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Distributed ledger technology for decentralized energy trading – Complete Phd and Masters Thesis

[ad_1] Introduction In recent years, decentralized energy trading has gained significant attention as a means to empower consumers and increase the efficiency of energy markets. Distributed ledger technology, such as blockchain, has emerged as a…

Serverless computing for event-driven architectures – Complete Phd and Masters Thesis

[ad_1] Introduction: Serverless computing is a revolutionary approach to building and deploying applications in the cloud. It allows developers to focus on writing code without having to worry about managing the underlying infrastructure. Event-driven architectures…

Generative adversarial networks for style transfer – Complete Phd and Masters Thesis

[ad_1] Introduction Generative adversarial networks (GANs) have revolutionized the field of artificial intelligence by enabling the generation of highly realistic images, text, and other forms of data. One of the most exciting applications of GANs…

Zero-knowledge succinct non-interactive arguments of knowledge (zk-SNARKs) for privacy-preserving smart contracts – Complete Phd and Masters Thesis

[ad_1] Introduction Privacy-preserving smart contracts have gained significant attention in recent years due to the growing concern over data privacy and security in decentralized applications. Zero-knowledge succinct non-interactive arguments of knowledge (zk-SNARKs) have emerged as…

Federated transfer learning for cross-organization collaboration – Complete Phd and Masters Thesis

[ad_1] Introduction In today’s digital age, organizations are increasingly recognizing the importance of collaboration and knowledge sharing to drive innovation and stay competitive in the market. However, one of the challenges that organizations face when…

Quantum machine learning for quantum chemistry – Complete Phd and Masters Thesis

[ad_1] Introduction: Quantum machine learning is a relatively new and exciting field that combines aspects of quantum mechanics and machine learning to solve complex problems in various domains. In recent years, quantum machine learning has…

Quantum error correction for quantum communication – Complete Phd and Masters Thesis

[ad_1] Introduction Quantum communication has the potential to revolutionize the way we transmit and process information by taking advantage of the unique properties of quantum mechanics. However, quantum systems are inherently susceptible to errors due…

Graph neural networks for protein-protein interaction prediction – Complete Phd and Masters Thesis

[ad_1] Introduction: Protein-protein interactions play a crucial role in various cellular processes and diseases. Understanding the intricate interactions between proteins is essential for drug discovery, disease diagnosis, and treatment. Graph neural networks (GNNs) have emerged…

Federated reinforcement learning for smart manufacturing – Complete Phd and Masters Thesis

[ad_1] Introduction: Federated reinforcement learning is a cutting-edge technique that combines the power of reinforcement learning with the distributed nature of federated learning. This approach has shown immense potential in various domains, including smart manufacturing.…

Transfer learning for cross-lingual information retrieval – Complete Phd and Masters Thesis

[ad_1] Introduction: Transfer learning has emerged as a powerful technique in the field of machine learning, allowing models trained on one task or dataset to be adapted to perform well on another task or dataset.…

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