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Abstract Our reply on the above comment [1] shows that the new mapping method which proposed by Zeng and Yong [2] is absolutely right. Consequently, the solutions of the nonlinear evolution equations obtained in Zayed and Al-Nowehy [3,4] are true. Unfortunately, the author of this comment [1] failed in using this method and wrote a wrong comment. [ABSTRACT FROM AUTHOR]

We construct a counterexample that disproves the claim of Theorem 0.2 of the paper “Injective mappings and solvable vector fields of Euclidean spaces”, which appeared in Topology Appl. 136 (2004), 261–274. [ABSTRACT FROM AUTHOR]

This paper proposes an extended state observer (ESO) based data-driven set-point learning control (DDSPLC) scheme for a class of nonlinear batch processes with a priori P-type feedback control structure subject to nonrepetitive uncertainties, by only using the process input and output data available in practice. Firstly, the unknown process dynamics is equivalently transformed into an iterative dynamic linearization data model (IDLDM) with a residual term. A radial basis function neural network is adopted to estimate the pseudo partial derivative information related to IDLDM, and meanwhile, a data-driven iterative ESO is constructed to estimate the unknown residual term along the batch direction. Then, an adaptive set-point learning control law is designed to merely regulate the set-point command of the closed-loop control structure for realizing batch optimization. Robust convergence of the output tracking error along the batch direction is rigorously analyzed by using the contraction mapping approach and mathematical induction. Finally, two illustrative examples from the literature are used to validate the effectiveness and advantage of the proposed design. • Novel extended state observer (ESO) based data-driven set-point learning control (DDSPLC). • Iterative dynamic linearized data model (IDLDM) for nonlinear batch processes. • Use the radial basis function neural network (RBFNN) to approximate pseudo partial derivative. • Set-point learning law with an adaptive learning gain for a priori P-type feedback structure. • Robust convergence of the resulting ILC system along the batch direction is rigorously analyzed. [ABSTRACT FROM AUTHOR]

In this paper, synchronization issue of discrete-time fractional fuzzy neural networks (DFFNNs) with delays is solved via quantized control, and is applied in image encryption. Firstly, a novel fractional-order h -difference inequality which makes Lyapunov method more flexible and practical is strictly proved based on the properties of convex functions and theory of discrete fractional calculus. Secondly, by using compression mapping theorem and mathematical induction, we obtain two sufficient conditions to ensure the existence and uniqueness of solutions for DFFNNs. Whereafter, we design a suitable quantized controller, which not only saves channel resources but also reduces control costs. By utilizing our inequality and some analytical techniques, several conservative synchronization criteria for DFFNNs are acquired. Finally, two examples are arranged to illustrate the validity and practicability of our results. • An important fractional difference inequality is strictly proved, which contributes to constructing more flexible Lyapunov functions in the study of discrete-time fractional systems. • Two sufficient conditions are derived to guarantee the existence and uniqueness of the solution for DFFNN with delay by utilizing the compression mapping and mathematical induction. • Discrete-time fractional Halanay inequality is employed to explore synchronization of DFFNNs for the first time. • Under the quantized controller, some easily verifiable synchronization criteria related to step h are acquired. • Based on synchronization of DFFNNs, an image encryption algorithm is designed, and an example is given to verify the encryption effect of our designed algorithm. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of analyzing the performance of 3D face alignment (3DFA), or facial landmark localization. This task is usually supervised, based on annotated datasets. Nevertheless, in the particular case of 3DFA, the annotation process is rarely error-free, which strongly biases the results. Alternatively, unsupervised performance analysis (UPA) is investigated. The core ingredient of the proposed methodology is the robust estimation of the rigid transformation between predicted landmarks and model landmarks. It is shown that the rigid mapping thus computed is affected neither by non-rigid facial deformations, due to variabilities in expression and in identity, nor by landmark localization errors, due to various perturbations. The guiding idea is to apply the estimated rotation, translation and scale to a set of predicted landmarks in order to map them onto a mathematical home for the shape embedded in these landmarks (including possible errors). UPA proceeds as follows: (i) 3D landmarks are extracted from a 2D face using the 3DFA method under investigation; (ii) these landmarks are rigidly mapped onto a canonical (frontal) pose, and (iii) a statistically-robust confidence score is computed for each landmark. This allows to assess whether the mapped landmarks lie inside (inliers) or outside (outliers) a confidence volume. An experimental evaluation protocol, that uses publicly available datasets and several 3DFA software packages associated with published articles, is described in detail. The results show that the proposed analysis is consistent with supervised metrics and that it can be used to measure the accuracy of both predicted landmarks and of automatically annotated 3DFA datasets, to detect errors and to eliminate them. Source code and supplemental materials for this paper are publicly available at https://team.inria.fr/robotlearn/upa3dfa/. [ABSTRACT FROM AUTHOR]

In this paper, we propose the concept of fuzzy Meir–Keeler contractive mappings in fuzzy metric spaces, which covers fuzzy ψ -contractive mappings and fuzzy H -contractive mappings as special cases. With the aid of the proposed concept, we obtain some Meir–Keeler type fixed point theorems. The derived theorems improve and extend the corresponding ones developed by D. Mihet, D. Wardowski and V. Gregori, et al. And an example in the end of the paper illustrates the validity of our results. [ABSTRACT FROM AUTHOR]

In this paper we provide arguments supporting the idea that module theory in the symmetric, monoidal closed category of complete lattices and join-preserving maps is a mathematical framework for fuzzy set theory as developed by Zadeh. In this context, quantale-enriched category theory is a well established mathematical technique allowing an internal development of various concepts from fuzzy set theory – e.g. the fuzzy power set, Zadeh's forward operator or the fuzzy inclusion order. [ABSTRACT FROM AUTHOR]

