目的探讨甘精胰岛素U300联合口服降糖药治疗2型糖尿病的临床效果。方法选择2021年10月—2023年1月广东省吴川市人民医院收治的79例2型糖尿病患者,随机分为非甘精组(39例)和U300组(40例)。非甘精组口服降糖药物治疗,在此之上,U300组增加...目的探讨甘精胰岛素U300联合口服降糖药治疗2型糖尿病的临床效果。方法选择2021年10月—2023年1月广东省吴川市人民医院收治的79例2型糖尿病患者,随机分为非甘精组(39例)和U300组(40例)。非甘精组口服降糖药物治疗,在此之上,U300组增加甘精胰岛素U300治疗,持续治疗3个月,对比2组血糖及相关指标变化,并监测患者胰岛素功能相关指标改善情况,评估低血糖反应等不良反应情况。结果治疗后,U300组血糖指标、血糖波动指标均显著低于非甘精组,差异有统计学意义(P<0.05)。U300组治疗后胰岛素功能指标均显著优于非甘精组,空腹及餐后2 h C肽均显著高于非甘精组,差异有统计学意义(P<0.05)。U300组低血糖反应发生率(2.50%,1/40)和不良反应总发生率(20.00%,8/40)与非甘精组(2.56,1/39;17.95%,7/39)比较,差异无统计学意义(P>0.05)。结论增加甘精胰岛素U300治疗,可更好地提升患者血糖管理效果,并可改善胰岛功能,有利于稳定控制血糖,有助于提高患者病情控制效果,应用效果安全可靠。展开更多
当前工业指针式仪表读数过程中存在特殊环境下依赖人工和推理精度低等问题,本文提出一种基于改进U2-Net的指针式仪表读数方法。针对目前仪表识别算法推理精度差和模型参数数量过多的问题,将U2-Net编码阶段的RSU4和RSU5的最深层的两个卷...当前工业指针式仪表读数过程中存在特殊环境下依赖人工和推理精度低等问题,本文提出一种基于改进U2-Net的指针式仪表读数方法。针对目前仪表识别算法推理精度差和模型参数数量过多的问题,将U2-Net编码阶段的RSU4和RSU5的最深层的两个卷积更换成深度可分离卷积,并在每个RSU的编码阶段后加入了ECA注意力模块,使模型更好地关注指针和刻度区域,提高指针和刻度的识别精度。本文在收集到的数据集上进行评估,通过对比实验表明,相较于SegNet、Deeplabv3+及U2-Net方法,本文改进的模型查准率达到94.58%,针对两种量程25 MPa和1.6 MPa的压力仪表读数引用误差达到1.012%,具有较好的性能表现。At present, there are some problems in the reading process of industrial pointer instruments, such as relying on manual work and low reasoning accuracy. This paper proposes a reading method for pointer instruments based on improved U2-Net. Aiming at the problems of poor reasoning accuracy and too many model parameters in the current instrument identification algorithm, the deepest two convolutions of RSU4 and RSU5 in the U2-Net coding stage are replaced by deep separable convolutions, and the ECA attention module is added after each RSU coding stage, which made the model pay more attention to the pointer and scale area and improved the recognition accuracy of pointer and scale. In this paper, the collected data sets are evaluated. Compared with SegNet, Deeplabv3+ and U2-Net methods, the accuracy of the improved model in this paper reaches 94.58%, and the reference error of pressure instruments with two measuring ranges of 25 MPa and 1.6 MPa reaches 1.012%, which has good performance.展开更多
文摘目的探讨甘精胰岛素U300联合口服降糖药治疗2型糖尿病的临床效果。方法选择2021年10月—2023年1月广东省吴川市人民医院收治的79例2型糖尿病患者,随机分为非甘精组(39例)和U300组(40例)。非甘精组口服降糖药物治疗,在此之上,U300组增加甘精胰岛素U300治疗,持续治疗3个月,对比2组血糖及相关指标变化,并监测患者胰岛素功能相关指标改善情况,评估低血糖反应等不良反应情况。结果治疗后,U300组血糖指标、血糖波动指标均显著低于非甘精组,差异有统计学意义(P<0.05)。U300组治疗后胰岛素功能指标均显著优于非甘精组,空腹及餐后2 h C肽均显著高于非甘精组,差异有统计学意义(P<0.05)。U300组低血糖反应发生率(2.50%,1/40)和不良反应总发生率(20.00%,8/40)与非甘精组(2.56,1/39;17.95%,7/39)比较,差异无统计学意义(P>0.05)。结论增加甘精胰岛素U300治疗,可更好地提升患者血糖管理效果,并可改善胰岛功能,有利于稳定控制血糖,有助于提高患者病情控制效果,应用效果安全可靠。
文摘当前工业指针式仪表读数过程中存在特殊环境下依赖人工和推理精度低等问题,本文提出一种基于改进U2-Net的指针式仪表读数方法。针对目前仪表识别算法推理精度差和模型参数数量过多的问题,将U2-Net编码阶段的RSU4和RSU5的最深层的两个卷积更换成深度可分离卷积,并在每个RSU的编码阶段后加入了ECA注意力模块,使模型更好地关注指针和刻度区域,提高指针和刻度的识别精度。本文在收集到的数据集上进行评估,通过对比实验表明,相较于SegNet、Deeplabv3+及U2-Net方法,本文改进的模型查准率达到94.58%,针对两种量程25 MPa和1.6 MPa的压力仪表读数引用误差达到1.012%,具有较好的性能表现。At present, there are some problems in the reading process of industrial pointer instruments, such as relying on manual work and low reasoning accuracy. This paper proposes a reading method for pointer instruments based on improved U2-Net. Aiming at the problems of poor reasoning accuracy and too many model parameters in the current instrument identification algorithm, the deepest two convolutions of RSU4 and RSU5 in the U2-Net coding stage are replaced by deep separable convolutions, and the ECA attention module is added after each RSU coding stage, which made the model pay more attention to the pointer and scale area and improved the recognition accuracy of pointer and scale. In this paper, the collected data sets are evaluated. Compared with SegNet, Deeplabv3+ and U2-Net methods, the accuracy of the improved model in this paper reaches 94.58%, and the reference error of pressure instruments with two measuring ranges of 25 MPa and 1.6 MPa reaches 1.012%, which has good performance.
