Mardin Anwer - Academia.edu (original) (raw)

Papers by Mardin Anwer

Engineering Science and Technology, an International Journal, Apr 1, 2017

In this paper a hidden Markov model and harmony search algorithms are combined for writer indepen... more In this paper a hidden Markov model and harmony search algorithms are combined for writer independent online Kurdish character recognition. The Markov model is integrated as an intermediate group classifier instead of a main character classifier/recognizer as in most of previous works. Markov model is used to classify each group of characters, according to their forms, into smaller sub groups based on common directional feature vector. This process reduced the processing time taken by the later recognition stage. The small number of candidate characters are then processed by harmony search recognizer. The harmony search recognizer uses a dominant and common movement pattern as a fitness function. The objective function is used to minimize the matching score according to the fitness function criteria and according to the least score for each segmented group of characters. Then, the system displays the generated word which has the lowest score from the generated character combinations. The system was tested on a dataset of 4500 words structured with 21,234 characters in different positions or forms (isolated, start, middle and end). The system scored 93.52% successful recognition rate with an average of 500 ms. The system showed a high improvement in recognition rate when compared to similar systems that use HMM as its main recognizer.

Cihan University-Erbil scientific journal, 2017

Edge detection plays an important role in image processing, pattern recognition and computer visi... more Edge detection plays an important role in image processing, pattern recognition and computer vision applications. Most of edge detection schemes are based on finding maximum in the first derivative of the image function or zero crossings in the second derivative of the image function. Various methods of edge detection for color images, including techniques extended from monochrome edge detection as well as vector space methods are presented. This research presents a comparative study on different methods of edge detection of color images. The methods are based on vector space, color space and numerical methods. Seven different colored images are test in this research. Performance is analyzed depending on Mean Square Error (MSE). The experimental results show that applying vector value (Jacobian method)will create a thick and disconnected edge with all operators Sobel, Prewitt and Log. While the least square method produce edges that are much thicker but continuous. The best performance was found when using YCbCr luminance (Y) and chrominance (Cb and Cr) method, the edges are sharpened, continuous, and not thickness. They are similar with Sobel and Prewitt operators nonetheless with some missing edges while it is better with Log operator.

Journal of University of Human Development, 2016

E-health is the present communication structure in medicine especially in developed countries. To... more E-health is the present communication structure in medicine especially in developed countries. Toward enhancing the quality of care and reduce the health care delivery cost, cloud Computing technology has been adopted. In recent times services such as exchange and share medical data among staff and then to the patients are one the main reasons behind using this technology in e-health. Hence, using cloud computing in e-health has many challenges particularly when dealing with electronic healthcare records (EHR). Cloud computing is an agglomeration of technologies, operating systems, storage, networking, virtualisation, each fraught with inherent security issues. For example, browser-based attacks, denial of service attacks and network intrusion become carry-over risks into cloud computing. It differs from traditional computing paradigms as it is scalable which can be encapsulated as an abstract entity to provide different levels of services to the clients. In this paper, we identified the users of e-health such as doctors, nurses and family members and then their security requirements are identified. An application with five stages toward encryption and decryption process is designed. Since trust is a critical factor in cloud computing, this project will investigate the obstacles that cause this technology lose its credibility in certain clouds. To enhance user authentication process, two-tier mechanisms are used to identify the user's identity. While in confidentiality, it should be assured that information is shared only among authorised people or vendors by applying powerful cryptographic concepts. In this prototype application, the user will be able to protect his/her data and is responsible for providing a high level of security as long as these data are highly private and important.

