Thabit Sultan Mohammed - Academia.edu (original) (raw)

Papers by Thabit Sultan Mohammed

Research paper thumbnail of Mathematical Model and Experimental Study To Optimize Rates Constants of Desorption And Adsorption of The Waste Water Using Palm Fronds

Journal of the Pakistan Institute of Chemical Engineers

Physical, mechanical and multi – step chemical treatments on the adsorptivity of palm fronds ad... more Physical, mechanical and multi – step chemical treatments on the adsorptivity of palm fronds adsorbent for the removal of 5 waste metal components from wastewater was studied and estimated in this paper. Three techniques are used for palm frond to produce modified activated carbon as adsorbents. Physical treatment is represented in the furnace at 600 oC. Mechanical treatment is established more suitable surface area from 300µm2 to 500 µm2 to increase efficiency of adsorbent. Chemical treatment of palm fronds used Acetone – ethanol - methanol treated palm fronds. The fixed bed column study was achieved under multi layered fixed bed columns. It was discovered that, the adsorption of 5 metals were expressively increased in the following order: Acetone – ethanol – Methanol treated palm fronds. The highest percentage reduction of the area under the curve was represented by chemical treatment for palm fronds reached 98.74%. Derived mathematical model to describe the system and...

Research paper thumbnail of Study and analysis of electric vehicles adoption: a middle eastern country as a case study

Indonesian Journal of Electrical Engineering and Computer Science

Adaption of hybrid electric vehicles (HEVs) and electric vehicles (EVs) is an important choice th... more Adaption of hybrid electric vehicles (HEVs) and electric vehicles (EVs) is an important choice that has many positive environmental and economic impacts, where, it helps in reducing exhaust emission, participation in dropping down the amount of noise pollution, and improving the air quality. With these encouraging impacts as well as the reduction in the price of fuel consumption, electric vehicles become at the top of car industry. A study on electric vehicles and their impact on improving the quality of environment is the main motive of this research. Selected theories and factors related to the electric vehicles’ adoption are investigated and analysed. The main factor that led to the spread of electric vehicles is the reliance on electric energy, so it is considered as zero emissions. But there is another effect, which is that these vehicles need continuous electric charging daily, which in turn needs to generate electricity, which leads to environmental pollution indirectly.

Research paper thumbnail of COVID-19 Diagnosis Using Spectral and Statistical Analysis of Cough Recordings Based on the Combination of SVD and DWT

Baghdad Science Journal

Healthcare professionals routinely use audio signals, generated by the human body, to help diagno... more Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopting a combination of Singular Value Decomposition (SVD), and Discrete Wavelet Transform (DWT). The combination of these two signal processing techniques is gaining lots of interest in the field of speaker and speech recognition. As a cough recognitio...

Research paper thumbnail of Corresponding Author

Abstract: The theory and application of (t-EC-AUED) codes was presented and among the methods pro... more Abstract: The theory and application of (t-EC-AUED) codes was presented and among the methods proposed in literature, the most efficient was chosen and a software was written for encoding and decoding of the codes. Comparison and evaluation of the construction techniques were carried out. A t-Error Correction (EC)/All Unidirectional Error Detection (AUED) codes are constructed by appending a single check symbol to a linear t-EC code to achieve the AUED property.

Research paper thumbnail of Enhanced Image Segmentation: Merging Fuzzy K-Means and Fuzzy C-Means Clustering Algorithms for Medical Applications

Computer Science and Information Technology, 2021

Research paper thumbnail of Computer-Supported Learning: A Teaching Aid for ECE Students

The use of computer hardware and software in education and training is a long established practic... more The use of computer hardware and software in education and training is a long established practice. In this work, an educational software is developed as a computer- supported tool to assist students' learning. Software engineering aspects are emphasized during the development, for the product to be simple and user friendly such that it can be used by all targeted students. In addition, the package is open for future expansions. Emphasis is paid to implementing solutions for issues that students face difficulties in understanding. The developed software system is provided with a database for many courses of the Electrical and Computer Engineering department. For the purpose of evaluation, number of students have used the software. Those students express a noticeable interest and benefit.

