Muna H A D I Saleh | University of Baghdad (original) (raw)
Videos by Muna H A D I Saleh
soft computing (SC) techniques have been used in designing industrial intelligent controllers and... more soft computing (SC) techniques have been used in designing industrial intelligent controllers and implementing them in the application of an Overhead Traveling Crane (OTC). A real practical OTC prototype model controlled by personal computer has been designed and built in order to simulate the operations of the OTC. These operations include moving the suspended load through a desired distance in the minimum possible time, minimum swing angle approximately (0º) and with all state variables of the trolley and their suspended load coming to rest at the end of the manoeurve. In addition, there are two types of trajectory commands. One that represents position command, and the other represents velocity command. A fuzzy Logic Controller (FLC) has been designed with a new algorithm. A Case-Based Knowledge and Global Weight (GW) was used in building their algorithm. This new FLC has been combined with a more modern theory called Rough Set Theory.
Papers by Muna H A D I Saleh
JOURNAL OF THE COLLEGE OF EDUCATION FOR WOMEN, 2013
Abstract: The mobile device be used in all fields in society to be the life is more easy. So that... more Abstract: The mobile device be used in all fields in society to be the life is more easy. So that it's used in the instructional operation and that need to study the effective of it in the teaching operation. The aims of research are known the effect of using the Bluetooth techniques in the mobile upon students' achievement and their retention of information. The sample consist of (34) students in the first class in Electrical Techniques Department in Technical Institute of Nassiriayah at (2010 – 2011) which divided to two equivalent groups, experimental and control by using the two equivalent groups design. Seven subjects were choices of Electrical Installation subject in second course. The researcher limited the teaching objectives and built the teaching plans of each group and the final achievement test which consist of (28) questions and doing the psychometrics characterizes by using suitable statistical methods. The teaching operation to the all students is beginning, the students in the two groups teaching the subject together at same time by the teacher. After that the teacher send the more explaining information by the Bluetooth techniques in the mobile about the teaching subject to the students in experimental group while don’t send anything to the students in the control group. The research continue seven weeks and after that the final achievement test is applied to the students in two group at same time and re– applied to them after three weeks as retention of information test. And using suitable statistical methods to analysis the finding and doing the psychometrics characterizes to the research instrument. The finding is supremacy the students in the experimental group which using the Bluetooth techniques in mobile in the achievement and retention of information than the student in the control group which don’t used it. The researcher including the affectivity of the Bluetooth techniques in mobile to increased the achievement of students and their retention of information and they suggest some suggestions that suitable with the finding.
Journal of Al-Ma'moon College, 2012
Baghdad Science Journal, Sep 6, 2009
Periodicals of Engineering and Natural Sciences (PEN), Feb 28, 2023
This work is based on encouraging a generous and conceivable estimation for modified an algorithm... more This work is based on encouraging a generous and conceivable estimation for modified an algorithm for vehicle travel times on a highway from the eliminated traffic information using set aside camera image groupings. The strategy for the assessment of vehicle travel times relies upon the distinctive verification of traffic state. The vehicle velocities are gotten from acknowledged vehicle positions in two persistent images by working out the distance covered all through elapsed past time doing mollification between the removed traffic flow data and cultivating a plan to unequivocally predict vehicle travel times. Erbil road data base is used to recognize road locales around road segments which are projected into the commended camera images and later distinguished vehicles are assigned to the looking at route segment so instantaneous and current velocities are calculated. All data were effectively processed and visualized using both MATLAB and Python programming language and its libraries.
Maǧallaẗ al-handasaẗ, Apr 1, 2023
One of the most important features of the Amazon Web Services (AWS) cloud is that the program can... more One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services through our cameras system to capture the images and upload them to the Amazon Simple Storage Service (AWS S3) cloud. Then two detectors were running, Haar cascade and multitask cascaded convolutional neural networks (MTCNN), at the Amazon Elastic Compute (AWS EC2) cloud, after that the output results of these two detectors are compared using accuracy and execution time. Then the classified non-permission images are uploaded to the AWS S3 cloud. The validation accuracy of the offline augmentation face detection classification model reached 98.81%, and the loss and mean square error were decreased to 0.0176 and 0.0064, respectively. The execution time of all AWS cloud systems for one image when using Haar cascade and MTCNN detectors reached three and seven seconds, respectively.
