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Competing risks models for discretely measured durations are partially identifying due to the unknown dependence structure between risks and the discrete nature of the outcome. This article develops a highly tractable bounds approach for underlying distributions of latent durations by exploiting the discreteness. Bounds are obtained from a system of nonlinear (in)equalities. I devise a sequential solution method that requires much less computational burden than existing methods. Asymptotic properties of bound estimators and a simple bootstrap procedure are provided. I apply the proposed approach to re-evaluate trends in cancer mortality extending the data studied in Honore and Lleras-Muney (2006). Estimated patterns differ from the original findings.

In this article, a novel linear parallel control method is developed for output regulation problems with disturbances. The traditional feedback regulators are passive regulation methods. In order to solve this problem, the parallel controllers are presented, where the time variation of the control is constructed instead of the control value itself, to stabilize the output of the system. The main contributions of the developed method include two aspects: 1) a novel parallel regulator structure is presented, which can provide greater flexibility comparing with traditional methods and 2) the necessary and sufficient conditions for the existence of parallel regulators are analyzed. First, the structure of the linear parallel regulators is provided. Next, considering the situations that the full system information is obtained and the information of error is obtained, respectively, the properties of the parallel regulators are analyzed, and the regulator designs for the two situations are provided. Finally, numerical examples are provided to verify the correctness of the present method.

This paper considers linear panel data models with a grouped pattern of heterogeneity when the latent group membership structure and/or the values of slope coefficients change at a break point. We propose a least squares approach to jointly estimate the break point, group membership structure, and coefficients. The proposed estimators are consistent, and the asymptotic distribution of the coefficient estimators is identical to that under known break point and group structure even when the cross-sectional sample size is much larger than the length of time series. Monte Carlo simulations and an empirical example illustrate the use of the approach and associated inference.

A case study of the steel–concrete composite structure in the Pidie Jaya Regency Multipurpose Hall which experienced substantial permanent lateral deformation due to the effect of an earthquake is presented in this study. Therefore, it is important to assess the response of the structure to earthquake load and propose the strengthening strategies to make the buildings useful again. The purpose was to evaluate the causes of large deformations and the behavior of structure in resisting earthquake loads. The building structure model used in this study is a space frame with two-column base support conditions which are fixed and hinged supports after which a non-linear time history analysis was conducted. The time history analysis was conducted using five ground motion acceleration data recorded during earthquakes to determine the deformation and it was found that the large structure permanent deformation was due to the small structure stiffness in the direction of the deformation due to the use of only one column row in front of the building. Moreover, hinged support was observed to have caused a greater deformation than fixed support but was found not to be the main cause of large permanent deformation of the structure. The building structure was further strengthened by adding 4 columns while the oblique columns remained in a sloping condition. Meanwhile, the response spectrum analysis showed the strengthening structure was able to withstand earthquake loads with less deformation than the required standard.

Density-Based clustering are the main clustering algorithms because they can cluster data with different shapes and densities, but some of these algorithms have high time complexity like OPTICS (Ordering Points to Identify Clustering Structure) and DBSCAN (Density-based spatial clustering of applications with noise) where the time complexity up to O( n 2 ). In this paper, we use an approach to reduce this complexity by providing fuzzy clusters to OPTICS, which make the process of finding neighbours within an only narrow region (fuzzy group) instead of searching all the state space making the algorithm faster than the original one with keeping almost the same accuracy of the innovative algorithm. The results show that there is an improvement in execution time using some synthetic and real datasets with high dimensions.

In this paper, for each of six families of three-valued \begin{document}$ m $\end{document} -sequence correlation, we construct an infinite family of five-weight codes from trace codes over the ring \begin{document}$ R = \mathbb{F}_2+u\mathbb{F}_2 $\end{document} , where \begin{document}$ u^2 = 0. $\end{document} The trace codes have the algebraic structure of abelian codes. Their Lee weight distribution is computed by using character sums. Their support structure is determined. An application to secret sharing schemes is given. The parameters of the binary image are \begin{document}$ [2^{m+1}(2^m-1),4m,2^{m}(2^m-2^r)] $\end{document} for some explicit \begin{document}$ r. $\end{document}

An algorithm for solving exciton Schrodinger equation in an arbitrary 2D multiple quantum well structure under applied electric field is proposed, allowing one to model both the absorption and refraction spectra consistently and efficiently. It gives much better quantitative results than variational approximation, while being faster than more advanced methods. The algorithm is implemented using R language and tested by comparing to other published results. Possible improvements are discussed.

