The geophysical ground-penetrating radar (GPR) method is able to detect and identify shallow buried targets especially cylindrical type without any destruction of the medium. GPR method is based on sending the electromagnetic waves generally in the range of 1 MHz up to 1 GHz frequency into the earth and receiving reflected off various buried targets. In present research, this method has been used to identify geometrical parameters of buried cylindrical targets containing burial depth and radius. This task was done through the mathematical relationships between geometrical parameters of cylindrical targets with their GPR hyperbolic response using the particle swarm optimization algorithm (PSO). To achieve this goal first, forward modeling of GPR data by 2-D finite-difference time-domain (FDTD) method using GPRMAX was performed for several synthetic models corresponding to common targets in geotechnical applications and subsurface cylindrical installations. Also in the research, several field surveys were carried out over the well-known buried cylindrical targets in Isfahan University of Technology campus, moreover their GPR response was investigated after employing different processing sequences. In order to extract the geometrical parameters of the buried cylindrical targets in synthetic models and real surveys, the PSO algorithm was used in MATLAB environment. The algorithm performance for 7 produced synthetic models, including cylindrical targets made by different materials, radii and burial depth, as well as the real radargrams of GPR profiles in Isfahan University of Technology campus was verified leading to favorite and reasonable results for the synthetic models and real radargrams, respectively.

Summary: In present research, GPR method has been used to identify geometrical parameters of buried cylindrical targets. To achieve this goal, first forward modeling of GPR data has been carried out for several synthetic models corresponding to common targets in geotechnical and subsurface installations. Afterward, an applied algorithm on the basis of signal processing on a radargram (A Scan) with high accuracy was implemented in MATLAB environment. The performance of the algorithm was validated for several synthetic models so that led to the favorite results in all cases. The primitive algorithm was improved to employ for real GPR images having a large amount of various noises. Introduction: One of the most important tasks in engineering design is extraction of geometrical parameters of subsurface hidden objects. In this research, has been attempted to investigate the treatment of GPR responses in spatial domain using simulated response of various synthetic models by forward modeling. Then after extraction of relationships between existence mathematical models with GPR system response, geometrical parameters of buried cylindrical targets and physical parameters of host medium are identified through employing appropriate algorithms and image processing methods. Methodology and Approaches: An applied algorithm based on signal processing on a radargram (A Scan) was implemented in MATLAB environment which investigates the treatment of GPR response in spatial domain. The performance of the algorithm was validated for several synthetic models such as empty metallic and PVC horizontal cylinders and also the model including the couple of empty horizontal cylinders made by PVC. The algorithm was improved by applying Cascade Object Detector (COD) algorithm, interest of region is defined so that null regions are removed, implementing on the finite interested region. Then the algorithm is trained based on definition of positive and negative images. The performance of the proposed algorithm was evaluated for a real GPR radargram related to one of the profiles surveyed in Imam-Hossein square, opposite the municipality of Isfahan city so that also yielded a favorite result in this regard. Results and conclusions: In order to evaluate the accuracy of curve fitting the hyperbolic equation on the data, statistical validation criterion well-known as determination coefficient has been used. According to this criterion fitting accuracy of hyperbolic equation on the data for all synthetic models except the couple of horizontal cylinders is up to 93 percent. The algorithm has estimated the geometrical parameters of cylindrical targets with an error less than 8 percent. Also using the improved algorithm, determination coefficient of the fitted curve is 83. 99 percent that is a favorite result. The algorithm could estimate radius, burial depth and horizontal location of the buried horizontal cylinder in the real GPR image with the errors of 7. 6, 1. 7 and 1. 1 percent, respectively.

Improving participation in voluntary activities in Iran is important because increasing productivity among young people, given the country's young population, contributes to community sustainability. Therefore, a better understanding of volunteer motivation in Iranian youth is needed. The Volunteer Functions Inventory (VFI) for assessing volunteer motivations has good psychometric properties and is adapted to several languages, but no validated Iranian translation yet exists. The purpose of this study was to investigate the psychometric Characteristics of voluntary functions inventory in members of Iranian Red Crescent Society. Sample size was 595 members of Youth Organization of Iranian Red Crescent Society from 31 provinces and 175 cities of Iran that were selected by multi-stage cluster sampling method and responded to voluntary functions inventory. Data were collected using a demographic sample and voluntary functions inventory (VFI). Confirmatory factor analysis using principal components method was used for data analysis. The results of the present study showed that the voluntary functions inventory had validity and reliability. Also, the factor structure showed that 29 items and 6 factors well assess people's attitudes to volunteering, and the structure of this inventory was well-fitted and confirmed all goodness of fit models. The present study provides the use of the Iranian translation of the Voluntary Functions Inventory (6 scales and 29 items) to assess volunteer motivation among young Iranian volunteers.