Journal of College of Education for Women, 2019
Shadow detection and removal is an important task when dealing with color outdoor images. Shadows... more Shadow detection and removal is an important task when dealing with color outdoor images. Shadows are generated by a local and relative absence of light. Shadows are, first of all, a local decrease in the amount of light that reaches a surface. Secondly, they are a local change in the amount of light rejected by a surface toward the observer. Most shadow detection and segmentation methods are based on image analysis. However, some factors will affect the detection result due to the complexity of the circumstances. In this paper a method of segmentation test present to detect shadows from an image and a function concept is used to remove the shadow from an image.
Porosity is one of the most important reservoir characteristics because it indicates to fluid col... more Porosity is one of the most important reservoir characteristics because it indicates to fluid collection. Several techniques used to get good porosity prediction, so, in this study we employed seismic attributes and well log data in a genetic algorithm to get the best porosity prediction. The study attempt to enhance the performance of genetic algorithm for attribute selection and therefore porosity prediction by applying genetic algorithm on different types of fitness functions like average mean square error fitness, average correlation coefficients fitness and performance index fitness. Also, used two methods to represent attributes in genetic algorithm. Different witnesses applied to choose the appropriate fitness function that gives high porosity prediction.
INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY, 2015
In this paper, used fuzzy set as a controller to control roll and yaw angles in lateral dynamic o... more In this paper, used fuzzy set as a controller to control roll and yaw angles in lateral dynamic of the autopilot system for jet transport using MATLAB/SIMULINK. Autopilot systems are complex devices that demand exact control and stability. In this paper explained the lateral dynamic on automatic pilot and studied the effect of atmospheric disturbances on the stability then designed the fuzzy set controller to reduce three type of disturbance which faced the pilot during the flight.
International Journal of Computer Applications, 2015
Autopilot systems have been vital to flight control for several years and have been making flight... more Autopilot systems have been vital to flight control for several years and have been making flight easier and more effective. Nevertheless, these autopilot systems are complex devices that demand exact control and stability. In this paper, design PID controller to control pitch angle in longitudinal dynamic of the autopilot system for jet transport using MATLAB/SIMULINK. In this paper designed on automatic pilot with Multi Input Multi Output (MIMO) system. Also, we studied the effect of atmospheric disturbances when a PID controller has been applied the results shown how this controller with good tuning reducing the effect of atmospheric disturbance on the consistency of the autopilot.
IAES International Journal of Artificial Intelligence, Jun 1, 2023
The fundamental of a downlink massive multiple-input multiple-output (MIMO) energy-issue efficien... more The fundamental of a downlink massive multiple-input multiple-output (MIMO) energy-issue efficiency strategy is known as minimum mean squared error (MMSE) implementation degrades the performance of a downlink massive MIMO energy-efficiency scheme, so some improvements are adding for this precoding scheme to improve its workthat is called our proposal solution as a proposed improved MMSE precoder (PIMP). The energy efficiency (EE) study has also taken into mind drastically lowering radiated power while maintaining high throughput and minimizing interference issues. We further find the tradeoff between spectral efficiency (SE) and EE although they coincide at the beginning but later their interests become conflicting and divergent then leading EE to decrease so gradually while SE continues increasing logarithmically. The results achieved that for a single-cellular massive MU-MIMO downlink model, our PIMP scheme is the appropriate scenario to achieve higher precoding performance system. Furthermore, both maximum ratio transmission (MRT) and PIMP are suitable for performance improvement in massive MIMO results of EE and SE. So, the main contribution comes with this work that highest EE and SE are belong to use a PIMP which performs better appreciably than MRT at bigger ratio of number of antennas to the number of the users.
This work is based on encouraging a generous and conceivable estimation for modified an algorithm... more This work is based on encouraging a generous and conceivable estimation for modified an algorithm for vehicle travel times on a highway from the eliminated traffic information using set aside camera image groupings. The strategy for the assessment of vehicle travel times relies upon the distinctive verification of traffic state. The vehicle velocities are gotten from acknowledged vehicle positions in two persistent images by working out the distance covered all through elapsed past time doing mollification between the removed traffic flow data and cultivating a plan to unequivocally predict vehicle travel times. Erbil road data base is used to recognize road locales around road segments which are projected into the commended camera images and later distinguished vehicles are assigned to the looking at route segment so instantaneous and current velocities are calculated. All data were effectively processed and visualized using both MATLAB and Python programming language and its libraries.
