Cross-Domain Authentication Scheme Based on Blockchain and Consistent Hash Algorithm for System-Wide Information Management

System-wide information management(SWIM)is a complex distributed information transfer and sharing system for the next generation of Air Transportation System(ATS).In response to the growing volume of civil aviation air operations,users accessing different authentication domains in the SWIM system have problems with the validity,security,and privacy of SWIM-shared data.In order to solve these problems,this paper proposes a SWIM crossdomain authentication scheme based on a consistent hashing algorithm on consortium blockchain and designs a blockchain certificate format for SWIM cross-domain authentication.The scheme uses a consistent hash algorithm with virtual nodes in combination with a cluster of authentication centers in the SWIM consortium blockchain architecture to synchronize the user’s authentication mapping relationships between authentication domains.The virtual authentication nodes are mapped separately using different services provided by SWIM to guarantee the partitioning of the consistent hash ring on the consortium blockchain.According to the dynamic change of user’s authentication requests,the nodes of virtual service authentication can be added and deleted to realize the dynamic load balancing of cross-domain authentication of different services.Security analysis shows that this protocol can resist network attacks such as man-in-the-middle attacks,replay attacks,and Sybil attacks.Experiments show that this scheme can reduce the redundant authentication operations of identity information and solve the problems of traditional cross-domain authentication with single-point collapse,difficulty in expansion,and uneven load.At the same time,it has better security of information storage and can realize the cross-domain authentication requirements of SWIM users with low communication costs and system overhead.KEYWORDS System-wide information management(SWIM);consortium blockchain;consistent hash;cross-domain authentication;load balancing.

A Consistent Mistake in Remote Sensing Images’Classification Literature

Recently,the convolutional neural network(CNN)has been dom-inant in studies on interpreting remote sensing images(RSI).However,it appears that training optimization strategies have received less attention in relevant research.To evaluate this problem,the author proposes a novel algo-rithm named the Fast Training CNN(FST-CNN).To verify the algorithm’s effectiveness,twenty methods,including six classic models and thirty archi-tectures from previous studies,are included in a performance comparison.The overall accuracy(OA)trained by the FST-CNN algorithm on the same model architecture and dataset is treated as an evaluation baseline.Results show that there is a maximal OA gap of 8.35%between the FST-CNN and those methods in the literature,which means a 10%margin in performance.Meanwhile,all those complex roadmaps,e.g.,deep feature fusion,model combination,model ensembles,and human feature engineering,are not as effective as expected.It reveals that there was systemic suboptimal perfor-mance in the previous studies.Most of the CNN-based methods proposed in the previous studies show a consistent mistake,which has made the model’s accuracy lower than its potential value.The most important reasons seem to be the inappropriate training strategy and the shift in data distribution introduced by data augmentation(DA).As a result,most of the performance evaluation was conducted based on an inaccurate,suboptimal,and unfair result.It has made most of the previous research findings questionable to some extent.However,all these confusing results also exactly demonstrate the effectiveness of FST-CNN.This novel algorithm is model-agnostic and can be employed on any image classification model to potentially boost performance.In addition,the results also show that a standardized training strategy is indeed very meaningful for the research tasks of the RSI-SC.

Consistent and Specific Multi-View Functional Brain Networks Fusion for Autism Spectrum Disorder Diagnosis

Functional brain networks (FBN) based on resting-state functional magnetic resonance imaging (rs-fMRI) have become an important tool for exploring underlying organization patterns in the brain, which can provide an objective basis for brain disorders such as autistic spectrum disorder (ASD). Due to its importance, researchers have proposed a number of FBN estimation methods. However, most existing methods only model a type of functional connection relationship between brain regions-of-interest (ROIs), such as partial correlation or full correlation, which is difficult to fully capture the subtle connections among ROIs since these connections are extremely complex. Motivated by the multi-view learning, in this study we propose a novel Consistent and Specific Multi-view FBNs Fusion (CSMF) approach. Concretely, we first construct multi-view FBNs (i.e., multiple types of FBNs modelling various relationships among ROIs), and then these FBNs are decomposed into a consistent representation matrix and their own specific matrices which capture their common and unique information, respectively. Lastly, to obtain a better brain representation, it is fusing the consistent and specific representation matrices in the latent representation spaces of FBNs, but not directly fusing the original FBNs. This potentially makes it more easily to find the comprehensively brain connections. The experimental results of ASD identification on the ABIDE datasets validate the effectiveness of our proposed method compared to several state-of-the-art methods. Our proposed CSMF method achieved 72.8% and 76.67% classification performance on the ABIDE dataset.

