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Dr. Omaima AlMustawi Al-Allaf

IMAM Mohammed ben Saud University, Information system, Faculty Member

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Dr. Omaima N. A. AlMustawi AlAllaf is an Associate Professor in Computer Information Systems and Web Engineering, Information Systems Dept. Computers and Information College, Imam Muhammad Ibn Saud Islamic University, Kingdom of Saudi Arabia.
She received B.Sc. in Computer Science from Dept. of Computer Science, Faculty of Sciences, University of Mosul- Mosul- Iraq (1990-1994), and received M.Sc. in Dept. of Computer Science, Faculty of Computer & Mathematical Sciences, University of Mosul- Mosul- Iraq (1997-1999). She received PhD in Computer Information Systems from the Department of CIS, The Arab Academy for Banking and Financial Sciences- Amman- Jordan (2004-2008).
She worked as Teacher B in Applied Science University (Private)- Amman- Jordan from 14-9-2000 to 14-9-2004. During 2005-2009, she worked as a part time lecturer in the AABFS from 14-2-2005 to 14-2-2009. Finally, she worked as an Associate Professor at Faculty of Science and IT, AL-Zaytoonah University of Jordan- Amman-Jordan from 15 February 2009 to 30 August 2018.
Her research interests are in the fields of: Artificial Intelligence, Artificial Neural Networks, Image Processing, Genetic Algorithms, Web Engineering Process Models, Information Systems Analysis and Design, Project Management.
Dr.omaima Al-AllafAssociate ProfessorComputer information systems Faculty of science and information technology-Alzaytoonah university of Jordan-Amman - Jordan
Address: Imam Mohammad Bn Saud Islamic University, Riyadh -
Kingdom of Saudi Arabia

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Papers by Dr. Omaima AlMustawi Al-Allaf

ARTIFICIAL NEURAL NETWORKS MODELS AND ALGORITHMS FOR DIABETES DISEASE DIAGNOSIS: A REVIEW

International Journal of Advanced Computational Engineering and Networking, 2022

Diabetes disease can be considered as one of the major health problem over the world. Diabetes is... more Diabetes disease can be considered as one of the major health problem over the world. Diabetes is a condition in which sugar amount in the blood is higher than normal. There is an urgent need to develop efficient systems for diabetes diagnoses according to high health care costs for individuals and hospitals. Artificial Neural Networks (ANNs) were successfully used in image and signal processing systems. Many literature studies were considered ANN approaches and algorithms for classification of the diabetes diseases. The objective of this paper is to review and discuss the studies related to diabetes diagnosis using ANNs. Models, Algorithms, data sets, strengths and limitations of these studies were considered in this paper. Finally, recommendations were suggested for building ANNs methodologies for diabetes classification and diagnosis.

Pattern Recognition Neural Network for Improving the Performance of Iris Recognition System

This research employs pattern recognition neural networks for Iris recognition systems. The neura... more This research employs pattern recognition neural networks for Iris recognition systems. The neural networks have a seven- layers architecture consisting of one input layer, five hidden layers, and one output layer. Ten different ANN optimization training algorithms were used separately to train this model to get best results for the iris recognition system. Many experiments were conducted to compare the results of this model with the results of other ANN models to identify the model which improves the performance of the iris recognition system. The performances were compared using mean square error (MSE), PSNR and recognition rate to identify the best model and algorithm. The best results were obtained from the patternNet model especially when it was trained with TrainLM. The results of this model were compared also with the results of other researches to show its efficiency.

Review of Face Detection Systems Based Artificial Neural Networks Algorithms

Zenodo (CERN European Organization for Nuclear Research), Apr 30, 2021

Guidelines for Using MultiMedia in Web Page and User Interface Design

A multimedia system can include a combination of text, still images, graphics, video, and sound. ... more A multimedia system can include a combination of text, still images, graphics, video, and sound. The strength of multimedia lies in the integration of different media thus increasing the understanding of information. However, the success of multimedia depends on how the combinations of media are used, i.e. good design. This paper describes the guidelines for designing multimedia user interfaces. Most of the guidelines are based on independent research. The guidelines are to keep the user interface simple and consistent. Let the user control the interaction and give immediate, obvious feedback for every user action. Using of appropriate layout, grid, and animation. This paper also focuses on describing guidelines, principles, and factors for how to use multimedia in web page designing.

