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Knowledge graph (KG) embedding aims to study the embedding representation to retain the inherent structure of KGs. Graph neural networks (GNNs), as an effective graph representation technique, have shown impressive performance in learning graph embedding. However, KGs have an intrinsic property of heterogeneity, which contains various types of entities and relations. How to address complex graph data and aggregate multiple types of semantic information simultaneously is a critical issue. In this article, a novel heterogeneous GNNs framework based on attention mechanism is proposed. Specifically, the neighbor features of an entity are first aggregated under each relation-path. Then the importance of different relation-paths is learned through the relation features. Finally, each relation-path-based features with the learned weight values are aggregated to generate the embedding representation. Thus, the proposed method not only aggregates entity features from different semantic aspects but also allocates appropriate weights to them. This method can capture various types of semantic information and selectively aggregate informative features. The experiment results on three real-world KGs demonstrate superior performance when compared with several state-of-the-art methods. [ABSTRACT FROM AUTHOR]

• A fast hypervolume approximation algorithm is proposed that accelerates the hypervolume calculation with a steady accuracy error, through a segmentation strategy and the Monte Carlo simulation. The proposed algorithm achieves ten times faster than other compared algorithms in experiments. • Base on above the fast approximation method, an incremental version algorithm is proposed to solve many objective optimization problem and promotes the performance of hypervolume based algorithms. Hypervolume indicator based evolutionary algorithms have been reported to be very promising in many-objective optimization, but the high computational complexity of hypervolume calculation in high dimensions restrains its further applications and developments. In this paper, we develop a fast hypervolume approximation method with both improved speed and accuracy than the previous approximation methods via a new segmentation strategy. The proposed approach consists of two crucial process: segmentation and approximation. The segmentation process recursively finds areas easy to be measured and quantified from the original geometric figure as many as possible, and then divides the measurement of the rest areas into several subproblems. In the approximation process, an improved Monte Carlo simulation is developed to estimate these subproblems. Those two processes are mutually complementary to simultaneously improve the accuracy and the speed of hypervolume approximation. To validate its effectiveness, experimental studies on four widely-used instances are conducted and the simulation results show that the proposed method is ten times faster than other comparison algorithms with a same measurement error. Furthermore, we integrate an incremental version of this method into the framework of SMS-EMOA, and the performance of the integrated algorithm is also very competitive among the experimental algorithms. [ABSTRACT FROM AUTHOR]

This paper presents the dynamic non-local theory solution to a limited-permeable mode-I crack in piezoelectric materials (PMs) with the crack surfaces subjected to harmonic stress waves. The generalized Almansi's theorem and the Schmidt method are used for this purpose. Based on the Fourier transform technique, this problem is formulated into coupled dual integral equations. The dynamic non-local stress and the dynamic non-local electric displacement fields at the crack tips are obtained by solving the derived dual integral equations. Numerical results are reported and discussed to illustrate the influences of the crack length, the lattice parameter, the characteristics of the harmonic wave and the electric permittivity of the air inside the crack on the dynamic non-local stress field and the dynamic non-local electric displacement field near the crack tips in PMs. As compared to the known electrically permeable crack mode, the proposed one exhibits more applicability. • Dynamic non-local theory solution to a mode-I crack in piezoelectric materials is studied. • The limited permeable conditions are applied at the crack faces. • The dynamic non-local stress and electric displacement fields near the crack tips are obtained. [ABSTRACT FROM AUTHOR]

To solve the contradictory problem of local data sharing and privacy protection, this paper presented the models and algorithms for privacy-utility equilibrium data generation based on Wasserstein generative adversarial networks. First, we introduce the expected estimation error between the discriminant probability of real data and generated data into Wasserstein generative adversarial networks, and we formally construct a basic mathematical model of privacy-utility equilibrium data generation based on computationally indistinguishable. Second, we construct the basic model and the basic algorithm of privacy-utility equilibrium data generation based on Wasserstein generative adversarial networks according to the constructed basic mathematical model, and our theoretical analysis results show that the basic algorithm can achieve the equilibrium between local data sharing and privacy protection. Third, according to the constructed basic model, we construct the federated model and the federated algorithm of privacy-utility equilibrium data generation based on Wasserstein generative adversarial networks using the serialized training method of federated learning, and our theoretical analysis results also show that the federated algorithm can achieve the equilibrium between local data sharing and privacy protection in a distributed environment. Finally, our experimental results show that the proposed algorithms can achieve the equilibrium between local data sharing and privacy protection in this paper. Therefore, the constructed basic mathematical model provides a theoretical basis of achieving the equilibrium between local data sharing and privacy protection. At the same time, the proposed basic model and the federated model of privacy-utility equilibrium data generation provide a concrete method of achieving the equilibrium between local data sharing and privacy protection in centralized and distributed environment respectively. [ABSTRACT FROM AUTHOR]