In this paper, the existence results of the solution and the finite-time stability (FTS) are focused for fractional fuzzy differential equations (FFDEs) involving non-instantaneous impulsive effects and perturbance parameters. In view of the definitions of short-memory fractional derivatives and a short-memory fractional modeling approach, the existence of a unique solution is proved through utilizing the fixed point theorem of a weakly contractive mapping on the partially ordered fuzzy space, and the sufficient condition of FTS is obtained by using the generalized fractional Gronwall inequality. The fuzzy fractional derivatives used in this study include the concept of derivatives based on the generalized Hukuhara difference (gH-difference) and the granular difference (gr-difference). It is demonstrated that the obtained results based on the gr-difference can overcome restrictions associated with the previous approaches defined via the gH-difference concept. Finally, some numerical examples are provided to verify our main results. [ABSTRACT FROM AUTHOR]

Abstract This paper aims to achieve both high degree-of-freedom (DOF) and high efficiency in direction-of-arrival (DOA) estimation. On one hand, to realize high DOF, this paper optimizes the interelement spacings and the displacement of the generalized coprime sparse array. On the other hand, to achieve high efficiency, a series of approaches are proposed: Firstly, a normalized-coordinate representation is formulated to explore the conversion relationship between the covariance matrix of the physical sparse array and that of the expected virtual Nyquist uniform linear array (ULA); Secondly, a difference-set table traversal searching method is proposed to guide this conversion; Thirdly, the mapping relationship between the element coordinates in the observation covariance matrix and a lag of the Nyquist-ULA is built up, from which the DOAs can be readily estimated through MUSIC decomposition. Deep analysis shows that the proposed estimator saves approximately O ((MN + 1) 3) times of multiplications involved in the spatial smoothing based estimator. Numerical results also confirmed that our proposed estimator does not pay the cost of performance attenuation, which presents vast potentials in radar, communication and sonar systems, etc. [ABSTRACT FROM AUTHOR]

Abstract In a recent paper (Mérida-Angulo and Thas, 2017), the authors introduced a map F which associates a Deitmar constructible set (which is defined over the field with one element, denoted by F 1) with any given loose graph Γ. By base extension, a constructible set X k = F (Γ) ⊗ F 1 k over any field k arises. In the present paper, we will show that all these mappings are functors, and we will use this fact to study automorphism groups of the constructible sets X k. Several automorphism groups are considered: combinatorial, topological and also groups induced by automorphisms of the ambient projective space. When Γ is a finite tree, we will give a precise description of the combinatorial and projective groups, amongst other results. [ABSTRACT FROM AUTHOR]

Highlights • Proposal of integration of OPC UA with REST architecture. • Definition of a web application-based platform able to map OPC UA services to RESTful web services and vice versa. • Definition of RESTful web services and related mapping algorithms to offer OPC UA data to common users on the web. • Implementation of the proposed platform. The source code is available on Github at the address. https://github.com/OPCUAUniCT/OPCUAWebPlatformUniCT. Abstract The so-called fourth industrial revolution features the application of modern Information & Communication Technology (ICT) concepts and technologies in industrial contexts to create more flexible and innovative products and services leading to new business models and added value. The emerging Industrial Internet of Things (IIoT) is one of the main results of this revolution. One of the most known and adopted communication protocol in the context of the fourth industrial revolution is OPC UA (IEC 62541). Although this standard already combines features coming from both industrial and ICT contexts, current literature presents several approaches aimed to introduce ICT enhancements into OPC UA in order to further improve its usability in industrial environments. Some of these approaches are based on the proposal to make OPC UA RESTful, due to many advantages of RESTful services in industrial settings. OPC UA is based on a client/server architecture and adopts an information model at the server side, whose access from the client side requires knowledge of a data model, whose structure is sometimes complex, creating some difficulties for a resource-constrained device acting as client. The paper proposes the definition of a web platform able to offer access to OPC UA servers through a REST architecture. The approach presented in the paper differs from other existing solutions, mainly because it allows to realise a lightweight OPC UA RESTful interface reducing the complexity of the basic knowledge to be held by a generic user of the platform. For this reason, the solution presented allows enhancement of OPC UA interoperability towards resource-constrained devices. The web platform has been implemented and the relevant code is available on GitHub. [ABSTRACT FROM AUTHOR]

It is shown that many systems of nonlinear differential equations of interest in various fields are naturally embedded in a new family of differential equations. In this paper, we improve new and effective methods for nonautonomous systems and they produce new exact solutions to some important biological systems. The exact solution of predator and prey population for different particular cases has been derived. The numerical examples show that new exact solutions can be obtained for many biological systems such as SIR model, Lotka–Volterra model. The methods perform extremely well in terms of efficiency and simplicity to solve this historical biological models. The Lotka–Volterra nonlinear differential equations for two competing species, namely X and Y, contain six independent parameters. Their general analytic solutions, valid for arbitrary values of the parameters, are at present unknown. However, when two or more of these parameters are interrelated, it is possible to obtain the exact solutions in the X, Y phase plane, and six cases of solvability are given in this paper. The dependence of the solutions on the parameters and the initial conditions can thus be readily investigated. [ABSTRACT FROM AUTHOR]

