Vol. 2 No. 4 (2024)

Articles

• Optimization of Renewable Energy Systems Using Computational Methods

  Adrian Garcia, Dana King, Drew Garcia

  40-54

  • Optimization of Renewable Energy Systems Using Computational Methods

• Enhancing Data Integrity in Cloud Computing through Intelligent Redundancy Management

  Ashley Collins, Nico Collins, Casey Hall

  155-169

  • Enhancing Data Integrity in Cloud Computing through Intelligent Redundancy Management

• Enhancing Cybersecurity Protocols with Computational Intelligence

  Sam Anderson, Dana Parker, Kai Lee

  4-19

  • Enhancing Cybersecurity Protocols with Computational Intelligence

• A Comparative Analysis of Quantum-inspired Algorithms for Optimizing Machine Learning Models

  Kim Phillips, Kim Thompson, Henry Brown, Jordan Lopez

  120-134

  • A Comparative Analysis of Quantum-inspired Algorithms for Optimizing Machine Learning Models

• Adaptive Quantum-Inspired Algorithms for Efficient Resource Allocation in Cloud Computing Environments

  Kai Brown, Jesse Miller, Pat Davis, Jacob Edwards

  245-259

  • Adaptive Quantum-Inspired Algorithms for Efficient Resource Allocation in Cloud Computing Environments

• Edge Computing: Enhancing IoT Applications with Real-Time Data Processing

  Pat Robinson, Adrian Miller, Dana Gonzalez

  85-104

  • Edge Computing: Enhancing IoT Applications with Real-Time Data Processing

• A Comparative Analysis of Quantum-Inspired Algorithms for Enhanced Optimization in High-Dimensional Spaces

  Taylor Young, Quinn Perez, Chris Williams, Alex Robinson

  205-224

  • A Comparative Analysis of Quantum-Inspired Algorithms for Enhanced Optimization in High-Dimensional Spaces

• The Role of Machine Learning in Climate Modeling

  Sam Hall, Kim Brown, Casey Edwards

  55-69

  • The Role of Machine Learning in Climate Modeling

• A Novel Technical Framework for Enhancing Quantum Computing Efficiency through Adaptive Algorithmic Optimizations

  Jamie Parker, Nico Jones, Avery Anderson, Chris Martinez

  170-184

  • A Novel Technical Framework for Enhancing Quantum Computing Efficiency through Adaptive Algorithmic Optimizations

• Machine Learning Techniques for Computational Fluid Dynamics

  George Jackson, Kim Taylor, Casey Allen

  20-39

  • Machine Learning Techniques for Computational Fluid Dynamics

• Deterministic Algorithmic Approaches to Cyber-Physical System Synchronization Challenges in Quantum Computing

  Sam Thomas, Skyler Walker, Sam White

  135-154

  • Deterministic Algorithmic Approaches to Cyber-Physical System Synchronization Challenges in Quantum Computing

• A Case Study on Quantum-Dot Cellular Automata Based Logic Design for Ultra-Low Power VLSI Circuits

  Jordan Evans, Ruby Smith, Riley Hill, Riley Scott

  105-119

  • A Case Study on Quantum-Dot Cellular Automata Based Logic Design for Ultra-Low Power VLSI Circuits

• A Paradigm Shift in Algorithmic Fairness: A Critical Re-evaluation of Theoretical Constructs and Practical Applications

  Jamie Young, Kai Turner, Kai White

  225-244

  • A Paradigm Shift in Algorithmic Fairness: A Critical Re-evaluation of Theoretical Constructs and Practical Applications

• Quantum Computing Applications in Machine Learning

  Pat King, Edward Martin, Chris Carter

  70-84

  • Quantum Computing Applications in Machine Learning

• Empirical Analysis of Hybrid Quantum-Classical Algorithms for Optimization Problems in Large-Scale Machine Learning

  Sam Williams, Skyler Hernandez, Avery Hill, Kai Harris

  185-204

  • Empirical Analysis of Hybrid Quantum-Classical Algorithms for Optimization Problems in Large-Scale Machine Learning