Abstract For the purpose of fault detection and isolation (FDI), reconstruction-based contribution (RBC) analysis is carried out in a model-based way. A bank of adaptive observers are designed for a set of potential faults. From these observers, fault estimates and fault signatures are directly available, thus contribution functions are conveniently constructed to accomplish the FDI work. This integrated design of contribution analysis and adaptive observer takes advantages of both data-driven and model-based approaches, and the diagnosis performance is improved. Furthermore, quantitative isolability analysis is also studied by similarity measurement of the obtained fault signatures. Simulation study with a nonlinear unmanned aerial vehicle (UAV) model shows the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In cloud storage, many encrypted data are inaccessible unless several users are simultaneously present. However, when directly adopting the existing rational secret sharing schemes, it is difficult to achieve a fair key reconstruction, which leads that none of the users sends their shares and no one can access the shared data. To address this problem, this paper introduces an incentive exchange mechanism into rational secret sharing, and proposes a fair data access control scheme for cloud storage. In the proposed scheme, a large number of fake keys are generated to obfuscate the decryption key of the shared data. During the exchange of shares, a user is required to first send his/her shares when he/she deviates from the prescribed scheme. This punishes the users’ selfish behaviors and incentives them to access the shared data together. Theoretical analysis shows that, in the proposed scheme, the Nash equilibrium is that all the users always send their shares, enabling them to reconstruct the decryption key fairly. Additionally, extensive experiments demonstrate that the proposal can control data access policies efficiently. [ABSTRACT FROM AUTHOR]

In order to absorb the vibration from the flywheel, a nonlinear energy sink ( NES) is presented in this paper. The NES is composed of a linear spring and the parallel Euler buckled beams. A discrete multi-degree-of-freedom dynamic model, including the flywheel, the NES and the supporting structure is built. The systematic dynamic equations under the transient and steady loadings, respectively, are solved by fourth-order Runge-Kutta method. Based on these calculating results, it is shown that the NES exhibits the efficiency of energy transfer from the linear system, which includes the supporting structure and the flywheel, to the NES. Meanwhile, the targeted energy transfer has been excited. Then, a detailed computational research of the different types of nonlinear energy transitions that occur under the three-level inputting energy is provided. As a result of these studies, the medium-level exciting energy leads to the effective targeted energy transfer from the linear system to the NES. Under this condition, it exhibits that apparent responses of the NES in a wider frequency range. According to the calculating results under the experimental data from the flywheel, it can be concluded that the NES has suppressed the influences from the disturbance of the flywheel effectively. [ABSTRACT FROM AUTHOR]

In order to meet the requirement of inertial navigation system (INS) for low cost and high performance and solve problems of high cost and large volume of the traditional single master INS, low cost MEMS inertial sensors are installed in skew redundant configuration. Based on the Kalman filter, a new optimal data fusion approach based on virtual sensors is proposed, thus the dynamic model of measurement system is simplified, the computational effort is reduced, and the measurement accuracy is improved. The distributed navigation system based on skew redundant sensors is designed by installing multiple skew redundant inertial measurement unit (SRIMU) nodes in different parts of the carrier. With analysis on the sensor network architecture, the measurement fusion of the distribution navigation system is designed by using the equivalent model based on virtual sensors. The simulation results verify that the optimal data fusion based on virtual sensors improves the measurement accuracy and that the distributed navigation system provides the high accuracy navigation information and suppresses the impact of carrier's local stochastic perturbation on navigation performance. [ABSTRACT FROM AUTHOR]

The dynamic stress intensity factors (DSIFs) of two 3D rectangular cracks in a transversely isotropic elastic material under an incident harmonic stress wave are investigated by generalized Almansi’s theorem and the Schmidt method in the present paper. Using 2D Fourier transform and defining the jumps of displacement components across the crack surface as the unknown functions, three pairs of dual integral equations are derived. To solve the dual integral equations, the jumps of the displacement components across the crack surfaces are expanded in a series of Jacobi polynomials. Numerical examples are provided to show the effects of the geometric shape of the rectangular crack, the characteristics of the harmonic wave and the distance between two rectangular cracks on the DSIFs of the transversely isotropic elastic material. [ABSTRACT FROM AUTHOR]

