A composite anti-disturbance predictive control strategy employing a Multi-dimensional Taylor Network(MTN)is presented for unmanned systems subject to time-delay and multi-source disturbances.First,the multi-source di...A composite anti-disturbance predictive control strategy employing a Multi-dimensional Taylor Network(MTN)is presented for unmanned systems subject to time-delay and multi-source disturbances.First,the multi-source disturbances are addressed according to their specific characteristics as follows:(A)an MTN data-driven model,which is used for uncertainty description,is designed accompanied with the mechanism model to represent the unmanned systems;(B)an adaptive MTN filter is used to remove the influence of the internal disturbance;(C)an MTN disturbance observer is constructed to estimate and compensate for the influence of the external disturbance;(D)the Extended Kalman Filter(EKF)algorithm is utilized as the learning mechanism for MTNs.Second,to address the time-delay effect,a recursiveτstep-ahead MTN predictive model is designed utilizing recursive technology,aiming to mitigate the impact of time-delay,and the EKF algorithm is employed as its learning mechanism.Then,the MTN predictive control law is designed based on the quadratic performance index.By implementing the proposed composite controller to unmanned systems,simultaneous feedforward compensation and feedback suppression to the multi-source disturbances are conducted.Finally,the convergence of the MTN and the stability of the closed-loop system are established utilizing the Lyapunov theorem.Two exemplary applications of unmanned systems involving unmanned vehicle and rigid spacecraft are presented to validate the effectiveness of the proposed approach.展开更多
Normal forms have a significant role in the theory of relational database normalization.The definitions of normal forms are established through the functional dependency(FD)relationship between a prime or nonprime att...Normal forms have a significant role in the theory of relational database normalization.The definitions of normal forms are established through the functional dependency(FD)relationship between a prime or nonprime attribute and a key.However,determining whether an attribute is a prime attribute is a nondeterministic polynomial-time complete(NP-complete)problem,making it intractable to determine if a relation scheme is in a specific normal form.While the prime attribute problem is generally NP-complete,there are cases where identifying prime attributes is not challenging.In a relation scheme R(U,F),we partition U into four distinct subsets based on where attributes in U appear in F:U_(1)(attributes only appearing on the left-hand side of FDs),U_(2)(attributes only appearing on the right-hand side of FDs),U_(3)(attributes appearing on both sides of FDs),and U_(4)(attributes not present in F).Next,we demonstrate the necessary and sufficient conditions for a key to be the unique key of a relation scheme.Subsequently,we illustrate the features of prime attributes in U_(3) and generalize the features of common prime attributes.The findings lay the groundwork for distinguishing between complex and simple cases in prime attribute identification,thereby deepening the understanding of this problem.展开更多
The ancient tacit knowledge behind the logic system permeated the culture and promoted numerous impactful inventions throughout the history. Traditional Chinese medicine with its effectiveness should also have stemmed...The ancient tacit knowledge behind the logic system permeated the culture and promoted numerous impactful inventions throughout the history. Traditional Chinese medicine with its effectiveness should also have stemmed out from such logic system. This article aims to rearticulate the underlying lucid multi-dimensional logic system, which faded in obscurity only because of time-out loss of the mid-right concept. Retracing this past tacit but important concept could uncover a multi-dimensional system over a point relating to all matters while capturing the central core of the matter. The seemingly unmanageable multidimensional logic was strengthened by verification processes which affirmed its further extensions, and made up the language of the people, the concepts of yin-yang(阴阳), and the development of extensions of Ba Gua(八卦) derivatives, which furthered the interpretation of the space-time properties and Chinese medicine.展开更多
Stress accumulation is a key factor leading to sodium storage performance deterioration for NiSe_(2)-based anodes.Therefore,inhibiting the concentrated local stress during the sodiataion/desodiation process is crucial...Stress accumulation is a key factor leading to sodium storage performance deterioration for NiSe_(2)-based anodes.Therefore,inhibiting the concentrated local stress during the sodiataion/desodiation process is crucial for acquiring stable NiSe2-based materials for sodium-ion batteries(SIBs),Herein,a stress dissipation strategy driven by architecture engineering is proposed,which can achieve ultrafast and ultralong sodium storage properties.Different from the conventional sphere-like or rod-like architecture,the three-dimensional(3D)flower-like NiSe_(2)@C composite is delicately designed and assembled with onedimensional nanorods and carbon framework.More importantly,the fundamental mechanism of improved structure stability is unveiled by simulations and experimental results simultaneously.It demonstrates that this designed multidimensional flower-like architecture with dispersed nanorods can balance the structural mismatch,avoid concentrated local strain,and relax the internal stress,mainly induced by the unavoidable volume variation during the repeated conversion processes.Moreover,it can provide more Na^(+)-storage sites and multi-directional migration pathways,leading to a fast Na^(+)-migration channel with boosted reaction kinetic.As expected,it delivers superior rate performance(441 mA h g^(-1)at 5.0 A g^(-1))and long cycling stability(563 mA h g^(-1)at 1.0 A g^(-1)over 1000 cycles)for SIBs.This work provides useful insights for designing high-performance conversion-based anode materials for SIBs.展开更多
This paper explores whole-process engineering consulting,including its application models in public buildings and elderly-friendly projects,such as service integration and whole lifecycle management.It also addresses ...This paper explores whole-process engineering consulting,including its application models in public buildings and elderly-friendly projects,such as service integration and whole lifecycle management.It also addresses the construction of multi-dimensional collaborative theoretical models,public space streamline organization,and other aspects,emphasizing the importance of multi-dimensional collaboration.Additionally,it highlights the role of talent cultivation and digital transformation in enhancing project efficiency.展开更多
This study analyzes the risks of re-identification in Korean text data and proposes a secure,ethical approach to data anonymization.Following the‘Lee Luda’AI chatbot incident,concerns over data privacy have increase...This study analyzes the risks of re-identification in Korean text data and proposes a secure,ethical approach to data anonymization.Following the‘Lee Luda’AI chatbot incident,concerns over data privacy have increased.The Personal Information Protection Commission of Korea conducted inspections of AI services,uncovering 850 cases of personal information in user input datasets,highlighting the need for pseudonymization standards.While current anonymization techniques remove personal data like names,phone numbers,and addresses,linguistic features such as writing habits and language-specific traits can still identify individuals when combined with other data.To address this,we analyzed 50,000 Korean text samples from the X platform,focusing on language-specific features for authorship attribution.Unlike English,Korean features flexible syntax,honorifics,syllabic and grapheme patterns,and referential terms.These linguistic characteristics were used to enhance re-identification accuracy.Our experiments combined five machine learning models,six stopword processing methods,and four morphological analyzers.By using a tokenizer that captures word frequency and order,and employing the LSTM model,OKT morphological analyzer,and stopword removal,we achieved the maximum authorship attributions accuracy of 90.51%.This demonstrates the significant role of Korean linguistic features in re-identification.The findings emphasize the risk of re-identification through language data and call for a re-evaluation of anonymization methods,urging the consideration of linguistic traits in anonymization beyond simply removing personal information.展开更多
