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Ammonia Removal in Free-Surface Constructed Wetlands Employing Synthetic Floating Islands: Employing synthetic floating islands
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Free water surface constructed wetlands (FSCWs) can be used to complement conventional waste water treatment but removal efficiencies are often limited by a high ratio of water volume to biofilm surface area (i.e. high water depth). Floating treatment wetlands (FTWs) consist of floating matrices which can enhance the surface area available for the development of fixed microbial biofilms and provide a platform for plant growth (which can remove pollutants by uptake).  In this study the potential of FTWs for ammoniacal nitrogen (AN) removal was evaluated using experimental mesocosms operated under steady-state flow conditions with ten different treatments (two water depths, two levels of FTW mat coverage, two different plant densities and a control, all replicated three times). A simple model was constructed as a framework for understanding N dynamics in each treatment.  The model was calibrated using data obtained from one treatment and validated independently for the other treatments. Specifically, we hypothesized that the nitrification and volatilization rate constants are inversely proportional to water depth and proportional to mat surface area. This allowed the relative magnitude of different removal mechanisms to be estimated.  The model was able to predict steady-state concentrations of AN and total oxidized nitrogen (TON) across the different treatments well (values for correlation in the regression between measured and predicted steady-state concentrations and RMSE were 0.88 and 0.40 mg N L-1 for AN, and 0.63 and 1.75 mg N L-1 for TON).  The results confirm that nitrification is the principal AN removal process, with maximum removal occurring in shallow systems with high matrix cover (i.e. a high ratio of biofilm surface area to water volume). Plant uptake was a relatively minor loss process compared to nitrification. Integrated experimental and model-based approach was found to be a useful tool to improve mechanistic understanding AN dynamics in FSCWs and system performance.

 

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Publication Date
Wed Jul 01 2020
Journal Name
Journal Of Engineering
Using Adaptive Neuro Fuzzy Inference System to Predict Rate of Penetration from Dynamic Elastic Properties
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Rate of penetration plays a vital role in field development process because the drilling operation is expensive and include the cost of equipment and materials used during the penetration of rock and efforts of the crew in order to complete the well without major problems. It’s important to finish the well as soon as possible to reduce the expenditures. So, knowing the rate of penetration in the area that is going to be drilled will help in speculation of the cost and that will lead to optimize drilling outgoings. In this research, an intelligent model was built using artificial intelligence to achieve this goal.  The model was built using adaptive neuro fuzzy inference system to predict the rate of penetration in

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Publication Date
Wed Nov 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
The trend to Joint Audit as an approach to Improve the Financial Reports Quality - An Applied Study –
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This study aimed at identifying the trend to applying the Joint Audit as an approach to improve the financial reports quality with all their characteristics (Relevance, Reliability, Comparability, Consistency), as well as enclose the difficulties that faced the auditors in the Gaza Strip in implementing the Joint Audit. In order to achieve the study aims, a measure was used to identify the trend to apply the Joint Audit and it was distributed to the study sample which is consisting of (119) individuals and retrieved thereof (99) valid for analysis, approximately (83.2%), (69) of them are Auditors, (30) financial managers and accountants. The researcher used the analytical descriptive method, and after analyzing the results, the s

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Publication Date
Tue Jun 01 2021
Journal Name
Journal Of Engineering
Designing a Secure Software-Defined Radio Transceiver using the Logistic Map
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The need to exchange large amounts of real-time data is constantly increasing in wireless communication. While traditional radio transceivers are not cost-effective and their components should be integrated, software-defined radio (SDR) ones have opened up a new class of wireless technologies with high security.  This study aims to design an  SDR  transceiver was built using one type of modulation, which is 16 QAM, and adding a  security subsystem using one type of chaos map, which is a  logistic map, because it is a very simple nonlinear dynamical equations that generate a random key and  EXCLUSIVE  OR with the originally transmitted data to protect data through the transmission. At th

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Publication Date
Sat Dec 02 2017
Journal Name
Al-khwarizmi Engineering Journal
Design of a Programmable System for Failure Modes and Effect Analysis of Steam-Power Plant Based on the Fault Tree Analysis
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In this paper, the system of the power plant has been investigated as a special type of industrial systems, which has a significant role in improving societies since the electrical energy has entered all kinds of industries, and it is considered as the artery of modern life.

