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.

Background and aims: Parking areas that are gathering places for tank trucks are potentially dangerous places. This study analyzes accident consequences of oil products carriers, to check and compare the hazard radius with recommended Separation Distances. Methods: This descriptive-analytical study was carried out in 5 stages, including: scenario selection, determination of the accidents source parameters, determination of atmospheric conditions, selection of reference values, and modeling the analysis of scenarios and its consequences. The process hazard analysis software tool (PHAST) is used to analyze the consequences of accidents in liquid petroleum gas and gasoline tankers. Results: Based on average values, the appropriate Separation Distances are 50±25. 8 m and 361. 4±184. 8 m for leakage and catastrophic rupture of a liquefied petroleum gas (LPG) tanker, and 28. 3±14. 9 m and 571. 2±137. 6 m for leakage and catastrophic rupture of a petrol tanker, respectively. The Separation Distance based on the catastrophic rupture is so large that it is not practical for the design and management of road tanker parking area. According to the leakage scenario, a safety Distance of 28. 3-50 m is required. Separation Distance based on catastrophic rupture is so great, it has no applicability in designing and managing road tanker parking areas. According to the leakage scenario, a safety Distance of approximately 28. 3-50 m is needed. Conclusion: With the existing Separation criteria a tanker accident may spread to other parts of the parking lot and it can lead to a disaster. Therefore, it seems necessary to review and update the guidelines and standards in parking lot design and Separation Distances as well as emergency planning.

Undoubtedly, bridges have substantially effect in metropolitan areas and are usually built to connect between two roads in order to decrease traffic. Pounding, is one of the important parameters to design different bridges as this structures should be controlled during seismic excitation to provide safety conditions in order to organize and support unpredictable situations. During very strong earthquake, bridges may experience large horizontal relative displacement, which may lead to pounding if sufficient gap size is not considered between adjacent slabs of bridge. Insufficient Separation Distance is naturally caused to collide between two slabs and, subsequently, stiffness of bridge is decreased and finally, collapse is occurred. In order to determine impact force and also absorption energy during collision, many researchers have demonstrated different theories and also suggested various equations by using impact velocity before and after impact. In this study, special element is used between two slabs to determine impact force and a new equation of motion is mathematically presented to calculate impact damping ratio focusing on coefficient of restitution.

In this paper, flow Separations at downstream of piggyback pipelines due to the steady current have experimentally been investigated for various Reynolds numbers, gap ratios and relative diameters of the two pipes. A number of experiments including 6 verification tests and 50 main tests were conducted in a channel with length of 10m, width of 0.3m and 0.5m depth using Teflon rods (PTFE) with different diameters. To visualize the Separation pattern, the polystyrene particles with a density of 1.05gr/cm3 have been used and the whole processes of tests have been recorded using a digital camera. The experimental results have shown that with adding the secondary pipe stuck to the main pipe, the symmetrical Separation pattern vanished and its length reduced up to 60%. Also, it was observed that with increasing the gap ratio to a certain extent, the Separation lengths increased and decreased gradually for the main and secondary pipes, respectively. However, further increase in the gap ratio showed that the two pipes behaved separately and the Separation or recirculation patterns became symmetrical and their effect to each other became negligible.

One of the primary principles in surgery is suitable and safe anesthesia with minimum side effects. Many drugs are used for this purpose. Propofol is a suitable drug for anesthesia in dogs. This drug, of course, can have effects on some of body parameters, the matter that should be controlled according to the sick subject. In this study, 10 male mixed adult dogs with about 20- 25kg weight were selected. The miteral valve of the dogs was surveyed by ultrasonography machine and their M-mode miteral value echocardiogram was registered. Then the Distance of E point to the wall between ventricles was measured. After preparation of M-mode miteral value echocardiography, the animals were anaesthetized by propofol with suggestive dose of 6 mg/kg through vein. M-mode echocardiography changes of miteral valve booked immediately after venous injection until the animal regained its consciousness. Then recorded changes of echocardiograms at especial times were transformed into computer pictures. Also the Distance of E point to the septum in the same way was measured. Changes in the Distance of E point to septum of M-mode valve echocardiography after and before injection were compared. In this study, the mean of Distance in control animal was 5.36Ÿ0.23 millimeters and the mean of Distance in anaesthetized animals was 6.00Ÿ0.20 millimeters which showed significant difference between them (P<0.05). And also this study indicated that Propofol can affect this Distance.

Background & Aim: There are several methods for determination of occlusal vertical dimension. The vertical dimension of rest position, interocclusal Distance and closest speaking space are two important methods. The purpose of this study was comparison the variability of interocclusal Distance and closest speaking space in denture wearers.Method &Materials: The subjects were 34 edentulous patients (18 males & 16 females with mean age of 56) who had received complete dentures in the prosthodontics department of Isfahan dental school. They had good residual ridges. The dentures had correct clinical vertical dimension with 1-2mm overjet and 0.5 -1mm overbite. There was no evidence of neuromuscular and TMJ problems. The TOM guage was used for measuring the vertical dimension of rest position and «S» position.Results: The results showed that the mean and standard deviation of interocclusal Distance were smaller than closest speaking space. Paired T-test and Levene's test were used for statistical analysis. There was a statistically difference between interocclusal Distance and closest speaking space, so the interocclusal Distance was less variable than closest speaking space (P<0.05).Conclusion: The closest speaking space during S position is affected by the occlusion, vertical and horizontal overlap of anterior teeth. These factors are up to dentist's judgement in complete denture and can influence the variability of vertical dimension of S position. Because of this variability it is recommended to use several methods for determining of vertical dimension.

Undoubtedly, bridges have substantially effect in metropolitan areas and are usually built to connect between two roads in order to decrease traffic. Pounding, is one of the important parameters to design different bridges Pounding, is one of the important parameters to design different bridges as this structures should be controlled during seismic excitation to provide safety conditions in order to organize and support unpredictable situations. During very strong earthquake, bridges may experience large horizontal relative displacement, which may lead to pounding if sufficient gap size is not considered between adjacent slabs of bridge. Insufficient Separation Distance is naturally caused to collide between two slabs and, subsequently, stiffness of bridge is decreased and finally, collapse is occurred. In order to determine critical Distance between two slabs, a mathematical program is used based on neural network to coordinate the result of analyses in order to calculate sufficient Separation Distance for avoiding collisions during earthquake.

In order to reduce errors and save money and energy, this research has dealt anomaly Separation. The importance of detecting anomaly values from the background is not hidden from anyone. For this purpose, several methods have been invented, among which we can mention Mahalanobis Distance Separation method, which is an effective and multi-variable method for separating anomalous values from the background. In the present study, the performance of the combination of the above Separation method with three data mining methods; K-Nearest Neighbor, Simple Bayes Classifier and Convolutional Neural Network is investigated. In this way, after separating the anomalous values of copper and molybdenum in the case of 177 samples obtained from the surface sampling operation in the area of Zafarghand with the Mahalanobis Distance method, in order to predict these values for each random sample, The above three data mining methods were used. The results show that K-Nearest Neighbor method is much stronger, because in the network designed by this method, no sample has been wrongly identified, which shows the high accuracy of the designed network. It should be noted that the number of wrongly predicted samples for convolutional neural network and Bayes methods are reported as 2 and 3, respectively. Considering the far more acceptable error rate for the network designed by the combination of K-Nearest Neighbor method and Mahalanobis intervals, the said combination has been introduced to the decision makers of this industry as a reliable and useful method to reach the most accurate predictions.