In social sciences it is more or less generally acknowledged that (social) networks seem to be the natural tool in the organization of social activity. In the liteature on the mathematical description of social phenom...In social sciences it is more or less generally acknowledged that (social) networks seem to be the natural tool in the organization of social activity. In the liteature on the mathematical description of social phenomena the concept of a network is hardly used.In this paper we focus on the development of a’possible mathematical formualtion of the properties of a social network and a minimal and nearly complete social relational subsystem as a quasi-network within the setting of an economic trade system.展开更多
To evaluate the effectiveness of weapon systems, the advantages and disadvantages of grey relational analysis and TOPSIS for multiattribute decision-making is pointed out, and an effectiveness evaluation model of weap...To evaluate the effectiveness of weapon systems, the advantages and disadvantages of grey relational analysis and TOPSIS for multiattribute decision-making is pointed out, and an effectiveness evaluation model of weapon systems by combining grey relational analysis and TOPSIS is proposed. The model aggregates the grey relational grade and the distance to a new integrated closeness and reflects not only the trend but also the situation of the alternative. The example illuminates that the model is effective for the effectiveness evaluation of weapon systems.展开更多
A proper weapon system is very important for a na- tional defense system. Generally, it means selecting the optimal weapon system among many alternatives, which is a multiple- attribute decision making （MADM） proble...A proper weapon system is very important for a na- tional defense system. Generally, it means selecting the optimal weapon system among many alternatives, which is a multiple- attribute decision making （MADM） problem. This paper proposes a new mathematical model based on the response surface method （RSM） and the grey relational analysis （GRA）. RSM is used to obtain the experimental points and analyze the factors that have a significant impact on the selection results. GRA is used to an- alyze the trend relationship between alternatives and reference series. And then an RSM model is obtained, which can be used to calculate all alternatives and obtain ranking results. A real world application is introduced to illustrate the utilization of the model for the weapon selection problem. The results show that this model can be used to help decision-makers to make a quick comparison of alternatives and select a proper weapon system from multiple alternatives, which is an effective and adaptable method for solving the weapon system selection problem.展开更多
The strength of the mould cavity in sand casting is very much significant to attain high-quality castings. Optimization of green sand process parameters plays a vital role in minimizing casting defects. In the present...The strength of the mould cavity in sand casting is very much significant to attain high-quality castings. Optimization of green sand process parameters plays a vital role in minimizing casting defects. In the present research work, the effect of process parameters such as AFS grain fineness number, water, molasses, bentonite, fly ash, and ramming, and their levels on the resultant mould properties were investigated and optimized using Taguchi based grey relational analysis. The Taguchi L18 orthogonal array and analysis of variance(ANOVA) were used. The quality characteristics viz., green compression strength, permeability, bulk density, mould hardness and shatter index of green sand mould were optimized using grey relational grade, based on the experiments designed using Taguchi's Design of Experiments. ANOVA analysis indicated that water content is the most influential parameter followed by bentonite, and degree of ramming that contributes to the quality characteristics. The results are confirmed by calculating confidence intervals, which lies within the interval limits. Finally, microstructure observations and X-ray diffraction analysis have been performed for the optimal sand parametric combination. Results show that presence of maximum amount of SiO_2, which might be the reason for enhancement of the physical properties of the sand.展开更多
Relational nature of language system is of vital importance in Saussure's theory of linguistics.As philosopher Ernst Cassirer put that the crucial and revolutionary aspect of modern linguistics was Saussure's ...Relational nature of language system is of vital importance in Saussure's theory of linguistics.As philosopher Ernst Cassirer put that the crucial and revolutionary aspect of modern linguistics was Saussure's affirmation of the primacy of relation and the system of relations.This paper is devoted to a clear elaboration of the relational nature of linguistic system in terms of three perspectives,namely the arbitrariness of sign,the nature of identity and the linguistic value.It is also suggested that profound understanding of this relational nature facilitate our understanding of its importance not only in linguistics but also beyond linguistics.展开更多
In this paper,the entity_relation data model for integrating spatio_temporal data is designed.In the design,spatio_temporal data can be effectively stored and spatiao_temporal analysis can be easily realized.