We study systematically the non-Markovian decoherence dynamics of a dissipative two-level system, i.e., the so-called spin-boson model. It is interesting to find that the decoherence tends to be inhibited with the increase of the coupling strength between the system and the reservoir, which is contrary to the common recognition that a stronger coupling always induces a severer decoherence. This is attributed to the occurrence of a quantum phase transition (QPT). The relationship between this QPT and conventional delocalized-localized QPT is also discussed. Our result suggests a useful control method to overcome the detrimental effects of the reservoir to the system. [ABSTRACT FROM AUTHOR]

Off-shell formulations of supergravities allow one to add closed-form higher-derivative super-invariants that are separately supersymmetric to the usual lower-derivative actions. In this paper we study four-dimensional off-shell N = 1 supergravity where additional super-invariants associated with the square of the Weyl tensor and the square of the Ricci scalar are included. We obtain a variety of solutions where the metric describes domain walls, Lifshitz geometries, and also solutions of a kind known as gyratons. We find that in some cases the solutions can be supersymmetric for appropriate choices of the parameters. In some solutions the auxiliary fields may be imaginary. One may reinterpret these as real solutions in an analytically continued theory. Since the supersymmetry transformation rules now require the gravitino to be complex, the analytically continued theory has a "fake supersymmetry" rather than a genuine supersymmetry. Nevertheless, the concept of pseudosupersymmetric solutions is a useful one, since the Killing spinor equations provide first-order equations for the bosonic fields. [ABSTRACT FROM AUTHOR]

Rocket nozzle is a key structural part of high-thrust liquid rocket engine. There are a hundreds of cooling channels around the nozzle, to ensure the reliable cooling and preheat the fuel. However, it is very difficult to machine the cooling channel due to large size, complex profile, low rigidity, etc. In this article, an integrated digital method for cooling channel machining composed of profile measuring, data processing and channel milling is proposed. Because of large difference between the actual contour and the design model, the channel bottom should be redesigned by using the measured geometric information. Therefore, the varying-thickness and varying-depth cooling channel of nozzle with high order contour or parametric shapes can be machined. Further, a special digital machining system is developed based on an open numerical control platform for the dual-channel vertical milling machine. Finally, an experiment utilizing a typical rocket nozzle is implemented to verify the feasibility of the system. It has been proved that the digital machining system can meet the machining requirements for liquid rocket engine nozzle. [ABSTRACT FROM AUTHOR]

Four new β -resorcylic acid lactones, including penochrochlactone A (2), 4-O-desmethyl-aigialomycin B (4), and penochrochlactones C and D (5 and 6), two compounds isolated from a natural source for the first time, 5 α , 6 β -acetonide-aigialomycin B (1) and penochrochlactone B (3), together with six known compounds, aigialomycin F (7), aigialomycins A, B, and D (8 – 10), zeaenol (11), and oxozeaenol (12), were isolated from a mycelial solid culture of the endophytic fungus Penicillium ochrochloron SWUKD4.1850 from the medicinal plant Kadsura angustifolia by sequential purification over silica gel, Sephadex LH-20 column chromatography, and preparative HPLC. Their structures were elucidated by extensive spectroscopic analysis and chemical conversions. In addition, all the new compounds were evaluated for their cytotoxic and antibacterial activities in vitro. Penochrochlactone C (5) displayed moderate cytotoxicity against the HeLa tumor cell line with an IC50 value of 9.70 µM. In the antibacterial assays, compounds 4 – 6 exhibited moderate activities against Staphylococcus aureus, Bacillus subtilis, Escherichia coli , and Pseudomonas aeruginosa with MIC values between 9.7 and 32.0 µg/mL. [ABSTRACT FROM AUTHOR]

To improve the utilization of infrastructure resources and reduce the cost of operators in the future 6G network construction, a 6G shared base stations optimization model is proposed in this paper, which is a bi-level multiobjective optimization problem (BLMOP). In such a BLMOP, the tower company is responsible for the construction of base stations at the upper level, while operators share the base station resources of the tower company at the lower level. In addition, we also propose two strategies to solve the optimization efficiently. First, we use surrogate models to fit lower-level Pareto fronts (PF), then the degree of lower-level optimality constraint violation is converted to distance between the candidate solutions and the approximate lower level PF. So the BLMOP is transformed to a single-level constrained multi-objective optimization problem. Second, to accelerate the current lower-level optimization, we migrate the modified population from the adjacent lower-level optimization tasks. These two strategies effectively reduce the computational overhead. Compared with three existing works, the proposed method has achieved the best or comparable results on 7 benchmark problems and 5 generated test instances with less computation overhead, whose efficiency has been confirmed. [ABSTRACT FROM AUTHOR]