   The aim of this research is to construct a programming system, which could be used to identify the most important failure modes that are occur in a steam type of power plants. Also the effects and reasons of each failure mode could be analyzed through the usage of this programming system reaching to the basic events (main reasons) that causing each failure mode. The construction of this system for FMEA is dependi

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Publication Date
Sun Jul 20 2025
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Using a 3D Chaotic Dynamic System as a Random Key Generator for Image Steganography
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In today's digital era, the importance of securing information has reached critical levels. Steganography is one of the methods used for this purpose by hiding sensitive data within other files. This study introduces an approach utilizing a chaotic dynamic system as a random key generator, governing both the selection of hiding locations within an image and the amount of data concealed in each location. The security of the steganography approach is considerably improved by using this random procedure. A 3D dynamic system with nine parameters influencing its behavior was carefully chosen. For each parameter, suitable interval values were determined to guarantee the system's chaotic behavior. Analysis of chaotic performance is given using the

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Publication Date
Wed Nov 12 2025
Journal Name
2025 7th International Conference On Control Systems, Mathematical Modeling, Automation And Energy Efficiency (summa)
Comparative Analysis of Robust Strategies for an Electro-hydraulic Servo Valve System
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PID (proportional-integral-derivative) and Mu controllers are widely used in electro-hydraulic servo systems due to their effectiveness and ease of implementation. This paper explores using particle swarm optimization (PSO) for tuning traditional and robust PID controllers, along with D-K iteration for Mu controller tuning. Three controller types: conventional PID (CPID), robust PID (RPID), and structured singular value controllers are developed, while analyzing multiplicative uncertainty with six uncertain coefficients. Their findings indicated that both PID (CPID and RPID) and Mu controllers maintained system stability. Notably, the Mu controller can handle coefficient uncertainty without a pure integral term, while the RPID controller de

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Publication Date
Mon Nov 01 2021
Journal Name
Journal Of Engineering
Performance Evaluation of Pole Placement and Linear Quadratic Regulator Strategies Designed for Mass-Spring-Damper System Based on Simulated Annealing and Ant Colony Optimization
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This paper investigates the performance evaluation of two state feedback controllers, Pole Placement (PP) and Linear Quadratic Regulator (LQR). The two controllers are designed for a Mass-Spring-Damper (MSD) system found in numerous applications to stabilize the MSD system performance and minimize the position tracking error of the system output. The state space model of the MSD system is first developed. Then, two meta-heuristic optimizations, Simulated Annealing (SA) optimization and Ant Colony (AC) optimization are utilized to optimize feedback gains matrix K of the PP and the weighting matrices Q and R of the LQR to make the MSD system reach stabilization and reduce the oscillation of the response. The Matlab softwar

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Publication Date
Sun Sep 01 2019
Journal Name
Al-dhad Book Store
Multivariate Analysis - First Edition
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This Book is intended to be textbook studied for undergraduate course in multivariate analysis. This book is designed to be used in semester system. In order to achieve the goals of the book, it is divided into the following chapters. Chapter One introduces matrix algebra. Chapter Two devotes to Linear Equation System Solution with quadratic forms, Characteristic roots & vectors. Chapter Three discusses Partitioned Matrices and how to get Inverse, Jacobi and Hessian matrices. Chapter Four deals with Multivariate Normal Distribution (MVN). Chapter Five concern with Joint, Marginal and Conditional Normal Distribution, independency and correlations. Many solved examples are intended in this book, in addition to a variety of unsolved relied pro

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Publication Date
Fri Feb 01 2019
Journal Name
Al-dhad - Book Store And Publishing
Multivariate Analysis (First Edition)
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This Book is intended to be textbook studied for undergraduate course in multivariate analysis. This book is designed to be used in semester system. In order to achieve the goals of the book, it is divided into the following chapters. Chapter One introduces matrix algebra. Chapter Two devotes to Linear Equation System Solution with quadratic forms, Characteristic roots & vectors. Chapter Three discusses Partitioned Matrices and how to get Inverse, Jacobi and Hessian matrices. Chapter Four deals with Multivariate Normal Distribution (MVN). Chapter Five concern with Joint, Marginal and Conditional Normal Distribution, independency and correlations. Many solved examples are intended in this book, in addition to a variety of unsolved relied pro

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Publication Date
Tue Dec 12 2017
Journal Name
Al-khwarizmi Engineering Journal
Model Reference Adaptive Control based on a Self-Recurrent Wavelet Neural Network Utilizing Micro Artificial Immune Systems
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Abstract 

This paper presents an intelligent model reference adaptive control (MRAC) utilizing a self-recurrent wavelet neural network (SRWNN) to control nonlinear systems. The proposed SRWNN is an improved version of a previously reported wavelet neural network (WNN). In particular, this improvement was achieved by adopting two modifications to the original WNN structure. These modifications include, firstly, the utilization of a specific initialization phase to improve the convergence to the optimal weight values, and secondly, the inclusion of self-feedback weights to the wavelons of the wavelet layer. Furthermore, an on-line training procedure was proposed to enhance the control per

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