Search

Creating machines that behave and work in a way similar to humans is the objective of artificial intelligence (AI). In addition to pattern recognition, planning, and problem-solving, computer activities with artificial intelligence include other activities. A group of algorithms called "deep learning" is used in machine learning. With the aid of magnetic resonance imaging (MRI), deep learning is utilized to create models for the detection and categorization of brain tumors. This allows for the quick and simple identification of brain tumors. Brain disorders are mostly the result of aberrant brain cell proliferation, which can harm the structure of the brain and ultimately result in malignant brain cancer. The early identification of brain tumors and the subsequent appropriate treatment may lower the death rate. In this study, we suggest a convolutional neural network (CNN) architecture for the efficient identification of brain tumors using MR images. This paper also discusses various models such as ResNet-50, VGG16, and Inception V3 and conducts a comparison between the proposed architecture and these models. To analyze the performance of the models, we considered different metrics such as the accuracy, recall, loss, and area under the curve (AUC). As a result of analyzing different models with our proposed model using these metrics, we concluded that the proposed model performed better than the others. Using a dataset of 3264 MR images, we found that the CNN model had an accuracy of 93.3%, an AUC of 98.43%, a recall of 91.19%, and a loss of 0.25. We may infer that the proposed model is reliable for the early detection of a variety of brain tumors after comparing it to the other models. [ABSTRACT FROM AUTHOR]

The smartphone exemplifies the rhetorical smart city movement. This paper examines one potential use of smartphone technology—mapping public transportation services in a megacity of the Global South. We examine the potential user impacts of introducing a smartphone-generated and analogue-delivered schematic bus map in Dhaka, Bangladesh. After distributing the map, we used a web-based survey to investigate impacts on users’ knowledge, as measured by their stated understanding, navigation and perceptions of the system. While a small and biased sample, the results suggest that the map fills a knowledge gap, provides useful and valued information and may stimulate ‘exploration’ of the city and its bus system. [ABSTRACT FROM AUTHOR]

This paper focuses on the coexistence of literary and historical values, giving equal weight to both. In this connection, Humayun Ahmed's Jochhona o Jononir Golpo is examined from the perspective of new historicism. New Historicism is a method which puts equal importance on the reading of literary and non-literary texts, usually of the same historical period. In this approach, literary and non-literary texts are studied parallel, given equal weight and constantly inform or interrogate each other. It takes combined interest in the textuality of history, and the historicity of a literary or other text. In Jochhona o Jononir Golpo, the facts by which the plot of the novel is knit states the real pieces of information from history, thereby, the storyline containing real life incidents, characters and happenings of 1971. These incidents are represented through various techniques like flashback, dreams, interview, letters and diaries. As a result, the historical events mentioned in the novel, become inseparable from the literary text. This parallel study of history and literature is the focus of our research which we believe will give a new dimension to the study of fictional work. [ABSTRACT FROM AUTHOR]