Govarî Qeła, Apr 15, 2017

Indonesian Journal of Electrical Engineering and Computer Science, 2021

Classifying and finding type of individual vehicles within an accident image are considered diffi... more Classifying and finding type of individual vehicles within an accident image are considered difficult problems. This research concentrates on accurately classifying and recognizing vehicle accidents in question. The aim to provide a comparative analysis of vehicle accidents. A number of network topologies are tested to arrive at convincing results and a variety of matrices are used in the evaluation process to identify the best networks. The best two networks are used with faster recurrent convolution neural network (Faster RCNN) and you only look once (YOLO) to determine which network will identifiably detect the location and type of the vehicle. In addition, two datasets are used in this research. In consequence, experiment results show that MobileNetV2 and ResNet50 have accomplished higher accuracy compared to the rest of the models, with 89.11% and 88.45% for the GAI dataset as well as 88.72% and 89.69% for KAI dataset, respectively. The findings reveal that the ResNet50 base ne...

ZANCO Journal of Pure and Applied Sciences, 2016

Social media has been considered to have major changes to the strategies and tools used by busine... more Social media has been considered to have major changes to the strategies and tools used by business organizations to communicate with potential customers. Merely because it connects millions of user together in an easy and simple way. Although, there are many types of social media which are used to endorse business, Facebook has been noticeably used for this purpose by many corporations because it needs limited financial resources and little experience in the IT field. In Kurdistan, many businesses started to use Facebook to be the main tool for marketing and E-Commerce. Therefore, this paper inspects the role of Facebook pages in promoting Small and Medium Enterprises (SMEs) in Kurdistan. The paper compares 200 organizations that have business page with 200 organizations that do not have one. Thus, it explores if Facebook has achieved its role as target-oriented advertising campaigns or not. Moreover, these pages have been examined to conclude the factors that make some of these bu...

Proceeding of 1st International Conference on Information Technology, 2017

Engineering Science and Technology, an International Journal, 2017

In this paper a hidden Markov model and harmony search algorithms are combined for writer indepen... more In this paper a hidden Markov model and harmony search algorithms are combined for writer independent online Kurdish character recognition. The Markov model is integrated as an intermediate group classifier instead of a main character classifier/recognizer as in most of previous works. Markov model is used to classify each group of characters, according to their forms, into smaller sub groups based on common directional feature vector. This process reduced the processing time taken by the later recognition stage. The small number of candidate characters are then processed by harmony search recognizer. The harmony search recognizer uses a dominant and common movement pattern as a fitness function. The objective function is used to minimize the matching score according to the fitness function criteria and according to the least score for each segmented group of characters. Then, the system displays the generated word which has the lowest score from the generated character combinations. The system was tested on a dataset of 4500 words structured with 21,234 characters in different positions or forms (isolated, start, middle and end). The system scored 93.52% successful recognition rate with an average of 500 ms. The system showed a high improvement in recognition rate when compared to similar systems that use HMM as its main recognizer.

2nd International Conference of Cihan University-Erbil on Communication Engineering and Computer Science, 2017

Edge detection plays an important role in image processing, pattern recognition and computer visi... more Edge detection plays an important role in image processing, pattern recognition and computer vision applications. Most of edge detection schemes are based on finding maximum in the first derivative of the image function or zero crossings in the second derivative of the image function. Various methods of edge detection for color images, including techniques extended from monochrome edge detection as well as vector space methods are presented. This research presents a comparative study on different methods of edge detection of color images. The methods are based on vector space, color space and numerical methods. Seven different colored images are test in this research. Performance is analyzed depending on Mean Square Error (MSE). The experimental results show that applying vector value (Jacobian method)will create a thick and disconnected edge with all operators Sobel, Prewitt and Log. While the least square method produce edges that are much thicker but continuous. The best performance was found when using YCbCr luminance (Y) and chrominance (Cb and Cr) method, the edges are sharpened, continuous, and not thickness. They are similar with Sobel and Prewitt operators nonetheless with some missing edges while it is better with Log operator.

