKJ2022010095,XGKJ2022010094)the Science and Technology Research Project of Education Department of Hubei Province(No.Q20222704).
文摘Effective data communication is a crucial aspect of the Social Internet of Things(SIoT)and continues to be a significant research focus.This paper proposes a data forwarding algorithm based on Multidimensional Social Relations(MSRR)in SIoT to solve this problem.The proposed algorithm separates message forwarding into intra-and cross-community forwarding by analyzing interest traits and social connections among nodes.Three new metrics are defined:the intensity of node social relationships,node activity,and community connectivity.Within the community,messages are sent by determining which node is most similar to the sender by weighing the strength of social connections and node activity.When a node performs cross-community forwarding,the message is forwarded to the most reasonable relay community by measuring the node activity and the connection between communities.The proposed algorithm was compared to three existing routing algorithms in simulation experiments.Results indicate that the proposed algorithmsubstantially improves message delivery efficiency while lessening network overhead and enhancing connectivity and coordination in the SIoT context.
基金Industrial Support and Program Project of Universities in Gansu Province(No.2022CYZC-30)National Natural Science Foundation of China(Nos.42430108,41930101)China Scholarship Council(No.202306180085).
文摘We-map is an interactive mobile map that can be easily communicated and applied on personal electronic devices,such as personal computers and mobile phones.Therefore,the study of direction systems and coordinate systems is critical,and exploring reference frames is essential in direction and coordinate systems.Despite its significance,existing research on We-map lacks specific solutions for the exploration of reference frames is indispensable for the establishment of accurate direction and coordinate systems.In this paper,we endeavor to address this gap by elucidating the significance of We-map reference frames,defining them with mathematical constraints,summarizing their nature and characteristics,deriving their transformation relationships and representing them through mathematical formulars and equations.Our work contributes to the fundamental theory of We-map and provides valuable systems and support for the mathematical foundation of We-map,map production,and platform development.Ultimately,this research serves to advance the development of We-map.
基金supported by the National Natural Science Foundation of China(Grant No.62161025)the Project of Scientific and Technological Innovation Base of Jiangxi Province(Grant No.20203CCD46008)the Jiangxi Provincial Key Laboratory of Fusion and Information Control(Grant No.20171BCD40005).
文摘Currently,all quantum private comparison protocols based on two-dimensional quantum states can only compare equality,via using high-dimensional quantum states that it is possible to compare the size relation in existing work.In addition,it is difficult to manipulate high-dimensional quantum states under the existing conditions of quantum information processing,leading to low practicality and engineering feasibility of protocols for comparing size relation.Considering this situation,we propose an innovative protocol.The proposed protocol can make size comparison by exploiting more manageable two-dimensional Bell states,which significantly enhances its feasibility with current quantum technologies.Simultaneously,the proposed protocol enables multiple participants to compare their privacies with the semi-quantum model.The communication process of the protocol is simulated on the IBM Quantum Experience platform to verify its effectiveness.Security analysis shows that the proposed protocol can withstand common attacks while preserving the privacies of all participants.Thus,the devised protocol may provide an important reference for implementation of quantum private size comparison protocols.
文摘Text classification,by automatically categorizing texts,is one of the foundational elements of natural language processing applications.This study investigates how text classification performance can be improved through the integration of entity-relation information obtained from the Wikidata(Wikipedia database)database and BERTbased pre-trained Named Entity Recognition(NER)models.Focusing on a significant challenge in the field of natural language processing(NLP),the research evaluates the potential of using entity and relational information to extract deeper meaning from texts.The adopted methodology encompasses a comprehensive approach that includes text preprocessing,entity detection,and the integration of relational information.Experiments conducted on text datasets in both Turkish and English assess the performance of various classification algorithms,such as Support Vector Machine,Logistic Regression,Deep Neural Network,and Convolutional Neural Network.The results indicate that the integration of entity-relation information can significantly enhance algorithmperformance in text classification tasks and offer new perspectives for information extraction and semantic analysis in NLP applications.Contributions of this work include the utilization of distant supervised entity-relation information in Turkish text classification,the development of a Turkish relational text classification approach,and the creation of a relational database.By demonstrating potential performance improvements through the integration of distant supervised entity-relation information into Turkish text classification,this research aims to support the effectiveness of text-based artificial intelligence(AI)tools.Additionally,it makes significant contributions to the development ofmultilingual text classification systems by adding deeper meaning to text content,thereby providing a valuable addition to current NLP studies and setting an important reference point for future research.
基金supported by the Technology Projects of Guizhou Province under Grant[2024]003National Natural Science Foundation of China(GrantNos.62166007,62066008,62066007)Guizhou Provincial Science and Technology Projects under Grant No.ZK[2023]300.
文摘The relation is a semantic expression relevant to two named entities in a sentence.Since a sentence usually contains several named entities,it is essential to learn a structured sentence representation that encodes dependency information specific to the two named entities.In related work,graph convolutional neural networks are widely adopted to learn semantic dependencies,where a dependency tree initializes the adjacency matrix.However,this approach has two main issues.First,parsing a sentence heavily relies on external toolkits,which can be errorprone.Second,the dependency tree only encodes the syntactical structure of a sentence,which may not align with the relational semantic expression.In this paper,we propose an automatic graph learningmethod to autonomously learn a sentence’s structural information.Instead of using a fixed adjacency matrix initialized by a dependency tree,we introduce an Adaptive Adjacency Matrix to encode the semantic dependency between tokens.The elements of thismatrix are dynamically learned during the training process and optimized by task-relevant learning objectives,enabling the construction of task-relevant semantic dependencies within a sentence.Our model demonstrates superior performance on the TACRED and SemEval 2010 datasets,surpassing previous works by 1.3%and 0.8%,respectively.These experimental results show that our model excels in the relation extraction task,outperforming prior models.
文摘This study explored the construction of power relations in the cognitive assessment of older adults within the Chinese clinical context.Data is derived from audio and video recordings that nine older adults produced in the cognitive assessment of the Chinese version of the Montreal Cognitive Assessment-Basic(MoCA-B),which were then annotated and analyzed from a multimodal pragmatic perspective.The study reveals that examiners and older adults employed various speech acts to achieve distinct communicative goals,with power relations between them being reflected through these speech acts.Examiners tend to claim high power,utilizing discourse strategies such as request,interruption,evaluation,rhetorical questions,and directive speech acts.In contrast,older adults assert high power through directive speech acts,rhetorical questions,and interruptions.Both parties also exhibit low power by using confirming questions and explanations.Additionally,gestures,smiles,prosody features,and other non-verbal communicative resources are synergistically employed to exercise power.The interactive mechanism of constructing power relations reveals that age affects older adults’power relations construction even in a professional setting of the Chinese context.The negotiation between the advanced age of older adults and the expertise of examiners jointly shapes power relations in their interactions.