Research paper thumbnail of A Novel Algorithm Based on LoRa Technology for Open-Field and Protected Agriculture Smart Irrigation System

2019 2nd IEEE Middle East and North Africa COMMunications Conference (MENACOMM), 2019

A novel algorithm for smart irrigation system adaptable for both open-field and protected agricul... more A novel algorithm for smart irrigation system adaptable for both open-field and protected agriculture based on LoRa technology is proposed in this paper. The algorithm suits a networked architecture, in which a central controller is communicating with distributed units of sensors and actuators. Communication within the system units use LoRa devices, where a LoRa is an IoT based technology providing low-power and long-range radio connectivity. Within an agricultural farm, the system can be configured such that it can suit the control of environmental conditions applicable for either an open-field and/or a protected (e.g. greenhouse) agricultures. A database has been developed and designed to comply with the system architecture. The collected data is analyzed and used by the system for automatically adjusting itself to an optimal or semi-optimal performance. At the central control, the user interface offer system monitoring capability, statistics, as well as report generation.

Research paper thumbnail of Detection and Diagnostic Approach of COVID-19 Based on Cough Sound Analysis

Journal of Computer Science, 2021

Research paper thumbnail of Remote-Controlled Microcontroller-Based Temperature System : An Economical Design

Temperature measurement and monitoring are very important for most service and industrial applica... more Temperature measurement and monitoring are very important for most service and industrial applications. This paper presents the design of a remote-controlled microcontroller-based system. A multi-sensor/ multi-actuator system is proposed and the paper illustrates the steps for the design development. System simulation and the fabrication of a hardware prototype are both presented. Design alternatives are described, and emphasization on the choice of the economical and reliable ones are justified. The IR remote control unit, used in the hardware prototype as to replace keypad for the temperature setting, is described. Keywords— Automation; microcontroller; sensors; temperature control ; thermistor.

Research paper thumbnail of Modified Fuzzy C-Means Clustering Algorithm Application in Medical Image Segmentation

Developing effective algorithm for segmenting image is very important in pattern recognition, med... more Developing effective algorithm for segmenting image is very important in pattern recognition, medical MRI, X-Ray images analysis and in computer vision. Fuzzy c-means (FCM) is one of the mostly used methodologies in clustering image for segmentation. However, the results of the standard and the modified version FCM are not always satisfactory. This paper introduces a spatial FCM that considers the weighted fuzzy effect of neighboring pixels on the cluster center depending on the location and intensity (kernel metric). The objective function in the FCM algorithm is modified to minimize the intensity inhomogeneities, by implicating the spatial neighborhood information and modifying the membership weighting of each cluster. The advantages of the new FCM algorithm are: (a) produces homogeneous regions more than FCM algorithm, (b) handles noisy spots, and (c) it is relatively less sensitive to noise. Experimental results on real images show that the algorithm is effective, efficient, a...

Research paper thumbnail of Fault Diagnosis of Rotating Machine Based on Audio Signal Recognition System: An Efficient Approach

International journal of simulation: systems, science & technology, 2020

An efficient algorithm for condition monitoring of rotating machines is proposed in this paper. C... more An efficient algorithm for condition monitoring of rotating machines is proposed in this paper. Condition indicators are derived from sound signals, and used to arrive at a decision about the performance state of the machine. Sound signals are recorded by microphones and processed using time-frequency domain analysis. In this study, number of statistical features; such as mean, standard deviation, skewness, and kurtosis are considered. These statistical features were proven to be effective and simple to interpret. Healthy, about to be faulty, and faulty performance states of the machine are considered, and audio signals are recorded for each state. The five main steps comprising the implemented approach are data acquisition, preprocessing, feature extraction, time and frequency domain analysis, and the decision making. Based on the adopted statistical measures, the experimental results indicate that an excellent recognition of machine performance states is obtained, leading to an efficient fault detection and diagnosis.

