We study a particular digraph dynamical system, the so called digraph diclique operator. Dicliques have frequently appeared in the literature the last years in connection with the construction and analysis of different types of networks, for instance biochemical, neural, ecological, sociological and computer networks among others. Let D=(V,A) be a reflexive digraph (or network). Consider X and Y (not necessarily disjoint) nonempty subsets of vertices (or nodes) of D. A disimplex K(X,Y) of D is the subdigraph of D with vertex set X ∪ Y and arc set {(x,y)∶ x ∈ X, y ∈ Y\} (when X ∩ Y ≠ ∅, loops are not considered). A disimplex K(X,Y) of D is called a diclique of $D$ if $K(X,Y)$ is not a proper subdigraph of any other disimplex of D. The diclique digraph $\overrightarrow {k}(D) of a digraph $D$ is the digraph whose vertex set is the set of all dicliques of $D$ and ( K(X,Y),K(X',Y'))$ is an arc of $\overrightarrow {k}(D) if and only if Y ∩ X' ≠ ∅. We say that a digraph $D$ is self-diclique if $\overrightarrow {k}(D)$ is isomorphic to D. In this paper, we provide a characterization of the self-diclique circulant digraphs and an infinite family of non-circulant self-diclique digraphs.
The presented study deals with an object-relation mental model of drivers reasoning. The model stands on logic positions and brings a degree of logical proving into advanced microscopic models of road traffic. The future improvement of microscopic simulation is possible only by improvement of driver's behavior models, applying mental models of human drivers. The works are based on many sources: robotics, mathematical logic, cognitive science, computer science (ontologies, object oriented representation), and psychological researches from the fields of mental capacity, human problem solving, etc.
Semantic analysis of multimedia content is an ongoing research area that has gained a lot of attention over the last few years. Additionally, machine learning techniques are widely used for multimedia analysis with great success. This work presents a combined approach aiming at the semantic adaptation of neural network classifiers in a multimedia framework. Our proposal is based on a fuzzy reasoning engine which is able to evaluate the outputs and the confidence levels of the neural network classifier, using a domain specific knowledge base. The results obtained by the fuzzy reasoning engine are used as input for the adaptation of the network classifier, further increasing its ability to provide accurate classification of the specific content. The improved performance of the adapted neural network is used by a semantic segmentation algorithm that merges neighbouring regions satisfying certain criteria. In that way, fine image segmentation and classification are established.
Contextual word prominence in a text is a consequence of the functional relationship between word frequency and text segmentation. This probabilistic function is formalized in quantitative linguistics as Menzerath-Altmann´s law. When this law is applied not only to a text as a whole, but also to individual lexical units which, within contextual boundaries, are transformed into word forms, two contextual levels are formed from each text structure: a segmental and a textual level. On these two levels, the interaction between words can be characterized as the semantic specification of the lexical units. The contextual characteristics of individual words are defined as their contextual weights. The maximum value of this variable, proper to a given frequency, belongs to a set that forms a Menzerathian curve, i.e. a curve that complies with the basic principle of text structures. This curve can be treated as a semantic attractor.
The verbo-nominal syntagmas in Hindī represent multi-word naming units of action, process or state. They are developed from some more complex syntactic structures also including other functional words (postpositions and postpositional phrases, adverbs etc.). As condensed structures/formations they include a noun or an adjective and a functional verb. There is a set of verbs, which lost their original meaning (light verbs) and have a verbalizing function. The VNS-es as naming units in their semantic structure and development include several types. As literal VNS-es they are easily comprehensible, since the nominal and the verbal constituents signalize the meaning of the syntagma sufficiently clearly. In other types of VNS-es at least one constituent shifts its original meaning and different types or stages of metaphoric and idiomatic syntagmas arise. The metaphor is a poetic and stylistic figure; nevertheless many metaphors become semantic units denoting verbal action/process/state.
Recently, Drygaś generalized nullnorms and t-operators and introduced semi-t-operators by eliminating commutativity from the axiom of t-operators. This paper is devoted to the study of the discrete counterpart of semi-t-operators on a finite totally ordered set. A characterization of semi-t-operators on a finite totally ordered set is given. Moreover, The relations among nullnorms, t-operators, semi-t-operators and pseudo-t-operators (i. e., commutative semi-t-operators) on a finite totally ordered set are shown.
We characterize some bivariate semicopulas and, among them, the semicopulas satisfying a Lipschitz condition. In particular, the characterization of harmonic semicopulas allows us to introduce a new concept of depedence between two random variables. The notion of multivariate semicopula is given and two applications in the theory of fuzzy measures and stochastic processes are given.
Using recent results on measure theory and algebraic geometry, we show how semidefinite programming can be used to construct invariant measures of one-dimensional discrete dynamical systems (iterated maps on a real interval). In particular we show that both discrete measures (corresponding to finite cycles) and continuous measures (corresponding to chaotic behavior) can be recovered using standard software.
A Riemannian manifold is said to be semisymmetric if $R(X,Y)\cdot R=0$. A submanifold of Euclidean space which satisfies $\bar{R}(X,Y)\cdot h=0$ is called semiparallel. It is known that semiparallel submanifolds are intrinsically semisymmetric. But can every semisymmetric manifold be immersed isometrically as a semiparallel submanifold? This problem has been solved up to now only for the dimension 2, when the answer is affirmative for the positive Gaussian curvature. Among semisymmetric manifolds a special role is played by the foliated ones, which in the dimension 3 are divided by Kowalski into four classes: elliptic, hyperbolic, parabolic and planar. It is shown now that only the planar ones can be immersed isometrically into Euclidean spaces as 3-dimensional semiparallel submanifolds. This result is obtained by a complete classification of such submanifolds.