Individual consistency in spatiotemporal characteristics of migratory Whimbrels in the East Asian-Australasian Flyway

Many migratory birds exhibit interannual consistency in migration schedules,routes and stopover sites.Detecting the interannual consistency in spatiotemporal characteristics helps understand the maintenance of migration and enables the implementation of targeted conservation measures.We tracked the migration of Whimbrel(Numenius phaeopus)in the East Asian-Australasian Flyway and collected spatiotemporal data from individuals that were tracked for at least two years.Wilcoxon non-parametric tests were used to compare the interannual variations in the dates of departure from and arrival at breeding/nonbreeding sites,and the inter-annual variation in the longitudes when the same individual across the same latitudes.Whimbrels exhibited a high degree of consistency in the use of breeding,nonbreeding,and stopover sites between years.The variation of arrival dates at nonbreeding sites was significantly larger than that of the departure dates from nonbreeding and breeding sites.Repeatedly used stopover sites by the same individuals in multiple years were concentrated in the Yellow Sea coast during northward migration,but were more widespread during southward migration.The stopover duration at repeatedly used sites was significantly longer than that at sites used only once.When flying across the Yellow Sea,Whimbrels breeding in Sakha(Yakutia)exhibited the highest consistency in migration routes in both autumn and spring.Moreover,the consistency in migration routes of Yakutia breeding birds was generally higher than that of birds breeding in Chukotka.Our results suggest that the northward migration schedule of the Whimbrels is mainly controlled by endogenous factors,while the southward migration schedule is less affected by endogenous factors.The repeated use of stopover sites in the Yellow Sea coast suggests this region is important for the migration of Whimbrel,and thus has high conservation value.

Differentiating consistency of meningioma based on grey-level histogram analysis of T2WI

Objective To observe the value of grey-level histogram analysis based on T2WI for differentiating consistency of meningioma.Methods Data of 109 patients with meningioma were retrospectively analyzed.The patients were divided into hard group(n=71)and soft group(n=38)according to the consistency of tumors.Tumor ROI was outlined on axial T2WI showing the largest tumor section,gray levels were extracted and histogram analysis was performed.The value of each histogram parameter were compared between groups.Then receiver operating characteristic curve was drawn,and the area under the curve(AUC)was calculated to evaluate the efficiency for differentiating soft and hard meningioma.Results P 1,P 10,P 50,P 90,P 99 and the mean grey levels on T2WI in soft group were all higher than those in hard group(all P<0.05),while the variance,the kurtosis and the skewness were not significantly different between groups(all P>0.05).The differentiating efficiency of P 1,P 10,P 50,P 90,P 99 and the mean grey levels on T2WI were all fine,with AUC of 0.774 to 0.833,and no significant difference was found(all P>0.05).Conclusion Parameters of grey-level histogram analysis such as P 1,P 10,P 50,P 90,P 99 and the mean values based on T2WI were all valuable for differentiating soft and hard meningioma.

Cross-Modal Consistency with Aesthetic Similarity for Multimodal False Information Detection

With the explosive growth of false information on social media platforms, the automatic detection of multimodalfalse information has received increasing attention. Recent research has significantly contributed to multimodalinformation exchange and fusion, with many methods attempting to integrate unimodal features to generatemultimodal news representations. However, they still need to fully explore the hierarchical and complex semanticcorrelations between different modal contents, severely limiting their performance detecting multimodal falseinformation. This work proposes a two-stage detection framework for multimodal false information detection,called ASMFD, which is based on image aesthetic similarity to segment and explores the consistency andinconsistency features of images and texts. Specifically, we first use the Contrastive Language-Image Pre-training(CLIP) model to learn the relationship between text and images through label awareness and train an imageaesthetic attribute scorer using an aesthetic attribute dataset. Then, we calculate the aesthetic similarity betweenthe image and related images and use this similarity as a threshold to divide the multimodal correlation matrixinto consistency and inconsistencymatrices. Finally, the fusionmodule is designed to identify essential features fordetectingmultimodal false information. In extensive experiments on four datasets, the performance of the ASMFDis superior to state-of-the-art baseline methods.