We developed a parallel object relational DBMS named PORLES. It uses BSP model as its parallel computing model, and monoid calculus as its basis of data model. In this paper, we introduce its data model, parallel que...We developed a parallel object relational DBMS named PORLES. It uses BSP model as its parallel computing model, and monoid calculus as its basis of data model. In this paper, we introduce its data model, parallel query optimization, transaction processing system and parallel access method in detail.展开更多
For a transaction processing system to operate effectively and efficiently in cloud environments, it is important to distribute huge amount of data while guaranteeing the ACID （atomic, consistent, isolated, and dura...For a transaction processing system to operate effectively and efficiently in cloud environments, it is important to distribute huge amount of data while guaranteeing the ACID （atomic, consistent, isolated, and durable） properties. Moreover, database partition and migration tools can help transplanting conventional relational database systems to the cloud environment rather than rebuilding a new system. This paper proposes a database distribution management （DBDM） system, which partitions or replicates the data according to the transaction behaviors of the application system. The principle strategy of DBDM is to keep together the data used in a single transaction, and thus, avoiding massive transmission of records in join operations. The proposed system has been implemented successfully. The preliminary experiments show that the DBDM performs the database partition and migration effectively. Also, the DBDM system is modularly designed to adapt to different database management system （DBMS） or different partition algorithms.展开更多
In order to improve the utilization of the residential electricity consumption data which contains the information on the user’s electricity consumption habits, a residential electricity consumption behaviors mining ...In order to improve the utilization of the residential electricity consumption data which contains the information on the user’s electricity consumption habits, a residential electricity consumption behaviors mining algorithm model is constructed. Firstly, according to the attribute, the collected data can be divided into the global data and the phase data, then the appropriate global variables are selected to mine the user’s electricity consumption patterns in the near future on the system clustering algorithm. Based on the theory of grey relational analysis, combing phase data with the power modes to analyze the potential characteristics of residential electricity consumption behaviors deeply that verify the ability of latest power mode to predict household electricity consumption situation in the coming few days and the effect of dominant phase variables on the peak load shifting. Finally, from the actual data of a certain family, the proposed data mining algorithm is testified that it can effectively explore the electricity consumption behavior habits and characteristics of the family.展开更多
Cloud computing is one of the fastest growing and popular computer technologies, and there are more and more enterprise services based on the cloud computing. In order to save costs, more and more enterprises and thei...Cloud computing is one of the fastest growing and popular computer technologies, and there are more and more enterprise services based on the cloud computing. In order to save costs, more and more enterprises and their employees have hired the enterprise cloud services, and put much important information in the cloud gradually. Cloud service systems have become the main targets of malicious attacks. However, the cloud computing technologies are still not perfect, and the management and maintenance of enterprise cloud services are more complex compared to traditional network services of cloud computing. So, enterprise cloud services are more likely to encounter some security problems, and the influenced scale of these security problems is broad. But there are few researches on the security of enterprise cloud services. In this paper, we analyze the software as a service（Saa S） enterprise cloud services and introduce the research status of security problems in cloud computing environment. Combining with the analysis of the characteristics and application architecture of Saa S enterprise cloud services, we propose the security problems analysis model, the analysis system architecture and the relational model. Our researches can support further research of the automatic generation of solutions and guide the deployment of security policies of Saa S enterprise cloud services.展开更多
This study investigates the coordination between regional economic growth and ecological sustainability within the context of high-quality town economy development.To address the challenges of balancing economic expan...This study investigates the coordination between regional economic growth and ecological sustainability within the context of high-quality town economy development.To address the challenges of balancing economic expansion with environmental protection,a comprehensive evaluation index system is constructed,encompassing two key dimensions:regional economy and ecological environment.Using panel data from 2013 to 2022,the coupling coordination degree model is employed to quantify the interactions and synergy between these dimensions.Additionally,spatial econometric methods are applied to calculate both global and local Moran’s Index,revealing spatial clustering patterns,regional disparities,and heterogeneity.The relative development model further identifies critical factors influencing regional coordination,with a focus on the lagging development of basic infrastructure and public services.The findings demonstrate a positive temporal trend toward improved regional coordination and reduced development gaps,with a spatial pattern characterized by higher coupling degrees in eastern and central regions compared to western areas.Based on these results,this study proposes actionable strategies to enhance coordinated development,emphasizing ecological conservation,the establishment of green production and consumption systems,ecological restoration,and strengthened municipal collaboration.This revised abstract emphasizes the study’s purpose,methods,and key findings more clearly while maintaining a professional and concise tone.Finally,based on the above analysis results,the corresponding coordinated development suggestions of regional economy and ecological environment are given from the aspects of ecological environment protection measures,green production and consumption system construction,ecological environment restoration and municipal coordination.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
