Design and evaluation of robot patient for nursing skill training in patient transfer

We developed a robot patient for patient transfer training for simulating a patient’s performance during patient transfer and for enabling nurses to practice their nursing skills on it. To realize the robot patient, we focused on addressing the problems of designing its limb actions to enable it to respond to nurses’ operations. RC servos and electromagnetic brakes were installed in the joints to enable the robot to simulate a patient’s limb actions, such as embracing and remaining standing. To enable the robot to automatically respond to nurses’ operations, an identification method for these operations was developed that used voice commands and the features of the limbs’ posture measured by angle sensors installed in the robot’s joints. The robot patient’s performance was examined by a control test in which four experienced nursing teachers performed patient transfer with the robot patient and a human-simulated patient. The results revealed that the robot patient could successfully simulate the actions of a patient’s limbs according to the nursing teachers’ operations and that it is suitable for nursing skill training.     

“光传输实训”课程融合探讨与实践

通过对通信工程专业特点及现行的教学方式分析的基础上,得出"光纤通信"课程多课程融合模式及相应的教学项目,以提高课程的教学质量。通过开展"光纤通信"多课程融合的实训教学,以达到专业核心课程的多课程融合,进一步提高学生对通信技术的知识的掌握,并为高职院校的人才培养提供了新思路。     

助行训练机器人骨盆位姿机构动力学分析

为了辅助偏瘫病人完成行走训练,提出了一种助行训练机器人骨盆位姿控制机构,根据该机构的原理和组成,利用凯恩方法建立了骨盆平面机构的动力学方程,并根据骨盆位姿的运动规律进行了运动学仿真计算,得到了机构运动杆件的位移、速度和加速度曲线。通过解算动力学方程得到了驱动力曲线。计算结果表明:该骨盆位姿控制机构能够实现人体骨盆的位姿控制,通过控制x、z方向的移动机构和骨盆平面机构两个杆的伸缩,可以实现人行走训练时骨盆四个自由度的运动。     

Method to generate training samples for neural network used in target recognition

Training neural network to recognize targets needs a lot of samples.People usually get these samples in a non-systematic way,which can miss or overemphasize some target information.To improve this situation,a new method based on virtual model and invariant moments was proposed to generate training samples.The method was composed of the following steps:use computer and simulation software to build target object’s virtual model and then simulate the environment,light condition,camera parameter,etc.;rotate the model by spin and nutation of inclination to get the image sequence by virtual camera;preprocess each image and transfer them into binary image;calculate the invariant moments for each image and get a vectors’ sequence.The vectors’ sequence which was proved to be complete became the training samples together with the target outputs.The simulated results showed that the proposed method could be used to recognize the real targets and improve the accuracy of target recognition effectively when the sampling interval was short enough and the circumstance simulation was close enough.     

基于预测对抗网络的图像二分类模型

正未标记学习仅使用无标签样本和正样本训练一个二分类器, 而生成式对抗网络(generative adversarial networks, GAN)中通过对抗性训练得到一个图像生成器. 为将GAN的对抗训练方法迁移到正未标记学习中以提升正未标记学习的效果, 可将GAN中的生成器替换为分类器C, 在无标签数据集中挑选样本以欺骗判别器D, 对C与D进行迭代优化. 本文提出基于以Jensen-Shannon散度(JS散度)为目标函数的JS-PAN模型. 最后, 结合数据分布特点及现状需求, 说明了PAN模型在医疗诊断图像二分类应用的合理性及高性能. 在MNIST, CIFAR-10数据集上的实验结果显示: KL-PAN模型与同类正未标记学习模型对比有更高的精确度(ACC)及F1-score; 对称化改进后, JS-PAN模型在两个指标上均有所提升, 因此JS-PAN模型的提出更具有合理性. 在Med-MNIST的3个子图像数据集上的实验显示: KL-PAN模型与4个benchmark有监督模型有几乎相同的ACC, JS-PAN也有更高表现. 因此, 综合PAN模型的出色分类效果及医疗诊断数据的分布特征, PAN作为半监督学习方法可获得更快、更好的效果, 在医学图像的二分类的任务上具有更高的性能.     

Effects of real‐time visual feedback on pre‐service teachers' singing

This pilot study focuses on the use real‐time visual feedback technology (VFT) in vocal training. The empirical research has two aims: to ascertain the effectiveness of the real‐time visual feedback software ‘Sing & See’ in the vocal training of pre‐service music teachers and the teachers' perspective on their experience with VFT. Forty participants from an undergraduate music teacher education programme were randomly assigned to three groups. The first two groups were assigned the teacher and student versions of Sing & See, respectively, and the third group served as a control group without access to the software. The experimental groups were given 12 weeks to use the software for vocal training on a self‐regulated basis. The technique of complex selections (TCS) was designed to assess the pitch accuracy and richness of vocal timbre. Pre‐ and post‐test singing tasks showed that the participants from the experimental groups significantly improved their vocal timbre. A questionnaire survey conducted after the training period found that most of the participants in the experimental s were positive about the effectiveness of VFT software in vocal training. As future leaders in the implementation of music education technology, pre‐service music teachers expressed a positive attitude towards the use of VFT as a technology‐enhanced learning (TEL) component in music education.     

“教学做”一体化教学模式探讨

针对职业教育中理论教学与实践教学相互独立的状况,在分析职业需求基础上,笔者提出利用模块化设计理念构建三级实训模块课程体系,建立融理论教学与实训教学为一体的理论与实训一体化教学模式,在数据库技术及应用课程中取得良好效果。     

主观音质评价能力培养与音质评价流程探讨

针对一款电声产品,需要进行主观音质评价.如何对产品进行主观音质评价,以及如何提升工程师主观音质评价能力至关重要.基于工作实践的积累和学习,给出提升音质评价能力的思路和方法,并结合产品主观评价的流程和方法,给出思路和建议.     

一种改进的粒子群优化RBF网络学习算法

提出了一种新的用粒子群优化RBF网络学习的算法,即分组训练合成优化。该算法利用粒子之间的合作与竞争以实现对多维复杂空间的高维搜索能力,找出神经网络权值的最优解,以达到优化神经网络学习的目的。通过与用最小二乘法优化的神经网络进行了比较,结果表明算法所优化的神经网络收敛效果明显、收敛速度快。     

高校篮球运动员拼抢进攻篮板球技术训练初探

通过对拼抢进攻篮板球重要性的分析，强调抢拼篮板球是影响篮球比赛胜负的关键因素之一，并就高校培养运动员的抢拼进攻篮板球意识和意志，以及相关的基本技术训练、能力训练、身体素质训练等问题进行了系统探讨，指出高校的篮球运动应把运动员拼抢进攻篮板球训练作为训练工作的重点而常抓不懈，只有这样，才能切实有效地提高高校篮球竞赛的整体实力。