Decoding the inconsistency of six cropland maps in China

Accurate cropland information is critical for agricultural planning and production,especially in foodstressed countries like China.Although widely used medium-to-high-resolution satellite-based cropland maps have been developed from various remotely sensed data sources over the past few decades,considerable discrepancies exist among these products both in total area and in spatial distribution of croplands,impeding further applications of these datasets.The factors influencing their inconsistency are also unknown.In this study,we evaluated the consistency and accuracy of six cropland maps widely used in China in circa 2020,including three state-of-the-art 10-m products(i.e.,Google Dynamic World,ESRI Land Cover,and ESA WorldCover)and three 30-m ones(i.e.,GLC_FCS30,GlobeLand 30,and CLCD).We also investigated the effects of landscape fragmentation,climate,and agricultural management.Validation using a ground-truth sample revealed that the 10-m-resolution WorldCover provided the highest accuracy(92.3%).These maps collectively overestimated Chinese cropland area by up to 56%.Up to 37%of the land showed spatial inconsistency among the maps,concentrated mainly in mountainous regions and attributed to the varying accuracy of cropland maps,cropland fragmentation and management practices such as irrigation.Our work shed light on the promotion of future cropland mapping efforts,especially in highly inconsistent regions.

Identifying Brand Consistency by Product Differentiation Using CNN

This paper presents a new method of using a convolutional neural network(CNN)in machine learning to identify brand consistency by product appearance variation.In Experiment 1,we collected fifty mouse devices from the past thirty-five years from a renowned company to build a dataset consisting of product pictures with pre-defined design features of their appearance and functions.Results show that it is a challenge to distinguish periods for the subtle evolution of themouse devices with such traditionalmethods as time series analysis and principal component analysis(PCA).In Experiment 2,we applied deep learning to predict the extent to which the product appearance variation ofmouse devices of various brands.The investigation collected 6,042 images ofmouse devices and divided theminto the Early Stage and the Late Stage.Results show the highest accuracy of 81.4%with the CNNmodel,and the evaluation score of brand style consistency is 0.36,implying that the brand consistency score converted by the CNN accuracy rate is not always perfect in the real world.The relationship between product appearance variation,brand style consistency,and evaluation score is beneficial for predicting new product styles and future product style roadmaps.In addition,the CNN heat maps highlight the critical areas of design features of different styles,providing alternative clues related to the blurred boundary.The study provides insights into practical problems for designers,manufacturers,and marketers in product design.It not only contributes to the scientific understanding of design development,but also provides industry professionals with practical tools and methods to improve the design process and maintain brand consistency.Designers can use these techniques to find features that influence brand style.Then,capture these features as innovative design elements and maintain core brand values.

Probability-consistent spectrum and code spectrum

In the seismic safety evaluation (SSE) for key projects, the probability-consistent spectrum (PCS), usually obtained from probabilistic seismic hazard analysis (PSHA), is not consistent with the design response spectrum given by Code for Seismic Design of Buildings (GB50011-2001). Sometimes, there may be a remarkable difference be-tween them. If the PCS is lower than the corresponding code design response spectrum (CDS), the seismic fortifi-cation criterion for the key projects would be lower than that for the general industry and civil buildings. In the paper, the relation between PCS and CDS is discussed by using the ideal simple potential seismic source. The re-sults show that in the most areas influenced mainly by the potential sources of the epicentral earthquakes and the regional earthquakes, PCS is generally lower than CDS in the long periods. We point out that the long-period re-sponse spectra of the code should be further studied and combined with the probability method of seismic zoning as much as possible. Because of the uncertainties in SSE, it should be prudent to use the long-period response spectra given by SSE for key projects when they are lower than CDS.