Multi-view clustering is a critical research area in computer science aimed at effectively extracting meaningful patterns from complex,high-dimensional data that single-view methods cannot capture.Traditional fuzzy cl...Multi-view clustering is a critical research area in computer science aimed at effectively extracting meaningful patterns from complex,high-dimensional data that single-view methods cannot capture.Traditional fuzzy clustering techniques,such as Fuzzy C-Means(FCM),face significant challenges in handling uncertainty and the dependencies between different views.To overcome these limitations,we introduce a new multi-view fuzzy clustering approach that integrates picture fuzzy sets with a dual-anchor graph method for multi-view data,aiming to enhance clustering accuracy and robustness,termed Multi-view Picture Fuzzy Clustering(MPFC).In particular,the picture fuzzy set theory extends the capability to represent uncertainty by modeling three membership levels:membership degrees,neutral degrees,and refusal degrees.This allows for a more flexible representation of uncertain and conflicting data than traditional fuzzy models.Meanwhile,dual-anchor graphs exploit the similarity relationships between data points and integrate information across views.This combination improves stability,scalability,and robustness when handling noisy and heterogeneous data.Experimental results on several benchmark datasets demonstrate significant improvements in clustering accuracy and efficiency,outperforming traditional methods.Specifically,the MPFC algorithm demonstrates outstanding clustering performance on a variety of datasets,attaining a Purity(PUR)score of 0.6440 and an Accuracy(ACC)score of 0.6213 for the 3 Sources dataset,underscoring its robustness and efficiency.The proposed approach significantly contributes to fields such as pattern recognition,multi-view relational data analysis,and large-scale clustering problems.Future work will focus on extending the method for semi-supervised multi-view clustering,aiming to enhance adaptability,scalability,and performance in real-world applications.展开更多
Moso bamboo(Phyllostachys edulis)forests are a vital resource in subtropical China,known for their high carbon(C)sequestration capacity.However,the dynamic processes of C fluxes within each component(canopy,culm,and s...Moso bamboo(Phyllostachys edulis)forests are a vital resource in subtropical China,known for their high carbon(C)sequestration capacity.However,the dynamic processes of C fluxes within each component(canopy,culm,and soil)and their individual contributions,particularly during on-and off-years,remain unclear.A 2-year field experiment was conducted to investigate the dynamics of C fluxes from the canopy,culm,and soil(partitioned into heterotrophic,rhizome,and stump respiration)and their contributions to net ecosystem productivity(NEP)in a representative Moso bamboo forest in the subtropical region of China.The average annual NEP of the Moso bamboo forest was 7.31±2.76 t C·ha^(-1).Specifically,the canopy's annual net C uptake was 17.30±3.23 tC·ha^(-1),accounting for 237%of NEP.In contrast,C emissions from heterotrophs,culms,rhizomes,and stumps were 5.37±1.20,2.18±1.05,1.29±0.04,and 1.15±0.33 t C·ha^(-1),accounting for73%,30%,18%,and16%of NEP,respectively.The NEP,net cumulative C uptake in the canopy,and C emissions from the respiration of heterotrophs and stumps were all significantly higher during on-years when compared to off-years,whereas C emissions from bamboo culms displayed opposite trends.These findings offer a new approach for quantifying the C budgets of Moso bamboo forests and provide valuable insights into the C cycling processes in forest ecosystems.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
Relational theory represents a critical paradigm in understanding organizational dynamics,policy formation,and leadership effectiveness.This comprehensive literature review explores the theoretical foundations,practic...Relational theory represents a critical paradigm in understanding organizational dynamics,policy formation,and leadership effectiveness.This comprehensive literature review explores the theoretical foundations,practical implications,and organizational leadership applications of relational theory across diverse contextual frameworks.By synthesizing contemporary scholarly research,this review critically examines the theory’s epistemological underpinnings,methodological approaches,and transformative potential in organizational policy development.The analysis reveals complex interconnections between relational theory,organizational behavior,leadership strategies,and systemic policy implementation,highlighting both the theory’s significant potential and inherent limitations in contemporary organizational contexts.展开更多
This study introduces a novel approach to addressing the challenges of high-dimensional variables and strong nonlinearity in reservoir production and layer configuration optimization.For the first time,relational mach...This study introduces a novel approach to addressing the challenges of high-dimensional variables and strong nonlinearity in reservoir production and layer configuration optimization.For the first time,relational machine learning models are applied in reservoir development optimization.Traditional regression-based models often struggle in complex scenarios,but the proposed relational and regression-based composite differential evolution(RRCODE)method combines a Gaussian naive Bayes relational model with a radial basis function network regression model.This integration effectively captures complex relationships in the optimization process,improving both accuracy and convergence speed.Experimental tests on a multi-layer multi-channel reservoir model,the Egg reservoir model,and a real-field reservoir model(the S reservoir)demonstrate that RRCODE significantly reduces water injection and production volumes while increasing economic returns and cumulative oil recovery.Moreover,the surrogate models employed in RRCODE exhibit lightweight characteristics with low computational overhead.These results highlight RRCODE's superior performance in the integrated optimization of reservoir production and layer configurations,offering more efficient and economically viable solutions for oilfield development.展开更多
