An Empirical Analysis of cluster-based routing protocols in wireless sensor network

Wireless Sensor Networks (WSNs) are utilized for condition monitoring, developing the board, following animals or goods, social protection, transportation, and house frameworks. WSNs are revolutionizing research. A WSN includes a large number of sensor nodes, or bits, in the application. Bits outfitted with the application\u27s sensors acquire nature data and send it to at least one sink center (in like manner called base stations). This article simulates energy-efficient network initialization strategies using simulation models. First, an overview of network initiation and exploration procedures in wireless ad-hoc networks is provided. The clustering-based routing strategy was selected since it\u27s best for ad-hoc sensor networks. The clustering-based routing techniques used for this study are described below. LEACH, SEP, and Z-SEP are used. MATLAB was used to implement and simulate all routing protocols. All protocols were simulated with various parameters like Number of CHs, Number of Alive Nodes, Number of Dead Nodes, Number of packets to BS, and circumstances to show their functioning and to determine their behavior in different sensor networks

En-PaFlower: An Ensemble Approach using PSO and Flower Pollination Algorithm for Cancer Diagnosis

Machine learning now is used across many sectors and provides consistently precise predictions. The machine learning system is able to learn effectively because the training dataset contains examples of previously completed tasks. After learning how to process the necessary data, researchers have proven that machine learning algorithms can carry out the whole work autonomously. In recent years, cancer has become a major cause of the worldwide increase in mortality. Therefore, early detection of cancer improves the chance of a complete recovery, and Machine Learning (ML) plays a significant role in this perspective. Cancer diagnostic and prognosis microarray dataset is available with the biopsy dataset. Because of its importance in making diagnoses and classifying cancer diseases, the microarray data represents a massive amount. It may be challenging to do an analysis on a large number of datasets, though. As a result, feature selection is crucial, and machine learning provides classification techniques. These algorithms choose the relevant features that help build a more precise categorization model. Accurately classifying diseases is facilitated as a result, which aids in disease prevention. This work aims to synthesize existing knowledge on cancer diagnosis using machine learning techniques into a compact report.  Current research work aims to propose an ensemble-based machine learning model En-PaFlower using Particle Swarm Optimization (PSO) as the feature selection algorithm, Flower Pollination algorithm (FPA) as the optimization algorithm with the majority voting algorithm. Finally, the performance of the proposed algorithm is evaluated over three different types of cancer disease datasets with accuracy, precision, recall, specificity, and F-1 Score etc as the evaluation parameters. The empirical analysis shows that the proposed methodology shows highest accuracy as 95.65%

Fashioning readers: canon, criticism and pedagogy in the emergence of modern Oriya literature

Through a brief history of a widely published canon debate in nineteenth century Orissa, this article describes how anxieties about the quality of ‘traditional’ Oriya literature served as a site for imagining a cohesive Oriya public who would become the consumers and beneficiaries of a new, modernized Oriya-language canon. A public controversy about the status of Oriya literature was initiated in the 1890s with the publication of a serialized critique of the works of Upendra Bhanja, a very popular pre-colonial Oriya poet. The critic argued that Bhanja’s writing was not true poetry, that it did not speak to the contemporary era, and that it featured embarrassingly detailed discussions of obscene material. By unpacking the terms of this criticism and Oriya responses to it, I reveal how at the heart of these discussions were concerns about community building that presupposed a new kind of readership of literature in the Oriya language. Ultimately, this article offers a longer, regional history to the emerging concern of post-colonial scholarship with relationships between publication histories, readerships, and broader ideas of community – local, Indian, and global