Journal of University of Human Development, 2016

E-health is the present communication structure in medicine especially in developed countries. To... more E-health is the present communication structure in medicine especially in developed countries. Toward enhancing the quality of care and reduce the health care delivery cost, cloud Computing technology has been adopted. In recent times services such as exchange and share medical data among staff and then to the patients are one the main reasons behind using this technology in e-health. Hence, using cloud computing in e-health has many challenges particularly when dealing with electronic healthcare records (EHR). Cloud computing is an agglomeration of technologies, operating systems, storage, networking, virtualisation, each fraught with inherent security issues. For example, browser-based attacks, denial of service attacks and network intrusion become carry-over risks into cloud computing. It differs from traditional computing paradigms as it is scalable which can be encapsulated as an abstract entity to provide different levels of services to the clients. In this paper, we identified the users of e-health such as doctors, nurses and family members and then their security requirements are identified. An application with five stages toward encryption and decryption process is designed. Since trust is a critical factor in cloud computing, this project will investigate the obstacles that cause this technology lose its credibility in certain clouds. To enhance user authentication process, two-tier mechanisms are used to identify the user's identity. While in confidentiality, it should be assured that information is shared only among authorised people or vendors by applying powerful cryptographic concepts. In this prototype application, the user will be able to protect his/her data and is responsible for providing a high level of security as long as these data are highly private and important.

ZANCO JOURNAL OF PURE AND APPLIED SCIENCES

The IoT has become a trend in recent years, and the smart home system has achieved great interest... more The IoT has become a trend in recent years, and the smart home system has achieved great interest due to its need and requirement from consumers around the world. Smart home technology refers to the devices that are connected over the internet to monitor, support, and control the home in order to make our life easier. The revolution in technology has made homes more convenient, efficient, and even simpler. However, there are some challenges and obstacles that need to take into consideration when using a smart home system. Based on a comprehensive survey, this study aims to provide an overview of the critical security issues for IoT smart home systems and propose potential solutions to mitigate these risks by understanding vulnerabilities and applying security measures to ensure that the IoT system is more reliable and safe. The challenges and security issues highlighted with an emphasis on providing solutions, as well as smart home approaches and IoT layers.

Solid State Technology, 2020

Reporting Vehicle Accident recognition based on computer vision using deep learning techniques ha... more Reporting Vehicle Accident recognition based on computer vision using deep learning techniques has achieved reasonable results. Two problems regarding these techniques are computational complexity for the generated network, and accuracy of recognition. In this paper, a modified ResNet-based accident image recognition network is proposed. It is used as a feature extractor. Only the most important features will be selected using greedy stepwise. These selected features are used as input data for the KNN accident classifier. Two datasets have been used for this purpose. The results show that the proposed network has outperformed noticeable accuracy of about 96.9% in 29.7167 sec training compared to 93.7 % accuracy and 58.06449 Sec training for ResNet18. 93.9 % accuracy and 150.5573 Sec training for ResNet50 and 95.0% and 270.4034 Sec training for ResNet 101. The accident images are made understandable by adding descriptions using YOLOV2, which can be used for reporting the accident Key...

ZANCO JOURNAL OF PURE AND APPLIED SCIENCES, 2020

Video processing becomes one of the most popular and needed steps in machine leering. Todays, Cam... more Video processing becomes one of the most popular and needed steps in machine leering. Todays, Cameras are installed in many places for many reasons including government services. One of the most applications for this concern is traffic police services. One of the main problems of using videos in machine learning application is the duration of the video; which is consuming time, paperwork and space in processing. This leads to increase the computation cost through a high number of frames. This paper proposes an algorithm to optimize videos duration using a Gaussian mixture model (GMM) method for real accident video. The Histogram of Gradient (HoG) has been used to extract the features of the video frames, a scratch CNN has been designed and conducted on two common datasets; Stanford Dogs Dataset (SDD) and Vehicle Make and Model Recognition Dataset (VMMRdb) in addition to a local dataset that created for this research. The experimental work is done in two ways, the first is after applying GMM, the finding revealed that the number of frames in the dataset was decreased by nearly 51%. The second is comparing the accuracy and complexity of these datasets has been done. Whereas the experimental results of accuracy illustrated for the proposed CNN, 85% on the local dataset, 85% on SDD Dataset and 86% on VMMRdb Dataset. However, applying GoogleNet and AlexNet on the same datasets achieved 82%, 79%, 80%, 83%, 81%, 83% respectively.

