Quchan University of Advanced Technology

Qūchān, Iran

Quchan University of Advanced Technology

Qūchān, Iran
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Amouzegar T.,Quchan University of Advanced Technology
Tamkang Journal of Mathematics | Year: 2017

Let M be a right R-module and S = EndR(M). We call M a K-extending module if for every element φ ∈ S, Kerφ is essential in a direct summand of M. In this paper we investigate these modules. We give a characterization of K-extending modules. We prove that if M is a projective self-generator module, then M is a K-extending module and every finitely generated projective right ideal of S is a summand if and only if S is semiregular and Δ(M) = Jac(S), where Δ(M) = {f ∈ S | Kerf ≤e M} if and only if M is Z(M)-f-lifting.

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.

Hadizadeh H.,Quchan University of Advanced Technology
Iranian Conference on Machine Vision and Image Processing, MVIP | Year: 2015

This paper presents a rotation-invariant and noise-robust texture descriptor based on fractal analysis of digital images. In the proposed method, the fractal dimension and lacunarity of local regions in the given texture image is first computed, and considered as local fractal features. The histogram of the computed features is then calculated. To extract global features, a global map called average neighborhood structure is computed, which represents the average similarity between the computed local fractal features of any given image pixel and its surrounding neighbors within a specific window. A number of rotation-invariant features are then extracted from the obtained map. The extracted global features along with the calculated histogram is finally used for texture description and classification. Extensive experiments were conducted on two well-known texture datasets (Outex TC10 and CUReT) in the presence of different levels of Gaussion noise. The obtained results indicate that the proposed method achieves high texture classification accuracy, especially in the presence of high levels of Gaussian noise. © 2015 IEEE.

Hadizadeh H.,Quchan University of Advanced Technology
Pattern Recognition Letters | Year: 2016

It is well-known that the human visual system (HVS) cannot sense small variations of visual signals below the so-called just-noticeable distortion (JND) thresholds due to their underlying spatial/temporal masking properties. It is also known that the visual attention mechanism of the human brain can enhance or reduce visual sensitivity. In other words, the visual attention has modulatory effects on JND thresholds. The current knowledge also states that the visual attention is mainly driven by visual saliency in an automatic and involuntary manner. In this paper we present a saliency-modulated JND (SJND) model for static images in the discrete cosine transform (DCT) domain. In the proposed model, the JND thresholds of each block in a given image are elevated by two non-linear modulation functions using the visual saliency of the block. The parameters of the saliency modulation functions are obtained through an optimization framework, which utilizes a state-of-the-art saliency-based objective image quality assessment method. To evaluate the proposed SJND model, two subjective experiments were conducted. The obtained experimental results demonstrated that the proposed method achieves a high accuracy in JND estimation, and also it provides a high distortion-hiding capacity. © 2016 Elsevier B.V.

Anbarsooz M.,Quchan University of Advanced Technology
Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy | Year: 2016

In this study, the aerodynamic performance of helical Savonius rotors with 30° and 45° twist angles have been investigated experimentally and numerically and compared with the conventional rotor with zero twist. This comparison has been performed at two Reynolds number of 1.50 × 105 and 1.84 × 105 (corresponding to wind velocities of 7.3 and 9 m/s) on Savonius type rotors with an aspect ratio of 1.0. Numerical simulations have been performed using the ANSYS-Fluent commercial software using the sliding-mesh method for considering the rotation of the turbine. The experimental measurements, however, are performed at an open-circuit wind tunnel facility. Results show that the maximum power coefficient of the helical rotors are less than the conventional rotor, in a manner that this coefficient decreases from 0.12 to 0.11, when the conventional rotor is replaced with the helical rotor having 45° twist angle. However, the helical rotors have a more uniform time variations of the torque coefficient. The maximum power coefficient for all the rotors has occurred at the tip speed ratio of 0.7. The good agreement observed between the numerical and experimental results revealed the suitability of the employed numerical scheme for predicting the aerodynamic performance of Savonius-type wind turbines. © Institution of Mechanical Engineers.

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

Karizaki V.M.,Quchan University of Advanced Technology
Innovative Food Science and Emerging Technologies | Year: 2016

The mass transfer parameters including effective moisture diffusivity (Deff), mass transfer coefficient (KC) and mass transfer biot number (Bi) during rice cooking were calculated by developing a mathematical model in cylindrical coordinates. According to the evaluation of these parameters, the values of Bi ranged from 0.66 to 2.94. The values of KC and Deff were also found to be in the range of [1.12 − 1.81] × 10− 5 m/s and [0.46 − 3.26] × 10− 8 m2/s, respectively. The kinetics behavior of cooking process was also modeled by the most commonly used predictive models (e.g. Page, Newton, Logarithmic, Henderson and Pabis) and by 13 new models that were proposed in this study. Five statistical parameters (i.e. the coefficient of determination, Sum of square error, root mean square error, reduced chi-square and t-value) were applied for comparison of all predictive models. The quadratic model was found to be the best predictive model for describing the cooking behavior of rice. It was also found that the proposed models of this study show the better prediction than common models used by other researchers. Industrial relevance Design, operation, control, and optimization of various food processors and equipment such as dryers, fryers and cookers in pilot and industrial scale must be safe, efficient and economical. A suitable design of such equipment will be possible by obtained results of this study. © 2016 Elsevier Ltd

Yazdi A.A.,Quchan University of Advanced Technology
Latin American Journal of Solids and Structures | Year: 2016

In this paper the nonlinear forced vibration of an orthotropic circular plate resting on Winkler, Pasternak and nonlinear Winkler foundation is investigated. Plates with edges elastically restrained against rotation and inplane displacement are analyzed and the Von-Karman geometric nonlinear equations are employed. In this study it is assumed that the plate can be subjected to any periodic distributed lateral loading with respect to time. The Galerkin method is used to obtain Duffing's equation for the central deflection. The Homotopy Perturbation Method was used to study the effects of various parameters including orthotropic parameter, elastic foundation parameters and initial deflection on frequency ratio. Highly accurate results were obtained by the application of the aforementioned method. © 2016, Brazilian Association of Computational Mechanics. All rights reserved.

Farhadinia B.,Quchan University of Advanced Technology
Information Sciences | Year: 2016

There exist several types of hesitant fuzzy set (HFS) ranking techniques that have been widely used for handling multi-attribute decision making problems with HFS information. The main goal of this paper is to present firstly a brief study of some existing HFS ranking techniques by emphasizing their counterintuitive examples, and then a novel HFS ranking technique is introduced based on the idea of lexicographical ordering. © 2015 Elsevier Inc.

Hadizadeh H.,Quchan University of Advanced Technology
Pattern Recognition Letters | Year: 2015

In this letter an effective multi-resolution and rotation-invariant texture description approach is presented, which can be utilized in various computer vision and image processing tasks such as texture classification and texture segmentation. In the proposed method, a given gray-scale texture image is first processed by a bank of Gabor wavelets (filters) at different scales and orientations. The obtained filters' responses are then further processed, and a set of local binary patterns called "Local Gabor Wavelets Binary Patterns" (LGWBPs) are computed by comparing the local filters' outputs at different orientations with the global mean of filters' outputs at the same orientations. The obtained patterns are then converted to a number of decimal rotation-invariant codes, and a histogram of the resultant codes at different scales is finally used as a texture feature vector. Experimental results on three popular texture datasets (Outex TC10, CUReT, and Brodatz) indicate that the proposed method achieves high texture classification accuracy, especially in the presence of various levels of Gaussian noise. © 2015 Elsevier B.V.

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