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Radon and Exhalation Rate Measurement of Soil Samples in Al-Amiriya Area in Baghdad Governorate Using a Nuclear Track Detector
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Abstract<p>Radon is the most dangerous natural radioactive component affecting the human population, since it is a radioactive gas that results from the decomposition process of uranium deposits in soil, rocks, and water, and it is damaging both humans and the ecosystem. The radon concentrations and exhalation rate in soil samples from various locations were determined using a passive approach with a CR-39 (CR-39 is Columbia Resin #39; it is allyl diglycol carbonate C12H18O7) detector in Amiriya region in Baghdad Governorate. The average values of radon concentrations are ranged from 47.3 to 54.2 Bq·m−3. From the obtained results, we can conclude that the values of all studied locations are within the allowed levels. This research can be utilized to examine any variations in the radioactive baseline level in our homes and regions as well as to identify any hazardous radiation that could harm humans.</p>
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Publication Date
Sun Jan 27 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The Role of Inspection In Achieving Banking Compliance: An Applied Study In A Sample o Iraq Banks
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The Banking Supervision of the most important functions of the Central Bank of Iraq, which he intended to have a strong banking system and a sound and competitive, and exercised control over the banks by inspection bodies to ensure their compliance with the laws, regulations and orders and instructions and the safety of their financial positions.

The research was aimed to release the concept of banking inspection, compliance and problems and obstacles faced by the inspectors, and monitors compliance and down to make recommendations.

Has been reached on a set of theoretical and practical conclusions, including: -

1-confirmed the statistical analysis of the answers to the research sample the importance of the role o

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Publication Date
Sat Jan 01 2022
Journal Name
Materials Today: Proceedings
Investigating the use of lean manufacturing techniques in liquid batteries production: A field research in Babylon plants
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Publication Date
Wed Jan 10 2018
Journal Name
Al–bahith Al–a'alami
Work Stress Sources of the Communicator in Public Relations “A field study on Governmental Institutions in UAE”.
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This study addressed the work stress sources and level of the communicator in public relations in governmental institutions in the United Arab Emirates. The importance of this study is the lack of studies on work stress of the communicator in public relations. The study aimed to investigate the work stress source Physical, individual, groups, organizational and Professional source which effect on the performance of communicator in public relations. The researcher used the descriptive approach and questionnaire as an essential tool for collecting information. Some of the important results of the study are The communicator in public relations facing stress in work by 42% which affect on his performance by average level. The organizational

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Publication Date
Sat Mar 07 2026
Journal Name
Retos: Nuevas Tendencias En Educación Física, Deporte Y Recreación, Issn-e 1988-2041, Issn 1579-1726, Nº. 68, 2025, Págs. 1048-1062
The impact of knowledge management on cognitive achievement in sports science: A case study in boxing education
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Introduction: Knowledge management plays a crucial role in students’ ability to acquire, organize, retrieve, and apply information, impacting academic performance. In sports sciences, especially in combat sports like boxing, effective knowledge management supports both theoretical understanding and practical skill application. Despite exposure to boxing through training and media, students’ academic performance remains inconsistent. Objective: This study examines the relationship between knowledge management and cognitive achievement among second-year students in the College of Physical Education and Sport Sciences at the University of Basrah. It evaluates how students manage knowledge and its impact on their retention and application

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Publication Date
Thu Aug 17 2017
Journal Name
Journal Of Health, Medicine And Nursing
Adherence to Guidelines of Secondary Prevention in patients with Ischemic Heart Disease in a Tertiary Cardiac Center
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Coronary heart disease (CHD) is the leading cause of death in United State (U.S.). Controlling of modifiable risk factors such as smoking, hypertension (HT), diabetes mellitus (D.M.), dyslipidemia, physical inactivity & obesity will prevent other serious cardiovascular complications

Publication Date
Tue Jul 09 2024
Journal Name
Diagnostics
A Novel Hybrid Machine Learning-Based System Using Deep Learning Techniques and Meta-Heuristic Algorithms for Various Medical Datatypes Classification
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Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea

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Publication Date
Mon Dec 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
The Effect of importance in the Intellectual Capital On Internal control Systems Analytical Research in A sample of general inspectors’ offices in Iraq
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The research aims to know the influence of the intellectual capital on the internal control system in a sample of General Inspection Offices in Iraq. The research includes a sample of individuals who are working in these offices total sample (46) individuals distributed according to functional levels (General Inspector, Deputy Inspector General, and Director) , The data and information were collected by using questionnaire, which is done for this purpose, as well as personal interviews in order to reach to the results that achieve the aim of this research , Two hypotheses were formed , the first hypothesis consists of (4) secondary hypothesis , All these hypotheses were tested by using statistical tools such as (percentages, freq

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Publication Date
Fri Jan 01 2016
Journal Name
Machine Learning And Data Mining In Pattern Recognition
A New Strategy for Case-Based Reasoning Retrieval Using Classification Based on Association
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Publication Date
Thu Jan 11 2018
Journal Name
Al-khwarizmi Engineering Journal
Control on a 2-D Wing Flutter Using an Adaptive Nonlinear Neural Controller
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An adaptive nonlinear neural controller to reduce the nonlinear flutter in 2-D wing is proposed in the paper. The nonlinearities in the system come from the quasi steady aerodynamic model and torsional spring in pitch direction. Time domain simulations are used to examine the dynamic aero elastic instabilities of the system (e.g. the onset of flutter and limit cycle oscillation, LCO). The structure of the controller consists of two models :the modified Elman neural network (MENN) and the feed forward multi-layer Perceptron (MLP). The MENN model is trained with off-line and on-line stages to guarantee that the outputs of the model accurately represent the plunge and pitch motion of the wing and this neural model acts as the identifier. Th

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Publication Date
Fri Nov 21 2025
Journal Name
Journal Of Advances In Information Technology
Towards Accurate SDG Research Categorization: A Hybrid Deep Learning Approach Using Scopus Metadata
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The complexity and variety of language included in policy and academic documents make the automatic classification of research papers based on the United Nations Sustainable Development Goals (SDGs) somewhat difficult. Using both pre-trained and contextual word embeddings to increase semantic understanding, this study presents a complete deep learning pipeline combining Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Network (CNN) architectures which aims primarily to improve the comprehensibility and accuracy of SDG text classification, thereby enabling more effective policy monitoring and research evaluation. Successful document representation via Global Vector (GloVe), Bidirectional Encoder Representations from Tra

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