Using Physics Simulations to Find Targeting Strategies in Competitive Tenpin Bowling

Academic Background Bowling is one of the most popular sports in the United States, with over 45 million people regularly participating as of 2017. With millions of dollars at stake in national competitions each year, improving player scores has become a research focus. However, due to the complexity of calculations and the numerous variables affec...

ShockFluidX: A Novel OpenFOAM-Based Modular Solver for High-Speed Flows

Academic Background Hypersonic technology is a critical research direction in the aerospace field, with applications spanning national defense, space launch, and ultra-high-speed commercial aviation. With the rapid development of Computational Fluid Dynamics (CFD) technology, high-fidelity CFD simulations play an increasingly important role in the ...

Scaling of Hardware-Compatible Perturbative Training Algorithms

With the rapid development of artificial intelligence (AI) technology, artificial neural networks (ANNs) have achieved significant success in multiple fields. However, traditional neural network training methods—especially the backpropagation algorithm—face numerous challenges in hardware implementation. Although the backpropagation algorithm is ef...

2D Material Integrated Photonics: Toward Industrial Manufacturing and Commercialization

Academic Background With the advent of the information age, integrated circuits (ICs) have become the driving force behind technological advancements. However, traditional integrated photonics platforms, such as silicon and silicon nitride, face numerous limitations in material properties. For instance, silicon’s indirect bandgap restricts its use ...

Fast Machine Learning for Building Management Systems

Academic Background With the intensification of the global energy crisis and the increasing awareness of environmental protection, the intelligence and efficiency of Building Management Systems (BMS) have become a focal point in both academia and industry. Traditional BMS relies on rule-based control methods, which are unable to dynamically adapt t...

Enhancing Decentralized Energy Storage Investments with Artificial Intelligence-Driven Decision Models

Academic Background As the global energy structure transitions towards renewable energy, the importance of decentralized energy storage is becoming increasingly prominent. Unlike traditional centralized energy storage systems, decentralized energy storage localizes the energy production and storage processes, reducing the risk of large-scale system...

Power Aggregation Operators Based on Aczel-Alsina T-Norm and T-Conorm for Intuitionistic Hesitant Fuzzy Information and Their Application to Logistics Service Provider Selection

Academic Background In modern supply chain management, the selection of logistics service providers is a complex and critical issue. Enterprises need to evaluate and choose third-party organizations capable of efficiently managing and executing logistics tasks. However, the decision-making process in reality often involves significant uncertainty a...

A Systematic Survey of Hybrid ML Techniques for Predicting Peak Particle Velocity (PPV) in Open-Cast Mine Blasting Operations

Blasting operations in open-cast mines are crucial for mineral extraction but also come with significant environmental and structural risks. The peak particle velocity (PPV) generated during blasting is a key metric for assessing the impact of blasting vibrations on surrounding structures and the environment. Accurate PPV prediction is essential fo...

Pythagorean Linguistic Information-Based Green Supplier Selection Using Quantum-Based Group Decision-Making Methodology and the MULTIMOORA Approach

With the increasing severity of global environmental issues, companies are placing greater emphasis on green and sustainable development in supply chain management. Green Supply Chain Management (GSCM) has become a crucial means for enterprises to enhance competitiveness and achieve sustainable development. However, Green Supplier Selection (GSS) i...

A Comprehensive Review of Machine Learning Applications for Internet of Nano Things: Challenges and Future Directions

Academic Background In recent years, the rapid development of nanotechnology and the Internet of Things (IoT) has given rise to a revolutionary field—the Internet of Nano Things (IoNT). The IoNT connects nanoscale devices to the internet, enabling them to play significant roles in areas such as agriculture, military, multimedia, and healthcare. How...