Research paper thumbnail of Bridging for cross protocol talk in IOT devices using windows communication foundation

International Journal of Engineering & Technology, 2018

In the Internet of Things (IoT), multiple communication protocols are used to connect the smart d... more In the Internet of Things (IoT), multiple communication protocols are used to connect the smart device. Wi-Fi, Xbee, ZigBee, Bluetooth, and LoRaWAN are some of the communication channels utilized for connectivity by devices using some IoT platform.In order to enable the development of smart services for IoT platforms, there are solutions by different vendors to connect between IoT devices. For example, multiple IoT platforms are available in the market namely IoTivity platform developed by Open Connectivity Foundation (OCF), AllJoyn platform from All Seen Alliance, Weave made by Google, and Home Kit by Apple. In view of such segmentation of IoT platforms, IoT Application’s development has been made complex, where IoT device and accompanying application compatibility with available platforms requires support for multiple protocols.To simplify the complexity introduced by multiple platforms, M2M [4] International standard was already proposed as the bridge for integrating IoT protocol...

Research paper thumbnail of Neural Network Classification of White Blood Cell using Microscopic Images

International Journal of Advanced Computer Science and Applications, 2017

Research paper thumbnail of A Universal Decoding Algorithm for t-EC/AUED Codes

Asian Journal of Information Technology, Dec 1, 2014

Research paper thumbnail of Full Automation in Driverless Trains: A Microcontroller-Based Prototype

International Journal of Advanced Research in Electrical, Electronics and Instrumentation Energy, Jul 30, 2014

Research paper thumbnail of Artificial Neural Network as a Decision- Makers for Stereo Matching

Research paper thumbnail of Artificial Neural Networks as Decision-Makers for Stereo Matching

PsycEXTRA Dataset

This paper investigates the use of artificial neural networks to help making a decision on matchi... more This paper investigates the use of artificial neural networks to help making a decision on matching of stereo images. An image matching technique based on extracting features from segmented regions is adopted in this work, and a neural network framework is applied for region matching of stereo photographs. Two types of neural networks are used, the radial basis network, (RB) for learning clustering, and the back propagation (BP) network for learning image matching. The (RB) neural network is to cluster the regions according to the locations of their centered points. For each region, the BP network uses differential features as input training data. While training and testing the system, multiple features are extracted and used for enhancing the accuracy of the matching process. Features include (compactness, Euler number, and invariant moments) for each region. Results obtained from the neural networks (namely; clustering and initial matching array) are used to select the best matching pair. Results are showing a good matching accuracy.

Research paper thumbnail of Evaluating the Effect of Inheritance on the Characteristics of Object Oriented Programs

Journal of Computer Science, 2006

Research paper thumbnail of Performance Improvement and Deadlock Prevention for a Distributed Fault Diagnosis Algorithm

Journal of Computer Science, 2007

Research paper thumbnail of Applying a Neural Network Framework for Stereo Matching

PsycEXTRA Dataset

Approaches for image matching can be broadly classified into two categories: the intensity-based ... more Approaches for image matching can be broadly classified into two categories: the intensity-based matching and the feature-based matching techniques. A technique from the second category is adopted in this work, where a neural framework is applied for region matching of stereo photographs. Two different types of neural networks are used in this framework, the radial basis network, (RB) for learning clustering, and the back propagation (BP) network for learning image matching. The (RB) neural network is to cluster the regions according to the locations of their centered points. The BP network uses differential features of each region as input training data. Rather than using a single algorithm for feature extraction, the model here follows the paradigm of quality from quantity by implementing multiple feature extraction. Features include (compactness, Euler number, and invariant moments) for each region. Results obtained from the neural networks (namely; clustering and initial matching list) are used to select the best matching pair. Lastly, a refinement step is then applied.

