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A solution of the fractional N-dimensional radial Schrodinger equation with the Deng-Fan potential is investigated by the generalized fractional NU method. The analytical formulas of energy eigenvalues and corresponding eigen functions for the Deng-Fan potential are generated. Furthermore, the current results are applied to several diatomic molecules for the Deng-Fan potential as well as the shifted Deng Fan potential. For both the Deng-Fan potential and its shifted potential, the effect of the fractional parameter on the energy levels of various diatomic molecules is examined numerically and graphically. We found that the energy eigenvalues are gradually improved when the fractional parameter increases. The energy spectra of various diatomic molecules are also evaluated in three-dimensional space and higher dimensions. It is worthy to note that the energy spectrum raises as the number of dimensions increases. In addition, the dependence of the energy spectra of the Deng-Fan potential and its shifted potential on the reduced mass, screening parameter, equilibrium bond length, rotational and vibrational quantum numbers is illustrated. To validate our findings, we estimate the energy levels of the Deng-Fan potential and shifted Deng-Fan potential at the classical case for various diatomic molecules and found that they are entirely compatible with earlier studies., Comment: 20 pages, 6 figures

This paper develops a framework to study multi-hop relaying in a vehicular network consisting of vehicles and Road Side Units (RSUs), and the effect of this relaying on the network coverage and the communication delay. We use a stochastic geometry model that consists of a combination of Poisson Line Process (PLP) and 1D Poisson Point Process (PPP) to reliably characterize the vehicular network layout and the locations of the vehicles and the RSUs. Using this model, we analyze the effect of the different network parameters on the coverage provided by the RSUs to the vehicles. Then, we investigate how the uncovered vehicles can receive their intended packets by relaying them through multiple hops that form connected paths to the RSUs. We also analyze the delay introduced to packet delivery due to multi-hop relaying. Namely, we present results that illustrate the coverage gains achieved through multi-hop relaying and the delays induced. Such results could be used by network planners and operators to decide on the different configurations and operational parameters of the vehicular network to suit particular scenarios and objectives., Comment: Addendum for a paper

Thermodynamics properties of heavy mesons are calculated within the framework of the N-dimensional radial Schrodinger equation. The Cornell potential is extended by including the quadratic potential plus the inverse of quadratic potential. The energy eigenvalues and the corresponding wave functions are calculated in the N-dimensional space using the Nikiforov-Uvarov (NV) method. The obtained results are applied for calculating the mass of spectra of charmonium, bottomonium, bc, and cs mesons. The thermodynamics properties of heavy quarkonia such as, the mean energy, specific heat, free energy, and entropy are calculated. The effect of temperature and the dimensionality number on heavy mesons masses and thermodynamics properties is investigated. The obtained results are improved in comparison with other theoretical approaches and in a good agreement with experimental data. We conclude that the present potential well describes thermodynamic properties in the three-dimensional space and also the higher dimensional space., Comment: 17 pages, 10 Figures, 4 Tables

The exact solution of N- dimensional radial Schr\"odinger equation with the generalized Cornell potential has been obtained using the Laplace transformation (LT) method. The energy eigenvalues and the corresponding wave functions for any state have been determined. The eigenvalues for some special cases of the generalized Cornell potential are obtained. The present results are applied to calculate the mass spectra of heavy quarkonium systems such as charmonium and bottomonium and the bc meson. A comparison is discussed with the experimental data and recent works. The present results are improved in comparison with other recent studies and are in a good agreement with the experimental data. The effect of the dimensional number (N) on the meson masses has been studied. We note that the meson masses increase in higher dimensions., Comment: 14 pages, 1 figure

The N-dimensional radial Schr\"odinger equation has been solved using the analytical exact iteration method (AEIM), in which the Cornell potential is generalized to finite temperature and chemical potential. The energy eigenvalues have been calculated in the N-dimensional space for any state (n, l). The present results have been applied for studying quarkonium properties such as charmonium and bottomonium masses. The binding energies and the mass spectra of heavy quarkonia are studied in the N-dimensional space. The dissociation temperatures for different states of heavy quarkonia are calculated in the three dimensional space. The influence of dimensionality number (N) has been discussed on the dissociation temperatures. A comparison is studied with other recent works. We conclude that the AEIM successes to predict the heavy-quarkonium properties at finite temperature and chemical potential., Comment: 17 Pages, 9 Figures, and 3 Tables

The aim of this study is to present a good modernistic strategy for solving some well-known classes of Lane-Emden type singular differential equations. The proposed approach is based on the reproducing kernel Hilbert space (RKHS) and introducing the reproducing kernel properties in which the initial conditions of the problem are satisfied. The analytical solution that obtained involves in the form of a convergent series with easily computable terms in its reproducing kernel space. The approximation solution is expressed by n-term summation of reproducing kernel functions and it is converge to the analytical solution. Our investigations indicate that there is excellent agreement between the numerical results and the RKHS method, which is applied to some examples to illustrate the accuracy, efficiency, and applicability of the method. The present work shows the potential of the RKHS technique in solving such nonlinear singular initial value problems., Comment: International Arab Conference on Mathematics and Computations (2016), Zarqa University, Jordan

