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BER Performance Improvement of Dual Chaotic Maps Based on STBC Communication System
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Sensitive information of any multimedia must be encrypted before transmission. The dual chaotic algorithm is a good option to encrypt sensitive information by using different parameters and different initial conditions for two chaotic maps. A dual chaotic framework creates a complex chaotic trajectory to prevent the illegal use of information from eavesdroppers. Limited precisions of a single chaotic map cause a degradation in the dynamical behavior of the communication system. To overcome this degradation issue in, a novel form of dual chaos map algorithm is analyzed. To maintain the stability of the dynamical system, the Lyapunov Exponent (LE) is determined for the single and dual maps. In this paper, the LE of the single and dual maps have been computed numerically. Increasing the dynamical behavior of the system by using more complex chaotic maps leads to inferiority in the overall system performance. So, in this work, the BER performance for the dual and single chaotic maps by exploiting the benefits of a hybrid Chaos Shift Keying-Multiple-Input-Multiple-Output (CSK-MIMO) communication system has been investigated. The results show that the dual tent map has more randomness, whereas the single logistic map has the least randomness. As well as the CSK-MIMO gives an outstanding BER performance when it compared with the SISO system which helps in reducing the system’s inferiority. 

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Publication Date
Tue Jan 01 2019
Journal Name
Ieee Access
Sensing Performance of Modified Single Mode Optical Fiber Coated With Nanomaterials-Based Ammonia Sensors Operated in the C-Band
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Publication Date
Sat Apr 30 2022
Journal Name
Revue D'intelligence Artificielle
Performance Evaluation of SDN DDoS Attack Detection and Mitigation Based Random Forest and K-Nearest Neighbors Machine Learning Algorithms
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

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Publication Date
Tue Nov 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Analysis of The Effect of The Administration of Communications Towers in The Selling Prices of Residential Real estate )New University Village Model(
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Abstract                          

 Should be the goal of Government controls, including environmental controls and safety laws to protect citizens from the harmful effects of negative secreted by human's additions and changes in the environment. and perhaps the protection aspects of the protection of citizens from the adverse effects of communications towers, including those produced by towers of health effects. The people the right to choose the nature of the physical environment, which should not be imposed on them by others. Communications towers are one of the main problems that have been

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Publication Date
Tue Mar 30 2021
Journal Name
Baghdad Science Journal
Solvability of Some Types for Multi-fractional Integro-Partial Differential Equation
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In this article, the solvability of some proposal types of the multi-fractional integro-partial differential system has been discussed in details by using the concept of abstract Cauchy problem and certain semigroup operators and some necessary and sufficient conditions. 

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Publication Date
Thu Apr 27 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Effect of Carbimazol-induced Hypothyroidism on Male Rat Reproductive System
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The present study is undertaken to evaluate the effects of hypothyroidism induced by carbimazol in male rat reproductive system. Rats were treated with carbimazol (80 and 160 mg/kg body weight) daily for two, four, six, and eight weeks, while control rats were given distilled water orally. The results of these experiments are: 1-Treatment with carbimazol produced increase in body weight of treated animals. This increase was not statistically significant even at high concentrations. 2-Decrease in testicular weight  was observed during all administration points. This decrease was aggravated proportional to duration and dose (p≤0.001). 3-Results of most intervals showed significant decrease in epididymal-head weight, while no sig

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Publication Date
Wed Feb 29 2012
Journal Name
Al-khwarizmi Engineering Journal
Effect of Construction Joints on Performance of Reinforced Concrete Beams
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Construction joints are stopping places in the process of placing concrete, and they are required because in many structures it is impractical to place concrete in one continuous operation. The amount of concrete that can be placed at one time is governed by the batching and mixing capacity and by the strength of the formwork. A good construction joint should provide adequate flexural and shear continuity through the interface.

In this study, the effect of location of construction joints on the performance of reinforced concrete structural elements is experimentally investigated.

Nineteen beam specimens with dimensions of 200×200×950 mm were tested. The variables investigated are the location of the construction joints

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Publication Date
Wed Jan 01 2020
Journal Name
Iraqi National Journal Of Nursing Specialties
Effectiveness of Health Educational Program on Nurses’ Knowledge About Communication Skills with Children at Welfare Children Teaching Hospital in Baghdad City
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Background: Therapeutic communication is the basis of interactive relationships among nursing team and their children: that affords opportunities to establish rapport, understand the client’s experience, formulate individualized or client interventions and optimize health care resources.

Objectives: The main aim of the study is to determine the Effectiveness of Education Program on Nurses’ Knowledge about Communication Skills with Children.

Methodology: A quasi-experimental study was conducted in Children Welfare Teaching Hospitals from 7th, October 2018 to the 20th, May 2019. The program and instruments have been constructed by the researcher for the purpose of the study. A non- prob

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Publication Date
Sat Dec 17 2022
Journal Name
Iraqi Journal Of Laser
PDF Biosensing technique for detection of H.pylori bacteria: Israa M.L. SaQari*, Layla M.H. Al-ameri
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Abstract :H.pylori is an important cause of gastric duodenal disease, including gastric ulcers, Mucosa-associated lymphoid tissue (MALT), and gastric carcinoma. biosensors are becoming the most extensively studied discipline because the easy, rapid, low-cost, highly sensitive, and highly selective biosensors contribute to advances in next-generation medicines such as individualized medicine and ultrasensitive point-of-care detection of markers for diseases.  Five of ten patients diagnosed with H.pylori ranging in age from 15–85 participated in this research. who [gastritis, duodenitis, duodenal ulcer (DU), and peptic ulcer (PU)] Suspected H.pylori colonies w

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Publication Date
Fri Jun 20 2025
Journal Name
University Of Anbar Sport And Physical Education Sciences
The Impact of the Concept Maps Strategy in the Guided Discovery Method at Learning the Skill of Layup Shooting of Basketball
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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Recurrent Stroke Prediction using Machine Learning Algorithms with Clinical Public Datasets: An Empirical Performance Evaluation
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Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al

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