PhD in Computer Engineering - 2023/College of Computer Engineering, University of Mosul - 2024

Sep 21, 2020 - Jul 10, 2023

This PhD thesis focuses on the implementation of an SDN-IoT system for critical healthcare in an intensive care unit (ICU) and patient care environment. The SDN-IoT network was tested using RyU and Pox controllers to measure throughput, latency, jitter, delay, average packet throughput, and bit rate. A Raspberry Pi 4 was used as the controller to manage the network, with the ability to efficiently replace any failures that occur in real time compared to traditional networks.

MSc in Computer Engineering - 2009 / Technical College of Engineering / Northern Technical University - 2009

Oct 18, 2025 - Feb 16, 2009

Development of an adaptive filtering system to obtain a noise-free ECG signal. The filter was designed using the ADALINE algorithm and represented on a microcontroller.

BSc in Computer Engineering / Technical College of Engineering / Mosul - 2000

Oct 1, 1996 - Jul 1, 2000

تدريسية [الكلية التقنية الهندسية /الموصل]

Jul 3, 2001 - Feb 8, 2024

تدريسية /مسؤبلة وحدة الانظمة الدراسية /عضو في اللجنة الامتحانية [الكلية التقنية الهندسية للحاسوب والذكاء الاصطناعي]

Feb 8, 2024 - Present

Translating Sumerian Symbols into French Letters

Mar 11, 2024

Journal NTU Journal of Engineering and Technology

DOI DOI: https://doi.org/10.56286/ntujet.v3i1.660

Volume 3 (1) : 12-17

Sumerian symbols, which look like cuneiform letters, were used in a very old writing style. In this paper, a new method to translate the Sumerian symbols into French letters is introduced. It is based on the Cascade- Forward Neural Network (CFNN). The CFNN is exploited and adapted for the translation issue. It accepts a cuneiform letter image as an input and produces an appropriate output that refers to the translated french letter. Reasonable image augmentations are employed. These augmentations are for the: left direction rotations, right direction rotations and multiple translation directions (to the left, right, bottom and top). Total of 780 images are utilized for rotations and 338 images are collected for translations. This work can successfully attain the performance of 100%.

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A survey of iot systems for critical hospital cases

Mar 2, 2023

Journal International Journal of Computing and Digital Systems

publisher The Mattingley Publishing Co., Inc

DOI http://dx.doi.org/10.12785/ijcds/130146

Issue ISSN (2210-142X) Int. J. Com. Dig. Sys.

Volume 13, No.1 (Mar-23)

The Internet of Things plays an important role in health care, as there are many health applications through which the Internet of things can be used, and the most important of these applications is the so-called telemedicine, as it can be applied in hospitals to track the number of patients and determine the appropriate medication for them, in addition to following the development of the health status of patients. Telemedicine has been certified for its convenience, time-saving, and intelligence features thanks to the development of the Internet of Things and cloud computing. Therefore, telemedicine technology will see further improvements that support communication between clinicians and patients across space and time. In the presented paper, a body of literature dealing with the telemedicine process has been reviewed for many critical cases in which the Internet of Things is being adopted as an essential technology for the treatment and follow-up of patients in hospitals. The most important aspects of this literature are highlighted in terms of sensors, devices, processors and even communication methods used, as well as means of storing and analyzing patient vital data collected from patients to provide real-time interaction. The most important failures and obstacles in this literature have been identified and appropriate suggestions have been made to reach an integrated health care system based on the Internet of Things. The focus has been on several aspects including safety, network traffic flow, and energy consumption for achieving the requirements of smart hospitals and transition to E-health care.

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Palm print verification based deep learning

Jun 3, 2021

Journal TELKOMNIKA Telecommunication, Computing, Electronics and Control

DOI DOI: 10.12928/TELKOMNIKA

Issue 1693-6930

Volume .v19i3.16573

n this paper, we consider a palm print characteristic which has taken wide attentions in recent studies. We focused on palm print verification problem by designing a deep network called a palm convolutional neural network (PCNN). This network is adapted to deal with two-dimensional palm print images. It is carefully designed and implemented for palm print data. Palm prints from the Hong Kong Polytechnic University Contact-free (PolyUC) 3D/2D hand images dataset are applied and evaluated. The results have reached the accuracy of 97.67%, this performance is superior and it shows that our proposed method is efficient.

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Translating cuneiform symbols using artificial neural network

Apr 2, 2021

Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) 19(2)

DOI DOI:10.12928/telkomnika.

Issue 1693-6930

Volume v19i2.16134

Cuneiform language is an old language that was invented by the people of Sumerian nation. It is an essential language for many archeologists. Especially who are interested in studying and investigating the old nations of Iraq. Dealing with this type of language usually requires specialist to translate its symbols, which are basically forms of nail shapes. This study presents a new approach to translate the cuneiform writing by employing artificial neural network (ANN) technique. Effectively, multi-layer perceptron (MLP) neural network has been adapted for translating the Sumerian cuneiform symbol images to their corresponding English letters. This work has been successfully established and it attained 100%. © 2020, TELKOMNIKA Telecommunication, Computing, Electronics and Control. All Rights Reserved

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Earprint recognition using deep learning technique

Apr 2, 2021

Journal TELKOMNIKA Telecommunication, Computing, Electronics and Control

DOI DOI: 10.12928/TELKOMNIKA.v19i2.16572

Issue 1693-6930

Volume Vol. 19, No. 2

Earprint has interestingly been considered for recognition systems. It refers to the shape of ear, where each person has a unique shape of earprint. It is a strong biometric pattern and it can effectively be used for authentications. In this paper, an efficient deep learning (DL) model for earprint recognition is designed. This model is named the deep earprint learning (DEL). It is a deep network that carefully designed for segmented and normalized ear patterns. IIT Delhi ear database (IITDED) version 1.0 has been exploited in this study. The best obtaining accuracy of 94% is recorded for the proposed DEL.

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Design Security System based on Arduino

Mar 2, 2020

Journal test engineering and managment

publisher The Mattingley Publishing Co., Inc

Issue ISSN: 0193-4120 Page No. 3341 - 3346

Advanced technologies make life easier where people can protect their properties from burglars even if they exist in different locations. This paper presents a security system that uses Arduino with a mobile phone for remote protection. The proposed system has an infrared sensor that sends a signal to the microcontroller after detecting a motion. After processing the signal, the mobile takes a picture and sends warning messages to the stored phone numbers of the property owner. This can reduce the risk of having a burglar threat. The proposed design has advantages of low cost and flexible security.

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Wireless Waiter Robot

Sep 2, 2019

Journal test engineering an managment

publisher The Mattingley Publishing Co., Inc

Issue ISSN: 0193-4120

Volume Page No. 2486- 2494

A robotic waiter with integrated technology is an ideal solution for restaurants. This paper considers facilitating the services in restaurants. Many problems can be observed in this case such as overcrowding of customers and lacking for waiters. These problems can be addressed by using the robotic techniques. In this study, A waiter robot and a smart restaurant are designed to provide better services for customers. The robot can response to a lighting signal from any table in order to provide the restaurant services for that location. In addition, the customer can use an Electronic-Menu (E-Menu) which is embedded within the robot to select his/her order. The order will be sent to the kitchen and the food will be prepared. Consequently, it can be delivered to the determined table by the waiter robot. A credit card service within the same robot is suggested for paymentpurposes.

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