Bøger af Vishal Goar

The medical field has witnessed a surge in the importance of data, with medical data playing a crucial role in patient diagnosis and healthcare practices. It encompasses a wide range of information, including patient personal details, reports, and treatment records. The advent of technology has led to the generation of data in various formats, such as text, images, and videos. However, effectively storing and retrieving electronically generated medical data presents significant challenges. Data storage has always been a priority, and healthcare data is no exception. As healthcare data becomes increasingly digitized, its volume, velocity, and value continue to grow. Efficient management of this data is essential for practitioners, healthcare organizations, and patient well-being. Moreover, medical imaging technology has revolutionized the healthcare industry, enabling early disease detection and improved patient recovery. However, it generates massive amounts of semi-structured and unstructured visual data, necessitating advanced data models for efficient retention and retrieval. This research aims to evaluate different database management systems.

There has been an extensive demand in the use of databases for decision support in these days. This was mainly due to the fact that information, one of the most precious assets of an organization, can assist in decision making and this way considerably improves the value of an organization. This phenomenon is a result of the increased availability of new technologies to support capable storage and retrieval of large volumes of data, namely data warehousing. One of the most important requirements of a data warehouse server is the query performance. The principal aspect from the user perspective is how quickly the server processes a given query: ¿the data warehouse must be fast¿. The main focus of our research is finding adequate solutions to improve query response time of typical data ware house queries and improve scalability using an environment that takes advantage of characteristics specific to the data ware house context. Our propose model provides very good performance and scalability even on huge data warehouses.

His research is a comparison and study of the key characteristics of cloud technologies in today¿s market that enable users to retrieve meaningful information from data storage virtually integrated reducing the cost of infrastructure and storage. This research work proposed to evaluates the performance of data mining approaches on live cloud environment and found that the approaches with cloud implementation giving better and effective results. With the advent and adoption of cloud technologies, most of the work is done on real cloud and that¿s why this work is solely dependent on the integration of data mining with cloud environment along with the adoption level in the general dimensions.

Computer science had magnificently positioned the sensor network on earth and on human body but still underwater is unscathed area and our 2/3rdportion of globe is enclosed with seawater. Underwater sensor networks (UWSN) are the emergent and auspicious announcement framework which empowers a wide range of imperative applications. This book mainly focuses on the various energy harvesting techniques for scalable and reliable for data dissemination UWSN. It considered few of the above challenges in the research work. A brief summary of the goal is mentioned below: ¿ Deployment of sensor at three levels in ocean at bottom level which are immobility, then at middle level which are also in mobility and then at top level which are static. ¿ To provide the mechanism to recharge sensor¿s batteries from natural energy harvesting sources. ¿ The network positioned should be energy efficient. ¿ Data Transmission Rate is fast and high.

This book features selected research papers presented at the International Conference on Advances in Information Communication Technology and Computing (AICTC 2019), held at the Government Engineering College Bikaner, Bikaner, India, on 8-9 November 2019. It covers ICT-based approaches in the areas ICT for energy efficiency, life cycle assessment of ICT, green IT, green information systems, environmental informatics, energy informatics, sustainable HCI and computational sustainability.