This paper deals with range-only simultaneous localization and mapping (RO-SLAM), which is of particular interest in aerial robotics where low-weight range-only devices can provide a complementary continuous estimation between robot and landmarks when using radio-based sensors. Range-only sensors work at greater distances when compared to other commonly used sensors in aerial robotics and they are low-cost. However, the spherical shell uniform distribution inherent to range-only observations poses significant technological challenges, restricting the approaches that can be used to solve this problem. This paper presents an undelayed multi-hypothesis Extended Kalman Filter (EKF) approach based on Gaussian Mixture Models (GMM) and a reduced parameterization of the state vector to improve its efficiency. The paper also proposes a new robot-to-landmark and landmark-to-landmark range-only observation model for EKF-SLAM which takes advantage of the reduced parameterization. Finally, a new scheme is proposed for updating hypothesis weights based on an independence of beacon parameters. The method is firstly validated with simulations comparing the results with other state-of-the-art methods and later validated with real experiments for 3D RO-SLAM using several radio-based range-only sensors and an aerial robot. [ABSTRACT FROM AUTHOR]

This study investigates the use, citation and diffusion of three bibliometric mapping software tools (CiteSpace, HistCite and VOSviewer) in scientific papers. We first conduct a content analysis of a sample of 481 English core journal papers—i.e., papers from journals deemed central to their respective disciplines—in which at least one of these tools is mentioned. This allows us to understand the predominant mention and citation practices surrounding these tools. We then employ several diffusion indicators to gain insight into the diffusion patterns of the three software tools. Overall, we find that researchers mention and cite the tools in diverse ways, many of which fall short of a traditional formal citation. Our results further indicate a clear upward trend in the use of all three tools, though VOSviewer is more frequently used than CiteSpace or HistCite. We also find that these three software tools have seen the fastest and most widespread adoption in library and information science research, where the tools originated. They have since been gradually adopted in other areas of study, initially at a lower diffusion speed but afterward at a rapidly growing rate. [ABSTRACT FROM AUTHOR]

The Catalan numbers occur in various counting problems in combinatorics. This paper reveals a connection between the Catalan numbers and list colouring of graphs. Assume G is a graph and f : V ( G ) → N is a mapping. For a nonnegative integer m , let f ( m ) be the extension of f to the graph G K m ¯ for which f ( m ) ( v ) = | V ( G ) | for each vertex v of K m ¯ . Let m c ( G , f ) be the minimum m such that G K m ¯ is not f ( m ) -choosable and m p ( G , f ) be the minimum m such that G K m ¯ is not f ( m ) -paintable. We study the parameter m c ( K n , f ) and m p ( K n , f ) for arbitrary mappings f . For x → = ( x 1 , x 2 , … , x n ) , an x → -dominated path ending at ( a , b ) is a monotonic path P of the a × b grid from ( 0 , 0 ) to ( a , b ) such that each vertex ( i , j ) on P satisfies i ≤ x j + 1 . Let ψ ( x → ) be the number of x → -dominated paths ending at ( x n , n ) . By this definition, the Catalan number C n equals ψ ( ( 0 , 1 , … , n − 1 ) ) . This paper proves that if G = K n has vertices v 1 , v 2 , … , v n and f ( v 1 ) ≤ f ( v 2 ) ≤ … ≤ f ( v n ) , then m c ( G , f ) = m p ( G , f ) = ψ ( x → ( f ) ) , where x → ( f ) = ( x 1 , x 2 , … , x n ) and x i = f ( v i ) − i for i = 1 , 2 , … , n . Therefore, if f ( v i ) = n , then m c ( K n , f ) = m p ( K n , f ) equals the Catalan number C n . We also show that if G = G 1 ∪ G 2 ∪ ⋯ ∪ G p is the disjoint union of graphs G 1 , G 2 , … , G p and f = f 1 ∪ f 2 ∪ ⋯ ∪ f p , then m c ( G , f ) = ∏ i = 1 p m c ( G i , f i ) and m p ( G , f ) = ∏ i = 1 p m p ( G i , f i ) . This generalizes a result in Carraher et al. (2014), where the case each G i is a copy of K 1 is considered. [ABSTRACT FROM AUTHOR]

This paper addresses the disparity map estimation problem in the context of stereoscopic image coding. It is undeniable that the use of variable size blocks offers the possibility to describe more precisely the predicted view but at the expense of a high bitrate if no particular consideration is taken into account by the estimation algorithm. Indeed more information related to the block layout, considered here as a block-length map, is required at the prediction step. This paper presents an algorithm which jointly optimizes the block-length map as well as the disparity map so as to ensure a good reconstruction of the predicted view while minimizing the bitrate. This is done thanks to a joint metric taking into account the quality of the reconstruction as well as the bitrate needed to encode the maps. Moreover the developed algorithm iteratively improves its performance by refining the estimated maps. Simulation results conducted on several stereoscopic images from the CMU-VASC and the Middlebury dataset confirm the benefits of this approach as compared to competitive block matching algorithms. [ABSTRACT FROM AUTHOR]

The classification of data streams is an interesting but also a challenging problem. A data stream may grow infinitely making it impractical for storage prior to processing and classification. Due to its dynamic nature, the underlying distribution of the data stream may change over time resulting in the so-called concept drift or the possible emergence and fading of classes, known as concept evolution . In addition, acquiring labels of data samples in a stream is admittedly expensive if not infeasible at all. In this paper, we propose a novel stream-based active learning algorithm (SAL) which is capable of coping with both concept drift and concept evolution by adapting the classification model to the dynamic changes in the stream. SAL is the first AL algorithm in the literature to explicitly take account of these concepts. Moreover, using SAL, only labels of samples that are expected to reduce the expected future error are queried. This process is done while tackling the problem of sampling bias so that samples that induce the change (i.e., drifting samples or samples coming from new classes) are queried. To efficiently implement SAL, the paper proposes the application of non-parametric Bayesian models allowing to cope with the lack of prior knowledge about the data stream. In particular, Dirichlet mixture models and the stick breaking process are adopted and adapted to meet the requirements of online learning. The empirical results obtained on real-world benchmarks demonstrate the superiority of SAL in terms of classification performance over the state-of-the-art methods using average and average class accuracy. [ABSTRACT FROM AUTHOR]

