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Pour M.,Quchan University of Advanced Technology
International Journal of Advanced Manufacturing Technology | Year: 2015

The absence of a rapid method for the estimation of surface roughness has been considered as one of the main problems in accurate machining processes. The probability of encountering measurement equipment to other production equipments and unsuitable environments for the measurement equipment can be considered as the main problem for lack of utilizing them on the production. On the other hand, the surface roughness is not uniform at different regions of the manufactured workpiece. The vibration of the cutting tool and boundary conditions of the workpiece can be considered as the main source of these variations. Thus, in contact measurement method, the surface roughness must be determined by repeating and averaging of sampling results. In this paper, a novel non-contact method based on combination of the time series analysis and decomposition of the image by wavelet transform is presented. In this method, the image entropy criterion is used for specifying the appropriate position of the camera and light source relation to the calibrated surface roughness sample. Then, the surface texture of the captured image is extracted by wavelet transform. After that, the analysis of the images for finding the logical relationship between surface roughness and the largest Lyapunov exponent of the approximation coefficients is done. To confirm the suggested method, the grinding experiments on ck45 material with different cutting conditions are done, and their surface roughness has been specified and compared using the contact and the suggested method. The results indicate that the accuracy of the suggested method for determining the surface roughness of ground surface is significant. © 2015 Springer-Verlag London

Farhadinia B.,Quchan University of Advanced Technology
Knowledge-Based Systems | Year: 2016

As for multi-criteria decision making problems with hesitant fuzzy linguistic information, it is common that the criteria involved in the problems are associated with the predetermined weights, whereas the information about criteria weights is generally incomplete. This is because of the complexity and the inherent subjective nature of human thinking. In this circumstance, the weights of criteria can be derived by means of information entropy from the evaluation values of criteria for alternatives. To the best of our knowledge, up to now, there is no work having introduced the concept of entropy measure for hesitant fuzzy linguistic term sets (HFLTSs). Hence, in this paper, we are going to fill in this gap by developing information about how entropy measures of HFLTSs can be designed. © 2015 Elsevier B.V. All rights reserved.

Farhadinia B.,Quchan University of Advanced Technology
Journal of Intelligent and Fuzzy Systems | Year: 2014

There exist several types of measured functions that have been widely used for handling fuzzy multicriteria decision-making problems with vague (interchangeably, intuitionistic fuzzy) information. The main goal of this paper is to present firstly a comparative study of some existing measured functions underling their counter-intuitive examples and then a family of novel measured functions under vague environment is introduced. © 2014 - IOS Press and the authors.

Khani H.,Quchan University of Advanced Technology
Proceedings - IEEE International Conference on Ultra-Wideband | Year: 2014

Recently finite-resolution digital receivers have been proposed for weighted-transmitted reference ultra-wideband (WTR-UWB) systems. However, employing a finite-resolution receiver severely degrades the performance due to a sever quantization noise. In this paper, two novel iterative algorithms are proposed to recover the reference pulse based on the detected data pulses and employing nonlinear signal processing while preventing the error propagation. The first algorithm exploits a new signal processing approach, referred to as polarity invariant square law technique. In this approach the reconstructed reference pulse is first squared and multiplied by its sign and then is used to demodulate the monobit data pulses. Hence, it can be assumed that in this technique data pulses have been recovered from monobit quantization noise as well. In the second algorithm, the mentioned reconstructed reference pulse is cubed and then is used for demodulation. Simulation results illustrate that employing these two novel signal-processing methods highly mitigates the contribution of the small (noise dominant) samples to the decision statistic. The performance of the proposed algorithms is evaluated at a data rate of 23.78 Mbps over in-vehicle channels, taking into account noise, inter-symbol interference (ISI), and inter-block interference (IBI). The obtained simulation results demonstrate that the proposed algorithms enhance the performance about 1.7 dB as compared to the existing algorithms. As a result, applying these algorithms would be a promising approach to implement high performance monobit transmitted-reference (TR) receivers. © 2014 IEEE.

Farhadinia B.,Quchan University of Advanced Technology
Journal of Intelligent and Fuzzy Systems | Year: 2015

Hesitant fuzzy sets (HFSs), interval-valued hesitant fuzzy sets (IVHFSs) and typical dual hesitant fuzzy sets (T-DHFSs) are new extensions of classical fuzzy sets (FSs) that have attracted more and more scholars attention nowadays. Although several contributions exist regarding basic operations on HFSs, IVHFSs and T-DHFSs, most of them are focused on the multiplication and the addition operations and do not refer extensively to the division and the subtraction operations. Thus, the main purpose of the present paper is to develop division and subtraction formulas for HFSs, IVHFSs and T-DHFSs, which provides more choices for the decision makers. © 2015 - IOS Press and the authors. All rights reserved.

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