Faculty Publications

Permanent URI for this communityhttp://192.168.24.11:4000/handle/123456789/7

Scholarly Publications by Integral Academia

Browse

Filters

20247

Settings

Start date: 2024Subject: search.filters.subject.Artificial Intelligence

Search Results

Now showing 1 - 7 of 7
  • Thumbnail Image
    Item
    The Evolution of Artificial Intelligence from Philosophy to New Frontier
    (Bentham Science, 2024) Manisha Singh, Arbind K Jha, Tameena Khan, Saman Raza
    In an era characterized by significant technical advancements in the field of Artificial Intelligence (AI), it is crucial to comprehend AI by considering its origins and future prospects. This chapter examines the historical origins of artificial intelligence (AI) and explores its relationship with philosophy. It also delves into the significant inquiries that philosophy poses regarding AI, encompassing its metaphysical, epistemological, and axiological dimensions. The chapter additionally provides an overview of the historical context of artificial intelligence (AI), its various manifestations, its theoretical underpinnings, and a framework that establishes a correlation between humans and machines, referred to as “Human-machine Teamwork.” The chapter also explores the importance of AI in several fields and illuminates emerging areas where artificial intelligence is also examined, giving rise to significant inquiries. The objective of this chapter is to offer comprehensive knowledge and a fresh viewpoint on the examination of AI by its users, producers, and designers.
  • Thumbnail Image
    Item
    Artificial Intelligence: A multidisciplinary approach towards teaching-learning
    (Bentham Science, 2024) Tahmina Khan, Manisha Singh, Saman Raza
    As we stand on the brink of the Fourth Industrial Revolution, AI has revolutionized and acted as a transformative force in redefining and reshaping industries, economies, and perhaps most significantly, education. The andscape of education is positioned for a paradigm shift with the infusion of AI. This book delves into the absorbing connection of AI and the teaching learning process, exploring this constantly evolving association that has the potential to impact educators and learners in a way that is productive for them. The book is a compilation of 11 chapters from the contribution of different experts in their areas and therefore covers a rich account of insights, new frontiers, and collaboration across disciplines. Each chapter is constructed to be self-contained, permitting readers to dive in and out as per their own understanding. The book begins with an introduction to AI, its roots in philosophy, its application in different disciplines, and most importantly an analysis of AI from the perspective of philosophy. The subsequent chapters will cover a spectrum of topics, which are constructed in a way that each chapter draws upon insights from various fields including biological science, physical sciences, mathematics, languages, environmental science, bio-informatics, chemical science, education, and research. The book examines the theoretical underpinnings of AI-assisted teaching-learning in different disciplines, explores the latest technological advancements, and offers practical strategies for integrating AI into the classroom. The chapters delve deeper, delivering a comprehensive in-depth analysis of the multi-faceted connection between AI and the teaching-learning process of different disciplines. Our aim is to provide a rich tapestry of insights to educators, researchers, policymakers, and students, while encouraging cross-disciplinary dialogue and collaboration. We hope to empower stakeholders to harness the potential of technology while addressing the challenges it presents by fostering a deeper understanding of AI's impact on teaching and learning.
  • Thumbnail Image
    Item
    Artificial Intelligence Scale
    (National Psychological Corporation, 2024) Huma Naz
    The Artificial Intelligence Scales measure the usage of AI (Artificial Intelligence). It is basically used for research purposes. This tool is developed for secondary school students of CBSE, ICSE, and U.P. boards. It consists of 31 items on a 5-point Likert scale and measures dimensions. The age range is from 08 to 15 years and is available in English and Hindi language.
  • Thumbnail Image
    Item
    Artificial Intelligence Integration with student school adjustment: A balance Act
    (STUDENT PRESS, South India Book Traders, 2024) Huma Naz