In the era of exponential growth of digital information,recommender algorithms are vital for helping users navigate vast data to find relevant items.Traditional approaches such as collaborative filtering and contentba...In the era of exponential growth of digital information,recommender algorithms are vital for helping users navigate vast data to find relevant items.Traditional approaches such as collaborative filtering and contentbasedmethods have limitations in capturing complex,multi-faceted relationships in large-scale,sparse datasets.Recent advances in Graph Neural Networks(GNNs)have significantly improved recommendation performance by modeling high-order connection patterns within user-item interaction networks.However,existing GNN-based models like LightGCN and NGCF focus primarily on single-type interactions and often overlook diverse semantic relationships,leading to reduced recommendation diversity and limited generalization.To address these challenges,this paper proposes a dual multi-relational graph neural network recommendation algorithm based on relational interactions.Our approach constructs two complementary graph structures:a User-Item Interaction Graph(UIIG),which explicitly models direct user behaviors such as clicks and purchases,and a Relational Association Graph(RAG),which uncovers latent associations based on user similarities and item attributes.The proposed Dual Multi-relational Graph Neural Network(DMGNN)features two parallel branches that perform multi-layer graph convolutional operations,followed by an adaptive fusion mechanism to effectively integrate information from both graphs.This design enhances the model’s capacity to capture diverse relationship types and complex relational patterns.Extensive experiments conducted on benchmark datasets—including MovieLens-1M,Amazon-Electronics,and Yelp—demonstrate thatDMGNN outperforms state-of-the-art baselines,achieving improvements of up to 12.3%in Precision,9.7%in Recall,and 11.5%in F1 score.Moreover,DMGNN significantly boosts recommendation diversity by 15.2%,balancing accuracy with exploration.These results highlight the effectiveness of leveraging hierarchical multi-relational information,offering a promising solution to the challenges of data sparsity and relation heterogeneity in recommendation systems.Our work advances the theoretical understanding of multi-relational graph modeling and presents practical insights for developing more personalized,diverse,and robust recommender systems.展开更多
Based on the variation of discrete surface,a new grey relational analysis model,called the grey variation relational ana-lysis(GVRA)model,is proposed in this paper.Meanwhile,the proposed model avoids the inconsistent ...Based on the variation of discrete surface,a new grey relational analysis model,called the grey variation relational ana-lysis(GVRA)model,is proposed in this paper.Meanwhile,the proposed model avoids the inconsistent results caused by diffe-rent construction of discrete surface of panel data or the change in the order of indicators or objects in existing grey relational analysis models.Firstly,the submatrix of the sample matrix is given according to the permutation and combination theory.Secondly,the amplitude of the submatrix is calculated and the variation of discrete surface is obtained.Then,a grey relational coefficient is presented by variation difference,and the GVRA model is established.Furthermore,the properties of the pro-posed model,such as normality,symmetry,reflexivity,transla-tion invariant,and number multiplication invariant,are also veri-fied.Finally,the proposed model is used to identify the driving factors of haze in the cities along the Yellow River in Shandong Province,China.The result reveals that the proposed model can effectively measure the relationship between panel data.展开更多
Conceptualizations of empathy have been most fully developed in a variety of fields in recent years.Many approaches to empathy dwell on the cognitive,affective,and behavioral aspects,the intra-psychic processes that c...Conceptualizations of empathy have been most fully developed in a variety of fields in recent years.Many approaches to empathy dwell on the cognitive,affective,and behavioral aspects,the intra-psychic processes that cause one to feel emotions more like those of another,rather than the interpersonal functions of empathy,which may be influenced by the variables during the communication process.Therefore,this study designed and implemented a virtual ethnographic intercultural project between Chinese and American university students with WeChat as the main social medium.The whole process included three phases:exploring the unique cultural experiences of Chinese and American students,seeking an empathy based on commonality and seeking a relational empathy,a form of harmonization and integration through interactive and continuous intercultural dialogues.During the process,the method of discourse-centered online ethnography(DCOE)was employed,which involved systematic observation and interaction with WeChat users.We used the collective data to analyze how relational empathy was developed through understanding cultural differences,seeking similarities,and creating a third culture by engaging students in a substantial and dynamic natural and interactive setting.The study shows that the most challenging process to nurture relational empathy is to move from Phases One and Two to Phase Three,during which,some strategies to build relational empathy need to be taught and practiced in a specific cultural setting.In conclusion,virtual ethnographic intercultural teaching is an effective approach to offer students a long-term intercultural dialogue and insight into developing shared meaning,or dynamic relational empathy with culturally different others.展开更多
文摘In social sciences it is more or less generally acknowledged that (social) networks seem to be the natural tool in the organization of social activity. In the liteature on the mathematical description of social phenomena the concept of a network is hardly used.In this paper we focus on the development of a’possible mathematical formualtion of the properties of a social network and a minimal and nearly complete social relational subsystem as a quasi-network within the setting of an economic trade system.