Journal of Robotics
Image classification is the process of finding common features in images from various classes and... more Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven classifiers. A hybrid supervised learning system that takes advantage of rich intermediate features extracted from deep learning compared to traditional feature extraction to boost classification accuracy and parameters is suggested. They provide the same set of c...
Hindawi Journal of Robotics, 2023
Image classifcation is the process of fnding common features in images from various classes and a... more Image classifcation is the process of fnding common features in images from various classes and applying them to categorize and label them. Te main problem of the image classifcation process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classifcation. Te cornerstone of image classifcation is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifers. Tis study proposes a new approach of "hybrid learning" by combining deep learning with machine learning for image classifcation based on convolutional feature extraction using the VGG-16 deep learning model and seven classifers. A hybrid supervised learning system that takes advantage of rich intermediate features extracted from deep learning compared to traditional feature extraction to boost classifcation accuracy and parameters is suggested. Tey provide the same set of characteristics to discover and verify which classifer yields the best classifcation with our new proposed approach of "hybrid learning." To achieve this, the performance of classifers was assessed depending on a genuine dataset that was taken by our camera system. Te simulation results show that the support vector machine (SVM) has a mean square error of 0.011, a total accuracy ratio of 98.80%, and an F1 score of 0.99. Moreover, the results show that the LR classifer has a mean square error of 0.035 and a total ratio of 96.42%, and an F1 score of 0.96 comes in the second place. Te ANN classifer has a mean square error of 0.047 and a total ratio of 95.23%, and an F1 score of 0.94 comes in the third place. Furthermore, RF, WKNN, DT, and NB with a mean square error and an F1 score advance to the next stage with accuracy ratios of 91.66%, 90.47%, 79.76%, and 75%, respectively. As a result, the main contribution is the enhancement of the classifcation performance parameters with images of varying brightness and clarity using the proposed hybrid learning approach.
Periodicals of Engineering and Natural Sciences, 2023
This work is based on encouraging a generous and conceivable estimation for modified an algorithm... more This work is based on encouraging a generous and conceivable estimation for modified an algorithm for vehicle travel times on a highway from the eliminated traffic information using set aside camera image groupings. The strategy for the assessment of vehicle travel times relies upon the distinctive verification of traffic state. The vehicle velocities are gotten from acknowledged vehicle positions in two persistent images by working out the distance covered all through elapsed past time doing mollification between the removed traffic flow data and cultivating a plan to unequivocally predict vehicle travel times. Erbil road data base is used to recognize road locales around road segments which are projected into the commended camera images and later distinguished vehicles are assigned to the looking at route segment so instantaneous and current velocities are calculated. All data were effectively processed and visualized using both MATLAB and Python programming language and its libraries.
Indonesian Journal of Electrical Engineering and Computer Science, 2022
During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and off... more During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieved lower computational complexity and number of layers, while being more reliable compared with other algorithms applied to recognize face masks. The findings reveal that the model's validation accuracy reaches 97.55% to 98.43% at different learning rates and different values of features vector in the dense layer, which represents a neural network layer that is connected deeply of the CNN proposed model training. Finally, the suggested model enhances recognition performance parameters such as precision, recall, and area under the curve (AUC).
IAES International Journal of Artificial Intelligence (IJ-AI), 2022
The fundamental of a downlink massive multiple-input multiple-output (MIMO) energy-issue efficie... more The fundamental of a downlink massive multiple-input multiple-output
(MIMO) energy-issue efficiency strategy is known as minimum mean
squared error (MMSE) implementation degrades the performance of a
downlink massive MIMO energy-efficiency scheme, so some improvements
are adding for this precoding scheme to improve its workthat is called our
proposal solution as a proposed improved MMSE precoder (PIMP). The
energy efficiency (EE) study has also taken into mind drastically lowering
radiated power while maintaining high throughput and minimizing
interference issues. We further find the tradeoff between spectral efficiency
(SE) and EE although they coincide at the beginning but later their interests
become conflicting and divergent then leading EE to decrease so gradually
while SE continues increasing logarithmically. The results achieved that for
a single-cellular massive MU-MIMO downlink model, our PIMP scheme is
the appropriate scenario to achieve higher precoding performance system.
Furthermore, both maximum ratio transmission (MRT) and PIMP are
suitable for performance improvement in massive MIMO results of EE and
SE. So, the main contribution comes with this work that highest EE and SE
are belong to use a PIMP which performs better appreciably than MRT at
bigger ratio of number of antennas to the number of the users.
