Aiming at the problem of low detection rate caused by class imbalance and limited detection ability of single model in abnormal traffic detection, an abnormal traffic detection model based on hybrid sampling and deep ...
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In dynamic software development, ensuring high reliability and quality is an important goal. The biggest challenge in this field is the early detection and correction of errors, which if not addressed in time can lead...
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This didactic paper explores topological superconductivity, an essential idea for enhancing topological quantum computing by utilizing Majorana Fermions (Majorana Zero Modes). Topological quantum computing can enable ...
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ISBN:
(纸本)9783031734762;9783031734779
This didactic paper explores topological superconductivity, an essential idea for enhancing topological quantum computing by utilizing Majorana Fermions (Majorana Zero Modes). Topological quantum computing can enable fault-tolerant qubits, which are essential for implementing quantum AI algorithms and related techniques. This paper discusses the basic principles of topological superconductors, their experimental implementations, and the crucial importance of Majorana Fermions in facilitating error-resistant quantum computing. The paper also examines the integration of quantum AI, emphasizing how the stability of topological qubits enhances the performance of quantum machine learning algorithms. It discusses the obstacles and future possibilities of using topological states for quantum technologies, focusing on engineering applications and recent technical advancements. The study highlights the potential of topological superconductivity to transform quantum computing by providing insight into the creation of reliable quantum systems and scalable quantum circuits.
Automatically describing the content of a picture with meaningful and contextually appropriate textual descriptions is a difficult challenge at the interface of computer vision and natural language processing. This re...
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The paper explores the complexities of personalized breast cancer treatment, by integration of multi-omics data, clinical data, and advanced computational tools. The heterogeneous nature of breast cancer causes challe...
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In the field of medical imaging, prompt and precise brain tumor identification is critical for efficient treatment planning and better patient outcomes. The goal of this project is to improve diagnostic skills by crea...
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Blind symbol rate estimation is crucial for adaptive communication systems and cognitive radios. This paper presents a novel approach to tackle blind symbol rate estimation from received complex baseband signals. The ...
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Accurate wind power forecasting is crucial for grid stability and renewable energy integration, but existing methods struggle to capture complex temporal dependencies in wind data. This paper introduces Collaborative ...
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As techniques and tools for synthetic media and Deepfakes continue to advance, it is increasingly clear that video, audio and images can no longer be relied upon as truthful recordings of reality. Every digital commun...
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This research investigates the application of Random Forest algorithms to enhance disease prediction within healthcare analytics. Using large healthcare datasets, the research compares Random Forests to other machine ...
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