Sharif Digital Repository

In this research work, a modified fuzzy approach referred to as modified fuzzy logic method (MFLM) is proposed to more conveniently solve intricate decision-making problems under uncertainty and data deficiency. The method resolves major drawbacks like inaccuracy, complexity, and a high volume of computational efforts with the existing approaches for the mentioned problems. Here, MFLM is applied to materials selection for a cryogenic storage tank and a gas turbine blade, which are standard engineering problems used for verification by researchers, and the ranking results are compared with the state-of-the-art techniques in the literature, such as the conventional fuzzy logic method.... 

In this paper, an intelligent CAD tool for the design of analog circuits is presented. First, the system uses fuzzy rule based reasoning to select alternative architectures for the circuits at each level of hierarchy and, then, deduces the device size using case-based reasoning, whose objective is to determine the plausible building blocks subspecifications on the basis of past design experience. In cases where some of the specifications have not been met, a qualitative reasoning-based approach is used to make final corrections. The above approach is demonstrated through the example of a CMOS Op-Amp  

A phase frequency detector (PFD) with a very low dead zone is proposed which is based on a configuration adaptable to both CMOS or carbon nano-tube transistors (CNTFETs). In the first step the proposed configuration is designed using CMOS transistors, and then CNTFETs are substituted to improve the speed and reduce the propagation delay. The proposed PFD in addition to very low dead zone, has low power consumption and high frequency range of operation, which are achieved as a result of the elimination of the reset path. The simulation results based on 32 nm technology for CNTFET and 180 nm technology for CMOS, illustrate that CNTFET-based proposed circuit dissipates 2 µW and has frequency of... 

Inspired by Williamson’s knowledge-first epistemology, I propose a position on practical knowledge that can be called the ‘know-how-first view’; yet whereas Williamson is one of the pioneers of the new intellectualism about know-how, I employ the know-how-first view to argue against intellectualism and instead develop a know-how-first version of anti-intellectualism. Williamson argues that propositional knowledge is a sui generis unanalyzable mental state that comes first in the epistemic realm; in parallel, I propose that know-how is a sui generis unanalyzable power that comes first in the practical realm. To motivate this suggestion, I put forward two arguments: (1) drawing on... 

The hydro-acoustic analysis of submerged propellers is an important issue in marine industries, which is examined to reduce the vibrations and noise level of vessels alongside reducing fuel consumption and improving hydrodynamic efficiency. B-series propellers are common propellers whose hydrodynamic and acoustic investigation through applying suitable rake, and skew angle can offer proper results to designers for enhancing the hydrodynamic performance and reducing noise. In this study, a model of the five-bladed B-series propeller with the normal skew angle is chosen. The effects of geometric parameters, including the rake angle, skew angle, geometric pitch ratio, and the number of blades... 

In this paper we proposed a new real-time learning method. The engine of this method is a fuzzy-modeling technique which is called ink drop spread (IDS). IDS method has good convergence and is very simple and away from complex formula. The proposed method uses a reinforcement learning approach by an actor-critic system similar to Generalized Approximate Reasoning based Intelligent Control (GARIC) structure to adapt the IDS by delayed reinforcement signals. Our system uses Temporal Difference (TD) learning to model the behavior of useful actions of a control system. It is shown that the system can adapt itself, commencing with random actions. © 2008 IEEE