Simulation of multi-component multi-phase fluid flow in two-dimensional anisotropic heterogeneous porous media using high-order control volume distributed methods

Peer reviewedPostprin

A comparative study of explicit high-resolution schemes for compositional simulations

Peer reviewedPostprin

Market orientation, learning orientation, and innovation capabilities in SMEs: Case study from Iran's SMEs

Increasing market changes has led to a need for increased innovation and, therefore, programs of innovation in SMEs. The interrelationships among a firm’s market-orientation, learning-orientation, and innovativeness are an important research area for investigators in the literature of management, strategy, and marketing. However, most of the empirical studies were conducted in large-scale firms in developed countries and ignored small and medium-sized business (SMEs) in general, and in developing countries in particular. This paper examine the nomological relations among market-orientation, learning-orientation and innovativeness in medium-sized business (SMEs) of developing countries. The study involves a questionnaire-based survey of managers from small-sized-firms operating in Iran. These were subjected to a structural equation modeling (SEM) analysis. The results show that; firm learning-orientation positively influences firm innovativeness; firm market-orientation positively impacts firm learning orientation; firm learning-orientation mediates the relationship between firm market-orientation and firm innovativeness

A New Fusion Estimation Method for Multi-Rate Multi-Sensor Systems with Missing Measurements

A new fusion strategy is introduced in this article to estimate state for multi-rate multi-sensor systems with missing measurements. N sensors, which possess various sampling rates, render the measurements. Missing measurements with a certain probability pattern are also investigated. For these types of systems, Multi-rate Kalman filters are designed to estimate a target position at various sampling rates. Next, Ordered Weighted Averaging (OWA) operator is utilized to integrate multi-rate Kalman filters and improve the estimation quality. A new fusion strategy based on a real covariance matrix is introduced for updating the weighting factors, and proof of convergence is granted. Simulation studies on a tracking system verify the superior performance of the proposed fusion strategy in comparison with the Kalman filter, the multi-rate Kalman filters, and also the previous fusion methodology