Computer Science articles list

Numerous initiatives to rely on new renewable energy sources, such solar electricity, have been sparked by the increased interest in global warming. With an increase in home photovoltaic (PV) panels that are available to the public, more precise calculations of energy generation are now possible. Segmenting satellite images offers a straightforward and inexpensive way to categorize solar panels..This work suggests a method for classifying and segmenting solar panels that combines the watershed algorithm with deep learning approaches. First, a Convolutional Neural Network (CNN) architecture with the ResNet, EfficientNet, and Inception architectures is used for classification. Through the fine-tuning of pre-trained networks on a heterogeneous dataset of solar panels, transfer learning improves performance. The categorization model recognizes solar panels in a variety of settings with accuracy, making maintenance and monitoring easier. After classification, the watershed method uses intensity gradients to precisely delineate solar panels from the background. Tasks like defect detection and layout optimization are made easier when deep learning-based classification and watershed segmentation are combined. The outcomes of the experiments show how well the suggested method performs in terms of segmenting and classifying solar panels under various circumstances. A flexible automated solar panel management solution is provided by the combination of deep learning and the watershed algorithm, which promotes increased sustainability and efficiency in solar energy systems.

BAKKA ARUN KUMAR

Online distance learning policies were formulated and implemented among some Malaysian universities long ago, but their value emerged since COVID- 19. Emanating from the diffusion of innovation theory, this study examined the perception of higher education students on the influence and relationship between six independent variables (compatibility, observability, relative advantage, complexity, trialability, and digital skills) and one dependent variable (digital literacy). A total of 524 respondents were sampled, comprising students from six public and private Malaysian universities. The findings from the correlation analysis show a significant positive relationship between the six independent variables and the dependent variable. Meanwhile, in the regression analysis, three of the independent variables (observability, trialability, and digital skill) have a significant and positive effect on digital literacy. This study placed the diffusion of innovation in a specific context that supports designing online distance learning and digital literacy policies

Mohammed Fadel Arandas