Conventional neural network elastoplasticity models are often perceived as lacking interpretability. This paper introduces a two-step machine learning approach that returns mathematical models interpretable by human experts. In particular, we introduce a surrogate model where yield surfaces are expressed in terms of a set of single-variable feature mappings obtained from supervised learning. A post-processing step is then used to re-interpret the set of single-variable neural network mapping functions into mathematical form through symbolic regression. This divide-and-conquer approach provides several important advantages. First, it enables us to overcome the scaling issue of symbolic regression algorithms. From a practical perspective, it enhances the portability of learned models for partial differential equation solvers written in different programming languages. Finally, it enables us to have a concrete understanding of the attributes of the materials, such as convexity and symmetries of models, through automated derivations and reasoning. Numerical examples have been provided, along with an open-source code to enable third-party validation at https://github.com/bbhm-90/SymPolyNN. [ABSTRACT FROM AUTHOR]

Let Cl t ( A ) denote the t -class group of an integral domain A . P. Samuel has established that if A is a Krull domain then the mapping Cl t ( A ) → Cl t ( A 〚 X 〛 ) , is injective and if A is a regular UFD, then Cl t ( A ) → Cl t ( A 〚 X 〛 ) , is bijective. Later, L. Claborn extended this result in case A is a regular Noetherian domain. In the first part of this paper we prove that the mapping Cl t ( A ) → Cl t ( A 〚 X 〛 ) ; [ I ] ↦ [ ( I . A 〚 X 〛 ) t ] is an injective homomorphism and in case of an integral domain A such that each υ -invertible υ -ideal of A has υ -finite type, we give an equivalent condition for Cl t ( A ) → Cl t ( A 〚 X 〛 ) , to be bijective, thus generalizing the result of Claborn. In the second part of this paper, we define the S -class group of an integral domain A : let S be a (not necessarily saturated) multiplicative subset of an integral domain A . Following [11] , a nonzero fractional ideal I of A is S -principal if there exist an s ∈ S and a ∈ I such that s I ⊆ a A ⊆ I . The S -class group of A , S - Cl t ( A ) is the group of fractional t -invertible t -ideals of A under t -multiplication modulo its subgroup of S -principal t -invertible t -ideals of A . We generalize some known results developed for the classic contexts of Krull and P υ MD domain and we investigate the case of isomorphism S - Cl t ( A ) ≃ S - Cl t ( A 〚 X 〛 ) . [ABSTRACT FROM AUTHOR]

In this paper, we give a classification of orientation reversing periodic maps on closed surfaces which generalizes the theory of Nielsen for the orientation preserving periodic maps. On one hand, we give a collection of data for each orientation reversing periodic map such that two periodic maps with the same data must be conjugate to each other. On the other hand, we give the criterion to judge when two different collections of data correspond to the same conjugacy class. As an application of the results of this paper, we shall show that a given orientation reversing periodic map on Σ g with period larger than or equal to 3 g must be conjugate to the power of a list of particular types of periodic maps. [ABSTRACT FROM AUTHOR]

Aiming at the problem of mismatch between real-time data distribution and modeling data distribution caused by the change of working conditions in industrial process, which leads to the performance deterioration of the soft sensor model, a multi-source unsupervised soft sensor method based on joint distribution alignment and mapping structure preservation is proposed. Firstly, the method uses the hypergraph to establish the complex structure of feature and label, and clusters the hypergraph matrix in multiple views to completely construct the class pseudo label; then dynamic distribution alignment is used to adapt marginal distribution and conditional distribution between the data of historical working conditions and the current working conditions, and the hypergraph Laplacian operator is introduced for manifold regularization to prevent the mapping relationship between feature and label from being destroyed; finally, similar working conditions are introduced to further enhance the robustness of the model. The experimental results show that compared with the traditional unsupervised soft sensor methods, the method used in this paper can effectively improve the prediction accuracy of the model. • DASP constructs pseudo label to dynamically distribute adapt the continuous regression data. • The new label can retain the mapping relationship between the original data feature and label. • Several experimental results verify the effectiveness of the method. [ABSTRACT FROM AUTHOR]

Time series data have grown at an explosive rate in numerous domains and have stimulated a surge of time series modeling research. A comprehensive comparison of different time series models, for a considered data analytics task, provides useful guidance on model selection for data analytics practitioners. Data scarcity is a universal issue that occurs in a vast range of data analytics problems, due to the high costs associated with collecting, generating, and labeling data as well as some data quality issues such as missing data. In this paper, we focus on the temporal classification/regression problem that attempts to build a mathematical mapping from multivariate time series inputs to a discrete class label or a real-valued response variable. For this specific problem, we identify two types of scarce data: scarce data with small samples and scarce data with sparsely and irregularly observed time series covariates. Observing that all existing works are incapable of utilizing the sparse time series inputs for proper modeling building, we propose a model called sparse functional multilayer perceptron (SFMLP) for handling the sparsity in the time series covariates. The effectiveness of the proposed SFMLP under each of the two types of data scarcity, in comparison with the conventional deep sequential learning models (e.g., Recurrent Neural Network, and Long Short-Term Memory), is investigated through mathematical arguments and numerical experiments. [ABSTRACT FROM AUTHOR]

