Privacy-Preserving Multi-Keyword Fuzzy Adjacency Search Strategy for Encrypted Graph in Cloud Environment

In a cloud environment,outsourced graph data is widely used in companies,enterprises,medical institutions,and so on.Data owners and users can save costs and improve efficiency by storing large amounts of graph data on cloud servers.Servers on cloud platforms usually have some subjective or objective attacks,which make the outsourced graph data in an insecure state.The issue of privacy data protection has become an important obstacle to data sharing and usage.How to query outsourcing graph data safely and effectively has become the focus of research.Adjacency query is a basic and frequently used operation in graph,and it will effectively promote the query range and query ability if multi-keyword fuzzy search can be supported at the same time.This work proposes to protect the privacy information of outsourcing graph data by encryption,mainly studies the problem of multi-keyword fuzzy adjacency query,and puts forward a solution.In our scheme,we use the Bloom filter and encryption mechanism to build a secure index and query token,and adjacency queries are implemented through indexes and query tokens on the cloud server.Our proposed scheme is proved by formal analysis,and the performance and effectiveness of the scheme are illustrated by experimental analysis.The research results of this work will provide solid theoretical and technical support for the further popularization and application of encrypted graph data processing technology.

A Graph with Adaptive AdjacencyMatrix for Relation Extraction

The relation is a semantic expression relevant to two named entities in a sentence.Since a sentence usually contains several named entities,it is essential to learn a structured sentence representation that encodes dependency information specific to the two named entities.In related work,graph convolutional neural networks are widely adopted to learn semantic dependencies,where a dependency tree initializes the adjacency matrix.However,this approach has two main issues.First,parsing a sentence heavily relies on external toolkits,which can be errorprone.Second,the dependency tree only encodes the syntactical structure of a sentence,which may not align with the relational semantic expression.In this paper,we propose an automatic graph learningmethod to autonomously learn a sentence’s structural information.Instead of using a fixed adjacency matrix initialized by a dependency tree,we introduce an Adaptive Adjacency Matrix to encode the semantic dependency between tokens.The elements of thismatrix are dynamically learned during the training process and optimized by task-relevant learning objectives,enabling the construction of task-relevant semantic dependencies within a sentence.Our model demonstrates superior performance on the TACRED and SemEval 2010 datasets,surpassing previous works by 1.3%and 0.8%,respectively.These experimental results show that our model excels in the relation extraction task,outperforming prior models.

How Do the Participant Relations Affect Adjacency Pairs?

This paper will briefly discuss the issue of how different participant relations affect adjacency pairs in conversation analysis.In terms of the affects or influence on adjacency pairs,this article only places its focus on the ways how the first pair part (FPP) and second pair part (SPP) in conversation are relevant to each other.As for the final result,the data back up such conclusions:in conversation between acquaintance /friends,family members,and as such,the relevance are built up either directly or indirectly.However,in conversation between strangers,this relevance seems to be constructed only directly.

Structural Synthesis of Compliant Metamorphic Mechanisms Based on Adjacency Matrix Operations

A compliant metamorphic mechanism attributes to a new type of metamorphic mechanisms evolved from rigid metamorphic mechanisms. The structural characteristics and representations of a compliant metamorphic mechanism are different from its rigid counterparts, so does the structural synthesis method. In order to carry out its structural synthesis, a constraint graph representation for topological structure of compliant metamorphic mechanisms is introduced, which can not only represent the structure of a compliant metamorphic mechanism, but also describe the characteristics of its links and kinematic pairs. An adjacency matrix representation of the link relationships in a compliant metamorphic mechanism is presented according to the constraint graph. Then, a method for structural synthesis of compliant metamorphic mechanisms is proposed based on the adjacency matrix operations. The operation rules and the operation procedures of adjacency matrices are described through synthesis of the initial configurations composed of s＋1 links from an s-link mechanism （the final configuration）. The method is demonstrated by synthesizing all the possible four-link compliant metamorphic mechanisms that can transform into a three-link mechanism through combining two of its links. Sixty-five adjacency matrices are obtained in the synthesis, each of which corresponds to a compliant metamorphic mechanism having four links. Therefore, the effectiveness of the method is validated by a specific compliant metamorphic mechanism corresponding to one of the sixty-five adjacency matrices. The structural synthesis method is put into practice as a fully compliant metamorphic hand is presented based on the synthesis results. The synthesis method has the advantages of simple operation rules, clear geometric meanings, ease of programming with matrix operation, and provides an effective method for structural synthesis of compliant metamorphic mechanisms and can be used in the design of new compliant metamorphic mechanisms.