Eigen Faces and Principle Component Analysis for Face Recognition Systems: A Comparative Study

Face recognition has been largely used in biometric field as a security measure at air ports, pas... more Face recognition has been largely used in biometric field as a security measure at air ports, passport verif ication, criminals ' list verification, visa processing, and so on. Various literature studies suggested different approaches for face recognition systems and most of these studies have limitations with low performance rates. Eigenfaces and principle component analysis (PCA) can be considered as most important face recognition approaches in the literature. There is a need to develop algorithms and approaches that overcome these disadvantages and improve performance of face recognition systems. At the same time, there is a lack of literature studies which are related to face recognition systems based on EigenFaces and PCA. Therefore, this work includes a comparative study of literature researches related to Eigenfaces and PCA for face recognition systems. The main steps, strengths and limitations of each study will be discussed. Many recommendations were suggested in this...

Improving the Performance of Backpropagation Neural Network algorithm for Image Compression/Decompression System

Abstract: Problem statement: The problem inherent to any digital image is the large amount of ban... more Abstract: Problem statement: The problem inherent to any digital image is the large amount of bandwidth required for transmission or storage. This has driven the research area of image compression to develop algorithms that compress images to lower data rates with better quality. Artificial neural networks are becoming attractive in image processing where high computational performance and parallel architectures are required. Approach: In this research, a three layered Backpropagation Neural Network (BPNN) was designed for building image compression/decompression system. The Backpropagation neural network algorithm (BP) was used for training the designed BPNN. Many techniques were used to speed up and improve this algorithm by using different BPNN architecture and different values of learning rate and momentum variables. Results: Experiments had been achieved, the results obtained, such as Compression Ratio (CR) and peak signal to noise ratio (PSNR) are compared with the performance...

www.ijacsa.thesai.org Hiding an Image inside another Image using

Abstract—A new algorithm is presented for hiding a secret image in the least significant bits of ... more Abstract—A new algorithm is presented for hiding a secret image in the least significant bits of a cover image. The images used may be color or grayscale images. The number of bits used for hiding changes according to pixel neighborhood information of the cover image. The exclusive-or (XOR) of a pixel’s neighbors is used to determine the smoothness of the neighborhood. A higher XOR value indicates less smoothness and leads to using more bits for hiding without causing noticeable degradation to the cover image. Experimental results are presented to show that the algorithm generally hides images without significant changes to the cover image, where the results are sensitive to the smoothness of the cover image. Keywords—image steganography; information hiding; LSB method I.

Artificial Neural Networks for Iris Recognition System: Comparisons between Different Models, Architectures and Algorithms 1

In this research, an iris recognition system was suggested based on five Artificial Neural Networ... more In this research, an iris recognition system was suggested based on five Artificial Neural Network (ANN) models separately: feed forward (FFBPNN), cascade forward (CFBPNN), function fitting (FitNet), pattern recognition (PatternNet) and learning vector quantization (LVQNet). For each ANN model, two architectures were constructed separately; 4 layers and 7 layers, each with different numbers of hidden layer units (5, 10 and 15). Ten different ANN optimization training algorithms (LM, BFG, BR, CGF, GD, GDM, GDA, GDX, OSS and RP) were used to train each model separately. Many experiments were conducted for each one of the five models. Each model used two different architectures, a different number of hidden layer neurons and ten different training algorithms. The performance results of the models were compared according to mean square error to identify the best ANN model. The results showed that the PatternNet model was the best model used. Finally, comparisons between the ten training...