Hydrodynamic analysis of semi-submersible offshore structures has been the topic of several numerical and experimental research studies conducted in the past. In this work, the effect of structure alignment and mooring lines on the dynamic behaviour of semi-submersible platforms was taken into account. The contribution of pitch and roll into heave motion of side-points was also investigated. Mooring lines are connected to semi-submersible platforms at the sides; therefore, the total displacement of side-points is related to the total displacement of mooring lines and total tension. A three-dimensional boundary element model of Amirkabir platform in the Caspian Sea was created using the boundary element method and the resulting response amplitude operators (RAOs) were obtained. A conceptual study on RAOs was conducted, which showed that structure alignment with respect to wave direction is highly important for a range of wave periods. In addition, in surge and sway, the effect of mooring lines is significant in particular ranges of wave periods. The contributions of roll and pitch to the side-points of semi-submersible platforms are also considerable in a range of periods.

Chromosome conformation capture (3C) is a method of measuring chromosome topology in terms of loci interaction. The Hi-C method is a derivative of 3C that allows for genome wide quantification of chromosome interaction. From such interaction data, it is possible to infer the three-dimensional (3D) structure of the underlying chromosome. In this paper, we use a node embedding algorithm and a graph neural network to predict the 3D coordinates of each genomic loci from the corresponding Hi-C contact data. Unlike other chromosome structure prediction methods, our method can generalize a single model across Hi-C resolutions, multiple restriction enzymes, and multiple cell populations while maintaining reconstruction accuracy. We derive these results using three separate Hi-C data sets from the GM12878, GM06990, and K562 cell lines. We also compare the reconstruction accuracy of our method to four other existing methods and show that our method yields superior performance. Our algorithm outperforms the state-of-the-art methods in the accuracy of prediction and introduces a novel method for 3D structure prediction from Hi-C data.Author SummaryWe developed a novel method, HiC-GNN, for predicting the three-dimensional structures of chromosomes from Hi-C data. HiC-GNN is unique from other methods for chromosome structure prediction in that it learns in an eager setting rather than a lazy setting. Thus, the models learned by HiC-GNN can be generalized to unseen data. To the authors’ knowledge, this generalizing capability is not present in any existing methods. We show that this generalization is robust to input resolution, restriction enzyme, and contact sparsity. We also show that our method outperforms existing methods using both generalized and non-generalized models. Moreover, we also show that our method is more robust to contact variance than the compared methods.AvailabilityAll our source codes and data are available at https://github.com/OluwadareLab/HiC-GNN, and is made available as a containerized application that can be run on any platform.

The submonoid of the 3-strand braid group B 3 generated by σ 1 and σ 1 σ 2 is known to yield an exotic Garside structure on B 3 . We introduce and study an infinite family ( M n ) n ≥ 1 of Garside monoids generalizing this exotic Garside structure, i.e., such that M 2 is isomorphic to the above monoid. The corresponding Garside group G ( M n ) is isomorphic to the ( n , n + 1 ) -torus knot group–which is isomorphic to B 3 for n = 2 and to the braid group of the exceptional complex reflection group G 12 for n = 3 . This yields a new Garside structure on ( n , n + 1 ) -torus knot groups, which already admit several distinct Garside structures. The ( n , n + 1 ) -torus knot group is an extension of B n + 1 , and the Garside monoid M n surjects onto the submonoid Σ n of B n + 1 generated by σ 1 , σ 1 σ 2 , … , σ 1 σ 2 ⋯ σ n , which is not a Garside monoid when n > 2 . Using a new presentation of B n + 1 that is similar to the presentation of G ( M n ) , we nevertheless check that Σ n is an Ore monoid with group of fractions isomorphic to B n + 1 , and give a conjectural presentation of it, similar to the defining presentation of M n . This partially answers a question of Dehornoy–Digne–Godelle–Krammer–Michel.

An asymmetric coloring of a graph is a coloring of its vertices that is not preserved by any non-identity automorphism of the graph. The motion of a graph is the minimal degree of its automorphism group, i.e., the minimum number of elements displaced by any non-identity automorphism. In this paper we confirm Tom Tucker's "Infinite Motion Conjecture" that connected locally finite graphs with infinite motion admit an asymmetric 2-coloring. We infer this from the more general result that the inverse limit of a sequence of finite permutation groups with disjoint domains, viewed as a permutation group on the union of those domains, admits an asymmetric 2-coloring. The proof is based on the study of the interaction between epimorphisms of finite permutation groups and the structure of the setwise stabilizers of subsets of their domains., Comment: V.2 updates: Choi 1972 ref. added, Sec. 8.3 (Mathieu groups) updated, question about $M_{24}$ deleted from "Open questions." New material: New Sec. 14 added, incl. two conjectures. Minor changes made for improved clarity throughout the paper. None of the updates affects the main results or their proofs

