In recent years,the application of various advanced technologies,such as digitization and informatization,has become the primary tool for innovation in education and teaching.For traditional single-chip microcomputer ...In recent years,the application of various advanced technologies,such as digitization and informatization,has become the primary tool for innovation in education and teaching.For traditional single-chip microcomputer course teaching,it is necessary to emphasize the introduction and application of high-tech innovations in its path of innovative development.This course is a typical representative of multidisciplinary teaching,involving multiple disciplines such as electronic engineering,automation,and computer science.In response to issues faced in traditional teaching,such as rigid organization of teaching content that struggles to keep pace with technological advancements,resulting in a noticeable lag in knowledge transfer,and monotonous teaching methods that fail to precisely meet the diverse learning needs of students,analyzing the innovative applications of this course under the empowerment of AI technology holds significant practical relevance.In this regard,the study relies on AI technology empowerment to analyze the application paths for the deep integration of AI technology and single-chip microcomputer courses,constructing a new teaching model to provide references for enhancing teaching quality and stimulating students’innovative potential.展开更多
In recent years,research on industrial innovation and development has primarily focused on industrial automation and intelligent manufacturing.Within the field of integrating mechatronics and intelligent control,analy...In recent years,research on industrial innovation and development has primarily focused on industrial automation and intelligent manufacturing.Within the field of integrating mechatronics and intelligent control,analyzing the efficient control of mechatronic systems enabled by generative AI for single-chip microcomputers can further highlight the value and significance of promoting AI technology applications.This paper examines the technical characteristics of generative AI in data generation,multimodal fusion,and dynamic adaptation,proposing lightweight model deployment strategies that compress large generative models to a range compatible with single-chip microcomputers,ensuring local real-time inference capabilities.It constructs an edge intelligent control architecture,enabling generative AI to directly participate in decision-making instruction generation,forming a new working system of perception,decision-making,and execution.Additionally,it designs a collaborative optimization training mechanism that leverages federated learning to overcome single-machine data limitations and enhance model generalization performance.At the application level,an intelligent fault prediction system is developed for early identification of equipment anomalies,an adaptive parameter optimization module is constructed for dynamically adjusting control strategies,and a multi-device collaborative scheduling engine is established to optimize production processes,providing technical support for embedded intelligent control in Industry 4.0 scenarios.展开更多
文摘为了评价PIC猪的胴体性状和肉质性状,试验屠宰了健康的PIC猪9头,测定了其胴体性状、肉质性状和肌肉成分等相关指标,并分析了各性状间的相关性。结果表明,宰前活重为123.78 kg的PIC猪,屠宰率为75.58%,瘦肉率为60.8%,平均背膘厚25.62 mm,眼肌面积45.95 cm 2,滴水损失2.14%,嫩度43.56N,肌内脂肪含量2.23%,总氨基酸含量20.3%,饱和脂肪酸含量41.54%,总不饱和脂肪酸含量58.44%。性状间相关性分析表明,PIC猪的宰前活重与屠宰率呈显著正相关(P<0.05),肌内脂肪与MUFA呈极显著正相关(P<0.01),与PUFA呈极显著负相关(P<0.01),与水分呈显著负相关(P<0.05)。肌内脂肪与水分间的相关系数为-0.718,二者间线性模型Y=-0.9985x+75.299,决定系数R^(2)为0.5153。
基金Single-Chip Microcomputer and Interface Technology Project(Project No.:SYSJ2025032)。
文摘In recent years,the application of various advanced technologies,such as digitization and informatization,has become the primary tool for innovation in education and teaching.For traditional single-chip microcomputer course teaching,it is necessary to emphasize the introduction and application of high-tech innovations in its path of innovative development.This course is a typical representative of multidisciplinary teaching,involving multiple disciplines such as electronic engineering,automation,and computer science.In response to issues faced in traditional teaching,such as rigid organization of teaching content that struggles to keep pace with technological advancements,resulting in a noticeable lag in knowledge transfer,and monotonous teaching methods that fail to precisely meet the diverse learning needs of students,analyzing the innovative applications of this course under the empowerment of AI technology holds significant practical relevance.In this regard,the study relies on AI technology empowerment to analyze the application paths for the deep integration of AI technology and single-chip microcomputer courses,constructing a new teaching model to provide references for enhancing teaching quality and stimulating students’innovative potential.
基金Single-Chip Microcomputer and Interface Technology Project(Project No.:SYSJ2025032)。
文摘In recent years,research on industrial innovation and development has primarily focused on industrial automation and intelligent manufacturing.Within the field of integrating mechatronics and intelligent control,analyzing the efficient control of mechatronic systems enabled by generative AI for single-chip microcomputers can further highlight the value and significance of promoting AI technology applications.This paper examines the technical characteristics of generative AI in data generation,multimodal fusion,and dynamic adaptation,proposing lightweight model deployment strategies that compress large generative models to a range compatible with single-chip microcomputers,ensuring local real-time inference capabilities.It constructs an edge intelligent control architecture,enabling generative AI to directly participate in decision-making instruction generation,forming a new working system of perception,decision-making,and execution.Additionally,it designs a collaborative optimization training mechanism that leverages federated learning to overcome single-machine data limitations and enhance model generalization performance.At the application level,an intelligent fault prediction system is developed for early identification of equipment anomalies,an adaptive parameter optimization module is constructed for dynamically adjusting control strategies,and a multi-device collaborative scheduling engine is established to optimize production processes,providing technical support for embedded intelligent control in Industry 4.0 scenarios.
