Search results for: Sahand Golmohammadi

Authors: Sahand Golmohammadi, Sana Hosseini Shirazi

Abstract:

Because the status and mechanical parameters of discontinuities in the rock mass are included in the calculations, various methods of rock engineering classification are often used as a starting point for the design of different types of structures. The Q-system is one of the most frequently used methods for stability analysis and determination of support systems of underground structures in rock, including tunnel. In this method, six main parameters of the rock mass, namely, the rock quality designation (RQD), joint set number (Jn), joint roughness number (Jr), joint alteration number (Ja), joint water parameter (Jw) and stress reduction factor (SRF) are required. In this regard, in order to achieve a reasonable and optimal design, identifying the effective parameters for the stability of the mentioned structures is one of the most important goals and the most necessary actions in rock engineering. Therefore, it is necessary to study the relationships between the parameters of a system and how they interact with each other and, ultimately, the whole system. In this research, it has attempted to determine the most effective parameters (key parameters) from the six parameters of rock mass in the Q-system using the rock engineering system (RES) method to improve the relationships between the parameters in the calculation of the Q value. The RES system is, in fact, a method by which one can determine the degree of cause and effect of a system's parameters by making an interaction matrix. In this research, the geomechanical data collected from the water conveyor tunnel of Azad Dam were used to make the interaction matrix of the Q-system. For this purpose, instead of using the conventional methods that are always accompanied by defects such as uncertainty, the Q-system interaction matrix is coded using a technique that is actually a statistical analysis of the data and determining the correlation coefficient between them. So, the effect of each parameter on the system is evaluated with greater certainty. The results of this study show that the formed interaction matrix provides a reasonable estimate of the effective parameters in the Q-system. Among the six parameters of the Q-system, the SRF and Jr parameters have the maximum and minimum impact on the system, respectively, and also the RQD and Jw parameters have the maximum and minimum impact on the system, respectively. Therefore, by developing this method, we can obtain a more accurate relation to the rock mass classification by weighting the required parameters in the Q-system.

Keywords: Q-system, rock engineering system, statistical analysis, rock mass, tunnel

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Authors: Elham Alaee, Mousa Shamsi, Hossein Ahmadi, Soroosh Nazem, Mohammad Hossein Sedaaghi

Abstract:

Human face has a fundamental role in the appearance of individuals. So the importance of facial surgeries is undeniable. Thus, there is a need for the appropriate and accurate facial skin segmentation in order to extract different features. Since Fuzzy C-Means (FCM) clustering algorithm doesn’t work appropriately for noisy images and outliers, in this paper we exploit Possibilistic C-Means (PCM) algorithm in order to segment the facial skin. For this purpose, first, we convert facial images from RGB to YCbCr color space. To evaluate performance of the proposed algorithm, the database of Sahand University of Technology, Tabriz, Iran was used. In order to have a better understanding from the proposed algorithm; FCM and Expectation-Maximization (EM) algorithms are also used for facial skin segmentation. The proposed method shows better results than the other segmentation methods. Results include misclassification error (0.032) and the region’s area error (0.045) for the proposed algorithm.

Keywords: facial image, segmentation, PCM, FCM, skin error, facial surgery

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Authors: Sahand Hamed Moeel Ardebil, Zohreh Taebi Noghondari, Mahmood Reza Ghorban Sabbagh

Abstract:

Gillian Flynn’s Gone Girl, depicts a society in which, as a result of media dominance, the reality is very precarious and difficult to grasp. In Gone Girl, reality and image of reality represented on TV, are challenging to differentiate. Along with reality, individuals’ agency and independence before media and the capitalist rule are called in to question in the novel. In order to expose the unstable nature of reality and an individual’s complicated relationship with media, this study has deployed the ideas of Marxist-media theorist Guy Debord (1931-1992). In his book Society of the Spectacle (1966), Debord delineates a society in which images replace the objective reality, and people are incapable of making real changes. The results of the current study show that despite their efforts, Nick and Amy, the two main characters of the novel, are no more than spectators with very little agency before the media. Moreover, following Debord’s argument about the replacement of reality with images, everyone and every institution in Gone Girl projects an image that does not necessarily embody the objective reality, a fact that makes it very hard to differentiate the real from unreal.

Keywords: agency, Debord, Gone Girl, media studies, society of spectacle, reality

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Authors: Behnaz Sohani, Sahand Shahalinezhad, Amir Rahmani, Aliyu Aliyu

Abstract:

Recently, medical imaging and specifically medical image processing is becoming one of the most dynamically developing areas of medical science. It has led to the emergence of new approaches in terms of the prevention, diagnosis, and treatment of various diseases. In the process of diagnosis of lung cancer, medical professionals rely on computed tomography (CT) scans, in which failure to correctly identify masses can lead to incorrect diagnosis or sampling of lung tissue. Identification and demarcation of masses in terms of detecting cancer within lung tissue are critical challenges in diagnosis. In this work, a segmentation system in image processing techniques has been applied for detection purposes. Particularly, the use and validation of a novel lung cancer detection algorithm have been presented through simulation. This has been performed employing CT images based on multilevel thresholding. The proposed technique consists of segmentation, feature extraction, and feature selection and classification. More in detail, the features with useful information are selected after featuring extraction. Eventually, the output image of lung cancer is obtained with 96.3% accuracy and 87.25%. The purpose of feature extraction applying the proposed approach is to transform the raw data into a more usable form for subsequent statistical processing. Future steps will involve employing the current feature extraction method to achieve more accurate resulting images, including further details available to machine vision systems to recognise objects in lung CT scan images.

