With the rapid development of artificial intelligence (AI) technologies, deep learning has made significant progress in complex tasks. However, the success of deep learning largely relies on massive amounts of labeled data, and the data labeling process is not only time-consuming and labor-intensive but also requires specialized domain knowledge, m...
Research on Programmable Shape Optimization and Deformation Problems: Development and Application of the Morpho Environment Academic Background Soft materials play a crucial role in the fields of science and engineering, particularly in areas such as soft robotics, structured fluids, biological materials, and particulate media. These materials unde...
Research Report on the Spatiotemporal Style Transfer Algorithm for Dynamic Visual Stimulus Generation Academic Background The encoding and processing of visual information has been a significant focus in the fields of neuroscience and vision science. With the rapid development of deep learning techniques, investigating the similarities between arti...
Research on Weighted Network Randomization Based on Simulated Annealing Algorithm Background Introduction In the field of neuroscience, connectomics is an important branch for studying the structure and function of brain neural networks. With the development of modern imaging technologies, researchers are able to acquire a wealth of biologically me...
Introduction In recent years, solving partial differential equations (PDEs) using numerical methods has played a significant role in various fields such as engineering and medicine. These methods have shown remarkable effectiveness in applications like topology and design optimization as well as clinical prognostication. However, the high computati...
Research Based on Genotype Representation Graph (GRG): A New Framework to Enhance Biobank-Scale Data Analysis Efficiency Academic Background and Research Motivation With the rapid advancement of sequencing technologies, the collection of large-scale genomic data has become increasingly common, especially in the field of human disease association st...
Predicting the Emergence of Crystals from Amorphous Precursors: Deep Learning Empowers Breakthroughs in Materials Science Background Introduction The process of crystallization from amorphous materials holds significant importance in both natural and laboratory settings. This phenomenon is widespread in various processes ranging from geological to ...
Can Large Language Models Tackle Misinformation? — In-Depth Research on LLMs In today’s digital era of rapid information dissemination, the spread of misinformation and fake news has become a significant societal challenge. The widespread use of the internet and social media has dramatically lowered the barriers to information sharing, enabling any...
In-Depth Exploration of Sector-Based Pairs Trading Strategies and Innovative Pair Selection Techniques Background and Research Objectives Pairs Trading Strategy (PTS) is a widely used financial arbitrage strategy that leverages the relative performance of two highly correlated stocks to profit from temporary price deviations. The core concept of tr...
A Research Report on a New Framework for Solving Migrant Resettlement Using Multiobjective Evolutionary Optimization Against the backdrop of accelerated globalization and evolving socio-economic conditions, migration has become an undeniable global trend. From the perspective of humanitarian relief or the sustainable development of a globalized eco...