文摘To evaluate the effectiveness of weapon systems, the advantages and disadvantages of grey relational analysis and TOPSIS for multiattribute decision-making is pointed out, and an effectiveness evaluation model of weapon systems by combining grey relational analysis and TOPSIS is proposed. The model aggregates the grey relational grade and the distance to a new integrated closeness and reflects not only the trend but also the situation of the alternative. The example illuminates that the model is effective for the effectiveness evaluation of weapon systems.
基金supported by the National Natural Science Foundation of China(51375389)
文摘A proper weapon system is very important for a na- tional defense system. Generally, it means selecting the optimal weapon system among many alternatives, which is a multiple- attribute decision making （MADM） problem. This paper proposes a new mathematical model based on the response surface method （RSM） and the grey relational analysis （GRA）. RSM is used to obtain the experimental points and analyze the factors that have a significant impact on the selection results. GRA is used to an- alyze the trend relationship between alternatives and reference series. And then an RSM model is obtained, which can be used to calculate all alternatives and obtain ranking results. A real world application is introduced to illustrate the utilization of the model for the weapon selection problem. The results show that this model can be used to help decision-makers to make a quick comparison of alternatives and select a proper weapon system from multiple alternatives, which is an effective and adaptable method for solving the weapon system selection problem.
基金financially supported by the National Institute of Technology,Manipur,India
文摘The strength of the mould cavity in sand casting is very much significant to attain high-quality castings. Optimization of green sand process parameters plays a vital role in minimizing casting defects. In the present research work, the effect of process parameters such as AFS grain fineness number, water, molasses, bentonite, fly ash, and ramming, and their levels on the resultant mould properties were investigated and optimized using Taguchi based grey relational analysis. The Taguchi L18 orthogonal array and analysis of variance(ANOVA) were used. The quality characteristics viz., green compression strength, permeability, bulk density, mould hardness and shatter index of green sand mould were optimized using grey relational grade, based on the experiments designed using Taguchi's Design of Experiments. ANOVA analysis indicated that water content is the most influential parameter followed by bentonite, and degree of ramming that contributes to the quality characteristics. The results are confirmed by calculating confidence intervals, which lies within the interval limits. Finally, microstructure observations and X-ray diffraction analysis have been performed for the optimal sand parametric combination. Results show that presence of maximum amount of SiO_2, which might be the reason for enhancement of the physical properties of the sand.
文摘Relational nature of language system is of vital importance in Saussure's theory of linguistics.As philosopher Ernst Cassirer put that the crucial and revolutionary aspect of modern linguistics was Saussure's affirmation of the primacy of relation and the system of relations.This paper is devoted to a clear elaboration of the relational nature of linguistic system in terms of three perspectives,namely the arbitrariness of sign,the nature of identity and the linguistic value.It is also suggested that profound understanding of this relational nature facilitate our understanding of its importance not only in linguistics but also beyond linguistics.
基金Project supported by the National Surveying Technical Fund(No.200_07)
文摘In this paper,the entity_relation data model for integrating spatio_temporal data is designed.In the design,spatio_temporal data can be effectively stored and spatiao_temporal analysis can be easily realized.
文摘We developed a parallel object relational DBMS named PORLES. It uses BSP model as its parallel computing model, and monoid calculus as its basis of data model. In this paper, we introduce its data model, parallel query optimization, transaction processing system and parallel access method in detail.