$Research paper thumbnail of ParFor and co-distributor parallel approaches for implementing fractal image compression based genetic algorithm$

ParFor and co-distributor parallel approaches for implementing fractal image compression based genetic algorithm

2014 Science and Information Conference, 2014

This research focuses on using Two MATLAB parallel approaches (ParFor and Co-distributor) to impl... more This research focuses on using Two MATLAB parallel approaches (ParFor and Co-distributor) to implement fractal image compression based on genetic algorithm (GA) to decrease processing time with maintaining quality of the reconstructed images. Many experiments based on these two approaches (ParFor and Co-distributor) were conducted with comparisons. The research results showed that the compression computation time can be reduced when decreasing the GA population size and increasing number of workers in parallel computing. Best results obtained from implementing Co-distributor approach with 6 workers and 150 population size. The execution speed for Co-distributor reached 3s with PSNR equal 34.89db and CR equal 90.65%.

Improving the Performance of Particle Swarm Optimization for Iris Recognition System Using Independent Component Analysis

Recently, iris recognition had been gained growing interest from researchers because of its high ... more Recently, iris recognition had been gained growing interest from researchers because of its high accuracy against other person identification techniques. This work presents an iris recognition system based on particle swarm optimization (PSO) and Independent Component Analysis (ICA) as feature extraction algorithm. Many experiments were conducted using different: swarm size (20, 40 and 80), PSO iterations (100 and 200) and ICA feature vector length (64, 128, 256 and 512). The results showed that: the best performance of the iris recognition system (high PSNR, high recognition rate and lower MSE) will be increased when increasing the ICA feature vector length to 512, increasing the swarm size to 80 and decreasing the number of iterations to 100. Best obtained value of recognition rate is 98%, best PSNR value is 38 and lower MSE value is 0.0011. The suggested iris recognition system has the ability to recognize un trained iris images but with lower performance.

Nonlinear Autoregressive Neural Network for Estimation Soil Temperature: A Comparison of Different Optimization Neural Network Algorithms

The objective of this paper is to develop an Artificial Neural Network (ANN) model to estimate so... more The objective of this paper is to develop an Artificial Neural Network (ANN) model to estimate soil temperature for any day. We used air average temperature, sunshine, radiation and soil temperature for meteorological data between years (1980 and 1984) at Nineveh/Iraq Meteorological Station. In this research, three ANN models with their associated training algorithms (Backpropagation neural network (BPNN), Cascade-Forward and Nonlinear Autoregressive (NARX)) were used for estimating soil temperatures at different depths of 5, 10, 20, 50 and 100cm within the time 9, 12 and 15 respectively. The performance of the three models with their training algorithms were compared with the measured soil temperature values to identify the best fit ANN model for soil temperature forecasting. The results showed that the NARX model is the best model. Finally, a comparison between five optimization ANN training algorithms was adopted to train NARX ANN model to identify best fit optimization algorithm...

Hybrid Web Engineering Process Model for the Development of Large Scale Web Applications

Many web development models had been proposed in the literature and there are few studies related... more Many web development models had been proposed in the literature and there are few studies related to proposing models for developing large web applications. It is important to construct a model that lead to large web applications development with minimum likelihood of failure. A Hybrid web engineering process model for large web development enterprises has been proposed in this research. This model focuses on overall development process phases and consists of many activities: division of large web application into many small sub applications; division of large number of developers into many sub teams; identify a management team to control the development process; Stakeholders’ and customers’ inclusion and feedback during development process; requirement analysis and management; adopting the Spiral model by management team; adopting the Throwaway Prototype, XP agile method, Web Engineering process model by each sub team; conducting CMMI levels key process areas; conducting web engine...