Engineering Science and Technology, an International Journal, Apr 1, 2017

In this paper a hidden Markov model and harmony search algorithms are combined for writer indepen... more In this paper a hidden Markov model and harmony search algorithms are combined for writer independent online Kurdish character recognition. The Markov model is integrated as an intermediate group classifier instead of a main character classifier/recognizer as in most of previous works. Markov model is used to classify each group of characters, according to their forms, into smaller sub groups based on common directional feature vector. This process reduced the processing time taken by the later recognition stage. The small number of candidate characters are then processed by harmony search recognizer. The harmony search recognizer uses a dominant and common movement pattern as a fitness function. The objective function is used to minimize the matching score according to the fitness function criteria and according to the least score for each segmented group of characters. Then, the system displays the generated word which has the lowest score from the generated character combinations. The system was tested on a dataset of 4500 words structured with 21,234 characters in different positions or forms (isolated, start, middle and end). The system scored 93.52% successful recognition rate with an average of 500 ms. The system showed a high improvement in recognition rate when compared to similar systems that use HMM as its main recognizer.

Cihan University-Erbil scientific journal, 2017

Edge detection plays an important role in image processing, pattern recognition and computer visi... more Edge detection plays an important role in image processing, pattern recognition and computer vision applications. Most of edge detection schemes are based on finding maximum in the first derivative of the image function or zero crossings in the second derivative of the image function. Various methods of edge detection for color images, including techniques extended from monochrome edge detection as well as vector space methods are presented. This research presents a comparative study on different methods of edge detection of color images. The methods are based on vector space, color space and numerical methods. Seven different colored images are test in this research. Performance is analyzed depending on Mean Square Error (MSE). The experimental results show that applying vector value (Jacobian method)will create a thick and disconnected edge with all operators Sobel, Prewitt and Log. While the least square method produce edges that are much thicker but continuous. The best performance was found when using YCbCr luminance (Y) and chrominance (Cb and Cr) method, the edges are sharpened, continuous, and not thickness. They are similar with Sobel and Prewitt operators nonetheless with some missing edges while it is better with Log operator.

Journal of University of Human Development, 2016

E-health is the present communication structure in medicine especially in developed countries. To... more E-health is the present communication structure in medicine especially in developed countries. Toward enhancing the quality of care and reduce the health care delivery cost, cloud Computing technology has been adopted. In recent times services such as exchange and share medical data among staff and then to the patients are one the main reasons behind using this technology in e-health. Hence, using cloud computing in e-health has many challenges particularly when dealing with electronic healthcare records (EHR). Cloud computing is an agglomeration of technologies, operating systems, storage, networking, virtualisation, each fraught with inherent security issues. For example, browser-based attacks, denial of service attacks and network intrusion become carry-over risks into cloud computing. It differs from traditional computing paradigms as it is scalable which can be encapsulated as an abstract entity to provide different levels of services to the clients. In this paper, we identified the users of e-health such as doctors, nurses and family members and then their security requirements are identified. An application with five stages toward encryption and decryption process is designed. Since trust is a critical factor in cloud computing, this project will investigate the obstacles that cause this technology lose its credibility in certain clouds. To enhance user authentication process, two-tier mechanisms are used to identify the user's identity. While in confidentiality, it should be assured that information is shared only among authorised people or vendors by applying powerful cryptographic concepts. In this prototype application, the user will be able to protect his/her data and is responsible for providing a high level of security as long as these data are highly private and important.

Govarî Qeła, Apr 15, 2017

Indonesian Journal of Electrical Engineering and Computer Science, 2021

Classifying and finding type of individual vehicles within an accident image are considered diffi... more Classifying and finding type of individual vehicles within an accident image are considered difficult problems. This research concentrates on accurately classifying and recognizing vehicle accidents in question. The aim to provide a comparative analysis of vehicle accidents. A number of network topologies are tested to arrive at convincing results and a variety of matrices are used in the evaluation process to identify the best networks. The best two networks are used with faster recurrent convolution neural network (Faster RCNN) and you only look once (YOLO) to determine which network will identifiably detect the location and type of the vehicle. In addition, two datasets are used in this research. In consequence, experiment results show that MobileNetV2 and ResNet50 have accomplished higher accuracy compared to the rest of the models, with 89.11% and 88.45% for the GAI dataset as well as 88.72% and 89.69% for KAI dataset, respectively. The findings reveal that the ResNet50 base ne...

