Artificial intelligence (AI) and machine learning applications in the medical sector, pattern recognition, network security, financial sector, and many more sectors can produce excellent results for persons, patients, companies, and organizations such as improved efficiency, reduced operational cost, and enhanced customer satisfaction. ML has been explained as lying at the intersection of computer science, engineering, and systems. It has been marked as a tool that can be applied to various problems, especially in areas that require data to be interpreted and processed. ML, which is categorized as supervised machine learning, unsupervised machine learning, and reinforcement machine learning, plays an important role in solving the different problem using different dataset. In this paper we present the literature review for the different machine learning classifier using in different filed.

Shashi Tharoor’s The Great Indian Novel is veritably fascinating it deals with the Indian myth of Mahabharata and history of freedom struggle. He recites the history of ultramodern India through the grand story. The new passes to make a history of the colonizer and postcolonial India in terms of real events and characters from the twentieth century Indian socio- political gospel. Numbers from Indian history are converted into mythological characters and mythological story of the epic is retold as a history of India. In this exploration paper, I seek to concentrate on the new literal notion that reinterprets myth and history for reconstruction of the once reality. To develop ultramodern sensibility about the great legends and to define value of the history is the alternate major end of this composition. The composition aimsat erecting a new nation on rational lines with changed political testaments and altering political script. The exploration paper is divided into three sections, section first puts forth the generality of myth and history in fabrication, alternate analyses of the novel and section third concludes. The paper with exploration finding. This research paper examines Indian Postcolonial history of India and how its politicians are represented through myth in Shashi Tharoor’s The Great Indian Novel. Tharoor frames the progress of political events during colonial period and postcolonial period of India. His narrative represents the characters as the figures of The Mahabharat and the incidents of the Mythology take new forms in the contemporary politics of India. Tharoor has so dexterously knitted together the incidents and characters of the novel with that of the mythical characters of The Mahabharata.

Diabetes in adults is a global health problem and is considered as one of the main threats to human health and its management requires a fundamental change in patient’s lifestyle. Aim: The aim of this study to assess the effectiveness of structured teaching program on the lifestyle modification to control diabetes among individuals with type-2 diabetes mellitus in selected urban community of Delhi. Methods: A quantitative approach with pre-test post-test research design was implemented. Total 50 participant were selected from non-probability purposive sampling technique and data was collected by using closed ended structured questionnaire. Result and Conclusion: Descriptive and inferential statistics was used to analyse the data of the research. Thus, it shows that, individual suffering from diabetes mellitus gained knowledge about the lifestyle modification of diabetes mellitus after structured teaching programme. Hence the planned teaching programme was found effective in imparting knowledge on lifestyle modification among individual suffering from diabetes mellitus in selected urban community of Delhi.

The integration of Internet of Things (IoT) technology in agriculture has revolutionized traditional farming methods, leading to the emergence of smart agriculture practices. This paper provides a comprehensive review of IoT sensors for smart agriculture, exploring the diverse ecosystem of IoT applications in the agricultural sector. Various IoT-supported technologies utilized in agriculture are discussed, highlighting their roles in enhancing productivity, efficiency, and sustainability. Additionally, a summary of different IoT-based methods employed in agriculture is provided, elucidating their contributions to precision farming and resource optimization. The benefits of IoT in agriculture are underscored, encompassing improved decision-making, reduced resource wastage, and increased yields. However, alongside these benefits, several hardware and software challenges of implementing IoT in agriculture are examined, including issues related to connectivity, interoperability, data security, and scalability. Overall, this paper offers insights into the transformative potential of IoT in agriculture while acknowledging the complexities and hurdles that accompany its adoption.

In MC-CDMA system Peak-to-Average Power Ratio (PAPR) is major problem. High PAPR leads to nonlinear distortion of the amplifier and results in inter-carrier self-interference plus out-of-band radiation. Many approaches have been proposed to solve the PAPR problem in multicarrier systems, which include amplitude clipping, clipping and filtering, coding, tone reservation, tone injection, active constellation extension, and multiple signal representation techniques. All those techniques have their own drawbacks, such as transmit signal power increase, BER increase, data rate loss, computational complexity increase. Imperfect cross-correlation characteristics of the spreading codes and the multipath fading make the orthogonality among the users lost, and then cause MAI, which produces serious BER degradation in the system. Due to the ability of detecting all the users simultaneously with reduced latency, the PIC is also especially attractive for an uplink MC-CDMA system. Hence a new semi-blind channel estimation and multi-user data detection based on PIC have been proposed, which cancels interference partly by adjusting interference cancellation factors (ICF). There are two working modes in the system: pilot transmission (PT) mode and data transmission (DT) mode. Also in the partial interference cancellation techniques there is a new algorithm known as HEBB’s rule is proposed and simulations in both DS-CDMA and MC-CDMA systems show that the proposed Hebb-PPIC detector has strong anti-MAI ability and its performance of bit error rate (BER) is improved on the basis of conventional PIC.

Now days so much inaccurate information and fraud in the healthcare industry, so we need to explore a secure and trusting environment to better the system. Nonfinancial blockchain provides secure and immutable data sharing to data management in the diverse medical workflow. The data breaches reached a record high and for the past few years, the healthcare field has had the second highest number of breaches compared to other sectors. The frequency of medical data breaches has been highly concerning. In particular, armed with someone’s medical information, thieves can easily commit medical identity theft to get drug prescriptions, or make false insurance claims under the victim’s name. Medical data mostly comes with personal and private information which includes Social Security Numbers (SSNs), as well as financial information. This is done using trained algorithms. After storing we use Blockchain for data sharing and its reliability. For securing the medical data use Decentralized server for secure storage of medical data.

Ensuring the prevention and management of plant diseases is crucial for achieving a successful plant yield. The study enhanced the accuracy of plant leaf disease detection by utilizing advanced techniques such as "single shot multi-box detectors," "faster region-based convolutional neural networks," and "You only look once-X." These techniques incorporate effective attention mechanisms, including the convolutional block attention module, squeeze and excitation networks, and efficient channel attention. The implementation of diverse attention approaches effectively highlighted significant attributes while minimizing the influence of unimportant ones, hence enhancing the accuracy of the models and enabling real-time execution. After evaluating the optimal models from the three types, it was determined that the Faster (R-CNN) model had a lower precision value. On the other hand, You Only Look Once-X and SSD with various attention techniques had the highest precision and required the fewest parameters. Additionally, these models demonstrated the best real-time performance. This study not only offered useful insights into the detection of plant leaf diseases, but also provided insights into plant illnesses and symptoms in automated agricultural production.