We introduce the two-step average tree value for transferable utility games with restricted cooperation represented by undirected communication graphs or hypergraphs. The solution can be considered as an alternative for both the average tree solution for graph games and the average tree value for hypergraph games. Instead of averaging players’ marginal contributions corresponding to all admissible rooted spanning trees of the underlying (hyper)graph, which determines the average tree solution or value, we consider a two-step averaging procedure, in which first, for each player the average of players’ marginal contributions corresponding to all admissible rooted spanning trees that have this player as the root is calculated, and second, the average over all players of all the payoffs obtained in the first step is computed. In general these two approaches lead to different solution concepts. Contrary to the average tree value, the new solution satisfies component fairness and the total cooperation equal treatment property on the entire class of hypergraph games. Moreover, the two-step average tree value is axiomatized on the class of semi-cycle-free hypergraph games, which is more general than the class of cycle-free hypergraph games by allowing the underlying hypergraphs to contain certain cycles. The two-step average tree value is also core stable on the subclass of superadditive semi-cycle-free hypergraph games.

Moral virtue is, for Aristotle, a state to which an agent’s motivation is central. For anyone interested in Aristotle’s account of moral development this invites reflection on two questions: how is it that virtuous motivational dispositions are established? And what contribution do the moral learner’s existing motivational states make to the success of her habituation? I argue that views which demand that the learner act with virtuous motives if she is to acquire virtuous dispositions misconstrue the nature and structure of the habituation process, but also obscure Aristotle’s crucial insight that the very practice of virtuous actions affords a certain discovery and can be transformative of an agent’s motivational states. Drawing attention, in Aristotle’s account, to an asymmetry between the agential perspective and the observation of others, I consider what the agential perspective affords the learner, and offer a novel interpretation of the role a learner’s existing motives play in her habituation.

In this paper, we study a class of matrix functions of the combinatorial Laplacian that preserve its structure, i.e. that define matrices which are positive semidefinite, and which have zero row-sum and non-positive off-diagonal entries. This formulation has the merit of presenting different incarnations of the Laplacian matrix appeared in the recent literature, in a unified framework. For the first time, we apply this family of Laplacian functions to consensus theory, and we show that they leave the agreement value unchanged and offer distinctive advantages in terms of performance and design flexibility. The theory is illustrated via worked examples and numerical experiments featuring four representative Laplacian functions in a shape-based distributed formation control strategy for single-integrator robots.

A large number of experiments have proved that the ring structure is a common phenomenon in neural networks. Nevertheless, a few works have been devoted to studying the neurodynamics of networks with only one ring. Little is known about the dynamics of neural networks with multiple rings. Consequently, the study of neural networks with multiring structure is of more practical significance. In this article, a class of high-dimensional neural networks with three rings and multiple delays is proposed. Such network has an asymmetric structure, which entails that each ring has a different number of neurons. Simultaneously, three rings share a common node. Selecting the time delay as the bifurcation parameter, the stability switches are ascertained and the sufficient condition of Hopf bifurcation is derived. It is further revealed that both the number of neurons in the ring and the total number of neurons have obvious influences on the stability and bifurcation of the neural network. Ultimately, some numerical simulations are given to illustrate our qualitative results and to underpin the discussion.

We extend the block filtration, defined by Brown based on the work of Charlton, to all motivic multiple zeta values, and study relations compatible with this filtration. We construct a Lie algebra describing relations among motivic multiple zeta values modulo terms of lower block degree, proving Charlton's cyclic insertion conjecture in this structure, and showing the existence of a `block shuffle' relation, and a previously unknown dihedral symmetry and differential relation., Comment: 23 pages, based on work in the author's doctoral thesis. Typo in statement of Corollary 2.9 corrected

We introduce a natural temporal analogue of Eulerian circuits and prove that, in contrast with the static case, it is NP-hard to determine whether a given temporal graph is temporally Eulerian even if strong restrictions are placed on the structure of the underlying graph and each edge is active at only three times. However, we do obtain an FPT-algorithm with respect to a new parameter called interval-membership-width which restricts the times assigned to different edges; we believe that this parameter will be of independent interest for other temporal graph problems. Our techniques also allow us to resolve two open question of Akrida, Mertzios and Spirakis [CIAC 2019] concerning a related problem of exploring temporal stars. Furthermore, we introduce a vertex-variant of interval-membership-width (which can be arbitrarily larger than its edge-counterpart) and use it to obtain an FPT-time algorithm for a natural vertex-exploration problem that remains hard even when interval-membership-width is bounded., Extended abstract of this paper appeared in IWOCA 2021: Combinatorial Algorithms pp 107-121 (doi: https://doi.org/10.1007/978-3-030-79987-8_8 )

