A robust video-bitrate adaptive scheme at client-aspect plays a significant role in keeping a good quality of video streaming technology experience. Video quality affects the amount of time the video has turned off playing due to the unfilled buffer state. Therefore to maintain a video streaming continuously with smooth bandwidth fluctuation, a video buffer structure based on adapting the video bitrate is considered in this work. Initially, the video buffer structure is formulated as an optimal control-theoretic problem that combines both video bitrate and video buffer feedback signals. While protecting the video buffer occupancy from exceeding the limited operating level can provide continuous video streaming, it may also cause a video bitrate oscillation. So the video buffer structure is adjusted by adding two thresholds as operating points for overflow and underflow states to filter the impact of throughput fluctuation on video buffer occupancy level. Then a bandwidth prediction algorithm is proposed for enhancing the performance of video bitrate adaptation. This algorithm's work depends on the current video buffer level, video bitrate of the previous segment, and iterative throughput measurements to predict the best video bitrate for the next segment. Simulation results show that reserving a bandwidth margin is better in adapting the video bitrate under bandwidth variation and then reducing the risk of video playback freezing. Simulation results proved that the playback freezing happens two times: firstly, when there is no bandwidth margin used and secondly, when the bandwidth margin is high while smooth video bitrate is obtained with moderate value. The proposed scheme is compared with other two schemes such as smoothed throughput rate (STR) and Buffer Based Rate (BBR) in terms of prediction error, QoE preferences, buffer size, and startup delay time, then the proposed scheme outperforms these schemes in attaining smooth video bitrates and continuous video playback.
In this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performa
... Show MoreKS Ismaeil, BR Jawad, Journal of Physical Education, 2023
The current study aims to find a new plan to manage the water quality of the western part of the Hammar Marsh to reduce the salts that cause problems for the marshes and preserve their environmental life by isolating the southwestern part of the Hammar Marsh by closing the outlet under the railway embankment. The outlet is discharging saline water to the east-western part of Al Hammar Marsh. After isolating the southwestern part of the marsh, a new outlet is proposed. The impact of the flow hydrodynamics on improving the water quality was simulated using the SMS model. The hydrodynamics and water quality simulation models for the marsh are : a hydrodynamic model and average depth (SMS RMA2) and a two-dimensional water quality model (SMS
... Show MoreThe map of permeability distribution in the reservoirs is considered one of the most essential steps of the geologic model building due to its governing the fluid flow through the reservoir which makes it the most influential parameter on the history matching than other parameters. For that, it is the most petrophysical properties that are tuned during the history matching. Unfortunately, the prediction of the relationship between static petrophysics (porosity) and dynamic petrophysics (permeability) from conventional wells logs has a sophisticated problem to solve by conventional statistical methods for heterogeneous formations. For that, this paper examines the ability and performance of the artificial intelligence method in perme
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Objectives: The present study aims to evaluate effectiveness of educational program the nurses' knowledge towards early prediction of acquired weakness in the intensive care unit.
Methodology: A pre-experimental study design (comparison of two groups), which was achieved through the pre and post-test method for the study sample through the application of an educational program in the intensive care unit of Al-Zahra Teaching Hospital in Kut city, Wasit Governorate. The study was conducted for the period from 28th April 2022 to 15th August 2022 by selecting a purposive (non-probability) sample for this study. The study sample size was (52) nu
... Show MoreThe Makhoul Dam project proposed to be established is considered one of the strategic projects in Iraq as it works to insurance large quantity of water spare in flood seasons, increase the storage capacity of the dams in Iraq, as well as increase food security. The Makhool Dam is located on Tigris River in Salah al-Din Governorate, and 8 km south of the meeting point of the Tigris River with the Lower Zab River. The lake area is about 256 km2. In this research, a mathematical model was prepared by using HEC-RAS Two Dimension Software to analyze the velocity patterns and water depths inside makhool dam reservoir at the highest operational water elevation, based on the designs prepared
In this paper, we will provide a proposed method to estimate missing values for the Explanatory variables for Non-Parametric Multiple Regression Model and compare it with the Imputation Arithmetic mean Method, The basis of the idea of this method was based on how to employ the causal relationship between the variables in finding an efficient estimate of the missing value, we rely on the use of the Kernel estimate by Nadaraya – Watson Estimator , and on Least Squared Cross Validation (LSCV) to estimate the Bandwidth, and we use the simulation study to compare between the two methods.
This world is moving towards knowledge economy which basically depends on knowledge and information. So, the economic units need to develop its financial reporting system which helps to provide useful information in timeliness for investors in accordance with the requirements of the knowledge economy and meets the needs of those investors. This research aims to revealing the reflects of knowledge economy on the approaches of financial reporting and suggesting a financial reporting model in the environment of knowledge economy, depending on combining the value approach with the events approach using database and communication technology and providing useful accounting information for all users regardless of
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