Applying 4K, (Ultra HD) Real-time video streaming via the internet network, with low bitrate and low latency, is the challenge this paper addresses. Compression technology and transfer links are the important elements that influence video quality. So, to deliver video over the internet or another fixed capacity medium, it is essential to compress the video to more controllable bitrates (customarily in the 1-20 Mbps range). In this study, the video quality is examined using the H.265/HEVC compression standard, and the relationship between quality of video and bitrate flow is investigated using various constant rate factors, GOP patterns, quantization parameters, RC-lookahead, and other types of video motion sequences. The ultra-high-definition video source is used, down sampled and encoded at multiple resolutions of (3480x2160), (1920x1080), (1280x720), (704x576), (352x288), and (176x144). To determine the best H265 feature configuration for each resolution experiments were conducted that resulted in a PSNR of 36 dB at the specified bitrate. The resolution is selected by delivery (encoder resource) based on the end-user application. While video streaming adapted to the available bandwidth is achieved via embedding a controller with MPEG DASH protocol at the client-side. Video streaming Adaptation methods allow the delivery of content that is encoded at different representations of video quality and bitrate and then dividing each representation into chunks of time. Through this paper, we propose to utilize HTTP/2 as a protocol to achieve low latency video streaming focusing on live streaming video avoiding the problem of HTTP/1.
Abstract
In this paper presents two dimensional turbulent flow of different nanofluids and ribs configuration in a circular tube have been numerically investigation using FLUENT 6.3.26. Two samples of CuO and, ZnO nanoparticles with 2% v/v concentration and 40 nm as nanoparticle diameter combined with trapezoidalribs with aspect ratio of p/d=5.72 in a constant tube surface heat flux were conducted for simulation. The results showed that heat flow as Nusselt number for all cases raises with Reynolds number and volume fraction of nanofluid, likewise the results also reveal that ZnO with volume fractions of 2% in trapezoidal ribs offered highest Nusselt number at Reynolds number of Re= 30000.
Key
... Show MoreIn this research, a low cost, portable, disposable, environment friendly and an easy to use lab-on-paper platform sensor was made. The sensor was constructed using a mixture of Rhodamine-6G and gold nanoparticles also Sodium chloride salt. Drop–casting method was utilized as a technique to make a platform which is a commercial office paper. A substrate was characterized using Field Emission Scanning Electron Microscope, Fourier transform infrared spectroscopy, UV-visible spectrophotometer and Raman Spectrometer. Rh-6G Raman signal was enhanced based on Surface Enhanced Raman Spectroscopy technique utilized gold nanoparticles. High Enhancement factor of Plasmonic commercial office paper reaches up to 0.9 x105 because of local surface pl
... Show MoreThis paper proposes feedback linearization control (FBLC) based on function approximation technique (FAT) to regulate the vibrational motion of a smart thin plate considering the effect of axial stretching. The FBLC includes designing a nonlinear control law for the stabilization of the target dynamic system while the closedloop dynamics are linear with ensured stability. The objective of the FAT is to estimate the cubic nonlinear restoring force vector using the linear parameterization of weighting and orthogonal basis function matrices. Orthogonal Chebyshev polynomials are used as strong approximators for adaptive schemes. The proposed control architecture is applied to a thin plate with a large deflection that stimulates the axial loadin
... Show MoreThe aim of this paper is to design a PID controller based on an on-line tuning bat optimization algorithm for the step-down DC/DC buck converter system which is used in the battery operation of the mobile applications. In this paper, the bat optimization algorithm has been utilized to obtain the optimal parameters of the PID controller as a simple and fast on-line tuning technique to get the best control action for the system. The simulation results using (Matlab Package) show the robustness and the effectiveness of the proposed control system in terms of obtaining a suitable voltage control action as a smooth and unsaturated state of the buck converter input voltage of ( ) volt that will stabilize the buck converter sys
... Show MoreThe flexible joint robot (FJR) typically experiences parametric variations, nonlinearities, underactuation, noise propagation, and external disturbances which seriously degrade the FJR tracking. This article proposes an adaptive integral sliding mode controller (AISMC) based on a singular perturbation method and two state observers for the FJR to achieve high performance. First, the underactuated FJR is modeled into two simple second-order fast and slow subsystems by using Olfati transformation and singular perturbation method, which handles underactuation while reducing noise amplification. Then, the AISMC is proposed to effectively accomplish the desired tracking performance, in which the integral sliding surface is designed to reduce cha
... Show MoreVideo represented by a large number of frames synchronized with audio making video saving requires more storage, it's delivery slower, and computation cost expensive. Video summarization provides entire video information in minimum amount of time. This paper proposes static and dynamic video summarization
methods. The proposed static video summarization method includes several steps which are extracting frames from video, keyframes selection, feature extraction and description, and matching feature descriptor with bag of visual words, and finally save frames when features matched. The proposed dynamic video summarization
method includes in general extracting audio from video, calculating audio features
This paper proposes an on-line adaptive digital Proportional Integral Derivative (PID) control algorithm based on Field Programmable Gate Array (FPGA) for Proton Exchange Membrane Fuel Cell (PEMFC) Model. This research aims to design and implement Neural Network like a digital PID using FPGA in order to generate the best value of the hydrogen partial pressure action (PH2) to control the stack terminal output voltage of the (PEMFC) model during a variable load current applied. The on-line Particle Swarm Optimization (PSO) algorithm is used for finding and tuning the optimal value of the digital PID-NN controller (kp, ki, and kd) parameters that improve the dynamic behavior of the closed-loop digital control fue
... Show MoreThe virtual decomposition control (VDC) is an efficient tool suitable to deal with the full-dynamics-based control problem of complex robots. However, the regressor-based adaptive control used by VDC to control every subsystem and to estimate the unknown parameters demands specific knowledge about the system physics. Therefore, in this paper, we focus on reorganizing the equation of the VDC for a serial chain manipulator using the adaptive function approximation technique (FAT) without needing specific system physics. The dynamic matrices of the dynamic equation of every subsystem (e.g. link and joint) are approximated by orthogonal functions due to the minimum approximation errors produced. The contr
Electromyogram (EMG)-based Pattern Recognition (PR) systems for upper-limb prosthesis control provide promising ways to enable an intuitive control of the prostheses with multiple degrees of freedom and fast reaction times. However, the lack of robustness of the PR systems may limit their usability. In this paper, a novel adaptive time windowing framework is proposed to enhance the performance of the PR systems by focusing on their windowing and classification steps. The proposed framework estimates the output probabilities of each class and outputs a movement only if a decision with a probability above a certain threshold is achieved. Otherwise (i.e., all probability values are below the threshold), the window size of the EMG signa
... Show MoreAerial Robot Arms (ARAs) enable aerial drones to interact and influence objects in various environments. Traditional ARA controllers need the availability of a high-precision model to avoid high control chattering. Furthermore, in practical applications of aerial object manipulation, the payloads that ARAs can handle vary, depending on the nature of the task. The high uncertainties due to modeling errors and an unknown payload are inversely proportional to the stability of ARAs. To address the issue of stability, a new adaptive robust controller, based on the Radial Basis Function (RBF) neural network, is proposed. A three-tier approach is also followed. Firstly, a detailed new model for the ARA is derived using the Lagrange–d’A
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