Configuration Analysis of Metamorphic Mechanisms Based on Extended Adjacency Matrix Operations

The adjacency matrix operations,which connect with configuration transformation correspondingly,can be used for analysis of configuration transformation of metamorphic mechanisms and the corresponding algorithm can easily be simulated by computer.But the adjacency matrix based on monochrome topological graph is not suitable for the topological representation of mechanisms with multiple joints.The method of adjacency matrix operations has its own limitations for analysis of configuration transformation of metamorphic mechanisms because it can only be used in the topological representation of mechanisms with single joints.In order to overcome the drawback of the adjacency matrix,a kind of new matrix named as extended adjacency matrix is proposed to express topological structures of all mechanisms.The extended adjacency matrix is not only suitable for the topological representation of mechanisms with single joints,but also can be used in that of mechanisms with multiple joints.On this basis,a method of matrix operations based on the extended adjacency matrix is proposed to analyze the configuration transformation of metamorphic mechanisms.The method is not only suitable for configuration analysis of metamorphic mechanisms with single joints as well as metamorphic mechanisms with multiple joints.The method is evaluated by calculating two examples representing metamorphic mechanisms with single joint and multiple joints respectively.It can be concluded that the method is effective and correct for analysis of configuration transformation of all metamorphic mechanisms.The proposed method is simple and easy to be achieved by computer programming.It provides a basis for structural synthesis of all metamorphic mechanisms.

Drawing Weighted Directed Graph from It's Adjacency Matrix

This paper proposes an algorithm for building weighted directed graph, defmes the weighted directed relationship matrix of the graph, and describes algorithm implementation using this matrix. Based on this algorithm, an effective way for building and drawing weighted directed graphs is presented, forming a foundation for visual implementation of the algorithm in the graph theory.

Teaching Fillers,Discourse Markers and Adjacency Pairs to College Students

Speaking has long been underestimated in College English education,compared with reading,writing and listening.Even In universities where spoken courses are provided,verbal filler and discourse markers which vastly exist in native speaker'scorpora are rarely found in these prescribed spoken course books.For the teaching of adjacency pairs,which are always one ofthe focuses in teaching conversation skills in College English spoken program,students are required to make up a new one basedon the given scenario after they have memorized model dialogues.Unfortunately,students always experience pragmatic difficultywhen they interact with people in the real world if they are guided by this approach.This article suggests a triangle which is com-posed of exposure,instruction and practice to teach verbal filler,discourse markers and adjacency pairs.This triangle combinesboth direct approach and indirect approach.Furthermore,in spoken program,English teachers can adapt spoken course books tointegrate features of authentic conversations.

A Method for Generating Contour Tree Based on Voronoi Interior Adjacency

A contour tree is a good graphical tool for representing the spatial relations of contour lines and has many applications in map generalization, map annotation, terrain analysis, etc. A new method for generating contour trees by introducing a Voronoi based interior adjacency concept is proposed in this paper. The immediate interior adjacency set is employed to identify all of the children contours of each contour without contour elevations. It has advantages over existing methods such as the geometric method and the region growing based method.

A Layered Zone Routing Algorithm in Ad Hoc Network Based on Matrix of Adjacency Connection

The hybrid routing protocol has received more attention recently than the proactive and the reactive, especially for large-scale and highly dynamic connection,in mobile ad hoc network. A crucial reason is that zone-layered is being utilized in the complex systems.A hybrid routing algorithm which is layered zone based on adjacency connection(LZBAC) is put forward under the background of a few members in network with steady position and link. The algorithm modifies storage structure of nodes and improves routing mechanism. The theoretical analysis and simulation testing testify that the algorithm costs shorter time of route finding and less delay than others.

Using adjacency matrix to explore remarkable associations in big and small mineral data

Data exploration,usually the first step in data analysis,is a useful method to tackle challenges caused by big geoscience data.It conducts quick analysis of data,investigates the patterns,and generates/refines research questions to guide advanced statistics and machine learning algorithms.The background of this work is the open mineral data provided by several sources,and the focus is different types of associations in mineral properties and occurrences.Researchers in mineralogy have been applying different techniques for exploring such associations.Although the explored associations can lead to new scientific insights that contribute to crystallography,mineralogy,and geochemistry,the exploration process is often daunting due to the wide range and complexity of factors involved.In this study,our purpose is implementing a visualization tool based on the adjacency matrix for a variety of datasets and testing its utility for quick exploration of association patterns in mineral data.Algorithms,software packages,and use cases have been developed to process a variety of mineral data.The results demonstrate the efficiency of adjacency matrix in real-world usage.All the developed works of this study are open source and open access.