Detecting overlapping communities in attributed networks remains a significant challenge due to the complexity of jointly modeling topological structure and node attributes,the unknown number of communities,and the ne...Detecting overlapping communities in attributed networks remains a significant challenge due to the complexity of jointly modeling topological structure and node attributes,the unknown number of communities,and the need to capture nodes with multiple memberships.To address these issues,we propose a novel framework named density peaks clustering with neutrosophic C-means.First,we construct a consensus embedding by aligning structure-based and attribute-based representations using spectral decomposition and canonical correlation analysis.Then,an improved density peaks algorithm automatically estimates the number of communities and selects initial cluster centers based on a newly designed cluster strength metric.Finally,a neutrosophic C-means algorithm refines the community assignments,modeling uncertainty and overlap explicitly.Experimental results on synthetic and real-world networks demonstrate that the proposed method achieves superior performance in terms of detection accuracy,stability,and its ability to identify overlapping structures.展开更多
The multi-dimensional interactive teaching model significantly enhances the effectiveness of college English instruction by emphasizing dynamic engagement between teachers and students,as well as among students themse...The multi-dimensional interactive teaching model significantly enhances the effectiveness of college English instruction by emphasizing dynamic engagement between teachers and students,as well as among students themselves.This paper explores practical strategies for implementing this model,focusing on four key aspects:deepening teachers’understanding of the model through continuous learning,innovating interactive methods such as questioning techniques and practical activities,leveraging modern technology to integrate resources and track learning progress,and establishing a communication platform that centers on student participation.By adopting these approaches,the model fosters a student-centered classroom environment,improves comprehensive English application skills,and optimizes overall teaching quality.展开更多
Linguistic steganography(LS)aims to embed secret information into normal natural text for covert communication.It includes modification-based(MLS)and generation-based(GLS)methods.MLS often relies on limited manual rul...Linguistic steganography(LS)aims to embed secret information into normal natural text for covert communication.It includes modification-based(MLS)and generation-based(GLS)methods.MLS often relies on limited manual rules,resulting in low embedding capacity,while GLS achieves higher embedding capacity through automatic text generation but typically ignores extraction efficiency.To address this,we propose a sentence attribute encodingbased MLS method that enhances extraction efficiency while maintaining strong performance.The proposed method designs a lightweight semantic attribute analyzer to encode sentence attributes for embedding secret information.When the attribute values of the cover sentence differ from the secret information to be embedded,a semantic attribute adjuster based on paraphrasing is used to automatically generate paraphrase sentences of the target attribute,thereby improving the problem of insufficient manual rules.During the extraction,secret information can be extracted solely by employing the semantic attribute analyzer,thereby eliminating the dependence on the paraphrasing generation model.Experimental results show that thismethod achieves an extraction speed of 1141.54 bits/sec,compared with the existing methods,it has remarkable advantages regarding extraction speed.Meanwhile,the stego text generated by thismethod respectively reaches 68.53,39.88,and 80.77 on BLEU,△PPL,and BERTScore.Compared with the existing methods,the text quality is effectively improved.展开更多
During the critical transformation period of landscape architecture major after the adjustment of disciplinary structure and the changes in market demand,private colleges and universities,as important places for culti...During the critical transformation period of landscape architecture major after the adjustment of disciplinary structure and the changes in market demand,private colleges and universities,as important places for cultivating local talents,have pain points such as uneven quality of teachers and students and weak innovation and practice.The practice system with“multi-dimensional Integration”integrates four dimensions:interdisciplinary integration,spatial and temporal intersection,historical inheritance,and behavioral activity,deepens the disciplinary connotation,and integrates the three elements of nature,humanity,and technology,aiming to provide a new path for private colleges and universities to cultivate application-oriented and compound talents with innovative capabilities.In terms of optimizing talent cultivation and adapting to industry changes,this system provides thinking and reference for landscape architecture major,helping the major reshape its core competitiveness and promoting educational innovation and industry development.展开更多
Security attributes are the premise and foundation for implementing Attribute-Based Access Control(ABAC)mechanisms.However,when dealing with massive volumes of unstructured text big data resources,the current attribut...Security attributes are the premise and foundation for implementing Attribute-Based Access Control(ABAC)mechanisms.However,when dealing with massive volumes of unstructured text big data resources,the current attribute management methods based on manual extraction face several issues,such as high costs for attribute extraction,long processing times,unstable accuracy,and poor scalability.To address these problems,this paper proposes an attribute mining technology for access control institutions based on hybrid capsule networks.This technology leverages transfer learning ideas,utilizing Bidirectional Encoder Representations from Transformers(BERT)pre-trained language models to achieve vectorization of unstructured text data resources.Furthermore,we have designed a novel end-to-end parallel hybrid network structure,where the parallel networks handle global and local information features of the text that they excel at,respectively.By employing techniques such as attention mechanisms,capsule networks,and dynamic routing,effective mining of security attributes for access control resources has been achieved.Finally,we evaluated the performance level of the proposed attribute mining method for access control institutions through experiments on the medical referral text resource dataset.The experimental results show that,compared with baseline algorithms,our method adopts a parallel network structure that can better balance global and local feature information,resulting in improved overall performance.Specifically,it achieves a comprehensive performance enhancement of 2.06%to 8.18%in the F1 score metric.Therefore,this technology can effectively provide attribute support for access control of unstructured text big data resources.展开更多