International audience; This article proposes three new decompositions of inequality measures, drawn from the framework of cooperative game theory. It allows the impact of players' interactions, rather than players' contributions to inequality, to be taken into consideration. These innovative approaches are especially suited for the study of income inequality when the income has a hierarchical structure: the income is composed of several primary sources, with the particularity that each of them is also composed of secondary sources. We revisit the Shapley-Owen value that quantifies the importance of each of these secondary sources in the overall income inequality. Our main contribution is to decompose this importance into two parts: the pure marginal contribution of the considered source and a weighted sum of pairwise interactions. We then provide an axiomatic characterization of each additive interaction decomposable (AID) coalitional value considered in this paper. We give an application of these decompositions in the context of inequality theory.

In this paper, considering L a complete residuated lattice, we present a lattice-valued category TNG (resp., TTNG) of (topological) ⊤-neighborhood groups, where the object is defined as a group equipped with a (topological) ⊤-neighborhood space such that the group operations are continuous with respect to the (topological) ⊤-neighborhood space. It is proved that: (1) The ⊤-neighborhood space associated with a ⊤-neighborhood group is topological, so the category TNG is equivalent to the category TTNG. Hence TTNG is redundant, and we need only discuss TNG. (2) The category TNG has nice characterizations, localization and uniformization. (3) The category TNG has initial structure, so it is a topological category, and each initial structure has an ordered representation. (4) The category NG of neighborhood groups can be embedded in TNG as a reflective subcategory. (5) The category TNG can be embedded in the category SLNG of stratified L-neighborhood groups as a reflective subcategory when the underlying lattice L is a meet-continuous lattice. (6) The category TNG is equivalent to the category StrLTOPG of strong L-topological groups when L is a complete MV-algebra.

To allow versatile manipulation of soft robots made of compliant materials with limited force transmission, variable stiffness has been actively developed, which has become one of the most important factors in soft robotics. Variable stiffness is usually achieved by a jamming mechanism using layers, granules, or chain structures, through vacuum pressure or cable-driven mechanism due to its simple and rapid actuation. However, such jamming mechanisms are not suitable for actual robotic applications that require large supporting forces or drastic changes in stiffness. In this article, a hybrid jamming structure that combines granules and a rigid chain structure is proposed to simultaneously increase the average stiffness change in all directions and the maximum force in a certain direction. The improved performance of the proposed structure was compared to that of conventional granular and chain jamming structures. Based on the analytical model of the proposed structure, the principles for designing the hybrid jamming structure were derived and experimentally verified. Finally, based on the hybrid jamming structures, a multilink hybrid jamming structure was developed as a wearable system to assist the upper limbs and a robotic arm structure.

This study aims to develop the notion of general fuzzy automata (GFA) to a new one which is known as “ L B -valued general fuzzy automata”. Instead of the term L B -valued general fuzzy automata, for simplicity, L B -valued GFA is used where B is regarded as a set of propositions about the GFA, in which its underlying structure has been a complete infinitely distributive lattice. Further, L B -valued GFA is scrutinized via different operators and also the interrelationship among these operators is examined. Specifically, it is shown that L B -valued successor, L B -valued predecessor and L B -valued residuated operators play an important role in the algebraic study of L B -valued general fuzzy automaton and that under certain conditions these operators are interrelated. In addition, the concept of a homomorphism between L B -valued general fuzzy automata is introduced and studied. Finally, the concepts of equivalence and congruence are defined, the quotient L B -valued GFA with respect to congruence is formulated and the equivalence between L B -valued GFA and its quotient automaton is proved. To clarify the notions and the results obtained in this study, some examples are submitted as well.

