International Journal of Industrial Mathematics
Volume:9 Issue: 4, Autumn 2017

G-frames are natural generalizations of frames which provide more choices on analyzing functions from frame expansion coefficients. First, they were defined in Hilbert spaces and then generalized on C*-Hilbert modules. In this paper, we first generalize the concept of g-frames to Hilbert modules over pro-C*-algebras. Then, we introduce the g-frame operators in such spaces and show that they share many useful properties with their corresponding notions in Hilbert spaces. We also show that, by having a g-frame and an invertible operator in this spaces, we can produce the corresponding dual g-frame. Finally we introduce the canonical dual g-frames and provide a reconstruction formula for the elements of such Hilbert ýmodules.ý

ýData envelopment analysis (DEA) is an objective method for priority determination of decision making units (DMUs) with the same multiple inputs and outputs. DEA is an efficiency estimation technique, but it can be used for solving many problems of management such as rankig of DMUs. Many researchers have found similarity between DEA and MCDM techniques. One of the earliest techniques in MCDM is Quality Function Deployment (QFD) which is a team-based and disciplined approach to product design, engineering and production and provides in-depth evaluation of a product. The QFD team is responsible for assessing the relationships between costumer requirements (CRs) and design requirements (DRs) and the interrelationships between DRs. In practice, each member demonstrates significantly different behavior from the others and generates different assessment results, leading to the QFD with uncertainty. In this paper data envelopment analysis is used to overcome this uncertainty. Each member's subjective assessment is taken into account directly and a new data envelopment analysis method in group situation is constructed which differs from multi-objective decision making models. Then, without using Charnes-Cooper transformation, the proposed model is transformed into a linear programing problem in a completely different manner. We will call the proposed model "Grouped-QFDEA"ý.ý

In the present paper, the analytical solution for an exact second order fuzzy initial value problem under generalized Hukuhara differentiability is obtained. First the solution of first order linear fuzzy differential equation under generalized Hukuhara differentiability is investigated using integration factor methods in two cases. The second based on the type of generalized Hukuhara differentiability, the analytical solution of an exact second order fuzzy initial value problem is derived in two senses of differentiability. Also, several properties for generalized Hukuhara differentiability are obtained on the topics, such as, the univariate fuzzy chain rules, fuzzy integration by parts, among others. At the end, some illustrative examples are presented and these examples show the behavior of the ýsolutions.ý

This paper has examined the analytical solution of steady fully developed natural convective flow of a viscous incompressible and electrically conducting fluid between vertical channel by taking the Hall current and induced magnetic field into account. We have obtained the non-dimensional simultaneous ordinary differential equations using the suitable non-dimensional variables and parameters in the governing equations of the model. By obtaining the analytical solution of the simultaneous ordinary differential equations, the effects of the Hall current and the Hartmann number on the primary and secondary components of the velocity, induced magnetic field and induced current density are presented by the graphs. The influence of the Hall current is to increase both the primary and secondary components of the velocity and induced magnetic field profiles but decrease the components of induced current density. It is found that the effect of Hartmann number is to decrease both the primary and secondary components of velocity and induced current density but increase the components of the induced magnetic ýfield.ý

The present study is an attempt to find a solution for Volterra's Population Model by utilizing Spectral methods based on Rational Christov functions. Volterra's model is a nonlinear integro-differential equation. First, the Volterra's Population Model is converted to a nonlinear ordinary differential equation (ODE), then researchers solve this equation (ODE). The accuracy of method is tested in terms of $RES$ error and compare the obtained results with some well-known results.The numerical results obtained show that the proposed method produces a convergent ýsolution.ý

In recent years, the assessment of environmental performance has been received considerable attention by environmental policy indicators and decision makers. In this regard, this paper applies data envelopment analysis (DEA) as a management tool for evaluating the environmental performance of the firms and uses the extended bounded adjusted measure (extended BAM) for including undesirable outputs in the environmental assessment. On the other hand, congestion points to a situation where inputs are excessively used. The previous studies of congestion mainly considered the framework of desirable outputs, and undesirable outputs have been disregarded in the evaluation. To overcome these shortcomings, this paper introduces an alternative definition and approach to treat congestion in the simultaneous presence of desirable and undesirable outputs. Then, the presented method is applied on 31 administrative regions of China. As a result of this application, it is observed that seven industries are environmentally efficient and also do not show congestion. Four industries evidence congestion in one or both of their inputs. By reducing the amount of congestion in each input, these industries can increase their desirable output and decrease their undesirable
ýoutputs.ý

This paper will examine the relationship between "Data Envelopment Analysis" and a statistical concept ``Outlier". Data envelopment analysis (DEA) is a method for estimating the relative efficiency of decision making units (DMUs) having similar tasks in a production system by multiple inputs to produce multiple ýoutputs.ý An important issue in statistics is to identify the outliers. In this paper, we attempt to investigate the concept of the outliers determination by data envelopment analysis and assess the manner of decision making units when a sample contains an outlier. We will start by providing a review literature. We will then proceed with our proposed method and discuss the strengths and weaknesses of our method. We will provide some numerical results to demonstrate the applicability of our ýmethod.ý