The Adoption of Agile Processes in Large Web Development Enterprises: A Survey in Jordan

Int. J. Web Appl., 2010

Agile processes can be applied to any software process for effective response to changing require... more Agile processes can be applied to any software process for effective response to changing requirements during the development process and effective communication among stakeholders. There is lack of surveys related to agile processes in large web development enterprises in the world and the current state of adoption of agile processes by large enterprises is still unknown. A survey has been conducted in this research based on questionnaire and interviews in five large Jordanian enterprises to examine the process models adopted by these enterprises, the extent to which these enterprises are using agile processes, and finally to examine the problems associated with large web applications’ development. The results of this survey showed that there is a weakness in adoption of agile processes in large Jordanian enterprises and the Extreme Programming (XP) is well known agile process by the developers working in these enterprises. According to survey results, we suggested recommendations ...

The Usage of Capability Maturity Model Integration and Web Engineering Practices in Large Web Development Enterprises: An Empirical Study in Jordan

There is a lack of surveys in large web development enterprises to determine: the level of adopti... more There is a lack of surveys in large web development enterprises to determine: the level of adoption of web engineering practices and capability maturity model integration (CMMI) in these enterprises. Therefore , we need a survey in large enterprises to improve their web development processes and overcome their problems during the development process. We focus in this research on answering four questions: What are the characteristics of developers working in la rge enterprises? What are the properties of web development processes adopted by large enterprises? What are the symptoms that large enterprises face during web development? And finally, what are levels of usage of CMMI and web engineering practices by these enterprises. A survey has been conducted in t his research based on questionnaires in large enter prises in Jordan to answer the above questions. According to survey results, we noticed that: two of web engineering practices such as tools and technology, and standards and ...

Impacts of Information Technology on Organizational Structures

Organizational structure is the formal pattern of how people and jobs are grouped in an organizat... more Organizational structure is the formal pattern of how people and jobs are grouped in an organization where the organizational design is the decisions and actions that result in organizational structure. The purpose of information technology is to monitor, process, and disseminate information to assist in managing, decision making, and controlling the organization. The implementation of information technology produced change in an organization and its structure because the relationship between information technology and organizational structures is dynamic. In this paper, the impact of information technology on the organizational structure and its performance will be discussed and analyzed.

Swarm Optimization Algorithm vs . Genetic Algorithm for Image Watermarking Based Discrete Wavelet Transform

Over communication networks, images can be easily copied and distributed in an illegal way. The c... more Over communication networks, images can be easily copied and distributed in an illegal way. The copyright protection for authors and owners is necessary. Therefore, the digital watermarking techniques play an important role as a valid solution for authority problems. Digital image watermarking techniques are used to hide watermarks into images to achieve copyright protection and prevent its illegal copy. Watermarks need to be robust to attacks and maintain data quality. Therefore, we discussed in this paper two approaches for image watermarking, first is based on Particle Swarm Optimization (PSO) and the second approach is based on Genetic Algorithm (GA). Discrete wavelet transformation (DWT) is used with the two approaches separately for embedding process to cover image transformation. Each of PSO and GA is based on co-relation coefficient to detect the high energy coefficient watermark bit in the original image and then hide the watermark in original image. Many experiments were c...

Cascade-Forward vs. Function Fitting Neural Network for Improving Image Quality and Learning Time in Image Compression System

Abstract— The backpropagation neural network algorithm (BP) was used largely in image and signal... more Abstract— The backpropagation neural network algorithm (BP) was used largely in image and signal processing. The BP requires long time to train the BPNN with small error. Therefore, in this research, three Artificial Neural Networks models (ANNs) were constructed. Three algorithms: FeedForwardNet, CascadeForwardNet and FitNet were adopted to train the three constructed ANNs models separately. Each one of constructed models consists of input layer to input the original image, hidden layer to produce the compressed image and finally output layer for decompressed image. The training and testing performance of the constructed models with different architecture were compared to identify the model with best compression ratio (CR) and Peak to Signal to Noise Ratio (PSNR). From experiments, we noted that the better results are obtained when we used the FitNet ANN model. According to results, the performance of constructed FitNet ANN for image compression can be increased by changing the nu...

