International Journal of Advanced Computer Science and Applications, 2013
Visual inspection by a human operator has been mostly used up till now to detect cracks in sewer ... more Visual inspection by a human operator has been mostly used up till now to detect cracks in sewer pipes. In this paper, we address the problem of automated detection of such cracks. We propose a model which detects crack fractures that may occur in weak areas of a network of pipes. The model also predicts the level of dangerousness of the detected cracks among five crack levels. We evaluate our results by comparing them with those obtained by using the Canny algorithm. The accuracy percentage of this model exceeds 90% and outperforms other approaches.
International Journal of Computer Applications, 2014
Sewer overflows may cause communities to be vulnerable to various health problems and other monet... more Sewer overflows may cause communities to be vulnerable to various health problems and other monetary losses. This puts a lot of burden on responsible to minimize end user complaints. Therefore, crack prediction would be helpful to facilitate decision makers to control sewer overflow problems and prioritize inspection and rehabilitation needs .The accurate prediction of current underground sewer pipe cracks must be done before any pipe crashing with enough period of time to enable rehabilitation and replacement intervals, appropriate remedial methods and preventing sewer pipes crashing. Unfortunately, traditional technologies and models approaches have been limited to predict the development of sewer pipe cracks. In this paper, we address the problem of crack prediction of such cracks. This paper provides a proposed model which predict crack and cracks developments in any period of time that may occur in weak areas of a network of pipes.. We evaluate our results by comparing them with those obtained by many other models. The accuracy percentage of this model exceeds 90% and outperforms other approaches.
Abstract: The increasing use of cloud computing resources have placed a large workload on the dat... more Abstract: The increasing use of cloud computing resources have placed a large workload on the data centers. Solving the load balancing problem among all virtual machines (VMs) increases performance, throughput and decreases the request delay. In this paper, Roulette Wheel Selection algorithm is applied on all VMs for balancing the load in the cloud computing environment based on virtual machine weight. In our experiments, measures such as response time, data center request servicing time and processing cost are used. Simulation results show that Roulette Wheel Selection algorithm reduces data transfer cost when compared to three other load balancing algorithms. Keywords: Cloud computing, Roulette Wheel Selection, VM load balancer.
International Journal of Advanced Computer Science and Applications, 2012
Aspect mining is a reverse engineering process that aims at mining legacy systems to discover cro... more Aspect mining is a reverse engineering process that aims at mining legacy systems to discover crosscutting concerns to be refactored into aspects. This process improves system reusability and maintainability. But, locating crosscutting concerns in legacy systems manually is very difficult and causes many errors. So, there is a need for automated techniques that can discover crosscutting concerns in source code. Aspect mining approaches are automated techniques that vary according to the type of crosscutting concerns symptoms they search for. Code duplication is one of such symptoms which risks software maintenance and evolution. So, many code clone detection techniques have been proposed to find this duplicated code in legacy systems. In this paper, we present a clone detection technique to extract exact clones from object-oriented source code using Differential File Comparison Algorithm (DIFF) to improve system reusability and maintainability which is a major objective of aspect mining.
International Journal of Computer Applications, 2014
In this research, an automatic multiple choice question generation system for evaluating semantic... more In this research, an automatic multiple choice question generation system for evaluating semantic role labels and named entities is proposed. The selection of the informative sentence and the keyword to be asked about are based on the semantic labels and named entities that exist in the question sentence. The research introduces a novel method for the distractor selection process. Distractors are chosen based on a string similarity measure between sentences in the data set. Eight algorithms of string similarity measures are used in this research. The system is tested using a set of sentences extracted from the data set for question answering. Experimental results prove that the semantic role labeling and named entity recognition approaches can be used for keyword selection. String similarity measures have been used in generating the distractors in the process of automatic multiple choice questions generation. Combining the similarity measures of some algorithms led to enhancing the results.
International Journal of Computer Applications, 2014
Question Generation (QG) is an important element of learning environments, information seeking sy... more Question Generation (QG) is an important element of learning environments, information seeking systems, help systems, and other applications. There are a number of distinct research subfields which are concerned with the Automatic Question Generation (AQG) Systems. This research tries to have a wide look on existing automatic question generation systems, and some trials of overcoming its difficulties from different points of views.
International Journal of Computer Science and Information Technology, 2011
As the amount of internet documents has been growing, document clustering has become practically ... more As the amount of internet documents has been growing, document clustering has become practically important. This has led the interest in developing document clustering algorithms. Exploiting parallelism plays an important role in achieving fast and high quality clustering. In this ...
Gene therapy is an exciting field that has attracted much interest since the first submission of ... more Gene therapy is an exciting field that has attracted much interest since the first submission of clinical trials. Preliminary results were very encouraging and prompted many investigators and researchers. However, the ability of stem cells to differentiate into specific cell types holds immense potential for therapeutic use in gene therapy. Realization of this potential depends on efficient and optimized protocols for genetic manipulation of stem cells. It is widely recognized that gain/loss of function approaches using gene therapy are essential for understanding specific genes functions, and such approaches would be particularly valuable in studies involving stem cells. A significant complexity is that the development stage of vectors and their variety are still not sufficient to be efficiently applied in stem cell therapy. The development of scalable computer systems constitutes one step toward understanding dynamics of its potential. Therefore, the primary goal of this work is to develop a computer model that will support investigations of virus’ behavior and organization on regenerative tissues including genetically modified stem cells. Different simulation scenarios were implemented, and their results were encouraging compared to ex vivo experiments, where the error rate lies in the range of acceptable values in this domain of application.
