This paper addresses refinement and testing based on CSP models, when we distinguish input and output events. From a testing perspective, there is an asymmetry: the tester (or the environment) controls the inputs, and the system under test controls the outputs. The standard models and refinement relations of CSP are, therefore, not entirely suitable for testing. Here, we adapt the CSP stable-fa...

Monotone systems constitute one of the most important classes of dynamical systems used in mathematical biology modeling. The objective of this paper is to extend the notion of monotonicity to systems with inputs and outputs, a necessary first step in trying to understand interconnections, especially including feedback loops, built up out of monotone components. Basic definitions and theorems a...

This paper studies testing based on labelled transition systems , using the assumption that implementations communicate with their environment via inputs and outputs. Such implementations are formalized by restricting the class of transition systems to those systems that can always accept input actions, as in input/output automata. Implementation relations, formalizing the notion of conformance...

Performance measurement with undesirable outputs is an important subject in production processes. There are papers in which works can be divided into two groups. First group develops production models which undesirable outputs are considered as inputs and in second one undesirable outputs are modeled as outputs. We provide a comparison between these two groups and we axiomatically show that pro...

Most of the research in online learning is focused either on the problem of adversarial classification (i.e., both inputs and labels are arbitrarily chosen by an adversary) or on the traditional supervised learning problem in which samples are independent and identically distributed according to a stationary probability distribution. Nonetheless, in a number of domains the relationship between ...

in this article, non radial method of dynamic dea with the parallel network structure is presented and is used for calculation of relative efficiency measures when inputs and outputs do not change equally. in this model, dmu divisions under evaluation have been put together in parallel. but its dynamic structure is assumed in series. since in real applications there are undesirable inputs and o...

In supervised learning there is usually a clear distinction between inputs and outputs inputs are what you will measure, outputs are what you will predict from those measurements. This paper shows that the distinction between inputs and outputs is not this simple. Some features are more useful as extra outputs than as inputs. By using a feature as an output we get more than just the case values...

In this paper, by introducing two virtual decision-making units (DMUs) called ideal DMU (IDMU) and anti-ideal DMU (ADMU) with fuzzy inputs-outputs, the efficiency evaluation of DMUs are done by fuzzy data envelopment analysis (FDEA). Therefore, we evaluate DMUs from the perspective of the best and worst possible relative efficiency. For each DMU two efficiencies are calculated while inputs and ...