Research paper thumbnail of Mathematical Model and Experimental Study To Optimize Rates Constants of Desorption And Adsorption of The Waste Water Using Palm Fronds

Journal of the Pakistan Institute of Chemical Engineers

Physical, mechanical and multi – step chemical treatments on the adsorptivity of palm fronds ad... more Physical, mechanical and multi – step chemical treatments on the adsorptivity of palm fronds adsorbent for the removal of 5 waste metal components from wastewater was studied and estimated in this paper. Three techniques are used for palm frond to produce modified activated carbon as adsorbents. Physical treatment is represented in the furnace at 600 oC. Mechanical treatment is established more suitable surface area from 300µm2 to 500 µm2 to increase efficiency of adsorbent. Chemical treatment of palm fronds used Acetone – ethanol - methanol treated palm fronds. The fixed bed column study was achieved under multi layered fixed bed columns. It was discovered that, the adsorption of 5 metals were expressively increased in the following order: Acetone – ethanol – Methanol treated palm fronds. The highest percentage reduction of the area under the curve was represented by chemical treatment for palm fronds reached 98.74%. Derived mathematical model to describe the system and...

Research paper thumbnail of Study and analysis of electric vehicles adoption: a middle eastern country as a case study

Indonesian Journal of Electrical Engineering and Computer Science

Adaption of hybrid electric vehicles (HEVs) and electric vehicles (EVs) is an important choice th... more Adaption of hybrid electric vehicles (HEVs) and electric vehicles (EVs) is an important choice that has many positive environmental and economic impacts, where, it helps in reducing exhaust emission, participation in dropping down the amount of noise pollution, and improving the air quality. With these encouraging impacts as well as the reduction in the price of fuel consumption, electric vehicles become at the top of car industry. A study on electric vehicles and their impact on improving the quality of environment is the main motive of this research. Selected theories and factors related to the electric vehicles’ adoption are investigated and analysed. The main factor that led to the spread of electric vehicles is the reliance on electric energy, so it is considered as zero emissions. But there is another effect, which is that these vehicles need continuous electric charging daily, which in turn needs to generate electricity, which leads to environmental pollution indirectly.

Research paper thumbnail of COVID-19 Diagnosis Using Spectral and Statistical Analysis of Cough Recordings Based on the Combination of SVD and DWT

Baghdad Science Journal

Healthcare professionals routinely use audio signals, generated by the human body, to help diagno... more Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopting a combination of Singular Value Decomposition (SVD), and Discrete Wavelet Transform (DWT). The combination of these two signal processing techniques is gaining lots of interest in the field of speaker and speech recognition. As a cough recognitio...

Research paper thumbnail of Corresponding Author

Abstract: The theory and application of (t-EC-AUED) codes was presented and among the methods pro... more Abstract: The theory and application of (t-EC-AUED) codes was presented and among the methods proposed in literature, the most efficient was chosen and a software was written for encoding and decoding of the codes. Comparison and evaluation of the construction techniques were carried out. A t-Error Correction (EC)/All Unidirectional Error Detection (AUED) codes are constructed by appending a single check symbol to a linear t-EC code to achieve the AUED property.

Research paper thumbnail of Enhanced Image Segmentation: Merging Fuzzy K-Means and Fuzzy C-Means Clustering Algorithms for Medical Applications

Computer Science and Information Technology, 2021

Research paper thumbnail of Computer-Supported Learning: A Teaching Aid for ECE Students

The use of computer hardware and software in education and training is a long established practic... more The use of computer hardware and software in education and training is a long established practice. In this work, an educational software is developed as a computer- supported tool to assist students' learning. Software engineering aspects are emphasized during the development, for the product to be simple and user friendly such that it can be used by all targeted students. In addition, the package is open for future expansions. Emphasis is paid to implementing solutions for issues that students face difficulties in understanding. The developed software system is provided with a database for many courses of the Electrical and Computer Engineering department. For the purpose of evaluation, number of students have used the software. Those students express a noticeable interest and benefit.