Journal of Engineering
The need for quick airborne transportation is critical, especially in emergencies. Drones with su... more The need for quick airborne transportation is critical, especially in emergencies. Drones with suspended payloads might be used to accomplish quick airborne transportation. Due to the environment or the drone's motion, the slung load may oscillate and lead the drone to fall. The altitude and attitude controls are the backbones of the drone's stability, and they must be adequately designed. Because of their symmetrical and simple structure, quadrotor helicopters are one of the most popular drone classes. In this work, a genetic algorithm with two weighted terms fitness function is used to adjust a Proportional-Integral-Derivative (PID) controller to compensate for the altitude and attitude controllers in a quadrotor drone with a slung load.
International Journal of Computer Applications, 2016
This study aimed to identify the impact of the complementary relationship between the application... more This study aimed to identify the impact of the complementary relationship between the application of electronic environment and quality instruction, through a review of the most effective means to achieve quality assurance in line with modern items, features of the twenty-first century. The study also found a set of conclusions: an instruction institution is one of the most important phases of e-Government, in particular with regard to the dissemination of information and two-way communication. So the activation of information technology in instruction institutions is one of the most important reasons for the success of e-government project. Finally, the study showed a trace of integration between application quality instruction under information and communication technology and the success of instruction institutions.
International Journal of Computer Applications, 2016
In this paper, the application of the Artificial Immune System (AIS) algorithm for optimization p... more In this paper, the application of the Artificial Immune System (AIS) algorithm for optimization problems is presented, DC Servo Motor (DCSM) speed control was taken as a case study. The PID controller was tuned using AIS algorithm by minimizing the Integral Time Absolute Error (ITAE). The results were compared with the results of the Ziegler-Nichols tuning method and it was obvious that the AIS gives better results. The AIS algorithm showed it has the ability to find the global optimum solution and it gave a response better than the response of the traditional tuning methods in terms of rise time, settling time, steady state error and overshoot.
soft computing (SC) techniques have been used in designing industrial intelligent controllers and... more soft computing (SC) techniques have been used in designing industrial intelligent controllers and implementing them in the application of an Overhead Traveling Crane (OTC). A real practical OTC prototype model controlled by personal computer has been designed and built in order to simulate the operations of the OTC. These operations include moving the suspended load through a desired distance in the minimum possible time, minimum swing angle approximately (0º) and with all state variables of the trolley and their suspended load coming to rest at the end of the manoeurve. In addition, there are two types of trajectory commands. One that represents position command, and the other represents velocity command. A fuzzy Logic Controller (FLC) has been designed with a new algorithm. A Case-Based Knowledge and Global Weight (GW) was used in building their algorithm. This new FLC has been combined with a more modern theory called Rough Set Theory.
JOURNAL OF THE COLLEGE OF EDUCATION FOR WOMEN, 2013
Abstract: The mobile device be used in all fields in society to be the life is more easy. So that... more Abstract: The mobile device be used in all fields in society to be the life is more easy. So that it's used in the instructional operation and that need to study the effective of it in the teaching operation. The aims of research are known the effect of using the Bluetooth techniques in the mobile upon students' achievement and their retention of information. The sample consist of (34) students in the first class in Electrical Techniques Department in Technical Institute of Nassiriayah at (2010 – 2011) which divided to two equivalent groups, experimental and control by using the two equivalent groups design. Seven subjects were choices of Electrical Installation subject in second course. The researcher limited the teaching objectives and built the teaching plans of each group and the final achievement test which consist of (28) questions and doing the psychometrics characterizes by using suitable statistical methods. The teaching operation to the all students is beginning, the students in the two groups teaching the subject together at same time by the teacher. After that the teacher send the more explaining information by the Bluetooth techniques in the mobile about the teaching subject to the students in experimental group while don’t send anything to the students in the control group. The research continue seven weeks and after that the final achievement test is applied to the students in two group at same time and re– applied to them after three weeks as retention of information test. And using suitable statistical methods to analysis the finding and doing the psychometrics characterizes to the research instrument. The finding is supremacy the students in the experimental group which using the Bluetooth techniques in mobile in the achievement and retention of information than the student in the control group which don’t used it. The researcher including the affectivity of the Bluetooth techniques in mobile to increased the achievement of students and their retention of information and they suggest some suggestions that suitable with the finding.
