Distance-based clustering methods categorize samples by optimizing a global criterion, finding ellipsoid clusters with roughly equal sizes. In contrast, density-based clustering techniques form clusters with arbitrary shapes and sizes by optimizing a local criterion. Most of these methods have several hyper-parameters, and their performance is highly dependent on the hyper-parameter setup. Recently, a Gaussian density Distance (GDD) approach was proposed to optimize local criteria in terms of distance and density properties of samples. GDD can find clusters with different shapes and sizes without any free parameters. However, it may fail to discover the appropriate clusters due to the interfering of clustered samples in estimating the density and distance properties of remaining unclustered samples. Here, we introduce Adaptive GDD (AGDD), which eliminates the inappropriate effect of clustered samples by adaptively updating the parameters during clustering. It is stable and can identify clusters with various shapes, sizes, and densities without adding extra parameters. The distance metrics calculating the dissimilarity between samples can affect the clustering performance. The effect of different distance measurements is also analyzed on the method. The experimental results conducted on several well-known datasets show the effectiveness of the proposed AGDD method compared to the other well-known clustering methods.

Objective: To examine the efficiency of both the Zeta and density gradient centrifugation (DGC) methods for the selection of normal chromatin sperm by TUNEL, sperm chromatin dispersion (SCD), acridine orange and chromomycin A3 (CMA3).Materials and Methods: The study was performed on 63 patients. Semen analysis was carried out according to WHO criteria. Semen samples were divided into three equal portions. One portion was used as the control, the second portion was used for the Zeta method and the third portion underwent DGC method. All portions were evaluated for sperm morphology (Diff Quick staining), protamine deficiency (CMA3) and DNA integrity (SCD, AO and TUNEL). Coefficients of correlation and student’s t test were carried out using SPSS 11.5.Results: The mean percentage of abnormal sperm, protamine deficiency and DNA fragmentation in the Zeta and DGC methods were significantly decreased as compared to the control group (p<0.005). In addition, the DGC method was higher in comparison to the Zeta method in the selection of sperm with normal morphology (p<0.005). The Zeta method was higher in comparison to the DGC method in the selection of sperm with intact DNA (p<0.005).Conclusion: Both Zeta and DGC methods were effective in the selection of sperm with better quality in terms of normal morphology, normal protamine content and DNA integrity. Therefore, we suggested that the combined Zeta and DGC method should be used for selection of normal sperm.

Probability density functions of the involved random variables are essential for the reliability-based design of offshore structures. The objective of present research was the derivation of probability density function (PDF) for the local joint flexibility (LJF) factor, fLJF, in two-planar tubular DK-joints commonly found in jacket-type offshore structures. A total of 162 finite element (FE) analyses were carried out on 81 FE models of DK-joints subjected to two types of axial loading. Generated FE models were validated using available experimental data, FE results, and design formulas. Based on the results of parametric FE study, a sample database was prepared for the fLJF values and density histograms were generated for respective samples based on the Freedman-Diaconis rule. Nine theoretical PDFs were fitted to the developed histograms and the maximum likelihood (ML) method was applied to evaluate the parameters of fitted PDFs. In each case, the Kolmogorov-Smirnov and chi-squared tests were used to evaluate the goodness of fit. Finally, the Inverse Gaussian model was proposed as the governing probability distribution function for the fLJF. After substituting the values of estimated parameters, two fully defined PDFs were presented for the fLJF in tubular DK-joints subjected to two types of axial loading.

INTRODUCTIONExtraction and processing of various features with the help of aerial imagery reduces the time and financial costs associated with the use of ground mapping and the resulting human error. Advances in the field of aerial sensors in terms of spatial and spectral resolution with precise place and performance picking up altitude from the ground have led to the use of each part of information about terrestrial phenomena such as spectral and spatial characteristics Brought. Today, complementary data used to detect complications are Lidar data, the sensor of which is sent and received, and the electromagnetic spectrum in the near-infrared spectrum (in its aerial form) and joined the spectrum. Pays close infrared and green band (in space type). DATA AND METHODSLidar data and spectral images were analyzed using different types of algorithms effective in landfill extraction to assess density. New layers of images were obtained in the form of raster from the study area, which was analyzed by performing slope extraction steps on flat and sloping surfaces. Buildings that were definitely not buildings were removed. The size and spectral characteristics of the missing structures were identified and the parcels were redistributed to extract the impermeable surfaces. Which led to the achievement of two levels of parcels and impenetrable points. The data set is related to the northern part of Bandar Anzali, which includes a vertical aerial photograph, irregular cloud points of the region with dense one to two points per square meter with an average point space of 0.69 square meters, and vertical aerial photograph with spatial resolution. It is 8 cm square. RESULTS AND DISCUSSIONIn this study, a different method for extracting buildings using airborne Lidar data and ultracam images was presented. The proposed system used geometric and spatial information of Lidar data and ultracam images, which included three general steps, in the first step; Lidar data were filtered and extracted using spectral clustering of buildings. In the second step; The obtained model was compared with the two-dimensional boundaries of buildings by the height threshold method. In the third step; After extraction, the first building boundaries were merged with the structures extracted by the checker algorithm. In the stage of separating terrestrial from non-terrestrial points, all points related to land were classified and extracted. The remaining points were classified as roof points, which were dealt with in the fault section of the buildings. All the functions used enabled the system to successfully extract the structures from the Lidar data. CONCLUSIONThe data for the first return points were subtracted from the data for the last return points and a fixed value was obtained which depended on the altitude accuracy of the difference between the two returns. In addition to the mentioned method, the clustering method was used during the research that each cluster belonged to a roof section so that the characteristics of each surface model could be easily determined.Then, to complete the shape of the roof, the footprint of the building that was extracted was used. In fact, the borderlines and inner vertices extracted only part of the shape of the border. Other sections, such as vertical edges, were not detected due to intersection. This is due to the lack of front sampling. Finally, the items extracted through spectral clustering in eCoginition software and two-dimensional boundaries extracted from ENVI Lidar software, to increase the accuracy of land surface extraction (buildings) and make the area of ​​buildings studied in this data Were merged. As mentioned; After extraction, the primary building boundaries were merged with the structures extracted by the checker algorithm. In the section of buildings diagnostics, buildings with errors were discussed and the evaluation of the results showed that the system used has relatively reached the set goals and the methods used include the threshold method. Elevation, clustering, spectral method, and integration method were evaluated for each of the four blocks with error rates of 28%, 15%, and 0%, respectively, based on the area of ​​extracted tolls to the study area. The error of each building was first examined in general and then in detail, and it was found that aerial Lidar technology has an extraordinary ability to collect very right and dense samples of altitude measurements of cities and a new level of detail information can be Accurately extracted building density automatically and efficiently from aerial Lidar data. In 417 buildings that were surveyed and analyzed, the height of the buildings was achieved with high accuracy and all the buildings in the study area were extracted with a compact and organic density as well as scattered and planned.