Retrieval of high spatial resolution mountainous land surface temperature considering topographic and adjacency effects

Land surface temperature(LST) is a key parameter reflecting the interaction between land and atmosphere. Currently,thermal infrared(TIR) quantitative remote sensing technology is the only means to obtain large-scale, high spatial resolution LST. Accurately retrieving high spatial resolution mountainous LST(MLST) plays an important role in the study of mountain climate change. The complex terrain and strong spatial heterogeneity in mountainous areas change the geometric relationship between the surface and satellite sensors, affecting the radiation received by the sensors, and rendering the assumption of planar parallelism invalid. In this study, considering the influence of complex terrain in mountainous areas on atmospheric downward radiation and the thermal radiation contribution of adjacent pixels, a mountainous TIR radiative transfer model based on the sky view factor was developed. Combining with the atmospheric radiative transfer model MODTRAN 5.2, a nonlinear generalized split-window algorithm suitable for high spatial resolution MLST retrieval was constructed and applied to Landsat-9 TIRS-2satellite TIR remote sensing data. The analysis results indicate that neglecting the topographic and adjacency effects would lead to significant discrepancies in LST retrieval, with simulated data showing LST differences of up to 2.5 K. Furthermore, due to the lack of measured MLST in the field, the MLST accuracy obtained by this retrieval method was indirectly validated using the currently recognized highest-accuracy forward 3D radiative transfer model DART. The MLST and emissivity were input into the DART model to simulate the brightness temperature at the top of the atmosphere(TOA) of Landsat-9 band 10, and compared with the brightness temperature at TOA of Landsat-9 band 10. The RMSE(Root Mean Square Error) for the two subregions was0.50 and 0.61 K, respectively, indicating that the method proposed can retrieve high-precision MLST.

Revealing connectivity in residential Architecture: An algorithmic approach to extracting adjacency matrices from floor plans

In today's world, various approaches and parameters exist for designing a plan and determining its spatial, placement. Hence, various modes for identifying crucial locations can be explored when an architectural plan is designed in different dimensions. While designing all these modes takes considerable time, there are numerous potential applications for artificial intelligence (AI) in this domain. This study aims to compute and use an adjacency matrix to generate architectural residential plans. Additionally, it develops a plan generation algorithm in Rhinoceros software, utilizing the Grasshopper plugin to create a dataset of architectural plans. In the following step, the data was entered into a neural network to identify the architectural plan's type, furniture, icons, and use of spaces, which was achieved using YOLOv4, EfficientDet, YOLOv5, DetectoRS, and RetinaNet. The algorithm's execution, testing, and training were conducted using Darknet and PyTorch. The research dataset comprises 12,000 plans, with 70% employed in the training phase and 30% in the testing phase. The network was appropriately trained practically and precisely in relation to an average precision (AP) resulting of 91.50%. After detecting the types of space use, the main research algorithm has been designed and coded, which includes determining the adjacency matrix of architectural plan spaces in seven stages. All research processes were conducted in Python, including dataset preparation, network object detection, and adjacency matrix algorithm design. Finally, the adjacency matrix is given to the input of the proposed plan generator network, which consequently, based on the resulting adjacency, obtains different placement modes for spaces and furniture.

Adjacency Preserving Bijection Maps of Hermitian Matrices over any Division Ring with an Involution

Let D be any division ring with an involution,Hn （D） be the space of all n × n hermitian matrices over D. Two hermitian matrices A and B are said to be adjacent if rank（A - B） = 1. It is proved that if φ is a bijective map from Hn（D）（n ≥ 2） to itself such that φ preserves the adjacency, then φ^-1 also preserves the adjacency. Moreover, if Hn（D） ≠J3（F2）, then φ preserves the arithmetic distance. Thus, an open problem posed by Wan Zhe-Xian is answered for geometry of symmetric and hermitian matrices.

ADJACENCY PRESERVING MAPS ON THE SPACE OF SELF-ADJOINT OPERATORS

The authors extend Hua’s fundamental theorem of the geometry of Hermitian matri- ces to the in?nite-dimensional case. An application to characterizing the corresponding Jordan ring automorphism is also presented.