Journal of Al-Ma'moon College, 2012
Baghdad Science Journal, Sep 6, 2009
Periodicals of Engineering and Natural Sciences (PEN), Feb 28, 2023
This work is based on encouraging a generous and conceivable estimation for modified an algorithm... more This work is based on encouraging a generous and conceivable estimation for modified an algorithm for vehicle travel times on a highway from the eliminated traffic information using set aside camera image groupings. The strategy for the assessment of vehicle travel times relies upon the distinctive verification of traffic state. The vehicle velocities are gotten from acknowledged vehicle positions in two persistent images by working out the distance covered all through elapsed past time doing mollification between the removed traffic flow data and cultivating a plan to unequivocally predict vehicle travel times. Erbil road data base is used to recognize road locales around road segments which are projected into the commended camera images and later distinguished vehicles are assigned to the looking at route segment so instantaneous and current velocities are calculated. All data were effectively processed and visualized using both MATLAB and Python programming language and its libraries.
Maǧallaẗ al-handasaẗ, Apr 1, 2023
One of the most important features of the Amazon Web Services (AWS) cloud is that the program can... more One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services through our cameras system to capture the images and upload them to the Amazon Simple Storage Service (AWS S3) cloud. Then two detectors were running, Haar cascade and multitask cascaded convolutional neural networks (MTCNN), at the Amazon Elastic Compute (AWS EC2) cloud, after that the output results of these two detectors are compared using accuracy and execution time. Then the classified non-permission images are uploaded to the AWS S3 cloud. The validation accuracy of the offline augmentation face detection classification model reached 98.81%, and the loss and mean square error were decreased to 0.0176 and 0.0064, respectively. The execution time of all AWS cloud systems for one image when using Haar cascade and MTCNN detectors reached three and seven seconds, respectively.
Journal of College of Education for Women, 2019
Shadow detection and removal is an important task when dealing with color outdoor images. Shadows... more Shadow detection and removal is an important task when dealing with color outdoor images. Shadows are generated by a local and relative absence of light. Shadows are, first of all, a local decrease in the amount of light that reaches a surface. Secondly, they are a local change in the amount of light rejected by a surface toward the observer. Most shadow detection and segmentation methods are based on image analysis. However, some factors will affect the detection result due to the complexity of the circumstances. In this paper a method of segmentation test present to detect shadows from an image and a function concept is used to remove the shadow from an image.
Porosity is one of the most important reservoir characteristics because it indicates to fluid col... more Porosity is one of the most important reservoir characteristics because it indicates to fluid collection. Several techniques used to get good porosity prediction, so, in this study we employed seismic attributes and well log data in a genetic algorithm to get the best porosity prediction. The study attempt to enhance the performance of genetic algorithm for attribute selection and therefore porosity prediction by applying genetic algorithm on different types of fitness functions like average mean square error fitness, average correlation coefficients fitness and performance index fitness. Also, used two methods to represent attributes in genetic algorithm. Different witnesses applied to choose the appropriate fitness function that gives high porosity prediction.
INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY, 2015
In this paper, used fuzzy set as a controller to control roll and yaw angles in lateral dynamic o... more In this paper, used fuzzy set as a controller to control roll and yaw angles in lateral dynamic of the autopilot system for jet transport using MATLAB/SIMULINK. Autopilot systems are complex devices that demand exact control and stability. In this paper explained the lateral dynamic on automatic pilot and studied the effect of atmospheric disturbances on the stability then designed the fuzzy set controller to reduce three type of disturbance which faced the pilot during the flight.
International Journal of Computer Applications, 2015
Autopilot systems have been vital to flight control for several years and have been making flight... more Autopilot systems have been vital to flight control for several years and have been making flight easier and more effective. Nevertheless, these autopilot systems are complex devices that demand exact control and stability. In this paper, design PID controller to control pitch angle in longitudinal dynamic of the autopilot system for jet transport using MATLAB/SIMULINK. In this paper designed on automatic pilot with Multi Input Multi Output (MIMO) system. Also, we studied the effect of atmospheric disturbances when a PID controller has been applied the results shown how this controller with good tuning reducing the effect of atmospheric disturbance on the consistency of the autopilot.
