data envelopment analysis (dea) is one of the scientific method that computes the efficiency by using a powerful mathematics basic. data envelopment analysis is a non-parametric technique to evaluate the efficiency of a set of decision making units (dmu) with multi inputs and outputs . since dea’s models classifies decision making units into two categories of efficient and inefficient, so most ...

Methods: This was a descriptive and prospective study , the applied instrument was the Spanish Red Cross Scales. The above mentioned evaluation was completed by applying a second instrument for social evaluation described by Marin et al in Chile in 1994. Besides, other general information was collected from the studied population such as: environmental, family, and social conditions. A group of...

The structural approach of credit risk modeling has gained growing attention in both academics and industry. While there has been increasing effort in testing the structural models for credit derivatives pricing, little result has been shown on the default prediction of the structural models. In this paper, we compare comprehensively various credit structural models for their default prediction...

Risk is mitigated in the course of reliable prediction. A probabilistic model is proposed to predict the risk effects on time and cost of construction projects. Project managers and consultants can use the model in estimating project cost and duration based on historic data. Statistical regression models and sample tests are developed using real data of 140 projects. The research objective is t...

Partition of unity parametrics (PUPs) are a recent framework designed for geometric modeling. We propose employing PUPs for procedural texture synthesis, taking advantage of the framework’s guarantees of high continuity and local support. Using PUPs to interpolate among data values distributed through the plane, the problem of texture synthesis can be approached from the perspective of point pl...

The problem of fitting a parametric model in Tobit errors-in-variables regression models is discussed in this paper. The proposed test is based on the supremum of the Khamaladze type transformation of a certain partial sum process of calibrated residuals. This framework covers the usual error-free Tobit model as a special case. The asymptotic null distribution of this transformed process is sho...

Keywords: parametric, classifier, similarity-based. A parametric classifier builds class models and classifies test points as being from classes that they are most likely to belong to, given the class models. Over the summer, I worked with Professor to develop a parametric classifier that builds models based on only the similarity between samples. The parametric clas-sifier was compared to othe...