Television white spaces (TVWSs) refer to the unused part of the spectrum under the very high frequency (VHF) and ultra-high frequency (UHF) bands. TVWS are frequencies under licenced primary users (PUs) that are not being used and are available for secondary users (SUs). There are several ways of implementing TVWS in communications, one of which is the use of TVWS database (TVWSDB). The primary purpose of TVWSDB is to protect PUs from interference with SUs. There are several geolocation databases available for this purpose. However, it is unclear if those databases have the prediction feature that gives TVWSDB the capability of decreasing the number of inquiries from SUs. With this in mind, the authors present a reinforcement learning-based TVWSDB. Reinforcement learning (RL) is a machine learning technique that focuses on what has been done based on mapping situations to actions to obtain the highest reward. The learning process was conducted by trying out the actions to gain the reward instead of being told what to do. The actions may directly affect the rewards and future rewards. Based on the results, this algorithm effectively searched the most optimal channel for the SUs in query with the minimum search duration. This paper presents the advantage of using a machine learning approach in TVWSDB with an accurate and faster-searching capability for the available TVWS channels intended for SUs.
This research was conducted in order to monitor and measure the dimensions of media policy in satellite channels directed from the point of view of the communicator, and this research is classified among the descriptive studies, as the researcher used the survey method to answer the questions that were formulated in light of the research problem represented by the main question: What are the dimensions of media policy in Directed satellite channels? .
To achieve the objectives of the study, the researcher used the following tools:
The questionnaire, in order to survey the attitudes of communicators about the extent to which the media policy during crises reflects on their professional standards. The research community is represente
The literature shows conflicting outcomes, making it difficult to determine how e-learning affects the performance of students in higher education. The effect of e-learning was studied and data has been gathered with the utilization of a variety of qualitative and quantitative methods, especially in relation to students' academic achievements and perceptions in higher education, according to literature review that has been drawn from articles published in the past two decades (2000-2020). The development of a sense of community in the on-line environment has been identified to be one of the main difficulties in e-learning education across this whole review. In order to create an efficient online learning community, it could be claim
... Show MoreE-learning seeks to create an interactive learning environment between the teacher and the learner through electronic media conveying in more than one direction, regardless of how the environment and its variables are identified. It also develops skills necessary to deal with technology in order to be able to take into account the individual differences between them and helps e-learning teacher and learner to achieve the goals set in advance and identify educational objectives in a clear manner. The research aims to identify e-learning in its benefits and management systems. It has three sections dealt with in the current research. Chapter II concentrates on the research Methodology, which consisted of three sections: The first s
... Show MoreBackground: White spot lesions are esthetic problems caused by subsurface enamel demineralization that seen as white opacity. Aim of the study: This study aimed to evaluate and to compare the color change after the treatment of the white spot lesions with resin nϔtrton and micro abrasion. Materials and Methods: rtϔ white spot lesions were generated on 48 premolar teeth by the use of a demineralization solution. The teeth were randomly divided using the Diagnodent into three study groups (16 teeth for each group) depending on the depth of the induced lesions: outer enamel, inner enamel and outer dentine. Then each group was fatherly subdivided into two groups (8 teeth for each group) the ϔrst group was treated wit
... Show MoreIn this research a proposed technique is used to enhance the frame difference technique performance for extracting moving objects in video file. One of the most effective factors in performance dropping is noise existence, which may cause incorrect moving objects identification. Therefore it was necessary to find a way to diminish this noise effect. Traditional Average and Median spatial filters can be used to handle such situations. But here in this work the focus is on utilizing spectral domain through using Fourier and Wavelet transformations in order to decrease this noise effect. Experiments and statistical features (Entropy, Standard deviation) proved that these transformations can stand to overcome such problems in an elegant way.
... Show MoreThere is various human biometrics used nowadays, one of the most important of these biometrics is the face. Many techniques have been suggested for face recognition, but they still face a variety of challenges for recognizing faces in images captured in the uncontrolled environment, and for real-life applications. Some of these challenges are pose variation, occlusion, facial expression, illumination, bad lighting, and image quality. New techniques are updating continuously. In this paper, the singular value decomposition is used to extract the features matrix for face recognition and classification. The input color image is converted into a grayscale image and then transformed into a local ternary pattern before splitting the image into
... Show MoreCorrosion of steel reinforcement is one of the biggest problems facing all countries in the world like bridges in the beach area and marine constructions which lead to study these problems and apply some economical solutions. According to the high cost of repair for these constructions, were studied the effect of using kind of chemical compounds sodium nitrite(NaNO2) and sodium silicate(Na2SiO3) as corrosion inhibitors admixture for steel bars that immersed partially in electrolyte solution (water + sodium chloride in 3% conc.) (Approximately similar to the concentration of salt in sea water). The two inhibitors above added each one to the electrolyte solution at concentrations (0.5%, 1% and 2%) for both
... Show MorePhoenix dactylifera l. pinnae (the green leaves of dates palm) were used as natural reinforcing (strengthening) fibers to improve the mechanical properties of polyester as a matrix material, the fibers of the green leaves of dates palm were used in two lengths, 10 and 20mm with five rates of 0, 2.5, 5, 10, and 20% , where the reinforcing with the leaves fibers increases the hardness strength from 76.5 to be about 86.55 , the Impact value raised from about 0.313 to 0.461 , in addition to that the flexural strength from 2.66 to be about 55 , and the thermal conductivity increases from 2.54 𝑤∕𝑚.℃ to 5.41 𝑤∕𝑚.℃. The results of the present search explains that the composite samples reinforced at rate 20% and 10mm fiber length
... Show MoreCastellated columns are structural members that are created by breaking a rolled column along the center-line by flame after that rejoining the equivalent halves by welding such that for better structural strength against axial loading, the total column depth is increased by around 50 percent. The implementation of these institutional members will also contribute to significant economies of material value. The main objectives of this study are to study the enhancement of the load-carrying capacity of castellated columns with encasement of the columns by Reactive Powder Concrete (RPC) and lacing reinforcement, and serviceability of the confined castellated columns. The Castellated columns with RPC and Lacing Reinforcement improve com
... Show MoreThe purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals
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