Particle Swarm Optimization Algorithm vs. Genetic Algorithm for Image Watermarking Based Discrete Wavelet Transform

Pattern Recognition Neural Network for Improving the Performance of Iris Recognition System

( IJSER.org ) - International Journal of Scientific & Engineering Research, Jun 1, 2013

This research employs pattern recognition neural networks for Iris recognition systems. The neura... more This research employs pattern recognition neural networks for Iris recognition systems. The neural networks have a seven- layers architecture consisting of one input layer, five hidden layers, and one output layer. Ten different ANN optimization training algorithms were used separately to train this model to get best results for the iris recognition system. Many experiments were conducted to compare the results of this model with the results of other ANN models to identify the model which improves the performance of the iris recognition system. The performances were compared using mean square error (MSE), PSNR and recognition rate to identify the best model and algorithm. The best results were obtained from the patternNet model especially when it was trained with TrainLM. The results of this model were compared also with the results of other researches to show its efficiency.

Cryptography Based Authentication Methods

ARTIFICIAL NEURAL NETWORKS MODELS AND ALGORITHMS FOR DIABETES DISEASE DIAGNOSIS: A REVIEW

International Journal of Advanced Computational Engineering and Networking, 2022

Diabetes disease can be considered as one of the major health problem over the world. Diabetes is... more Diabetes disease can be considered as one of the major health problem over the world. Diabetes is a condition in which sugar amount in the blood is higher than normal. There is an urgent need to develop efficient systems for diabetes diagnoses according to high health care costs for individuals and hospitals. Artificial Neural Networks (ANNs) were successfully used in image and signal processing systems. Many literature studies were considered ANN approaches and algorithms for classification of the diabetes diseases. The objective of this paper is to review and discuss the studies related to diabetes diagnosis using ANNs. Models, Algorithms, data sets, strengths and limitations of these studies were considered in this paper. Finally, recommendations were suggested for building ANNs methodologies for diabetes classification and diagnosis.

Pattern Recognition Neural Network for Improving the Performance of Iris Recognition System

This research employs pattern recognition neural networks for Iris recognition systems. The neura... more This research employs pattern recognition neural networks for Iris recognition systems. The neural networks have a seven- layers architecture consisting of one input layer, five hidden layers, and one output layer. Ten different ANN optimization training algorithms were used separately to train this model to get best results for the iris recognition system. Many experiments were conducted to compare the results of this model with the results of other ANN models to identify the model which improves the performance of the iris recognition system. The performances were compared using mean square error (MSE), PSNR and recognition rate to identify the best model and algorithm. The best results were obtained from the patternNet model especially when it was trained with TrainLM. The results of this model were compared also with the results of other researches to show its efficiency.

Review of Face Detection Systems Based Artificial Neural Networks Algorithms

Zenodo (CERN European Organization for Nuclear Research), Apr 30, 2021

Guidelines for Using MultiMedia in Web Page and User Interface Design

A multimedia system can include a combination of text, still images, graphics, video, and sound. ... more A multimedia system can include a combination of text, still images, graphics, video, and sound. The strength of multimedia lies in the integration of different media thus increasing the understanding of information. However, the success of multimedia depends on how the combinations of media are used, i.e. good design. This paper describes the guidelines for designing multimedia user interfaces. Most of the guidelines are based on independent research. The guidelines are to keep the user interface simple and consistent. Let the user control the interaction and give immediate, obvious feedback for every user action. Using of appropriate layout, grid, and animation. This paper also focuses on describing guidelines, principles, and factors for how to use multimedia in web page designing.

Eigen Faces and Principle Component Analysis for Face Recognition Systems: A Comparative Study

Face recognition has been largely used in biometric field as a security measure at air ports, pas... more Face recognition has been largely used in biometric field as a security measure at air ports, passport verif ication, criminals ' list verification, visa processing, and so on. Various literature studies suggested different approaches for face recognition systems and most of these studies have limitations with low performance rates. Eigenfaces and principle component analysis (PCA) can be considered as most important face recognition approaches in the literature. There is a need to develop algorithms and approaches that overcome these disadvantages and improve performance of face recognition systems. At the same time, there is a lack of literature studies which are related to face recognition systems based on EigenFaces and PCA. Therefore, this work includes a comparative study of literature researches related to Eigenfaces and PCA for face recognition systems. The main steps, strengths and limitations of each study will be discussed. Many recommendations were suggested in this...