基金supported by the Taiwan Ministry of Economic Affairs and Institute for Information Industry under the project titled "Fundamental Industrial Technology Development Program (1/4)"
文摘For a transaction processing system to operate effectively and efficiently in cloud environments, it is important to distribute huge amount of data while guaranteeing the ACID （atomic, consistent, isolated, and durable） properties. Moreover, database partition and migration tools can help transplanting conventional relational database systems to the cloud environment rather than rebuilding a new system. This paper proposes a database distribution management （DBDM） system, which partitions or replicates the data according to the transaction behaviors of the application system. The principle strategy of DBDM is to keep together the data used in a single transaction, and thus, avoiding massive transmission of records in join operations. The proposed system has been implemented successfully. The preliminary experiments show that the DBDM performs the database partition and migration effectively. Also, the DBDM system is modularly designed to adapt to different database management system （DBMS） or different partition algorithms.
文摘In order to improve the utilization of the residential electricity consumption data which contains the information on the user’s electricity consumption habits, a residential electricity consumption behaviors mining algorithm model is constructed. Firstly, according to the attribute, the collected data can be divided into the global data and the phase data, then the appropriate global variables are selected to mine the user’s electricity consumption patterns in the near future on the system clustering algorithm. Based on the theory of grey relational analysis, combing phase data with the power modes to analyze the potential characteristics of residential electricity consumption behaviors deeply that verify the ability of latest power mode to predict household electricity consumption situation in the coming few days and the effect of dominant phase variables on the peak load shifting. Finally, from the actual data of a certain family, the proposed data mining algorithm is testified that it can effectively explore the electricity consumption behavior habits and characteristics of the family.
基金supported by National Natural Science Foundation of China(Nos.61300049,61502197 and 61503044)the Specialized Research Fund for the Doctoral Program of Higher Education of China(No.20120061120059)+2 种基金the China Postdoctoral Science Foundation(No.2011M500612)the Key Program for Science and Technology Development of Jilin Province of China(No.20130206052GX)the Natural Science Research Foundation of Jilin Province of China(Nos.20140520069JH,20150101054JC and 20150520058JH)
文摘Cloud computing is one of the fastest growing and popular computer technologies, and there are more and more enterprise services based on the cloud computing. In order to save costs, more and more enterprises and their employees have hired the enterprise cloud services, and put much important information in the cloud gradually. Cloud service systems have become the main targets of malicious attacks. However, the cloud computing technologies are still not perfect, and the management and maintenance of enterprise cloud services are more complex compared to traditional network services of cloud computing. So, enterprise cloud services are more likely to encounter some security problems, and the influenced scale of these security problems is broad. But there are few researches on the security of enterprise cloud services. In this paper, we analyze the software as a service（Saa S） enterprise cloud services and introduce the research status of security problems in cloud computing environment. Combining with the analysis of the characteristics and application architecture of Saa S enterprise cloud services, we propose the security problems analysis model, the analysis system architecture and the relational model. Our researches can support further research of the automatic generation of solutions and guide the deployment of security policies of Saa S enterprise cloud services.
基金support from Guangdong Science and Technology(20230505)Guangdong Provincial Philosophy and Social Science Planning Project(GD20SQ25)Guangdong Provincial Special Fund for Science and Technology Innovation Strategy in 2024(Cultivation of College Students’Science and Technology Innovation)(pdjh2024a391)during preparation of this manuscript.
文摘This study investigates the coordination between regional economic growth and ecological sustainability within the context of high-quality town economy development.To address the challenges of balancing economic expansion with environmental protection,a comprehensive evaluation index system is constructed,encompassing two key dimensions:regional economy and ecological environment.Using panel data from 2013 to 2022,the coupling coordination degree model is employed to quantify the interactions and synergy between these dimensions.Additionally,spatial econometric methods are applied to calculate both global and local Moran’s Index,revealing spatial clustering patterns,regional disparities,and heterogeneity.The relative development model further identifies critical factors influencing regional coordination,with a focus on the lagging development of basic infrastructure and public services.The findings demonstrate a positive temporal trend toward improved regional coordination and reduced development gaps,with a spatial pattern characterized by higher coupling degrees in eastern and central regions compared to western areas.Based on these results,this study proposes actionable strategies to enhance coordinated development,emphasizing ecological conservation,the establishment of green production and consumption systems,ecological restoration,and strengthened municipal collaboration.This revised abstract emphasizes the study’s purpose,methods,and key findings more clearly while maintaining a professional and concise tone.Finally,based on the above analysis results,the corresponding coordinated development suggestions of regional economy and ecological environment are given from the aspects of ecological environment protection measures,green production and consumption system construction,ecological environment restoration and municipal coordination.
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.
基金funded by the Research Project:THTETN.05/24-25,VietnamAcademy of Science and Technology.