Modeling texture evolution during rolling process of AZ31 magnesium alloy with elasto-plastic self consistent model

To gain a better understanding about texture evolution during rolling process of AZ31 alloy, polycrystalline plasticity model was implemented into the explicit FE package, ABAQUS/Explicit by writing a user subroutine VUMAT. For each individual grain in the polycrystalline aggregate, the rate dependent model was adopted to calculate the plastic shear strain increment in combination with the Voce hardening law to describe the hardening response, the lattice reorientation caused by slip and twinning were calculated separately due to their different mechanisms. The elasto-plastic self consistent （EPSC） model was employed to relate the response of individual grain to the response of the polycrystalline aggregate. Rolling processes of AZ31 sheet and as-cast AZ31 alloy were simulated respectively. The predicted texture distributions are in aualitative a^reement with experimental results.

Marginal optimization method to improve the inconsistent comparison matrix in the analytic hierarchy process

To improve the inconsistency in the analytic hierarchy process(AHP), a new method based on marginal optimization theory is proposed. During the improving process, this paper regards the reduction of consistency ratio(CR) as benefit, and the maximum modification compared to the original pairwise comparison matrix(PCM) as cost, then the improvement of consistency is transformed to a benefit/cost analysis problem. According to the maximal marginal effect principle, the elements of PCM are modified by a fixed increment(or decrement) step by step till the consistency ratio becomes acceptable, which can ensure minimum adjustment to the original PCM so that the decision makers’ judgment is preserved as much as possible. The correctness of the proposed method is proved mathematically by theorem. Firstly, the marginal benefit/cost ratio is calculated for each single element of the PCM when it has been modified by a fixed increment(or decrement).Then, modification to the element with the maximum marginal benefit/cost ratio is accepted. Next, the marginal benefit/cost ratio is calculated again upon the revised matrix, and followed by choosing the modification to the element with the maximum marginal benefit/cost ratio. The process of calculating marginal effect and choosing the best modified element is repeated for each revised matrix till acceptable consistency is reached, i.e., CR<0.1. Finally,illustrative examples show the proposed method is more effective and better in preserving the original comparison information than existing methods.

Fuzzy Consistent Matrix and Its Application

This paper presents a kind of fuzzy consistent matrix and introduces its application in analytic hierarchy process and adaptive fuzzy reasoning.

A consistent projection-based SUPG/PSPG XFEM for incompressible two-phase flows

In this paper, a consistent projection-based streamline upwind/pressure stabilizing Petrov-Galerkin （SUPG/PSPG） extended finite element method （XFEM） is presented to model incompressible immiscible two-phase flows. As the application of linear elements in SUPG/PSPG schemes gives rise to inconsistency in stabilization terms due to the inability to regenerate the diffusive term from viscous stresses, the numerical accuracy would deteriorate dramatically. To address this issue, projections of convection and pressure gradient terms are constructed and incorporated into the stabilization formulation in our method. This would substantially recover the consistency and free the practitioner from burdensome computations of most items in the residual. Moreover, the XFEM is employed to consider in a convenient way the fluid properties that have interfacial jumps leading to discontinuities in the velocity and pressure fields as well as the projections. A number of numerical examples are analyzed to demonstrate the complete recovery of consistency, the reproduction of interfacial discontinuities and the ability of the proposed projection-based SUPG/PSPG XFEM to model two-phase flows with open and closed interfaces.

Direct simulation of MHD flows in dual-coolant liquid metal fusion blanket using a consistent and conservative scheme

Direct simulation of 3-D MHD(magnetohydrodynamics) flows in liquid metal fusion blanket with flow channel insert(FCI) has been conducted.Two kinds of pressure equilibrium slot (PES) in FCI,which are used to balance the pressure difference between the inside and outside of FCI,are considered with a slot in Hartmann wall or a slot in side wall,respectively.The velocity and pressure distribution of FCI made of SiC/SiC_f are numerically studied to illustrate the 3-D MHD flow effects,which clearly show that the flows in fusion blanket with FCI are typical three-dimensional issues and the assumption of 2-D fully developed flows is not the real physical problem of the MHD flows in dual-coolant liquid metal fusion blanket.The optimum opening location of PES has been analyzed based on the 3-D pressure and velocity distributions.

The construction and combined operation for fuzzy consistent matrixes

Fuzziness is one of the general characteristics of human thinking and objective things. Introducing fuzzy techniques into decision-making yields very good results. Fuzzy consistent matrix has many excellent characteristics, especially cen- ter-division transitivity conforming to the reality of the human thinking process in decision-making. This paper presents a new approach for creating fuzzy consistent matrix from mutual supplementary matrix in fuzzy decision-making. At the same time, based on the distance between individual fuzzy consistent matrix and average fuzzy consistent matrix, a kind of combined opera- tion for several fuzzy consistent matrixes is presented which reflects most opinions of experienced experts. Finally, a practical example shows its flexibility and practicability further.

