Defensive Auto-Updatable and Adaptable Bot Recommender System (DAABRS): A New Architecture Approach in Cloud Computing Systems

Khwaldeh, Sufian; Y, Mohit; S, Khushwant

doi:10.1109/hora61326.2024.10550519

2024 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA) 2024

DOI: 10.1109/hora61326.2024.10550519

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Defensive Auto-Updatable and Adaptable Bot Recommender System (DAABRS): A New Architecture Approach in Cloud Computing Systems

Sufian Khwaldeh,

Mohit Y,

Khushwant S

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2025

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Cited by 3 publications

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Responsive e-learning dynamic assessment structure using intelligent learning design

Singh,

Yadav

2025

Gamification and Augmented Reality

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A previously created e-learning model and learning system research have been conducted based on the 'one size fits all' idea. This approach ignores the distinctions between learners and pupils, delivering the same educational content to each one. With the advent of a new R&D style, researchers' and students' demands and preferences will shift. These days, quick e-learning courses come with online videos, audios, and desktop recording capabilities that used to need separate software. In contrast to printed textual lectures, students learn more effectively and enhance their abilities using onscreen instructional materials. As a consequence, there is a need for more adaptable learning and knowledge-based e-learning model assessment. This article focusses mostly on the learner modelling module and illustrates an adaptable model for an e-learning system. Students who are modelling are accountable for meeting this criteria in order to assess the degree of performance of learners in an online learning environment and satisfy specific needs.

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Responsive e-learning dynamic assessment structure using intelligent learning design

Singh,

Yadav

2025

Gamification and Augmented Reality

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Prognosis of artificial intelligence in education

Singh,

Yadav

2025

LatIA

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The Higher Education Institutions require emphasis on disruptive intelligent systems which includes Artificial Intelligence that challenges conventional methods with improved products and services. This study aimed to know the trend artificial intelligence in engineering education. Specifically, it aimed to know the profile of the respondents, know the level of utilization of artificial intelligence tools in engineering education, know if there is significant relationship between profile of respondents to the AI tools used in engineering education, and propose a model of artificial intelligence in engineering education. This paper used quantitative correlational methods of research. Result showed that majority of the respondents has more work experience, found that most teachers have five years or more of experience and found that in terms of educational attainment, majority of the respondents had master’s degree. Artificial intelligence tools are generally “Sometimes Utilized” in engineering education and the respondents' profiles had no significant relationship on the use of the AI technologies, which are often occasionally used in engineering education. To fully utilize AI capabilities in engineering education, the model achieved offers a number of particular actions, including institutional in-house training, awareness campaigns, research conferences, and informal information exchange.

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Design of AI in leadership

Singh,

Yadav

2025

LatIA

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The present research aims to demonstrate the dominance of AI-based technologies over the Leadership sector in Industry 4.0 by combining the two main industries, such as "artificial intelligence" and "leadership." Artificial Intelligence (AI) has had a notable impact on the technical and social working environment due to the growing use of AI-supported technology. In particular, to recognise and address the needs and difficulties faced by leaders in the majority of organisations. The current essay emphasises how crucial leadership is to the adoption and use of AI in business. It has been thought that a thorough examination of the literature studies now in existence would demonstrate the need for AI-supported leadership techniques in businesses. The research divided leadership into four categories: the Process of Strategic Transformation, Competencies and Qualification, Culture, and the Interaction of Human-AI. This division was made based on the analysis of the literature review. The study's findings provide potential paths for further research and growth, as well as a thorough view.

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Defensive Auto-Updatable and Adaptable Bot Recommender System (DAABRS): A New Architecture Approach in Cloud Computing Systems

Cited by 3 publications

References 18 publications

Responsive e-learning dynamic assessment structure using intelligent learning design

Responsive e-learning dynamic assessment structure using intelligent learning design

Prognosis of artificial intelligence in education

Design of AI in leadership

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