Improving the Performance of Backpropagation Neural Network algorithm for Image Compression/Decompression System

Abstract: Problem statement: The problem inherent to any digital image is the large amount of ban... more Abstract: Problem statement: The problem inherent to any digital image is the large amount of bandwidth required for transmission or storage. This has driven the research area of image compression to develop algorithms that compress images to lower data rates with better quality. Artificial neural networks are becoming attractive in image processing where high computational performance and parallel architectures are required. Approach: In this research, a three layered Backpropagation Neural Network (BPNN) was designed for building image compression/decompression system. The Backpropagation neural network algorithm (BP) was used for training the designed BPNN. Many techniques were used to speed up and improve this algorithm by using different BPNN architecture and different values of learning rate and momentum variables. Results: Experiments had been achieved, the results obtained, such as Compression Ratio (CR) and peak signal to noise ratio (PSNR) are compared with the performance...

www.ijacsa.thesai.org Hiding an Image inside another Image using

Abstract—A new algorithm is presented for hiding a secret image in the least significant bits of ... more Abstract—A new algorithm is presented for hiding a secret image in the least significant bits of a cover image. The images used may be color or grayscale images. The number of bits used for hiding changes according to pixel neighborhood information of the cover image. The exclusive-or (XOR) of a pixel’s neighbors is used to determine the smoothness of the neighborhood. A higher XOR value indicates less smoothness and leads to using more bits for hiding without causing noticeable degradation to the cover image. Experimental results are presented to show that the algorithm generally hides images without significant changes to the cover image, where the results are sensitive to the smoothness of the cover image. Keywords—image steganography; information hiding; LSB method I.

Artificial Neural Networks for Iris Recognition System: Comparisons between Different Models, Architectures and Algorithms 1

In this research, an iris recognition system was suggested based on five Artificial Neural Networ... more In this research, an iris recognition system was suggested based on five Artificial Neural Network (ANN) models separately: feed forward (FFBPNN), cascade forward (CFBPNN), function fitting (FitNet), pattern recognition (PatternNet) and learning vector quantization (LVQNet). For each ANN model, two architectures were constructed separately; 4 layers and 7 layers, each with different numbers of hidden layer units (5, 10 and 15). Ten different ANN optimization training algorithms (LM, BFG, BR, CGF, GD, GDM, GDA, GDX, OSS and RP) were used to train each model separately. Many experiments were conducted for each one of the five models. Each model used two different architectures, a different number of hidden layer neurons and ten different training algorithms. The performance results of the models were compared according to mean square error to identify the best ANN model. The results showed that the PatternNet model was the best model used. Finally, comparisons between the ten training...

$Research paper thumbnail of ParFor and co-distributor parallel approaches for implementing fractal image compression based genetic algorithm$

ParFor and co-distributor parallel approaches for implementing fractal image compression based genetic algorithm

2014 Science and Information Conference, 2014

This research focuses on using Two MATLAB parallel approaches (ParFor and Co-distributor) to impl... more This research focuses on using Two MATLAB parallel approaches (ParFor and Co-distributor) to implement fractal image compression based on genetic algorithm (GA) to decrease processing time with maintaining quality of the reconstructed images. Many experiments based on these two approaches (ParFor and Co-distributor) were conducted with comparisons. The research results showed that the compression computation time can be reduced when decreasing the GA population size and increasing number of workers in parallel computing. Best results obtained from implementing Co-distributor approach with 6 workers and 150 population size. The execution speed for Co-distributor reached 3s with PSNR equal 34.89db and CR equal 90.65%.