Introduction: Some studies conducted so far suggest that exercising during adolescence and young age can increase the amount and density of bone minerals to be stored for the age of senility. However, it has not been confirmed yet what type and intensity of bone minerals may provide for a maximum rate of the anabolic stimulation. Thus, the purpose of this study is to compare the amount and density of the bone minerals in male soccer and handball professional athletes with those of male non-athletes’.Materials and Methods: This is a an experimental research study on 42 males ranging 20-30 years old who were divided into three groups consisting of: 14 professional soccer athletes (Experimental Group 1) ,14 professional handball athletes (Experimental Group 2) and 14 young male non-athletes (Control Group). The athletes had the experience of at least three continuous years of regular professional exercising (3 sessions a week) and participating in national championships. These participants were selected from Mashhad athletic clubs, while the non-athletes were experiencing their first session of exercising in the club. Using DEXA, the participants’ BMD of arm femur and bone mass was measured. Then, the collected data were investigated at the significance level of 5 percent, using descriptive statistics and unilateral variance analysis as well as LSD pursuit test.Results: The obtained results from this research indicate that there was not any significant difference among the three groups of the study in terms of BMD of the arms. Also, in terms of femur and bone mass, there was no significant difference between two groups of athletes, i.e. soccer players and handball players (P=0.465). However, the findings suggest a significant difference between the control group and soccer player group (P=0.001) and also between the control and handball player group (P=0.004).Conclusion: As a result, the findings of this study conform to the theory which states that bone response to the mechanical loading depends on the type and style of athletic activities.

Introduction: Steoporosis is currently one of the prevalent diseases. The effect of exercise on bone marrow density (BMD) has been documented for all age groups. The aim of this research was to compare the effects of endurance vs. resistance trainings on local Bone Mineral density (BMD) changes. Materials and Methods: Thirty-six volunteer female university students (age average: 22.58±1.56; Body Mass Index average: 22.85±2.17), with sedentary lifestyles, were selected and randomly divided to three groups (n=12 in each group). These groups were determined as: The endurance group who ran for 36 sessions on a treadmill over a period of 3 weeks at 70 to 80 percent of the maximum heart-beat rate. They were required to run for 40 minutes per session on the other hand, the resistance group received 36 circuit training sessions at the rate of 70 to 80 percent of 1RM with 6 to 8 repetitions in 3 sets with 2 minutes of rest in between. The third group of the study was the control group.Results: Both the endurance and the resistance training protocols induced significant increases in BMD in the areas of lumbar, neck and femur (P<0.05). However, the variation was more significant for the endurance group in the neck and femur while it was in the aerobic group where better effects were observed in the lumbar region (P<0.05). Conclusion: There was no considerable differences between the two modes of exercise (i.e. endurance and resistance) in terms of the increase of skeleton’s local bone mineral density.

The goal of this research is to evaluate structure and distribution of N – particle systems including electron gas with respect to relative interactions. In this project the quantum density functional theory is used. Which is now days widely used in two classic and quantum forms. Here we use quantum density functional theory for N - particle systems, actually this theory roots in Thomas-Fermi theory with regards to quantum density functional theory. We consider Thomas-Fermi equation theory and related models namely initial TF, TFD, TFD W and TFD - lW model. Wave function or density of rare elements like Ne, Ar, Kr, Xe is calculated from general equation, then we draw the density with respect to distance for all these elements. As it is shown all these densities have a maximum value in an exact distance from the center of ions so probably the chances of existence of electrons in this distance are more than others.