Developing Magnetic Field Maps to Enable the Effective Use of Quantum Magnetometers as a Supplement to Conventional Sensors

This project explores how quantum magnetometers—highly sensitive sensors that detect variations in the Earth’s magnetic field—can enhance positioning systems in urban environments where GPS signals are weak or obstructed. The research involves collecting magnetic field data across selected city areas to create detailed magnetic field maps. These maps will help determine how stable and reliable […]

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Blockchain Smart Contract Vulnerability Detection Using Quantum Convolution Neural Network

The proposed project aims to develop a Quantum Convolutional Neural Network (QCNN)-based approach to detect vulnerabilities in smart contracts, which are critical components of blockchain technology. By leveraging quantum machine learning techniques, the project seeks to enhance the accuracy and efficiency of identifying security threats in smart contracts, such as reentrancy attacks and integer overflows. […]

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Quantum-Hybridized Cloud Integration for Next-Generation Security and Performance

The main goal of this research endeavor is the development of a hybrid cloud infrastructure that incorporates quantum computing techniques into its design in order to increase the security, scalability, and level of usability of existing cloud computing systems. This specifically means integrating the more sophisticated aspects of quantum computing, such as quantum cryptography and […]

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Employing Quantum Machine Learning for Improved Deepfake Audio Detection

This project aims to research and develop on building a real-time deepfake audio detection system that is capable of distinguishing between authentic and spoofed audio voices with the help of Quantum Machine Learning (QML). The primary goal is to identify the limitations of existing classical ML techniques and explore how QML can improve the different […]

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Hybrid Quantum-Classical Image Processing by Merging Enhanced Flexible Qubit Representation for Quantum Images equipped with Probability Distribution (EFQRQI-PD) and Machine Learning for Enhanced Accuracy

Image processing principles and techniques represent a significant advancement in modern technology, offering invaluable contributions to numerous sectors. Despite their efficacy, conventional AI and ML-based image processing algorithms encounter inherent limitations that obstruct their scalability and performance. The main aim of the proposed research project is to develop image processing algorithm based on quantum computing […]

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Design a quantum-safe blockchain using post-quantum cryptography.

Blockchain technology consists of a distributed ledger that operates through a decentralized network of data blocks, sequentially connected and regulated by consensus mechanisms. Initially developed to underpin cryptocurrencies like Bitcoin, broader business and technological sectors now recognize blockchains’ potential applicability across various fields, including healthcare, communication, and smart grids. Blockchains currently rely on established cryptographic […]

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Quantum sensor-based localization system for future urban air mobility

This project is investigation of conventional air vehicle localization using GPS and mobile networks and verification on that their weaknesses in the accurate and seamless localization can be supplemented or strengthened by future quantum sensor-based localization to discover a new blue ocean in the mobility industry.

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Design a post-quantum cryptographic algorithm based on lattice for mitigating quantum computing threats.

Cryptographic algorithms are fundamental tools for securing digital information, with symmetric and asymmetric algorithms serving as the cornerstone of modern encryption techniques. Symmetric algorithms utilize a single key for both encryption and decryption, while asymmetric algorithms employ a pair of keys for these operations. Classical cryptographic algorithms, including RSA and AES, have been extensively utilized […]

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Integrating Deep Learning and Machine Learning Techniques for Maize Yield Monitoring with Earth Observation and Climate Data to Ensure Food Security in Dry Regions

Our project aims to improve maize production efficiency and mitigate the impacts of climate change. By combining advanced computing, artificial intelligence, and remote sensing techniques, we will analyze data on maize cultivation, climate patterns, and soil health. This collaboration between institutions in both countries seeks to enhance agricultural sustainability, increase food security, and contribute valuable […]

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