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.

A spatial trajectory is a record of moving object’s spatial changes through time and is modeled by a sequence of discrete points with spatio-temporal coordinates. Increasing number of moving objects and positioning technologies resulted in immense number of spatio-temporal data needing various analyses. Extracting similar trajectories is one of the crucial analyses in spatial trajectories. So far various Distance Functions have been proposed for measuring similarity where each one has addressed similarity from its own point of view and is suitable for particular data with special characteristics. Thus, Functions effectiveness is not the same for all kind of data and applications and understanding capabilities and characteristics of Functions is the prerequisite of choosing the suitable function. In this paper, a comparative experimental study is conducted on the effectiveness of seven widely used trajectory similarity measures which are the base of many other former proposed Distance Functions and their advantages and drawbacks are discussed.

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.

Having a ranking range for each unit allows for assessing the extent to which the choice of DEA weights may affect the ranking derived from the cross-efficiency evaluation and can deal with the most important difficulty of cross-efficiency evaluations (i.e., the possible existence of alternative optimal solutions for the DEA weights, which may lead to different cross-efficiency scores depending on the choice that is made). This may, furthermore, yields some useful information in the case of real life problems. This paper develops the ranking ranges by the use of directional Distance Functions in calculating cross-efficiency evaluations. In this case, by simultaneously accounting for the inefficiency in inputs and outputs, more comprehensive ranking ranges were achieved in crossefficiency evaluations. A numerical example is presented to show the validity of the proposed procedure by comparing the results with those of the previous approaches.

In this paper, an alternative approach in operational modal analysis is presented, utilizing image processing technique and transmissibility Functions. Imaging sensors do not impose additional mass on the structure due to their non-contact nature, while transmissibility Functions, independent of excitation type, can directly extract mode shapes. The innovation of this research lies in combining these two techniques to record dynamic responses and identify modal properties. To capture the temporal response history from video signals, the block-matching method with sub-pixel accuracy was employed. Validation was conducted by recording the response of the tip of a cantilevered steel beam subjected to impact excitation, using a high-speed camera and a laser vibrometer, simultaneously. The RMSE plots in the time domain and the PSD in the frequency domain indicate high accuracy of this method. Using this approach, the displacement time histories of various points on the structure were extracted from the video signals, and the modal properties, including natural frequencies, damping ratios, and mode shapes, were identified using the transmissibility matrix method. The results obtained from the proposed method were compared with the stochastic subspace identification (SSI) method and analytical solutions. The findings reveal the accuracy of the modal identification approach introduced in this article. The highest relative error in estimating the natural frequencies of the first and second modes, compared to the values from the laser method, are 0.19% and 0.13%, respectively, and in comparison to the analytical values, they are 0.34% and 1.5%, respectively.

Persistent surveillance is one of an important problem in the field of aerial investigation, border patrolling, surveillance and search, Which distinguishes it from other matters by revisit time of major area. The main point of our problem is the minimizing of the time interval between two consecutive hits for a particular area that makes the details and dynamics tracking with higher accuracy. In this paper in order to achieve the minimum revisit time, the heuristic function based on the waypoints time age was used. This function defines the value of each point with the weight Functions that optimized by genetic algorithm in several successive iterations. These optimal values are dependent on the position of major point and number of UAV. In multi-agent problems, the patrolling pattern is determined by heuristic weight function in several iterations. Some basic patterns such as lawn mover and spiral are organized to calculate the minimum traveling Distance in the search area and obtain the comparative criteria for the results. The paper results lead to improved the navigation during aerial patrolling the area with the graded region, with respect to the UAV dynamics and minimum revisit time.

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.