Value iteration is a fixed point iteration technique utilized to obtain the optimal value function and policy in a discounted reward Markov Decision Process (MDP). Here, a contraction operator is constructed and applied repeatedly to arrive at the optimal solution. Value iteration is a first order method and therefore it may take a large number of iterations to converge to the optimal solution. Successive relaxation is a popular technique that can be applied to solve a fixed point equation. It has been shown in the literature that, under a special structure of the MDP, successive over-relaxation technique computes the optimal value function faster than standard value iteration. In this work, we propose a second order value iteration procedure that is obtained by applying the Newton-Raphson method to the successive relaxation value iteration scheme. We prove the global convergence of our algorithm to the optimal solution asymptotically and show the second order convergence. Through experiments, we demonstrate the effectiveness of our proposed approach., Comment: Accepted for publication at IEEE Transactions on Automatic Control

We study the problem of learning the structure of an optimal Bayesian network when additional constraints are posed on the network or on its moralized graph. More precisely, we consider the constraint that the network or its moralized graph are close, in terms of vertex or edge deletions, to a sparse graph class $Π$. For example, we show that learning an optimal network whose moralized graph has vertex deletion distance at most $k$ from a graph with maximum degree 1 can be computed in polynomial time when $k$ is constant. This extends previous work that gave an algorithm with such a running time for the vertex deletion distance to edgeless graphs [Korhonen & Parviainen, NIPS 2015]. We then show that further extensions or improvements are presumably impossible. For example, we show that learning optimal networks where the network or its moralized graph have maximum degree $2$ or connected components of size at most $c$, $c\ge 3$, is NP-hard. Finally, we show that learning an optimal network with at most $k$ edges in the moralized graph presumably has no $f(k)\cdot |I|^{O(1)}$-time algorithm and that, in contrast, an optimal network with at most $k$ arcs can be computed in $2^{O(k)}\cdot |I|^{O(1)}$ time where $|I|$ is the total input size., 42 pages

The double-sided tubular linear machine (DSTLM) has a more compact structure than general single-sided motors, resulting in a higher power density, typically at the cost of a higher cogging force. To reduce this aspect and make it more suitable for applications in wave energy conversion systems or elevator driver systems, a new tooth-cutting topology is proposed in this paper. The Schwarz-Christoffel (SC) mapping method is used to model and analyze the magnetic field and cogging force of the DSTLM. Based on the analytical model and the relationships between the cutting dimensions and the force performances, optimization is carried out by using a differential evolution algorithm (DEA). The optimization and the experiment results show that the proposed tooth-cutting topology can effectively reduce the cogging force at the small cost of weakening average thrust.

Because of its paramount importance in the successful industrial control strategy of a given heat exchanger network (HEN), the control structure designs for providing appropriate manipulated variable (MV) and controlled variable (CV) pairings have received considerable attention. However, quite frequently HENs with such control structures face the problem of hard constraints, typically holding the HENs at less controlled operating space. So both the MV pairings and the above control pairings should be considered to design a control structure. This paper investigates the systematic incorporation of the two pairings, and presents a methodology for designing such two-tier control structure. This is developed based on the sequential strategy, coupling an indirect-tier with direct-tier control structure design, wherein the intention is realized in the former stage and the latter is implemented for further optimization. The MV identification and pairing are achieved through variations in heat load of heat exchangers to design the indirect-tier control structure. Then the direct-tier control structure is followed the relative gain array (RGA) pairing rules. With the proposed methodology, on the one hand, it generates an explicit connection between the MV pairings and the HEN configuration, and the quantitative interaction measure is improved to avoid the multiple solutions to break the relationship among all the control pairings into individuals; on the other hand, a two-tier control structure reveals control potentials and control system design requirements, this may avoid complex and economically unfavourable control and HEN structures. The application of proposed framework is illustrated with two cases involving the dynamic simulation analysis, the quantitative assessment and the random test.

In recent years, grey models based on fractional-order accumulation and/or derivatives have attracted considerable research interest because they offer better performance in handling limited samples with uncertainty than integer-order grey models; however, there remains room for improvement. This paper considers a more flexible and general structure for the fractional grey model by incorporating a generalized fractional-order derivative (GFOD) that complies by memory effects, resulting in the development of a generalized fractional grey model (denoted as GFGM(1,1)). Specifically, we comprehensively analyse the modelling mechanism of the proposed GFGM(1,1) model, involving model parameter estimation and time response function derivation, and discuss the link between the proposed approach and existing special cases. Then, to further improve the efficacy of the proposed approach, four mainstream metaheuristic algorithms are employed to ascertain the orders of fractional accumulation and derivatives. Finally, we carry out a series of simulation studies and a real-world application case to demonstrate the applicability and advantage of the our approach. The numerical results show that GFGM(1,1) outperforms other benchmarks, and some significant insights are obtained from the numerical experiments.

