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.
Heuristic Program proposal for the treatment of talented emotional and Cognitive problems .
1-The Curtent research aims : to identify the needs of gifted students and their problems and Ways to diagnose .
2-reprepare aproposal heuristic program for the treatment of emotional and Cognitive talented problems .
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Chapter ll : Includes recipes gifted child and Methods diagnosis gifted by filtrontion and standavds of personal and mental and behavioral Doramwaliman and parental Features and Leader in the detection of the gif
... Show MoreIn this paper, a study was made to determine the properties of Jovian radio bursts emitted at frequency 20.1MHZ. The data were provided from the Radio Jove archive for twelve years (2000-2012) for multi stations. The duration time for Long bursts (L) was (10-30) seconds and for Short bursts (S) was (10-20) seconds. The effect of radio bursts from the Sun and the galactic background were calculated at the same frequency and were found that radio bursts from the Sun will reduce the occurrence probability of Jovian radio bursts much more than radio bursts from the galactic background. The distribution of Jovian radio bursts was different; the occurrence probability with respect to the northern latitudes was more than the southern latitudes.
Teikyo Medical and medicine Journal (ISSN:03875547) is a monthly peer reviewed fast publishing international medical and medicine journal that aims to publish good quality of Medical and pharmaceutical, medicine and health science Journal.
This study aims to determine the effect of x-ray radiation resulting from solar flares in high-frequency radio wave communications through the ionosphere and to study the radio blackout events that occur over Iraq, located within (38,28) latitude, and (38,49) longitude. Using X-ray data during strong X flares and radio wave absorption data across the D ionosphere for 10 years from 2012 to 2021. The study concluded that there were 43 events of x-flare, most of which were during years of high solar activity. All of these flares produced X-rays that caused a radio blackout, R3 and only 13 events affected Iraq.
This study relates to the estimation of a simultaneous equations system for the Tobit model where the dependent variables ( ) are limited, and this will affect the method to choose the good estimator. So, we will use new estimations methods different from the classical methods, which if used in such a case, will produce biased and inconsistent estimators which is (Nelson-Olson) method and Two- Stage limited dependent variables(2SLDV) method to get of estimators that hold characteristics the good estimator .
That is , parameters will be estim
... Show MoreThe aim of this paper is to approximate multidimensional functions f∈C(R^s) by developing a new type of Feedforward neural networks (FFNS) which we called it Greedy ridge function neural networks (GRGFNNS). Also, we introduce a modification to the greedy algorithm which is used to train the greedy ridge function neural networks. An error bound are introduced in Sobolov space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result in [1]).