Probability-consistent earthquakes and probability-consistent conservative earthquakes

It is pointed out in this paper that the concept of scenario earthquake, expectant earthquake or proposed earthquake suggested by Kameda Nojima (1988) is not probability consistent due to unfit understanding for the aseismic design standard of probabilistic method. The corresponding concept proposed by QI FENG LUO meets the meaning of probability consistent, but it is still in a meaning of average so the result is not good enough. On the basis of above analysis, a concept of probability consistent conservative earthquakes is suggested. And a new method selecting aseismic objective earthquake with physical meaning is proposed on the basis of probabilistic method. After seismic hazard is analysed by certain control parameters, such as peak acceleration, we can determine the aseismic standard according to certain probabilistic level. Based on the attenuation law and the potential sources, we can find out some earthquakes or their combinations of magnitudes and distances. Such earthquakes or combinations are probability consistent for this control parameter. Based on above parameter, we suggest considering the destructive effects of other parameters (such as response spectrum), and selecting conservative earthquakes to replace the average earthquake and meet the requirements of aseismic design better.

THIRD ORDER SHEAR DEFORMATION MODEL FOR LAMINATED SHELLS WITH FINITE ROTATIONS:FORMULATION AND CONSISTENT LINEARIZATION

The paper presents an approach for the formulation of general laminated shells based on a third order shear deformation theory. These shells undergo finite (unlimited in size) rotations and large overall motions but with small strains. A singularity-free parametrization of the rotation field is adopted. The constitutive equations, derived with respect to laminate curvilinear coordinates, are applicable to shell elements with an arbitrary number of orthotropic layers and where the material principal axes can vary from layer to layer. A careful consideration of the consistent linearization procedure pertinent to the proposed parametrization of finite rotations leads to symmetric tangent stiffness matrices. The matrix formulation adopted here makes it possible to implement the present formulation within the framework of the finite element method as a straightforward task.

DISSIPATION-BASED CONSISTENT RATE-DEPENDENT MODEL FOR CONCRETE

An energy-dissipation based viscoplastic consistency model is presented to describe the performance of concrete under dynamic loading. The development of plasticity is started with the thermodynamic hypotheses in order that the model may have a sound theoretical background. Independent hardening and softening and the rate dependence of concrete are described separately for tension and compression. A modified implicit backward Euler integration scheme is adopted for the numerical computation. Static and dynamic behavior of the material is illustrated with certain numerical examples at material point level and structural level, and compared with existing experimental data. Results validate the effectiveness of the model.

The consistent Riccati expansion and new interaction solution for a Boussinesq-type coupled system

Starting from the Davey-Stewartson equation, a Boussinesq-type coupled equation system is obtained by using a variable separation approach. For the Boussinesq-type coupled equation system, its consistent Riccati expansion （CRE） solvability is studied with the help of a Riccati equation. It is significant that the soliton--cnoidal wave interaction solution, expressed explicitly by Jacobi elliptic functions and the third type of incomplete elliptic integral, of the system is also given.

Condensed hyperelements method of non-vertical consistent boundaries for wave propagation analysis in irregular media

The study of wave propagation in finite/infinite media has many applications in geotechnical and structural earthquake engineering and has been a focus of research for the past few decades. This paper presents an analysis of 2D anti- plane problems （Love waves） and 2D in-plane problems （Rayleigh waves） in the frequency domain in media consisting of a near-field irregular and a far-field regular part. The near field part may contain structures and its boundaries with the far-field can be of any shape. In this study, the irregular boundaries of the near-field are treated as consistent boundaries, extending the concept of Lysmer＇s vertical consistent boundaries. The presented technique is called the Condensed Hyperelements Method （CHM）. In this method, the irregular boundary is limited to a vertical boundary at each end that is a consistent boundary at the far-field side. Between the two ends, the medium is discretized with hyperelements. Using static condensation, the stiffness matrix of the far-field is derived for the nodes on the irregular boundary. Examples of the application of the CHM illustrate its excellent accuracy and efficiency.