nazim imal - Academia.edu (original) (raw)
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Papers by nazim imal
Balkan Journal of Electrical and Computer Engineering, 2015
Photovoltaic panels (solar cells), they receive photon energy from sunlight, convert them to elec... more Photovoltaic panels (solar cells), they receive photon energy from sunlight, convert them to electrical energy by the semiconductor structural features. Photovoltaic panels produce a voltage, depending on the change of functional sunlight exposure. Produced voltage and determining of provided electrical power, must be dealt with the physical parameters that uses the concepts of light and temperature. In this study, usage of monocrystalline and polycrystalline structured photovoltaic panels electrical energy conversion for different atmospheric temperature and different sunlight intensity are studied. With the realization of the applications, photovoltaic panels' thermal change effects upon the energy production is discussed. With the conclusions obtained from the research applications and analyses, for heat exchange in photovoltaic panels to effects upon energy production, the obtained principles of functional changes are interpreted.
Computational and mathematical methods in medicine, 2013
Our aim was to analyze the feasibility of computer aided malignant tumor detection using the trad... more Our aim was to analyze the feasibility of computer aided malignant tumor detection using the traditional texture analysis applied on two-compartment-based parameter pseudoimages of dynamic contrast-enhanced magnetic resonance (DCE-MR) breast image data. A major contribution of this research will be the through-plane assessment capability. Texture analysis was performed on two-compartment-based pseudo images of DCE-MRI datasets of breast data of eight subjects. The resulting texture parameter pseudo images were inputted to a feedforward neural network classification system which uses the manual segmentations of a primary radiologist as a gold standard, and each voxel was assigned as malignant or nonmalignant. The classification results were compared with the lesions manually segmented by a second radiologist. Results show that the mean true positive fraction (TPF) and false positive fraction (FPF) performance of the classifier vs. primary radiologist is statistically as good as the m...
Balkan Journal of Electrical and Computer Engineering, 2015
Photovoltaic panels (solar cells), they receive photon energy from sunlight, convert them to elec... more Photovoltaic panels (solar cells), they receive photon energy from sunlight, convert them to electrical energy by the semiconductor structural features. Photovoltaic panels produce a voltage, depending on the change of functional sunlight exposure. Produced voltage and determining of provided electrical power, must be dealt with the physical parameters that uses the concepts of light and temperature. In this study, usage of monocrystalline and polycrystalline structured photovoltaic panels electrical energy conversion for different atmospheric temperature and different sunlight intensity are studied. With the realization of the applications, photovoltaic panels' thermal change effects upon the energy production is discussed. With the conclusions obtained from the research applications and analyses, for heat exchange in photovoltaic panels to effects upon energy production, the obtained principles of functional changes are interpreted.
Computational and mathematical methods in medicine, 2013
Our aim was to analyze the feasibility of computer aided malignant tumor detection using the trad... more Our aim was to analyze the feasibility of computer aided malignant tumor detection using the traditional texture analysis applied on two-compartment-based parameter pseudoimages of dynamic contrast-enhanced magnetic resonance (DCE-MR) breast image data. A major contribution of this research will be the through-plane assessment capability. Texture analysis was performed on two-compartment-based pseudo images of DCE-MRI datasets of breast data of eight subjects. The resulting texture parameter pseudo images were inputted to a feedforward neural network classification system which uses the manual segmentations of a primary radiologist as a gold standard, and each voxel was assigned as malignant or nonmalignant. The classification results were compared with the lesions manually segmented by a second radiologist. Results show that the mean true positive fraction (TPF) and false positive fraction (FPF) performance of the classifier vs. primary radiologist is statistically as good as the m...