Bøger af Pankaj Bhambri

Recently, the fields of Artificial Intelligence (AI) and the Internet of Things (IoT) have revolutionized numerous industries, including healthcare. The convergence of AI and IoT has given birth to smart healthcare systems, transforming the way we deliver, receive, and experience healthcare services. This book explores the profound impact of these technologies on healthcare and presents a comprehensive overview of their applications, challenges, and prospects.Smart Healthcare Systems: AI and IoT Perspectives addresses various aspects of how smart healthcare can be used to detect and analyze diseases, the underlying methodologies, and related security concerns. It also discusses healthcare as a multidisciplinary field that involves a range of sectors such as the financial system, social factors, health technologies, and organizational structures that affect individuals, families, institutions, organizations, and populations' healthcare. The book presents the goals of healthcare services which include patient safety, timeliness, effectiveness, efficiency, and equity. An outline of what smart healthcare consists of which is m-health, e-health, electronic resource management, smart and intelligent home services, and medical devices is included. Along with highlights on how AI and IoT-enabled healthcare technologies are suitable for remote health monitoring, including rehabilitation, and assisted ambient living. Rounding the offers of this book out is that it also covers how healthcare analytics can be applied to the data gathered from different areas to improve healthcare at a minimum expense.Researchers, Academicians, Industry, R&D Organizations, medical professionals, PG students, and policymakers in the fields of artificial intelligence, the internet of things, healthcare informatics, biomedical engineering, medical informatics, and related subjects can use this book to assist them in making appropriate decisions regarding these emerging disciplines.

Master's Thesis from the year 2017 in the subject Computer Science - Bioinformatics, grade: 90, Punjabi University (Guru Nanak Dev Engineering College, Ludhiana), course: Masters of Technology, language: English, abstract: Computational screening of databases has gained immense popularity in the pharmaceutical research and development. To do such screening tests the Virtual Screening technique is used. It uses computer-based algorithms and methods which takes into consideration a lot of parameters to discover new ligands on the basis of biological structures. The process of discovering new drugs has now become a crucial factor for all the Pharmaceutical Industries. Acceleration of Virtual screening would provide an edge to save the resources as well as the time required. Here, the effectual implementation of the parallel architecture of CUDA and GP-GPU for the acceleration of Virtual screening has been analyzed. The implementation is in CUDA programming models. This implementation tries to take maximum advantage of a GPU to give a better solution in the process of drug discovery. The result which would be higher speedup when implemented on CUDA GPU architecture to provide the better solution considering performance & cost ratio.

Research Paper (undergraduate) from the year 2018 in the subject Engineering - Computer Engineering, grade: 9.8, University of the Punjab (Guru Nanak Dev Engineering College, Ludhiana), course: Masters of Technology, language: English, abstract: The traditional test extraction suffers from the drawback of size style and rotation of text arose on the images. Thus the scanning device needs to focus on the textual region of the images. Which is going to involve the person who is using the application software? This can be automated using algorithm which is written and designed in such a way so that the text area on the image will be easily identified either at some orientation or at variable sizes. In the presented work, the characters are segmented by using the pixel neighborhood technique and resized to a 32x32 block. The centre of gravity of the different characters is computed by using the first order moments. The contour of the pixel is extracted by means of Robert¿s operator. The radii from centre of gravity to contour pixel and are arranged in descending order. If the same character is rotated about its centre of gravity by some angle, the same radii are extracted and are arranged in descending order. It is observed that the first few radii are same for the same character if rotated at any angle. This gives the rotation invariant character recognition. Further, the characters are normalized with respect to size by dividing the radii by mean radius. The location invariance is obtained by use of centre of gravity. In the proposed algorithm, the different in-variances are considered into the features extraction process such that the normalization of characters is done in all respect. Once the features of different characters are set and are constant for the same object in either form, then that features can be used for character identification purposes.