This paper proposes a reliability evaluation model for a multi-dimensional network system,which has potential to be applied to the internet of things or other practical networks.A multi-dimensional network system with...This paper proposes a reliability evaluation model for a multi-dimensional network system,which has potential to be applied to the internet of things or other practical networks.A multi-dimensional network system with one source element and multiple sink elements is considered first.Each element can con-nect with other elements within a stochastic connection ranges.The system is regarded as successful as long as the source ele-ment remains connected with all sink elements.An importance measure is proposed to evaluate the performance of non-source elements.Furthermore,to calculate the system reliability and the element importance measure,a multi-valued decision diagram based approach is structured and its complexity is analyzed.Finally,a numerical example about the signal transfer station system is illustrated to analyze the system reliability and the ele-ment importance measure.展开更多
Seismic attributes encapsulate substantial reservoir characterization information and can effectively support reservoir prediction.Given the high-dimensional nonlinear between sandbodies and seismic attributes,this st...Seismic attributes encapsulate substantial reservoir characterization information and can effectively support reservoir prediction.Given the high-dimensional nonlinear between sandbodies and seismic attributes,this study employs the RFECV method for seismic attribute selection,inputting the optimized attributes into a LightGBM model to enhance spatial delineation of sandbody identification.By constructing training datasets based on optimized seismic attributes and well logs,followed by class imbalance correction as input variables for machine learning models,with sandbody probability as the output variable,and employing grid search to optimize model parameters,a high-precision sandbody prediction model was established.Taking the 3D seismic data of Block F3 in the North Sea of Holland as an example,this method successfully depicted the three-dimensional spatial distribution of target formation sandstones.The results indicate that even under strong noise conditions,the multi-attribute sandbody identification method based on LightGBM effectively characterizes the distribution features of sandbodies.Compared to unselected attributes,the prediction results using selected attributes have higher vertical resolution and inter-well conformity,with the prediction accuracy for single wells reaching 80.77%,significantly improving the accuracy of sandbody boundary delineation.展开更多
Thunderstorm detection based on the Atmospheric Electric Field(AEF)has evolved from time-domain models to space-domain models.It is especially important to evaluate and determine the particularly Weather Attribute(WA)...Thunderstorm detection based on the Atmospheric Electric Field(AEF)has evolved from time-domain models to space-domain models.It is especially important to evaluate and determine the particularly Weather Attribute(WA),which is directly related to the detection reliability and authenticity.In this paper,a strategy is proposed to integrate three currently competitive WA's evaluation methods.First,a conventional evaluation method based on AEF statistical indicators is selected.Subsequent evaluation approaches include competing AEF-based predicted value intervals,and AEF classification based on fuzzy c-means.Different AEF attributes contribute to a more accurate AEF classification to different degrees.The resulting dynamic weighting applied to these attributes improves the classification accuracy.Each evaluation method is applied to evaluate the WA of a particular AEF,to obtain the corresponding evaluation score.The integration in the proposed strategy takes the form of a score accumulation.Different cumulative score levels correspond to different final WA results.Thunderstorm imaging is performed to visualize thunderstorm activities using those AEFs already evaluated to exhibit thunderstorm attributes.Empirical results confirm that the proposed strategy effectively and reliably images thunderstorms,with a 100%accuracy of WA evaluation.This is the first study to design an integrated thunderstorm detection strategy from a new perspective of WA evaluation,which provides promising solutions for a more reliable and flexible thunderstorm detection.展开更多
Conditional proxy re-encryption(CPRE)is an effective cryptographic primitive language that enhances the access control mechanism and makes the delegation of decryption permissions more granular,but most of the attribu...Conditional proxy re-encryption(CPRE)is an effective cryptographic primitive language that enhances the access control mechanism and makes the delegation of decryption permissions more granular,but most of the attribute-based conditional proxy re-encryption(AB-CPRE)schemes proposed so far do not take into account the importance of user attributes.A weighted attribute-based conditional proxy re-encryption(WAB-CPRE)scheme is thus designed to provide more precise decryption rights delegation.By introducing the concept of weight attributes,the quantity of system attributes managed by the server is reduced greatly.At the same time,a weighted tree structure is constructed to simplify the expression of access structure effectively.With conditional proxy re-encryption,large amounts of data and complex computations are outsourced to cloud servers,so the data owner(DO)can revoke the user’s decryption rights directly with minimal costs.The scheme proposed achieves security against chosen plaintext attacks(CPA).Experimental simulation results demonstrated that the decryption time is within 6–9 ms,and it has a significant reduction in communication and computation cost on the user side with better functionality compared to other related schemes,which enables users to access cloud data on devices with limited resources.展开更多
Attribute-based encryption(ABE)is a cryptographic framework that provides flexible access control by allowing encryption based on user attributes.ABE is widely applied in cloud storage,file sharing,e-Health,and digita...Attribute-based encryption(ABE)is a cryptographic framework that provides flexible access control by allowing encryption based on user attributes.ABE is widely applied in cloud storage,file sharing,e-Health,and digital rightsmanagement.ABE schemes rely on hard cryptographic assumptions such as pairings and others(pairingfree)to ensure their security against external and internal attacks.Internal attacks are carried out by authorized users who misuse their access to compromise security with potentially malicious intent.One common internal attack is the attribute collusion attack,in which users with different attribute keys collaborate to decrypt data they could not individually access.This paper focuses on the ciphertext-policy ABE(CP-ABE),a type of ABE where ciphertexts are produced with access policies.Our firstwork is to carry out the attribute collusion attack against several existing pairingfree CP-ABE schemes.As a main contribution,we introduce a novel attack,termed the anonymous key-leakage attack,concerning the context in which users could anonymously publish their secret keys associated with certain attributes on public platforms without the risk of detection.This kind of internal attack has not been defined or investigated in the literature.We then show that several prominent pairing-based CP-ABE schemes are vulnerable to this attack.We believe that this work will contribute to helping the community evaluate suitable CP-ABE schemes for secure deployment in real-life applications.展开更多
