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Reinforcement Learning-Based Television White Space Database
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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.

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Publication Date
Wed Jan 02 2019
Journal Name
Journal Of Educational And Psychological Researches
An Instructional Design According to the Active Learning Model and Its Effect on Students' Achievement in Chemistry for Fifth Intermediate Stage
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The objective of the research is to identify the effect of an instructional design according to the active learning modelsالباحثين in the achievement of the students of the fifth grade, the instructional design was constructed according to the active learning models for the design of education. The research experience was applied for a full academic year (the first & the second term of 2017-2018). The sample consisted of 58 students, 28 students for the experimental group and 30 students for the control group. The experimental design was adopted with partial and post-test, the final achievement test consisted of (50) objectives and essays items on two terms, the validity of the test was verified by the adoption of the Kudoric

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Publication Date
Tue Dec 29 2020
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Medication Safety in Patients under 18 Years Old; a Retrospective Study based on Iraqi Pharmacovigilance Center Database
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Medication safety is an important part of the comprehensive patient safety term. Medication safety is gaining more attention as the World Health Organization set the goal of decreasing medication harm by (50%) for the next 5 years when launching the third global challenge. Studying medication safety in the risk groups such as young ages, children are crucial to learn more about the effect of medicines in this risk group since they are not included in the clinical trials. Adverse drug reaction is defined as any harm resulted from the drug itself during medical process journey, while medication errors are any harm resulted from the treatment process rather than the drug or it is the result of the failure in a step of the treatment process

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Publication Date
Fri Apr 12 2019
Journal Name
Journal Of Economics And Administrative Sciences
The Compatibility between leadership of empowerment and organizational learning abilities and their reflection on knowledge capital Applied research at Wasit University
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The current research aims at: - Identifying the role played by the leadership in empowerment and organizational learning abilities and their reflection on the knowledge capital, and the extent to which these concepts can be applied effectively at Wasit University. The problem of research .... In a series of questions: The most important is that the dimensions leadership empowerment and distance learning organizational capacity correlation relationship and impact and significant statistical significance with the capital knowledge.

     To understand the nature of the relationship and the impact between the variables, leadership was adopted by empowerment as the fir

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Publication Date
Wed Jun 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
The Impact of the Strategic Leadership in Strategic Learning Exploratory Research at Anbar University
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        This study aims to know the extent of the impact of Strategic Leadership as an independent variable in Strategic Learning as a dependent variable to help the senior leadership in Anbar University to take the right decisions to develop Strategic Learning programs in light of the circumstances of the Covid-19 and the sudden decisions adopted by the university to switch to E-learning and to blend. The survey was conducted by distributing a questionnaire that was adopted as a primary tool in data collection from the study sample represented by the university's senior leaders, An intentional random sample of (105) was selected from our community of (127), the data were analyzed by (SPSS) Depe

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Publication Date
Thu Dec 01 2022
Journal Name
Al-khwarizmi Engineering Journal
Comparative Transfer Learning Models for End-to-End Self-Driving Car
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Self-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin

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Publication Date
Mon May 06 2019
Journal Name
Journal Of Physical Education
Designing Teaching Aids and Their Effects on Learning and Retaining Diving and Cartwheel on Floor Exercises in Women’s’ Artistic Gymnastics
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Designing Teaching Aids and Their Effects on Learning and Retaining Diving and Cartwheel on Floor Exercises in Women’s’ Artistic Gymnastics

The research aimed at designing teaching aids that develop and help retain diving and cartwheel for third year college of physical education and sport sciences students in women’s artistic gymnastics. In addition to that, the researchers aimed at identifying the effect of these aids on learning and retaining cartwheel and diving in floor exercises. The researchers used the experimental method. The subjects were (20) third year female students from the college of physical education and sport sciences/ university of Baghdad sections K and H. the main experiment lasted for

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Publication Date
Sat Mar 29 2014
Journal Name
International Journal Of Academic Research In Progressive Education And Development
The Effects of Problem-Based Learning on Self-Directed Learning Skills among Physics Undergraduates
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The aim of this study is to compare the effects of three methods: problem-based learning (PBL), PBL with lecture method, and conventional teaching on self-directed learning skills among physics undergraduates. The actual sample size comprises of 122 students, who were selected randomly from the Physics Department, College of Education in Iraq. In this study, the pre- and post-test were done and the instruments were administered to the students for data collection. The data was analyzed and statistical results rejected null hypothesis of this study. This study revealed that there are no signifigant differences between PBL and PBL with lecture method, thus the PBL without or with lecture method enhances the self-directed learning skills bette

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Performance Evaluation of Intrusion Detection System using Selected Features and Machine Learning Classifiers
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Some of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems.  Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic.  Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance.  In this study, two different sets of select

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Engineering
Face-based Gender Classification Using Deep Learning Model
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Gender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer lea

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Publication Date
Mon Jan 28 2013
Journal Name
Spie Proceedings
Enhancement of security for free space optics based on reconfigurable chaotic technique
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Free Space Optical (FSO) technology offers highly directional, high bandwidth communication channels. This technology can provide fiber-like data rate over short distances. In order to improve security associated with data transmission in FSO networks, a secure communication method based on chaotic technique is presented. In this paper, we have turned our focus on a specific class of piece wise linear one-dimensional chaotic maps. Simulation results indicate that this approach has the advantage of possessing excellent correlation property. In this paper we examine the security vulnerabilities of single FSO links and propose a solution to this problem by implementing the chaotic signal generator “reconfigurable tent map”. As synchronizat

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