For a social robot, the ability of learning tasks via human demonstration is very crucial. But most current approaches suffer from either the demanding of the huge amount of labeled training data, or the limited recognition cabability caused by very domain-specific modeling. This paper puts forward a semi-supervised incremental strategy for the robot to learn the manipulative tasks performed by...

This study aimed at presenting a method for formulating optimal production, repair and replacement policies. The system was based on the production rate of defective parts and machine repairs and then was set up to optimize maintenance activities and related costs. The machine is either repaired or replaced. The machine is changed completely in the replacement process, but the productio...

this paper is devoted to the study of determining optimal process mean in system production with the two markets for the sale of goods. in this paper, we developed an absorbing markov chain model in production systems where all items are inspected %100 for conformance with their specification limits. when the value of the quality characteristic of an item falls below a lower limit, the item is ...

High-level semi-Markov modelling paradigms such as semi-Markov stochastic Petri nets and process algebras are used to capture realistic performance models of computer and communication systems but often have the drawback of generating huge underlying semi-Markov processes. Extraction of performance measures such as steady-state probabilities and passage-time distributions therefore relies on sp...

In this paper, we investigate the use of hidden semi-Markov models (HSMMs) in analyzing data of human activities, a task commonly referred to as activity recognition. In particular, we use the models to recognize normal and abnormal twodimensional joystick-generated movements of a cursor, controlled by human users in a computerized clinical maze task. This task – as many other activity recognit...

We consider semiparametric models of semi-Markov processes with arbitrary state space. Assuming that the process is geometrically ergodic, we characterize efficient estimators, in the sense of Hájek and Le Cam, for arbitrary real-valued smooth functionals of the distribution of the embedded Markov renewal process. We construct efficient estimators of the parameter and of linear functionals of t...

This paper proposes a boosting algorithm that uses a semi-Markov perceptron. The training algorithm repeats the training of a semi-Markov model and the update of the weights of training samples. In the boosting, training samples that are incorrectly segmented or labeled have large weights. Such training samples are aggressively learned in the training of the semi-Markov perceptron because the w...

Problems related to the exit of a process with independent increments from an interval were investigated in many works (see, e.g. [1], [2]). Analogous problems were investigated for processes on a finite Markov chain under the semicontinuity condition [3, 4]. For walks on a countable Markov chain, a two-dimensional problem was studied in [5]. In the present paper, we consider distributions of s...

We prove that if a right Markov process is associated with a semi-Dirichlet form, then the form is necessarily quasi-regular. As an applications, we develop the theory of Revuz measures in the semi-Dirichlet context and we show that quasi-regularity is invariant with respect to time change.

In this paper we give a necessary and sufficient condition for the mean stability of switched linear systems having a Markov regenerative process as its switching signal. This class of switched linear systems, which we call Markov regenerative switched linear systems, includes various switched linear systems including Markov jump linear systems and semi-Markov jump linear systems. We show that ...