ZANCO Journal of Pure and Applied Sciences, 2016

Social media has been considered to have major changes to the strategies and tools used by busine... more Social media has been considered to have major changes to the strategies and tools used by business organizations to communicate with potential customers. Merely because it connects millions of user together in an easy and simple way. Although, there are many types of social media which are used to endorse business, Facebook has been noticeably used for this purpose by many corporations because it needs limited financial resources and little experience in the IT field. In Kurdistan, many businesses started to use Facebook to be the main tool for marketing and E-Commerce. Therefore, this paper inspects the role of Facebook pages in promoting Small and Medium Enterprises (SMEs) in Kurdistan. The paper compares 200 organizations that have business page with 200 organizations that do not have one. Thus, it explores if Facebook has achieved its role as target-oriented advertising campaigns or not. Moreover, these pages have been examined to conclude the factors that make some of these bu...

Proceeding of 1st International Conference on Information Technology, 2017

Engineering Science and Technology, an International Journal, 2017

In this paper a hidden Markov model and harmony search algorithms are combined for writer indepen... more In this paper a hidden Markov model and harmony search algorithms are combined for writer independent online Kurdish character recognition. The Markov model is integrated as an intermediate group classifier instead of a main character classifier/recognizer as in most of previous works. Markov model is used to classify each group of characters, according to their forms, into smaller sub groups based on common directional feature vector. This process reduced the processing time taken by the later recognition stage. The small number of candidate characters are then processed by harmony search recognizer. The harmony search recognizer uses a dominant and common movement pattern as a fitness function. The objective function is used to minimize the matching score according to the fitness function criteria and according to the least score for each segmented group of characters. Then, the system displays the generated word which has the lowest score from the generated character combinations. The system was tested on a dataset of 4500 words structured with 21,234 characters in different positions or forms (isolated, start, middle and end). The system scored 93.52% successful recognition rate with an average of 500 ms. The system showed a high improvement in recognition rate when compared to similar systems that use HMM as its main recognizer.

2nd International Conference of Cihan University-Erbil on Communication Engineering and Computer Science, 2017

Edge detection plays an important role in image processing, pattern recognition and computer visi... more Edge detection plays an important role in image processing, pattern recognition and computer vision applications. Most of edge detection schemes are based on finding maximum in the first derivative of the image function or zero crossings in the second derivative of the image function. Various methods of edge detection for color images, including techniques extended from monochrome edge detection as well as vector space methods are presented. This research presents a comparative study on different methods of edge detection of color images. The methods are based on vector space, color space and numerical methods. Seven different colored images are test in this research. Performance is analyzed depending on Mean Square Error (MSE). The experimental results show that applying vector value (Jacobian method)will create a thick and disconnected edge with all operators Sobel, Prewitt and Log. While the least square method produce edges that are much thicker but continuous. The best performance was found when using YCbCr luminance (Y) and chrominance (Cb and Cr) method, the edges are sharpened, continuous, and not thickness. They are similar with Sobel and Prewitt operators nonetheless with some missing edges while it is better with Log operator.