Research paper thumbnail of A Novel Algorithm Based on LoRa Technology for Open-Field and Protected Agriculture Smart Irrigation System

2019 2nd IEEE Middle East and North Africa COMMunications Conference (MENACOMM), 2019

A novel algorithm for smart irrigation system adaptable for both open-field and protected agricul... more A novel algorithm for smart irrigation system adaptable for both open-field and protected agriculture based on LoRa technology is proposed in this paper. The algorithm suits a networked architecture, in which a central controller is communicating with distributed units of sensors and actuators. Communication within the system units use LoRa devices, where a LoRa is an IoT based technology providing low-power and long-range radio connectivity. Within an agricultural farm, the system can be configured such that it can suit the control of environmental conditions applicable for either an open-field and/or a protected (e.g. greenhouse) agricultures. A database has been developed and designed to comply with the system architecture. The collected data is analyzed and used by the system for automatically adjusting itself to an optimal or semi-optimal performance. At the central control, the user interface offer system monitoring capability, statistics, as well as report generation.

Research paper thumbnail of Detection and Diagnostic Approach of COVID-19 Based on Cough Sound Analysis

Journal of Computer Science, 2021

Research paper thumbnail of Remote-Controlled Microcontroller-Based Temperature System : An Economical Design

Temperature measurement and monitoring are very important for most service and industrial applica... more Temperature measurement and monitoring are very important for most service and industrial applications. This paper presents the design of a remote-controlled microcontroller-based system. A multi-sensor/ multi-actuator system is proposed and the paper illustrates the steps for the design development. System simulation and the fabrication of a hardware prototype are both presented. Design alternatives are described, and emphasization on the choice of the economical and reliable ones are justified. The IR remote control unit, used in the hardware prototype as to replace keypad for the temperature setting, is described. Keywords— Automation; microcontroller; sensors; temperature control ; thermistor.

Research paper thumbnail of Modified Fuzzy C-Means Clustering Algorithm Application in Medical Image Segmentation

Developing effective algorithm for segmenting image is very important in pattern recognition, med... more Developing effective algorithm for segmenting image is very important in pattern recognition, medical MRI, X-Ray images analysis and in computer vision. Fuzzy c-means (FCM) is one of the mostly used methodologies in clustering image for segmentation. However, the results of the standard and the modified version FCM are not always satisfactory. This paper introduces a spatial FCM that considers the weighted fuzzy effect of neighboring pixels on the cluster center depending on the location and intensity (kernel metric). The objective function in the FCM algorithm is modified to minimize the intensity inhomogeneities, by implicating the spatial neighborhood information and modifying the membership weighting of each cluster. The advantages of the new FCM algorithm are: (a) produces homogeneous regions more than FCM algorithm, (b) handles noisy spots, and (c) it is relatively less sensitive to noise. Experimental results on real images show that the algorithm is effective, efficient, a...

Research paper thumbnail of Fault Diagnosis of Rotating Machine Based on Audio Signal Recognition System: An Efficient Approach

International journal of simulation: systems, science & technology, 2020

An efficient algorithm for condition monitoring of rotating machines is proposed in this paper. C... more An efficient algorithm for condition monitoring of rotating machines is proposed in this paper. Condition indicators are derived from sound signals, and used to arrive at a decision about the performance state of the machine. Sound signals are recorded by microphones and processed using time-frequency domain analysis. In this study, number of statistical features; such as mean, standard deviation, skewness, and kurtosis are considered. These statistical features were proven to be effective and simple to interpret. Healthy, about to be faulty, and faulty performance states of the machine are considered, and audio signals are recorded for each state. The five main steps comprising the implemented approach are data acquisition, preprocessing, feature extraction, time and frequency domain analysis, and the decision making. Based on the adopted statistical measures, the experimental results indicate that an excellent recognition of machine performance states is obtained, leading to an efficient fault detection and diagnosis.

