ABSTRACT

The very long delay that is suffered by patients of breast cancer in their early stages in low-income countries is due to access barriers and quality deficiencies in the care of cancer giving rise to the need for an alternative and efficient computer-based diagnostic system for the early detection and prevention of the disease. The early detection and improved therapy still remain a crucial approach for the prevention and cure of breast cancer. To this end, recent research looks into the development of different classifier models for the classification of breast cancer. This paper investigates the potentials of applying multiple neural network architectures with increased number of hidden layers and hidden units. The network architectures have one-hidden-layer, two-hidden-layer and three hidden layer (deep neural network) architectures respectively using the backpropagation training algorithm for the training of the models. The experimental results show that by applying this approach the models yield efficient and promising results

No abstract

to evaluate the quality of sediment in Bung Binh Thien through the indicators of organic matter, total nitrogen, and total phosphorus by collecting the sediment samples in the outside, inlet, middle, and end areas of the reservoir in the dry and rainy seasons. The findings revealed that the quality of sediment in the area of Bung Binh Thien was spatially and temporally fluctuated. In the dry season, the content of organic matter, total nitrogen, total phosphorus fluctuated respectively from 1.04 to 5.35%; 0.06-0.35% and 0.036-0.076% which were higher than those in the rainy season with the corresponding values were 1.51-4.65%; 0.10-0.28% and 0.042-0.072%, respectively. The nutrients in the sediment inside the reservoir was relatively higher than those in the outside area. There was a strong correlation between total nitrogen, total phosphorus and organic matter in the study area. This partially reflected the impact of living activities and production of the surrounding community on environmental quality in the area of Bung Binh Thien.