The Adjacency and Signless Laplacian Spectra of Cored Hypergraphs and Power Hypergraphs

In this paper,we study the adjacency and signless Laplacian tensors of cored hypergraphs and power hypergraphs.We investigate the properties of their adjacency and signless Laplacian H-eigenvalues.Especially,we find out the largest H-eigenvalues of adjacency and signless Laplacian tensors for uniform squids.We also compute the H-spectra of sunflowers and some numerical results are reported for the H-spectra.

Least H-eigenvalue of adjacency tensor of hypergraphs with cut vertices

Let G be a connected hypergraph with even uniformity,which contains cut vertices.Then G is the coalescence of two nontrivial connected sub-hypergraphs(called branches)at a cut vertex.Let A(G)be the adjacency tensor of G.The least H-eigenvalue of A(G)refers to the least real eigenvalue of A(G)associated with a real eigenvector.In this paper,we obtain a perturbation result on the least H-eigenvalue of A(G)when a branch of G attached at one vertex is relocated to another vertex,and characterize the unique hypergraph whose least H-eigenvalue attains the minimum among all hypergraphs in a certain class of hypergraphs which contain a fixed connected hypergraph.

Hermitian Adjacency Spectrum of Cayley Digraphs over Dihedral Group

We first study the spectrum of Hermitian adjacency matrix(H-spectrum)of Cayley digraphs X(D 2n,S)on dihedral group D2n with|S|=3.Then we show that all Cayley digraphs X(D2P,S)with|S|=3 and p odd prime are Cay-DS,namely,for any Cayley digraph X(D2P,T),X(D2P,T)and X(D2P,S)having the same H-spectrum implies that they are isomorphic.

The Adjacency Codes of the First Yellow Graphs

The authors study the binary codes spanned by the adjacency matrices of the strongly regular graphs(SRGs)on at most two hundred vertices whose existence is unknown.The authors show that in length less than one hundred they cannot be cyclic,except for the exceptions of the SRGs of parameters(85,42,20,21)and(96,60,38,36).In particular,the adjacency code of a(85,42,20,21)is the zero-sum code.In the range[100,200]the authors find 29 SRGs that could possibly have a cyclic adjacency code.

m, argest adjacency, signless Laplacian, and Laplacian H-eigenvalues of loose paths

We investigate k-uniform loose paths. We show that the largest H- eigenvalues of their adjacency tensors, Laplacian tensors, and signless Laplacian tensors are computable. For a k-uniform loose path with length l≥ 3, we show that the largest H-eigenvalue of its adjacency tensor is （（1 ＋ √-5）/2）2/k when = 3 and ）λ（A） = 31/k when g = 4, respectively. For the case of l ≥ 5, we tighten the existing upper bound 2. We also show that the largest H-eigenvalue of its signless Laplacian tensor lies in the interval （2, 3） when l≥ 5. Finally, we investigate the largest H-eigenvalue of its Laplacian tensor when k is even and we tighten the upper bound 4.

AFSTGCN:Prediction for multivariate time series using an adaptive fused spatial-temporal graph convolutional network

The prediction for Multivariate Time Series(MTS)explores the interrelationships among variables at historical moments,extracts their relevant characteristics,and is widely used in finance,weather,complex industries and other fields.Furthermore,it is important to construct a digital twin system.However,existing methods do not take full advantage of the potential properties of variables,which results in poor predicted accuracy.In this paper,we propose the Adaptive Fused Spatial-Temporal Graph Convolutional Network(AFSTGCN).First,to address the problem of the unknown spatial-temporal structure,we construct the Adaptive Fused Spatial-Temporal Graph(AFSTG)layer.Specifically,we fuse the spatial-temporal graph based on the interrelationship of spatial graphs.Simultaneously,we construct the adaptive adjacency matrix of the spatial-temporal graph using node embedding methods.Subsequently,to overcome the insufficient extraction of disordered correlation features,we construct the Adaptive Fused Spatial-Temporal Graph Convolutional(AFSTGC)module.The module forces the reordering of disordered temporal,spatial and spatial-temporal dependencies into rule-like data.AFSTGCN dynamically and synchronously acquires potential temporal,spatial and spatial-temporal correlations,thereby fully extracting rich hierarchical feature information to enhance the predicted accuracy.Experiments on different types of MTS datasets demonstrate that the model achieves state-of-the-art single-step and multi-step performance compared with eight other deep learning models.