فهرست مطالب بهرام صادقی

Exercise training is important to reduce the physical performance disorders among mentally retarted children. The aim of the present study was to analyze the effect of two combined exercise trainings (trampoline-racquet and rope skipping-racquet) on physical fitness indicators and movement ability among mentally retarded children.

Twenty-four mentally retarded male students, aged 8-15 y., with an IQ of 50 to 70 were purposefully selected and randomly divided into two experimental groups and one control (each eight persons). One of the experimental groups performed trampoline-racquet training, and the second group performed rope-racquet training (eight-week, three sessions per week, 60 min in each session). The control group did not participate in the intervention exercise and followed the school’s regular training programs. Before and after the exercise trainings, physical fitness and mobility tests were taken from all subjects. Analysis of variance with repeated measures and Bonferroni’s tests were used for data analysis at a significance level of p≤0.05.

Both exercise trainings improved static balance with eyes closed, dynamic balance, abdominal muscle endurance, lower limb muscle power, and motor ability compared to the control group, but there was no significant difference between the two training programs. Moreover, the static balance index of the left leg with eyes open and explosive power was significantly improved only in the rope skipping-rocket group compared to the trampoline-rocket and also the control group; while there was no significant differences between the indicators of cardiorespiratory fitness and hand muscle power between the three groups.

Studies suggest that exercise training programs can improve physical fitness and mobility in mentally retarded children.

The effect of plyometric training on physical function is well known and the effect of exercise training with blood flow restriction has also been studied. However, the effect of aquatic plyometric with blood flow restriction has not been studied. Therefore, the aim of this study was to investigate the effect of aquatic plyometric training with and without blood flow restriction on physical fitness in young active women.

The study was a quasi-experimental study with a pre-post test. Thirty young women aged 18 to 30 years were randomly allocated to three groups: aquatic plyometric training with blood flow restriction (n = 10), aquatic plyometric training without blood flow restriction (n = 10) and control (n = 10). The protocol included six weeks of plyometric training (three days a week). The intensity of training (number of sets and repetitions) was considered less in the group with blood flow restriction than the other group. Restriction of blood flow was applied by tightening the elastic band of the upper thigh. Physical function tests were taken before and after the training program. Data were analyzed by using repeated measures of ANOVA with between subject factor. The significant level was set at P≤0.05.

Significant improvements were found in fat percentage, anaerobic power, lower body power, speed and maximum strength following aquatic plyometric training with blood flow restriction (P<0.05). There were no significant differences between the groups in other variables of physical function including weight, body mass index, agility and upper body power (P>0.05).

According to the results of this study, aquatic plyometric training with blood flow restriction could be effective in improving fat percentage, anaerobic power, lower body power, speed and maximum strength of young active women.

Three-dimensional classification of urban features is one of the important tools for urban management and the basis of many analyzes in photogrammetry and remote sensing. Therefore, it is applied in many applications such as planning, urban management and disaster management. In this study, dense point clouds extracted from dense image matching is applied for classification in urban areas. Applied images are acquired using a Micasense RedEdge multispectral camera to increase the classification accuracy. The band to band registration is one of the existing challenges of multi-spectral camera, which the SIFT algorithm is used to extract the corresponding features of each band. One band selected as reference and other bands are transferred to the reference band by projective transformation. Finally, the bands are combined to create a color image from each three bands. So, two point clouds are generated using dense image matching techniques from two sets of images. To produce a multi-spectral point cloud, the two set of point clouds have been integrated using nearest neighbor interpolation. The multi-spectral point clouds are classified by using random forest algorithm, structural and multi-spectral features. This process composed of three parts as structural information, multi-spectral information, and integration of both. Finally, the results are shown a 25% improvement in the accuracy of the integration of multi-spectral and structural information compared to multi-spectral information and 32% improvement in the accuracy of the integration of multi-spectral and structural information compared to structural information. Classification using visible information (RGB) instead of multispectral information resulted in an accuracy drop by 5%.