International Journal of Advanced Computer Science and Applications, 2013
Visual inspection by a human operator has been mostly used up till now to detect cracks in sewer ... more Visual inspection by a human operator has been mostly used up till now to detect cracks in sewer pipes. In this paper, we address the problem of automated detection of such cracks. We propose a model which detects crack fractures that may occur in weak areas of a network of pipes. The model also predicts the level of dangerousness of the detected cracks among five crack levels. We evaluate our results by comparing them with those obtained by using the Canny algorithm. The accuracy percentage of this model exceeds 90% and outperforms other approaches.
International Journal of Computer Applications, 2014
Sewer overflows may cause communities to be vulnerable to various health problems and other monet... more Sewer overflows may cause communities to be vulnerable to various health problems and other monetary losses. This puts a lot of burden on responsible to minimize end user complaints. Therefore, crack prediction would be helpful to facilitate decision makers to control sewer overflow problems and prioritize inspection and rehabilitation needs .The accurate prediction of current underground sewer pipe cracks must be done before any pipe crashing with enough period of time to enable rehabilitation and replacement intervals, appropriate remedial methods and preventing sewer pipes crashing. Unfortunately, traditional technologies and models approaches have been limited to predict the development of sewer pipe cracks. In this paper, we address the problem of crack prediction of such cracks. This paper provides a proposed model which predict crack and cracks developments in any period of time that may occur in weak areas of a network of pipes.. We evaluate our results by comparing them with those obtained by many other models. The accuracy percentage of this model exceeds 90% and outperforms other approaches.
Abstract: The increasing use of cloud computing resources have placed a large workload on the dat... more Abstract: The increasing use of cloud computing resources have placed a large workload on the data centers. Solving the load balancing problem among all virtual machines (VMs) increases performance, throughput and decreases the request delay. In this paper, Roulette Wheel Selection algorithm is applied on all VMs for balancing the load in the cloud computing environment based on virtual machine weight. In our experiments, measures such as response time, data center request servicing time and processing cost are used. Simulation results show that Roulette Wheel Selection algorithm reduces data transfer cost when compared to three other load balancing algorithms. Keywords: Cloud computing, Roulette Wheel Selection, VM load balancer.
International Journal of Advanced Computer Science and Applications, 2012
Aspect mining is a reverse engineering process that aims at mining legacy systems to discover cro... more Aspect mining is a reverse engineering process that aims at mining legacy systems to discover crosscutting concerns to be refactored into aspects. This process improves system reusability and maintainability. But, locating crosscutting concerns in legacy systems manually is very difficult and causes many errors. So, there is a need for automated techniques that can discover crosscutting concerns in source code. Aspect mining approaches are automated techniques that vary according to the type of crosscutting concerns symptoms they search for. Code duplication is one of such symptoms which risks software maintenance and evolution. So, many code clone detection techniques have been proposed to find this duplicated code in legacy systems. In this paper, we present a clone detection technique to extract exact clones from object-oriented source code using Differential File Comparison Algorithm (DIFF) to improve system reusability and maintainability which is a major objective of aspect mining.
International Journal of Computer Applications, 2014
In this research, an automatic multiple choice question generation system for evaluating semantic... more In this research, an automatic multiple choice question generation system for evaluating semantic role labels and named entities is proposed. The selection of the informative sentence and the keyword to be asked about are based on the semantic labels and named entities that exist in the question sentence. The research introduces a novel method for the distractor selection process. Distractors are chosen based on a string similarity measure between sentences in the data set. Eight algorithms of string similarity measures are used in this research. The system is tested using a set of sentences extracted from the data set for question answering. Experimental results prove that the semantic role labeling and named entity recognition approaches can be used for keyword selection. String similarity measures have been used in generating the distractors in the process of automatic multiple choice questions generation. Combining the similarity measures of some algorithms led to enhancing the results.
International Journal of Computer Applications, 2014
Question Generation (QG) is an important element of learning environments, information seeking sy... more Question Generation (QG) is an important element of learning environments, information seeking systems, help systems, and other applications. There are a number of distinct research subfields which are concerned with the Automatic Question Generation (AQG) Systems. This research tries to have a wide look on existing automatic question generation systems, and some trials of overcoming its difficulties from different points of views.
International Journal of Computer Science and Information Technology, 2011
As the amount of internet documents has been growing, document clustering has become practically ... more As the amount of internet documents has been growing, document clustering has become practically important. This has led the interest in developing document clustering algorithms. Exploiting parallelism plays an important role in achieving fast and high quality clustering. In this ...
Gene therapy is an exciting field that has attracted much interest since the first submission of ... more Gene therapy is an exciting field that has attracted much interest since the first submission of clinical trials. Preliminary results were very encouraging and prompted many investigators and researchers. However, the ability of stem cells to differentiate into specific cell types holds immense potential for therapeutic use in gene therapy. Realization of this potential depends on efficient and optimized protocols for genetic manipulation of stem cells. It is widely recognized that gain/loss of function approaches using gene therapy are essential for understanding specific genes functions, and such approaches would be particularly valuable in studies involving stem cells. A significant complexity is that the development stage of vectors and their variety are still not sufficient to be efficiently applied in stem cell therapy. The development of scalable computer systems constitutes one step toward understanding dynamics of its potential. Therefore, the primary goal of this work is to develop a computer model that will support investigations of virus’ behavior and organization on regenerative tissues including genetically modified stem cells. Different simulation scenarios were implemented, and their results were encouraging compared to ex vivo experiments, where the error rate lies in the range of acceptable values in this domain of application.
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Papers by Amal Aboutabl