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About Us

Nidhi Srivastava

Dr. Nidhi Srivastava is currently working as Assistant Professor at AIIT, Amity University, Lucknow Campus, India and has 18+ yrs of experience. Her research interest areas are HCI, Image Processing, Cloud computing, e-governance and Machine leaning. She has numerous publications in various international/national journals and conferences. She has edited books on Semantic Web and Quantum Computing published in book series Studies in Computational Intelligence, Springer

Publications

Open AI and Computational Intelligence for Society 5.0

As technology rapidly advances, the complexity of societal challenges grows, necessitating intelligent solutions that can adapt and evolve. However, developing such solutions...

Implementation of an AI-Based Chatbot Using Machine Learning Algorithms for Answering and Categorization in Medical Diagnosis and Treatments

Answering frequently asked questions (FAQs) is an important task for many businesses and organizations, but it can be time-consuming and repetitive. Here we present the design...

Enhanced Bone Cancer Detection Using Deep Convolutional Learning Classification From Histopathological Images

The old procedures of the conventional histology process continue to limit pathologists. Bone structure is complex, which makes diagnosis difficult. To improve diagnostic...

Analyze and Optimize the Performance of MRI Images for Tumor Detection Using Image Segmentation With YOLOV7 Algorithm: A Practical Approach

Brain-tumor detection is a very complicated task in the medical domain. The early detection of tumors in patients' lives can provide improved outcomes and a balanced life....

Architecture and Technological Advancements of Education 4.0

Academics 4.0 has become increasingly crucial in recent times due to the impact of Industry 4.0 on various fields. The emergence of disruptive technologies and the cyber-physical...

Assessing the Impact of Student Employability Using Decision Tree Classifier in Education 4.0: An Analysis of Key Factors and Predictive Model Development

After graduation, student employability is a crucial issue that has an impact on people's lives, society, and the economy as a whole. Employers are looking for applicants in...

E-Learning: But Missing Semantics

E-learning is the use of technology to enable people to learn at any time and from anywhere. It is quick, relevant, and ever-changing, and it might include training and the...

Ontology and Description Logic for E-Learning

A semantic web is a web environment in which users and computer agents interact semantically. Users need to put their queries exactly as they want; its goal is to make accurate...

Exploring Provenance for E-Learning Ontologies

The World Wide Web's provenance is an important feature. Provenance is important since it helps in establishing the appropriateness, legitimacy, and faithfulness of...

Enabling Trust in an E-Learning Ontology Through Provenance

E-learning is the acquisition and application of knowledge that is primarily provided and assisted through electronic means. Ontology is the pillar on which the semantic web...