Attributed graph clustering plays a vital role in uncovering hidden network structures,but it presents significant challenges.In recent years,various models have been proposed to identify meaningful clusters by integr...Attributed graph clustering plays a vital role in uncovering hidden network structures,but it presents significant challenges.In recent years,various models have been proposed to identify meaningful clusters by integrating both structural and attribute-based information.However,these models often emphasize node proximities without adequately balancing the efficiency of clustering based on both structural and attribute data.Furthermore,they tend to neglect the critical fuzzy information inherent in attributed graph clusters.To address these issues,we introduce a new framework,Markov lumpability optimization,for efficient clustering of large-scale attributed graphs.Specifically,we define a lumped Markov chain on an attribute-augmented graph and introduce a new metric,Markov lumpability,to quantify the differences between the original and lumped Markov transition probability matrices.To minimize this measure,we propose a conjugate gradient projectionbased approach that ensures the partitioning closely aligns with the intrinsic structure of fuzzy clusters through conditional optimization.Extensive experiments on both synthetic and real-world datasets demonstrate the superior performance of the proposed framework compared to existing clustering algorithms.This framework has many potential applications,including dynamic community analysis of social networks,user profiling in recommendation systems,functional module identification in biological molecular networks,and financial risk control,offering a new paradigm for mining complex patterns in high-dimensional attributed graph data.展开更多
Constructing multi-dimensional hydrogen bond(H-bond)regulated single-molecule systems with multiemission remains a challenge.Herein,we report the design of a new excited-state intramolecular proton transfer(ESIPT)feat...Constructing multi-dimensional hydrogen bond(H-bond)regulated single-molecule systems with multiemission remains a challenge.Herein,we report the design of a new excited-state intramolecular proton transfer(ESIPT)featured chromophore(HBT-DPI)that shows flexible emission tunability via the multidimensional regulation of intra-and intermolecular H-bonds.The feature of switchable intramolecular Hbonds is induced via incorporating several hydrogen bond acceptors and donors into one single HBT-DPI molecule,allowing the“turn on/off”of ESIPT process by forming isomers with distinct intramolecular Hbonds configurations.In response to different external H-bonding environments,the obtained four types of crystal/cocrystals vary in the contents of isomers and the molecular packing modes,which are mainly guided by the intermolecular H-bonds,exhibiting non-emissive features or emissions ranging from green to orange.Utilizing the feature of intermolecular H-bond guided molecular packing,we demonstrate the utility of this fluorescent material for visualizing hydrophobic/hydrophilic areas on large-scale heterogeneous surfaces of modified poly(1,1-difluoroethylene)(PVDF)membranes and quantitatively estimating the surface hydrophobicity,providing a new approach for hydrophobicity/hydrophilicity monitoring and measurement.Overall,this study represents a new design strategy for constructing multi-dimensional hydrogen bond regulated ESIPT-based fluorescent materials that enable multiple emissions and unique applications.展开更多
Studies to enhance the management of electrical energy have gained considerable momentum in recent years. The question of how much energy will be needed in households is a pressing issue as it allows the management pl...Studies to enhance the management of electrical energy have gained considerable momentum in recent years. The question of how much energy will be needed in households is a pressing issue as it allows the management plan of the available resources at the power grids and consumer levels. A non-intrusive inference process can be adopted to predict the amount of energy required by appliances. In this study, an inference process of appliance consumption based on temporal and environmental factors used as a soft sensor is proposed. First, a study of the correlation between the electrical and environmental variables is presented. Then, a resampling process is applied to the initial data set to generate three other subsets of data. All the subsets were evaluated to deduce the adequate granularity for the prediction of the energy demand. Then, a cloud-assisted deep neural network model is designed to forecast short-term energy consumption in a residential area while preserving user privacy. The solution is applied to the consumption data of four appliances elected from a set of real household power data. The experiment results show that the proposed framework is effective for estimating consumption with convincing accuracy.展开更多
To break the limitations of the multi-dimensional(M-D)vibration isolation(VI)platforms with the Stewart-Gough design,such as strongly coupling motions,excessive friction in connections,heavy weight,and limited workspa...To break the limitations of the multi-dimensional(M-D)vibration isolation(VI)platforms with the Stewart-Gough design,such as strongly coupling motions,excessive friction in connections,heavy weight,and limited workspace,this study processes a novel platform integrated by a stiffness-adjustable origami spring sub-structure and a parallel mechanism.The origami-based stiffness-adjustable spring realizes low-frequency VI,and the parallel mechanism symmetry design realizes motions decoupling.In the origami-based sub-leg,the parallel-stack-assembly(PSA)design mechanism with two Miura origami configurations is proposed to generate a symmetrical negative stiffness property.Paired with a linear positive stiffness spring,the origami-based sub-leg has wide-amplitude-high-static-low-dynamic stiffness(WA-HSLDS)characteristics in one direction.Then,with construction of the parallel mechanism connected with origami-based sub-legs,an M-D VI platform is achieved,whose motions in the vertical direction and yaw direction are decoupled with the motions in the other directions.Based on the dynamic model and incremental harmonic balance(IHB)with the arc-length continuation method,appropriate structural parameters in the parallel mechanism part are figured out,and the accurate transmissibility in different directions is defined,which gives the parametric influencing investigations for realization of low-frequency VI performances.Finally,experiments are conducted to validate the accuracy and feasibility of the theoretical methods,and to demonstrate the performance of M-D low-frequency isolation with load-carrying capacity of the proposed VI platform.The integration of the origami into the parallel mechanism results in a compact,efficient,and flexible platform with nonlinear adjustability,offering new possibilities for lightweight M-D VI,and developing the practical applications in high-precision platforms in ocean and aerospace environments.展开更多
基金co-supported by the National Key R&D Program of China(No.2023YFB4704400)the Zhejiang Provincial Natural Science Foundation of China(No.LQ24F030012)the National Natural Science Foundation of China General Project(No.62373033)。
文摘A composite anti-disturbance predictive control strategy employing a Multi-dimensional Taylor Network(MTN)is presented for unmanned systems subject to time-delay and multi-source disturbances.First,the multi-source disturbances are addressed according to their specific characteristics as follows:(A)an MTN data-driven model,which is used for uncertainty description,is designed accompanied with the mechanism model to represent the unmanned systems;(B)an adaptive MTN filter is used to remove the influence of the internal disturbance;(C)an MTN disturbance observer is constructed to estimate and compensate for the influence of the external disturbance;(D)the Extended Kalman Filter(EKF)algorithm is utilized as the learning mechanism for MTNs.Second,to address the time-delay effect,a recursiveτstep-ahead MTN predictive model is designed utilizing recursive technology,aiming to mitigate the impact of time-delay,and the EKF algorithm is employed as its learning mechanism.Then,the MTN predictive control law is designed based on the quadratic performance index.By implementing the proposed composite controller to unmanned systems,simultaneous feedforward compensation and feedback suppression to the multi-source disturbances are conducted.Finally,the convergence of the MTN and the stability of the closed-loop system are established utilizing the Lyapunov theorem.Two exemplary applications of unmanned systems involving unmanned vehicle and rigid spacecraft are presented to validate the effectiveness of the proposed approach.
