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A systematic study of radiation effects on the major parameters of ohmic and Schottky contacts based on n-ZnO is introduced. Al and Au metals were used as contact elements in order to fabricate the ohmic and Schottky structures, respectively. The transmission line method (TLM) measurements on Al/n-ZnO have revealed that high-energy (6, 9, 12 MeV) and relatively low-dose (3 × 10 12 e − cm −2 ) electron irradiation produced lower specific ohmic contact resistivity values as compared with the reference sample. The current-voltage (I-V ) and capacitance-voltage (C-V ) measurements on the Au/n-ZnO structures are shown to increase in ideality and to decrease in the Schottky barrier heights with increasing electron energy. These findings have been interpreted based on the assumption that the atoms of the contact elements diffused into the semiconductor material, thus turning the rectifying character to ohmic behaviour with the influence of radiation-matter interaction and subsequent annealing effects.

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Abstract:The most common type of cancer seen in women is breast cancer. To enable recovery from this severe disease, monitoring and early detection must be provided, and related precautions must be taken as a first step. During diagnosis, some cases may be overlooked due to fatigue and eyestrain, because the determination of abnormalities is a repetitive procedure. In this study, a computer-aided diagnosis (CAD) system, using the wave atom transform (WAT) algorithm and support vector machine (SVM), is proposed to evaluate mammography images. During the process, the region of interest (ROI) is defined before applying the method. The system includes a feature extraction approach based on the WAT algorithm. In terms of classification, the process has 2 main stages: the classification of normal/abnormal regions and malignant/benign ones. The proposed system also uses principle component analysis (PCA) for further dimensional reduction and feature selection. A dataset from the Mammographic Image Analysis Society database is employed for testing and measuring the performance of the proposed system. The best success rates in this work are obtained using the coefficients at scales of 1, 2, and 3, by employing SVM with PCA. The maximum classification success rate to define the regions of interest as normal/abnormal is 100%. The success rate of malignant/benign classification is also achieved as 100% in the tests. According to the results, it is observed that these features ensure important support for more comprehensive clinical investigations and the results are very encouraging when mammograms are categorized via WAT, PCA, and SVM.