Sharif Digital Repository

Resin in pulp, as the most frequently employed process for extraction of uranium from low-grade ores, encounters difficulties when the pulp contains dense or abrasive minerals, e.g., Saghand ores in central Iran. To overcome these complications, it was suggested to remove solid content of the pulp at first, and inject the clear solution into a cascade of Pachuca reactors, where uranium is adsorbed by an anion exchanger such as Varion-AP. We made two mini pilot cascades, each comprising ten Pachuca reactors, to check both co-current and countercurrent resin in solution processes on the Saghand leach liquor. The countercurrent scheme, having a higher efficiency, was able to adsorb 99% of... 

In this paper, a framework for distributed and decentralized state estimation in high-pressure and long-distance gas transmission networks (GTNs) is proposed. The non-isothermal model of the plant including mass, momentum and energy balance equations are used to simulate the dynamic behavior. Due to several disadvantages of implementing a centralized Kalman filter for large-scale systems, the continuous/discrete form of extended Kalman filter for distributed and decentralized estimation (DDE) has been extended for these systems. Accordingly, the global model is decomposed into several subsystems, called local models. Some heuristic rules are suggested for system decomposition in gas pipeline... 

In this paper, a non-isothermal model of natural gas in pipelines including mass, momentum and energy balance equations are used as model equations for modeling and state estimation in gas pipeline systems. It is shown that differential equations describing the dynamic behavior of a high-pressure and long-distance gas transmission network (GTN) can be solved efficiently using the orthogonal collocation method. The issues corresponding to the presence of discontinuities in the dynamic model is substantially discussed and studied. The non-isothermal model of a GTN can experience discontinuities during transient operations, which causes challenges in simulation and state estimation in this... 

In natural gas transmission networks, the efficiency of daily operation is strongly dependent on our knowledge about the customer future demands. Unavailability of accurate demand forecasts makes it more important to be able to characterize the loads and quantify the corresponding uncertainty. A planning strategy for natural gas transmission networks under future demand uncertainty is addressed, which involves coupling of a gas transmission network dynamic simulator with the stochastic optimization framework. Loads from a gas-fired power plant are studied where the loads are characterized by a number of uncertain parameters, and unscented transform is utilized for uncertainty propagation.... 

The activity coefficient at infinite dilution is a representative of the limiting non-ideality of a solute in a mixture. Various methods for the prediction of infinite dilution activity coefficients (IDACs) have been developed. Artificial neural networks are powerful mapping tools for nonlinear function approximations. Accordingly, an artificial neural network model is proposed for the prediction of the IDACs of binary systems where the properties of the individual components are used as inputs to the network. The input parameters of the neural network are the mixture temperature, critical temperature, critical pressure, critical volume, molecular weight, dipole moment and the acentric... 

Brain-computer interface (BCI) systems enable individuals to control external devices through brain activity. Among the various paradigms in the BCI domain, steady-state visual evoked potentials (SSVEPs) are particularly dominant. One of the most effective methods for frequency detection in SSVEP-based BCIs is canonical correlation analysis (CCA). In standard CCA, a sine-cosine signal is used as a reference signal, which may not be optimal for SSVEP recognition. In this paper, we propose a novel graph reference signal that preserves a sinusoidal form, yet exhibits temporal smoothness on a graph learned from the reference signal. We employ an alternating optimization approach to obtain the... 

Steady State Visual Evoked Potential (SSVEP)-based Brain Computer Interfaces (BCIs) is one of the most prevalent methods in BCIs. The main purpose of these systems is to detect the frequency of SSVEP to understand which visual stimulus a person is looking at. Various methods have been proposed to detect the frequency of SSVEP. One of the most widely used methods is the Canonical Correlation Analysis (CCA) algorithm. Despite the simplicity and efficiency of the CCA algorithm, none of the methods based on CCA have incorporated the graph structure presented in the EEG and reference signals into the CCA cost function. In this paper, we introduce a novel approach that considers the graph... 

This article deals with technology strategy and its linkage with overall strategy at multi-business, diversified groups. In the last two decades, the alignment of technology and business strategy has been one of the important research fields in strategy and technology management literature. These researches has been concentrated on single companies through which different frameworks, models, and decision support tools have been developed and widely utilized by industries. Although multi-business and diversified groups play an important role in national economy of developing countries and need a comprehensive and overall plan for the management of their diversified technological capabilities,...