汽车除雾过程中,手动操作除雾按钮易导致驾驶员分心,针对此问题设计了基于STM32的自动除雾控制系统。首先,进行自动除雾控制系统的总体设计,包括设计自动除雾的功能、总体架构和除雾方案;然后,进行硬件选型研究,设计了以STM32芯片为核...汽车除雾过程中,手动操作除雾按钮易导致驾驶员分心,针对此问题设计了基于STM32的自动除雾控制系统。首先,进行自动除雾控制系统的总体设计,包括设计自动除雾的功能、总体架构和除雾方案;然后,进行硬件选型研究,设计了以STM32芯片为核心的硬件电路原理图,开发了自动除雾控制系统的主程序、模数(analog-to-digital,AD)转换采集程序以及控制器局域网(controller area network,CAN)总线通信程序;最后,利用LabVIEW开发出数据监控界面,可实时监控系统运行状态。实验结果表明:该自动除雾控制系统性能可靠,数据精准,可长时间稳定运行。展开更多
The brain's extracellular matrix(ECM),which is comprised of protein and glycosaminoglycan(GAG)scaffolds,constitutes 20%-40% of the human brain and is considered one of the largest influencers on brain cell functio...The brain's extracellular matrix(ECM),which is comprised of protein and glycosaminoglycan(GAG)scaffolds,constitutes 20%-40% of the human brain and is considered one of the largest influencers on brain cell functioning(Soles et al.,2023).Synthesized by neural and glial cells,the brain's ECM regulates a myriad of homeostatic cellular processes,including neuronal plasticity and firing(Miyata et al.,2012),cation buffering(Moraws ki et al.,2015),and glia-neuron interactions(Anderson et al.,2016).Considering the diversity of functions,dynamic remodeling of the brain's ECM indicates that this understudied medium is an active participant in both normal physiology and neurological diseases.展开更多
针对不同品种花卉生长环境参数的需求不同以及用户存在无法远程实时监测花卉的生长状态和管理不到位情况,论文设计了一套低功耗的花卉智能监控管理系统,通过采用了最小二乘支持向量机(Least Squares Support Veotor Mashine,LSSVM)来预...针对不同品种花卉生长环境参数的需求不同以及用户存在无法远程实时监测花卉的生长状态和管理不到位情况,论文设计了一套低功耗的花卉智能监控管理系统,通过采用了最小二乘支持向量机(Least Squares Support Veotor Mashine,LSSVM)来预测温湿度,根据预测的温湿度实现不同品种花卉精准滴灌、光照补偿和施肥。同时环境数据使用本地SQlite轻量级数据库进行保存,远端数据借助服务器进行缓存,农业工作者根据各项环境数据曲线分析花卉生长趋势,为农业管理者提供可靠的理论依据和实践指导。展开更多
随着科技的飞速发展,现代社会逐渐趋向智能化,智能小车和智能机器人的发展前景越来越广阔,本设计开发了基于STM32f103C8T6微控制器的智能循迹避障小车。以STM32芯片作为核心控制单元,充分利用其高性能、低功耗以及丰富的外设接口等优势...随着科技的飞速发展,现代社会逐渐趋向智能化,智能小车和智能机器人的发展前景越来越广阔,本设计开发了基于STM32f103C8T6微控制器的智能循迹避障小车。以STM32芯片作为核心控制单元,充分利用其高性能、低功耗以及丰富的外设接口等优势来实现小车的各项功能。对于避障功能,通过搭载超声波传感器、红外传感器等多种类型的距离检测传感器,实时感知小车周围环境中的障碍物信息。运用PID算法对传感器采集的数据进行处理分析,使小车能够在行进过程中及时检测到前方、侧方等潜在障碍物,并自主做出合理的避障决策,例如改变行驶方向或者暂停运动,确保小车安全且平稳地运行。本设计结合了嵌入式系统开发、传感器技术以及无线通信技术,经过实际测试验证,小车可有效实现无线智能控制与避障功能,具备一定的实用价值和应用前景,可广泛应用于智能家居、仓储物流巡检等诸多领域。With the rapid development of science and technology, modern society is gradually becoming more intelligent. The development prospects of intelligent cars and intelligent robots are getting broader. This design develops an intelligent line-following and obstacle-avoiding car based on the STM32f103C8T6 microcontroller. Taking the STM32 chip as the core control unit, it fully utilizes its advantages such as high performance, low power consumption, and rich peripheral interfaces to achieve various functions of the car. For the obstacle-avoiding function, by installing multiple types of distance detection sensors, such as ultrasonic sensors and infrared sensors, it can perceive the obstacle information in the surrounding environment of the car in real-time. The PID algorithm is used to process and analyze the data collected by the sensors, enabling the car to detect potential obstacles in the front, side, and other directions promptly during the driving process and make reasonable obstacle-avoiding decisions independently, such as changing the driving direction or pausing movement, to ensure the safe and stable operation of the car. This design combines embedded system development, sensor technology, and wireless communication technology. Through practical tests, the car can effectively achieve wireless intelligent control and obstacle-avoiding functions, has certain practical value and application prospects, and can be widely applied in many fields, such as smart home, warehousing logistics inspection.展开更多