In this paper, we modify the general iterative method to approximate a common element of the set of solutions of split variational inclusion problem and the set of common fixed points of a finite family of k -strictly pseudo-contractive nonself mappings. Strong convergence theorem is established under some suitable conditions in a real Hilbert space, which also solves some variational inequality problems. Results presented in this paper may be viewed as a refinement and important generalizations of the previously known results announced by many other authors. Finally, some examples to study the rate of convergence and some illustrative numerical examples are presented. [ABSTRACT FROM AUTHOR]

In an earlier paper we argued that the concept of multisets should be based on families, that is, on sets and functions between sets, rather than, as usual, on sets and cardinal numbers. We showed how certain fundamental problems regarding the distinguishablity of objects as well as unexpected anomalies of the basic operations of union, intersection, and complement can be avoided elegantly using families rather than multisets. On the other hand, there is a trivial mapping of families to multisets. Hence, using families does not introduce any significant formal complications. The difficulties with the usual definition of multisets by multiplicities reach beyond the philosophical or metamathematical foundations. For the basic operations one can find acceptable compromises. For higher-level set constructs like Cartesian products, projections, relations, functions, or the power set the multiset counterparts are rather contrived, and many of the constructions leave the strict definition of multisets, actually introducing family-like constructs through a back door. In the earlier paper we proposed to use families instead of multisets to resolve the basic problems. In this paper we show that families instead of multisets support the higher-level constructions even, when no appropriate multiset-based constructions exist. We also show that multisets form a category and that the natural mapping from families to multisets is a functor. This emphasizes our claim that, for a definition of multisets, one should start with families and only introduce multiplicities as a secondary concept. [ABSTRACT FROM AUTHOR]

Expert Cloud as a new class of Cloud computing systems enables its users to request the skill, knowledge and expertise of people without any information of their location by employing Internet infrastructures and Cloud computing concepts. Effective load balancing in a heterogeneous distributed environment such as Cloud is important. Since the differences in the human resource (HRs) capabilities and the variety of users' requests causes that some HRs are overloaded and some others are idle. The task allocation to the HR based on the announced requirements by the user may cause the imbalanced load distribution among HRs as well. Hence resource management and scheduling are among the important cases to achieve load balancing. Using static and dynamic algorithms, the ant colony, and the method based on searching tree all are among the methods to achieve load balancing. This paper presents a new method in order to distribute the dynamic load based on distributed queues aware of service quality in the Cloud environment. In this method, we utilize the colorful ants as a ranking for making distinction among the HRs capabilities. In this paper, we perform the mapping among the tasks and HRs using allocating a label to each HR. We model the load balancing and mapping process based on Poisson and exponential distribution. This model allows us to allocate each task to the HR which is able to execute it with maximum power using the distributed queues aware of the service quality. Simulation results show that the expert Cloud can reduce the execution and tardiness time and improve HR utilization. The cost of using resources as an effective factor in load balancing is also observed. [ABSTRACT FROM AUTHOR]

There are users and organizations that resist adopting cloud computing solutions, due to concerns about the security and privacy of their data. A Service Level Agreement (SLA) can be used to address these concerns, increasing trust in the purchased services through the clear description of the guarantees offered by the provider to the subscribers. For this purpose, the authors performed a literature systematic mapping to enumerate existing solutions and open issues in security SLAs in cloud computing. This review is presented in this paper as well as an analysis of the state of art. This paper also presents a classification of the selected papers and a discussion about management of security SLAs in clouds. [ABSTRACT FROM AUTHOR]

A set of five manuscripts written by Sister Lúcia between 1941 and 1944 were under study. Among them is the one that contains the description of the third part of the Secret of Fátima also known as the Third Secret of Fátima. In this work, a characterization of the paper and the ink used in these documents was achieved using micro-X-ray fluorescence spectrometry. Quantitative results were obtained for P, K, Ca, Fe, Cu and Zn, revealing different paper composition and Zn in the inks. 2D elemental maps confirmed that Zn was present in the five documents ink and that the manuscript revealing the Third Secret of Fátima contained no erasures or alteration attempts to the original manuscript. [ABSTRACT FROM AUTHOR]

The main purpose of this paper is to revisit the proximal point algorithms with over-relaxed A -maximal m -relaxed monotone mappings for solving variational inclusions in Hilbert spaces without Lipschitz continuity requirement to overcome the drawbacks of the paper (Verma, 2009) [5] . We affirmatively answer the open question mentioned in the paper (Huang and Noor, 2012) [6] . [ABSTRACT FROM AUTHOR]

In this paper, we introduce and study a new viscosity approximation method based on the conjugate gradient method and an averaged mapping approach for finding a common element of the set of solutions of a constrained convex minimization problem and the set of solutions of a split variational inclusion problem. Under suitable conditions, we prove that the sequences generated by the proposed iterative method converge strongly to a common solution of the split variational inclusion problem and the set of solutions of the constrained convex minimization problem. The results presented in this paper are the supplement, extension and generalization of the previously known results in this area. Finally, preliminary numerical results indicate the feasibility and efficiency of the proposed methods. [ABSTRACT FROM AUTHOR]

Distributed systems exhibit probabilistic and non-deterministic behaviors and may have time constraints. Probabilistic Timed Rebeca (PTRebeca) is introduced as a timed and probabilistic actor-based language for modeling distributed real-time systems with asynchronous message passing. The semantics of PTRebeca is a Timed Markov Decision Process. In this paper, we provide SOS rules for PTRebeca, introduce a new tool-set and describe the corresponding mappings. The tool-set automatically generates a Markov Automaton from a PTRebeca model in the form of the input language of the Interactive Markov Chain Analyzer (IMCA). The IMCA can be used as a back-end model checker for performance analysis of PTRebeca models against expected reachability and probabilistic reachability properties. Comparing to the existing tool-set, proposed in the conference paper, we now have the ability of analyzing significantly larger models, and we also can add different rewards to the model. We show the applicability of our approach and efficiency of our tool by analyzing a Network on Chip architecture as a real-world case study. [ABSTRACT FROM AUTHOR]