This article addresses the trajectory consensus problem of coordinating the trajectories of vehicles at multiple future time points. The objective is the consensus of the geometry of the vehicles' planned trajectories. The geometric feature of trajectories is parameterized by a set of trajectory states defined as required lengths along the trajectory to reduce the distance to its ending point to specific values. To solve this special consensus problem involving coupled state variables, the conventional consensus model is extended by attaching it to a mapping from the state variables to the trajectory's geometry. This mapping is established using a homotopic structure that creates a compact and efficient form for the mapping. The geometry of the homotopic structure is based on the shapes of its envelopes, and the elements in the structure are derived from their deformation. Through a homotopic search in the structure, an asymptotic consensus of trajectory states is achieved. Simulation results show the proposed coupled state consensus method can achieve better performance on the consensus of multiple vehicles than the conventional isolated state consensus method.

Exploiting Bilevel Optimization Techniques to Disconnect Graphs into Small Components In order to limit the spread of possible viral attacks in a communication or social network, it is necessary to identify critical nodes, the protection of which disconnects the remaining unprotected graph into a bounded number of shores (subsets of vertices) of limited cardinality. In the article “'Casting Light on the Hidden Bilevel Combinatorial Structure of the Capacitated Vertex Separator Problem”, Furini, Ljubic, Malaguti, and Paronuzzi provide a new bilevel interpretation of the associated capacitated vertex separator problem and model it as a two-player Stackelberg game in which the leader interdicts (protects) the vertices, and the follower solves a combinatorial optimization problem on the resulting graph. Thanks to this bilevel interpretation, the authors derive different families of strengthening inequalities and show that they can be separated in polynomial time. The ideas exploited in their framework can also be extended to other vertex/edge deletion/insertion problems or graph partitioning problems by modeling them as two-player Stackelberg games to be solved through bilevel optimization.

This study proposes a hierarchical structure-based fault-tolerant tracking control methodology for multiple 3-DOF helicopters in the presence of system nonlinearities, uncertainties and simultaneous actuator faults (partial loss of effectiveness, stuck, and saturation), and sensor faults (bias and drift). The hierarchical structure consists of the decentralized fault estimation hierarchy and distributed fault-tolerant tracking control hierarchy. The distributed constant gain-based, node-based, and edge-based adaptive fault-tolerant tracking control designs are developed to cope with bidirectional interactions and to guarantee the robust asymptotic stability and the good tracking property of multihelicopter systems, respectively. Simulation results validate the effectiveness of the proposed hierarchical structure-based tracking control algorithm.

We consider optimal control problems for continuous-time systems with time-dependent dynamics, in which the time-dependence arises from the presence of a known exogenous signal. The problem has been elegantly solved in the case of linear input-affine systems, for which it has been shown that the solution has a remarkable structure: it is given by the sum of two contributions; a state feedback, which coincides with the unperturbed optimal control law, and a purely feedforward term in charge of compensating the effect of the exogenous signal. The objective of this note is to extend the above result to nonlinear input-affine systems. It is shown that, while some of the relevant features of the linear case indeed rely heavily on linearity and are not preserved in the nonlinear setting, several structural claims can be proved also in the nonlinear case.

In networks of identical linear oscillators (e.g. pendulums undergoing small vibrations) coupled through both dissipative connectors (e.g. dampers) and restorative connectors (e.g. springs) the relation between asymptotic synchronization and coupling structure is studied. Conditions on the interconnection under which synchronization can be achieved for some selection of coupling strengths are established. How to strengthen those conditions so that synchronization is guaranteed for all admissible parameter values is also presented.

This paper discusses a new method for finding the complete set of tolerable solutions of max-Archimedean interval-valued fuzzy relation equations. According to the literature, three types of solution sets, namely; tolerable solution set, united solution set and controllable solution set can be identified with interval-valued fuzzy relation equations. The structure and the properties of the tolerable solution set are studied. The complete set of tolerable solutions can be characterized by one maximum solution and finitely many minimal solutions. An efficient method based on the concept of covering is proposed which computes all minimal solutions. The concept of covering is useful for large size problems in terms of computation. The proposed method is illustrated with some examples.

Decision making under uncertainty includes reassessing and reevaluating risk after initial decisions. To this end, it is essential to consider a governing value process and to track its evolution over time. The paper, “Risk-Averse Stochastic Programming: Time Consistency and Optimal Stopping,” by Pichler, Liu, and Shapiro, develops a consistent framework by consolidating risk and optimal stopping. The paper develops the notion of time consistency for the stochastic multistage optimization problem. Supermartingales and envelopes characterizing optimal decisions are given explicitly. With that, dynamic equations are derived, which gradually reveal the optimal policy. Taking risk into account requires updating optimal policies, as an explicit example on American options demonstrates.

