153 papers indexed here
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This paper explores the concept and potential of parallel gene editing for rapid optimization and adaptation of complex biological systems. The core idea is to leverage the inherent parallelism offered by technologies like CRISPR-Cas9 to simultaneously modify multiple genomic copies. This is then coupled with optimizat...
This paper explores the concept and potential of parallel gene editing for rapid optimization and adaptation of complex biological systems. The core idea is to leverage the inherent parallelism offered by technologies like CRISPR-Cas9 to simultaneously modify multiple genomic copies. This is then coupled with optimizat...
Dynamical Topology Optimization (DTO) provides a framework for optimizing complex network topologies by iteratively refining connections based on emergent properties. This paper introduces a novel algorithm, termed 'Adaptive Topology Evolution', which integrates reinforcement learning and graph theory to achieve automa...
This paper presents a novel approach to modeling phase transitions, specifically focusing on the emergence of control within complex systems. We introduce a dynamic resonance field that evolves in response to the system's state, generating feedback loops that influence the transition process. This mechanism allows for...
This paper presents a novel approach to modeling phase transitions, specifically focusing on the emergence of control within complex systems. We introduce a dynamic resonance field that evolves in response to the system's state, generating feedback loops that influence the transition process. This mechanism allows for...
This paper investigates the application of quantum walks to network security analysis, specifically focusing on graph traversal algorithms for anomaly detection and vulnerability assessment. Traditional graph traversal methods often struggle with the complexity of large and dynamic network topologies. Quantum walks, le...
This paper proposes a novel cryptographic key exchange protocol leveraging concepts inspired by quantum mechanics, specifically superposition and probabilistic exploration, through a graph-based routing mechanism. Traditional key exchange protocols often rely on computationally intensive mathematical problems, making t...
The simulation of quantum systems on classical computers faces significant challenges due to the exponential scaling of computational resources required to accurately represent quantum states and their evolution. This work proposes a novel approach to quantum computing simulation based on graph representation and graph...
This paper proposes a novel approach to distributed edge computing resource scheduling based on consensus mechanisms. Traditional edge computing resource management often suffers from inefficiencies due to manual allocation, lack of real-time adaptability, and limited scalability. This research addresses these limitati...
This paper proposes a novel approach to edge computing resource sharing leveraging blockchain technology. Traditional edge computing platforms often suffer from centralized control, leading to vulnerabilities and a suboptimal utilization of resources. This research introduces a decentralized system where edge computing...
This paper proposes a novel approach to distributed edge computing resource scheduling based on consensus mechanisms. Traditional edge computing resource management often suffers from inefficiencies due to manual allocation, lack of real-time adaptability, and limited scalability. This research addresses these limitati...
The proliferation of Internet of Things (IoT) devices has generated vast amounts of data, presenting significant challenges for centralized processing. Graph Neural Networks (GNNs) have emerged as a powerful tool for analyzing complex, interconnected data, particularly in applications like smart cities, industrial moni...
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