Given an arbitrary set T in the Euclidean space whose elements are called sites, and a particular site s , the Voronoi cell of s , denoted by V T ( s ) , consists of all points closer to s than to any other site. The Voronoi mapping of s , denoted by ψ s , associates to each set T ∋ s the Voronoi cell V T ( s ) of s w.r.t. T . These Voronoi cells are solution sets of linear inequality systems, so they are closed convex sets. In this paper we study the Voronoi inverse problem consisting in computing, for a given closed convex set F ∋ s , the family of sets T ∋ s such that ψ s ( T ) = F . More in detail, the paper analyzes relationships between the elements of this family, ψ s − 1 ( F ) , and the linear representations of F , provides explicit formulas for maximal and minimal elements of ψ s − 1 ( F ) , and studies the closure operator that assigns, to each closed set T containing s , the largest element of ψ s − 1 ( F ) , where F = V T ( s ) . [ABSTRACT FROM AUTHOR]

This paper addresses model reduction and extends balanced truncation to the class of switched affine systems with endogenous switching. The switched affine system is rewritten as a switched linear one with state resets that account for the affine terms. Balanced truncation can then be applied to each mode dynamics, independently. As a result, different reduced state vectors are associated with the different modes, and reset maps are here appropriately redefined so as to account and compensate for this mismatch, possibly preserving the continuity of the output. The overall behavior of the reduced switched system is determined by both the selected reduction per mode and the adopted reset maps. In this paper, we consider a stochastic setting and propose a randomized method for the selection of the reduced order. The performance of the proposed approach is illustrated through a multi-room temperature control example. [ABSTRACT FROM AUTHOR]

This paper presents a novel automatic polycube construction algorithm using centroidal Voronoi tessellation (CVT) based surface segmentation. Given a smooth surface triangle mesh, we segment triangles into six clusters in the surface normal space while satisfying the constraints of polycube construction. A bijective mapping between the input mesh and polycube surfaces is then built via a planar domain parameterization. We develop a new harmonic boundary-enhanced centroidal Voronoi tessellation (HBECVT) method by including local neighbouring information in the energy function. Improving upon the classic CVT method, the HBECVT algorithm can not only overcome the sensitivity to the initialization and noise, but also improve the segmentation results and the resulting polycubes by reducing non-monotone boundaries. Based on the constructed polycube, we then generate quality all-hexahedral (all-hex) meshes. The uniform all-hex mesh and volumetric T -mesh can be obtained through the octree subdivision and mapping. We can also generate adaptive all-hex meshes by extracting the dual mesh from a hybrid octree, which consists of polyhedral cells and each grid point is always shared by eight cells. Several examples are presented in this paper to show the robustness of our algorithms. [ABSTRACT FROM AUTHOR]

Tracking is an important task that is used for several applications, such as navigation assistance and augmented reality. The improvement and popularization of mobile devices in recent years allowed these applications to be executed on such devices. Thus, several tracking techniques proposed lately take into consideration the benefits and limitations of handheld devices. Therefore, the goal of this work is to perform a systematic mapping in order to provide trends and classification regarding the recent publications in the area of tracking for mobile devices. This study collected 2276 papers from three scientific databases using an open-source crawler, from which 360 were selected to be classified according to four properties: tracking type, degree of freedom, tracking platform and research type. The analysis of these data resulted in a map of the research field, which was presented under three perspectives: the distribution and trends over time of each classification property and the relationship between them. Besides the visual map, the full list of classified papers is available through an open-source web-based catalog. The results showed that the number of publications is increasing every year, which shows a growing interest in this field. Moreover, most works use the device׳s sensors for tracking in location-based applications and almost all of them calculate a 2D or 2D + θ pose. There are also several papers about vision-based techniques to compute the device׳s pose and in the majority of them a full 6D pose is computed. Beyond that, there is a clear preference for systems that calculate the pose locally on the device and only a few use a remote server to assist in this task. Moreover, more than 92% of all papers propose a new technique or use existing ones to create a solution. [ABSTRACT FROM AUTHOR]

This paper shows that generic 2D-Free-Form Deformations of degree 1 × n can be made birational by a suitable assignment of weights to the Bézier or B-spline control points. An FFD that is birational facilitates operations such as backward mapping for image warping, and Extended Free-Form Deformation. While birational maps have been studied extensively in the classical algebraic geometry literature, this paper is the first to present a family of non-linear birational maps that are flexible enough to be of practical use in geometric modeling. [ABSTRACT FROM AUTHOR]

A pseudo-Boolean function is a real-valued function f ( x ) = f ( x 1 , x 2 , … , x n ) of n binary variables, that is, a mapping from { 0 , 1 } n to R . For a pseudo-Boolean function f ( x ) on { 0 , 1 } n , we say that g ( x , y ) is a quadratization of f if g ( x , y ) is a quadratic polynomial depending on x and on m auxiliary binary variables y 1 , y 2 , … , y m such that f ( x ) = min { g ( x , y ) : y ∈ { 0 , 1 } m } for all x ∈ { 0 , 1 } n . By means of quadratizations, minimization of f is reduced to minimization (over its extended set of variables) of the quadratic function g ( x , y ) . This is of practical interest because minimization of quadratic functions has been thoroughly studied for the last few decades, and much progress has been made in solving such problems exactly or heuristically. A related paper by Anthony et al. (2015) initiated a systematic study of the minimum number of auxiliary y -variables required in a quadratization of an arbitrary function f (a natural question, since the complexity of minimizing the quadratic function g ( x , y ) depends, among other factors, on the number of binary variables). In this paper, we determine more precisely the number of auxiliary variables required by quadratizations of symmetric pseudo-Boolean functions f ( x ) , those functions whose value depends only on the Hamming weight of the input x (the number of variables equal to 1). [ABSTRACT FROM AUTHOR]

