Vol. 5 No. 5 (2023): ISJR

Harnessing AI for Sustainable Traffic Management: Enhancing Efficiency, Safety, and Mobility in Smart Cities

Unleashing the Potential of AI in Stock Market Analysis: Enhancing Efficiency, Accuracy, and Decision-Making

AI in Jobs: Embracing Automation, Skills Transformation, and Human-AI Collaboration for the Future of Work

AI in the Next Five Years: Advancements, Applications, and Ethical Considerations

AI in Communication: Transforming Connectivity, Enhancing User Experience, and Addressing Ethical Considerations

AI in Manufacturing: Revolutionizing Efficiency, Quality, and Automation for the Factory of the Future

Towards Sustainable Education: Integrating Environmental and Social Responsibility into the Curriculum

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Enhancing Security in Enterprise Cloud Computing Applications: Concerns and Solutions

Best Practices for Implementing Oracle Cloud ERP Security in Industry

Harnessing the Power of Artificial Intelligence for Enhanced Enterprise Resource Planning

Advancing Cloud Data Analytics and Chatbots through Machine Learning Technology: Key Recommendations

AI-Enabled IoT: Transforming Healthcare Frontiers for Patient-Centric Solutions

Deep Learning Approaches for Anomaly Detection in IoT Sensor Networks

Ethical Implications of AI and ML Integration in IoT Devices: A Comprehensive Review

Enhance banking systems to digitalize using advanced artificial intelligence techniques in emerging markets

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Artificial Intelligence influence in individual investors performance for capital gains in the stock market

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Optimizing Analytics: Integrating Data Warehouses and Lakes for Accelerated Workflows

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Evaluating the Effectiveness of Machine Learning in Phishing Detection

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Data Ethics in AI: Addressing Challenges in Machine Learning and Data Governance for Responsible Data Science

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Scalable Machine Learning: Techniques for Managing Data Volume and Velocity in AI Applications

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Real-Time Anomaly Detection in Industrial IoT Systems Using Hybrid AI Models

Ethical AI Framework for Bias Mitigation in Machine Learning Algorithms

Multi-Modal Deep Learning for Enhanced Emotion Recognition