The aim of this study was to investigate the effect of using portulaca oleracea as a source of plant antioxidants for feeding fattening male lambs, on carcass traits, meat quality, and oxidative stability. Twenty-one male lambs with an average weight of 24±1.5 kg and 150±15 days old were fed with one of the experimental rations included a diet without portulaca oleracea as control, a diet containing 7.5%, and a diet containing 15% portulaca oleracea, for 84 days. The muscle (Longissimus dorsi) samplewas used to determine pH, chemical composition, colorimetric properties, and oxidative stability of meat. Meat lipid oxidation was determined after 1, 7, and 30 days of refrigerated storage using thiobarbituric acid (TBARS). The use of portulaca oleracea in diets improved meat color characteristics such as L, chroma, and Hue. The highest ash concentration and the lowest meat moisture were observed in the treatment of 15% portulaca oleracea (P<0.05). Meat pH was the lowest in the first hour after slaughter but did not differ at 24 h. Compared to the control, in both treatment groups feeding the lambs with portulaca significantly reduced the concentration of Malondialdehyde in the meat of the lambs and increased the meat oxidative stability (P<0.05). The results of this experiment showed that feeding portulaca oleracea by improving properties such as color and increasing the meat oxidative stability improves meat quality, which may have lead to an increase in its nutritional value in terms of human health.

Evaluating the cutting rate (CR) of stones is important in the cost estimation and the planning of the stone processing plants. This research used regression models to estimate the stones’ CR based on their physico-mechanical characteristics. Stone processing factories in Mahallat City (Markazi province, Iran) were visited, and the CR of diamond circular saws was recorded on six different travertine stones. Next, the stone block samples were collected from the quarries for laboratory tests. Stones’ porosity (n), uniaxial compressive strength (UCS), and Schmidt hammer hardness (SH) were determined in the laboratory as their physico-mechanical characteristics. Correlation relationships of CR with physico-mechanical characteristics were evaluated using simple and multiple regression analyses, and estimator models were developed. Results showed that multiple regression models are more reliable than simple regression for estimating the stones’ CR. The validity of the developed multiple regression models was verified with the published data of one researcher. The findings indicated that these models are accurate enough for estimating the CR of stones. Consequently, the multiple regression models provide practical advantages for estimating the CR and save time and cost during the planning and design of the stone processing factories.

In this study, chemical compositions of black seed meals samples were determined. 18 male weaning Zandi lambs with an average body weight of 23.5 ±1.5 kg were used in a completely randomized design in three groups of six in individual pens. Experimental treatments were: 1) control (basal diet with 12% soybean meal and without black seed meal), 2) diet containing 6% soybean meal and 9% black seed meal and 3) diet containing 18% black seed meal and without soybean meal. The concentration of dry matter, crude protein, crude fat, NDF, ADF, ADIN, and crude ash of black seed meal samples were 97.53±0.58, 31.26±0.99, 15.16 ± 0.61, 25.95 ± 1.34, 14.2±0.80, 0.69±0.04 and 5.07 ± 0.24, respectively. Replacement of soybean meal with black seed meal in the diet of experimental lambs had no effect on final body weight, daily weight gain, feed conversion ratio, dry matter intake, dressing percentage, tail and total body fat deposition. Albumin and total protein were higher for lambs fed by diet containing 18 % black seed meal compared to other treatments (P <0.05). However, the concentration of blood triglyceride, cholesterol and urea nitrogen were not differed between experimental groups. The digestibility of dry matter, organic matter, crude fat and protein were not affect by feeding of experimental diets. It seems that black seed meal can be used in the diet of fattening lambs up to 18% without adverse effect on performance and nutrients digestibility of growing lambs.

