In this paper, we characterize the percolation condition for a continuum secondary cognitive radio network under the SINR model. We show that the well-established condition for continuum percolation does not hold true in the SINR regime. Thus, we find the condition under which a cognitive radio network percolates. We argue that due to the SINR requirements of the secondaries along with the interference tolerance of the primaries, not all the deployed secondary nodes necessarily contribute towards the percolation process- even though they might participate in the communication process. We model the invisibility of such nodes using the concept of Poisson thinning, both in the presence and absence of primaries. Invisibility occurs due to nodes that i) cannot decode transmissions except from their nearest neighbors, ii) are always interfered, and iii) belong to isolated components. We find the thinning probability in terms of primary and secondary densities, communication radii, and interference cancellation coefficient. Further, we show how the effective coverage radius shrinks which also adds to the thinning. Theoretical findings are validated through simulations.
Background: One of the most common and prevalent oral diseases among adolescents is periodontal disease particularly gingivitis, however enamel anomalies and dental trauma could occur. Aims of the study: This study was conducted among 14-15 years intermediate school male students in urban area of Al-Khalis city to assess the oral hygiene (dental plaque) and to estimate the prevalence and severity of gingivitis, enamel anomalies, as well as traumatic dental injuries, furthermore to show the significant difference between these two ages concerning these oral problems. Materials and methods: In this study the total sample consisted of 735 students (397 aged 15 years and 338 aged 14 years ). In present study dental plaque was recorded accord
... Show MoreThis paper analyzes the effect of scaling-up model and acceleration history on seismic response of closed-ended pipe pile using a finite element modeling approach and the findings of 1 g shaking table tests of a pile embedded in dry and saturated soils. A number of scaling laws were used to create the numerical modeling according to the data obtained from 1 g shake table tests performed in the laboratory. The current study found that the behaviors of the scaled models, in general have similar trends. From numerical modeling on both the dry and saturated sands, the normalized lateral displacement, bending moment, and vertical displacement of piles with scale factors of 2 and 35 are less than those of the pile with a scale factor of 1 and the
... Show MoreThe present work focuses on examining the strategy of cognitive trips and the Arabic language teachers’ training needs of such a strategy when teaching Arabic language courses in the Saudi Arabia Kingdom. To achieve the objective of the study, and check whether this strategy is used in lesson planning, lesson teaching, or lesson assessment, a descriptive approach and a questionnaire have been adopted. The researchers used a number of statistical tools, and chose a purposive sample, which consists of (58) Arabic language teachers from Saudi Arabia Kingdom. Results have shown that the training needs of Arabic language teachers for implemining the strategy of cognitive journeys while teaching Arabic language courses came in the following
... Show MoreCommunity detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem. In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a
... Show MoreThis paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is bett
... Show MoreThis work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOM’s were used and a comparison between the results from these SOM’s was given.
The next stage is the classification stage, and consists of self-organizing map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20
... Show MoreSensing insole systems are a promising technology for various applications in healthcare and sports. They can provide valuable information about the foot pressure distribution and gait patterns of different individuals. However, designing and implementing such systems poses several challenges, such as sensor selection, calibration, data processing, and interpretation. This paper proposes a sensing insole system that uses force-sensitive resistors (FSRs) to measure the pressure exerted by the foot on different regions of the insole. This system classifies four types of foot deformities: normal, flat, over-pronation, and excessive supination. The classification stage uses the differential values of pressure points as input for a feedforwar
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