文摘Normal forms have a significant role in the theory of relational database normalization.The definitions of normal forms are established through the functional dependency(FD)relationship between a prime or nonprime attribute and a key.However,determining whether an attribute is a prime attribute is a nondeterministic polynomial-time complete(NP-complete)problem,making it intractable to determine if a relation scheme is in a specific normal form.While the prime attribute problem is generally NP-complete,there are cases where identifying prime attributes is not challenging.In a relation scheme R(U,F),we partition U into four distinct subsets based on where attributes in U appear in F:U_(1)(attributes only appearing on the left-hand side of FDs),U_(2)(attributes only appearing on the right-hand side of FDs),U_(3)(attributes appearing on both sides of FDs),and U_(4)(attributes not present in F).Next,we demonstrate the necessary and sufficient conditions for a key to be the unique key of a relation scheme.Subsequently,we illustrate the features of prime attributes in U_(3) and generalize the features of common prime attributes.The findings lay the groundwork for distinguishing between complex and simple cases in prime attribute identification,thereby deepening the understanding of this problem.
文摘The ancient tacit knowledge behind the logic system permeated the culture and promoted numerous impactful inventions throughout the history. Traditional Chinese medicine with its effectiveness should also have stemmed out from such logic system. This article aims to rearticulate the underlying lucid multi-dimensional logic system, which faded in obscurity only because of time-out loss of the mid-right concept. Retracing this past tacit but important concept could uncover a multi-dimensional system over a point relating to all matters while capturing the central core of the matter. The seemingly unmanageable multidimensional logic was strengthened by verification processes which affirmed its further extensions, and made up the language of the people, the concepts of yin-yang(阴阳), and the development of extensions of Ba Gua(八卦) derivatives, which furthered the interpretation of the space-time properties and Chinese medicine.
基金the financial support from the Guangxi Natural Science Foundation(grant no.2021GXNSFDA075012,2023GXNSFGA026002)National Natural Science Foundation of China(52104298,22075073,52362027,52462029)Fundamental Research Funds for the Central Universities(531107051077).
文摘Stress accumulation is a key factor leading to sodium storage performance deterioration for NiSe_(2)-based anodes.Therefore,inhibiting the concentrated local stress during the sodiataion/desodiation process is crucial for acquiring stable NiSe2-based materials for sodium-ion batteries(SIBs),Herein,a stress dissipation strategy driven by architecture engineering is proposed,which can achieve ultrafast and ultralong sodium storage properties.Different from the conventional sphere-like or rod-like architecture,the three-dimensional(3D)flower-like NiSe_(2)@C composite is delicately designed and assembled with onedimensional nanorods and carbon framework.More importantly,the fundamental mechanism of improved structure stability is unveiled by simulations and experimental results simultaneously.It demonstrates that this designed multidimensional flower-like architecture with dispersed nanorods can balance the structural mismatch,avoid concentrated local strain,and relax the internal stress,mainly induced by the unavoidable volume variation during the repeated conversion processes.Moreover,it can provide more Na^(+)-storage sites and multi-directional migration pathways,leading to a fast Na^(+)-migration channel with boosted reaction kinetic.As expected,it delivers superior rate performance(441 mA h g^(-1)at 5.0 A g^(-1))and long cycling stability(563 mA h g^(-1)at 1.0 A g^(-1)over 1000 cycles)for SIBs.This work provides useful insights for designing high-performance conversion-based anode materials for SIBs.
文摘This paper explores whole-process engineering consulting,including its application models in public buildings and elderly-friendly projects,such as service integration and whole lifecycle management.It also addresses the construction of multi-dimensional collaborative theoretical models,public space streamline organization,and other aspects,emphasizing the importance of multi-dimensional collaboration.Additionally,it highlights the role of talent cultivation and digital transformation in enhancing project efficiency.
基金supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(RS-2023-00238866)Korea government(MOE)(2024 government collaboration type training project[Information security field],No.2024 personal information protection-002).
文摘This study analyzes the risks of re-identification in Korean text data and proposes a secure,ethical approach to data anonymization.Following the‘Lee Luda’AI chatbot incident,concerns over data privacy have increased.The Personal Information Protection Commission of Korea conducted inspections of AI services,uncovering 850 cases of personal information in user input datasets,highlighting the need for pseudonymization standards.While current anonymization techniques remove personal data like names,phone numbers,and addresses,linguistic features such as writing habits and language-specific traits can still identify individuals when combined with other data.To address this,we analyzed 50,000 Korean text samples from the X platform,focusing on language-specific features for authorship attribution.Unlike English,Korean features flexible syntax,honorifics,syllabic and grapheme patterns,and referential terms.These linguistic characteristics were used to enhance re-identification accuracy.Our experiments combined five machine learning models,six stopword processing methods,and four morphological analyzers.By using a tokenizer that captures word frequency and order,and employing the LSTM model,OKT morphological analyzer,and stopword removal,we achieved the maximum authorship attributions accuracy of 90.51%.This demonstrates the significant role of Korean linguistic features in re-identification.The findings emphasize the risk of re-identification through language data and call for a re-evaluation of anonymization methods,urging the consideration of linguistic traits in anonymization beyond simply removing personal information.