    Students studied in exclusive ways. Some decide on facts, facts, and experiments, whereas others option for ideas and theories. Artificial Intelligence methods are seemed as precious gear, as they have the potential to broaden and mirror the choice-making process adopted through human beings. There are numerous Artificial Intelligence techniques that have been utilized in adaptive academic structures. Here, Artificial Intelligence based totally device is advanced that takes into consideration a couple of learning style models and multiple Artificial Intelligence techniques for determining college students’ mastering styles. This machine may be deployed each in e-mastering and conventional academic environments to impart adaptive education. The present study focused on the use of Artificial Intelligence of Secondary School Students in relation to School Adjustment. This study is descriptive survey type in nature. The main reason behind this is the curriculum of the boards. All boards have different pattern of content presentation. During Covid-19 pandemic every student whether it is boy and girl is getting their education through online mode. In every project and exam all are using Artificial Intelligence where as many girls were not using mobile phone to full utilize of teaching and learning. The students have different level of School Adjustment due to boards. One of reasons is that lack of boards. One of the reasons is that lack of digital resources. When the comparison was made on the basis of their gender, the present study released that the gender played a significant role on the use of Artificial Intelligence. It makes education easy in this difficult time. It is based on learning by doing. From the findings it may interrupted that gender of students feel more comfortable and engaged in school. Location is also played a significant difference between the students of rural and urban areas, many problems come in rural areas. This study shows that less school adjustment is found in rural students as compared to urban students because there is difference between two environments. The correlation study was also employed in the present research work.
  • Thumbnail Image
    Item
    Technological Advancements And Quality Of Education
    (CIRS PUBLICATION, 2024) PRIYANSHI GUPTA
  • Thumbnail Image
    Item
    Detection of Rheumatoid Arthritis Using CNN by Transfer Learning
    (Springer, Singapore, 2024) Afroj Alam, Muhammad Kalamuddin Ahamad, K. O. Mohammed Aarif , Taushif Anwar
    Rheumatoid arthritis (RA) represents a long-term autoimmune condition marked by joint inflammation, resulting in discomfort and distortions of the joint structure. Early and accurate detection of RA plays a pivotal role in managing the disease and preventing irreversible joint damage. In this study, we propose a novel approach for detecting Rheumatoid Arthritis through the utilization of Convolutional Neural Networks (CNN) employing transfer learning. Our methodology leverages pre-trained CNN architectures to extract hierarchical features from medical images, particularly X-ray images of affected joints. Transfer learning enables the model to capitalize on the knowledge learned from large and diverse datasets, enhancing its ability to discriminate between healthy and RA-affected joints even with limited labeled data. Fine-tuning of the pre-trained model is performed to adapt the network to the specific characteristics of RA-related features. We present a comprehensive evaluation of our approach using a dataset consisting of X-ray images from both RA patients and healthy individuals. The experimental results showcase the effectiveness of our CNN-based transfer learning method in accurately detecting RA. The outcomes of this research have significant implications for early diagnosis and management of RA. By harnessing the power of deep learning and transfer learning, our approach contributes to the development of a non-invasive and efficient tool for RA detection, which can aid healthcare practitioners in making informed decisions and improving patient outcomes.
  • Thumbnail Image
    Item
    Revisiting Digital India 2.0: Exploring New Horizon and Insights
    (IGI Global, 2024) Farheen Zehra; Farhina Sardar Khan; Syed Shahid Mazhar; Ambrina Sardar Khan
    Technology has become a crucial part of people's lives. Digitization has become essential for its seamless communication and omnipresent access to information. This chapter delves into the transformative landscape of technology and its impact on India's digital progression. This topic encapsulates a diverse range of facets essential for understanding the ever-evolving digital paradigm in the country. It aims to provide new insights into innovative advancements and the potential for growth in various sectors. This chapter is an in-depth examination of complex technological advancements that have been and will continue to change India's socioeconomic landscape. The report covers integrating emerging and disruptive technologies, such as artificial intelligence, machine learning, blockchain, and the internet of things (IoT), in various domains. This chapter illustrates the profound transformation held in various segments, namely, digital technology, online infrastructure, internet connectivity, smart cities, digital literacy, knowledge-driven economy and e-services