Clinical Gastrointestinal Disease Screening Based on the Bionic Artificial Tentacle Method Background Gastrointestinal diseases display a wide range of complex symptoms globally, such as diarrhea, gastrointestinal bleeding, malabsorption, malnutrition, and even neurological dysfunction. These diseases pose significant health challenges and socioeco...

Discussion on Risk-Sensitive Robot Control Based on Self-Attention Mechanism Research Background The kinematics and dynamics in robot control are key factors to ensure the precise completion of tasks. Most robot control schemes rely on various models to achieve task optimization, scheduling, and priority control. However, the dynamic characteristic...

Research Background In rescue missions, to improve search and rescue efficiency, an emerging solution is the use of a combination of electronic backpacks and insects, known as cyborg insects. These insects combine the advantages of biological and electronic technologies, with additional electronic backpacks used for communication, sensing, and cont...

Using Generative Cellular Automata to Study the Chiral Morphogenesis of Gold Background and Objectives Chirality is ubiquitous in nature and can be transferred and amplified between systems through specific molecular interactions and multi-scale couplings. However, the mechanisms of chiral formation and the critical steps during the growth process ...

Accelerating the Discovery of Ionizable Lipids for mRNA Delivery using Machine Learning and Combinatorial Chemistry Research Background To fully realize the potential of mRNA therapies, it is essential to expand the toolkit of lipid nanoparticles (LNPs). However, a key bottleneck in LNP development is identifying new ionizable lipids. Previous stud...

Academic Report: Advanced Optimal Tracking Integrating Neural Critic Technique for Asymmetric Constrained Zero-Sum Games Background and Research Problem In the field of modern control, game theory is the mathematical model that studies the competition and cooperation between intelligent decision-makers, involving an interaction decision problem wit...

Invisible and Robust Protection Method for Content Generated by Deep Neural Networks Academic Background In recent years, with the revolutionary development and widespread application of deep learning models in engineering applications, phenomenon-level applications such as ChatGPT and DALL⋅E 2 have emerged, profoundly impacting people’s daily live...

Academic Report Background A Knowledge Graph (KG) is structured data that records information about entities and relationships, widely used in question-answering systems, information retrieval, machine reading, and other fields. Knowledge Graph Embedding (KGE) technology maps entities and relationships in the graph into a low-dimensional dense vect...

In recent years, applications such as privacy protection and large-scale data transmission have posed significant challenges to the inaccessibility of data. Researchers have proposed Data-Free Knowledge Distillation (DFKD) methods to address these issues. Knowledge Distillation (KD) is a method for training a lightweight model (student model) to le...

Background and Research Objectives Reinforcement Learning (RL) has recently become a dynamic and transformative field within artificial intelligence, aiming to maximize cumulative rewards through the interaction between agents and the environment. However, the application of RL faces challenges in optimizing the Bellman Error. This error is particu...