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Real time handwriting recognition system using CNN algorithms
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Abstract— The growing use of digital technologies across various sectors and daily activities has made handwriting recognition a popular research topic. Despite the continued relevance of handwriting, people still require the conversion of handwritten copies into digital versions that can be stored and shared digitally. Handwriting recognition involves the computer's strength to identify and understand legible handwriting input data from various sources, including document, photo-graphs and others. Handwriting recognition pose a complexity challenge due to the diversity in handwriting styles among different individuals especially in real time applications. In this paper, an automatic system was designed to handwriting recognition using the recent artificial intelligent algorithms, the conventional neural network (CNN). Different CNN models were tested and modified to produce a system has two important features high performance accuracy and less testing time. These features are the most important factors for real time applications. The experimental results were conducted on a dataset includes over 400,000 handwritten names; the best performance accuracy results were 99.8% for SqueezeNet model.

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Publication Date
Sun Dec 13 2020
Journal Name
International Journal On Advanced Science, Engineering And Information Technology
Robust Approach of Optimal Control for DC Motor in Robotic Arm System using Matlab Environment
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Modern automation robotics have replaced many human workers in industrial factories around the globe. The robotic arms are used for several manufacturing applications, and their responses required optimal control. In this paper, a robust approach of optimal position control for a DC motor in the robotic arm system is proposed. The general component of the automation system is first introduced. The mathematical model and the corresponding transfer functions of a DC motor in the robotic arm system are presented.  The investigations of using DC motor in the robotic arm system without controller lead to poor system performance. Therefore, the analysis and design of a Proportional plus Integration plus Divertive (PID) controller is illustrated.

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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
Thu Jun 01 2023
Journal Name
Baghdad Science Journal
Design and construction of anair pollution detection system using a laser beam and absorption spectroscopy
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Air pollution is one of the important problems facing Iraq. Air pollution is the result of uncontrolled emissions from factories, car exhaust electric generators, and oil refineries and often reaches unacceptable limits by international standards. These pollutants can greatly affect human health and regular population activities. For this reason, there is an urgent need for effective devices to monitor the molecular concentration of air pollutants in cities and urban areas. In this research, an optical system has been built consisting of aHelium-Neonlaser,5mWand at 632.8 nm, a glass cell with a defined size, and a power meter(Gentec-E-model: uno) where a scattering of the laser beam occurs due to air pollution. Two pollutants were examin

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Publication Date
Thu Sep 30 2004
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Control of Calcium Scale and Corrosion of Medical City Cooling Water System using Sulfuric Acid
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Publication Date
Wed Dec 25 2019
Journal Name
Journal Of Engineering
Link Failure Recovery for a Large-Scale Video Surveillance System using a Software-Defined Network
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The software-defined network (SDN) is a new technology that separates the control plane from data plane for the network devices. One of the most significant issues in the video surveillance system is the link failure. When the path failure occurs, the monitoring center cannot receive the video from the cameras. In this paper, two methods are proposed to solve this problem.  The first method uses the Dijkstra algorithm to re-find the path at the source node switch. The second method uses the Dijkstra algorithm to re-find the path at the ingress node switch (or failed link).

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Publication Date
Sat Apr 01 2017
Journal Name
Applied Energy
Melting enhancement in triplex-tube latent heat energy storage system using nanoparticles-metal foam combination
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Publication Date
Tue Jun 01 2010
Journal Name
Al-khwarizmi Engineering Journal
Comparison of the RLS and LMS Algorithms to Remove Power Line Interference Noise from ECG Signal
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    Biomedical signal such as ECG is extremely important in the diagnosis of patients and is commonly recorded with a noise. Many different kinds of noise exist in biomedical environment such as Power Line Interference Noise (PLIN). Adaptive filtering is selected to contend with these defects, the adaptive filters can adjust the filter coefficient with the given filter order. The objectives of this paper are: first an application of the Least Mean Square (LMS) algorithm, Second is an application of the Recursive Least Square (RLS) algorithm to remove the PLIN. The LMS and RLS algorithms of the adaptive filter were proposed to adapt the filter order and the filter coefficients simultaneously, the performance of existing LMS

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Publication Date
Thu Mar 01 2018
Journal Name
2018 International Conference On Computing Sciences And Engineering (iccse)
Comparison between Epsilon Normalized Least Means Square (ϵ-NLMS) and Recursive Least Squares (RLS) Adaptive Algorithms
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There is an evidence that channel estimation in communication systems plays a crucial issue in recovering the transmitted data. In recent years, there has been an increasing interest to solve problems due to channel estimation and equalization especially when the channel impulse response is fast time varying Rician fading distribution that means channel impulse response change rapidly. Therefore, there must be an optimal channel estimation and equalization to recover transmitted data. However. this paper attempt to compare epsilon normalized least mean square (ε-NLMS) and recursive least squares (RLS) algorithms by computing their performance ability to track multiple fast time varying Rician fading channel with different values of Doppler

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Publication Date
Mon Mar 11 2019
Journal Name
Baghdad Science Journal
Developing Load Balancing for IoT - Cloud Computing Based on Advanced Firefly and Weighted Round Robin Algorithms
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The evolution of the Internet of things (IoT) led to connect billions of heterogeneous physical devices together to improve the quality of human life by collecting data from their environment. However, there is a need to store huge data in big storage and high computational capabilities.   Cloud computing can be used to store big data.  The data of IoT devices is transferred using two types of protocols: Message Queuing Telemetry Transport (MQTT) and Hypertext Transfer Protocol (HTTP). This paper aims to make a high performance and more reliable system through efficient use of resources. Thus, load balancing in cloud computing is used to dynamically distribute the workload across nodes to avoid overloading any individual r

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Publication Date
Fri Jan 01 2021
Journal Name
Int. J. Agricult.
FORECASTING THE EXCHANGE RATES OF THE US DOLLAR AGAINST THE IRAQI DINAR USING THE BOX-JENKINS METHODOLOGY IN TIME SERIES WITH PRACTICAL APPLICATION
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The goal of the study is to discover the best model for forecasting the exchange rate of the US dollar against the Iraqi dinar by analyzing time series using the Box Jenkis approach, which is one of the most significant subjects in the statistical sciences employed in the analysis. The exchange rate of the dollar is considered one of the most important determinants of the relative level of the health of the country's economy. It is considered the most watched, analyzed and manipulated measure by the government. There are factors affecting in determining the exchange rate, the most important of which are the amount of money, interest rate and local inflation global balance of payments. The data for the research that represents the exchange r

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