Complex network is the simplest abstraction of the interaction of the components of the systems. Reconstructing the full topology of the network from data is a focal problem for understanding and controlling the dynamics behavior of the systems. Based on the characteristics of generalized periodic splay state of weakly coupled systems, that is, when the system is in the generalized periodic splay state, the nodes which are connected directly usually have different phases, and the phases of the nodes which are not connected directly are usually random, we develop an efficient approach to reconstruct the topology of complex network. With the most simplified form of Logistic map as the node dynamics of the coupled systems, we calculate the matrix of the phase correlation, and reconstruct the topological structure of the networks according to the matrix. It’s found that this method can reconstruct the topological structure of the complex network with sparse connection perfectly.

To obtain the seismic performance of plate-shell integrated concrete liquid-storage structures (PSICLSS), a scale test model was built for shaking table testing. A combination isolation layer is proposed, and the dynamic responses of non-isolation and combination isolation PSICLSS under unidirectional and bidirectional earthquakes were tested. The results show that the combination isolation layer can change the spectral characteristics of the input acceleration, reducing the acceleration response and displacement of the structure, but it will increase the hydrodynamic pressure and liquid sloshing height. Under earthquake action, the liquid sloshing of combination isolation PSICLSS clearly appears as a nonlinear splash phenomenon. When considering the vertical earthquake, the horizontal acceleration response of PSICLSS and the liquid sloshing height change little, the peak hydrodynamic pressure changes significantly, and the peak position also changes. The maximum displacement of the isolation layer increases, but the residual displacement decreases.

A metamaterial is any material engineered with a property not discovered in naturally occurring materials. Its existence is important in the development and application of modern technology in this century. Furthermore, Its characteristics such as high sensitivity and gain can be potentially applied in antenna technology. In this research, the metamaterial implementation was used to improve low-profile microstrip antennas as ultra-wideband (UWB) applications. The proposed metamaterial consists of variations of one to four hexagonal shape split ring resonator (SRR-H) elements. This study was carried out through simulation and experiments which were operated in the frequency range 0.05–9 GHz. Based on the results, the proposed antenna with the variation of the SRR-H elements provides increased performance than the without SRR-H. The highest double-negative (DNG) metamaterial characteristic of the SRR-H four-element structure provides the highest antenna performance compared to others. The given working frequency occurs at 5.98 GHz with an increase in bandwidth of 47.49% from without SRR-H. The antenna metamaterial structure also responds by providing an ultimate gain radiation pattern of 5.97 dBi at a 45-degree angle in the Quadrant II region. Thus, the performance of the proposed antenna shows the potential for use in UWB technology.

With integer linear programming problems (ILPPs) being formulated and solved, the existing approaches design optimal Petri-net supervisors via nonpure net structures, including self-loops and data inhibitor arcs. Nonpure net structures are powerful for control of Petri-net-modeled discrete-event systems. However, in the existing work, the formulated ILPPs contain a large number of constraints, which is computationally inefficient. In this article, we propose approaches that formulate ILPPs with fewer constraints such that the computational efficiency is significantly improved. To do so, in formulating ILPPs for optimal Petri-net controllers by using self-loops and data inhibitor arcs, we remove the reachability conditions for legal markings. By doing so, an obtained solution may result in some legal markings unreachable. To solve this problem, a novel technique is developed to design an optimal controller by modifying the initial marking and structure of the obtained supervisor. It is shown that, by the reduced ILPPs, one can find the same feasible solutions as that obtained by the existing work. Finally, the proposed approaches are demonstrated by examples.

A generalized version of fractional models is introduced for the COVID-19 pandemic, including the effects of isolation and quarantine. First, the general structure of fractional derivatives and integrals is discussed; then the generalized fractional model is defined from which the stability results are derived. Meanwhile, a set of real clinical observations from China is considered to determine the parameters and compute the basic reproduction number, i.e., R 0 ≈ 6.6361 . Additionally, an efficient numerical technique is applied to simulate the new model and provide the associated numerical results. Based on these simulations, some figures and tables are presented, and the data of reported cases from China are compared with the numerical findings in both classical and fractional frameworks. Our comparative study indicates that a particular case of general fractional formula provides a better fit to the real data compared to the other classical and fractional models. There are also some other key parameters to be examined that show the health of society when they come to eliminate the disease.

