In this paper, we study the problem of facial expression recognition using a novel space-time geometric representation. We describe the temporal evolution of facial landmarks as parametrized trajectories on the Riemannian manifold of positive semidefinite matrices of fixed-rank. Our representation has the advantage to bring naturally a second desirable quantity when comparing shapes – the spati...

We present a novel and efficient technique to extract Lagrangian coherent structures in two-dimensional time-dependent vector fields. We show that this can be achieved by employing bifurcation line extraction in the space-time representation of the vector field, and generating space-time bifurcation manifolds therefrom. To show the utility and applicability of our approach, we provide an evalua...

We performed two experiments with statistical techniques for classifying documents by date and author, using large bodies of publicly-available texts. In one experiment, we produced a Markov chain of every United States Supreme Court opinion ever written, and evaluated its ability to classify American judicial opinions by decade of authorship. In the other, we examined the performance of two se...

We present a novel network-based continuous-time formulation for process scheduling that addresses multiple limitations of existing approaches. Specifically, it handles nonsimultaneous transfers of input/output materials to/from processing units; it employs a more flexible time representation; and it explicitly accounts for unit connectivity. This is accomplished via the modelling of two key is...

The contribution of this paper is twofold. On the one hand, it introduces T DLR, a novel temporal logic for temporal conceptual modelling, motivated as the obvious generalisation of the successful DLR Description Logic. Tight decidability and complexity results are proved for T DLR and the monodic fragment of it (T DLR ). Moreover, the decidability of conjunctive query containment under T DLR c...

This paper presents a Workflow Mining new paradigm. This paradigm keeps in mind on one side the processes,and on the other hand the results given by these processes themselves. This is a contrast between the Event-Based Workflow Mining and the one it is presented in this paper. Finite Automata are a good idea to represent this paradigm to take profit of the theoretical advantages of the Regular...

Abstract In the current work, a new precedence-based mixed integer linear programming (MILP) scheduling framework, based on a continuous-time representation, is developed for the scheduling in multi-stage batch plants. Advantages and special features of the proposed scheduling model are highlighted through several instances of two base case studies. Results are analyzed and further criticized t...

This paper suggests a new technique to construct first order Markov processes using products of copula functions, in the spirit of Darsow et al. (1992). The approach requires the definition of: i) a sequence of distribution functions of the increments of the process; ii) a sequence of copula functions representing dependence between each increment of the process and the corresponding level of t...

An enhanced continuous-time formulation is presented for the short-term scheduling of multipurpose batch plants with intermediate due dates. The proposed formulation is based on the continuous-time formulation introduced by Ierapetritou and Floudas (Ind. Eng. Chem. Res. 1998, 37, 4341 and 4360) and incorporates and elaborates on several features that include (i) various storage policies (UIS, F...

The notion of time granularity comes into play in a variety of problems involving time representation and management in database applications, including temporal database design, temporal data conversion, temporal database inter-operability, temporal constraint reasoning, data mining, and time management in workflow systems. According to a commonly accepted view, any time granularity can be vie...