文摘Multi-view clustering is a critical research area in computer science aimed at effectively extracting meaningful patterns from complex,high-dimensional data that single-view methods cannot capture.Traditional fuzzy clustering techniques,such as Fuzzy C-Means(FCM),face significant challenges in handling uncertainty and the dependencies between different views.To overcome these limitations,we introduce a new multi-view fuzzy clustering approach that integrates picture fuzzy sets with a dual-anchor graph method for multi-view data,aiming to enhance clustering accuracy and robustness,termed Multi-view Picture Fuzzy Clustering(MPFC).In particular,the picture fuzzy set theory extends the capability to represent uncertainty by modeling three membership levels:membership degrees,neutral degrees,and refusal degrees.This allows for a more flexible representation of uncertain and conflicting data than traditional fuzzy models.Meanwhile,dual-anchor graphs exploit the similarity relationships between data points and integrate information across views.This combination improves stability,scalability,and robustness when handling noisy and heterogeneous data.Experimental results on several benchmark datasets demonstrate significant improvements in clustering accuracy and efficiency,outperforming traditional methods.Specifically,the MPFC algorithm demonstrates outstanding clustering performance on a variety of datasets,attaining a Purity(PUR)score of 0.6440 and an Accuracy(ACC)score of 0.6213 for the 3 Sources dataset,underscoring its robustness and efficiency.The proposed approach significantly contributes to fields such as pattern recognition,multi-view relational data analysis,and large-scale clustering problems.Future work will focus on extending the method for semi-supervised multi-view clustering,aiming to enhance adaptability,scalability,and performance in real-world applications.
基金sponsored by the National Natural Science Foundation of China(Grant Nos.32125027,31930075)Zhejiang A&F University Research and Development Fund(No.2022LFR006).
文摘Moso bamboo(Phyllostachys edulis)forests are a vital resource in subtropical China,known for their high carbon(C)sequestration capacity.However,the dynamic processes of C fluxes within each component(canopy,culm,and soil)and their individual contributions,particularly during on-and off-years,remain unclear.A 2-year field experiment was conducted to investigate the dynamics of C fluxes from the canopy,culm,and soil(partitioned into heterotrophic,rhizome,and stump respiration)and their contributions to net ecosystem productivity(NEP)in a representative Moso bamboo forest in the subtropical region of China.The average annual NEP of the Moso bamboo forest was 7.31±2.76 t C·ha^(-1).Specifically,the canopy's annual net C uptake was 17.30±3.23 tC·ha^(-1),accounting for 237%of NEP.In contrast,C emissions from heterotrophs,culms,rhizomes,and stumps were 5.37±1.20,2.18±1.05,1.29±0.04,and 1.15±0.33 t C·ha^(-1),accounting for73%,30%,18%,and16%of NEP,respectively.The NEP,net cumulative C uptake in the canopy,and C emissions from the respiration of heterotrophs and stumps were all significantly higher during on-years when compared to off-years,whereas C emissions from bamboo culms displayed opposite trends.These findings offer a new approach for quantifying the C budgets of Moso bamboo forests and provide valuable insights into the C cycling processes in forest ecosystems.
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.
文摘Relational theory represents a critical paradigm in understanding organizational dynamics,policy formation,and leadership effectiveness.This comprehensive literature review explores the theoretical foundations,practical implications,and organizational leadership applications of relational theory across diverse contextual frameworks.By synthesizing contemporary scholarly research,this review critically examines the theory’s epistemological underpinnings,methodological approaches,and transformative potential in organizational policy development.The analysis reveals complex interconnections between relational theory,organizational behavior,leadership strategies,and systemic policy implementation,highlighting both the theory’s significant potential and inherent limitations in contemporary organizational contexts.
基金supported by the National Natural Science Foundation of China under Grant 52325402,52274057,and 52074340the National Key R&D Program of China under Grant 2023YFB4104200+2 种基金the Major Scientific and Technological Projects of CNOOC under Grant CCL2022RCPS0397RSN111 Project under Grant B08028China Scholarship Council under Grant 202306450108.
文摘This study introduces a novel approach to addressing the challenges of high-dimensional variables and strong nonlinearity in reservoir production and layer configuration optimization.For the first time,relational machine learning models are applied in reservoir development optimization.Traditional regression-based models often struggle in complex scenarios,but the proposed relational and regression-based composite differential evolution(RRCODE)method combines a Gaussian naive Bayes relational model with a radial basis function network regression model.This integration effectively captures complex relationships in the optimization process,improving both accuracy and convergence speed.Experimental tests on a multi-layer multi-channel reservoir model,the Egg reservoir model,and a real-field reservoir model(the S reservoir)demonstrate that RRCODE significantly reduces water injection and production volumes while increasing economic returns and cumulative oil recovery.Moreover,the surrogate models employed in RRCODE exhibit lightweight characteristics with low computational overhead.These results highlight RRCODE's superior performance in the integrated optimization of reservoir production and layer configurations,offering more efficient and economically viable solutions for oilfield development.
