Model transformation is one of the prominent features and the rising research area of Model Driven Engineering (MDE). MDE promotes models to primary artifacts that drive the whole development process. This paper prese...Model transformation is one of the prominent features and the rising research area of Model Driven Engineering (MDE). MDE promotes models to primary artifacts that drive the whole development process. This paper presents the model transformation approach for textual model oriented programs Umple (UML Programming Language) to generate android applications (apps). The proposed approach improved the generation of android source code by using Drools transformation rules and introducing new concern in model driven mobile engineering. The major objective of proposed transformation approach intends to address consistency between source and target model and also intends to handle productivity issues in model driven software development. The main results of model transformation approach are Java class for model layer, XML file for view layer and android activity class for controller layer. Results show that proposed approach achieves high consistency between source and target model and also improves model transformation productivity.展开更多
Multimodal medical image fusion is a powerful tool for diagnosing diseases in medical field. The main objective is to capture the relevant information from input images into a single output image, which plays an impor...Multimodal medical image fusion is a powerful tool for diagnosing diseases in medical field. The main objective is to capture the relevant information from input images into a single output image, which plays an important role in clinical applications. In this paper, an image fusion technique for the fusion of multimodal medical images is proposed based on Non-Subsampled Contourlet Transform. The proposed technique uses the Non-Subsampled Contourlet Transform (NSCT) to decompose the images into lowpass and highpass subbands. The lowpass and highpass subbands are fused by using mean based and variance based fusion rules. The reconstructed image is obtained by taking Inverse Non-Subsampled Contourlet Transform (INSCT) on fused subbands. The experimental results on six pairs of medical images are compared in terms of entropy, mean, standard deviation, Q<sup>AB/F</sup> as performance parameters. It reveals that the proposed image fusion technique outperforms the existing image fusion techniques in terms of quantitative and qualitative outcomes of the images. The percentage improvement in entropy is 0% - 40%, mean is 3% - 42%, standard deviation is 1% - 42%, Q<sup>AB/F</sup>is 0.4% - 48% in proposed method comparing to conventional methods for six pairs of medical images.展开更多
Objective This paper proposed a novel algorithm of discrete wavelet transform(DWT) which is used for multimodal medical image fusion. Methods The source medical images are initially transformed by DWT followed by fusi...Objective This paper proposed a novel algorithm of discrete wavelet transform(DWT) which is used for multimodal medical image fusion. Methods The source medical images are initially transformed by DWT followed by fusing low and high frequency sub-images. Then, the "coefficient absolute value" that can provide clear and detail parts is adapted to fuse high-frequency coefficients, where as the "region energy ratio" which can efficiently preserve most information of source images is employed to fuse low-frequency coefficients. Finally, the fused image is reconstructed by inverse wavelet transform. Results Visually and quantitatively experimental results indicate that the proposed fusion method is superior to traditional wavelet transform and the existing fusion methods. Conclusion The proposed method is a feasible approach for multimodal medical image fusion which can obtain more efficient and accurate fusions results even in the noise environment.展开更多
In order to find stable, accurate, and computationally efficient methods for performing the inverse Laplace transform, a new double transformation approach is proposed. To validate and improve the inversion solution o...In order to find stable, accurate, and computationally efficient methods for performing the inverse Laplace transform, a new double transformation approach is proposed. To validate and improve the inversion solution obtained using the Gaver-Stehfest algorithm, direct Laplace transforms are taken of the numerically inverted transforms to compare with the original function. The numerical direct Laplace transform is implemented with a composite Simpson’s rule. Challenging numerical examples involving periodic and oscillatory functions, are investigated. The numerical examples illustrate the computational accuracy and efficiency of the direct Laplace transform and its inverse due to increasing the precision level and the number of terms included in the expansion. It is found that the number of expansion terms and the precision level selected must be in a harmonious balance in order for correct and stable results to be obtained.展开更多
文摘Model transformation is one of the prominent features and the rising research area of Model Driven Engineering (MDE). MDE promotes models to primary artifacts that drive the whole development process. This paper presents the model transformation approach for textual model oriented programs Umple (UML Programming Language) to generate android applications (apps). The proposed approach improved the generation of android source code by using Drools transformation rules and introducing new concern in model driven mobile engineering. The major objective of proposed transformation approach intends to address consistency between source and target model and also intends to handle productivity issues in model driven software development. The main results of model transformation approach are Java class for model layer, XML file for view layer and android activity class for controller layer. Results show that proposed approach achieves high consistency between source and target model and also improves model transformation productivity.
文摘Multimodal medical image fusion is a powerful tool for diagnosing diseases in medical field. The main objective is to capture the relevant information from input images into a single output image, which plays an important role in clinical applications. In this paper, an image fusion technique for the fusion of multimodal medical images is proposed based on Non-Subsampled Contourlet Transform. The proposed technique uses the Non-Subsampled Contourlet Transform (NSCT) to decompose the images into lowpass and highpass subbands. The lowpass and highpass subbands are fused by using mean based and variance based fusion rules. The reconstructed image is obtained by taking Inverse Non-Subsampled Contourlet Transform (INSCT) on fused subbands. The experimental results on six pairs of medical images are compared in terms of entropy, mean, standard deviation, Q<sup>AB/F</sup> as performance parameters. It reveals that the proposed image fusion technique outperforms the existing image fusion techniques in terms of quantitative and qualitative outcomes of the images. The percentage improvement in entropy is 0% - 40%, mean is 3% - 42%, standard deviation is 1% - 42%, Q<sup>AB/F</sup>is 0.4% - 48% in proposed method comparing to conventional methods for six pairs of medical images.
文摘Objective This paper proposed a novel algorithm of discrete wavelet transform(DWT) which is used for multimodal medical image fusion. Methods The source medical images are initially transformed by DWT followed by fusing low and high frequency sub-images. Then, the "coefficient absolute value" that can provide clear and detail parts is adapted to fuse high-frequency coefficients, where as the "region energy ratio" which can efficiently preserve most information of source images is employed to fuse low-frequency coefficients. Finally, the fused image is reconstructed by inverse wavelet transform. Results Visually and quantitatively experimental results indicate that the proposed fusion method is superior to traditional wavelet transform and the existing fusion methods. Conclusion The proposed method is a feasible approach for multimodal medical image fusion which can obtain more efficient and accurate fusions results even in the noise environment.
文摘In order to find stable, accurate, and computationally efficient methods for performing the inverse Laplace transform, a new double transformation approach is proposed. To validate and improve the inversion solution obtained using the Gaver-Stehfest algorithm, direct Laplace transforms are taken of the numerically inverted transforms to compare with the original function. The numerical direct Laplace transform is implemented with a composite Simpson’s rule. Challenging numerical examples involving periodic and oscillatory functions, are investigated. The numerical examples illustrate the computational accuracy and efficiency of the direct Laplace transform and its inverse due to increasing the precision level and the number of terms included in the expansion. It is found that the number of expansion terms and the precision level selected must be in a harmonious balance in order for correct and stable results to be obtained.