基金supported by the Natural Science Foundation of China(Grant No.72571150)。
文摘Detecting overlapping communities in attributed networks remains a significant challenge due to the complexity of jointly modeling topological structure and node attributes,the unknown number of communities,and the need to capture nodes with multiple memberships.To address these issues,we propose a novel framework named density peaks clustering with neutrosophic C-means.First,we construct a consensus embedding by aligning structure-based and attribute-based representations using spectral decomposition and canonical correlation analysis.Then,an improved density peaks algorithm automatically estimates the number of communities and selects initial cluster centers based on a newly designed cluster strength metric.Finally,a neutrosophic C-means algorithm refines the community assignments,modeling uncertainty and overlap explicitly.Experimental results on synthetic and real-world networks demonstrate that the proposed method achieves superior performance in terms of detection accuracy,stability,and its ability to identify overlapping structures.
文摘The multi-dimensional interactive teaching model significantly enhances the effectiveness of college English instruction by emphasizing dynamic engagement between teachers and students,as well as among students themselves.This paper explores practical strategies for implementing this model,focusing on four key aspects:deepening teachers’understanding of the model through continuous learning,innovating interactive methods such as questioning techniques and practical activities,leveraging modern technology to integrate resources and track learning progress,and establishing a communication platform that centers on student participation.By adopting these approaches,the model fosters a student-centered classroom environment,improves comprehensive English application skills,and optimizes overall teaching quality.
基金supported by the National Natural Science Foundation of China under Grant 61972057Hunan Provincial Natural Science Foundation of China under Grant 2022JJ30623.
文摘Linguistic steganography(LS)aims to embed secret information into normal natural text for covert communication.It includes modification-based(MLS)and generation-based(GLS)methods.MLS often relies on limited manual rules,resulting in low embedding capacity,while GLS achieves higher embedding capacity through automatic text generation but typically ignores extraction efficiency.To address this,we propose a sentence attribute encodingbased MLS method that enhances extraction efficiency while maintaining strong performance.The proposed method designs a lightweight semantic attribute analyzer to encode sentence attributes for embedding secret information.When the attribute values of the cover sentence differ from the secret information to be embedded,a semantic attribute adjuster based on paraphrasing is used to automatically generate paraphrase sentences of the target attribute,thereby improving the problem of insufficient manual rules.During the extraction,secret information can be extracted solely by employing the semantic attribute analyzer,thereby eliminating the dependence on the paraphrasing generation model.Experimental results show that thismethod achieves an extraction speed of 1141.54 bits/sec,compared with the existing methods,it has remarkable advantages regarding extraction speed.Meanwhile,the stego text generated by thismethod respectively reaches 68.53,39.88,and 80.77 on BLEU,△PPL,and BERTScore.Compared with the existing methods,the text quality is effectively improved.
基金Sponsored by the Quality Engineering Project of Education Department of Anhui Province(2022jyxm671)Research Team Project of Anhui Xinhua University(kytd202202)+1 种基金Key Project of Scientific Research(Natural Science)of Higher Education Institutions in Anhui Province(2022AH051861)Teaching Reform Research and Practice Quality Engineering Project of Anhui Xinhua University(2024jy035).
文摘During the critical transformation period of landscape architecture major after the adjustment of disciplinary structure and the changes in market demand,private colleges and universities,as important places for cultivating local talents,have pain points such as uneven quality of teachers and students and weak innovation and practice.The practice system with“multi-dimensional Integration”integrates four dimensions:interdisciplinary integration,spatial and temporal intersection,historical inheritance,and behavioral activity,deepens the disciplinary connotation,and integrates the three elements of nature,humanity,and technology,aiming to provide a new path for private colleges and universities to cultivate application-oriented and compound talents with innovative capabilities.In terms of optimizing talent cultivation and adapting to industry changes,this system provides thinking and reference for landscape architecture major,helping the major reshape its core competitiveness and promoting educational innovation and industry development.
基金supported by National Natural Science Foundation of China(No.62102449).
文摘Security attributes are the premise and foundation for implementing Attribute-Based Access Control(ABAC)mechanisms.However,when dealing with massive volumes of unstructured text big data resources,the current attribute management methods based on manual extraction face several issues,such as high costs for attribute extraction,long processing times,unstable accuracy,and poor scalability.To address these problems,this paper proposes an attribute mining technology for access control institutions based on hybrid capsule networks.This technology leverages transfer learning ideas,utilizing Bidirectional Encoder Representations from Transformers(BERT)pre-trained language models to achieve vectorization of unstructured text data resources.Furthermore,we have designed a novel end-to-end parallel hybrid network structure,where the parallel networks handle global and local information features of the text that they excel at,respectively.By employing techniques such as attention mechanisms,capsule networks,and dynamic routing,effective mining of security attributes for access control resources has been achieved.Finally,we evaluated the performance level of the proposed attribute mining method for access control institutions through experiments on the medical referral text resource dataset.The experimental results show that,compared with baseline algorithms,our method adopts a parallel network structure that can better balance global and local feature information,resulting in improved overall performance.Specifically,it achieves a comprehensive performance enhancement of 2.06%to 8.18%in the F1 score metric.Therefore,this technology can effectively provide attribute support for access control of unstructured text big data resources.
基金supported by the National Natural Science Foundation of China(72101025,72271049),the Interdisciplinary Research Project for Young Teachers of USTB(Fundamental Research Funds for the Central Universities,FRF-IDRY-24-024)the Hebei Natural Science Foundation(F2023501011)+1 种基金the Fundamental Research Funds for the Central Universities(FRF-TP-20-073A1)the R&D Program of Beijing Municipal Education Commission(KM202411232015).