Keywords: lung cancer detection, image segmentation, lung computed tomography (CT) images, medical image processing

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Authors: Fatemeh Abbasi, Sahand Daneshvar

Abstract:

Productivity is one of the essential goals of companies to improve performance, which as a strategy-oriented method, determines the basis of the company's economic growth. The history of productivity goes back centuries, but most researchers defined productivity as the relationship between a product and the factors used in production in the early twentieth century. Productivity as the optimal use of available resources means that "more output using less input" can increase companies' economic growth and prosperity capacity. Also, having a quality life based on economic progress depends on productivity growth in that society. Therefore, productivity is a national priority for any developed country. There are several methods for calculating productivity growth measurements that can be divided into parametric and non-parametric methods. Parametric methods rely on the existence of a function in their hypotheses, while non-parametric methods do not require a function based on empirical evidence. One of the most popular non-parametric methods is Data Envelopment Analysis (DEA), which measures changes in productivity over time. The DEA evaluates the productivity of decision-making units (DMUs) based on mathematical models. This method uses multiple inputs and outputs to compare the productivity of similar DMUs such as banks, government agencies, companies, airports, Etc. Non-parametric methods are themselves divided into the frontier and non frontier approaches. The Malmquist productivity index (MPI) proposed by Caves, Christensen, and Diewert (1982), the Hicks–Moorsteen productivity index (HMPI) proposed by Bjurek (1996), or the Luenberger productivity indicator (LPI) proposed by Chambers (2002) are powerful tools for measuring productivity changes over time. This study will compare the Malmquist, Hicks–Moorsteen, and Luenberger indices theoretically and empirically based on DEA models and review their strengths and weaknesses.

Keywords: data envelopment analysis, Hicks–Moorsteen productivity index, Leuenberger productivity indicator, malmquist productivity index

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Authors: Yasaman Samani, Ali Golmohammadi

Abstract:

Introduction: The degree of conversion and depth of cure affects the clinical success of resin composite restorations directly. One of the main challenges in achieving a successful composite restoration is the achievement of sufficient depth of cure. The insufficient polymerization may lead to a decrease in the physical/mechanical and biological properties of resin composites and, as a result of that, unsuccessful composite restoration. Thus, because of the importance of studying and evaluating the depth of cure and degree of conversion in bulk-fill composites, we decided to evaluate and compare the degree of conversion and depth of cure in two bulk-fill composites; x-tra fill (Voco, Germany) and Opus Bulk fill APS (FGM, Brazil). Materials and Methods: Composite resin specimens (n=10) per group were prepared as cylinder blocks (4×8 mm) with bulk-fill composites, x-tra fil (Voco, Germany) designated as Group A, and Opus Bulk fill APS (FGM, Brazil) designated as Group B. Depth of cure was determined according to “ISO 4049; Depth of Cure” method, In which each specimen were cured (iLED, Woodpecker, China) 40 seconds and FTIR spectroscopy method was used to estimate the degree of conversion of both the bulk-fill composites. The degree of conversion of monomer to polymer was estimated individually in the coronal half (Group A1 and B1) and pulpal half (Group A2 and Group B2) by dividing each specimen into two halves. The data were analyzed using a Student’s t-test and one-way ANOVA at a 5% level of significance. Results: The mean depth of cure in x-tra fil (Voco, Germany) was 3.99 (±0.16), and for Opus Bulk fill, APS (FGM, Brazil) was 2.14 (±0.3). The degree of conversion percentage in Group A1 was 82.7 (±6.1), in group A2 was 73.4 (±5.2), in group B1 was 63.3 (±4.7) and in Group B2 was 56.5 (±7.7). Statistical analysis revealed a significant difference in the depth of cure between the two bulk-fill composites with x-tra fil (Voco, Germany) higher than Opus Bulk fill APS (FGM, Brazil) (P<0.001). The degree of conversion percentage also showed a significant difference, Group A1 being higher than A2 (P=0.0085), B1, and B2 (P<0.001). Group A2 was also higher than B1 (P=0.003) and B2 (P<0.001). There was no significant difference between B1 and B2 (P=0.072). Conclusion: The results indicate that x-tra fill has more depth of cure and a higher percentage of the degree of conversion than Opus Bulk fill APS. The coronal half of x-tra fil had the highest depth of cure percentage (82.66%), and the pulpal half of Opus Bulk fill APS had the lowest percentage (56.45%). Even though both bulk-fill composite materials had an acceptable degree of conversion (55% and higher), x-tra fill has shown better results.

Keywords: depth of cure, degree of conversion, bulk-fill composite, FTIR

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