The act of transmitting photos via the Internet has become a routine and significant activity.Enhancing the security measures to safeguard these images from counterfeiting and modifications is a critical domain that c...The act of transmitting photos via the Internet has become a routine and significant activity.Enhancing the security measures to safeguard these images from counterfeiting and modifications is a critical domain that can still be further enhanced.This study presents a system that employs a range of approaches and algorithms to ensure the security of transmitted venous images.The main goal of this work is to create a very effective system for compressing individual biometrics in order to improve the overall accuracy and security of digital photographs by means of image compression.This paper introduces a content-based image authentication mechanism that is suitable for usage across an untrusted network and resistant to data loss during transmission.By employing scale attributes and a key-dependent parametric Long Short-Term Memory(LSTM),it is feasible to improve the resilience of digital signatures against image deterioration and strengthen their security against malicious actions.Furthermore,the successful implementation of transmitting biometric data in a compressed format over a wireless network has been accomplished.For applications involving the transmission and sharing of images across a network.The suggested technique utilizes the scalability of a structural digital signature to attain a satisfactory equilibrium between security and picture transfer.An effective adaptive compression strategy was created to lengthen the overall lifetime of the network by sharing the processing of responsibilities.This scheme ensures a large reduction in computational and energy requirements while minimizing image quality loss.This approach employs multi-scale characteristics to improve the resistance of signatures against image deterioration.The proposed system attained a Gaussian noise value of 98%and a rotation accuracy surpassing 99%.展开更多
针对茶园拖拉机(tractor in tea plantation,TTP)在作业时进行避障转弯极易发生侧翻、倾覆等安全问题,提出一种基于Bezier曲线优化的避障稳定路径控制方法.首先,从作业场景和运行稳定性两个方面进行运动学分析,系统分析了TTP安全作业特...针对茶园拖拉机(tractor in tea plantation,TTP)在作业时进行避障转弯极易发生侧翻、倾覆等安全问题,提出一种基于Bezier曲线优化的避障稳定路径控制方法.首先,从作业场景和运行稳定性两个方面进行运动学分析,系统分析了TTP安全作业特点;然后,针对TTP设计了一种避障路径规划系统方案及Bezier曲线路径优化控制方法,该方法拟合出的路径具有路径光滑、曲率连续、初末位置曲率相同等优点;最后,在CarSim仿真平台搭建TTP模型和坡道避障作业的环境模型,验证并分析横摆角速度、质心侧偏角两项重要的操稳性参数.结果表明:TTP在Bezier曲线拟合的避障路径控制方法下当运行速度小于转向极限速度时,运行稳定性良好,当转向速度超过极限速度的65.1%,其横摆角速度和质心侧偏角的超调量变化率分别达到了50.3%和78.6%;同时在该避障控制方法下,随着坡度的增加,即使速度保证在极限速度以下,TTP稳定性也会进一步恶化;在极限坡度角范围内,坡度角增大10°,其横摆角速度和质心侧偏角的超调量变化率平均达到了32.8%和14.5%.展开更多
文摘The act of transmitting photos via the Internet has become a routine and significant activity.Enhancing the security measures to safeguard these images from counterfeiting and modifications is a critical domain that can still be further enhanced.This study presents a system that employs a range of approaches and algorithms to ensure the security of transmitted venous images.The main goal of this work is to create a very effective system for compressing individual biometrics in order to improve the overall accuracy and security of digital photographs by means of image compression.This paper introduces a content-based image authentication mechanism that is suitable for usage across an untrusted network and resistant to data loss during transmission.By employing scale attributes and a key-dependent parametric Long Short-Term Memory(LSTM),it is feasible to improve the resilience of digital signatures against image deterioration and strengthen their security against malicious actions.Furthermore,the successful implementation of transmitting biometric data in a compressed format over a wireless network has been accomplished.For applications involving the transmission and sharing of images across a network.The suggested technique utilizes the scalability of a structural digital signature to attain a satisfactory equilibrium between security and picture transfer.An effective adaptive compression strategy was created to lengthen the overall lifetime of the network by sharing the processing of responsibilities.This scheme ensures a large reduction in computational and energy requirements while minimizing image quality loss.This approach employs multi-scale characteristics to improve the resistance of signatures against image deterioration.The proposed system attained a Gaussian noise value of 98%and a rotation accuracy surpassing 99%.
文摘针对茶园拖拉机(tractor in tea plantation,TTP)在作业时进行避障转弯极易发生侧翻、倾覆等安全问题,提出一种基于Bezier曲线优化的避障稳定路径控制方法.首先,从作业场景和运行稳定性两个方面进行运动学分析,系统分析了TTP安全作业特点;然后,针对TTP设计了一种避障路径规划系统方案及Bezier曲线路径优化控制方法,该方法拟合出的路径具有路径光滑、曲率连续、初末位置曲率相同等优点;最后,在CarSim仿真平台搭建TTP模型和坡道避障作业的环境模型,验证并分析横摆角速度、质心侧偏角两项重要的操稳性参数.结果表明:TTP在Bezier曲线拟合的避障路径控制方法下当运行速度小于转向极限速度时,运行稳定性良好,当转向速度超过极限速度的65.1%,其横摆角速度和质心侧偏角的超调量变化率分别达到了50.3%和78.6%;同时在该避障控制方法下,随着坡度的增加,即使速度保证在极限速度以下,TTP稳定性也会进一步恶化;在极限坡度角范围内,坡度角增大10°,其横摆角速度和质心侧偏角的超调量变化率平均达到了32.8%和14.5%.