IAES International Journal of Artificial Intelligence, Jun 1, 2023
The fundamental of a downlink massive multiple-input multiple-output (MIMO) energy-issue efficien... more The fundamental of a downlink massive multiple-input multiple-output (MIMO) energy-issue efficiency strategy is known as minimum mean squared error (MMSE) implementation degrades the performance of a downlink massive MIMO energy-efficiency scheme, so some improvements are adding for this precoding scheme to improve its workthat is called our proposal solution as a proposed improved MMSE precoder (PIMP). The energy efficiency (EE) study has also taken into mind drastically lowering radiated power while maintaining high throughput and minimizing interference issues. We further find the tradeoff between spectral efficiency (SE) and EE although they coincide at the beginning but later their interests become conflicting and divergent then leading EE to decrease so gradually while SE continues increasing logarithmically. The results achieved that for a single-cellular massive MU-MIMO downlink model, our PIMP scheme is the appropriate scenario to achieve higher precoding performance system. Furthermore, both maximum ratio transmission (MRT) and PIMP are suitable for performance improvement in massive MIMO results of EE and SE. So, the main contribution comes with this work that highest EE and SE are belong to use a PIMP which performs better appreciably than MRT at bigger ratio of number of antennas to the number of the users.
This work is based on encouraging a generous and conceivable estimation for modified an algorithm... more This work is based on encouraging a generous and conceivable estimation for modified an algorithm for vehicle travel times on a highway from the eliminated traffic information using set aside camera image groupings. The strategy for the assessment of vehicle travel times relies upon the distinctive verification of traffic state. The vehicle velocities are gotten from acknowledged vehicle positions in two persistent images by working out the distance covered all through elapsed past time doing mollification between the removed traffic flow data and cultivating a plan to unequivocally predict vehicle travel times. Erbil road data base is used to recognize road locales around road segments which are projected into the commended camera images and later distinguished vehicles are assigned to the looking at route segment so instantaneous and current velocities are calculated. All data were effectively processed and visualized using both MATLAB and Python programming language and its libraries.
Journal of Robotics
Image classification is the process of finding common features in images from various classes and... more Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven classifiers. A hybrid supervised learning system that takes advantage of rich intermediate features extracted from deep learning compared to traditional feature extraction to boost classification accuracy and parameters is suggested. They provide the same set of c...
Hindawi Journal of Robotics, 2023
Image classifcation is the process of fnding common features in images from various classes and a... more Image classifcation is the process of fnding common features in images from various classes and applying them to categorize and label them. Te main problem of the image classifcation process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classifcation. Te cornerstone of image classifcation is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifers. Tis study proposes a new approach of "hybrid learning" by combining deep learning with machine learning for image classifcation based on convolutional feature extraction using the VGG-16 deep learning model and seven classifers. A hybrid supervised learning system that takes advantage of rich intermediate features extracted from deep learning compared to traditional feature extraction to boost classifcation accuracy and parameters is suggested. Tey provide the same set of characteristics to discover and verify which classifer yields the best classifcation with our new proposed approach of "hybrid learning." To achieve this, the performance of classifers was assessed depending on a genuine dataset that was taken by our camera system. Te simulation results show that the support vector machine (SVM) has a mean square error of 0.011, a total accuracy ratio of 98.80%, and an F1 score of 0.99. Moreover, the results show that the LR classifer has a mean square error of 0.035 and a total ratio of 96.42%, and an F1 score of 0.96 comes in the second place. Te ANN classifer has a mean square error of 0.047 and a total ratio of 95.23%, and an F1 score of 0.94 comes in the third place. Furthermore, RF, WKNN, DT, and NB with a mean square error and an F1 score advance to the next stage with accuracy ratios of 91.66%, 90.47%, 79.76%, and 75%, respectively. As a result, the main contribution is the enhancement of the classifcation performance parameters with images of varying brightness and clarity using the proposed hybrid learning approach.
Periodicals of Engineering and Natural Sciences, 2023
This work is based on encouraging a generous and conceivable estimation for modified an algorithm... more This work is based on encouraging a generous and conceivable estimation for modified an algorithm for vehicle travel times on a highway from the eliminated traffic information using set aside camera image groupings. The strategy for the assessment of vehicle travel times relies upon the distinctive verification of traffic state. The vehicle velocities are gotten from acknowledged vehicle positions in two persistent images by working out the distance covered all through elapsed past time doing mollification between the removed traffic flow data and cultivating a plan to unequivocally predict vehicle travel times. Erbil road data base is used to recognize road locales around road segments which are projected into the commended camera images and later distinguished vehicles are assigned to the looking at route segment so instantaneous and current velocities are calculated. All data were effectively processed and visualized using both MATLAB and Python programming language and its libraries.