文摘汽车除雾过程中,手动操作除雾按钮易导致驾驶员分心,针对此问题设计了基于STM32的自动除雾控制系统。首先,进行自动除雾控制系统的总体设计,包括设计自动除雾的功能、总体架构和除雾方案;然后,进行硬件选型研究,设计了以STM32芯片为核心的硬件电路原理图,开发了自动除雾控制系统的主程序、模数(analog-to-digital,AD)转换采集程序以及控制器局域网(controller area network,CAN)总线通信程序;最后,利用LabVIEW开发出数据监控界面,可实时监控系统运行状态。实验结果表明:该自动除雾控制系统性能可靠,数据精准,可长时间稳定运行。
基金supported by National Institute on Aging(NIH-NIA)R21 AG074152(to KMA)National Institute of Allergy and Infectious Diseases(NIAID)grant DP2 AI171150(to KMA)Department of Defense(DoD)grant AZ210089(to KMA)。
文摘The brain's extracellular matrix(ECM),which is comprised of protein and glycosaminoglycan(GAG)scaffolds,constitutes 20%-40% of the human brain and is considered one of the largest influencers on brain cell functioning(Soles et al.,2023).Synthesized by neural and glial cells,the brain's ECM regulates a myriad of homeostatic cellular processes,including neuronal plasticity and firing(Miyata et al.,2012),cation buffering(Moraws ki et al.,2015),and glia-neuron interactions(Anderson et al.,2016).Considering the diversity of functions,dynamic remodeling of the brain's ECM indicates that this understudied medium is an active participant in both normal physiology and neurological diseases.
文摘针对不同品种花卉生长环境参数的需求不同以及用户存在无法远程实时监测花卉的生长状态和管理不到位情况,论文设计了一套低功耗的花卉智能监控管理系统,通过采用了最小二乘支持向量机(Least Squares Support Veotor Mashine,LSSVM)来预测温湿度,根据预测的温湿度实现不同品种花卉精准滴灌、光照补偿和施肥。同时环境数据使用本地SQlite轻量级数据库进行保存,远端数据借助服务器进行缓存,农业工作者根据各项环境数据曲线分析花卉生长趋势,为农业管理者提供可靠的理论依据和实践指导。
文摘随着科技的飞速发展,现代社会逐渐趋向智能化,智能小车和智能机器人的发展前景越来越广阔,本设计开发了基于STM32f103C8T6微控制器的智能循迹避障小车。以STM32芯片作为核心控制单元,充分利用其高性能、低功耗以及丰富的外设接口等优势来实现小车的各项功能。对于避障功能,通过搭载超声波传感器、红外传感器等多种类型的距离检测传感器,实时感知小车周围环境中的障碍物信息。运用PID算法对传感器采集的数据进行处理分析,使小车能够在行进过程中及时检测到前方、侧方等潜在障碍物,并自主做出合理的避障决策,例如改变行驶方向或者暂停运动,确保小车安全且平稳地运行。本设计结合了嵌入式系统开发、传感器技术以及无线通信技术,经过实际测试验证,小车可有效实现无线智能控制与避障功能,具备一定的实用价值和应用前景,可广泛应用于智能家居、仓储物流巡检等诸多领域。With the rapid development of science and technology, modern society is gradually becoming more intelligent. The development prospects of intelligent cars and intelligent robots are getting broader. This design develops an intelligent line-following and obstacle-avoiding car based on the STM32f103C8T6 microcontroller. Taking the STM32 chip as the core control unit, it fully utilizes its advantages such as high performance, low power consumption, and rich peripheral interfaces to achieve various functions of the car. For the obstacle-avoiding function, by installing multiple types of distance detection sensors, such as ultrasonic sensors and infrared sensors, it can perceive the obstacle information in the surrounding environment of the car in real-time. The PID algorithm is used to process and analyze the data collected by the sensors, enabling the car to detect potential obstacles in the front, side, and other directions promptly during the driving process and make reasonable obstacle-avoiding decisions independently, such as changing the driving direction or pausing movement, to ensure the safe and stable operation of the car. This design combines embedded system development, sensor technology, and wireless communication technology. Through practical tests, the car can effectively achieve wireless intelligent control and obstacle-avoiding functions, has certain practical value and application prospects, and can be widely applied in many fields, such as smart home, warehousing logistics inspection.