Starting from the notion of a multidistance, we formalize, through a suitable system of axioms, the concept of an inequality measure defined on a nonempty set with no additional structure implemented a priori. Among inequality measures, apart from multidistances we pay special attention to dispersions, and study their main features. Classical concepts will be generalized to this abstract setting. Multidistances are then revisited, and some new methods to generate them are implemented. A wide spectrum of interdisciplinary applications is outlined in the final section. This work is partially supported by the research projects ECO2015-65031-R , MTM2015-63608-P , TIN2016-77356-P , TIN2017-87600-P (MINECO/AEI-FEDER, UE) and PID2019-108392GB-I00 (AEI/10.13039/501100011033)

The three-dimensional (3-D) finite element (FE) analysis is an extremely time-consuming task in the design and optimization of axial flux permanent magnet (AFPM) machines. The aim of this paper is to present a fast and accurate design model of slotless AFPM machines. Thanks to the separation of active- and end-winding parts, the overhang structure, which has widely been used in the air gap winding, can be handled by the proposed method. The winding eddy current loss, a primary source of losses in the air core structure, is incorporated into the analytical model. In addition to the high accuracy, this approach makes it possible to evaluate machine performances only once without needing to rotate the rotor position. As a result, the proposed analytical model can significantly reduce the computational time, preferred in applying an optimization algorithm. Finally, the accuracy of the proposed method is verified by both FE and experimental results.

For achieving the desired configuration of spacecraft at the desired fixed time, a sub-optimal fixed-finite-horizon configuration control method on the Lie group SE(3) is developed based on the Model Predictive Static Programming (MPSP). The MPSP technique has been widely used to solve finite-horizon optimal control problems and is known for its high computational efficiency thanks to the closed-form solution, but it cannot be directly applied to systems on SE(3). The methodological innovation in this paper enables that the MPSP technique is extended to the geometric control on SE(3), using the variational principle, the left-invariant properties of Lie groups, and the topology structure of Lie algebra space. Moreover, the energy consumption, which is crucial for spacecraft operations, is considered as the objective function to be optimized in the optimal control formulation. The effectiveness of the designed sub-optimal control method is demonstrated through an online simulation under disturbances and state measurement errors.

This work focuses on image anomaly detection by leveraging only normal images in the training phase. Most previous methods tackle anomaly detection by reconstructing the input images with an autoencoder (AE)-based model, and an underlying assumption is that the reconstruction errors for the normal images are small, and those for the abnormal images are large. However, these AE-based methods, sometimes, even reconstruct the anomalies well; consequently, they are less sensitive to anomalies. To conquer this issue, we propose to reconstruct the image by leveraging the structure-texture correspondence. Specifically, we observe that, usually, for normal images, the texture can be inferred from its corresponding structure (e.g., the blood vessels in the fundus image and the structured anatomy in optical coherence tomography image), while it is hard to infer the texture from a destroyed structure for the abnormal images. Therefore, a structure-texture correspondence memory (STCM) module is proposed to reconstruct image texture from its structure, where a memory mechanism is used to characterize the mapping from the normal structure to its corresponding normal texture. As the correspondence between destroyed structure and texture cannot be characterized by the memory, the abnormal images would have a larger reconstruction error, facilitating anomaly detection. In this work, we utilize two kinds of complementary structures (i.e., the semantic structure with human-labeled category information and the low-level structure with abundant details), which are extracted by two structure extractors. The reconstructions from the two kinds of structures are fused together by a learned attention weight to get the final reconstructed image. We further feed the reconstructed image into the two aforementioned structure extractors to extract structures. On the one hand, constraining the consistency between the structures extracted from the original input and that from the reconstructed image would regularize the network training; on the other hand, the error between the structures extracted from the original input and that from the reconstructed image can also be used as a supplement measurement to identify the anomaly. Extensive experiments validate the effectiveness of our method for image anomaly detection on both industrial inspection images and medical images.

The bifurcation structure of the oscillations of ultrasound contrast agents (UCAs) was studied as a function of the driving pressure for excitation frequencies that were determined using the UCAs pressure-dependent resonances $$(f_\mathrm{s})$$ . It was shown that when excited by the $$(f_\mathrm{s})$$ , the UCA can undergo a saddle-node bifurcation (SNB) to higher amplitude oscillations. The driving pressure at which the SNB occurs is controllable and depends on the $$(f_\mathrm{s})$$ magnitude. Utilizing the appropriate $$(f_\mathrm{s})$$ , the scattering cross section of the UCAs can significantly be enhanced (e.g., $$\sim $$ ninefold) while at the same time avoiding potential UCA destruction (by limiting the radial expansion ratio $$