Ground- Penetrating Radar (GPR) is a non-destructive and high-resolution geophysical method that uses high frequency reflected EM waves to detect buried objects and manmade structures. In current study this method has been used to identify geometrical characteristics of buried cylindrical targets such as tunnel structures. This aim has been obtained through determination of relationships between physical and geometrical characteristics of cylindrical targets with the parameters of GPR hyperbolic response using two intelligent pattern recognition methods known as artificial neural network and template matching. To this goal GPR responses of synthetic cylindrical objects corresponding to common geotechnical targets (such as tunnels, canals, qanats and pipes) have been simulated using forward modeling by 2D Finite Difference and have been used as templates in the neural network and template matching algorithms. The structure of applied neural network was designed based on extracting discriminant and unique features (eigen values and the norm of eigen values in the horizontal and vertical directions) from the GPR images and predicting all geometrical parameters of the objects simultaneously. The template matching operation also carried out by two different similarity approaches named spatial domain convolution and normalized cross correlation in 2D wave number domain. Afterward it was delineated that the wave number domain approach is generally faster (more than 23 times) than the other approach.The results of the research show that both two employed intelligent methods having in situ, real-time, accurate and automatic application capabilities can be applied for real geotechnical applications, however in general the neural network method has led to less error and as a result higher estimation power for the geometrical parameters of the cylindrical targets than template matching method.

The aim of the current research was to identify the characteristics of the four elements in order to provide a problem-oriented curriculum model in the elementary school mathematics course. There were 19 participants and the sampling was done purposefully. The data collection tools are semi-structured interviews and questionnaires. The problem-oriented curriculum template was designed using the characteristics of the elements and with the method of qualitative content analysis in the elementary school mathematics course. The identified features were validated by fuzzy Delphi method and Shannon's entropy method was used for data processing. Based on the results of the analysis, 7 main categories including the characteristics of goals at three levels of cognitive, attitudinal, skill, content, evaluation, teaching-learning strategy and 46 sub-categories were identified.                                                                                                                                                                In the fuzzy Delphi section, all features were confirmed by obtaining a de-fuzzified value greater than 0.7. The results of Shannon's entropy determined that the characteristics of starting teaching with a challenging question, creating a suitable educational environment, continuously monitoring the quality of learning strategies and communicating with students' talents have attracted the most attention and obtained the highest ranks and had a higher importance factor than other characteristics

Due to their light weights and high load carrying capacities, composite structures are widely used in various industrial applications especially in aerospace industry. Stiffening ribs are the main features of lattice type composite structures. Strength to weight ratio is known to be as one of the most critical design parameter in these structures. In this study, the effect of some parameters such as the physical characteristics of the material, shell thickness, angle, thickness and number of ribs on distribution of stresses and buckling loads of shell are investigated. For this purpose, 3D finite element analysis using ANSYS software explicitly was done and then compared with experimental test results. Increasing the thickness of the outer shell causes the structural strength will rise to 50 percent. The next effective parameter is reduction of rib angle which provides an increase of 30 percent in specific load. Although Stiffenerrs (ribs) have a major role in load carrying, but increasing the rib number causes the structural weight rises, thus compared with the two previous parameters do not have a significant effect on the strength of structures.

In the current research, GPR response of variety of synthetic models encountered with geotechnical applications containing single horizontal cylinder, 2D prism, double horizontal cylinders, 2D arbitrary polygon and layered earth have been produced using forward modeling through the finite-difference time-domain algorithm improved in the frequency domain. In this research by using the parameters of a hyperbola and GPR responses produced for cylindrical objects by means of the forward modeling, it was revealed that there exist some linear relationships between the hyperbola height to width ratio (H/W) with physical and geometrical parameters of the cylindrical objects. These relations can be used as proper quantitative criteria to identify physical and geometrical parameters of buried cylindrical objects on GPR images. To achieve this purpose, the effect of several parameters such as geometrical shape, material type, size and burial depth of the objects as well as type and interface of fluids content and host medium physical properties on GPR responses, have also been studied. The results lead us to the potential of GPR method to detect the kinds of targets; identifying the parameters of cylindrical objects and evaluating characteristics of fluid content, so that one can distinguish metallic from nonmetallic targets as well as type of fluid content of nonmetallic targets (i.e. air, fresh water and salt water). The results of the research were validated by applying for identification of buried qanat in Shahin-Shahr plain, Isfahan province. The burial depth and diameter of the qanat were estimated by 3.4% and 12% erorr respectively.