Indonesian Journal of Electrical Engineering and Computer Science, 2022
During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and off... more During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieved lower computational complexity and number of layers, while being more reliable compared with other algorithms applied to recognize face masks. The findings reveal that the model's validation accuracy reaches 97.55% to 98.43% at different learning rates and different values of features vector in the dense layer, which represents a neural network layer that is connected deeply of the CNN proposed model training. Finally, the suggested model enhances recognition performance parameters such as precision, recall, and area under the curve (AUC).
IAES International Journal of Artificial Intelligence (IJ-AI), 2022
The fundamental of a downlink massive multiple-input multiple-output (MIMO) energy-issue efficie... more The fundamental of a downlink massive multiple-input multiple-output
(MIMO) energy-issue efficiency strategy is known as minimum mean
squared error (MMSE) implementation degrades the performance of a
downlink massive MIMO energy-efficiency scheme, so some improvements
are adding for this precoding scheme to improve its workthat is called our
proposal solution as a proposed improved MMSE precoder (PIMP). The
energy efficiency (EE) study has also taken into mind drastically lowering
radiated power while maintaining high throughput and minimizing
interference issues. We further find the tradeoff between spectral efficiency
(SE) and EE although they coincide at the beginning but later their interests
become conflicting and divergent then leading EE to decrease so gradually
while SE continues increasing logarithmically. The results achieved that for
a single-cellular massive MU-MIMO downlink model, our PIMP scheme is
the appropriate scenario to achieve higher precoding performance system.
Furthermore, both maximum ratio transmission (MRT) and PIMP are
suitable for performance improvement in massive MIMO results of EE and
SE. So, the main contribution comes with this work that highest EE and SE
are belong to use a PIMP which performs better appreciably than MRT at
bigger ratio of number of antennas to the number of the users.
Journal of Engineering
The need for quick airborne transportation is critical, especially in emergencies. Drones with su... more The need for quick airborne transportation is critical, especially in emergencies. Drones with suspended payloads might be used to accomplish quick airborne transportation. Due to the environment or the drone's motion, the slung load may oscillate and lead the drone to fall. The altitude and attitude controls are the backbones of the drone's stability, and they must be adequately designed. Because of their symmetrical and simple structure, quadrotor helicopters are one of the most popular drone classes. In this work, a genetic algorithm with two weighted terms fitness function is used to adjust a Proportional-Integral-Derivative (PID) controller to compensate for the altitude and attitude controllers in a quadrotor drone with a slung load.
International Journal of Computer Applications, 2016
This study aimed to identify the impact of the complementary relationship between the application... more This study aimed to identify the impact of the complementary relationship between the application of electronic environment and quality instruction, through a review of the most effective means to achieve quality assurance in line with modern items, features of the twenty-first century. The study also found a set of conclusions: an instruction institution is one of the most important phases of e-Government, in particular with regard to the dissemination of information and two-way communication. So the activation of information technology in instruction institutions is one of the most important reasons for the success of e-government project. Finally, the study showed a trace of integration between application quality instruction under information and communication technology and the success of instruction institutions.
International Journal of Computer Applications, 2016
In this paper, the application of the Artificial Immune System (AIS) algorithm for optimization p... more In this paper, the application of the Artificial Immune System (AIS) algorithm for optimization problems is presented, DC Servo Motor (DCSM) speed control was taken as a case study. The PID controller was tuned using AIS algorithm by minimizing the Integral Time Absolute Error (ITAE). The results were compared with the results of the Ziegler-Nichols tuning method and it was obvious that the AIS gives better results. The AIS algorithm showed it has the ability to find the global optimum solution and it gave a response better than the response of the traditional tuning methods in terms of rise time, settling time, steady state error and overshoot.
International Journal of Computer Applications, 2016
Many applications require a careful selection of attributes or features from a much larger set of... more Many applications require a careful selection of attributes or features from a much larger set of data. This attributes selection problem need to optimized. In order to tackle this problem this paper proposes a binary-real code multi-gen multi-parameter genetic algorithm for attributes selection from large seismic data and prediction of effective porosity. Genetic Algorithm (GA) uses three selection methods for this purpose, mean square error and correlation coefficient are two witness criteria to choose the best subset of attributes that minimize the error and give high prediction of porosity.