Improving the Performance of Particle Swarm Optimization for Iris Recognition System Using Independent Component Analysis

Recently, iris recognition had been gained growing interest from researchers because of its high ... more Recently, iris recognition had been gained growing interest from researchers because of its high accuracy against other person identification techniques. This work presents an iris recognition system based on particle swarm optimization (PSO) and Independent Component Analysis (ICA) as feature extraction algorithm. Many experiments were conducted using different: swarm size (20, 40 and 80), PSO iterations (100 and 200) and ICA feature vector length (64, 128, 256 and 512). The results showed that: the best performance of the iris recognition system (high PSNR, high recognition rate and lower MSE) will be increased when increasing the ICA feature vector length to 512, increasing the swarm size to 80 and decreasing the number of iterations to 100. Best obtained value of recognition rate is 98%, best PSNR value is 38 and lower MSE value is 0.0011. The suggested iris recognition system has the ability to recognize un trained iris images but with lower performance.

Nonlinear Autoregressive Neural Network for Estimation Soil Temperature: A Comparison of Different Optimization Neural Network Algorithms

The objective of this paper is to develop an Artificial Neural Network (ANN) model to estimate so... more The objective of this paper is to develop an Artificial Neural Network (ANN) model to estimate soil temperature for any day. We used air average temperature, sunshine, radiation and soil temperature for meteorological data between years (1980 and 1984) at Nineveh/Iraq Meteorological Station. In this research, three ANN models with their associated training algorithms (Backpropagation neural network (BPNN), Cascade-Forward and Nonlinear Autoregressive (NARX)) were used for estimating soil temperatures at different depths of 5, 10, 20, 50 and 100cm within the time 9, 12 and 15 respectively. The performance of the three models with their training algorithms were compared with the measured soil temperature values to identify the best fit ANN model for soil temperature forecasting. The results showed that the NARX model is the best model. Finally, a comparison between five optimization ANN training algorithms was adopted to train NARX ANN model to identify best fit optimization algorithm...

Hybrid Web Engineering Process Model for the Development of Large Scale Web Applications

Many web development models had been proposed in the literature and there are few studies related... more Many web development models had been proposed in the literature and there are few studies related to proposing models for developing large web applications. It is important to construct a model that lead to large web applications development with minimum likelihood of failure. A Hybrid web engineering process model for large web development enterprises has been proposed in this research. This model focuses on overall development process phases and consists of many activities: division of large web application into many small sub applications; division of large number of developers into many sub teams; identify a management team to control the development process; Stakeholders’ and customers’ inclusion and feedback during development process; requirement analysis and management; adopting the Spiral model by management team; adopting the Throwaway Prototype, XP agile method, Web Engineering process model by each sub team; conducting CMMI levels key process areas; conducting web engine...

The Adoption of Agile Processes in Large Web Development Enterprises: A Survey in Jordan

Int. J. Web Appl., 2010

Agile processes can be applied to any software process for effective response to changing require... more Agile processes can be applied to any software process for effective response to changing requirements during the development process and effective communication among stakeholders. There is lack of surveys related to agile processes in large web development enterprises in the world and the current state of adoption of agile processes by large enterprises is still unknown. A survey has been conducted in this research based on questionnaire and interviews in five large Jordanian enterprises to examine the process models adopted by these enterprises, the extent to which these enterprises are using agile processes, and finally to examine the problems associated with large web applications’ development. The results of this survey showed that there is a weakness in adoption of agile processes in large Jordanian enterprises and the Extreme Programming (XP) is well known agile process by the developers working in these enterprises. According to survey results, we suggested recommendations ...

