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.
Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci
... Show MoreMany academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre
... Show MoreDiabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed
... Show MoreWitnessing human societies with the turn of the century atheist twenty huge revolution in information , the result of scientific and technological developments rapidly in space science and communications , and that made the whole world is like a small village not linked by road as it was in ancient times, through the rapid transportation as was the case a few years ago , thanks to the remote sensing devices that roam in space observant everything on the ground , that the information networks that overflowed the world a tremendous amount of information provided for each inhabitants of the earth , which made this information requirement for human life and human survival and well-being , as it has allowed that information to humans opportun
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The current research aims to identify the level of E-learning among middle school students, the level of academic passion among middle school students, and the correlation between e-learning and academic passion among middle school students. In order to achieve the objectives of the research, the researcher developed two questionnaires to measure the variables of the study (e-learning and study passion) among students, these two tools were applied to the research sample, which was (380) male and female students in the first and second intermediate classes. The research concluded that there is a relationship between e-learning and academic passion among students.
This study has came as a result to discover on the references of the educational theories which leads the professors in the educational art departments in the Iraqi universities through knowing these ideological references indeed in an important slice of the society. This slice is: the members of professoriate. The study goal knows the ideological references to these theories for the professors in these departments.
In order to approve the research's goals. The researcher has selected a sample contains (50) professoriate members in these departments in the Iraqi universities which they have the educational art profession among the next scientific degrees (assistant teacher. teacher. assistant professor & professor).
The resea