In recent years, quadruped robots have received many attention due to excellent adaptability in complex terrains,and the key to their stable locomotion lies in gait coordination. But,the traditional central pattern generator (CPG) models often face challenges such as high reliance on manual experience for tuning coupling parameters and poor adaptive capability. To address this problem, this study proposes a control method integrating coupling dynamics modeling and intelligent optimization. And,a four-leg coupling dynamics model based on Hopf nonlinear oscillator is constructed, in which coupling matrix describes inter-leg phase relationships. The matrix is automatically optimized by incorporating a genetic algorithm and implementing global search with a phase synchronization stability metric as the fitness function. Simulation results show that the optimized coupling parameters significantly improve the phase coordination ability of the four-leg oscillators. This effective eliminates phase deviations under natural dynamics, and greatly enhances both gait synchrony and stability.And so,the study contributes to the autonomous adaptability of quadruped robots by providing a data-driven global optimization framework for their gait control.\

In the digital economy, traditional software engineering faces complex needs and fast change, and it often meets risks such as cost overruns and low process efficiency. AI methods, including machine learning and natural language processing, provide strong support for a more intelligent form of development. This paper reviews the path of AI use in software work through literature study and real cases, and it covers tasks from requirement analysis to testing and operation. The findings show a shift from a simple helper to a driver of the whole process, and cases from many fields report higher efficiency and better quality. Yet several problems remain, such as weak model transparency, unstable data, and a lack of skilled staff. It presents a framework and guides firms toward high-quality growth globally.

This study takes Duolingo as a case study and, drawing on Second Language Acquisition (SLA) theories, examines the role of language-learning applications in the construction of a systematic language learning framework. It systematically analyzes the impact of interface interaction design on second language learning processes. Through an examination of Duolingo’s User Interface Design principles, learning task organization, and interactive feedback mechanisms, this study summarizes the app’s strengths in facilitating language input, enhancing learners’ attentional focus, and sustaining learning motivation. The study further identifies several limitations of Duolingo, including insufficient systematic representation for less commonly taught languages, limited support for productive skills, and a lack of coherence in learning pathways. Overall, this research provides theoretical insights for interface design and curriculum development in language-learning applications.