文摘This paper proposes a reliability evaluation model for a multi-dimensional network system,which has potential to be applied to the internet of things or other practical networks.A multi-dimensional network system with one source element and multiple sink elements is considered first.Each element can con-nect with other elements within a stochastic connection ranges.The system is regarded as successful as long as the source ele-ment remains connected with all sink elements.An importance measure is proposed to evaluate the performance of non-source elements.Furthermore,to calculate the system reliability and the element importance measure,a multi-valued decision diagram based approach is structured and its complexity is analyzed.Finally,a numerical example about the signal transfer station system is illustrated to analyze the system reliability and the ele-ment importance measure.
基金co-funded by the China National Nuclear Corporation-State Key Laboratory of Nuclear Resources and Environment(East ChinaUniversity of Technology)Joint Innovation Fund Project(No.2023NRE-LH-08)the Natural Science Foundation of Jiangxi Province,China(No.20252BAC240270)+1 种基金the Funding of National Key Laboratory of Uranium Resources Exploration-Mining and Nuclear Remote Sensing(2025QZ-YZZ-08)the National Major Science and Technology Project on Deep Earth of China(No.2024ZD 1003300)。
文摘Seismic attributes encapsulate substantial reservoir characterization information and can effectively support reservoir prediction.Given the high-dimensional nonlinear between sandbodies and seismic attributes,this study employs the RFECV method for seismic attribute selection,inputting the optimized attributes into a LightGBM model to enhance spatial delineation of sandbody identification.By constructing training datasets based on optimized seismic attributes and well logs,followed by class imbalance correction as input variables for machine learning models,with sandbody probability as the output variable,and employing grid search to optimize model parameters,a high-precision sandbody prediction model was established.Taking the 3D seismic data of Block F3 in the North Sea of Holland as an example,this method successfully depicted the three-dimensional spatial distribution of target formation sandstones.The results indicate that even under strong noise conditions,the multi-attribute sandbody identification method based on LightGBM effectively characterizes the distribution features of sandbodies.Compared to unselected attributes,the prediction results using selected attributes have higher vertical resolution and inter-well conformity,with the prediction accuracy for single wells reaching 80.77%,significantly improving the accuracy of sandbody boundary delineation.
基金supported in part by the National Natural Science Foundation of China under Grant 62171228in part by the National Key R&D Program of China under Grant 2021YFE0105500in part by the Program of China Scholarship Council under Grant 202209040027。
文摘Thunderstorm detection based on the Atmospheric Electric Field(AEF)has evolved from time-domain models to space-domain models.It is especially important to evaluate and determine the particularly Weather Attribute(WA),which is directly related to the detection reliability and authenticity.In this paper,a strategy is proposed to integrate three currently competitive WA's evaluation methods.First,a conventional evaluation method based on AEF statistical indicators is selected.Subsequent evaluation approaches include competing AEF-based predicted value intervals,and AEF classification based on fuzzy c-means.Different AEF attributes contribute to a more accurate AEF classification to different degrees.The resulting dynamic weighting applied to these attributes improves the classification accuracy.Each evaluation method is applied to evaluate the WA of a particular AEF,to obtain the corresponding evaluation score.The integration in the proposed strategy takes the form of a score accumulation.Different cumulative score levels correspond to different final WA results.Thunderstorm imaging is performed to visualize thunderstorm activities using those AEFs already evaluated to exhibit thunderstorm attributes.Empirical results confirm that the proposed strategy effectively and reliably images thunderstorms,with a 100%accuracy of WA evaluation.This is the first study to design an integrated thunderstorm detection strategy from a new perspective of WA evaluation,which provides promising solutions for a more reliable and flexible thunderstorm detection.
基金Programs for Science and Technology Development of Henan Province,grant number 242102210152The Fundamental Research Funds for the Universities of Henan Province,grant number NSFRF240620+1 种基金Key Scientific Research Project of Henan Higher Education Institutions,grant number 24A520015Henan Key Laboratory of Network Cryptography Technology,grant number LNCT2022-A11.
文摘Conditional proxy re-encryption(CPRE)is an effective cryptographic primitive language that enhances the access control mechanism and makes the delegation of decryption permissions more granular,but most of the attribute-based conditional proxy re-encryption(AB-CPRE)schemes proposed so far do not take into account the importance of user attributes.A weighted attribute-based conditional proxy re-encryption(WAB-CPRE)scheme is thus designed to provide more precise decryption rights delegation.By introducing the concept of weight attributes,the quantity of system attributes managed by the server is reduced greatly.At the same time,a weighted tree structure is constructed to simplify the expression of access structure effectively.With conditional proxy re-encryption,large amounts of data and complex computations are outsourced to cloud servers,so the data owner(DO)can revoke the user’s decryption rights directly with minimal costs.The scheme proposed achieves security against chosen plaintext attacks(CPA).Experimental simulation results demonstrated that the decryption time is within 6–9 ms,and it has a significant reduction in communication and computation cost on the user side with better functionality compared to other related schemes,which enables users to access cloud data on devices with limited resources.
文摘Attribute-based encryption(ABE)is a cryptographic framework that provides flexible access control by allowing encryption based on user attributes.ABE is widely applied in cloud storage,file sharing,e-Health,and digital rightsmanagement.ABE schemes rely on hard cryptographic assumptions such as pairings and others(pairingfree)to ensure their security against external and internal attacks.Internal attacks are carried out by authorized users who misuse their access to compromise security with potentially malicious intent.One common internal attack is the attribute collusion attack,in which users with different attribute keys collaborate to decrypt data they could not individually access.This paper focuses on the ciphertext-policy ABE(CP-ABE),a type of ABE where ciphertexts are produced with access policies.Our firstwork is to carry out the attribute collusion attack against several existing pairingfree CP-ABE schemes.As a main contribution,we introduce a novel attack,termed the anonymous key-leakage attack,concerning the context in which users could anonymously publish their secret keys associated with certain attributes on public platforms without the risk of detection.This kind of internal attack has not been defined or investigated in the literature.We then show that several prominent pairing-based CP-ABE schemes are vulnerable to this attack.We believe that this work will contribute to helping the community evaluate suitable CP-ABE schemes for secure deployment in real-life applications.