Research paper thumbnail of Bridging for cross protocol talk in IOT devices using windows communication foundation

International Journal of Engineering & Technology, 2018

In the Internet of Things (IoT), multiple communication protocols are used to connect the smart d... more In the Internet of Things (IoT), multiple communication protocols are used to connect the smart device. Wi-Fi, Xbee, ZigBee, Bluetooth, and LoRaWAN are some of the communication channels utilized for connectivity by devices using some IoT platform.In order to enable the development of smart services for IoT platforms, there are solutions by different vendors to connect between IoT devices. For example, multiple IoT platforms are available in the market namely IoTivity platform developed by Open Connectivity Foundation (OCF), AllJoyn platform from All Seen Alliance, Weave made by Google, and Home Kit by Apple. In view of such segmentation of IoT platforms, IoT Application’s development has been made complex, where IoT device and accompanying application compatibility with available platforms requires support for multiple protocols.To simplify the complexity introduced by multiple platforms, M2M [4] International standard was already proposed as the bridge for integrating IoT protocol...

Research paper thumbnail of Neural Network Classification of White Blood Cell using Microscopic Images

International Journal of Advanced Computer Science and Applications, 2017

Research paper thumbnail of A Universal Decoding Algorithm for t-EC/AUED Codes

Asian Journal of Information Technology, Dec 1, 2014

Research paper thumbnail of Full Automation in Driverless Trains: A Microcontroller-Based Prototype

International Journal of Advanced Research in Electrical, Electronics and Instrumentation Energy, Jul 30, 2014

Research paper thumbnail of Artificial Neural Network as a Decision- Makers for Stereo Matching

Research paper thumbnail of Artificial Neural Networks as Decision-Makers for Stereo Matching

PsycEXTRA Dataset

This paper investigates the use of artificial neural networks to help making a decision on matchi... more This paper investigates the use of artificial neural networks to help making a decision on matching of stereo images. An image matching technique based on extracting features from segmented regions is adopted in this work, and a neural network framework is applied for region matching of stereo photographs. Two types of neural networks are used, the radial basis network, (RB) for learning clustering, and the back propagation (BP) network for learning image matching. The (RB) neural network is to cluster the regions according to the locations of their centered points. For each region, the BP network uses differential features as input training data. While training and testing the system, multiple features are extracted and used for enhancing the accuracy of the matching process. Features include (compactness, Euler number, and invariant moments) for each region. Results obtained from the neural networks (namely; clustering and initial matching array) are used to select the best matching pair. Results are showing a good matching accuracy.

Research paper thumbnail of Evaluating the Effect of Inheritance on the Characteristics of Object Oriented Programs

Journal of Computer Science, 2006

Research paper thumbnail of Performance Improvement and Deadlock Prevention for a Distributed Fault Diagnosis Algorithm

Journal of Computer Science, 2007

Research paper thumbnail of Applying a Neural Network Framework for Stereo Matching

PsycEXTRA Dataset

Approaches for image matching can be broadly classified into two categories: the intensity-based ... more Approaches for image matching can be broadly classified into two categories: the intensity-based matching and the feature-based matching techniques. A technique from the second category is adopted in this work, where a neural framework is applied for region matching of stereo photographs. Two different types of neural networks are used in this framework, the radial basis network, (RB) for learning clustering, and the back propagation (BP) network for learning image matching. The (RB) neural network is to cluster the regions according to the locations of their centered points. The BP network uses differential features of each region as input training data. Rather than using a single algorithm for feature extraction, the model here follows the paradigm of quality from quantity by implementing multiple feature extraction. Features include (compactness, Euler number, and invariant moments) for each region. Results obtained from the neural networks (namely; clustering and initial matching list) are used to select the best matching pair. Lastly, a refinement step is then applied.