The present paper establishes a homotopy based on Marcus–Wyse (for brevity M -) topology, which can contribute to the classification of 2D digital images in an M -topological approach. Since M -topology is considered in the Euclidean 2D space with integer coordinates, it can be used in studying 2D digital images from the viewpoints of both digital topology and digital geometry such as image processing, image analysis, computer graphics, mathematical morphology and so forth. To develop the homotopy, the present paper uses two maps such as an M -continuous map and Marcus–Wyse adjacency (for brevity MA -) map because they have their own features and merits. Besides, using this homotopy, the present paper proposes an MA -homotopy equivalence and further, MA -contractibility which can be also used in classifying digital images. Finally, the paper establishes an MA -homotopic thinning derived from the above homotopy, which can contribute to the compression of 2D digital images. [ABSTRACT FROM AUTHOR]

In the first half of the paper, we are concerned with the problems of existence (and searching) of coincidence points and the common preimage of a closed subset (in particular, a common root) in the case of a finite system of mappings of one metric space to another one. The second half of the paper is devoted to fiberwise variants of Arutyunov's theorem on coincidence points. Obtaining the main results of the paper is based on the use of the class of almost exactly ( α , β ) -search functionals that is wider than Fomenko's class of ( α , β ) -search functionals. [ABSTRACT FROM AUTHOR]

In this paper, a novel approach based Hidden Markov Models (HMMs) approach is proposed for human action recognition using 3D positions of body joints. Unlike existing works, this paper addresses the challenging problem of spatio-temporal alignment of human actions which come from intra-class variability and inter-class similarity of actions. The first and foremost actions are segmented into meaningful action-units called dynamic instants and intervals by using motion velocities, the direction of motion, and the curvatures of 3D trajectories. Then action-units with its spatio-temporal feature sets are clustered using unsupervised learning, like Self-Organizing Mapping (SOM), to generate a sequence of discrete symbols. To overcome an abrupt change or an abnormal in its gesticulation between different appearances of the same kind of action, profile HMMs are applied with these symbol sequences using Viterbi and Baum–Welch algorithms for human activity recognition. The effectiveness of the proposed method is evaluated on three challenging 3D action datasets captured by commodity depth cameras. The experimental evaluations show that the proposed approach achieves promising results compared to other state-of-the-art algorithms. [ABSTRACT FROM AUTHOR]

This paper presents a substantially simplified axiomatization of Map Theory and proves the consistency of this axiomatization (called MT) in ZFC under the assumption that there exists an inaccessible ordinal. Map Theory axiomatizes lambda calculus plus Hilbert's epsilon operator. All theorems of ZFC set theory including the axiom of foundation are provable in Map Theory, and if one omits Hilbert's epsilon operator from Map Theory then one is left with a computer programming language. Map Theory fulfills Church's original aim of lambda calculus. Map Theory is suited for reasoning about classical mathematics as well as computer programs. Furthermore, Map Theory is suited for eliminating the barrier between classical mathematics and computer science rather than just supporting the two fields side by side. Map Theory axiomatizes a universe of “maps”, some of which are “wellfounded”. The class of wellfounded maps in Map Theory corresponds to the universe of sets in ZFC. The first axiomatization MT 0 of Map Theory had axioms which populated the class of wellfounded maps, much like the power set axiom along with others populate the universe of ZFC. The new axiomatization MT of Map Theory is “synthetic” in the sense that the class of wellfounded maps is defined inside Map Theory rather than being introduced through axioms. In the paper we define the notions of canonical and non-canonical κ - and κσ -expansions and prove that if σ is the smallest strongly inaccessible ordinal then canonical κσ -expansions are models of MT (which proves the consistency). Furthermore, in Appendix A , we prove that canonical ω -expansions are fully abstract models of the computational part of Map Theory. [ABSTRACT FROM AUTHOR]

This paper describes a methodology to obtain a land cover dataset for a selected Subcarpathian area from Prahova County, Romania. It proposes a combined Remote Sensing, GIS and Cartography approaches in order to produce an accurate land cover layer at regional and local scales for an area where the land cover features are various and complicated in configuration. The area between Prahova and Teleajen rivers is characterized by complex landforms as hills and depressions with active and dynamic geomorphic processes. This paper presents a model integrating a supervised classification derived from Landsat OLI images with currently available land cover models, as well as GIS processing results of data fusion and cartographic techniques for feature representation on the map, at different scales. Another research direction was to use some normalized differenced indices to separate the spectral classes, and to assess and validate the results from the classification. Land cover map was obtained using: 1) land cover classes derived from supervised classification of Landsat 8 OLI image data, and; b) land cover features extracted from two land cover models (CORINE Land Cover and GlobeLand30), integrated with the classification dataset. The results were confronted and validated with ground truth points generated from orthophotos and other satellite images. The layouts are generated at different scales in order to compare and validate the land cover categories. [ABSTRACT FROM AUTHOR]