The Usage of Capability Maturity Model Integration and Web Engineering Practices in Large Web Development Enterprises: An Empirical Study in Jordan

There is a lack of surveys in large web development enterprises to determine: the level of adopti... more There is a lack of surveys in large web development enterprises to determine: the level of adoption of web engineering practices and capability maturity model integration (CMMI) in these enterprises. Therefore , we need a survey in large enterprises to improve their web development processes and overcome their problems during the development process. We focus in this research on answering four questions: What are the characteristics of developers working in la rge enterprises? What are the properties of web development processes adopted by large enterprises? What are the symptoms that large enterprises face during web development? And finally, what are levels of usage of CMMI and web engineering practices by these enterprises. A survey has been conducted in t his research based on questionnaires in large enter prises in Jordan to answer the above questions. According to survey results, we noticed that: two of web engineering practices such as tools and technology, and standards and ...

Impacts of Information Technology on Organizational Structures

Organizational structure is the formal pattern of how people and jobs are grouped in an organizat... more Organizational structure is the formal pattern of how people and jobs are grouped in an organization where the organizational design is the decisions and actions that result in organizational structure. The purpose of information technology is to monitor, process, and disseminate information to assist in managing, decision making, and controlling the organization. The implementation of information technology produced change in an organization and its structure because the relationship between information technology and organizational structures is dynamic. In this paper, the impact of information technology on the organizational structure and its performance will be discussed and analyzed.

Swarm Optimization Algorithm vs . Genetic Algorithm for Image Watermarking Based Discrete Wavelet Transform

Over communication networks, images can be easily copied and distributed in an illegal way. The c... more Over communication networks, images can be easily copied and distributed in an illegal way. The copyright protection for authors and owners is necessary. Therefore, the digital watermarking techniques play an important role as a valid solution for authority problems. Digital image watermarking techniques are used to hide watermarks into images to achieve copyright protection and prevent its illegal copy. Watermarks need to be robust to attacks and maintain data quality. Therefore, we discussed in this paper two approaches for image watermarking, first is based on Particle Swarm Optimization (PSO) and the second approach is based on Genetic Algorithm (GA). Discrete wavelet transformation (DWT) is used with the two approaches separately for embedding process to cover image transformation. Each of PSO and GA is based on co-relation coefficient to detect the high energy coefficient watermark bit in the original image and then hide the watermark in original image. Many experiments were c...

Cascade-Forward vs. Function Fitting Neural Network for Improving Image Quality and Learning Time in Image Compression System

Abstract— The backpropagation neural network algorithm (BP) was used largely in image and signal... more Abstract— The backpropagation neural network algorithm (BP) was used largely in image and signal processing. The BP requires long time to train the BPNN with small error. Therefore, in this research, three Artificial Neural Networks models (ANNs) were constructed. Three algorithms: FeedForwardNet, CascadeForwardNet and FitNet were adopted to train the three constructed ANNs models separately. Each one of constructed models consists of input layer to input the original image, hidden layer to produce the compressed image and finally output layer for decompressed image. The training and testing performance of the constructed models with different architecture were compared to identify the model with best compression ratio (CR) and Peak to Signal to Noise Ratio (PSNR). From experiments, we noted that the better results are obtained when we used the FitNet ANN model. According to results, the performance of constructed FitNet ANN for image compression can be increased by changing the nu...

Particle Swarm Optimization Algorithm vs. Genetic Algorithm for Image Watermarking Based Discrete Wavelet Transform

Pattern Recognition Neural Network for Improving the Performance of Iris Recognition System

( IJSER.org ) - International Journal of Scientific & Engineering Research, Jun 1, 2013

This research employs pattern recognition neural networks for Iris recognition systems. The neura... more This research employs pattern recognition neural networks for Iris recognition systems. The neural networks have a seven- layers architecture consisting of one input layer, five hidden layers, and one output layer. Ten different ANN optimization training algorithms were used separately to train this model to get best results for the iris recognition system. Many experiments were conducted to compare the results of this model with the results of other ANN models to identify the model which improves the performance of the iris recognition system. The performances were compared using mean square error (MSE), PSNR and recognition rate to identify the best model and algorithm. The best results were obtained from the patternNet model especially when it was trained with TrainLM. The results of this model were compared also with the results of other researches to show its efficiency.

Cryptography Based Authentication Methods