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On Cotangent Bundles Hamiltonian Tubes Theorem and Its Some Applications in Reduction Theory
Abdel Radi Abdel Rahman Abdel Gadir,
Ragaa Mohammed Haj Ibrahim,
Nedal Hassan Elbadowi Eljaneid
Issue:
Volume 4, Issue 2, June 2019
Pages:
31-35
Received:
20 January 2019
Accepted:
25 April 2019
Published:
18 June 2019
Abstract: This paper aims to study the Cotangent Bundles Hamiltonian Tubes theorem and its applications in reduction theory. The mathematical analysis method used. And found some results; The theory of reduction of cotangent bundles developed playing an important role in solution of the general problem for reduction a single or bit type cotangent bundles for base manifolds, possibility study of Hamiltonian tubes when the simplistic manifolds is a cotangent bundles, in the concrete case of cotangent bundles there is a strong motivation coming from geometric mechanics and geometric quantization that makes it desirable to obtain explicit fiber local models.
Abstract: This paper aims to study the Cotangent Bundles Hamiltonian Tubes theorem and its applications in reduction theory. The mathematical analysis method used. And found some results; The theory of reduction of cotangent bundles developed playing an important role in solution of the general problem for reduction a single or bit type cotangent bundles for...
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Application of Multiple Linear Regression Technique to Predict Noise Pollution Levels and Their Spatial Patterns in the Tarkwa Mining Community of Ghana
Peter Ekow Baffoe,
Alfred Allen Duker
Issue:
Volume 4, Issue 2, June 2019
Pages:
36-44
Received:
30 April 2019
Accepted:
4 June 2019
Published:
20 June 2019
Abstract: Predicting and preventing intraurban noise levels in our communities are very challenging for urban planning, epidemiological studies and environmental management, especially in the developing world. Most existing noise-predicting models are limited in providing changes in noise levels during intraurban development and the corresponding noise pollution. In this study, noise levels were measured at 50 purpose-designed monitoring stations and then a land-use regression model was developed for the intraurban noise prediction applying the multiple linear regression (MLR) technique. The measured and the predicted noise levels were compared. These were further compared with noise estimates from a standard noise model, Lyons Empirical model. The results from the developed MLR model did not show any significant differences in the patterns as compared with those of the Lyons Empirical model. The model performance indicators showed a standard deviation of 1.585, high correlation (R) of 0.98, R2 of 0.961 and RMSE of 1.569. The resulting maps showed a heterogeneous distribution of the noise pollution levels in the community. This confirms the usefulness of the method for assessing the spatial pattern of noise pollution in a community. This makes it a useful tool for urban planning, epidemiological studies and environmental management.
Abstract: Predicting and preventing intraurban noise levels in our communities are very challenging for urban planning, epidemiological studies and environmental management, especially in the developing world. Most existing noise-predicting models are limited in providing changes in noise levels during intraurban development and the corresponding noise pollu...
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Comparative Study of Three Image Enhancement Techniques for Geospatial Data
Issue:
Volume 4, Issue 2, June 2019
Pages:
45-51
Received:
28 April 2019
Accepted:
4 June 2019
Published:
2 July 2019
Abstract: Processing images for Geomatic works is one of the most difficult techniques. The image enhancement algorithms have direct effect on the quality of images. It is normally done to improve visual appearance and provide a better technique for future automated image processing. Sources of mages include satellite, photography and aerial photogrammetry that are used for geospatial data processing. These images suffer from poor contrast and noise. To use these images effectively, there is the need to enhance the contrast and remove the noise from the image to increase its quality. There are different techniques for image enhancement but this study focused on image interpolation. This multi-resolution technique is useful for variety of fields where fine and minor details are important. In this research, the Nearest Neighbor, Bilinear and Bicubic image interpolation algorithm were compared. Using the aforementioned techniques, two images were enhanced in order to compare their strengths and processing speed. The results of the algorithm of Nearest Neighbor had low computational time, low complexity of algorithm and poor image quality. On the other hand, the algorithms of Bilinear and Bicubic had average and high computational time, average and high complexity of algorithm and average and good image quality respectively.
Abstract: Processing images for Geomatic works is one of the most difficult techniques. The image enhancement algorithms have direct effect on the quality of images. It is normally done to improve visual appearance and provide a better technique for future automated image processing. Sources of mages include satellite, photography and aerial photogrammetry t...
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