This paper addresses set invariance properties for linear time-delay systems. More precisely, the first goal of the article is to review known necessary and/or sufficient conditions for the existence of invariant sets with respect to dynamical systems described by linear discrete time-delay difference equations (dDDEs). Secondly, we address the construction of invariant sets in the original state space (also called D -invariant sets) by exploiting the forward mappings. The notion of D -invariance is appealing since it provides a region of attraction, which is difficult to obtain for delay systems without taking into account the delayed states in some appropriate extended state space model. The present paper contains a sufficient condition for the existence of ellipsoidal D -contractive sets for dDDEs, and a necessary and sufficient condition for the existence of D -invariant sets in relation to linear time-varying dDDE stability. Another contribution is the clarification of the relationship between convexity (convex hull operation) and D - invariance of linear dDDEs. In short, it is shown that the convex hull of the union of two or more D - invariant sets is not necessarily D - invariant , while the convex hull of a non-convex D - invariant set is D - invariant . [ABSTRACT FROM AUTHOR]

This paper presents the new investigations on the disturbance decoupling problem (DDP) for the geometric control of max-plus linear systems. The classical DDP concept in the geometric control theory means that the controlled outputs will not be changed by any disturbances. In practical manufacturing systems, solving for the DDP would require further delays on the output parts than the existing delays caused by the system breakdown. The new proposed modified disturbance decoupling problem (MDDP) in this paper ensures that the controlled output signals will not be delayed more than the existing delays caused by the disturbances in order to achieve the just-in-time optimal control. Furthermore, this paper presents the integration of output feedback and open-loop control strategies to solve for the MDDP, as well as for the DDP. If these controls can only solve for the MDDP, but not for the DDP, an evaluation principle is established to compare the distance between two output signals generated by controls solving for the MDDP and DDP, respectively. This distance can be interpreted as the number of tokens or firings that are needed in order for the controls to solve for the DDP. Moreover, another alternative approach is finding a new disturbance mapping in order to guarantee the solvability of the DDP by the same optimal control for the MDDP. The main results of this paper are illustrated by using a timed event graph model of a high throughput screening system in drug discovery. [ABSTRACT FROM AUTHOR]

In this paper, we introduce and study a generalized vector complementarity problem with fuzzy mappings. Under suitable conditions, we have shown that generalized vector complementarity problem with fuzzy mappings is equivalent to generalized vector variational inequality problem with fuzzy mappings. We derive some existence results for our problem. Results of this paper represent a significant improvement and refinement of the previously known results. [ABSTRACT FROM AUTHOR]

The present paper establishes two new maps such as an M -map and an M -isomorphism which are generalizations of a Marcus Wyse (for brevity, M -) continuous map and an M -homeomorphism because an M -continuous map is so rigid that some geometric transformations are not M -continuous maps (see Remark 3.2 ). Furthermore, it proves that in Z 2 an M -map and an M -isomorphism are equivalent to a (digitally) 4-continuous map and a (digitally) 4-isomorphism, respectively. Besides, the paper proves that SC MA l 1 is M -isomorphic to SC MA l 2 if and only if l 1 = l 2 , where SC MA l means a simple closed Marcus Wyse adjacent (for brevity, MA -) curve with l elements in Z 2 . Finally, the paper proves that MAC is equivalent to DTC ( 4 ) (see Theorem 6.7 ), where MAC is the category whose objects are M -topological spaces ( X , γ X ) with MA -adjacency and morphisms are all M -maps f : ( X , γ X ) → ( Y , γ Y ) for every ordered pair of objects ( X , γ X ) and ( Y , γ Y ) , and DTC ( 4 ) is the category whose objects are digital images ( X , k ) in Z 2 and morphisms are (digitally) 4-continuous maps. Besides, we propose the notion of an MA -retract for compressing 2D digital spaces. Using this new approach, we can substantially study and classify 2D digital topological spaces and 2D digital images. [ABSTRACT FROM AUTHOR]

Business models (BMs) describe how a company creates and delivers value to customers, the products or services that it offers and the compensation for them. Software companies need to be able to adopt different BMs to be successful in modern economy. Despite the number of publications on the field, there is still not a clear picture of software BMs. The purpose of this study is to structure and characterize the state of the art on software BMs with focus on sales and distribution models to help discover possible research gaps. The authors of this study conducted a systematic mapping study using relevant keywords to identify primary studies in the existing literature related to software BMs from a business management perspective. The search strategy returned 1871 papers and 51 were selected as primary studies. The analysis of results helps clarify the picture of software BMs and highlights the most relevant sources of papers. Results also reveal the broad interest of researchers on this topic. Most of the primary studies were related to service-based BMs, and to a lesser extent on product-based or open-source-based BMs; there is also an increase in the attention of researchers towards models built around mobile apps. While many authors report experience papers, only some authors validate or evaluate new proposals of sales and distribution models. [ABSTRACT FROM AUTHOR]

In this paper, we propose a deep neural network (DNN) architecture called Input Output Deep Architecture (IODA) for solving the problem of image labeling. IODA directly links a whole image to a whole label map, assigning a label to each pixel using a single neural network forward step. Instead of designing a handcrafted a priori model on labels (such as an atlas in the medical domain), we propose to automatically learn the dependencies between labels. The originality of IODA is to transpose DNN input pre-training trick to the output space, in order to learn a high level representation of labels. It allows a fast image labeling inside a fully neural network framework, without the need of any preprocessing such as feature designing or output coding. In this paper, IODA is applied on both a toy texture problem and a real-world medical image dataset, showing promising results. We provide an open source implementation of IODA. 1 1 http://mloss.org/software/view/562/ , 2 2 https://github.com/jlerouge/crino [ABSTRACT FROM AUTHOR]