文摘In the era of exponential growth of digital information,recommender algorithms are vital for helping users navigate vast data to find relevant items.Traditional approaches such as collaborative filtering and contentbasedmethods have limitations in capturing complex,multi-faceted relationships in large-scale,sparse datasets.Recent advances in Graph Neural Networks(GNNs)have significantly improved recommendation performance by modeling high-order connection patterns within user-item interaction networks.However,existing GNN-based models like LightGCN and NGCF focus primarily on single-type interactions and often overlook diverse semantic relationships,leading to reduced recommendation diversity and limited generalization.To address these challenges,this paper proposes a dual multi-relational graph neural network recommendation algorithm based on relational interactions.Our approach constructs two complementary graph structures:a User-Item Interaction Graph(UIIG),which explicitly models direct user behaviors such as clicks and purchases,and a Relational Association Graph(RAG),which uncovers latent associations based on user similarities and item attributes.The proposed Dual Multi-relational Graph Neural Network(DMGNN)features two parallel branches that perform multi-layer graph convolutional operations,followed by an adaptive fusion mechanism to effectively integrate information from both graphs.This design enhances the model’s capacity to capture diverse relationship types and complex relational patterns.Extensive experiments conducted on benchmark datasets—including MovieLens-1M,Amazon-Electronics,and Yelp—demonstrate thatDMGNN outperforms state-of-the-art baselines,achieving improvements of up to 12.3%in Precision,9.7%in Recall,and 11.5%in F1 score.Moreover,DMGNN significantly boosts recommendation diversity by 15.2%,balancing accuracy with exploration.These results highlight the effectiveness of leveraging hierarchical multi-relational information,offering a promising solution to the challenges of data sparsity and relation heterogeneity in recommendation systems.Our work advances the theoretical understanding of multi-relational graph modeling and presents practical insights for developing more personalized,diverse,and robust recommender systems.
基金supported by the National Natural Science Foundation of China(72271124,72071111)Shandong Natural Science Foundation(ZR2023MG070)the Social Science Planning Project of Shandong Province(23CGLJ03,21CTJJ01).
文摘Based on the variation of discrete surface,a new grey relational analysis model,called the grey variation relational ana-lysis(GVRA)model,is proposed in this paper.Meanwhile,the proposed model avoids the inconsistent results caused by diffe-rent construction of discrete surface of panel data or the change in the order of indicators or objects in existing grey relational analysis models.Firstly,the submatrix of the sample matrix is given according to the permutation and combination theory.Secondly,the amplitude of the submatrix is calculated and the variation of discrete surface is obtained.Then,a grey relational coefficient is presented by variation difference,and the GVRA model is established.Furthermore,the properties of the pro-posed model,such as normality,symmetry,reflexivity,transla-tion invariant,and number multiplication invariant,are also veri-fied.Finally,the proposed model is used to identify the driving factors of haze in the cities along the Yellow River in Shandong Province,China.The result reveals that the proposed model can effectively measure the relationship between panel data.
文摘Conceptualizations of empathy have been most fully developed in a variety of fields in recent years.Many approaches to empathy dwell on the cognitive,affective,and behavioral aspects,the intra-psychic processes that cause one to feel emotions more like those of another,rather than the interpersonal functions of empathy,which may be influenced by the variables during the communication process.Therefore,this study designed and implemented a virtual ethnographic intercultural project between Chinese and American university students with WeChat as the main social medium.The whole process included three phases:exploring the unique cultural experiences of Chinese and American students,seeking an empathy based on commonality and seeking a relational empathy,a form of harmonization and integration through interactive and continuous intercultural dialogues.During the process,the method of discourse-centered online ethnography(DCOE)was employed,which involved systematic observation and interaction with WeChat users.We used the collective data to analyze how relational empathy was developed through understanding cultural differences,seeking similarities,and creating a third culture by engaging students in a substantial and dynamic natural and interactive setting.The study shows that the most challenging process to nurture relational empathy is to move from Phases One and Two to Phase Three,during which,some strategies to build relational empathy need to be taught and practiced in a specific cultural setting.In conclusion,virtual ethnographic intercultural teaching is an effective approach to offer students a long-term intercultural dialogue and insight into developing shared meaning,or dynamic relational empathy with culturally different others.
