In multicategory classification, an estimated generalization error is often used to quantify a classifier’s generalization ability. As a result, quality of estimation of the generalization error becomes crucial in tuning and combining classifiers. This article proposes an estimation methodology for the generalization error, permitting a treatment of both fixed and random inputs, which is in con...

The measurement of RTS amounts measures a relationship between inputs and outputs in a production structure. There are many different ways to calculate RTS in primal or dual space. But in more realistic cases, governments usually intervene on DMU’s behavior as regulatory agency, this clearly represent a set of limitations and restrictions on behaviors of DMUs, So very few decisions in DMUs are ...

We evaluate, by means of mathematical programming formulations, the relative technical and scale efficiencies of decision making units (DMUs) when some of the inputs or outputs are exogenously fixed and beyond the discretionary control of DMU managers. This approach further develops the work on efficiency evaluation and on estimation of efficient production frontiers known as data envelopment a...

In traditional data envelopment analysis (DEA) the uncertainty of inputs and outputs is not considered when evaluating the performance of a unit. In other words, effects of uncertainty on optimality and feasibility of models are ignored. This paper introduces a new model for measuring the efficiency of decision making units (DMUs) having interval inputs and outputs. The proposed model is based ...

In this paper a family of homogeneity–based observers is proposed to estimate the state class multiple–outputs linear systems with some parametric uncertainties and unknown inputs. Such possesses robustness, finite– fixed–time convergence properties depending on considered The structure these simple since requires neither additional observers, for an priori stabilization, nor complex transforma...

Parallelism may reside in the input of a program rather than the program itself. A script interpreter, for example, is hard to parallelize because its dynamic behavior is unpredictable until an input script is given. Once the interpreter is combined with the script, the resulting program becomes predictable, and even parallelizable if the input script contains parallelism. Despite recent progre...