[Display omitted] The architecture of our proposed method SSGCAE for semi-supervised overlapping community detection in attributed graph. • An end-to-end method SSGCAE for overlapping community detection is proposed. • SSGCAE is based on graph convolutional autoencoder driven by community detection. • SSGCAE is comprehensively evaluated on synthetic and real attributed graphs. • SSGCAE outperforms state-of-the-art baselines. Community detection in attributed graph is of great application value and many related methods have been continually presented. However, existing methods for community detection in attributed graph still cannot well solve three key problems simultaneously: link information and attribute information fusion, prior information integration and overlapping community detection. Aiming at these problems, in this paper we devise a semi-supervised overlapping community detection method named SSGCAE which is based on graph neural networks. This method is composed of three modules: graph convolutional autoencoder (GCAE), semi-supervision and modularity maximization, which are respectively utilized to fuse link information and attribute information, integrate prior information and detect overlapping communities. We treat GCAE as the backbone framework and train it by using the unified loss from these three modules. Through this way, these three modules are jointly correlated via the community membership representation, which is very beneficial to improve the overall performance. SSGCAE is comprehensively evaluated on synthetic and real attributed graphs, and experiment results show that it is very effective and outperforms state-of-the-art baseline approaches. [ABSTRACT FROM AUTHOR]

Abstract: Molodtsov initiated the concept of soft set theory, which can be used as a generic mathematical tool for dealing with uncertainty. However, it has been pointed out that classical soft sets are not appropriate to deal with imprecise and fuzzy parameters. In order to handle these types of problem parameters, some fuzzy (or intuitionistic fuzzy, interval-valued fuzzy) extensions of soft set theory are presented, yielding fuzzy (or intuitionistic fuzzy, interval-valued fuzzy) soft set theory. In this paper, we define the distance measures between intuitionistic fuzzy soft sets and give an axiom definition of intuitionistic entropy for an intuitionistic fuzzy soft set and a theorem which characterizes it. Furthermore, we discuss the relationship between intuitionistic fuzzy soft sets and interval-valued fuzzy soft sets and transform the structure of entropy for intuitionistic fuzzy soft sets to the interval-valued fuzzy soft sets. [Copyright &y& Elsevier]

In this work, a unified phase field theory for two coupled fracture types is proposed. Compared with the existing unified phase field theory for single fracture type, it considers the coupling behavior between different fracture types and is consistent with the single fracture type theory when one type of fracture is suppressed. Based on a new form of energy decomposition, that is, the strain energy is decomposed into deviatoric, tensile volumetric and compressive volumetric parts, and specifying the driving energy for each fracture type, a double phase-field model for coupled spall and adiabatic shear banding, which are two kinds of typical dynamic ductile fracture, is realized with the proposed unified phase field theory for two coupled fracture types. This coupled model can be used to predict the potential spall and adiabatic shear banding failures in ductile metals under dynamic loading, revealing the corresponding fracture types under different loadings without any additional criteria. The entire damage and fracture evolution (that is, from damage evolution, through crack expansion, and to fragmentation) are captured with this unified phase-field modeling framework. In addition, as an advantage of the double phase-field model, the complex multicrack distributions of spall and adiabatic shear bands in ductile metals can be presented with the proposed model. Based on these features, the expanding characteristics of complex cracks in metallic expanding shells are numerically studied. It is found that, if multilayer spall occurs, the specimen tends to fracture into three layers, that is, a complete spall layer, fragmentations in multilayer areas, and the main body, which is consistent with the experimental observations under certain conditions and is not the regular multiple layers predicted by the multilayer spall theory with ideal material assumption. For multiple adiabatic shear bands (ASBs) in the shell, the spiral patterns of ASBs' distributions, the initial positions, and the propagating path are clarified for the collapsed and expanding shells. The collapsed shell tends to form a single-direction spiral pattern whereas the expanding shell tends to form a double-direction spiral pattern. In addition to the inner surface, the intersection points of two ASBs can initiate cracks, and, as the intersection points have the chance of being distributed on the outer surface, the expanding shell has a greater potential to initiate a crack on the outer surface than the collapsed shell. The propagating path will be deflected after interactions of two ASBs, and the quantitative relationship between the deflection angle and the stress state before the interactions is given, which explains why the deflection angle is significantly larger in the collapsed shell compared with that in the expanding shell. Based on the above results and analysis, four typical stages of fractures in the expanding shell under internal explosive loading are identified. [ABSTRACT FROM AUTHOR]

A novel subspace tracking algorithm based on subspace distance is proposed in this paper. The proposed algorithm provides robust orthonormal vector estimation adapting to signal subspace and noise subspace. Simulation results demonstrate that the proposed algorithm is numerically stable, because it does not accumulate roundoff errors. Moreover, the proposed method performs well in subspace tracking and it has a low complexity of 3NL + O(N). [ABSTRACT FROM AUTHOR]