fouling is one of the main parameters in design of any exchanger. ignoring this parameter causes problems such as overheating or under- heating of process streams. in this article a heat exchanger network was designed using process streams data in cdu of tehran refinery. then using tema fouling factors, network exchangers were designed and area and cost were estimated. by changing fouling facto...

Realistic mobility models can demonstrate more precise evaluation results because their parameters are closer to the reality. In this paper a realistic Fuzzy Mobility Model has been proposed. This model has rules which are changeable depending on nodes and environmental conditions. It seems that this model is more complete than other mobility models.After simulation, it was found out that not o...

In many regards, tuning deep-learning networks is still more an art than it is a technique. Choosing the correct hyper-parameters and getting a complex network to learn properly can be daunting to people not well versed in that art. Taking the example of entailment classification, this work will analyze different methods and tools that can be used in order to diagnose learning problems. It will...

This paper describes a novel fuzzy rule-based modeling approach for some slow industrial processses. Structure identification is realized by clustering and support vector machines. When the process is slow, fuzzy rules can be obtained automatically. Parameters identification uses the techniques of fuzzy neural networks. A time-varying learning rate assures stability of the modeling error.

Exceeding component maximum ratings due to transient events like current spikes can lead to premature failure of surface mount resistors due to thermal and electrical overstress. In order to accurately evaluate device parameters and their impact on the circuit behavior a coupled electro-thermal simulation method must be applied under the influence of packaging. This article presents an analysis...

We present a new model for studying mul-titask learning, linking theoretical results to practical simulations. In our model all tasks are combined in a single feedforward neu-ral network. Learning is implemented in a Bayesian fashion. In this Bayesian framework the hidden-to-output weights, being speciic to each task, play the role of model parameters. The input-to-hidden weights, which are sha...

Oscillatory chemical reactions often serve as a timing clock of cellular processes in living cells. The temporal dynamics of protein concentration levels is thus of great interest in biology. Here we propose a theoretical framework to analyze the frequency, phase and amplitude of oscillatory protein concentrations in gene regulatory networks with negative cyclic feedback. We first formulate the...

This paper describes how the most complete recent linguistic results on Korean scrambling (switching of word order) can be readily incorporated into an existing principlesand-parameters parser with minimal additional machinery. Out of all 29 sets of examples in chapters 2.2 and 3.2 of perhaps the most advanced linguistic analysis of Korean scrambling, [5]. 6 sets of examples can be correctly pa...

Linear optical networks are devices that turn classical incident modes by a linear transformation into outgoing ones. In general, the quantum version of such transformations may mix annihilation and creation operators. We derive a simple formula for the effective Hamiltonian of a general linear quantum network, if such a Hamiltonian exists. Otherwise we show how the scattering matrix of the net...

Sleep disorders affect a great percentage of the population. The diagnostic of these disorders is usually made by a polysomnography, requiring patient’s hospitalization. Low cost ambulatory diagnostic devices can in certain cases be used, especially when there is no need of a full or rigorous sleep staging. In this paper, several methods to extract features from 6 EEG channels are described in ...