Disabled people encounter many barriers while attempting to access the services on the web. Nevertheless, many tools, which could help them to access the web, are available. E-commerce websites have been also intensiv...Disabled people encounter many barriers while attempting to access the services on the web. Nevertheless, many tools, which could help them to access the web, are available. E-commerce websites have been also intensively and widely used. The e-commerce market in Saudi Arabia will hit $13.3 billion by 2015. This huge investment requires e-commerce websites to be accessible by different types of users. This paper explores the tools that usually used by disabled users while using the web. It also discusses a number of available tools that help designers, developers and testers to assess web accessibility. It also evaluates the accessibility of 3 popular Arab e- commerce websites using 5 accessibility testing tools;namely Achecker, TAW, Eval Access, MAUVE and FAE. This research has found that Most accessibility guidelines are covered by Achecker tool. Navigation, readability, input assistance and timing are the common found accessibility problems while assessing the accessibility of the targeted websites. It has been also revealed that HTML can influence accessibility evaluation as HTML errors are considered as accessibility problems. It has been clearly observed that improvements are needed for better web accessibility, although some tools did report a small number of accessibility problems for some websites.展开更多
An automated environment is presented which aids the software engineers in developing data pro- cessing systems by using rapid prototyping techniques.The environment is being developed on VAX sta- tion.It can render g...An automated environment is presented which aids the software engineers in developing data pro- cessing systems by using rapid prototyping techniques.The environment is being developed on VAX sta- tion.It can render good support to the specification of the requirements and the rapid creation of proto- type.The goal,the methodology,the general structure of the environment and two sub-systems are discussed.展开更多
The diagnosis of multiple sclerosis(MS)is based on accurate detection of lesions on magnetic resonance imaging(MRI)which also provides ongoing essential information about the progression and status of the disease.Manu...The diagnosis of multiple sclerosis(MS)is based on accurate detection of lesions on magnetic resonance imaging(MRI)which also provides ongoing essential information about the progression and status of the disease.Manual detection of lesions is very time consuming and lacks accuracy.Most of the lesions are difficult to detect manually,especially within the grey matter.This paper proposes a novel and fully automated convolution neural network(CNN)approach to segment lesions.The proposed system consists of two 2D patchwise CNNs which can segment lesions more accurately and robustly.The first CNN network is implemented to segment lesions accurately,and the second network aims to reduce the false positives to increase efficiency.The system consists of two parallel convolutional pathways,where one pathway is concatenated to the second and at the end,the fully connected layer is replaced with CNN.Three routine MRI sequences T1-w,T2-w and FLAIR are used as input to the CNN,where FLAIR is used for segmentation because most lesions on MRI appear as bright regions and T1-w&T2-w are used to reduce MRI artifacts.We evaluated the proposed system on two challenge datasets that are publicly available from MICCAI and ISBI.Quantitative and qualitative evaluation has been performed with various metrics like false positive rate(FPR),true positive rate(TPR)and dice similarities,and were compared to current state-of-the-art methods.The proposed method shows consistent higher precision and sensitivity than other methods.The proposed method can accurately and robustly segment MS lesions from images produced by different MRI scanners,with a precision up to 90%.展开更多
文摘Disabled people encounter many barriers while attempting to access the services on the web. Nevertheless, many tools, which could help them to access the web, are available. E-commerce websites have been also intensively and widely used. The e-commerce market in Saudi Arabia will hit $13.3 billion by 2015. This huge investment requires e-commerce websites to be accessible by different types of users. This paper explores the tools that usually used by disabled users while using the web. It also discusses a number of available tools that help designers, developers and testers to assess web accessibility. It also evaluates the accessibility of 3 popular Arab e- commerce websites using 5 accessibility testing tools;namely Achecker, TAW, Eval Access, MAUVE and FAE. This research has found that Most accessibility guidelines are covered by Achecker tool. Navigation, readability, input assistance and timing are the common found accessibility problems while assessing the accessibility of the targeted websites. It has been also revealed that HTML can influence accessibility evaluation as HTML errors are considered as accessibility problems. It has been clearly observed that improvements are needed for better web accessibility, although some tools did report a small number of accessibility problems for some websites.
文摘An automated environment is presented which aids the software engineers in developing data pro- cessing systems by using rapid prototyping techniques.The environment is being developed on VAX sta- tion.It can render good support to the specification of the requirements and the rapid creation of proto- type.The goal,the methodology,the general structure of the environment and two sub-systems are discussed.
基金Thanks to research training program(RTP)of University of Newcastle,Australia and PGRSS,UON for providing funding.APC of CMC will be paid by PGRSS,UON funding.
文摘The diagnosis of multiple sclerosis(MS)is based on accurate detection of lesions on magnetic resonance imaging(MRI)which also provides ongoing essential information about the progression and status of the disease.Manual detection of lesions is very time consuming and lacks accuracy.Most of the lesions are difficult to detect manually,especially within the grey matter.This paper proposes a novel and fully automated convolution neural network(CNN)approach to segment lesions.The proposed system consists of two 2D patchwise CNNs which can segment lesions more accurately and robustly.The first CNN network is implemented to segment lesions accurately,and the second network aims to reduce the false positives to increase efficiency.The system consists of two parallel convolutional pathways,where one pathway is concatenated to the second and at the end,the fully connected layer is replaced with CNN.Three routine MRI sequences T1-w,T2-w and FLAIR are used as input to the CNN,where FLAIR is used for segmentation because most lesions on MRI appear as bright regions and T1-w&T2-w are used to reduce MRI artifacts.We evaluated the proposed system on two challenge datasets that are publicly available from MICCAI and ISBI.Quantitative and qualitative evaluation has been performed with various metrics like false positive rate(FPR),true positive rate(TPR)and dice similarities,and were compared to current state-of-the-art methods.The proposed method shows consistent higher precision and sensitivity than other methods.The proposed method can accurately and robustly segment MS lesions from images produced by different MRI scanners,with a precision up to 90%.