The N-dimensional radial Schrodinger equation with an extended Cornell potential is solved. The analytical exact iteration method is applied. The energy eigenvalues are calculated in the N-dimensional space. The charmonium meson, the bottomonium meson and the bc meson masses are calculated in the N-dimensional space. The special cases are obtained from the general case. The study of the effect of dimensionality number is studied. The mean value of the radius and the mean square velocity of charmonium meson, bottomonium meson, and bc meson are calculated. The present results are improved in comparison with other recent studies and are in good agreement with the experimental data. Therefore, the present method with the present potential gives successfully description of heavy quarkonium properties., Comment: 7 pages, 3 figures, and 6 tables

This paper deals with the improvement of energy efficiency in wireless sensor networks (WSN).Taking into consideration the power saving problem which is of crucial importance when the sensors are supplied by a limited power source, this paper proposes a method that optimizes as much as possible the transmission power of the sensors. Under the assumption of perfect channel between the Base Station (BS) and the Sensor Nodes (SN's) and with sufficient power resources at the BS, transferring the effort of transmission power to the BS will not be a peculiar issue. This paper proposes a method that reduces the transmitted data at the SN's and compensate this by requesting the variance of the measured value form predicted values. Furthermore, a request management algorithm (RMA) is developed to reduce the amount of requested data based on consecutive successive predictions. The result of this method reveals a major impact on reducing the transmission power at the SN's. Keywords: Wireless Sensor Networks, Data Reduction, Time Series Forecasting, Artificial Neural Networks.

Mobile video is considered a major upcoming application and revenue generator for broadband wireless networks like WiMAX and LTE. Therefore, it is important to design a proper resource allocation scheme for mobile video, since video traffic is both throughput consuming and delay sensitive.

Most of the IEEE 802.16e Mobile WiMAX scheduling proposals for real-time traffic using Unsolicited Grant Service (UGS) focus on the throughput and the guaranteed latency. The delay variation or delay jitter and the effect of burst overhead have not yet been investigated. This paper introduces a new technique called Swapping Min-Max (SWIM) for UGS scheduling that not only meets the delay constraint with optimal throughput, but also minimizes the delay jitter and burst overhead., Comment: IEEE Systems Journal, August 2010

Recently, HTTP-based adaptive streaming has become the de facto standard for video streaming over the Internet. It allows clients to dynamically adapt media characteristics to network conditions in order to ensure a high quality of experience, that is, minimize playback interruptions, while maximizing video quality at a reasonable level of quality changes. In the case of live streaming, this task becomes particularly challenging due to the latency constraints. The challenge further increases if a client uses a wireless network, where the throughput is subject to considerable fluctuations. Consequently, live streams often exhibit latencies of up to 30 seconds. In the present work, we introduce an adaptation algorithm for HTTP-based live streaming called LOLYPOP (Low-Latency Prediction-Based Adaptation) that is designed to operate with a transport latency of few seconds. To reach this goal, LOLYPOP leverages TCP throughput predictions on multiple time scales, from 1 to 10 seconds, along with an estimate of the prediction error distribution. In addition to satisfying the latency constraint, the algorithm heuristically maximizes the quality of experience by maximizing the average video quality as a function of the number of skipped segments and quality transitions. In order to select an efficient prediction method, we studied the performance of several time series prediction methods in IEEE 802.11 wireless access networks. We evaluated LOLYPOP under a large set of experimental conditions limiting the transport latency to 3 seconds, against a state-of-the-art adaptation algorithm from the literature, called FESTIVE. We observed that the average video quality is by up to a factor of 3 higher than with FESTIVE. We also observed that LOLYPOP is able to reach a broader region in the quality of experience space, and thus it is better adjustable to the user profile or service provider requirements., Comment: Technical Report TKN-16-001, Telecommunication Networks Group, Technische Universitaet Berlin. This TR updated TR TKN-15-001

Recently, HTTP-Based Adaptive Streaming has become the de facto standard for video streaming over the Internet. It allows the client to adapt media characteristics to varying network conditions in order to maximize Quality of Experience (QoE). In the case of live streaming this task becomes particularly challenging. An important factor than might help improving performance is the capability to correctly predict network throughput dynamics on short to medium timescales. It becomes notably difficult in wireless networks that are often subject to continuous throughput fluctuations. In the present work, we develop an adaptation algorithm for HTTP-Based Adaptive Live Streaming that, for each adaptation decision, maximizes a QoE-based utility function depending on the probability of playback interruptions, average video quality, and the amount of video quality fluctuations. To compute the utility function the algorithm leverages throughput predictions, and dynamically estimated prediction accuracy. We are trying to close the gap created by the lack of studies analyzing TCP throughput on short to medium timescales. We study several time series prediction methods and their error distributions. We observe that Simple Moving Average performs best in most cases. We also observe that the relative underestimation error is best represented by a truncated normal distribution, while the relative overestimation error is best represented by a Lomax distribution. Moreover, underestimations and overestimations exhibit a temporal correlation that we use to further improve prediction accuracy. We compare the proposed algorithm with a baseline approach that uses a fixed margin between past throughput and selected media bit rate, and an oracle-based approach that has perfect knowledge over future throughput for a certain time horizon., Comment: Technical Report TKN-15-001, Telecommunication Networks Group, Technische Universitaet Berlin. Updated by TR TKN-16-001, available at http://arxiv.org/abs/1603.00859