Journal of University of Human Development, 2016

E-health is the present communication structure in medicine especially in developed countries. To... more E-health is the present communication structure in medicine especially in developed countries. Toward enhancing the quality of care and reduce the health care delivery cost, cloud Computing technology has been adopted. In recent times services such as exchange and share medical data among staff and then to the patients are one the main reasons behind using this technology in e-health. Hence, using cloud computing in e-health has many challenges particularly when dealing with electronic healthcare records (EHR). Cloud computing is an agglomeration of technologies, operating systems, storage, networking, virtualisation, each fraught with inherent security issues. For example, browser-based attacks, denial of service attacks and network intrusion become carry-over risks into cloud computing. It differs from traditional computing paradigms as it is scalable which can be encapsulated as an abstract entity to provide different levels of services to the clients. In this paper, we identified the users of e-health such as doctors, nurses and family members and then their security requirements are identified. An application with five stages toward encryption and decryption process is designed. Since trust is a critical factor in cloud computing, this project will investigate the obstacles that cause this technology lose its credibility in certain clouds. To enhance user authentication process, two-tier mechanisms are used to identify the user's identity. While in confidentiality, it should be assured that information is shared only among authorised people or vendors by applying powerful cryptographic concepts. In this prototype application, the user will be able to protect his/her data and is responsible for providing a high level of security as long as these data are highly private and important.

ZANCO JOURNAL OF PURE AND APPLIED SCIENCES

The IoT has become a trend in recent years, and the smart home system has achieved great interest... more The IoT has become a trend in recent years, and the smart home system has achieved great interest due to its need and requirement from consumers around the world. Smart home technology refers to the devices that are connected over the internet to monitor, support, and control the home in order to make our life easier. The revolution in technology has made homes more convenient, efficient, and even simpler. However, there are some challenges and obstacles that need to take into consideration when using a smart home system. Based on a comprehensive survey, this study aims to provide an overview of the critical security issues for IoT smart home systems and propose potential solutions to mitigate these risks by understanding vulnerabilities and applying security measures to ensure that the IoT system is more reliable and safe. The challenges and security issues highlighted with an emphasis on providing solutions, as well as smart home approaches and IoT layers.

Solid State Technology, 2020

Reporting Vehicle Accident recognition based on computer vision using deep learning techniques ha... more Reporting Vehicle Accident recognition based on computer vision using deep learning techniques has achieved reasonable results. Two problems regarding these techniques are computational complexity for the generated network, and accuracy of recognition. In this paper, a modified ResNet-based accident image recognition network is proposed. It is used as a feature extractor. Only the most important features will be selected using greedy stepwise. These selected features are used as input data for the KNN accident classifier. Two datasets have been used for this purpose. The results show that the proposed network has outperformed noticeable accuracy of about 96.9% in 29.7167 sec training compared to 93.7 % accuracy and 58.06449 Sec training for ResNet18. 93.9 % accuracy and 150.5573 Sec training for ResNet50 and 95.0% and 270.4034 Sec training for ResNet 101. The accident images are made understandable by adding descriptions using YOLOV2, which can be used for reporting the accident Key...

ZANCO JOURNAL OF PURE AND APPLIED SCIENCES, 2020

Video processing becomes one of the most popular and needed steps in machine leering. Todays, Cam... more Video processing becomes one of the most popular and needed steps in machine leering. Todays, Cameras are installed in many places for many reasons including government services. One of the most applications for this concern is traffic police services. One of the main problems of using videos in machine learning application is the duration of the video; which is consuming time, paperwork and space in processing. This leads to increase the computation cost through a high number of frames. This paper proposes an algorithm to optimize videos duration using a Gaussian mixture model (GMM) method for real accident video. The Histogram of Gradient (HoG) has been used to extract the features of the video frames, a scratch CNN has been designed and conducted on two common datasets; Stanford Dogs Dataset (SDD) and Vehicle Make and Model Recognition Dataset (VMMRdb) in addition to a local dataset that created for this research. The experimental work is done in two ways, the first is after applying GMM, the finding revealed that the number of frames in the dataset was decreased by nearly 51%. The second is comparing the accuracy and complexity of these datasets has been done. Whereas the experimental results of accuracy illustrated for the proposed CNN, 85% on the local dataset, 85% on SDD Dataset and 86% on VMMRdb Dataset. However, applying GoogleNet and AlexNet on the same datasets achieved 82%, 79%, 80%, 83%, 81%, 83% respectively.