基金supported by the National Natural Science Foundation of China(Grant No.72571150)Beijing Natural Science Foundation(Grant No.9182015)。
文摘Attributed graph clustering plays a vital role in uncovering hidden network structures,but it presents significant challenges.In recent years,various models have been proposed to identify meaningful clusters by integrating both structural and attribute-based information.However,these models often emphasize node proximities without adequately balancing the efficiency of clustering based on both structural and attribute data.Furthermore,they tend to neglect the critical fuzzy information inherent in attributed graph clusters.To address these issues,we introduce a new framework,Markov lumpability optimization,for efficient clustering of large-scale attributed graphs.Specifically,we define a lumped Markov chain on an attribute-augmented graph and introduce a new metric,Markov lumpability,to quantify the differences between the original and lumped Markov transition probability matrices.To minimize this measure,we propose a conjugate gradient projectionbased approach that ensures the partitioning closely aligns with the intrinsic structure of fuzzy clusters through conditional optimization.Extensive experiments on both synthetic and real-world datasets demonstrate the superior performance of the proposed framework compared to existing clustering algorithms.This framework has many potential applications,including dynamic community analysis of social networks,user profiling in recommendation systems,functional module identification in biological molecular networks,and financial risk control,offering a new paradigm for mining complex patterns in high-dimensional attributed graph data.
基金supported by the National Key R&D Program of China(No.2021YFC2103600)the National Natural Science Foundation of China(Nos.21878156,21978131,22275085,and 22278224)+2 种基金the Natural Science Foundation of Jiangsu Province(Nos.BK20200089 and BK20200691)the Project of Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)the State Key Laboratory of Materials-Oriented Chemical Engineering(No.KL21-08).
文摘Constructing multi-dimensional hydrogen bond(H-bond)regulated single-molecule systems with multiemission remains a challenge.Herein,we report the design of a new excited-state intramolecular proton transfer(ESIPT)featured chromophore(HBT-DPI)that shows flexible emission tunability via the multidimensional regulation of intra-and intermolecular H-bonds.The feature of switchable intramolecular Hbonds is induced via incorporating several hydrogen bond acceptors and donors into one single HBT-DPI molecule,allowing the“turn on/off”of ESIPT process by forming isomers with distinct intramolecular Hbonds configurations.In response to different external H-bonding environments,the obtained four types of crystal/cocrystals vary in the contents of isomers and the molecular packing modes,which are mainly guided by the intermolecular H-bonds,exhibiting non-emissive features or emissions ranging from green to orange.Utilizing the feature of intermolecular H-bond guided molecular packing,we demonstrate the utility of this fluorescent material for visualizing hydrophobic/hydrophilic areas on large-scale heterogeneous surfaces of modified poly(1,1-difluoroethylene)(PVDF)membranes and quantitatively estimating the surface hydrophobicity,providing a new approach for hydrophobicity/hydrophilicity monitoring and measurement.Overall,this study represents a new design strategy for constructing multi-dimensional hydrogen bond regulated ESIPT-based fluorescent materials that enable multiple emissions and unique applications.
基金funded by NARI Group’s Independent Project of China(Grant No.524609230125)the Foundation of NARI-TECH Nanjing Control System Ltd.of China(Grant No.0914202403120020).
文摘Studies to enhance the management of electrical energy have gained considerable momentum in recent years. The question of how much energy will be needed in households is a pressing issue as it allows the management plan of the available resources at the power grids and consumer levels. A non-intrusive inference process can be adopted to predict the amount of energy required by appliances. In this study, an inference process of appliance consumption based on temporal and environmental factors used as a soft sensor is proposed. First, a study of the correlation between the electrical and environmental variables is presented. Then, a resampling process is applied to the initial data set to generate three other subsets of data. All the subsets were evaluated to deduce the adequate granularity for the prediction of the energy demand. Then, a cloud-assisted deep neural network model is designed to forecast short-term energy consumption in a residential area while preserving user privacy. The solution is applied to the consumption data of four appliances elected from a set of real household power data. The experiment results show that the proposed framework is effective for estimating consumption with convincing accuracy.
基金Project supported by the National Natural Science Foundation of China(Nos.U2441202,12372043,and 12372022)the Fundamental Research Funds for Central Universities。
文摘To break the limitations of the multi-dimensional(M-D)vibration isolation(VI)platforms with the Stewart-Gough design,such as strongly coupling motions,excessive friction in connections,heavy weight,and limited workspace,this study processes a novel platform integrated by a stiffness-adjustable origami spring sub-structure and a parallel mechanism.The origami-based stiffness-adjustable spring realizes low-frequency VI,and the parallel mechanism symmetry design realizes motions decoupling.In the origami-based sub-leg,the parallel-stack-assembly(PSA)design mechanism with two Miura origami configurations is proposed to generate a symmetrical negative stiffness property.Paired with a linear positive stiffness spring,the origami-based sub-leg has wide-amplitude-high-static-low-dynamic stiffness(WA-HSLDS)characteristics in one direction.Then,with construction of the parallel mechanism connected with origami-based sub-legs,an M-D VI platform is achieved,whose motions in the vertical direction and yaw direction are decoupled with the motions in the other directions.Based on the dynamic model and incremental harmonic balance(IHB)with the arc-length continuation method,appropriate structural parameters in the parallel mechanism part are figured out,and the accurate transmissibility in different directions is defined,which gives the parametric influencing investigations for realization of low-frequency VI performances.Finally,experiments are conducted to validate the accuracy and feasibility of the theoretical methods,and to demonstrate the performance of M-D low-frequency isolation with load-carrying capacity of the proposed VI platform.The integration of the origami into the parallel mechanism results in a compact,efficient,and flexible platform with nonlinear adjustability,offering new possibilities for lightweight M-D VI,and developing the practical applications in high-precision platforms in ocean and aerospace environments.
